pax_global_header00006660000000000000000000000064142750221170014513gustar00rootroot0000000000000052 comment=40c89cb610f87cf1cd026eae42f72cb3de5c7279 sasdata-0.8.1/000077500000000000000000000000001427502211700131415ustar00rootroot00000000000000sasdata-0.8.1/.github/000077500000000000000000000000001427502211700145015ustar00rootroot00000000000000sasdata-0.8.1/.github/workflows/000077500000000000000000000000001427502211700165365ustar00rootroot00000000000000sasdata-0.8.1/.github/workflows/test.yml000066400000000000000000000031201427502211700202340ustar00rootroot00000000000000name: Tests on: [push, pull_request] defaults: run: shell: bash jobs: unit-test: runs-on: ${{ matrix.os }} strategy: matrix: os: [macos-latest, ubuntu-latest, windows-latest] python-version: [3.7, 3.8, 3.9] fail-fast: false steps: - name: Obtain SasData source from git uses: actions/checkout@v1 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v1 with: python-version: ${{ matrix.python-version }} ### Caching of pip downloads and local wheel builds - name: Get pip cache dir id: pip-cache run: | echo "::set-output name=dir::$(pip cache dir)" - name: Obtain pip cache (Linux) uses: actions/cache@v2 with: path: ${{ steps.pip-cache.outputs.dir }} key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ hashFiles('**/test.yml') }} restore-keys: | ${{ runner.os }}-pip-${{ matrix.python-version }}- ${{ runner.os }}-pip- ### Installation of build-dependencies - name: Install Python dependencies run: | python -m pip install --upgrade pip python -m pip install wheel setuptools python -m pip install numpy lxml h5py xmlrunner "pytest<6" ### Actual building/testing of sasdata - name: Build sasdata run: | # BUILD SASDATA python setup.py clean python setup.py build python -m pip install . - name: Test with pytest env: PYOPENCL_COMPILER_OUTPUT: 1 run: | python -m pytest -v -s test sasdata-0.8.1/.gitignore000066400000000000000000000011021427502211700151230ustar00rootroot00000000000000# stack dumps due to Git Bash internal crashes *.stackdump # Editor files *.pyproj *.sln .*.swp .DS_Store /.settings /.vscode /.project /.pydevproject /.idea /.vs # Build and run files **/__pycache__ /*.egg-info *.pyc *.so *.exe /build /dist .mplconfig # doc build /docs/sphinx-docs/build # test outputs /test/sasdataloader/data/test_log.txt /test/sasdataloader/data/isis_1_0_write_test.xml /test/sasdataloader/data/isis_1_1_write_test.xml /test/sasdataloader/data/write_test.xml **/logs tests.log /.pytest_cache # Installer files /installers/build /installers/dist *.exe sasdata-0.8.1/LICENSE.TXT000066400000000000000000000027301427502211700146260ustar00rootroot00000000000000Copyright (c) 2009-2022, SasView Developers All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. sasdata-0.8.1/README.md000066400000000000000000000040011427502211700144130ustar00rootroot00000000000000# Sasdata A package for loading and handling reduced small angle scattering data. The data loaders provided are usable as a standalone package, or in conjunction with the sasview analysis package. ## Install The easiest way to use sasdata is by using [SasView](http://www.sasview.org). You can also install sasdata as a standalone package in python. To create a python environment with the sasdata dependencies - Using a python virtual environment:: $ python -m venv sasdata $ python -m pip install numpy lxml h5py xmlrunner "pytest<6" - Activate the environment:: $ .\sasdata\Scripts\activate - Using [miniconda](https://docs.conda.io/en/latest/miniconda.html) or [anaconda](https://www.anaconda.com/):: $ conda create -n sasdata -c conda-forge numpy lxml h5py xmlrunner "pytest<6" - Activate the environment and install sasdata:: $ conda activate sasdata $ (sasdata) $ pip install sasdata View the latest release on the [sasdata pypi page](https://pypi.org/project/sasdata/). ## Usage Loading data sets: (sasdata) $ python >>> from sasdata.dataloader.loader import Loader >>> loader_module = Loader() >>> loaded_data_sets = loader_module.load(path="/path/to/file.ext") - The Loader() class is not callable and must be instantiated prior to use. - The load() method returns a list of Data1/2D objects as loaded from the specified path. Saving loaded data: >>> loaded_data_set = loaded_data_sets[0] >>> loader.save(path='/path/to/new/file.ext', data=loaded_data_set, format=None) - The save() method accepts three (3) arguments: - path: The file name and path to save the data. - data: A Data1D or Data2D object. - format (optional): The expected file extension for the file. Options include: - .xml: for the canSAS XMl format - .h5: for the NXcanSAS format - .txt: for the multi-column ascii format - .csv: for a comma delimited text format. - The file extension specified in the save path will be superseded by the format value.sasdata-0.8.1/pytest.ini000066400000000000000000000001361427502211700151720ustar00rootroot00000000000000[pytest] norecursedirs=sasdata/ addopts=--ignore test/utest_sasdata.py python_files='utest*py'sasdata-0.8.1/sasdata/000077500000000000000000000000001427502211700145615ustar00rootroot00000000000000sasdata-0.8.1/sasdata/__init__.py000066400000000000000000000000261427502211700166700ustar00rootroot00000000000000__version__ = "0.8.1" sasdata-0.8.1/sasdata/data_util/000077500000000000000000000000001427502211700165275ustar00rootroot00000000000000sasdata-0.8.1/sasdata/data_util/__init__.py000066400000000000000000000000001427502211700206260ustar00rootroot00000000000000sasdata-0.8.1/sasdata/data_util/err1d.py000066400000000000000000000074611427502211700201260ustar00rootroot00000000000000# This program is public domain """ Error propogation algorithms for simple arithmetic Warning: like the underlying numpy library, the inplace operations may return values of the wrong type if some of the arguments are integers, so be sure to create them with floating point inputs. """ import numpy as np def div(X, varX, Y, varY): """Division with error propagation""" # Direct algorithm: # Z = X/Y # varZ = (varX/X**2 + varY/Y**2) * Z**2 # = (varX + varY * Z**2) / Y**2 # Indirect algorithm to minimize intermediates Z = X/Y # truediv => Z is a float varZ = Z**2 # Z is a float => varZ is a float varZ *= varY varZ += varX T = Y**2 # Doesn't matter if T is float or int varZ /= T return Z, varZ def mul(X, varX, Y, varY): """Multiplication with error propagation""" # Direct algorithm: Z = X * Y varZ = Y**2 * varX + X**2 * varY # Indirect algorithm won't ensure floating point results # varZ = Y**2 # varZ *= varX # Z = X**2 # Using Z to hold the temporary # Z *= varY # varZ += Z # Z[:] = X # Z *= Y return Z, varZ def sub(X, varX, Y, varY): """Subtraction with error propagation""" Z = X - Y varZ = varX + varY return Z, varZ def add(X, varX, Y, varY): """Addition with error propagation""" Z = X + Y varZ = varX + varY return Z, varZ def exp(X, varX): """Exponentiation with error propagation""" Z = np.exp(X) varZ = varX * Z**2 return Z, varZ def log(X, varX): """Logarithm with error propagation""" Z = np.log(X) varZ = varX / X**2 return Z, varZ # Confirm this formula before using it # def pow(X,varX, Y,varY): # Z = X**Y # varZ = (Y**2 * varX/X**2 + varY * np.log(X)**2) * Z**2 # return Z,varZ # def pow(X, varX, n): """X**n with error propagation""" # Direct algorithm # Z = X**n # varZ = n*n * varX/X**2 * Z**2 # Indirect algorithm to minimize intermediates Z = X**n varZ = varX / X varZ /= X varZ *= Z varZ *= Z varZ *= n**2 return Z, varZ def div_inplace(X, varX, Y, varY): """In-place division with error propagation""" # Z = X/Y # varZ = (varX + varY * (X/Y)**2) / Y**2 = (varX + varY * Z**2) / Y**2 X /= Y # X now has Z = X/Y T = X**2 # create T with Z**2 T *= varY # T now has varY * Z**2 varX += T # varX now has varX + varY*Z**2 del T # may want to use T[:] = Y for vectors T = Y # reuse T for Y T **= 2 # T now has Y**2 varX /= T # varX now has varZ return X, varX def mul_inplace(X, varX, Y, varY): """In-place multiplication with error propagation""" # Z = X * Y # varZ = Y**2 * varX + X**2 * varY T = Y**2 # create T with Y**2 varX *= T # varX now has Y**2 * varX del T # may want to use T[:] = X for vectors T = X # reuse T for X**2 * varY T **=2 # T now has X**2 T *= varY # T now has X**2 * varY varX += T # varX now has varZ X *= Y # X now has Z return X, varX def sub_inplace(X, varX, Y, varY): """In-place subtraction with error propagation""" # Z = X - Y # varZ = varX + varY X -= Y varX += varY return X, varX def add_inplace(X, varX, Y, varY): """In-place addition with error propagation""" # Z = X + Y # varZ = varX + varY X += Y varX += varY return X, varX def pow_inplace(X, varX, n): """In-place X**n with error propagation""" # Direct algorithm # Z = X**n # varZ = abs(n) * varX/X**2 * Z**2 # Indirect algorithm to minimize intermediates varX /= X varX /= X # varX now has varX/X**2 X **= n # X now has Z = X**n varX *= X varX *= X # varX now has varX/X**2 * Z**2 varX *= n**2 # varX now has varZ return X, varX sasdata-0.8.1/sasdata/data_util/formatnum.py000066400000000000000000000447511427502211700211240ustar00rootroot00000000000000# This program is public domain # Author: Paul Kienzle """ Format values and uncertainties nicely for printing. :func:`format_uncertainty_pm` produces the expanded format v +/- err. :func:`format_uncertainty_compact` produces the compact format v(##), where the number in parenthesis is the uncertainty in the last two digits of v. :func:`format_uncertainty` uses the compact format by default, but this can be changed to use the expanded +/- format by setting format_uncertainty.compact to False. The formatted string uses only the number of digits warranted by the uncertainty in the measurement. If the uncertainty is 0 or not otherwise provided, the simple %g floating point format option is used. Infinite and indefinite numbers are represented as inf and NaN. Example:: >>> v,dv = 757.2356,0.01032 >>> print format_uncertainty_pm(v,dv) 757.236 +/- 0.010 >>> print format_uncertainty_compact(v,dv) 757.236(10) >>> print format_uncertainty(v,dv) 757.236(10) >>> format_uncertainty.compact = False >>> print format_uncertainty(v,dv) 757.236 +/- 0.010 UncertaintyFormatter() returns a private formatter with its own formatter.compact flag. """ import math import numpy as np __all__ = ['format_uncertainty', 'format_uncertainty_pm', 'format_uncertainty_compact'] # Coordinating scales across a set of numbers is not supported. For easy # comparison a set of numbers should be shown in the same scale. One could # force this from the outside by adding scale parameter (either 10**n, n, or # a string representing the desired SI prefix) and having a separate routine # which computes the scale given a set of values. # Coordinating scales with units offers its own problems. Again, the user # may want to force particular units. This can be done by outside of the # formatting routines by scaling the numbers to the appropriate units then # forcing them to print with scale 10**0. If this is a common operation, # however, it may want to happen inside. # The value e is currently formatted into the number. Alternatively this # scale factor could be returned so that the user can choose the appropriate # SI prefix when printing the units. This gets tricky when talking about # composite units such as 2.3e-3 m**2 -> 2300 mm**2, and with volumes # such as 1 g/cm**3 -> 1 kg/L. def format_uncertainty_pm(value, uncertainty): """ Given *value* v and *uncertainty* dv, return a string v +/- dv. """ return _format_uncertainty(value, uncertainty, compact=False) def format_uncertainty_compact(value, uncertainty): """ Given *value* v and *uncertainty* dv, return the compact representation v(##), where ## are the first two digits of the uncertainty. """ return _format_uncertainty(value, uncertainty, compact=True) class UncertaintyFormatter: """ Value and uncertainty formatter. The *formatter* instance will use either the expanded v +/- dv form or the compact v(##) form depending on whether *formatter.compact* is True or False. The default is True. """ compact = True def __call__(self, value, uncertainty): """ Given *value* and *uncertainty*, return a string representation. """ return _format_uncertainty(value, uncertainty, self.compact) format_uncertainty = UncertaintyFormatter() def _format_uncertainty(value, uncertainty, compact): """ Implementation of both the compact and the +/- formats. """ # Handle indefinite value if np.isinf(value): return "inf" if value > 0 else "-inf" if np.isnan(value): return "NaN" # Handle indefinite uncertainty if uncertainty is None or uncertainty <= 0 or np.isnan(uncertainty): return "%g" % value if np.isinf(uncertainty): if compact: return "%.2g(inf)" % value else: return "%.2g +/- inf" % value # Handle zero and negative values sign = "-" if value < 0 else "" value = abs(value) # Determine scale of value and error err_place = int(math.floor(math.log10(uncertainty))) if value == 0: val_place = err_place - 1 else: val_place = int(math.floor(math.log10(value))) if err_place > val_place: # Degenerate case: error bigger than value # The mantissa is 0.#(##)e#, 0.0#(##)e# or 0.00#(##)e# val_place = err_place + 2 elif err_place == val_place: # Degenerate case: error and value the same order of magnitude # The value is ##(##)e#, #.#(##)e# or 0.##(##)e# val_place = err_place + 1 elif err_place <= 1 and val_place >= -3: # Normal case: nice numbers and errors # The value is ###.###(##) val_place = 0 else: # Extreme cases: zeros before value or after error # The value is ###.###(##)e#, ##.####(##)e# or #.#####(##)e# pass # Force engineering notation, with exponent a multiple of 3 val_place = int(math.floor(val_place / 3.)) * 3 # Format the result digits_after_decimal = abs(val_place - err_place + 1) val_str = "%.*f" % (digits_after_decimal, value / 10.**val_place) exp_str = "e%d" % val_place if val_place != 0 else "" if compact: err_str = "(%2d)" % int(uncertainty / 10.**(err_place - 1) + 0.5) result = "".join((sign, val_str, err_str, exp_str)) else: err_str = "%.*f" % (digits_after_decimal, uncertainty / 10.**val_place) result = "".join((sign, val_str, exp_str + " +/- ", err_str, exp_str)) return result def test_compact(): # Oops... renamed function after writing tests value_str = format_uncertainty_compact # val_place > err_place assert value_str(1235670,766000) == "1.24(77)e6" assert value_str(123567.,76600) == "124(77)e3" assert value_str(12356.7,7660) == "12.4(77)e3" assert value_str(1235.67,766) == "1.24(77)e3" assert value_str(123.567,76.6) == "124(77)" assert value_str(12.3567,7.66) == "12.4(77)" assert value_str(1.23567,.766) == "1.24(77)" assert value_str(.123567,.0766) == "0.124(77)" assert value_str(.0123567,.00766) == "0.0124(77)" assert value_str(.00123567,.000766) == "0.00124(77)" assert value_str(.000123567,.0000766) == "124(77)e-6" assert value_str(.0000123567,.00000766) == "12.4(77)e-6" assert value_str(.00000123567,.000000766) == "1.24(77)e-6" assert value_str(.000000123567,.0000000766) == "124(77)e-9" assert value_str(.00000123567,.0000000766) == "1.236(77)e-6" assert value_str(.0000123567,.0000000766) == "12.357(77)e-6" assert value_str(.000123567,.0000000766) == "123.567(77)e-6" assert value_str(.00123567,.000000766) == "0.00123567(77)" assert value_str(.0123567,.00000766) == "0.0123567(77)" assert value_str(.123567,.0000766) == "0.123567(77)" assert value_str(1.23567,.000766) == "1.23567(77)" assert value_str(12.3567,.00766) == "12.3567(77)" assert value_str(123.567,.0764) == "123.567(76)" assert value_str(1235.67,.764) == "1235.67(76)" assert value_str(12356.7,7.64) == "12356.7(76)" assert value_str(123567,76.4) == "123567(76)" assert value_str(1235670,764) == "1.23567(76)e6" assert value_str(12356700,764) == "12.35670(76)e6" assert value_str(123567000,764) == "123.56700(76)e6" assert value_str(123567000,7640) == "123.5670(76)e6" assert value_str(1235670000,76400) == "1.235670(76)e9" # val_place == err_place assert value_str(123567,764000) == "0.12(76)e6" assert value_str(12356.7,76400) == "12(76)e3" assert value_str(1235.67,7640) == "1.2(76)e3" assert value_str(123.567,764) == "0.12(76)e3" assert value_str(12.3567,76.4) == "12(76)" assert value_str(1.23567,7.64) == "1.2(76)" assert value_str(.123567,.764) == "0.12(76)" assert value_str(.0123567,.0764) == "12(76)e-3" assert value_str(.00123567,.00764) == "1.2(76)e-3" assert value_str(.000123567,.000764) == "0.12(76)e-3" # val_place == err_place-1 assert value_str(123567,7640000) == "0.1(76)e6" assert value_str(12356.7,764000) == "0.01(76)e6" assert value_str(1235.67,76400) == "0.001(76)e6" assert value_str(123.567,7640) == "0.1(76)e3" assert value_str(12.3567,764) == "0.01(76)e3" assert value_str(1.23567,76.4) == "0.001(76)e3" assert value_str(.123567,7.64) == "0.1(76)" assert value_str(.0123567,.764) == "0.01(76)" assert value_str(.00123567,.0764) == "0.001(76)" assert value_str(.000123567,.00764) == "0.1(76)e-3" # val_place == err_place-2 assert value_str(12356700,7640000000) == "0.0(76)e9" assert value_str(1235670,764000000) == "0.00(76)e9" assert value_str(123567,76400000) == "0.000(76)e9" assert value_str(12356,7640000) == "0.0(76)e6" assert value_str(1235,764000) == "0.00(76)e6" assert value_str(123,76400) == "0.000(76)e6" assert value_str(12,7640) == "0.0(76)e3" assert value_str(1,764) == "0.00(76)e3" assert value_str(0.1,76.4) == "0.000(76)e3" assert value_str(0.01,7.64) == "0.0(76)" assert value_str(0.001,0.764) == "0.00(76)" assert value_str(0.0001,0.0764) == "0.000(76)" assert value_str(0.00001,0.00764) == "0.0(76)e-3" # val_place == err_place-3 assert value_str(12356700,76400000000) == "0.000(76)e12" assert value_str(1235670,7640000000) == "0.0(76)e9" assert value_str(123567,764000000) == "0.00(76)e9" assert value_str(12356,76400000) == "0.000(76)e9" assert value_str(1235,7640000) == "0.0(76)e6" assert value_str(123,764000) == "0.00(76)e6" assert value_str(12,76400) == "0.000(76)e6" assert value_str(1,7640) == "0.0(76)e3" assert value_str(0.1,764) == "0.00(76)e3" assert value_str(0.01,76.4) == "0.000(76)e3" assert value_str(0.001,7.64) == "0.0(76)" assert value_str(0.0001,0.764) == "0.00(76)" assert value_str(0.00001,0.0764) == "0.000(76)" assert value_str(0.000001,0.00764) == "0.0(76)e-3" # Zero values assert value_str(0,7640000) == "0.0(76)e6" assert value_str(0, 764000) == "0.00(76)e6" assert value_str(0, 76400) == "0.000(76)e6" assert value_str(0, 7640) == "0.0(76)e3" assert value_str(0, 764) == "0.00(76)e3" assert value_str(0, 76.4) == "0.000(76)e3" assert value_str(0, 7.64) == "0.0(76)" assert value_str(0, 0.764) == "0.00(76)" assert value_str(0, 0.0764) == "0.000(76)" assert value_str(0, 0.00764) == "0.0(76)e-3" assert value_str(0, 0.000764) == "0.00(76)e-3" assert value_str(0, 0.0000764) == "0.000(76)e-3" # negative values assert value_str(-1235670,765000) == "-1.24(77)e6" assert value_str(-1.23567,.766) == "-1.24(77)" assert value_str(-.00000123567,.0000000766) == "-1.236(77)e-6" assert value_str(-12356.7,7.64) == "-12356.7(76)" assert value_str(-123.567,764) == "-0.12(76)e3" assert value_str(-1235.67,76400) == "-0.001(76)e6" assert value_str(-.000123567,.00764) == "-0.1(76)e-3" assert value_str(-12356,7640000) == "-0.0(76)e6" assert value_str(-12,76400) == "-0.000(76)e6" assert value_str(-0.0001,0.764) == "-0.00(76)" # non-finite values assert value_str(-np.inf,None) == "-inf" assert value_str(np.inf,None) == "inf" assert value_str(np.NaN,None) == "NaN" # bad or missing uncertainty assert value_str(-1.23567,np.NaN) == "-1.23567" assert value_str(-1.23567,-np.inf) == "-1.23567" assert value_str(-1.23567,-0.1) == "-1.23567" assert value_str(-1.23567,0) == "-1.23567" assert value_str(-1.23567,None) == "-1.23567" assert value_str(-1.23567,np.inf) == "-1.2(inf)" def test_pm(): # Oops... renamed function after writing tests value_str = format_uncertainty_pm # val_place > err_place assert value_str(1235670,766000) == "1.24e6 +/- 0.77e6" assert value_str(123567., 76600) == "124e3 +/- 77e3" assert value_str(12356.7, 7660) == "12.4e3 +/- 7.7e3" assert value_str(1235.67, 766) == "1.24e3 +/- 0.77e3" assert value_str(123.567, 76.6) == "124 +/- 77" assert value_str(12.3567, 7.66) == "12.4 +/- 7.7" assert value_str(1.23567, .766) == "1.24 +/- 0.77" assert value_str(.123567, .0766) == "0.124 +/- 0.077" assert value_str(.0123567, .00766) == "0.0124 +/- 0.0077" assert value_str(.00123567, .000766) == "0.00124 +/- 0.00077" assert value_str(.000123567, .0000766) == "124e-6 +/- 77e-6" assert value_str(.0000123567, .00000766) == "12.4e-6 +/- 7.7e-6" assert value_str(.00000123567, .000000766) == "1.24e-6 +/- 0.77e-6" assert value_str(.000000123567,.0000000766) == "124e-9 +/- 77e-9" assert value_str(.00000123567, .0000000766) == "1.236e-6 +/- 0.077e-6" assert value_str(.0000123567, .0000000766) == "12.357e-6 +/- 0.077e-6" assert value_str(.000123567, .0000000766) == "123.567e-6 +/- 0.077e-6" assert value_str(.00123567, .000000766) == "0.00123567 +/- 0.00000077" assert value_str(.0123567, .00000766) == "0.0123567 +/- 0.0000077" assert value_str(.123567, .0000766) == "0.123567 +/- 0.000077" assert value_str(1.23567, .000766) == "1.23567 +/- 0.00077" assert value_str(12.3567, .00766) == "12.3567 +/- 0.0077" assert value_str(123.567, .0764) == "123.567 +/- 0.076" assert value_str(1235.67, .764) == "1235.67 +/- 0.76" assert value_str(12356.7, 7.64) == "12356.7 +/- 7.6" assert value_str(123567, 76.4) == "123567 +/- 76" assert value_str(1235670, 764) == "1.23567e6 +/- 0.00076e6" assert value_str(12356700, 764) == "12.35670e6 +/- 0.00076e6" assert value_str(123567000, 764) == "123.56700e6 +/- 0.00076e6" assert value_str(123567000,7640) == "123.5670e6 +/- 0.0076e6" assert value_str(1235670000,76400) == "1.235670e9 +/- 0.000076e9" # val_place == err_place assert value_str(123567,764000) == "0.12e6 +/- 0.76e6" assert value_str(12356.7,76400) == "12e3 +/- 76e3" assert value_str(1235.67,7640) == "1.2e3 +/- 7.6e3" assert value_str(123.567,764) == "0.12e3 +/- 0.76e3" assert value_str(12.3567,76.4) == "12 +/- 76" assert value_str(1.23567,7.64) == "1.2 +/- 7.6" assert value_str(.123567,.764) == "0.12 +/- 0.76" assert value_str(.0123567,.0764) == "12e-3 +/- 76e-3" assert value_str(.00123567,.00764) == "1.2e-3 +/- 7.6e-3" assert value_str(.000123567,.000764) == "0.12e-3 +/- 0.76e-3" # val_place == err_place-1 assert value_str(123567,7640000) == "0.1e6 +/- 7.6e6" assert value_str(12356.7,764000) == "0.01e6 +/- 0.76e6" assert value_str(1235.67,76400) == "0.001e6 +/- 0.076e6" assert value_str(123.567,7640) == "0.1e3 +/- 7.6e3" assert value_str(12.3567,764) == "0.01e3 +/- 0.76e3" assert value_str(1.23567,76.4) == "0.001e3 +/- 0.076e3" assert value_str(.123567,7.64) == "0.1 +/- 7.6" assert value_str(.0123567,.764) == "0.01 +/- 0.76" assert value_str(.00123567,.0764) == "0.001 +/- 0.076" assert value_str(.000123567,.00764) == "0.1e-3 +/- 7.6e-3" # val_place == err_place-2 assert value_str(12356700,7640000000) == "0.0e9 +/- 7.6e9" assert value_str(1235670,764000000) == "0.00e9 +/- 0.76e9" assert value_str(123567,76400000) == "0.000e9 +/- 0.076e9" assert value_str(12356,7640000) == "0.0e6 +/- 7.6e6" assert value_str(1235,764000) == "0.00e6 +/- 0.76e6" assert value_str(123,76400) == "0.000e6 +/- 0.076e6" assert value_str(12,7640) == "0.0e3 +/- 7.6e3" assert value_str(1,764) == "0.00e3 +/- 0.76e3" assert value_str(0.1,76.4) == "0.000e3 +/- 0.076e3" assert value_str(0.01,7.64) == "0.0 +/- 7.6" assert value_str(0.001,0.764) == "0.00 +/- 0.76" assert value_str(0.0001,0.0764) == "0.000 +/- 0.076" assert value_str(0.00001,0.00764) == "0.0e-3 +/- 7.6e-3" # val_place == err_place-3 assert value_str(12356700,76400000000) == "0.000e12 +/- 0.076e12" assert value_str(1235670,7640000000) == "0.0e9 +/- 7.6e9" assert value_str(123567,764000000) == "0.00e9 +/- 0.76e9" assert value_str(12356,76400000) == "0.000e9 +/- 0.076e9" assert value_str(1235,7640000) == "0.0e6 +/- 7.6e6" assert value_str(123,764000) == "0.00e6 +/- 0.76e6" assert value_str(12,76400) == "0.000e6 +/- 0.076e6" assert value_str(1,7640) == "0.0e3 +/- 7.6e3" assert value_str(0.1,764) == "0.00e3 +/- 0.76e3" assert value_str(0.01,76.4) == "0.000e3 +/- 0.076e3" assert value_str(0.001,7.64) == "0.0 +/- 7.6" assert value_str(0.0001,0.764) == "0.00 +/- 0.76" assert value_str(0.00001,0.0764) == "0.000 +/- 0.076" assert value_str(0.000001,0.00764) == "0.0e-3 +/- 7.6e-3" # Zero values assert value_str(0,7640000) == "0.0e6 +/- 7.6e6" assert value_str(0, 764000) == "0.00e6 +/- 0.76e6" assert value_str(0, 76400) == "0.000e6 +/- 0.076e6" assert value_str(0, 7640) == "0.0e3 +/- 7.6e3" assert value_str(0, 764) == "0.00e3 +/- 0.76e3" assert value_str(0, 76.4) == "0.000e3 +/- 0.076e3" assert value_str(0, 7.64) == "0.0 +/- 7.6" assert value_str(0, 0.764) == "0.00 +/- 0.76" assert value_str(0, 0.0764) == "0.000 +/- 0.076" assert value_str(0, 0.00764) == "0.0e-3 +/- 7.6e-3" assert value_str(0, 0.000764) == "0.00e-3 +/- 0.76e-3" assert value_str(0, 0.0000764) == "0.000e-3 +/- 0.076e-3" # negative values assert value_str(-1235670,766000) == "-1.24e6 +/- 0.77e6" assert value_str(-1.23567,.766) == "-1.24 +/- 0.77" assert value_str(-.00000123567,.0000000766) == "-1.236e-6 +/- 0.077e-6" assert value_str(-12356.7,7.64) == "-12356.7 +/- 7.6" assert value_str(-123.567,764) == "-0.12e3 +/- 0.76e3" assert value_str(-1235.67,76400) == "-0.001e6 +/- 0.076e6" assert value_str(-.000123567,.00764) == "-0.1e-3 +/- 7.6e-3" assert value_str(-12356,7640000) == "-0.0e6 +/- 7.6e6" assert value_str(-12,76400) == "-0.000e6 +/- 0.076e6" assert value_str(-0.0001,0.764) == "-0.00 +/- 0.76" # non-finite values assert value_str(-np.inf,None) == "-inf" assert value_str(np.inf,None) == "inf" assert value_str(np.NaN,None) == "NaN" # bad or missing uncertainty assert value_str(-1.23567,np.NaN) == "-1.23567" assert value_str(-1.23567,-np.inf) == "-1.23567" assert value_str(-1.23567,-0.1) == "-1.23567" assert value_str(-1.23567,0) == "-1.23567" assert value_str(-1.23567,None) == "-1.23567" assert value_str(-1.23567,np.inf) == "-1.2 +/- inf" def test_default(): # Check that the default is the compact format assert format_uncertainty(-1.23567,0.766) == "-1.24(77)" def main(): """ Run all tests. This is equivalent to "nosetests --with-doctest" """ test_compact() test_pm() test_default() import doctest doctest.testmod() if __name__ == "__main__": main() sasdata-0.8.1/sasdata/data_util/loader_exceptions.py000066400000000000000000000022651427502211700226150ustar00rootroot00000000000000""" Exceptions specific to loading data. """ from typing import Optional class NoKnownLoaderException(Exception): """ Exception for files with no associated reader based on the file extension of the loaded file. This exception should only be thrown by loader.py. """ def __init__(self, e: Optional[str] = None): self.message = e class DefaultReaderException(Exception): """ Exception for files with no associated reader. This should be thrown by default readers only to tell Loader to try the next reader. """ def __init__(self, e: Optional[str] = None): self.message = e class FileContentsException(Exception): """ Exception for files with an associated reader, but with no loadable data. This is useful for catching loader or file format issues. """ def __init__(self, e: Optional[str] = None): self.message = e class DataReaderException(Exception): """ Exception for files that were able to mostly load, but had minor issues along the way. Any exceptions of this type should be put into the datainfo.errors """ def __init__(self, e: Optional[str] = None): self.message = e sasdata-0.8.1/sasdata/data_util/manipulations.py000066400000000000000000001140661427502211700217740ustar00rootroot00000000000000""" Data manipulations for 2D data sets. Using the meta data information, various types of averaging are performed in Q-space To test this module use: ``` cd test PYTHONPATH=../src/ python2 -m sasdataloader.test.utest_averaging DataInfoTests.test_sectorphi_quarter ``` """ ##################################################################### # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # See the license text in license.txt # copyright 2008, University of Tennessee ###################################################################### # TODO: copy the meta data from the 2D object to the resulting 1D object import math import numpy as np from typing import Optional, Union from sasdata.dataloader.data_info import Data1D, Data2D def position_and_wavelength_to_q(dx: float, dy: float, detector_distance: float, wavelength: float) -> float: """ :param dx: x-distance from beam center [mm] :param dy: y-distance from beam center [mm] :param detector_distance: sample to detector distance [mm] :param wavelength: neutron wavelength [nm] :return: q-value at the given position """ # Distance from beam center in the plane of detector plane_dist = math.sqrt(dx * dx + dy * dy) # Half of the scattering angle theta = 0.5 * math.atan(plane_dist / detector_distance) return (4.0 * math.pi / wavelength) * math.sin(theta) def get_q_compo(dx: float, dy: float, detector_distance: float, wavelength: float, compo: Optional[str] = None) -> float: """ This reduces tiny error at very large q. Implementation of this func is not started yet.<--ToDo """ if dy == 0: if dx >= 0: angle_xy = 0 else: angle_xy = math.pi else: angle_xy = math.atan(dx / dy) if compo == "x": out = position_and_wavelength_to_q(dx, dy, detector_distance, wavelength) * math.cos(angle_xy) elif compo == "y": out = position_and_wavelength_to_q(dx, dy, detector_distance, wavelength) * math.sin(angle_xy) else: out = position_and_wavelength_to_q(dx, dy, detector_distance, wavelength) return out def flip_phi(phi: float) -> float: """ Correct phi to within the 0 <= to <= 2pi range :return: phi in >=0 and <=2Pi """ if phi < 0: phi_out = phi + (2 * math.pi) elif phi > (2 * math.pi): phi_out = phi - (2 * math.pi) else: phi_out = phi return phi_out def get_pixel_fraction_square(x: float, x_min: float, x_max: float) -> float: """ Return the fraction of the length from xmin to x.:: A B +-----------+---------+ xmin x xmax :param x: x-value :param x_min: minimum x for the length considered :param x_max: minimum x for the length considered :return: (x-xmin)/(xmax-xmin) when xmin < x < xmax """ if x <= x_min: return 0.0 if x_min < x < x_max: return (x - x_min) / (x_max - x_min) else: return 1.0 def get_intercept(q: float, q_0: float, q_1: float) -> Union[float, None]: """ Returns the fraction of the side at which the q-value intercept the pixel, None otherwise. The values returned is the fraction ON THE SIDE OF THE LOWEST Q. :: A B +-----------+--------+ <--- pixel size 0 1 Q_0 -------- Q ----- Q_1 <--- equivalent Q range if Q_1 > Q_0, A is returned if Q_1 < Q_0, B is returned if Q is outside the range of [Q_0, Q_1], None is returned """ if q_1 > q_0: if q_0 < q <= q_1: return (q - q_0) / (q_1 - q_0) else: if q_1 < q <= q_0: return (q - q_1) / (q_0 - q_1) return None def get_pixel_fraction(q_max: float, q_00: float, q_01: float, q_10: float, q_11: float) -> float: """ Returns the fraction of the pixel defined by the four corners (q_00, q_01, q_10, q_11) that has q < q_max.:: q_01 q_11 y=1 +--------------+ | | | | | | y=0 +--------------+ q_00 q_10 x=0 x=1 """ # y side for x = minx x_0 = get_intercept(q_max, q_00, q_01) # y side for x = maxx x_1 = get_intercept(q_max, q_10, q_11) # x side for y = miny y_0 = get_intercept(q_max, q_00, q_10) # x side for y = maxy y_1 = get_intercept(q_max, q_01, q_11) # surface fraction for a 1x1 pixel frac_max = 0 if x_0 and x_1: frac_max = (x_0 + x_1) / 2.0 elif y_0 and y_1: frac_max = (y_0 + y_1) / 2.0 elif x_0 and y_0: if q_00 < q_10: frac_max = x_0 * y_0 / 2.0 else: frac_max = 1.0 - x_0 * y_0 / 2.0 elif x_0 and y_1: if q_00 < q_10: frac_max = x_0 * y_1 / 2.0 else: frac_max = 1.0 - x_0 * y_1 / 2.0 elif x_1 and y_0: if q_00 > q_10: frac_max = x_1 * y_0 / 2.0 else: frac_max = 1.0 - x_1 * y_0 / 2.0 elif x_1 and y_1: if q_00 < q_10: frac_max = 1.0 - (1.0 - x_1) * (1.0 - y_1) / 2.0 else: frac_max = (1.0 - x_1) * (1.0 - y_1) / 2.0 # If we make it here, there is no intercept between # this pixel and the constant-q ring. We only need # to know if we have to include it or exclude it. elif (q_00 + q_01 + q_10 + q_11) / 4.0 < q_max: frac_max = 1.0 return frac_max def get_dq_data(data2d: Data2D) -> np.array: ''' Get the dq for resolution averaging The pinholes and det. pix contribution present in both direction of the 2D which must be subtracted when converting to 1D: dq_overlap should calculated ideally at q = 0. Note This method works on only pinhole geometry. Extrapolate dqx(r) and dqy(phi) at q = 0, and take an average. ''' z_max = max(data2d.q_data) z_min = min(data2d.q_data) dqx_at_z_max = data2d.dqx_data[np.argmax(data2d.q_data)] dqx_at_z_min = data2d.dqx_data[np.argmin(data2d.q_data)] dqy_at_z_max = data2d.dqy_data[np.argmax(data2d.q_data)] dqy_at_z_min = data2d.dqy_data[np.argmin(data2d.q_data)] # Find qdx at q = 0 dq_overlap_x = (dqx_at_z_min * z_max - dqx_at_z_max * z_min) / (z_max - z_min) # when extrapolation goes wrong if dq_overlap_x > min(data2d.dqx_data): dq_overlap_x = min(data2d.dqx_data) dq_overlap_x *= dq_overlap_x # Find qdx at q = 0 dq_overlap_y = (dqy_at_z_min * z_max - dqy_at_z_max * z_min) / (z_max - z_min) # when extrapolation goes wrong if dq_overlap_y > min(data2d.dqy_data): dq_overlap_y = min(data2d.dqy_data) # get dq at q=0. dq_overlap_y *= dq_overlap_y dq_overlap = np.sqrt((dq_overlap_x + dq_overlap_y) / 2.0) # Final protection of dq if dq_overlap < 0: dq_overlap = dqy_at_z_min dqx_data = data2d.dqx_data[np.isfinite(data2d.data)] dqy_data = data2d.dqy_data[np.isfinite( data2d.data)] - dq_overlap # def; dqx_data = dq_r dqy_data = dq_phi # Convert dq 2D to 1D here dq_data = np.sqrt(dqx_data**2 + dqx_data**2) return dq_data ################################################################################ def reader2D_converter(data2d: Optional[Data2D] = None) -> Data2D: """ convert old 2d format opened by IhorReader or danse_reader to new Data2D format This is mainly used by the Readers :param data2d: 2d array of Data2D object :return: 1d arrays of Data2D object """ if data2d.data is None or data2d.x_bins is None or data2d.y_bins is None: raise ValueError("Can't convert this data: data=None...") new_x = np.tile(data2d.x_bins, (len(data2d.y_bins), 1)) new_y = np.tile(data2d.y_bins, (len(data2d.x_bins), 1)) new_y = new_y.swapaxes(0, 1) new_data = data2d.data.flatten() qx_data = new_x.flatten() qy_data = new_y.flatten() q_data = np.sqrt(qx_data * qx_data + qy_data * qy_data) if data2d.err_data is None or np.any(data2d.err_data <= 0): new_err_data = np.sqrt(np.abs(new_data)) else: new_err_data = data2d.err_data.flatten() mask = np.ones(len(new_data), dtype=bool) output = data2d output.data = new_data output.err_data = new_err_data output.qx_data = qx_data output.qy_data = qy_data output.q_data = q_data output.mask = mask return output ################################################################################ class Binning: """ This class just creates a binning object either linear or log """ def __init__(self, min_value, max_value, n_bins, base=None): """ if base is None: Linear binning """ self.min = min_value if min_value > 0 else 0.0001 self.max = max_value self.n_bins = n_bins self.base = base def get_bin_index(self, value): """ The general formula logarithm binning is: bin = floor(N * (log(x) - log(min)) / (log(max) - log(min))) """ if self.base: temp_x = self.n_bins * (math.log(value, self.base) - math.log(self.min, self.base)) temp_y = math.log(self.max, self.base) - math.log(self.min, self.base) else: temp_x = self.n_bins * (value - self.min) temp_y = self.max - self.min # Bin index calulation return int(math.floor(temp_x / temp_y)) ################################################################################ class _Slab: """ Compute average I(Q) for a region of interest """ def __init__(self, x_min=0.0, x_max=0.0, y_min=0.0, y_max=0.0, bin_width=0.001, fold = False): # Minimum Qx value [A-1] self.x_min = x_min # Maximum Qx value [A-1] self.x_max = x_max # Minimum Qy value [A-1] self.y_min = y_min # Maximum Qy value [A-1] self.y_max = y_max # Bin width (step size) [A-1] self.bin_width = bin_width # If True, I(|Q|) will be return, otherwise, # negative q-values are allowed self.fold = fold def __call__(self, data2D): return NotImplemented def _avg(self, data2D, maj): """ Compute average I(Q_maj) for a region of interest. The major axis is defined as the axis of Q_maj. The minor axis is the axis that we average over. :param data2D: Data2D object :param maj_min: min value on the major axis :return: Data1D object """ if len(data2D.detector) > 1: msg = "_Slab._avg: invalid number of " msg += " detectors: %g" % len(data2D.detector) raise RuntimeError(msg) # Get data data = data2D.data[np.isfinite(data2D.data)] err_data = data2D.err_data[np.isfinite(data2D.data)] qx_data = data2D.qx_data[np.isfinite(data2D.data)] qy_data = data2D.qy_data[np.isfinite(data2D.data)] mask_data = data2D.mask[np.isfinite(data2D.data)] # Build array of Q intervals if maj == 'x': if self.fold: x_min = 0 else: x_min = self.x_min nbins = int(math.ceil((self.x_max - x_min) / self.bin_width)) elif maj == 'y': if self.fold: y_min = 0 else: y_min = self.y_min nbins = int(math.ceil((self.y_max - y_min) / self.bin_width)) else: raise RuntimeError("_Slab._avg: unrecognized axis %s" % str(maj)) x = np.zeros(nbins) y = np.zeros(nbins) err_y = np.zeros(nbins) y_counts = np.zeros(nbins) # Average pixelsize in q space for npts in range(len(data)): if not mask_data[npts]: # ignore points that are masked continue # default frac frac_x = 0 frac_y = 0 # get ROI if self.x_min <= qx_data[npts] and self.x_max > qx_data[npts]: frac_x = 1 if self.y_min <= qy_data[npts] and self.y_max > qy_data[npts]: frac_y = 1 frac = frac_x * frac_y if frac == 0: continue # binning: find axis of q if maj == 'x': q_value = qx_data[npts] min_value = x_min if maj == 'y': q_value = qy_data[npts] min_value = y_min if self.fold and q_value < 0: q_value = -q_value # bin i_q = int(math.ceil((q_value - min_value) / self.bin_width)) - 1 # skip outside of max bins if i_q < 0 or i_q >= nbins: continue # TODO: find better definition of x[i_q] based on q_data # min_value + (i_q + 1) * self.bin_width / 2.0 x[i_q] += frac * q_value y[i_q] += frac * data[npts] if err_data is None or err_data[npts] == 0.0: if data[npts] < 0: data[npts] = -data[npts] err_y[i_q] += frac * frac * data[npts] else: err_y[i_q] += frac * frac * err_data[npts] * err_data[npts] y_counts[i_q] += frac # Average the sums for n in range(nbins): err_y[n] = math.sqrt(err_y[n]) err_y = err_y / y_counts y = y / y_counts x = x / y_counts idx = (np.isfinite(y) & np.isfinite(x)) if not idx.any(): msg = "Average Error: No points inside ROI to average..." raise ValueError(msg) return Data1D(x=x[idx], y=y[idx], dy=err_y[idx]) class SlabY(_Slab): """ Compute average I(Qy) for a region of interest """ def __call__(self, data2D): """ Compute average I(Qy) for a region of interest :param data2D: Data2D object :return: Data1D object """ return self._avg(data2D, 'y') class SlabX(_Slab): """ Compute average I(Qx) for a region of interest """ def __call__(self, data2D): """ Compute average I(Qx) for a region of interest :param data2D: Data2D object :return: Data1D object """ return self._avg(data2D, 'x') ################################################################################ class Boxsum: """ Perform the sum of counts in a 2D region of interest. """ def __init__(self, x_min=0.0, x_max=0.0, y_min=0.0, y_max=0.0): # Minimum Qx value [A-1] self.x_min = x_min # Maximum Qx value [A-1] self.x_max = x_max # Minimum Qy value [A-1] self.y_min = y_min # Maximum Qy value [A-1] self.y_max = y_max def __call__(self, data2D): """ Perform the sum in the region of interest :param data2D: Data2D object :return: number of counts, error on number of counts, number of points summed """ y, err_y, y_counts = self._sum(data2D) # Average the sums counts = 0 if y_counts == 0 else y error = 0 if y_counts == 0 else math.sqrt(err_y) # Added y_counts to return, SMK & PDB, 04/03/2013 return counts, error, y_counts def _sum(self, data2D): """ Perform the sum in the region of interest :param data2D: Data2D object :return: number of counts, error on number of counts, number of entries summed """ if len(data2D.detector) > 1: msg = "Circular averaging: invalid number " msg += "of detectors: %g" % len(data2D.detector) raise RuntimeError(msg) # Get data data = data2D.data[np.isfinite(data2D.data)] err_data = data2D.err_data[np.isfinite(data2D.data)] qx_data = data2D.qx_data[np.isfinite(data2D.data)] qy_data = data2D.qy_data[np.isfinite(data2D.data)] mask_data = data2D.mask[np.isfinite(data2D.data)] y = 0.0 err_y = 0.0 y_counts = 0.0 # Average pixelsize in q space for npts in range(len(data)): if not mask_data[npts]: # ignore points that are masked continue # default frac frac_x = 0 frac_y = 0 # get min and max at each points qx = qx_data[npts] qy = qy_data[npts] # get the ROI if self.x_min <= qx and self.x_max > qx: frac_x = 1 if self.y_min <= qy and self.y_max > qy: frac_y = 1 # Find the fraction along each directions frac = frac_x * frac_y if frac == 0: continue y += frac * data[npts] if err_data is None or err_data[npts] == 0.0: if data[npts] < 0: data[npts] = -data[npts] err_y += frac * frac * data[npts] else: err_y += frac * frac * err_data[npts] * err_data[npts] y_counts += frac return y, err_y, y_counts class Boxavg(Boxsum): """ Perform the average of counts in a 2D region of interest. """ def __init__(self, x_min=0.0, x_max=0.0, y_min=0.0, y_max=0.0): super(Boxavg, self).__init__(x_min=x_min, x_max=x_max, y_min=y_min, y_max=y_max) def __call__(self, data2D): """ Perform the sum in the region of interest :param data2D: Data2D object :return: average counts, error on average counts """ y, err_y, y_counts = self._sum(data2D) # Average the sums counts = 0 if y_counts == 0 else y / y_counts error = 0 if y_counts == 0 else math.sqrt(err_y) / y_counts return counts, error ################################################################################ class CircularAverage: """ Perform circular averaging on 2D data The data returned is the distribution of counts as a function of Q """ def __init__(self, r_min=0.0, r_max=0.0, bin_width=0.0005): # Minimum radius included in the average [A-1] self.r_min = r_min # Maximum radius included in the average [A-1] self.r_max = r_max # Bin width (step size) [A-1] self.bin_width = bin_width def __call__(self, data2D, ismask=False): """ Perform circular averaging on the data :param data2D: Data2D object :return: Data1D object """ # Get data W/ finite values data = data2D.data[np.isfinite(data2D.data)] q_data = data2D.q_data[np.isfinite(data2D.data)] err_data = data2D.err_data[np.isfinite(data2D.data)] mask_data = data2D.mask[np.isfinite(data2D.data)] dq_data = None if data2D.dqx_data is not None and data2D.dqy_data is not None: dq_data = get_dq_data(data2D) if len(q_data) == 0: msg = "Circular averaging: invalid q_data: %g" % data2D.q_data raise RuntimeError(msg) # Build array of Q intervals nbins = int(math.ceil((self.r_max - self.r_min) / self.bin_width)) x = np.zeros(nbins) y = np.zeros(nbins) err_y = np.zeros(nbins) err_x = np.zeros(nbins) y_counts = np.zeros(nbins) for npt in range(len(data)): if ismask and not mask_data[npt]: continue frac = 0 # q-value at the pixel (j,i) q_value = q_data[npt] data_n = data[npt] # No need to calculate the frac when all data are within range if self.r_min >= self.r_max: raise ValueError("Limit Error: min > max") if self.r_min <= q_value and q_value <= self.r_max: frac = 1 if frac == 0: continue i_q = int(math.floor((q_value - self.r_min) / self.bin_width)) # Take care of the edge case at phi = 2pi. if i_q == nbins: i_q = nbins - 1 y[i_q] += frac * data_n # Take dqs from data to get the q_average x[i_q] += frac * q_value if err_data is None or err_data[npt] == 0.0: if data_n < 0: data_n = -data_n err_y[i_q] += frac * frac * data_n else: err_y[i_q] += frac * frac * err_data[npt] * err_data[npt] if dq_data is not None: # To be consistent with dq calculation in 1d reduction, # we need just the averages (not quadratures) because # it should not depend on the number of the q points # in the qr bins. err_x[i_q] += frac * dq_data[npt] else: err_x = None y_counts[i_q] += frac # Average the sums for n in range(nbins): if err_y[n] < 0: err_y[n] = -err_y[n] err_y[n] = math.sqrt(err_y[n]) # if err_x is not None: # err_x[n] = math.sqrt(err_x[n]) err_y = err_y / y_counts err_y[err_y == 0] = np.average(err_y) y = y / y_counts x = x / y_counts idx = (np.isfinite(y)) & (np.isfinite(x)) if err_x is not None: d_x = err_x[idx] / y_counts[idx] else: d_x = None if not idx.any(): msg = "Average Error: No points inside ROI to average..." raise ValueError(msg) return Data1D(x=x[idx], y=y[idx], dy=err_y[idx], dx=d_x) ################################################################################ class Ring: """ Defines a ring on a 2D data set. The ring is defined by r_min, r_max, and the position of the center of the ring. The data returned is the distribution of counts around the ring as a function of phi. Phi_min and phi_max should be defined between 0 and 2*pi in anti-clockwise starting from the x- axis on the left-hand side """ # Todo: remove center. def __init__(self, r_min=0, r_max=0, center_x=0, center_y=0, nbins=36): # Minimum radius self.r_min = r_min # Maximum radius self.r_max = r_max # Center of the ring in x self.center_x = center_x # Center of the ring in y self.center_y = center_y # Number of angular bins self.nbins_phi = nbins def __call__(self, data2D): """ Apply the ring to the data set. Returns the angular distribution for a given q range :param data2D: Data2D object :return: Data1D object """ if data2D.__class__.__name__ not in ["Data2D", "plottable_2D"]: raise RuntimeError("Ring averaging only take plottable_2D objects") Pi = math.pi # Get data data = data2D.data[np.isfinite(data2D.data)] q_data = data2D.q_data[np.isfinite(data2D.data)] err_data = data2D.err_data[np.isfinite(data2D.data)] qx_data = data2D.qx_data[np.isfinite(data2D.data)] qy_data = data2D.qy_data[np.isfinite(data2D.data)] mask_data = data2D.mask[np.isfinite(data2D.data)] # Set space for 1d outputs phi_bins = np.zeros(self.nbins_phi) phi_counts = np.zeros(self.nbins_phi) phi_values = np.zeros(self.nbins_phi) phi_err = np.zeros(self.nbins_phi) # Shift to apply to calculated phi values in order # to center first bin at zero phi_shift = Pi / self.nbins_phi for npt in range(len(data)): if not mask_data[npt]: # ignore points that are masked continue frac = 0 # q-value at the point (npt) q_value = q_data[npt] data_n = data[npt] # phi-value at the point (npt) phi_value = math.atan2(qy_data[npt], qx_data[npt]) + Pi if self.r_min <= q_value and q_value <= self.r_max: frac = 1 if frac == 0: continue # binning i_phi = int(math.floor((self.nbins_phi) * (phi_value + phi_shift) / (2 * Pi))) # Take care of the edge case at phi = 2pi. if i_phi >= self.nbins_phi: i_phi = 0 phi_bins[i_phi] += frac * data[npt] if err_data is None or err_data[npt] == 0.0: if data_n < 0: data_n = -data_n phi_err[i_phi] += frac * frac * math.fabs(data_n) else: phi_err[i_phi] += frac * frac * err_data[npt] * err_data[npt] phi_counts[i_phi] += frac for i in range(self.nbins_phi): phi_bins[i] = phi_bins[i] / phi_counts[i] phi_err[i] = math.sqrt(phi_err[i]) / phi_counts[i] phi_values[i] = 2.0 * math.pi / self.nbins_phi * (1.0 * i) idx = (np.isfinite(phi_bins)) if not idx.any(): msg = "Average Error: No points inside ROI to average..." raise ValueError(msg) # elif len(phi_bins[idx])!= self.nbins_phi: # print "resulted",self.nbins_phi- len(phi_bins[idx]) #,"empty bin(s) due to tight binning..." return Data1D(x=phi_values[idx], y=phi_bins[idx], dy=phi_err[idx]) class _Sector: """ Defines a sector region on a 2D data set. The sector is defined by r_min, r_max, phi_min, phi_max, and the position of the center of the ring where phi_min and phi_max are defined by the right and left lines wrt central line and phi_max could be less than phi_min. Phi is defined between 0 and 2*pi in anti-clockwise starting from the x- axis on the left-hand side """ def __init__(self, r_min, r_max, phi_min=0, phi_max=2 * math.pi, nbins=20, base=None): ''' :param base: must be a valid base for an algorithm, i.e., a positive number ''' self.r_min = r_min self.r_max = r_max self.phi_min = phi_min self.phi_max = phi_max self.nbins = nbins self.base = base def _agv(self, data2D, run='phi'): """ Perform sector averaging. :param data2D: Data2D object :param run: define the varying parameter ('phi' , 'q' , or 'q2') :return: Data1D object """ if data2D.__class__.__name__ not in ["Data2D", "plottable_2D"]: raise RuntimeError("Ring averaging only take plottable_2D objects") # Get the all data & info data = data2D.data[np.isfinite(data2D.data)] q_data = data2D.q_data[np.isfinite(data2D.data)] err_data = data2D.err_data[np.isfinite(data2D.data)] qx_data = data2D.qx_data[np.isfinite(data2D.data)] qy_data = data2D.qy_data[np.isfinite(data2D.data)] mask_data = data2D.mask[np.isfinite(data2D.data)] dq_data = None if data2D.dqx_data is not None and data2D.dqy_data is not None: dq_data = get_dq_data(data2D) # set space for 1d outputs x = np.zeros(self.nbins) y = np.zeros(self.nbins) y_err = np.zeros(self.nbins) x_err = np.zeros(self.nbins) y_counts = np.zeros(self.nbins) # Cycle counts (for the mean) # Get the min and max into the region: 0 <= phi < 2Pi phi_min = flip_phi(self.phi_min) phi_max = flip_phi(self.phi_max) # binning object if run.lower() == 'phi': binning = Binning(self.phi_min, self.phi_max, self.nbins, self.base) else: binning = Binning(self.r_min, self.r_max, self.nbins, self.base) for n in range(len(data)): if not mask_data[n]: # ignore points that are masked continue # q-value at the pixel (j,i) q_value = q_data[n] data_n = data[n] # Is pixel within range? is_in = False # phi-value of the pixel (j,i) phi_value = math.atan2(qy_data[n], qx_data[n]) + math.pi # No need to calculate: data outside of the radius if self.r_min > q_value or q_value > self.r_max: continue # In case of two ROIs (symmetric major and minor regions)(for 'q2') if run.lower() == 'q2': # For minor sector wing # Calculate the minor wing phis phi_min_minor = flip_phi(phi_min - math.pi) phi_max_minor = flip_phi(phi_max - math.pi) # Check if phis of the minor ring is within 0 to 2pi if phi_min_minor > phi_max_minor: is_in = (phi_value > phi_min_minor or phi_value < phi_max_minor) else: is_in = (phi_value > phi_min_minor and phi_value < phi_max_minor) # For all cases(i.e.,for 'q', 'q2', and 'phi') # Find pixels within ROI if phi_min > phi_max: is_in = is_in or (phi_value > phi_min or phi_value < phi_max) else: is_in = is_in or (phi_value >= phi_min and phi_value < phi_max) # data oustide of the phi range if not is_in: continue # Get the binning index if run.lower() == 'phi': i_bin = binning.get_bin_index(phi_value) else: i_bin = binning.get_bin_index(q_value) # Take care of the edge case at phi = 2pi. if i_bin == self.nbins: i_bin = self.nbins - 1 # Get the total y y[i_bin] += data_n x[i_bin] += q_value if err_data[n] is None or err_data[n] == 0.0: if data_n < 0: data_n = -data_n y_err[i_bin] += data_n else: y_err[i_bin] += err_data[n]**2 if dq_data is not None: # To be consistent with dq calculation in 1d reduction, # we need just the averages (not quadratures) because # it should not depend on the number of the q points # in the qr bins. x_err[i_bin] += dq_data[n] else: x_err = None y_counts[i_bin] += 1 # Organize the results with np.errstate(divide='ignore', invalid='ignore'): y = y/y_counts y_err = np.sqrt(y_err)/y_counts # The type of averaging: phi, q2, or q # Calculate x values at the center of the bin if run.lower() == 'phi': step = (self.phi_max - self.phi_min) / self.nbins x = (np.arange(self.nbins) + 0.5) * step + self.phi_min else: # set q to the average of the q values within each bin x = x/y_counts ### Alternate algorithm ## We take the center of ring area, not radius. ## This is more accurate than taking the radial center of ring. #step = (self.r_max - self.r_min) / self.nbins #r_inner = self.r_min + step * np.arange(self.nbins) #x = math.sqrt((r_inner**2 + (r_inner + step)**2) / 2) idx = (np.isfinite(y) & np.isfinite(y_err)) if x_err is not None: d_x = x_err[idx] / y_counts[idx] else: d_x = None if not idx.any(): msg = "Average Error: No points inside sector of ROI to average..." raise ValueError(msg) # elif len(y[idx])!= self.nbins: # print "resulted",self.nbins- len(y[idx]), # "empty bin(s) due to tight binning..." return Data1D(x=x[idx], y=y[idx], dy=y_err[idx], dx=d_x) class SectorPhi(_Sector): """ Sector average as a function of phi. I(phi) is return and the data is averaged over Q. A sector is defined by r_min, r_max, phi_min, phi_max. The number of bin in phi also has to be defined. """ def __call__(self, data2D): """ Perform sector average and return I(phi). :param data2D: Data2D object :return: Data1D object """ return self._agv(data2D, 'phi') class SectorQ(_Sector): """ Sector average as a function of Q for both symatric wings. I(Q) is return and the data is averaged over phi. A sector is defined by r_min, r_max, phi_min, phi_max. r_min, r_max, phi_min, phi_max >0. The number of bin in Q also has to be defined. """ def __call__(self, data2D): """ Perform sector average and return I(Q). :param data2D: Data2D object :return: Data1D object """ return self._agv(data2D, 'q2') ################################################################################ class Ringcut: """ Defines a ring on a 2D data set. The ring is defined by r_min, r_max, and the position of the center of the ring. The data returned is the region inside the ring Phi_min and phi_max should be defined between 0 and 2*pi in anti-clockwise starting from the x- axis on the left-hand side """ def __init__(self, r_min=0, r_max=0, center_x=0, center_y=0): # Minimum radius self.r_min = r_min # Maximum radius self.r_max = r_max # Center of the ring in x self.center_x = center_x # Center of the ring in y self.center_y = center_y def __call__(self, data2D): """ Apply the ring to the data set. Returns the angular distribution for a given q range :param data2D: Data2D object :return: index array in the range """ if data2D.__class__.__name__ not in ["Data2D", "plottable_2D"]: raise RuntimeError("Ring cut only take plottable_2D objects") # Get data qx_data = data2D.qx_data qy_data = data2D.qy_data q_data = np.sqrt(qx_data * qx_data + qy_data * qy_data) # check whether or not the data point is inside ROI out = (self.r_min <= q_data) & (self.r_max >= q_data) return out ################################################################################ class Boxcut: """ Find a rectangular 2D region of interest. """ def __init__(self, x_min=0.0, x_max=0.0, y_min=0.0, y_max=0.0): # Minimum Qx value [A-1] self.x_min = x_min # Maximum Qx value [A-1] self.x_max = x_max # Minimum Qy value [A-1] self.y_min = y_min # Maximum Qy value [A-1] self.y_max = y_max def __call__(self, data2D): """ Find a rectangular 2D region of interest. :param data2D: Data2D object :return: mask, 1d array (len = len(data)) with Trues where the data points are inside ROI, otherwise False """ mask = self._find(data2D) return mask def _find(self, data2D): """ Find a rectangular 2D region of interest. :param data2D: Data2D object :return: out, 1d array (length = len(data)) with Trues where the data points are inside ROI, otherwise Falses """ if data2D.__class__.__name__ not in ["Data2D", "plottable_2D"]: raise RuntimeError("Boxcut take only plottable_2D objects") # Get qx_ and qy_data qx_data = data2D.qx_data qy_data = data2D.qy_data # check whether or not the data point is inside ROI outx = (self.x_min <= qx_data) & (self.x_max > qx_data) outy = (self.y_min <= qy_data) & (self.y_max > qy_data) return outx & outy ################################################################################ class Sectorcut: """ Defines a sector (major + minor) region on a 2D data set. The sector is defined by phi_min, phi_max, where phi_min and phi_max are defined by the right and left lines wrt central line. Phi_min and phi_max are given in units of radian and (phi_max-phi_min) should not be larger than pi """ def __init__(self, phi_min=0, phi_max=math.pi): self.phi_min = phi_min self.phi_max = phi_max def __call__(self, data2D): """ Find a rectangular 2D region of interest. :param data2D: Data2D object :return: mask, 1d array (len = len(data)) with Trues where the data points are inside ROI, otherwise False """ mask = self._find(data2D) return mask def _find(self, data2D): """ Find a rectangular 2D region of interest. :param data2D: Data2D object :return: out, 1d array (length = len(data)) with Trues where the data points are inside ROI, otherwise Falses """ if data2D.__class__.__name__ not in ["Data2D", "plottable_2D"]: raise RuntimeError("Sectorcut take only plottable_2D objects") Pi = math.pi # Get data qx_data = data2D.qx_data qy_data = data2D.qy_data # get phi from data phi_data = np.arctan2(qy_data, qx_data) # Get the min and max into the region: -pi <= phi < Pi phi_min_major = flip_phi(self.phi_min + Pi) - Pi phi_max_major = flip_phi(self.phi_max + Pi) - Pi # check for major sector if phi_min_major > phi_max_major: out_major = (phi_min_major <= phi_data) + \ (phi_max_major > phi_data) else: out_major = (phi_min_major <= phi_data) & ( phi_max_major > phi_data) # minor sector # Get the min and max into the region: -pi <= phi < Pi phi_min_minor = flip_phi(self.phi_min) - Pi phi_max_minor = flip_phi(self.phi_max) - Pi # check for minor sector if phi_min_minor > phi_max_minor: out_minor = (phi_min_minor <= phi_data) + \ (phi_max_minor >= phi_data) else: out_minor = (phi_min_minor <= phi_data) & \ (phi_max_minor >= phi_data) out = out_major + out_minor return out sasdata-0.8.1/sasdata/data_util/nxsunit.py000066400000000000000000000202751427502211700206170ustar00rootroot00000000000000# This program is public domain # Author: Paul Kienzle """ Define unit conversion support for NeXus style units. The unit format is somewhat complicated. There are variant spellings and incorrect capitalization to worry about, as well as forms such as "mili*metre" and "1e-7 seconds". This is a minimal implementation of units including only what I happen to need now. It does not support the complete dimensional analysis provided by the package udunits on which NeXus is based, or even the units used in the NeXus definition files. Unlike other units packages, this package does not carry the units along with the value but merely provides a conversion function for transforming values. Usage example:: import nxsunit u = nxsunit.Converter('mili*metre') # Units stored in mm v = u(3000,'m') # Convert the value 3000 mm into meters NeXus example:: # Load sample orientation in radians regardless of how it is stored. # 1. Open the path file.openpath('/entry1/sample/sample_orientation') # 2. scan the attributes, retrieving 'units' units = [for attr,value in file.attrs() if attr == 'units'] # 3. set up the converter (assumes that units actually exists) u = nxsunit.Converter(units[0]) # 4. read the data and convert to the correct units v = u(file.read(),'radians') This is a standalone module, not relying on either DANSE or NeXus, and can be used for other unit conversion tasks. Note: minutes are used for angle and seconds are used for time. We cannot tell what the correct interpretation is without knowing something about the fields themselves. If this becomes an issue, we will need to allow the application to set the dimension for the unit rather than inferring the dimension from an example unit. """ # TODO: Add udunits to NAPI rather than reimplementing it in python # TODO: Alternatively, parse the udunits database directly # UDUnits: # http://www.unidata.ucar.edu/software/udunits/udunits-1/udunits.txt import math __all__ = ['Converter'] # Limited form of units for returning objects of a specific type. # Maybe want to do full units handling with e.g., pyre's # unit class. For now lets keep it simple. Note that def _build_metric_units(unit,abbr): """ Construct standard SI names for the given unit. Builds e.g., s, ns second, nanosecond, nano*second seconds, nanoseconds Includes prefixes for femto through peta. Ack! Allows, e.g., Coulomb and coulomb even though Coulomb is not a unit because some NeXus files store it that way! Returns a dictionary of names and scales. """ prefix = dict(peta=1e15,tera=1e12,giga=1e9,mega=1e6,kilo=1e3, deci=1e-1,centi=1e-2,milli=1e-3,mili=1e-3,micro=1e-6, nano=1e-9,pico=1e-12,femto=1e-15) short_prefix = dict(P=1e15,T=1e12,G=1e9,M=1e6,k=1e3, d=1e-1,c=1e-2,m=1e-3,u=1e-6, n=1e-9,p=1e-12,f=1e-15) map = {abbr:1} map.update([(P+abbr,scale) for (P,scale) in short_prefix.items()]) for name in [unit,unit.capitalize()]: map.update({name:1,name+'s':1}) map.update([(P+name,scale) for (P,scale) in prefix.items()]) map.update([(P+'*'+name,scale) for (P,scale) in prefix.items()]) map.update([(P+name+'s',scale) for (P,scale) in prefix.items()]) return map def _build_plural_units(**kw): """ Construct names for the given units. Builds singular and plural form. """ map = {} map.update([(name,scale) for name,scale in kw.items()]) map.update([(name+'s',scale) for name,scale in kw.items()]) return map def _caret_optional(s): """ Strip '^' from unit names. * WARNING * this will incorrectly transform 10^3 to 103. """ stripped = [(k.replace('^',''),v) for k, v in s.items() if '^' in k] s.update(stripped) def _build_all_units(): distance = _build_metric_units('meter','m') distance.update(_build_metric_units('metre','m')) distance.update(_build_plural_units(micron=1e-6, Angstrom=1e-10)) distance.update({'A':1e-10, 'Ang':1e-10}) # Note: minutes are used for angle time = _build_metric_units('second','s') time.update(_build_plural_units(hour=3600,day=24*3600,week=7*24*3600)) # Note: seconds are used for time angle = _build_plural_units(degree=1, minute=1/60., arcminute=1/60., arcsecond=1/3600., radian=180/math.pi) angle.update(deg=1, arcmin=1/60., arcsec=1/3600., rad=180/math.pi) frequency = _build_metric_units('hertz','Hz') frequency.update(_build_metric_units('Hertz','Hz')) frequency.update(_build_plural_units(rpm=1/60.)) # Note: degrees are used for angle # Note: temperature needs an offset as well as a scale temperature = _build_metric_units('kelvin','K') temperature.update(_build_metric_units('Kelvin','K')) temperature.update(_build_metric_units('Celcius', 'C')) temperature.update(_build_metric_units('celcius', 'C')) charge = _build_metric_units('coulomb','C') charge.update({'microAmp*hour':0.0036}) sld = { '10^-6 Angstrom^-2': 1e-6, 'Angstrom^-2': 1 } Q = { 'invA': 1, 'invAng': 1, 'invAngstroms': 1, '1/A': 1, '1/Angstrom': 1, '1/angstrom': 1, 'A^{-1}': 1, 'cm^{-1}': 1e-8, '10^-3 Angstrom^-1': 1e-3, '1/cm': 1e-8, '1/m': 1e-10, 'nm^{-1}': 1, 'nm^-1': 0.1, '1/nm': 0.1, 'n_m^-1': 0.1 } _caret_optional(sld) _caret_optional(Q) dims = [distance, time, angle, frequency, temperature, charge, sld, Q] return dims class Converter(object): """ Unit converter for NeXus style units. """ # Define the units, using both American and European spelling. scalemap = None scalebase = 1 dims = _build_all_units() # Note: a.u. stands for arbitrary units, which should return the default # units for that particular dimension. # Note: don't have support for dimensionless units. unknown = {None: 1, '???': 1, '': 1, 'a.u.': 1, 'Counts': 1, 'counts': 1, 'arbitrary': 1, 'arbitrary units': 1} def __init__(self, name): self.base = name for map in self.dims: if name in map: self.scalemap = map self.scalebase = self.scalemap[name] return if name in self.unknown: return # default scalemap and scalebase correspond to unknown else: raise KeyError("Unknown unit %s"%name) def scale(self, units=""): if units == "" or self.scalemap is None: return 1 return self.scalebase/self.scalemap[units] def __call__(self, value, units=""): # Note: calculating a*1 rather than simply returning a would produce # an unnecessary copy of the array, which in the case of the raw # counts array would be bad. Sometimes copying and other times # not copying is also bad, but copy on modify semantics isn't # supported. if units == "" or self.scalemap is None: return value try: return value * (self.scalebase/self.scalemap[units]) except KeyError: possible_units = ", ".join(str(k) for k in self.scalemap.keys()) raise KeyError("%s not in %s"%(units,possible_units)) def _check(expect,get): if expect != get: raise ValueError("Expected %s but got %s"%(expect, get)) #print expect,"==",get def test(): _check(1,Converter('n_m^-1')(10,'invA')) # 10 nm^-1 = 1 inv Angstroms _check(2,Converter('mm')(2000,'m')) # 2000 mm -> 2 m _check(2.011e10,Converter('1/A')(2.011,"1/m")) # 2.011 1/A -> 2.011 * 10^10 1/m _check(0.003,Converter('microseconds')(3,units='ms')) # 3 us -> 0.003 ms _check(45,Converter('nanokelvin')(45)) # 45 nK -> 45 nK _check(0.5,Converter('seconds')(1800,units='hours')) # 1800 s -> 0.5 hr _check(123,Converter('a.u.')(123,units='mm')) # arbitrary units always returns the same value _check(123,Converter('a.u.')(123,units='s')) # arbitrary units always returns the same value _check(123,Converter('a.u.')(123,units='')) # arbitrary units always returns the same value try: Converter('help') except KeyError: pass else: raise Exception("unknown unit did not raise an error") # TODO: more tests if __name__ == "__main__": test() sasdata-0.8.1/sasdata/data_util/registry.py000066400000000000000000000105311427502211700207510ustar00rootroot00000000000000""" File extension registry. This provides routines for opening files based on extension, and registers the built-in file extensions. """ from typing import Optional, List, Union from collections import defaultdict from sasdata.data_util.loader_exceptions import NoKnownLoaderException from sasdata.data_util.util import unique_preserve_order from sasdata.dataloader.filereader import FileReader class ExtensionRegistry: """ Associate a file loader with an extension. Note that there may be multiple loaders for the same extension. Example: :: registry = ExtensionRegistry() # Add an association by setting an element registry['.zip'] = unzip # Multiple extensions for one loader registry['.tgz'] = untar registry['.tar.gz'] = untar # Generic extensions to use after trying more specific extensions; # these will be checked after the more specific extensions fail. registry['.gz'] = gunzip # Multiple loaders for one extension registry['.cx'] = cx1 registry['.cx'] = cx2 registry['.cx'] = cx3 # Show registered extensions print registry.extensions() # Can also register a format name for explicit control from caller registry['cx3'] = cx3 print registry.formats() # Retrieve loaders for a file name registry.lookup('hello.cx') -> [cx3,cx2,cx1] # Run loader on a filename registry.load('hello.cx') -> try: return cx3('hello.cx') except: try: return cx2('hello.cx') except: return cx1('hello.cx') # Load in a specific format ignoring extension registry.load('hello.cx',format='cx3') -> return cx3('hello.cx') """ def __init__(self): self.readers = defaultdict(list) def __setitem__(self, ext: str, loader: FileReader): self.readers[ext].insert(0, loader) def __getitem__(self, ext: str) -> List[FileReader]: return self.readers[ext] def __contains__(self, ext: str) -> bool: return ext in self.readers def formats(self) -> List[str]: """ Return a sorted list of the registered formats. """ names = [a for a in self.readers.keys() if not a.startswith('.')] names.sort() return names def extensions(self) -> List[str]: """ Return a sorted list of registered extensions. """ exts = [a for a in self.readers.keys() if a.startswith('.')] exts.sort() return exts def lookup(self, path: str) -> List[str]: """ Return the loader associated with the file type of path. :param path: Data file path :return: List of available readers for the file extension (maybe empty) """ # Find matching lower-case extensions path_lower = path.lower() extensions = [ext for ext in self.extensions() if path_lower.endswith(ext)] # Sort matching extensions by decreasing order of length extensions.sort(key=len) # Combine readers for matching extensions into one big list readers = [reader for ext in extensions for reader in self.readers[ext]] return unique_preserve_order(readers) def load(self, path: str, ext: Optional[str] = None) -> Union[List[FileReader], Exception]: """ Call the loader for the file type of path. Raises an exception if the loader fails or if no loaders are defined for the given path or format. """ if ext is None: loaders = self.lookup(path) if not loaders: raise NoKnownLoaderException("No loaders match extension in %r" % path) else: loaders = self.readers.get(ext.lower(), []) if not loaders: raise NoKnownLoaderException("No loaders match format %r" % ext) last_exc = None for load_function in loaders: try: return load_function(path) except Exception as e: last_exc = e pass # give other loaders a chance to succeed # If we get here it is because all loaders failed raise last_exc sasdata-0.8.1/sasdata/data_util/uncertainty.py000066400000000000000000000261561427502211700214600ustar00rootroot00000000000000r""" Uncertainty propagation class for arithmetic, log and exp. Based on scalars or numpy vectors, this class allows you to store and manipulate values+uncertainties, with propagation of gaussian error for addition, subtraction, multiplication, division, power, exp and log. Storage properties are determined by the numbers used to set the value and uncertainty. Be sure to use floating point uncertainty vectors for inplace operations since numpy does not do automatic type conversion. Normal operations can use mixed integer and floating point. In place operations such as *a \*= b* create at most one extra copy for each operation. By contrast, *c = a\*b* uses four intermediate vectors, so shouldn't be used for huge arrays. """ import numpy as np from . import err1d from .formatnum import format_uncertainty __all__ = ['Uncertainty'] # TODO: rename to Measurement and add support for units? # TODO: C implementation of *,/,**? class Uncertainty(object): # Make standard deviation available def _getdx(self): return np.sqrt(self.variance) def _setdx(self,dx): # Direct operation # variance = dx**2 # Indirect operation to avoid temporaries self.variance[:] = dx self.variance **= 2 dx = property(_getdx,_setdx,doc="standard deviation") # Constructor def __init__(self, x, variance=None): self.x, self.variance = x, variance # Numpy array slicing operations def __len__(self): return len(self.x) def __getitem__(self,key): return Uncertainty(self.x[key],self.variance[key]) def __setitem__(self,key,value): self.x[key] = value.x self.variance[key] = value.variance def __delitem__(self, key): del self.x[key] del self.variance[key] #def __iter__(self): pass # Not sure we need iter # Normal operations: may be of mixed type def __add__(self, other): if isinstance(other,Uncertainty): return Uncertainty(*err1d.add(self.x,self.variance,other.x,other.variance)) else: return Uncertainty(self.x+other, self.variance+0) # Force copy def __sub__(self, other): if isinstance(other,Uncertainty): return Uncertainty(*err1d.sub(self.x,self.variance,other.x,other.variance)) else: return Uncertainty(self.x-other, self.variance+0) # Force copy def __mul__(self, other): if isinstance(other,Uncertainty): return Uncertainty(*err1d.mul(self.x,self.variance,other.x,other.variance)) else: return Uncertainty(self.x*other, self.variance*other**2) def __truediv__(self, other): if isinstance(other,Uncertainty): return Uncertainty(*err1d.div(self.x,self.variance,other.x,other.variance)) else: return Uncertainty(self.x/other, self.variance/other**2) def __pow__(self, other): if isinstance(other,Uncertainty): # Haven't calcuated variance in (a+/-da) ** (b+/-db) return NotImplemented else: return Uncertainty(*err1d.pow(self.x,self.variance,other)) # Reverse operations def __radd__(self, other): return Uncertainty(self.x+other, self.variance+0) # Force copy def __rsub__(self, other): return Uncertainty(other-self.x, self.variance+0) def __rmul__(self, other): return Uncertainty(self.x*other, self.variance*other**2) def __rtruediv__(self, other): x,variance = err1d.pow(self.x,self.variance,-1) return Uncertainty(x*other,variance*other**2) def __rpow__(self, other): return NotImplemented # In-place operations: may be of mixed type def __iadd__(self, other): if isinstance(other,Uncertainty): self.x,self.variance \ = err1d.add_inplace(self.x,self.variance,other.x,other.variance) else: self.x+=other return self def __isub__(self, other): if isinstance(other,Uncertainty): self.x,self.variance \ = err1d.sub_inplace(self.x,self.variance,other.x,other.variance) else: self.x-=other return self def __imul__(self, other): if isinstance(other,Uncertainty): self.x, self.variance \ = err1d.mul_inplace(self.x,self.variance,other.x,other.variance) else: self.x *= other self.variance *= other**2 return self def __itruediv__(self, other): if isinstance(other,Uncertainty): self.x,self.variance \ = err1d.div_inplace(self.x,self.variance,other.x,other.variance) else: self.x /= other self.variance /= other**2 return self def __ipow__(self, other): if isinstance(other,Uncertainty): # Haven't calcuated variance in (a+/-da) ** (b+/-db) return NotImplemented else: self.x,self.variance = err1d.pow_inplace(self.x, self.variance, other) return self # Use true division instead of integer division def __div__(self, other): return self.__truediv__(other) def __rdiv__(self, other): return self.__rtruediv__(other) def __idiv__(self, other): return self.__itruediv__(other) # Unary ops def __neg__(self): return Uncertainty(-self.x,self.variance) def __pos__(self): return self def __abs__(self): return Uncertainty(np.abs(self.x),self.variance) def __str__(self): #return str(self.x)+" +/- "+str(np.sqrt(self.variance)) if np.isscalar(self.x): return format_uncertainty(self.x,np.sqrt(self.variance)) else: return [format_uncertainty(v,dv) for v,dv in zip(self.x,np.sqrt(self.variance))] def __repr__(self): return "Uncertainty(%s,%s)"%(str(self.x),str(self.variance)) # Not implemented def __floordiv__(self, other): return NotImplemented def __mod__(self, other): return NotImplemented def __divmod__(self, other): return NotImplemented def __mod__(self, other): return NotImplemented def __lshift__(self, other): return NotImplemented def __rshift__(self, other): return NotImplemented def __and__(self, other): return NotImplemented def __xor__(self, other): return NotImplemented def __or__(self, other): return NotImplemented def __rfloordiv__(self, other): return NotImplemented def __rmod__(self, other): return NotImplemented def __rdivmod__(self, other): return NotImplemented def __rmod__(self, other): return NotImplemented def __rlshift__(self, other): return NotImplemented def __rrshift__(self, other): return NotImplemented def __rand__(self, other): return NotImplemented def __rxor__(self, other): return NotImplemented def __ror__(self, other): return NotImplemented def __ifloordiv__(self, other): return NotImplemented def __imod__(self, other): return NotImplemented def __idivmod__(self, other): return NotImplemented def __imod__(self, other): return NotImplemented def __ilshift__(self, other): return NotImplemented def __irshift__(self, other): return NotImplemented def __iand__(self, other): return NotImplemented def __ixor__(self, other): return NotImplemented def __ior__(self, other): return NotImplemented def __invert__(self): return NotImplmented # For ~x def __complex__(self): return NotImplmented def __int__(self): return NotImplmented def __long__(self): return NotImplmented def __float__(self): return NotImplmented def __oct__(self): return NotImplmented def __hex__(self): return NotImplmented def __index__(self): return NotImplmented def __coerce__(self): return NotImplmented def log(self): return Uncertainty(*err1d.log(self.x,self.variance)) def exp(self): return Uncertainty(*err1d.exp(self.x,self.variance)) def log(val): return self.log() def exp(val): return self.exp() def test(): a = Uncertainty(5,3) b = Uncertainty(4,2) # Scalar operations z = a+4 assert z.x == 5+4 and z.variance == 3 z = a-4 assert z.x == 5-4 and z.variance == 3 z = a*4 assert z.x == 5*4 and z.variance == 3*4**2 z = a/4 assert z.x == 5./4 and z.variance == 3./4**2 # Reverse scalar operations z = 4+a assert z.x == 4+5 and z.variance == 3 z = 4-a assert z.x == 4-5 and z.variance == 3 z = 4*a assert z.x == 4*5 and z.variance == 3*4**2 z = 4/a assert z.x == 4./5 and abs(z.variance - 3./5**4 * 4**2) < 1e-15 # Power operations z = a**2 assert z.x == 5**2 and z.variance == 4*3*5**2 z = a**1 assert z.x == 5**1 and z.variance == 3 z = a**0 assert z.x == 5**0 and z.variance == 0 z = a**-1 assert z.x == 5**-1 and abs(z.variance - 3./5**4) < 1e-15 # Binary operations z = a+b assert z.x == 5+4 and z.variance == 3+2 z = a-b assert z.x == 5-4 and z.variance == 3+2 z = a*b assert z.x == 5*4 and z.variance == (5**2*2 + 4**2*3) z = a/b assert z.x == 5./4 and abs(z.variance - (3./5**2 + 2./4**2)*(5./4)**2) < 1e-15 # ===== Inplace operations ===== # Scalar operations y = a+0; y += 4 z = a+4 assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y -= 4 z = a-4 assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y *= 4 z = a*4 assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y /= 4 z = a/4 assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 # Power operations y = a+0; y **= 4 z = a**4 assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 # Binary operations y = a+0; y += b z = a+b assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y -= b z = a-b assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y *= b z = a*b assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 y = a+0; y /= b z = a/b assert y.x == z.x and abs(y.variance-z.variance) < 1e-15 # =============== vector operations ================ # Slicing z = Uncertainty(np.array([1,2,3,4,5]),np.array([2,1,2,3,2])) assert z[2].x == 3 and z[2].variance == 2 assert (z[2:4].x == [3,4]).all() assert (z[2:4].variance == [2,3]).all() z[2:4] = Uncertainty(np.array([8,7]),np.array([4,5])) assert z[2].x == 8 and z[2].variance == 4 A = Uncertainty(np.array([a.x]*2),np.array([a.variance]*2)) B = Uncertainty(np.array([b.x]*2),np.array([b.variance]*2)) # TODO complete tests of copy and inplace operations for vectors and slices. # Binary operations z = A+B assert (z.x == 5+4).all() and (z.variance == 3+2).all() z = A-B assert (z.x == 5-4).all() and (z.variance == 3+2).all() z = A*B assert (z.x == 5*4).all() and (z.variance == (5**2*2 + 4**2*3)).all() z = A/B assert (z.x == 5./4).all() assert (abs(z.variance - (3./5**2 + 2./4**2)*(5./4)**2) < 1e-15).all() # printing; note that sqrt(3) ~ 1.7 assert str(Uncertainty(5,3)) == "5.0(17)" assert str(Uncertainty(15,3)) == "15.0(17)" assert str(Uncertainty(151.23356,0.324185**2)) == "151.23(32)" if __name__ == "__main__": test() sasdata-0.8.1/sasdata/data_util/util.py000066400000000000000000000005241427502211700200570ustar00rootroot00000000000000from typing import List, Any def unique_preserve_order(seq: List[Any]) -> List[Any]: """ Remove duplicates from list preserving order Fastest according to benchmarks at https://www.peterbe.com/plog/uniqifiers-benchmark """ seen = set() seen_add = seen.add return [x for x in seq if not (x in seen or seen_add(x))] sasdata-0.8.1/sasdata/dataloader/000077500000000000000000000000001427502211700166615ustar00rootroot00000000000000sasdata-0.8.1/sasdata/dataloader/__init__.py000066400000000000000000000002021427502211700207640ustar00rootroot00000000000000from sasdata.dataloader.data_info import * from sasdata.data_util.manipulations import * from sasdata.dataloader.readers import * sasdata-0.8.1/sasdata/dataloader/data_info.py000066400000000000000000001253371427502211700211720ustar00rootroot00000000000000""" Module that contains classes to hold information read from reduced data files. A good description of the data members can be found in the CanSAS 1D XML data format: http://www.smallangles.net/wgwiki/index.php/cansas1d_documentation """ ##################################################################### # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # See the license text in license.txt # copyright 2008, University of Tennessee ###################################################################### # TODO: Keep track of data manipulation in the 'process' data structure. # TODO: This module should be independent of plottables. We should write # an adapter class for plottables when needed. import math from math import fabs import copy import numpy as np from sasdata.data_util.uncertainty import Uncertainty class plottable_1D(object): """ Data1D is a place holder for 1D plottables. """ # The presence of these should be mutually # exclusive with the presence of Qdev (dx) x = None y = None dx = None dy = None # Slit smearing length dxl = None # Slit smearing width dxw = None # SESANS specific params (wavelengths for spin echo length calculation) lam = None dlam = None # Units _xaxis = '' _xunit = '' _yaxis = '' _yunit = '' def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None): self.x = np.asarray(x) self.y = np.asarray(y) if dx is not None: self.dx = np.asarray(dx) if dy is not None: self.dy = np.asarray(dy) if dxl is not None: self.dxl = np.asarray(dxl) if dxw is not None: self.dxw = np.asarray(dxw) if lam is not None: self.lam = np.asarray(lam) if dlam is not None: self.dlam = np.asarray(dlam) def xaxis(self, label, unit): """ set the x axis label and unit """ self._xaxis = label self._xunit = unit def yaxis(self, label, unit): """ set the y axis label and unit """ self._yaxis = label self._yunit = unit class plottable_2D(object): """ Data2D is a place holder for 2D plottables. """ xmin = None xmax = None ymin = None ymax = None data = None qx_data = None qy_data = None q_data = None err_data = None dqx_data = None dqy_data = None mask = None x_bins = None y_bins = None # Units _xaxis = '' _xunit = '' _yaxis = '' _yunit = '' _zaxis = '' _zunit = '' def __init__(self, data=None, err_data=None, qx_data=None, qy_data=None, q_data=None, mask=None, dqx_data=None, dqy_data=None, xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, x_bins=None, y_bins=None): self.data = np.asarray(data) self.qx_data = np.asarray(qx_data) self.qy_data = np.asarray(qy_data) self.q_data = np.asarray(q_data) if mask is not None: self.mask = np.asarray(mask) else: self.mask = np.ones(self.data.shape, dtype=bool) if err_data is not None: self.err_data = np.asarray(err_data) if dqx_data is not None: self.dqx_data = np.asarray(dqx_data) if dqy_data is not None: self.dqy_data = np.asarray(dqy_data) # plot limits self.xmin = xmin self.xmax = xmax self.ymin = ymin self.ymax = ymax self.zmin = zmin self.zmax = zmax self.y_bins = x_bins if x_bins else [] self.x_bins = y_bins if y_bins else [] def xaxis(self, label, unit): """ set the x axis label and unit """ self._xaxis = label self._xunit = unit def yaxis(self, label, unit): """ set the y axis label and unit """ self._yaxis = label self._yunit = unit def zaxis(self, label, unit): """ set the z axis label and unit """ self._zaxis = label self._zunit = unit class Vector(object): """ Vector class to hold multi-dimensional objects """ # x component x = None # y component y = None # z component z = None def __init__(self, x=None, y=None, z=None): """ Initialization. Components that are not set a set to None by default. :param x: x component :param y: y component :param z: z component """ self.x = x self.y = y self.z = z def __str__(self): msg = "x = %s\ty = %s\tz = %s" % (str(self.x), str(self.y), str(self.z)) return msg class Detector(object): """ Class to hold detector information """ # Name of the instrument [string] name = None # Sample to detector distance [float] [mm] distance = None distance_unit = 'mm' # Offset of this detector position in X, Y, # (and Z if necessary) [Vector] [mm] offset = None offset_unit = 'm' # Orientation (rotation) of this detector in roll, # pitch, and yaw [Vector] [degrees] orientation = None orientation_unit = 'degree' # Center of the beam on the detector in X and Y # (and Z if necessary) [Vector] [mm] beam_center = None beam_center_unit = 'mm' # Pixel size in X, Y, (and Z if necessary) [Vector] [mm] pixel_size = None pixel_size_unit = 'mm' # Slit length of the instrument for this detector.[float] [mm] slit_length = None slit_length_unit = 'mm' def __init__(self): """ Initialize class attribute that are objects... """ self.offset = Vector() self.orientation = Vector() self.beam_center = Vector() self.pixel_size = Vector() def __str__(self): _str = "Detector:\n" _str += " Name: %s\n" % self.name _str += " Distance: %s [%s]\n" % \ (str(self.distance), str(self.distance_unit)) _str += " Offset: %s [%s]\n" % \ (str(self.offset), str(self.offset_unit)) _str += " Orientation: %s [%s]\n" % \ (str(self.orientation), str(self.orientation_unit)) _str += " Beam center: %s [%s]\n" % \ (str(self.beam_center), str(self.beam_center_unit)) _str += " Pixel size: %s [%s]\n" % \ (str(self.pixel_size), str(self.pixel_size_unit)) _str += " Slit length: %s [%s]\n" % \ (str(self.slit_length), str(self.slit_length_unit)) return _str class Aperture(object): # Name name = None # Type type = None # Size name size_name = None # Aperture size [Vector] size = None size_unit = 'mm' # Aperture distance [float] distance = None distance_unit = 'mm' def __init__(self): self.size = Vector() class Collimation(object): """ Class to hold collimation information """ # Name name = None # Length [float] [mm] length = None length_unit = 'mm' # Aperture aperture = None def __init__(self): self.aperture = [] def __str__(self): _str = "Collimation:\n" _str += " Length: %s [%s]\n" % \ (str(self.length), str(self.length_unit)) for item in self.aperture: _str += " Aperture size:%s [%s]\n" % \ (str(item.size), str(item.size_unit)) _str += " Aperture_dist:%s [%s]\n" % \ (str(item.distance), str(item.distance_unit)) return _str class Source(object): """ Class to hold source information """ # Name name = None # Generic radiation type (Type and probe give more specific info) [string] radiation = None # Type and probe are only written to by the NXcanSAS reader # Specific radiation type (Synchotron X-ray, Reactor neutron, etc) [string] type = None # Radiation probe (generic probe such as neutron, x-ray, muon, etc) [string] probe = None # Beam size name beam_size_name = None # Beam size [Vector] [mm] beam_size = None beam_size_unit = 'mm' # Beam shape [string] beam_shape = None # Wavelength [float] [Angstrom] wavelength = None wavelength_unit = 'A' # Minimum wavelength [float] [Angstrom] wavelength_min = None wavelength_min_unit = 'nm' # Maximum wavelength [float] [Angstrom] wavelength_max = None wavelength_max_unit = 'nm' # Wavelength spread [float] [Angstrom] wavelength_spread = None wavelength_spread_unit = 'percent' def __init__(self): self.beam_size = Vector() def __str__(self): _str = "Source:\n" radiation = self.radiation if self.radiation is None and self.type and self.probe: radiation = self.type + " " + self.probe _str += " Radiation: %s\n" % str(radiation) _str += " Shape: %s\n" % str(self.beam_shape) _str += " Wavelength: %s [%s]\n" % \ (str(self.wavelength), str(self.wavelength_unit)) _str += " Waveln_min: %s [%s]\n" % \ (str(self.wavelength_min), str(self.wavelength_min_unit)) _str += " Waveln_max: %s [%s]\n" % \ (str(self.wavelength_max), str(self.wavelength_max_unit)) _str += " Waveln_spread:%s [%s]\n" % \ (str(self.wavelength_spread), str(self.wavelength_spread_unit)) _str += " Beam_size: %s [%s]\n" % \ (str(self.beam_size), str(self.beam_size_unit)) return _str """ Definitions of radiation types """ NEUTRON = 'neutron' XRAY = 'x-ray' MUON = 'muon' ELECTRON = 'electron' class Sample(object): """ Class to hold the sample description """ # Short name for sample name = '' # ID ID = '' # Thickness [float] [mm] thickness = None thickness_unit = 'mm' # Transmission [float] [fraction] transmission = None # Temperature [float] [No Default] temperature = None temperature_unit = None # Position [Vector] [mm] position = None position_unit = 'mm' # Orientation [Vector] [degrees] orientation = None orientation_unit = 'degree' # Details details = None # SESANS zacceptance zacceptance = (0,"") yacceptance = (0,"") def __init__(self): self.position = Vector() self.orientation = Vector() self.details = [] def __str__(self): _str = "Sample:\n" _str += " ID: %s\n" % str(self.ID) _str += " Transmission: %s\n" % str(self.transmission) _str += " Thickness: %s [%s]\n" % \ (str(self.thickness), str(self.thickness_unit)) _str += " Temperature: %s [%s]\n" % \ (str(self.temperature), str(self.temperature_unit)) _str += " Position: %s [%s]\n" % \ (str(self.position), str(self.position_unit)) _str += " Orientation: %s [%s]\n" % \ (str(self.orientation), str(self.orientation_unit)) _str += " Details:\n" for item in self.details: _str += " %s\n" % item return _str class Process(object): """ Class that holds information about the processes performed on the data. """ name = '' date = '' description = '' term = None notes = None def __init__(self): self.term = [] self.notes = [] def is_empty(self): """ Return True if the object is empty """ return (len(self.name) == 0 and len(self.date) == 0 and len(self.description) == 0 and len(self.term) == 0 and len(self.notes) == 0) def single_line_desc(self): """ Return a single line string representing the process """ return "%s %s %s" % (self.name, self.date, self.description) def __str__(self): _str = "Process:\n" _str += " Name: %s\n" % self.name _str += " Date: %s\n" % self.date _str += " Description: %s\n" % self.description for item in self.term: _str += " Term: %s\n" % item for item in self.notes: _str += " Note: %s\n" % item return _str class TransmissionSpectrum(object): """ Class that holds information about transmission spectrum for white beams and spallation sources. """ name = '' timestamp = '' # Wavelength (float) [A] wavelength = None wavelength_unit = 'A' # Transmission (float) [unit less] transmission = None transmission_unit = '' # Transmission Deviation (float) [unit less] transmission_deviation = None transmission_deviation_unit = '' def __init__(self): self.wavelength = [] self.transmission = [] self.transmission_deviation = [] def __str__(self): _str = "Transmission Spectrum:\n" _str += " Name: \t{0}\n".format(self.name) _str += " Timestamp: \t{0}\n".format(self.timestamp) _str += " Wavelength unit: \t{0}\n".format(self.wavelength_unit) _str += " Transmission unit:\t{0}\n".format(self.transmission_unit) _str += " Trans. Dev. unit: \t{0}\n".format( self.transmission_deviation_unit) length_list = [len(self.wavelength), len(self.transmission), len(self.transmission_deviation)] _str += " Number of Pts: \t{0}\n".format(max(length_list)) return _str class DataInfo(object): """ Class to hold the data read from a file. It includes four blocks of data for the instrument description, the sample description, the data itself and any other meta data. """ # Title title = '' # Run number run = None # Run name run_name = None # File name filename = '' # Notes notes = None # Processes (Action on the data) process = None # Instrument name instrument = '' # Detector information detector = None # Sample information sample = None # Source information source = None # Collimation information collimation = None # Transmission Spectrum INfo trans_spectrum = None # Additional meta-data meta_data = None # Loading errors errors = None # SESANS data check isSesans = None def __init__(self): """ Initialization """ # Title self.title = '' # Run number self.run = [] self.run_name = {} # File name self.filename = '' # Notes self.notes = [] # Processes (Action on the data) self.process = [] # Instrument name self.instrument = '' # Detector information self.detector = [] # Sample information self.sample = Sample() # Source information self.source = Source() # Collimation information self.collimation = [] # Transmission Spectrum self.trans_spectrum = [] # Additional meta-data self.meta_data = {} # Loading errors self.errors = [] # SESANS data check self.isSesans = False def append_empty_process(self): """ """ self.process.append(Process()) def add_notes(self, message=""): """ Add notes to datainfo """ self.notes.append(message) def __str__(self): """ Nice printout """ _str = f"File: {self.filename}\n" _str += f"Title: {self.title}\n" _str += f"Run: {self.run}\n" _str += f"SESANS: {self.isSesans}\n" _str += f"Instrument: {self.instrument}\n" _str += f"{str(self.sample)}\n" _str += f"{str(self.source)}\n" for item in self.detector: _str += f"{str(item)}\n" for item in self.collimation: _str += f"{str(item)}\n" for item in self.process: _str += f"{str(item)}\n" for item in self.notes: _str += f"{str(item)}\n" for item in self.trans_spectrum: _str += f"{str(item)}\n" return _str # Private method to perform operation. Not implemented for DataInfo, # but should be implemented for each data class inherited from DataInfo # that holds actual data (ex.: Data1D) def _perform_operation(self, other, operation): """ Private method to perform operation. Not implemented for DataInfo, but should be implemented for each data class inherited from DataInfo that holds actual data (ex.: Data1D) """ return NotImplemented def _perform_union(self, other): """ Private method to perform union operation. Not implemented for DataInfo, but should be implemented for each data class inherited from DataInfo that holds actual data (ex.: Data1D) """ return NotImplemented def __add__(self, other): """ Add two data sets :param other: data set to add to the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return a + b return self._perform_operation(other, operation) def __radd__(self, other): """ Add two data sets :param other: data set to add to the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return b + a return self._perform_operation(other, operation) def __sub__(self, other): """ Subtract two data sets :param other: data set to subtract from the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return a - b return self._perform_operation(other, operation) def __rsub__(self, other): """ Subtract two data sets :param other: data set to subtract from the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return b - a return self._perform_operation(other, operation) def __mul__(self, other): """ Multiply two data sets :param other: data set to subtract from the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return a * b return self._perform_operation(other, operation) def __rmul__(self, other): """ Multiply two data sets :param other: data set to subtract from the current one :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return b * a return self._perform_operation(other, operation) def __truediv__(self, other): """ Divided a data set by another :param other: data set that the current one is divided by :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return a/b return self._perform_operation(other, operation) __div__ = __truediv__ def __rtruediv__(self, other): """ Divided a data set by another :param other: data set that the current one is divided by :return: new data set :raise ValueError: raised when two data sets are incompatible """ def operation(a, b): return b/a return self._perform_operation(other, operation) __rdiv__ = __rtruediv__ def __or__(self, other): """ Union a data set with another :param other: data set to be unified :return: new data set :raise ValueError: raised when two data sets are incompatible """ return self._perform_union(other) def __ror__(self, other): """ Union a data set with another :param other: data set to be unified :return: new data set :raise ValueError: raised when two data sets are incompatible """ return self._perform_union(other) class Data1D(plottable_1D, DataInfo): """ 1D data class """ def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): DataInfo.__init__(self) plottable_1D.__init__(self, x, y, dx, dy, None, None, lam, dlam) self.isSesans = isSesans try: if self.isSesans: # the data is SESANS self.x_unit = 'A' self.y_unit = 'pol' elif not self.isSesans: # the data is SANS self.x_unit = '1/A' self.y_unit = '1/cm' except Exception: # the data is not recognized, notifying user raise TypeError('Check documentation for supported 1D data formats') def __str__(self): """ Nice printout """ _str = "%s\n" % DataInfo.__str__(self) _str += "Data:\n" _str += " Type: %s\n" % self.__class__.__name__ _str += " X-axis: %s\t[%s]\n" % (self._xaxis, self._xunit) _str += " Y-axis: %s\t[%s]\n" % (self._yaxis, self._yunit) _str += " Length: %g\n" % len(self.x) return _str def is_slit_smeared(self): """ Check whether the data has slit smearing information :return: True is slit smearing info is present, False otherwise """ def _check(v): return ((v.__class__ == list or v.__class__ == np.ndarray) and len(v) > 0 and min(v) > 0) return _check(self.dxl) or _check(self.dxw) def clone_without_data(self, length=0, clone=None): """ Clone the current object, without copying the data (which will be filled out by a subsequent operation). The data arrays will be initialized to zero. :param length: length of the data array to be initialized :param clone: if provided, the data will be copied to clone """ from copy import deepcopy if clone is None or not issubclass(clone.__class__, Data1D): x = np.zeros(length) dx = np.zeros(length) y = np.zeros(length) dy = np.zeros(length) lam = np.zeros(length) dlam = np.zeros(length) clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam) clone.title = self.title clone.run = self.run clone.filename = self.filename clone.instrument = self.instrument clone.notes = deepcopy(self.notes) clone.process = deepcopy(self.process) clone.detector = deepcopy(self.detector) clone.sample = deepcopy(self.sample) clone.source = deepcopy(self.source) clone.collimation = deepcopy(self.collimation) clone.trans_spectrum = deepcopy(self.trans_spectrum) clone.meta_data = deepcopy(self.meta_data) clone.errors = deepcopy(self.errors) return clone def copy_from_datainfo(self, data1d): """ copy values of Data1D of type DataLaoder.Data_info """ self.x = copy.deepcopy(data1d.x) self.y = copy.deepcopy(data1d.y) self.dy = copy.deepcopy(data1d.dy) if hasattr(data1d, "dx"): self.dx = copy.deepcopy(data1d.dx) if hasattr(data1d, "dxl"): self.dxl = copy.deepcopy(data1d.dxl) if hasattr(data1d, "dxw"): self.dxw = copy.deepcopy(data1d.dxw) self.xaxis(data1d._xaxis, data1d._xunit) self.yaxis(data1d._yaxis, data1d._yunit) self.title = data1d.title def _validity_check(self, other): """ Checks that the data lengths are compatible. Checks that the x vectors are compatible. Returns errors vectors equal to original errors vectors if they were present or vectors of zeros when none was found. :param other: other data set for operation :return: dy for self, dy for other [numpy arrays] :raise ValueError: when lengths are not compatible """ dy_other = None if isinstance(other, Data1D): # Check that data lengths are the same if len(self.x) != len(other.x) or len(self.y) != len(other.y): msg = "Unable to perform operation: data length are not equal" raise ValueError(msg) # Here we could also extrapolate between data points TOLERANCE = 0.01 for i in range(len(self.x)): if fabs(self.x[i] - other.x[i]) > self.x[i]*TOLERANCE: msg = "Incompatible data sets: x-values do not match" raise ValueError(msg) # Check that the other data set has errors, otherwise # create zero vector dy_other = other.dy if other.dy is None or (len(other.dy) != len(other.y)): dy_other = np.zeros(len(other.y)) # Check that we have errors, otherwise create zero vector dy = self.dy if self.dy is None or (len(self.dy) != len(self.y)): dy = np.zeros(len(self.y)) return dy, dy_other def _perform_operation(self, other, operation): """ """ # First, check the data compatibility dy, dy_other = self._validity_check(other) result = self.clone_without_data(len(self.x)) if self.dxw is None: result.dxw = None else: result.dxw = np.zeros(len(self.x)) if self.dxl is None: result.dxl = None else: result.dxl = np.zeros(len(self.x)) for i in range(len(self.x)): result.x[i] = self.x[i] if self.dx is not None and len(self.x) == len(self.dx): result.dx[i] = self.dx[i] if self.dxw is not None and len(self.x) == len(self.dxw): result.dxw[i] = self.dxw[i] if self.dxl is not None and len(self.x) == len(self.dxl): result.dxl[i] = self.dxl[i] a = Uncertainty(self.y[i], dy[i]**2) if isinstance(other, Data1D): b = Uncertainty(other.y[i], dy_other[i]**2) if other.dx is not None: result.dx[i] *= self.dx[i] result.dx[i] += (other.dx[i]**2) result.dx[i] /= 2 result.dx[i] = math.sqrt(result.dx[i]) if result.dxl is not None and other.dxl is not None: result.dxl[i] *= self.dxl[i] result.dxl[i] += (other.dxl[i]**2) result.dxl[i] /= 2 result.dxl[i] = math.sqrt(result.dxl[i]) else: b = other output = operation(a, b) result.y[i] = output.x result.dy[i] = math.sqrt(math.fabs(output.variance)) return result def _validity_check_union(self, other): """ Checks that the data lengths are compatible. Checks that the x vectors are compatible. Returns errors vectors equal to original errors vectors if they were present or vectors of zeros when none was found. :param other: other data set for operation :return: bool :raise ValueError: when data types are not compatible """ if not isinstance(other, Data1D): msg = "Unable to perform operation: different types of data set" raise ValueError(msg) return True def _perform_union(self, other): """ """ # First, check the data compatibility self._validity_check_union(other) result = self.clone_without_data(len(self.x) + len(other.x)) if self.dy is None or other.dy is None: result.dy = None else: result.dy = np.zeros(len(self.x) + len(other.x)) if self.dx is None or other.dx is None: result.dx = None else: result.dx = np.zeros(len(self.x) + len(other.x)) if self.dxw is None or other.dxw is None: result.dxw = None else: result.dxw = np.zeros(len(self.x) + len(other.x)) if self.dxl is None or other.dxl is None: result.dxl = None else: result.dxl = np.zeros(len(self.x) + len(other.x)) result.x = np.append(self.x, other.x) # argsorting ind = np.argsort(result.x) result.x = result.x[ind] result.y = np.append(self.y, other.y) result.y = result.y[ind] if result.dy is not None: result.dy = np.append(self.dy, other.dy) result.dy = result.dy[ind] if result.dx is not None: result.dx = np.append(self.dx, other.dx) result.dx = result.dx[ind] if result.dxw is not None: result.dxw = np.append(self.dxw, other.dxw) result.dxw = result.dxw[ind] if result.dxl is not None: result.dxl = np.append(self.dxl, other.dxl) result.dxl = result.dxl[ind] return result class Data2D(plottable_2D, DataInfo): """ 2D data class """ # Units for Q-values Q_unit = '1/A' # Units for I(Q) values I_unit = '1/cm' # No 2D SESANS data as of yet. Always set it to False isSesans = False def __init__(self, data=None, err_data=None, qx_data=None, qy_data=None, q_data=None, mask=None, dqx_data=None, dqy_data=None, xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None): DataInfo.__init__(self) plottable_2D.__init__(self, data=data, err_data=err_data, qx_data=qx_data, qy_data=qy_data, dqx_data=dqx_data, dqy_data=dqy_data, q_data=q_data, mask=mask, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax) if len(self.detector) > 0: raise RuntimeError("Data2D: Detector bank already filled at init") def __str__(self): _str = "%s\n" % DataInfo.__str__(self) _str += "Data:\n" _str += " Type: %s\n" % self.__class__.__name__ _str += " X-axis: %s\t[%s]\n" % (self._xaxis, self._xunit) _str += " Y-axis: %s\t[%s]\n" % (self._yaxis, self._yunit) _str += " Z-axis: %s\t[%s]\n" % (self._zaxis, self._zunit) _str += " Length: %g \n" % (len(self.data)) _str += " Shape: (%d, %d)\n" % (len(self.y_bins), len(self.x_bins)) return _str def clone_without_data(self, length=0, clone=None): """ Clone the current object, without copying the data (which will be filled out by a subsequent operation). The data arrays will be initialized to zero. :param length: length of the data array to be initialized :param clone: if provided, the data will be copied to clone """ from copy import deepcopy if clone is None or not issubclass(clone.__class__, Data2D): data = np.zeros(length) err_data = np.zeros(length) qx_data = np.zeros(length) qy_data = np.zeros(length) q_data = np.zeros(length) mask = np.zeros(length) clone = Data2D(data=data, err_data=err_data, qx_data=qx_data, qy_data=qy_data, q_data=q_data, mask=mask) clone._xaxis = self._xaxis clone._yaxis = self._yaxis clone._zaxis = self._zaxis clone._xunit = self._xunit clone._yunit = self._yunit clone._zunit = self._zunit clone.x_bins = self.x_bins clone.y_bins = self.y_bins clone.title = self.title clone.run = self.run clone.filename = self.filename clone.instrument = self.instrument clone.notes = deepcopy(self.notes) clone.process = deepcopy(self.process) clone.detector = deepcopy(self.detector) clone.sample = deepcopy(self.sample) clone.source = deepcopy(self.source) clone.collimation = deepcopy(self.collimation) clone.trans_spectrum = deepcopy(self.trans_spectrum) clone.meta_data = deepcopy(self.meta_data) clone.errors = deepcopy(self.errors) return clone def copy_from_datainfo(self, data2d): """ copy value of Data2D of type DataLoader.data_info """ self.data = copy.deepcopy(data2d.data) self.qx_data = copy.deepcopy(data2d.qx_data) self.qy_data = copy.deepcopy(data2d.qy_data) self.q_data = copy.deepcopy(data2d.q_data) self.mask = copy.deepcopy(data2d.mask) self.err_data = copy.deepcopy(data2d.err_data) self.x_bins = copy.deepcopy(data2d.x_bins) self.y_bins = copy.deepcopy(data2d.y_bins) if data2d.dqx_data is not None: self.dqx_data = copy.deepcopy(data2d.dqx_data) if data2d.dqy_data is not None: self.dqy_data = copy.deepcopy(data2d.dqy_data) self.xmin = data2d.xmin self.xmax = data2d.xmax self.ymin = data2d.ymin self.ymax = data2d.ymax if hasattr(data2d, "zmin"): self.zmin = data2d.zmin if hasattr(data2d, "zmax"): self.zmax = data2d.zmax self.xaxis(data2d._xaxis, data2d._xunit) self.yaxis(data2d._yaxis, data2d._yunit) self.title = data2d.title def _validity_check(self, other): """ Checks that the data lengths are compatible. Checks that the x vectors are compatible. Returns errors vectors equal to original errors vectors if they were present or vectors of zeros when none was found. :param other: other data set for operation :return: dy for self, dy for other [numpy arrays] :raise ValueError: when lengths are not compatible """ err_other = None TOLERANCE = 0.01 msg_base = "Incompatible data sets: q-values do not match: " if isinstance(other, Data2D): # Check that data lengths are the same if (len(self.data) != len(other.data) or len(self.qx_data) != len(other.qx_data) or len(self.qy_data) != len(other.qy_data)): msg = "Unable to perform operation: data length are not equal" raise ValueError(msg) for ind in range(len(self.data)): if (fabs(self.qx_data[ind] - other.qx_data[ind]) > fabs(self.qx_data[ind])*TOLERANCE): msg = f"{msg_base}{self.qx_data[ind]} {other.qx_data[ind]}" raise ValueError(msg) if (fabs(self.qy_data[ind] - other.qy_data[ind]) > fabs(self.qy_data[ind])*TOLERANCE): msg = f"{msg_base}{self.qy_data[ind]} {other.qy_data[ind]}" raise ValueError(msg) # Check that the scales match err_other = other.err_data if (other.err_data is None or (len(other.err_data) != len(other.data))): err_other = np.zeros(len(other.data)) # Check that we have errors, otherwise create zero vector err = self.err_data if self.err_data is None or (len(self.err_data) != len(self.data)): err = np.zeros(len(other.data)) return err, err_other def _perform_operation(self, other, operation): """ Perform 2D operations between data sets :param other: other data set :param operation: function defining the operation """ # First, check the data compatibility dy, dy_other = self._validity_check(other) result = self.clone_without_data(np.size(self.data)) if self.dqx_data is None or self.dqy_data is None: result.dqx_data = None result.dqy_data = None else: result.dqx_data = np.zeros(len(self.data)) result.dqy_data = np.zeros(len(self.data)) for i in range(np.size(self.data)): result.data[i] = self.data[i] if (self.err_data is not None and np.size(self.data) == np.size(self.err_data)): result.err_data[i] = self.err_data[i] if self.dqx_data is not None: result.dqx_data[i] = self.dqx_data[i] if self.dqy_data is not None: result.dqy_data[i] = self.dqy_data[i] result.qx_data[i] = self.qx_data[i] result.qy_data[i] = self.qy_data[i] result.q_data[i] = self.q_data[i] result.mask[i] = self.mask[i] a = Uncertainty(self.data[i], dy[i]**2) if isinstance(other, Data2D): b = Uncertainty(other.data[i], dy_other[i]**2) if other.dqx_data is not None and result.dqx_data is not None: result.dqx_data[i] *= self.dqx_data[i] result.dqx_data[i] += (other.dqx_data[i]**2) result.dqx_data[i] /= 2 result.dqx_data[i] = math.sqrt(result.dqx_data[i]) if other.dqy_data is not None and result.dqy_data is not None: result.dqy_data[i] *= self.dqy_data[i] result.dqy_data[i] += (other.dqy_data[i]**2) result.dqy_data[i] /= 2 result.dqy_data[i] = math.sqrt(result.dqy_data[i]) else: b = other output = operation(a, b) result.data[i] = output.x result.err_data[i] = math.sqrt(math.fabs(output.variance)) return result @staticmethod def _validity_check_union(self, other): """ Checks that the data lengths are compatible. Checks that the x vectors are compatible. Returns errors vectors equal to original errors vectors if they were present or vectors of zeros when none was found. :param other: other data set for operation :return: bool :raise ValueError: when data types are not compatible """ if not isinstance(other, Data2D): msg = "Unable to perform operation: different types of data set" raise ValueError(msg) return True def _perform_union(self, other): """ Perform 2D operations between data sets :param other: other data set :param operation: function defining the operation """ # First, check the data compatibility self._validity_check_union(other) result = self.clone_without_data(np.size(self.data) + np.size(other.data)) result.xmin = self.xmin result.xmax = self.xmax result.ymin = self.ymin result.ymax = self.ymax if (self.dqx_data is None or self.dqy_data is None or other.dqx_data is None or other.dqy_data is None): result.dqx_data = None result.dqy_data = None else: result.dqx_data = np.zeros(len(self.data) + np.size(other.data)) result.dqy_data = np.zeros(len(self.data) + np.size(other.data)) result.data = np.append(self.data, other.data) result.qx_data = np.append(self.qx_data, other.qx_data) result.qy_data = np.append(self.qy_data, other.qy_data) result.q_data = np.append(self.q_data, other.q_data) result.mask = np.append(self.mask, other.mask) if result.err_data is not None: result.err_data = np.append(self.err_data, other.err_data) if self.dqx_data is not None: result.dqx_data = np.append(self.dqx_data, other.dqx_data) if self.dqy_data is not None: result.dqy_data = np.append(self.dqy_data, other.dqy_data) return result def combine_data_info_with_plottable(data, datainfo): """ A function that combines the DataInfo data in self.current_datainto with a plottable_1D or 2D data object. :param data: A plottable_1D or plottable_2D data object :param datainfo: A DataInfo object to be combined with the plottable :return: A fully specified Data1D or Data2D object """ if isinstance(data, plottable_1D): final_dataset = Data1D(data.x, data.y, isSesans=datainfo.isSesans) final_dataset.dx = data.dx final_dataset.dy = data.dy final_dataset.dxl = data.dxl final_dataset.dxw = data.dxw final_dataset.x_unit = data._xunit final_dataset.y_unit = data._yunit final_dataset.xaxis(data._xaxis, data._xunit) final_dataset.yaxis(data._yaxis, data._yunit) elif isinstance(data, plottable_2D): final_dataset = Data2D(data.data, data.err_data, data.qx_data, data.qy_data, data.q_data, data.mask, data.dqx_data, data.dqy_data) final_dataset.xaxis(data._xaxis, data._xunit) final_dataset.yaxis(data._yaxis, data._yunit) final_dataset.zaxis(data._zaxis, data._zunit) final_dataset.x_bins = data.x_bins final_dataset.y_bins = data.y_bins else: return_string = ("Should Never Happen: _combine_data_info_with_plottabl" "e input is not a plottable1d or plottable2d data " "object") return return_string if hasattr(data, "xmax"): final_dataset.xmax = data.xmax if hasattr(data, "ymax"): final_dataset.ymax = data.ymax if hasattr(data, "xmin"): final_dataset.xmin = data.xmin if hasattr(data, "ymin"): final_dataset.ymin = data.ymin final_dataset.isSesans = datainfo.isSesans final_dataset.title = datainfo.title final_dataset.run = datainfo.run final_dataset.run_name = datainfo.run_name final_dataset.filename = datainfo.filename final_dataset.notes = datainfo.notes final_dataset.process = datainfo.process final_dataset.instrument = datainfo.instrument final_dataset.detector = datainfo.detector final_dataset.sample = datainfo.sample final_dataset.source = datainfo.source final_dataset.collimation = datainfo.collimation final_dataset.trans_spectrum = datainfo.trans_spectrum final_dataset.meta_data = datainfo.meta_data final_dataset.errors = datainfo.errors return final_dataset sasdata-0.8.1/sasdata/dataloader/filereader.py000066400000000000000000000511401427502211700213360ustar00rootroot00000000000000""" This is the base file reader class most file readers should inherit from. All generic functionality required for a file loader/reader is built into this class """ import os import codecs import logging from abc import abstractmethod from typing import List, Union import numpy as np from sasdata.data_util.loader_exceptions import NoKnownLoaderException, FileContentsException,\ DataReaderException from sasdata.dataloader.data_info import Data1D, Data2D, DataInfo, plottable_1D, plottable_2D,\ combine_data_info_with_plottable from sasdata.data_util.nxsunit import Converter logger = logging.getLogger(__name__) def decode(s): # Attempt to decode files using common encodings # *NB* windows-1252, aka cp1252, overlaps with most ASCII-style encodings for codec in ['utf-8', 'windows-1252']: try: return codecs.decode(s, codec) if isinstance(s, bytes) else s except (ValueError, UnicodeError): # If the specific codec fails, try the next one. pass except Exception as e: logger.warning(e) # Give warning if unable to decode the item using the codecs logger.warning(f"Unable to decode {s}") # Data 1D fields for iterative purposes FIELDS_1D = 'x', 'y', 'dx', 'dy', 'dxl', 'dxw' # Data 2D fields for iterative purposes FIELDS_2D = 'data', 'qx_data', 'qy_data', 'q_data', 'err_data', 'dqx_data', 'dqy_data', 'mask' DEPRECATION_MESSAGE = ("\rThe extension of this file suggests the data set migh" "t not be fully reduced. Support for the reader associat" "ed with this file type has been removed. An attempt to " "load the file was made, but, should it be successful, " "SasView cannot guarantee the accuracy of the data.") class FileReader: # String to describe the type of data this reader can load type_name = "ASCII" # Wildcards to display type = ["Text files (*.txt|*.TXT)"] # List of allowed extensions ext = ['.txt'] # Deprecated extensions deprecated_extensions = ['.asc'] # Bypass extension check and try to load anyway allow_all = False # Able to import the unit converter has_converter = True def __init__(self): # List of Data1D and Data2D objects to be sent back to data_loader self.output = [] # Current plottable_(1D/2D) object being loaded in self.current_dataset = None # Current DataInfo object being loaded in self.current_datainfo = None # File path sent to reader self.filepath = None # Open file handle self.f_open = None def read(self, filepath: str) -> List[Union[Data1D, Data2D]]: """ Basic file reader :param filepath: The full or relative path to a file to be loaded """ self.filepath = filepath if os.path.isfile(filepath): basename, extension = os.path.splitext(os.path.basename(filepath)) self.extension = extension.lower() # If the file type is not allowed, return nothing if self.extension in self.ext or self.allow_all: # Try to load the file, but raise an error if unable to. try: with open(filepath, 'rb') as self.f_open: self.get_file_contents() except DataReaderException as e: self.handle_error_message(str(e)) except FileContentsException as e: raise except OSError as e: # If the file cannot be opened msg = "Unable to open file: {}\n".format(filepath) msg += str(e) self.handle_error_message(msg) except Exception as e: self.handle_error_message(str(e)) finally: if any(filepath.lower().endswith(ext) for ext in self.deprecated_extensions): self.handle_error_message(DEPRECATION_MESSAGE) if len(self.output) > 0: # Sort the data that's been loaded self.convert_data_units() self.sort_data() else: msg = "Unable to find file at: {}\n".format(filepath) msg += "Please check your file path and try again." self.handle_error_message(msg) # Return a list of parsed entries that data_loader can manage final_data = self.output self.reset_state() return final_data def reset_state(self): """ Resets the class state to a base case when loading a new data file so previous data files do not appear a second time """ self.current_datainfo = None self.current_dataset = None self.filepath = None self.ind = None self.output = [] def nextline(self) -> str: """ Returns the next line in the file as a string. """ #return self.f_open.readline() return decode(self.f_open.readline()) def nextlines(self) -> str: """ Returns the next line in the file as a string. """ for line in self.f_open: #yield line yield decode(line) def readall(self) -> str: """ Returns the entire file as a string. """ return decode(self.f_open.read()) def handle_error_message(self, msg: str): """ Generic error handler to add an error to the current datainfo to propagate the error up the error chain. :param msg: Error message """ if len(self.output) > 0: self.output[-1].errors.append(msg) elif isinstance(self.current_datainfo, DataInfo): self.current_datainfo.errors.append(msg) else: logger.warning(msg) raise NoKnownLoaderException(msg) def send_to_output(self): """ Helper that automatically combines the info and set and then appends it to output """ data_obj = combine_data_info_with_plottable(self.current_dataset, self.current_datainfo) self.output.append(data_obj) def sort_data(self): """ Sort 1D data along the X axis for consistency """ for data in self.output: if isinstance(data, Data1D): # Normalize the units for data.x_unit = self.format_unit(data.x_unit) data._xunit = data.x_unit data.y_unit = self.format_unit(data.y_unit) data._yunit = data.y_unit # Sort data by increasing x and remove 1st point ind = np.lexsort((data.y, data.x)) data.x = self._reorder_1d_array(data.x, ind) data.y = self._reorder_1d_array(data.y, ind) if data.dx is not None: if len(data.dx) == 0: data.dx = None continue data.dx = self._reorder_1d_array(data.dx, ind) if data.dxl is not None: data.dxl = self._reorder_1d_array(data.dxl, ind) if data.dxw is not None: data.dxw = self._reorder_1d_array(data.dxw, ind) if data.dy is not None: if len(data.dy) == 0: data.dy = None continue data.dy = self._reorder_1d_array(data.dy, ind) if data.lam is not None: data.lam = self._reorder_1d_array(data.lam, ind) if data.dlam is not None: data.dlam = self._reorder_1d_array(data.dlam, ind) data = self._remove_nans_in_data(data) if len(data.x) > 0: data.xmin = np.min(data.x) data.xmax = np.max(data.x) data.ymin = np.min(data.y) data.ymax = np.max(data.y) elif isinstance(data, Data2D): # Normalize the units for data.Q_unit = self.format_unit(data.Q_unit) data.I_unit = self.format_unit(data.I_unit) data._xunit = data.Q_unit data._yunit = data.Q_unit data._zunit = data.I_unit data.data = data.data.astype(np.float64) data.qx_data = data.qx_data.astype(np.float64) data.xmin = np.min(data.qx_data) data.xmax = np.max(data.qx_data) data.qy_data = data.qy_data.astype(np.float64) data.ymin = np.min(data.qy_data) data.ymax = np.max(data.qy_data) data.q_data = np.sqrt(data.qx_data * data.qx_data + data.qy_data * data.qy_data) if data.err_data is not None: data.err_data = data.err_data.astype(np.float64) if data.dqx_data is not None: data.dqx_data = data.dqx_data.astype(np.float64) if data.dqy_data is not None: data.dqy_data = data.dqy_data.astype(np.float64) if data.mask is not None: data.mask = data.mask.astype(dtype=bool) # If all mask elements are False, give a warning to the user if not data.mask.any(): error = "The entire dataset is masked and may not " error += "produce usable fits." data.errors.append(error) if len(data.data.shape) == 2: n_rows, n_cols = data.data.shape data.y_bins = data.qy_data[0::int(n_cols)] data.x_bins = data.qx_data[:int(n_cols)] data.data = data.data.flatten() data = self._remove_nans_in_data(data) if len(data.data) > 0: data.xmin = np.min(data.qx_data) data.xmax = np.max(data.qx_data) data.ymin = np.min(data.qy_data) data.ymax = np.max(data.qy_data) @staticmethod def _reorder_1d_array(array: np.array, ind: int) -> np.array: """ Reorders a 1D array based on the indices passed as ind :param array: Array to be reordered :param ind: Indices used to reorder array :return: reordered array """ array = np.asarray(array, dtype=np.float64) return array[ind] @staticmethod def _remove_nans_in_data(data: Union[Data1D, Data2D]) -> Union[Data1D, Data2D]: """ Remove data points where nan is loaded :param data: 1D or 2D data object :return: data with nan points removed """ if isinstance(data, Data1D): fields = FIELDS_1D elif isinstance(data, Data2D): fields = FIELDS_2D else: return data # Make array of good points - all others will be removed good = np.isfinite(getattr(data, fields[0])) for name in fields[1:]: array = getattr(data, name) if array is not None: # Update good points only if not already changed good &= np.isfinite(array) if not np.all(good): for name in fields: array = getattr(data, name) if array is not None: setattr(data, name, array[good]) return data @staticmethod def set_default_1d_units(data: Union[Data1D, Data2D]) -> Union[Data1D, Data2D]: """ Set the x and y axes to the default 1D units :param data: 1D data set :return: """ data.xaxis(r"\rm{Q}", '1/A') data.yaxis(r"\rm{Intensity}", "1/cm") return data @staticmethod def set_default_2d_units(data: Union[Data1D, Data2D]) -> Union[Data1D, Data2D]: """ Set the x and y axes to the default 2D units :param data: 2D data set :return: """ data.xaxis("\\rm{Q_{x}}", '1/A') data.yaxis("\\rm{Q_{y}}", '1/A') data.zaxis("\\rm{Intensity}", "1/cm") return data def convert_data_units(self, default_q_unit: str = "1/A"): """ Converts al; data to the sasview default of units of A^{-1} for Q and cm^{-1} for I. :param default_q_unit: The default Q unit used by Sasview """ convert_q = True new_output = [] for data in self.output: if data.isSesans: new_output.append(data) continue try: file_x_unit = data._xunit data_conv_x = Converter(file_x_unit) except KeyError: logger.info("Unrecognized Q units in data file. No data conversion attempted") convert_q = False try: if isinstance(data, Data1D): if convert_q: data.x = data_conv_x(data.x, units=default_q_unit) data._xunit = default_q_unit data.x_unit = default_q_unit if data.dx is not None: data.dx = data_conv_x(data.dx, units=default_q_unit) if data.dxl is not None: data.dxl = data_conv_x(data.dxl, units=default_q_unit) if data.dxw is not None: data.dxw = data_conv_x(data.dxw, units=default_q_unit) elif isinstance(data, Data2D): if convert_q: data.qx_data = data_conv_x(data.qx_data, units=default_q_unit) if data.dqx_data is not None: data.dqx_data = data_conv_x(data.dqx_data, units=default_q_unit) try: file_y_unit = data._yunit data_conv_y = Converter(file_y_unit) data.qy_data = data_conv_y(data.qy_data, units=default_q_unit) if data.dqy_data is not None: data.dqy_data = data_conv_y(data.dqy_data, units=default_q_unit) except KeyError: logger.info("Unrecognized Qy units in data file. No" " data conversion attempted") except KeyError: message = "Unable to convert Q units from {0} to 1/A." message.format(default_q_unit) data.errors.append(message) new_output.append(data) self.output = new_output def format_unit(self, unit: str = None) -> str: """ Format units a common way :param unit: :return: """ if unit: split = unit.split("/") if len(split) == 1: return unit elif split[0] == '1': return f"{split[1]}^{{-1}}" else: return f"{split[0]}*{split[1]}^{{-1}}" def set_all_to_none(self): """ Set all mutable values to None for error handling purposes """ self.current_dataset = None self.current_datainfo = None self.output = [] def data_cleanup(self): """ Clean up the data sets and refresh everything :return: None """ self.remove_empty_q_values() self.send_to_output() # Combine datasets with DataInfo self.current_datainfo = DataInfo() # Reset DataInfo def remove_empty_q_values(self): """ Remove any point where Q == 0 """ if isinstance(self.current_dataset, plottable_1D): # Booleans for resolutions has_error_dx = self.current_dataset.dx is not None has_error_dxl = self.current_dataset.dxl is not None has_error_dxw = self.current_dataset.dxw is not None has_error_dy = self.current_dataset.dy is not None # Create arrays of zeros for non-existent resolutions if has_error_dxw and not has_error_dxl: array_size = self.current_dataset.dxw.size - 1 self.current_dataset.dxl = np.append(self.current_dataset.dxl, np.zeros([array_size])) has_error_dxl = True elif has_error_dxl and not has_error_dxw: array_size = self.current_dataset.dxl.size - 1 self.current_dataset.dxw = np.append(self.current_dataset.dxw, np.zeros([array_size])) has_error_dxw = True elif not has_error_dxl and not has_error_dxw and not has_error_dx: array_size = self.current_dataset.x.size - 1 self.current_dataset.dx = np.append(self.current_dataset.dx, np.zeros([array_size])) has_error_dx = True if not has_error_dy: array_size = self.current_dataset.y.size - 1 self.current_dataset.dy = np.append(self.current_dataset.dy, np.zeros([array_size])) has_error_dy = True # Remove points where q = 0 x = self.current_dataset.x self.current_dataset.x = self.current_dataset.x[x != 0] self.current_dataset.y = self.current_dataset.y[x != 0] if has_error_dy: self.current_dataset.dy = self.current_dataset.dy[x != 0] if has_error_dx: self.current_dataset.dx = self.current_dataset.dx[x != 0] if has_error_dxl: self.current_dataset.dxl = self.current_dataset.dxl[x != 0] if has_error_dxw: self.current_dataset.dxw = self.current_dataset.dxw[x != 0] elif isinstance(self.current_dataset, plottable_2D): has_error_dqx = self.current_dataset.dqx_data is not None has_error_dqy = self.current_dataset.dqy_data is not None has_error_dy = self.current_dataset.err_data is not None has_mask = self.current_dataset.mask is not None x = self.current_dataset.qx_data self.current_dataset.data = self.current_dataset.data[x != 0] self.current_dataset.qx_data = self.current_dataset.qx_data[x != 0] self.current_dataset.qy_data = self.current_dataset.qy_data[x != 0] self.current_dataset.q_data = np.sqrt( np.square(self.current_dataset.qx_data) + np.square( self.current_dataset.qy_data)) if has_error_dy: self.current_dataset.err_data = self.current_dataset.err_data[ x != 0] if has_error_dqx: self.current_dataset.dqx_data = self.current_dataset.dqx_data[ x != 0] if has_error_dqy: self.current_dataset.dqy_data = self.current_dataset.dqy_data[ x != 0] if has_mask: self.current_dataset.mask = self.current_dataset.mask[x != 0] def reset_data_list(self, no_lines: int = 0): """ Reset the plottable_1D object """ # Initialize data sets with arrays the maximum possible size x = np.zeros(no_lines) y = np.zeros(no_lines) dx = np.zeros(no_lines) dy = np.zeros(no_lines) self.current_dataset = plottable_1D(x, y, dx, dy) @staticmethod def splitline(line: str) -> List[str]: """ Splits a line into pieces based on common delimiters :param line: A single line of text :return: list of values """ # Initial try for CSV (split on ,) toks = line.split(',') # Now try SCSV (split on ;) if len(toks) < 2: toks = line.split(';') # Now go for whitespace if len(toks) < 2: toks = line.split() return toks @abstractmethod def get_file_contents(self): """ Reader specific class to access the contents of the file All reader classes that inherit from FileReader must implement """ pass sasdata-0.8.1/sasdata/dataloader/loader.py000066400000000000000000000357241427502211700205140ustar00rootroot00000000000000""" File handler to support different file extensions. Uses reflectometer registry utility. The default readers are found in the 'readers' sub-module and registered by default at initialization time. To add a new default reader, one must register it in the register_readers method found in readers/__init__.py. A utility method (find_plugins) is available to inspect a directory (for instance, a user plug-in directory) and look for new readers/writers. """ ##################################################################### # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # See the license text in license.txt # copyright 2008, University of Tennessee ###################################################################### import os import sys import logging import time from zipfile import ZipFile from collections import defaultdict from types import ModuleType from typing import Optional, Union from sasdata.data_util.registry import ExtensionRegistry from sasdata.data_util.util import unique_preserve_order # Default readers are defined in the readers sub-module from . import readers from sasdata.data_util.loader_exceptions import NoKnownLoaderException, DefaultReaderException logger = logging.getLogger(__name__) class Registry(ExtensionRegistry): """ Registry class for file format extensions. Readers and writers are supported. """ def __init__(self): super().__init__() # Writers self.writers = defaultdict(list) # List of wildcards self.wildcards = ['All (*.*)|*.*'] # Creation time, for testing self._created = time.time() # Register default readers readers.read_associations(self) def load(self, path: str, ext: Optional[str] = None, debug: Optional[bool] = False, use_defaults: Optional[bool] = True): """ Call the loader for the file type of path. :param path: file path :param ext: explicit extension, to force the use of a particular reader :param debug: when True, print the traceback for each loader that fails :param use_defaults: Flag to use the default readers as a backup if the main reader fails or no reader exists Defaults to the ascii (multi-column), cansas XML, and cansas NeXuS readers if no reader was registered for the file's extension. """ import traceback # Gets set to a string if the file has an associated reader that fails try: data_list = super().load(path, ext=ext) if data_list: return data_list if ext: logger.debug(f"No data returned from '{path}' for format {ext}") else: logger.debug(f"No data returned from '{path}'") except Exception as e: logger.debug(traceback.print_exc()) if not use_defaults: raise # Use backup readers try: return self.load_using_generic_loaders(path) except (NoKnownLoaderException, DefaultReaderException) as e: logger.debug(traceback.print_exc()) # No known reader available. Give up and throw an error msg = f"{str(e)}\nUnknown data format: {path}.\nThe file is not a format that can be loaded by SasView.\n" logger.error(msg) raise except Exception as e: logger.debug(traceback.print_exc()) raise def load_using_generic_loaders(self, path: str) -> list: """ If the expected reader cannot load the file or no known loader exists, attempt to load the file using a few defaults readers :param path: file path :return: List of Data1D and Data2D objects """ module_list = readers.get_generic_readers() for module in module_list: reader = module.Reader() try: data_list = reader.read(path) if data_list: return data_list except Exception as e: # Cycle through all generic readers pass # Only throw exception if all generic readers fail raise NoKnownLoaderException(f"Generic readers failed to load {path}") def find_plugins(self, dir: str): """ Find readers in a given directory. This method can be used to inspect user plug-in directories to find new readers/writers. :param dir: directory to search into :return: number of readers found """ readers_found = 0 temp_path = os.path.abspath(dir) if not os.path.isdir(temp_path): temp_path = os.path.join(os.getcwd(), dir) if not os.path.isdir(temp_path): temp_path = os.path.join(os.path.dirname(__file__), dir) if not os.path.isdir(temp_path): temp_path = os.path.join(os.path.dirname(sys.path[0]), dir) dir = temp_path # Check whether the directory exists if not os.path.isdir(dir): msg = f"DataLoader could nt locate plugin folder. {dir} does not exist" logger.warning(msg) return readers_found for item in os.listdir(dir): full_path = os.path.join(dir, item) if os.path.isfile(full_path): # Process python files if item.endswith('.py'): toks = os.path.splitext(os.path.basename(item)) try: sys.path.insert(0, os.path.abspath(dir)) module = __import__(toks[0], globals(), locals()) if self._identify_plugin(module): readers_found += 1 except Exception as exc: msg = f"Loader: Error importing {item}\n {str(exc)}" logger.error(msg) # Process zip files elif item.endswith('.zip'): try: # Find the modules in the zip file zfile = ZipFile(item) nlist = zfile.namelist() sys.path.insert(0, item) for mfile in nlist: try: # Change OS path to python path fullname = mfile.replace('/', '.') fullname = os.path.splitext(fullname)[0] module = __import__(fullname, globals(), locals(), [""]) if self._identify_plugin(module): readers_found += 1 except Exception as exc: msg = f"Loader: Error importing {mfile}\n {str(exc)}" logger.error(msg) except Exception as exc: msg = f"Loader: Error importing {item}\n {str(exc)}" logger.error(msg) return readers_found def associate_file_type(self, ext: str, module: ModuleType) -> bool: """ Look into a module to find whether it contains a Reader class. If so, APPEND it to readers and (potentially) to the list of writers for the given extension :param ext: file extension [string] :param module: module object """ reader_found = False if hasattr(module, "Reader"): try: # Find supported extensions loader = module.Reader() if ext not in self.readers: self.readers[ext] = [] # Append the new reader to the list self.readers[ext].append(loader.read) reader_found = True # Keep track of wildcards type_name = module.__name__ if hasattr(loader, 'type_name'): type_name = loader.type_name wcard = f"{type_name} files (*{ext.lower()})|*{ext.lower()}" if wcard not in self.wildcards: self.wildcards.append(wcard) # Check whether writing is supported if hasattr(loader, 'write'): if ext not in self.writers: self.writers[ext] = [] # Append the new writer to the list self.writers[ext].append(loader.write) except Exception as exc: msg = f"Loader: Error accessing Reader in {module.__name__}\n {str(exc)}" logger.error(msg) return reader_found def associate_file_reader(self, file_extension, reader): """ Append a reader object to readers :param file_extension: file extension [string] :param reader: reader object """ reader_found = False try: # Find supported extensions if file_extension not in self.readers: self.readers[file_extension] = [] # Append the new reader to the list self.readers[file_extension].append(reader.read) reader_found = True # Keep track of wildcards if hasattr(reader, 'type_name'): type_name = reader.type_name wcard = f"{type_name} files (*{file_extension.lower()})|*{file_extension.lower()}" if wcard not in self.wildcards: self.wildcards.append(wcard) except Exception as exc: msg = f"Loader: Error accessing Reader in {reader.__name__}\n {str(exc)}" logger.error(msg) return reader_found def _identify_plugin(self, module: ModuleType): """ Look into a module to find whether it contains a Reader class. If so, add it to readers and (potentially) to the list of writers. :param module: module object :returns: True if successful """ reader_found = False if hasattr(module, "Reader"): try: # Find supported extensions reader = module.Reader() for ext in reader.ext: if ext not in self.readers: self.readers[ext] = [] # When finding a reader at run time, # treat this reader as the new default self.readers[ext].insert(0, reader.read) reader_found = True # Keep track of wildcards file_description = reader.type_name if hasattr(reader, 'type_name') else module.__name__ wcard = f"{file_description} files (*{ext.lower()})|*{ext.lower()}" if wcard not in self.wildcards: self.wildcards.append(wcard) # Check whether writing is supported if hasattr(reader, 'write'): for ext in reader.ext: if ext not in self.writers: self.writers[ext] = [] self.writers[ext].insert(0, reader.write) except Exception as exc: msg = f"Loader: Error accessing Reader in {module.__name__}\n {str(exc)}" logger.error(msg) return reader_found def lookup_writers(self, path): """ :return: the loader associated with the file type of path. :Raises ValueError: if file type is not known. """ # Find matching extensions extlist = [ext for ext in self.extensions() if path.endswith(ext)] # Sort matching extensions by decreasing order of length extlist.sort(key=len) # Combine loaders for matching extensions into one big list writers = [writer for ext in extlist for writer in self.writers[ext]] # Remove duplicates if they exist writers = unique_preserve_order(writers) # Raise an error if there are no matching extensions if len(writers) == 0: raise ValueError("Unknown file type for " + path) # All done return writers def save(self, path: str, data, format: Optional[str] = None): """ Call the writer for the file type of path. Raises ValueError if no writer is available. Raises KeyError if format is not available. May raise a writer-defined exception if writer fails. """ if format is None: writers = self.lookup_writers(path) else: writers = self.writers[format] for writing_function in writers: try: return writing_function(path, data) except Exception as exc: msg = f"Saving file {path} using the {type(writing_function).__name__} writer failed.\n {str(exc)}" logger.exception(msg) # give other loaders a chance to succeed class Loader: """ Utility class to use the Registry as a singleton. """ __registry = Registry() def associate_file_type(self, ext: str, module: ModuleType) -> bool: """ Look into a module to find whether it contains a Reader class. If so, append it to readers and (potentially) to the list of writers for the given extension :param ext: file extension [string] :param module: module object """ return self.__registry.associate_file_type(ext, module) def associate_file_reader(self, ext: str, loader) -> bool: """ Append a reader object to readers :param ext: file extension [string] :param module: reader object """ return self.__registry.associate_file_reader(ext, loader) def load(self, file: str, format: Optional[str] = None) -> Union[list, Exception]: """ Load a file :param file: file name (path) :param format: specified format to use (optional) :return: DataInfo object """ return self.__registry.load(file, format) def save(self, file: str, data, format: str) -> bool: """ Save a DataInfo object to file :param file: file name (path) :param data: DataInfo object :param format: format to write the data in """ return self.__registry.save(file, data, format) def _get_registry_creation_time(self) -> float: """ Internal method used to test the uniqueness of the registry object """ return self.__registry._created def find_plugins(self, directory: str) -> int: """ Find plugins in a given directory :param directory: directory to look into to find new readers/writers """ return self.__registry.find_plugins(directory) def get_wildcards(self): """ Return the list of wildcards """ return self.__registry.wildcards sasdata-0.8.1/sasdata/dataloader/readers/000077500000000000000000000000001427502211700203065ustar00rootroot00000000000000sasdata-0.8.1/sasdata/dataloader/readers/__init__.py000066400000000000000000000001651427502211700224210ustar00rootroot00000000000000# Method to associate extensions to default readers from .associations import read_associations, get_generic_readers sasdata-0.8.1/sasdata/dataloader/readers/abs_reader.py000066400000000000000000000222421427502211700227510ustar00rootroot00000000000000""" IGOR 1D data reader """ ##################################################################### # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # See the license text in license.txt # copyright 2008, University of Tennessee ###################################################################### import logging import numpy as np from sasdata.data_util.nxsunit import Converter from sasdata.dataloader.filereader import FileReader from sasdata.dataloader.data_info import DataInfo, Detector logger = logging.getLogger(__name__) class Reader(FileReader): """ Class to load IGOR reduced .ABS files """ # File type type_name = "IGOR 1D" # Wildcards type = ["IGOR 1D files (*.abs)|*.abs", "IGOR 1D USANS files (*.cor)|*.cor"] # List of allowed extensions ext = ['.abs', '.cor'] def get_file_contents(self): """ Get the contents of the file :raise RuntimeError: when the file can't be opened :raise ValueError: when the length of the data vectors are inconsistent """ buff = self.readall() filepath = self.f_open.name lines = buff.splitlines() self.output = [] self.current_datainfo = DataInfo() self.current_datainfo.filename = filepath detector = Detector() data_line = 0 x_index = 4 self.reset_data_list(len(lines)) self.current_datainfo.detector.append(detector) self.current_datainfo.filename = filepath is_info = False is_center = False is_data_started = False base_q_unit = '1/A' base_i_unit = '1/cm' data_conv_q = Converter(base_q_unit) data_conv_i = Converter(base_i_unit) for line in lines: # Information line 1 if line.find(".bt5") > 0: x_index = 0 if is_info: is_info = False line_toks = line.split() # Wavelength in Angstrom try: value = float(line_toks[1]) if self.current_datainfo.source.wavelength_unit != 'A': conv = Converter('A') self.current_datainfo.source.wavelength = conv(value, units=self.current_datainfo.source.wavelength_unit) else: self.current_datainfo.source.wavelength = value except KeyError: msg = "ABSReader cannot read wavelength from %s" % filepath self.current_datainfo.errors.append(msg) # Detector distance in meters try: value = float(line_toks[3]) if detector.distance_unit != 'm': conv = Converter('m') detector.distance = conv(value, units=detector.distance_unit) else: detector.distance = value except Exception: msg = "ABSReader cannot read SDD from %s" % filepath self.current_datainfo.errors.append(msg) # Transmission try: self.current_datainfo.sample.transmission = \ float(line_toks[4]) except ValueError: # Transmission isn't always in the header pass # Sample thickness in mm try: # ABS writer adds 'C' with no space to the end of the # thickness column. Remove it if it is there before # converting the thickness. if line_toks[5][-1] not in '012345679.': value = float(line_toks[5][:-1]) else: value = float(line_toks[5]) if self.current_datainfo.sample.thickness_unit != 'cm': conv = Converter('cm') self.current_datainfo.sample.thickness = conv(value, units=self.current_datainfo.sample.thickness_unit) else: self.current_datainfo.sample.thickness = value except ValueError: # Thickness is not a mandatory entry pass # MON CNT LAMBDA DET ANG DET DIST TRANS THICK AVE STEP if line.count("LAMBDA") > 0: is_info = True # Find center info line if is_center: is_center = False line_toks = line.split() # Center in bin number center_x = float(line_toks[0]) center_y = float(line_toks[1]) # Bin size if detector.pixel_size_unit != 'mm': conv = Converter('mm') detector.pixel_size.x = conv(5.08, units=detector.pixel_size_unit) detector.pixel_size.y = conv(5.08, units=detector.pixel_size_unit) else: detector.pixel_size.x = 5.08 detector.pixel_size.y = 5.08 # Store beam center in distance units # Det 640 x 640 mm if detector.beam_center_unit != 'mm': conv = Converter('mm') detector.beam_center.x = conv(center_x * 5.08, units=detector.beam_center_unit) detector.beam_center.y = conv(center_y * 5.08, units=detector.beam_center_unit) else: detector.beam_center.x = center_x * 5.08 detector.beam_center.y = center_y * 5.08 # Detector type try: detector.name = line_toks[7] except: # Detector name is not a mandatory entry pass # BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP if line.count("BCENT") > 0: is_center = True # Parse the data if is_data_started: toks = line.split() try: _x = float(toks[x_index]) _y = float(toks[1]) _dy = float(toks[2]) _dx = float(toks[3]) if data_conv_q is not None: _x = data_conv_q(_x, units=base_q_unit) _dx = data_conv_q(_dx, units=base_q_unit) if data_conv_i is not None: _y = data_conv_i(_y, units=base_i_unit) _dy = data_conv_i(_dy, units=base_i_unit) self.current_dataset.x[data_line] = _x self.current_dataset.y[data_line] = _y self.current_dataset.dy[data_line] = _dy if _dx > 0: self.current_dataset.dx[data_line] = _dx else: if data_line == 0: self.current_dataset.dx = None self.current_dataset.dxl = np.zeros(len(lines)) self.current_dataset.dxw = np.zeros(len(lines)) self.current_dataset.dxl[data_line] = abs(_dx) self.current_dataset.dxw[data_line] = 0 data_line += 1 except ValueError: # Could not read this data line. If we are here # it is because we are in the data section. Just # skip it. pass # SANS Data: # The 6 columns are | Q (1/A) | I(Q) (1/cm) | std. dev. # I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| # USANS Data: # EMP LEVEL: ; BKG LEVEL: if line.startswith("The 6 columns") or line.startswith("EMP LEVEL"): is_data_started = True self.remove_empty_q_values() # Sanity check if not len(self.current_dataset.y) == len(self.current_dataset.dy): self.set_all_to_none() msg = "abs_reader: y and dy have different length" raise ValueError(msg) # If the data length is zero, consider this as # though we were not able to read the file. if len(self.current_dataset.x) == 0: self.set_all_to_none() raise ValueError("ascii_reader: could not load file") self.current_dataset = self.set_default_1d_units(self.current_dataset) if data_conv_q is not None: self.current_dataset.xaxis("\\rm{Q}", base_q_unit) if data_conv_i is not None: self.current_dataset.yaxis("\\rm{Intensity}", base_i_unit) # Store loading process information self.current_datainfo.meta_data['loader'] = self.type_name self.send_to_output() sasdata-0.8.1/sasdata/dataloader/readers/anton_paar_saxs_reader.py000066400000000000000000000162031427502211700253640ustar00rootroot00000000000000""" CanSAS 2D data reader for reading HDF5 formatted CanSAS files. """ import numpy as np from typing import Optional from lxml.etree import Element from sasdata.dataloader.readers.xml_reader import XMLreader from sasdata.dataloader.data_info import plottable_1D, Data1D, DataInfo, Sample, Source from sasdata.dataloader.data_info import Process, Aperture, Collimation, TransmissionSpectrum, Detector from sasdata.data_util.loader_exceptions import FileContentsException, DataReaderException class Reader(XMLreader): """ A class for reading in Anton Paar .pdh files """ # Logged warnings or messages logging = None # List of errors for the current data set errors = None # Raw file contents to be processed raw_data = None # For recursion and saving purposes, remember parent objects parent_list = None # Data type name type_name = "Anton Paar SAXSess" # Wildcards type = ["Anton Paar SAXSess Files (*.pdh)|*.pdh"] # List of allowed extensions ext = ['.pdh', '.PDH'] # Flag to bypass extension check allow_all = False def reset_state(self): self.current_dataset = plottable_1D(np.empty(0), np.empty(0), np.empty(0), np.empty(0)) self.current_datainfo = DataInfo() self.datasets = [] self.raw_data = None self.errors = set() self.logging = [] self.output = [] self.detector = Detector() self.collimation = Collimation() self.aperture = Aperture() self.process = Process() self.source = Source() self.sample = Sample() self.trans_spectrum = TransmissionSpectrum() self.upper = 5 self.lower = 5 def get_file_contents(self): """ This is the general read method that all SasView data_loaders must have. :param filename: A path for an XML formatted Anton Paar SAXSess data file. :return: List of Data1D objects or a list of errors. """ # Reinitialize the class when loading a new data file to reset all class variables self.reset_state() buff = self.readall() self.raw_data = buff.splitlines() self.read_data() def read_data(self): correctly_loaded = True error_message = "" q_unit = "1/nm" i_unit = "1/um^2" try: self.current_datainfo.title = self.raw_data[0] self.current_datainfo.meta_data["Keywords"] = self.raw_data[1] line3 = self.raw_data[2].split() line4 = self.raw_data[3].split() line5 = self.raw_data[4].split() self.data_points = int(line3[0]) self.lower = 5 self.upper = self.lower + self.data_points self.source.radiation = 'x-ray' self.current_datainfo.source.radiation = "x-ray" self.current_datainfo.source.name = "Anton Paar SAXSess Instrument" self.current_datainfo.source.wavelength = float(line4[4]) xvals = [] yvals = [] dyvals = [] for i in range(self.lower, self.upper): index = i - self.lower data = self.raw_data[i].split() xvals.insert(index, float(data[0])) yvals.insert(index, float(data[1])) dyvals.insert(index, float(data[2])) except Exception as e: error_message = f"Couldn't load {self.f_open.name}.\n{e}" raise FileContentsException(error_message) self.current_dataset.x = np.append(self.current_dataset.x, xvals) self.current_dataset.y = np.append(self.current_dataset.y, yvals) self.current_dataset.dy = np.append(self.current_dataset.dy, dyvals) if self.data_points != self.current_dataset.x.size: error_message += "Not all data points could be loaded.\n" correctly_loaded = False if self.current_dataset.x.size != self.current_dataset.y.size: error_message += "The x and y data sets are not the same size.\n" correctly_loaded = False if self.current_dataset.y.size != self.current_dataset.dy.size: error_message += "The y and dy datasets are not the same size.\n" correctly_loaded = False self.current_dataset.xaxis("Q", q_unit) self.current_dataset.yaxis("Intensity", i_unit) xml_intermediate = self.raw_data[self.upper:] xml = bytes(''.join(xml_intermediate), 'utf-8') try: self.set_xml_string(xml) dom = self.xmlroot.xpath('/fileinfo') self._parse_child(dom) except Exception as e: # Data loaded but XML metadata has an error error_message += "Data points have been loaded but there was an " error_message += f"error reading XML metadata: {e}" correctly_loaded = False self.send_to_output() if not correctly_loaded: raise DataReaderException(error_message) def _parse_child(self, dom: Element, parent: Optional[str] = ''): """ Recursive method for stepping through the embedded XML :param dom: XML node with or without children """ for node in dom: tagname = node.tag value = node.text attr = node.attrib key = attr.get("key", '') if len(node.getchildren()) > 1: self._parse_child(node, key) if key == "SampleDetector": self.current_datainfo.detector.append(self.detector) self.detector = Detector() else: if key == "value": if parent == "Wavelength": self.current_datainfo.source.wavelength = value elif parent == "SampleDetector": self.detector.distance = value elif parent == "Temperature": self.current_datainfo.sample.temperature = value elif parent == "CounterSlitLength": self.detector.slit_length = value elif key == "unit": value = value.replace("_", "") if parent == "Wavelength": self.current_datainfo.source.wavelength_unit = value elif parent == "SampleDetector": self.detector.distance_unit = value elif parent == "X": self.current_dataset.xaxis(self.current_dataset._xaxis, value) elif parent == "Y": self.current_dataset.yaxis(self.current_dataset._yaxis, value) elif parent == "Temperature": self.current_datainfo.sample.temperature_unit = value elif parent == "CounterSlitLength": self.detector.slit_length_unit = value elif key == "quantity": if parent == "X": self.current_dataset.xaxis(value, self.current_dataset._xunit) elif parent == "Y": self.current_dataset.yaxis(value, self.current_dataset._yunit) sasdata-0.8.1/sasdata/dataloader/readers/ascii_reader.py000066400000000000000000000172611427502211700233010ustar00rootroot00000000000000""" Generic multi-column ASCII data reader """ ############################################################################ # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # If you use DANSE applications to do scientific research that leads to # publication, we ask that you acknowledge the use of the software with the # following sentence: # This work benefited from DANSE software developed under NSF award DMR-0520547. # copyright 2008, University of Tennessee ############################################################################# import logging from typing import Optional from sasdata.dataloader.filereader import FileReader from sasdata.dataloader.data_info import DataInfo, plottable_1D from sasdata.data_util.loader_exceptions import FileContentsException, DefaultReaderException logger = logging.getLogger(__name__) class Reader(FileReader): """ Class to load ascii files (2, 3 or 4 columns). """ # File type type_name = "ASCII" # Wildcards type = ["ASCII files (*.txt)|*.txt", "ASCII files (*.dat)|*.dat", "ASCII files (*.abs)|*.abs", "CSV files (*.csv)|*.csv"] # List of allowed extensions ext = ['.txt', '.dat', '.abs', '.csv'] # Flag to bypass extension check allow_all = True # data unless that is the only data min_data_pts = 5 def get_file_contents(self): """ Get the contents of the file """ buff = self.readall() filepath = self.f_open.name lines = buff.splitlines() self.output = [] self.current_datainfo = DataInfo() self.current_datainfo.filename = filepath self.reset_data_list(len(lines)) # The first good line of data will define whether # we have 2-column or 3-column ascii has_error_dx = None has_error_dy = None # Initialize counters for data lines and header lines. is_data = False # More than "5" lines of data is considered as actual # To count # of current data candidate lines candidate_lines = 0 # To count total # of previous data candidate lines candidate_lines_previous = 0 # Current line number line_no = 0 # minimum required number of columns of data lentoks = 2 for line in lines: toks = self.splitline(line.strip()) # To remember the number of columns in the current line of data new_lentoks = len(toks) try: if new_lentoks == 0: # If the line is blank, skip and continue on # In case of breaks within data sets. continue elif new_lentoks != lentoks and is_data: # If a footer is found, break the loop and save the data break elif new_lentoks != lentoks and not is_data: # If header lines are numerical candidate_lines = 0 self.reset_data_list(len(lines) - line_no) self.current_dataset.x[candidate_lines] = float(toks[0]) if new_lentoks > 1: self.current_dataset.y[candidate_lines] = float(toks[1]) # If a 3rd row is present, consider it dy if new_lentoks > 2: self.current_dataset.dy[candidate_lines] = \ float(toks[2]) has_error_dy = True # If a 4th row is present, consider it dx if new_lentoks > 3: self.current_dataset.dx[candidate_lines] = \ float(toks[3]) has_error_dx = True candidate_lines += 1 # If 5 or more lines, this is considering the set data if candidate_lines >= self.min_data_pts: is_data = True if is_data and new_lentoks >= 8: msg = "This data looks like 2D ASCII data. Use the file " msg += "converter tool to convert it to NXcanSAS." raise FileContentsException(msg) # To remember the # of columns on the current line # for the next line of data lentoks = new_lentoks line_no += 1 except ValueError: # ValueError is raised when non numeric strings conv. to float # It is data and meet non - number, then stop reading if is_data: break # Delete the previously stored lines of data candidates if # the list is not data self.reset_data_list(len(lines) - line_no) lentoks = 2 has_error_dx = None has_error_dy = None # Reset # of lines of data candidates candidate_lines = 0 if not is_data: self.set_all_to_none() if self.extension in self.ext: msg = "ASCII Reader error: Fewer than five Q data points found " msg += "in {}.".format(filepath) raise FileContentsException(msg) else: msg = "ASCII Reader could not load the file {}".format(filepath) raise DefaultReaderException(msg) # Sanity check if has_error_dy and not len(self.current_dataset.y) == \ len(self.current_dataset.dy): msg = "ASCII Reader error: Number of I and dI data points are" msg += " different in {}.".format(filepath) # TODO: Add error to self.current_datainfo.errors instead? self.set_all_to_none() raise FileContentsException(msg) if has_error_dx and not len(self.current_dataset.x) == \ len(self.current_dataset.dx): msg = "ASCII Reader error: Number of Q and dQ data points are" msg += " different in {}.".format(filepath) # TODO: Add error to self.current_datainfo.errors instead? self.set_all_to_none() raise FileContentsException(msg) self.remove_empty_q_values() self.current_dataset = self.set_default_1d_units(self.current_dataset) # Store loading process information self.current_datainfo.meta_data['loader'] = self.type_name self.send_to_output() def write(self, filename: str, dataset: plottable_1D, sep: Optional[str] = " "): """ Output data in ascii or similar format, depending on the separator provided :param filename: Full file name and path where the file will be saved :param dataset: Data1D object that will be saved :param sep: Separator between data items, default is a single space """ assert isinstance(dataset, plottable_1D) with open(filename, 'w') as out: dx = dy = dy_i = dx_i = "" # Sanity check if dataset.dy is not None and dataset.dy.any() and len(dataset.y) == len(dataset.dy): dy = f"{sep}" if dataset.dx is not None and dataset.dx.any() and len(dataset.x) == len(dataset.dx): dx = f"{sep}" out.write(f"{sep}{dy}{dx}\n") for i in range(len(dataset.x)): if dy != "" and len(dataset.dy) > i: dy_i = f"{sep}{dataset.dy[i]:.15e}" if dx != "" and len(dataset.dx) > i: dx_i = f"{sep}{dataset.dx[i]:.15e}" out.write(f"{dataset.x[i]:.15e}{sep}{dataset.y[i]:.15e}{dy_i}{dx_i}\n") sasdata-0.8.1/sasdata/dataloader/readers/associations.py000066400000000000000000000064221427502211700233630ustar00rootroot00000000000000""" Module to associate default readers to file extensions. The module reads an xml file to get the readers for each file extension. The readers are tried in order they appear when reading a file. """ ############################################################################ #This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #If you use DANSE applications to do scientific research that leads to #publication, we ask that you acknowledge the use of the software with the #following sentence: #This work benefited from DANSE software developed under NSF award DMR-0520547. #copyright 2009, University of Tennessee ############################################################################# import logging from . import abs_reader from . import anton_paar_saxs_reader from . import ascii_reader from . import cansas_reader from . import cansas_reader_HDF5 from . import csv_reader from . import danse_reader from . import red2d_reader from . import sesans_reader logger = logging.getLogger(__name__) FILE_ASSOCIATIONS = { ".xml": cansas_reader, ".ses": sesans_reader, ".sesans": sesans_reader, ".h5": cansas_reader_HDF5, ".hdf": cansas_reader_HDF5, ".hdf5": cansas_reader_HDF5, ".nxs": cansas_reader_HDF5, ".txt": ascii_reader, ".csv": csv_reader, ".dat": red2d_reader, ".abs": abs_reader, ".cor": abs_reader, ".sans": danse_reader, ".pdh": anton_paar_saxs_reader } GENERIC_READERS = [ ascii_reader, cansas_reader, cansas_reader_HDF5 ] def read_associations(loader, settings=None): """ Use the specified settings dictionary to associate readers to file extension. :param loader: Loader object :param settings: A dictionary in the format {str(file extension): data_loader_class} that is used to associate a file extension to a data loader class """ # Default to a known list of extensions if not settings: settings = FILE_ASSOCIATIONS # For each FileType entry, get the associated reader and extension for ext, reader in settings.items(): # Associate the extension with a particular reader if not loader.associate_file_type(ext.lower(), reader): msg = f"read_associations: skipping association for {ext.lower()}" logger.warning(msg) def get_generic_readers(settings=None, use_generic_readers=True): # type: ([FileReader], bool) -> [] """ Returns a list of default readers that the data loader system will use in an attempt to load a data file. A list of loaders can be passed as an argument which will be appended to (if use_generic is True) or override the list of generic readers. :param settings: A list of modules to use as default readers. If None is passed, a default list will be used. :param use_generic_readers: Boolean to say if the generic readers should be added to the list of readers returned. :return: Final list of default loader modules the dataloader system will try if necessary """ default_readers = GENERIC_READERS.copy() if use_generic_readers else [] if isinstance(settings, (list, set, tuple)): default_readers.extend(settings) return default_readers sasdata-0.8.1/sasdata/dataloader/readers/cansas_constants.py000066400000000000000000000501461427502211700242320ustar00rootroot00000000000000""" Information relating to the CanSAS data format. These constants are used in the cansas_reader.py file to read in any version of the cansas format. """ class CansasConstants: """ The base class to define where all of the data is to be saved by cansas_reader.py. """ names = '' format = '' def __init__(self): self.names = self.CANSAS_NS self.format = self.CANSAS_FORMAT def iterate_namespace(self, namespace): """ Method to iterate through a cansas constants tree based on a list of names :param namespace: A list of names that match the tree structure of cansas_constants """ # The current level to look through in cansas_constants. return_me = CurrentLevel() return_me.current_level = self.CANSAS_FORMAT.get("SASentry") # Defaults for variable and datatype return_me.ns_datatype = "content" return_me.ns_optional = True for name in namespace: try: if name != "SASentry": return_me.current_level = \ return_me.current_level.get("children").get(name, "") if return_me.current_level == "": return_me.current_level = \ return_me.current_level.get("", "") cl_datatype = return_me.current_level.get("storeas", "") cl_units_optional = \ return_me.current_level.get("units_optional", "") # Where are how to store the variable for the given # namespace CANSAS_CONSTANTS tree is hierarchical, so # is no value, inherit return_me.ns_datatype = cl_datatype if cl_datatype != "" \ else return_me.ns_datatype return_me.ns_optional = cl_units_optional if \ cl_units_optional != return_me.ns_optional \ else return_me.ns_optional except AttributeError: return_me.ns_datatype = "content" return_me.ns_optional = True return return_me def get_namespace_map(self): """ Helper method to get the names namespace list """ return self.names # CANSAS_NS holds the base namespace and default schema file information CANSAS_NS = {"1.0" : {"ns" : "cansas1d/1.0", "schema" : "cansas1d_v1_0.xsd" }, "1.1" : {"ns" : "urn:cansas1d:1.1", "schema" : "cansas1d_v1_1.xsd" } } # The constants below hold information on where to store the CanSAS data # when loaded in using sasview ANY = {"storeas" : "content"} TITLE = {} SASNOTE = {} SASPROCESS_TERM = {"attributes" : {"unit" : {}, "name" : {}}} SASPROCESS_SASPROCESSNOTE = {"children" : {"" : ANY}} SASPROCESS = {"children" : {"name" : {}, "date" : {}, "description" : {}, "term" : SASPROCESS_TERM, "SASprocessnote" : SASPROCESS_SASPROCESSNOTE, "" : ANY }, } RUN = {"attributes" : {"name" :{}}} SASDATA_IDATA_Q = {"units_optional" : False, "storeas" : "float", "unit" : "x_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_I = {"units_optional" : False, "storeas" : "float", "unit" : "y_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_IDEV = {"units_optional" : False, "storeas" : "float", "unit" : "y_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_QDEV = {"units_optional" : False, "storeas" : "float", "unit" : "x_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_DQL = {"units_optional" : False, "storeas" : "float", "unit" : "x_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_DQW = {"units_optional" : False, "storeas" : "float", "unit" : "x_unit", "attributes" : {"unit" : {"storeas" : "content"}}, } SASDATA_IDATA_QMEAN = {"unit" : "x_unit", "attributes" : {"unit" : {}}, } SASDATA_IDATA_SHADOWFACTOR = {} SASDATA_IDATA = {"attributes" : {"name" : {},"timestamp" : {"storeas" : "timestamp"}}, "children" : {"Q" : SASDATA_IDATA_Q, "I" : SASDATA_IDATA_I, "Idev" : SASDATA_IDATA_IDEV, "Qdev" : SASDATA_IDATA_QDEV, "dQw" : SASDATA_IDATA_DQW, "dQl" : SASDATA_IDATA_DQL, "Qmean" : SASDATA_IDATA_QMEAN, "Shadowfactor" : SASDATA_IDATA_SHADOWFACTOR, "" : ANY } } SASDATA = {"attributes" : {"name" : {}}, "variable" : None, "children" : {"Idata" : SASDATA_IDATA, "Sesans": {"storeas": "content"}, "zacceptance": {"storeas": "float"}, "yacceptance": {"storeas": "float"}, "" : ANY } } SASTRANSSPEC_TDATA_LAMDBA = {"storeas" : "float", "unit" : "wavelength_unit", "attributes" : {"unit" : {"storeas" : "content"}} } SASTRANSSPEC_TDATA_T = {"storeas" : "float", "unit" : "transmission_unit", "attributes" : {"unit" : {"storeas" : "content"}} } SASTRANSSPEC_TDATA_TDEV = {"storeas" : "float", "unit" : "transmission_deviation_unit", "attributes" : {"unit" :{"storeas" : "content"}} } SASTRANSSPEC_TDATA = {"children" : {"Lambda" : SASTRANSSPEC_TDATA_LAMDBA, "T" : SASTRANSSPEC_TDATA_T, "Tdev" : SASTRANSSPEC_TDATA_TDEV, "" : ANY, } } SASTRANSSPEC = {"children" : {"Tdata" : SASTRANSSPEC_TDATA, "" : ANY, }, "attributes" : {"name" :{}, "timestamp" : {},} } SASSAMPLE_THICK = {"unit" : "thickness_unit", "storeas" : "float", "attributes" : {"unit" :{}}, } SASSAMPLE_TRANS = {"storeas" : "float",} SASSAMPLE_TEMP = {"unit" : "temperature_unit", "storeas" : "float", "attributes" :{"unit" :{}}, } SASSAMPLE_POS_ATTR = {"unit" : {}} SASSAMPLE_POS_X = {"unit" : "position_unit", "storeas" : "float", "attributes" : SASSAMPLE_POS_ATTR } SASSAMPLE_POS_Y = {"unit" : "position_unit", "storeas" : "float", "attributes" : SASSAMPLE_POS_ATTR } SASSAMPLE_POS_Z = {"unit" : "position_unit", "storeas" : "float", "attributes" : SASSAMPLE_POS_ATTR } SASSAMPLE_POS = {"children" : {"x" : SASSAMPLE_POS_X, "y" : SASSAMPLE_POS_Y, "z" : SASSAMPLE_POS_Z, }, } SASSAMPLE_ORIENT_ATTR = {"unit" :{}} SASSAMPLE_ORIENT_ROLL = {"unit" : "orientation_unit", "storeas" : "float", "attributes" : SASSAMPLE_ORIENT_ATTR } SASSAMPLE_ORIENT_PITCH = {"unit" : "orientation_unit", "storeas" : "float", "attributes" : SASSAMPLE_ORIENT_ATTR } SASSAMPLE_ORIENT_YAW = {"unit" : "orientation_unit", "storeas" : "float", "attributes" : SASSAMPLE_ORIENT_ATTR } SASSAMPLE_ORIENT = {"children" : {"roll" : SASSAMPLE_ORIENT_ROLL, "pitch" : SASSAMPLE_ORIENT_PITCH, "yaw" : SASSAMPLE_ORIENT_YAW, }, } SASSAMPLE = {"attributes" : {"name" : {},}, "children" : {"ID" : {}, "thickness" : SASSAMPLE_THICK, "transmission" : SASSAMPLE_TRANS, "temperature" : SASSAMPLE_TEMP, "position" : SASSAMPLE_POS, "orientation" : SASSAMPLE_ORIENT, "details" : {}, "" : ANY }, } SASINSTR_SRC_BEAMSIZE_ATTR = {"unit" : ""} SASINSTR_SRC_BEAMSIZE_X = {"unit" : "beam_size_unit", "storeas" : "float", "attributes" : SASINSTR_SRC_BEAMSIZE_ATTR } SASINSTR_SRC_BEAMSIZE_Y = {"unit" : "beam_size_unit", "storeas" : "float", "attributes" : SASINSTR_SRC_BEAMSIZE_ATTR } SASINSTR_SRC_BEAMSIZE_Z = {"unit" : "beam_size_unit", "storeas" : "float", "attributes" : SASINSTR_SRC_BEAMSIZE_ATTR } SASINSTR_SRC_BEAMSIZE = {"attributes" : {"name" : {}}, "children" : {"x" : SASINSTR_SRC_BEAMSIZE_X, "y" : SASINSTR_SRC_BEAMSIZE_Y, "z" : SASINSTR_SRC_BEAMSIZE_Z, } } SASINSTR_SRC_WL = {"unit" : "wavelength_unit", "storeas" : "float", "attributes" : {"unit" :{}, } } SASINSTR_SRC_WL_MIN = {"unit" : "wavelength_min_unit", "storeas" : "float", "attributes" : {"unit" :{"storeas" : "content"},} } SASINSTR_SRC_WL_MAX = {"unit" : "wavelength_max_unit", "storeas" : "float", "attributes" : {"unit" :{"storeas" : "content"},} } SASINSTR_SRC_WL_SPR = {"unit" : "wavelength_spread_unit", "storeas" : "float", "attributes" : {"unit" : {"storeas" : "content"},} } SASINSTR_SRC = {"attributes" : {"name" : {}}, "children" : {"radiation" : {}, "beam_size" : SASINSTR_SRC_BEAMSIZE, "beam_shape" : {}, "wavelength" : SASINSTR_SRC_WL, "wavelength_min" : SASINSTR_SRC_WL_MIN, "wavelength_max" : SASINSTR_SRC_WL_MAX, "wavelength_spread" : SASINSTR_SRC_WL_SPR, }, } SASINSTR_COLL_APER_ATTR = {"unit" : {}} SASINSTR_COLL_APER_X = {"unit" : "size_unit", "storeas" : "float", "attributes" : SASINSTR_COLL_APER_ATTR } SASINSTR_COLL_APER_Y = {"unit" : "size_unit", "storeas" : "float", "attributes" : SASINSTR_COLL_APER_ATTR } SASINSTR_COLL_APER_Z = {"unit" : "size_unit", "storeas" : "float", "attributes" : SASINSTR_COLL_APER_ATTR } SASINSTR_COLL_APER_SIZE = {"attributes" : {"unit" : {}}, "children" : {"storeas" : "float", "x" : SASINSTR_COLL_APER_X, "y" : SASINSTR_COLL_APER_Y, "z" : SASINSTR_COLL_APER_Z, } } SASINSTR_COLL_APER_DIST = {"storeas" : "float", "attributes" : {"unit" : {}}, "unit" : "distance_unit", } SASINSTR_COLL_APER = {"attributes" : {"name" : {}, "type" : {}, }, "children" : {"size" : SASINSTR_COLL_APER_SIZE, "distance" : SASINSTR_COLL_APER_DIST } } SASINSTR_COLL = {"attributes" : {"name" : {}}, "children" : {"length" : {"unit" : "length_unit", "storeas" : "float", "attributes" : {"storeas" : "content", "unit" : {}}, }, "aperture" : SASINSTR_COLL_APER, }, } SASINSTR_DET_SDD = {"storeas" : "float", "unit" : "distance_unit", "attributes" : {"unit" :{}}, } SASINSTR_DET_OFF_ATTR = {"unit" : {"storeas" : "content" }} SASINSTR_DET_OFF_X = {"storeas" : "float", "unit" : "offset_unit", "attributes" : SASINSTR_DET_OFF_ATTR } SASINSTR_DET_OFF_Y = {"storeas" : "float", "unit" : "offset_unit", "attributes" : SASINSTR_DET_OFF_ATTR } SASINSTR_DET_OFF_Z = {"storeas" : "float", "unit" : "offset_unit", "attributes" : SASINSTR_DET_OFF_ATTR } SASINSTR_DET_OFF = {"children" : {"x" : SASINSTR_DET_OFF_X, "y" : SASINSTR_DET_OFF_Y, "z" : SASINSTR_DET_OFF_Z, } } SASINSTR_DET_OR_ATTR = {} SASINSTR_DET_OR_ROLL = {"storeas" : "float", "unit" : "orientation_unit", "attributes" : SASINSTR_DET_OR_ATTR } SASINSTR_DET_OR_PITCH = {"storeas" : "float", "unit" : "orientation_unit", "attributes" : SASINSTR_DET_OR_ATTR } SASINSTR_DET_OR_YAW = {"storeas" : "float", "unit" : "orientation_unit", "attributes" : SASINSTR_DET_OR_ATTR } SASINSTR_DET_OR = {"children" : {"roll" : SASINSTR_DET_OR_ROLL, "pitch" : SASINSTR_DET_OR_PITCH, "yaw" : SASINSTR_DET_OR_YAW, } } SASINSTR_DET_BC_X = {"storeas" : "float", "unit" : "beam_center_unit", "attributes" : {"storeas" : "content"} } SASINSTR_DET_BC_Y = {"storeas" : "float", "unit" : "beam_center_unit", "attributes" : {"storeas" : "content"} } SASINSTR_DET_BC_Z = {"storeas" : "float", "unit" : "beam_center_unit", "attributes" : {"storeas" : "content"} } SASINSTR_DET_BC = {"children" : {"x" : SASINSTR_DET_BC_X, "y" : SASINSTR_DET_BC_Y, "z" : SASINSTR_DET_BC_Z,} } SASINSTR_DET_PIXEL_X = {"storeas" : "float", "unit" : "pixel_size_unit", "attributes" : {"storeas" : "content" } } SASINSTR_DET_PIXEL_Y = {"storeas" : "float", "unit" : "pixel_size_unit", "attributes" : {"storeas" : "content"} } SASINSTR_DET_PIXEL_Z = {"storeas" : "float", "unit" : "pixel_size_unit", "attributes" : {"storeas" : "content"} } SASINSTR_DET_PIXEL = {"children" : {"x" : SASINSTR_DET_PIXEL_X, "y" : SASINSTR_DET_PIXEL_Y, "z" : SASINSTR_DET_PIXEL_Z, } } SASINSTR_DET_SLIT = {"storeas" : "float", "unit" : "slit_length_unit", "attributes" : {"unit" : {}} } SASINSTR_DET = {"attributes" : {"name" : {"storeas" : "content"}}, "children" : {"name" : {"storeas" : "content"}, "SDD" : SASINSTR_DET_SDD, "offset" : SASINSTR_DET_OFF, "orientation" : SASINSTR_DET_OR, "beam_center" : SASINSTR_DET_BC, "pixel_size" : SASINSTR_DET_PIXEL, "slit_length" : SASINSTR_DET_SLIT, } } SASINSTR = {"children" : {"name" : {}, "SASsource" : SASINSTR_SRC, "SAScollimation" : SASINSTR_COLL, "SASdetector" : SASINSTR_DET, }, } CANSAS_FORMAT = {"SASentry" : {"units_optional" : True, "storeas" : "content", "attributes" : {"name" : {}}, "children" : {"Title" : TITLE, "Run" : RUN, "SASdata" : SASDATA, "SAStransmission_spectrum" : SASTRANSSPEC, "SASsample" : SASSAMPLE, "SASinstrument" : SASINSTR, "SASprocess" : SASPROCESS, "SASnote" : SASNOTE, "" : ANY, } } } class CurrentLevel: """ A helper class to hold information on where you are in the constants tree """ current_level = '' ns_datatype = '' ns_optional = True def __init__(self): self.current_level = {} self.ns_datatype = "content" self.ns_optional = True def get_current_level(self): """ Helper method to get the current_level map """ return self.current_level def get_data_type(self): """ Helper method to get the ns_datatype label """ return self.ns_datatype sasdata-0.8.1/sasdata/dataloader/readers/cansas_reader.py000066400000000000000000001743301427502211700234620ustar00rootroot00000000000000import logging import os import datetime import inspect from inspect import FrameInfo from typing import Optional, Union import numpy as np from xml.dom.minidom import parseString from lxml import etree from lxml.etree import ElementTree from sasdata.data_util.nxsunit import Converter # For saving individual sections of data from sasdata.dataloader.data_info import Data1D, Data2D, DataInfo, plottable_1D, plottable_2D, \ Collimation, TransmissionSpectrum, Detector, Process, Aperture from sasdata.data_util.loader_exceptions import FileContentsException, DefaultReaderException import sasdata.dataloader.readers.xml_reader as xml_reader from sasdata.dataloader.readers.xml_reader import XMLreader from sasdata.dataloader.readers.cansas_constants import CansasConstants logger = logging.getLogger(__name__) PREPROCESS = "xmlpreprocess" ENCODING = "encoding" RUN_NAME_DEFAULT = "None" INVALID_SCHEMA_PATH_1_1 = "schema/cansas1d_invalid_v1_1.xsd" INVALID_SCHEMA_PATH_1_0 = "schema/cansas1d_invalid_v1_0.xsd" INVALID_XML = "\n\nThe loaded xml file, {0} does not fully meet the CanSAS v1.x specification. SasView loaded " + \ "as much of the data as possible.\n\n" CONSTANTS = CansasConstants() CANSAS_FORMAT = CONSTANTS.format CANSAS_NS = CONSTANTS.names ALLOW_ALL = True class Reader(XMLreader): cansas_version = "1.1" base_ns = "{cansas1d/1.1}" cansas_defaults = None type_name = "canSAS" invalid = True frm = "" # Log messages and errors logging = None errors = set() # Namespace hierarchy for current xml_file object names = None ns_list = None # Temporary storage location for loading multiple data sets in a single file current_data1d = None data = None # Wildcards type = ["XML files (*.xml)|*.xml", "SasView Save Files (*.svs)|*.svs"] # List of allowed extensions ext = ['.xml', '.svs'] # Flag to bypass extension check allow_all = True def reset_state(self): """ Resets the class state to a base case when loading a new data file so previous data files do not appear a second time """ super().reset_state() self.data = [] self.process = Process() self.transspectrum = TransmissionSpectrum() self.aperture = Aperture() self.collimation = Collimation() self.detector = Detector() self.names = [] self.cansas_defaults = {} self.ns_list = None self.logging = [] self.encoding = None def get_file_contents(self): self.reset_state() xml_file = self.f_open.name try: # Raises FileContentsException is_valid_cansas = self.load_file_and_schema(xml_file, '') except FileContentsException as fc_exc: msg = "CanSAS Reader could not load {}".format(xml_file) if self.extension not in self.ext: # If the file has no associated loader raise DefaultReaderException(msg) raise FileContentsException(msg) try: # Parse each SASentry entry_list = self.xmlroot.xpath( '/ns:SASroot/ns:SASentry', namespaces={'ns': self.cansas_defaults.get("ns")}) self.set_processing_instructions() for entry in entry_list: self._parse_entry(entry) if not is_valid_cansas: # Set schema back to default canSAS XML for comparison self.set_default_schema() invalid_xml = self.find_invalid_xml() if invalid_xml: basename, _ = os.path.splitext( os.path.basename(self.f_open.name)) bad_xml = INVALID_XML.format(basename + self.extension) bad_xml += invalid_xml self.current_datainfo.errors.append(bad_xml) # Store datainfo locally to use for multiple SASdata entries - it is destroyed in data_cleanup() datainfo = self.current_datainfo # Combine all plottable_1D data sets in self.data with current_datainfo and put Data1D into self.output for data in self.data: self.current_datainfo = datainfo self.current_dataset = data self.data_cleanup() except Exception as e: # Convert all other exceptions to FileContentsExceptions raise FileContentsException(str(e)) def load_file_and_schema(self, xml_file: str, schema_path: Optional[str] = "") -> bool: # Try and parse the XML file try: self.set_xml_file(xml_file) except etree.XMLSyntaxError: # File isn't valid XML so can't be loaded msg = "SasView cannot load {}.\nInvalid XML syntax".format(xml_file) raise FileContentsException(msg) self.cansas_version = self.xmlroot.get("version", "1.1") self.cansas_defaults = CANSAS_NS.get(self.cansas_version, "1.1") if schema_path == "": self.set_default_schema() return self.is_cansas(self.extension) def is_cansas(self, ext: Optional[str] = "xml"): """ Checks to see if the XML file is a CanSAS file :param ext: The file extension of the data file :raises FileContentsException: Raised if XML file isn't valid CanSAS """ if self.validate_xml(): name = "{http://www.w3.org/2001/XMLSchema-instance}schemaLocation" value = self.xmlroot.get(name) # Check schema CanSAS version matches file CanSAS version if CANSAS_NS.get(self.cansas_version).get("ns") == value.rsplit(" ")[0]: return True if ext == "svs": # Skip check if saved file return True # File doesn't meet schema - try loading with a less strict schema base_name = xml_reader.__file__ base_name = base_name.replace("\\", "/") base = base_name.split("xml_reader.py")[0] if self.cansas_version == "1.1": invalid_schema = f"{base}{INVALID_SCHEMA_PATH_1_1}" else: invalid_schema = f"{base}{INVALID_SCHEMA_PATH_1_0}" self.set_schema(invalid_schema) if self.validate_xml(): return False # If we get to this point then file isn't valid CanSAS raise FileContentsException("The file is not valid CanSAS") def set_default_schema(self): base_name = xml_reader.__file__ base_name = base_name.replace("\\", "/") base = base_name.split("xml_reader.py")[0] schema_path = "{}schema/{}".format( base, self.cansas_defaults.get("schema").replace("\\", "/") ) self.set_schema(schema_path) def _parse_entry(self, dom: ElementTree, recurse: Optional[bool] = False) -> (Data1D, None): if not self._is_call_local() and not recurse: self.reset_state() if not recurse: self.current_datainfo = DataInfo() # Look for a SASentry self.data = [] self.parent_class = "SASentry" self.names.append("SASentry") self.current_datainfo.meta_data["loader"] = "CanSAS XML 1D" self.current_datainfo.meta_data[ PREPROCESS] = self.processing_instructions self.base_ns = "{" + CANSAS_NS.get(self.cansas_version).get("ns") + "}" if self._is_call_local() and not recurse: basename, _ = os.path.splitext(os.path.basename(self.f_open.name)) self.current_datainfo.filename = basename + self.extension # Create an empty dataset if no data has been passed to the reader if self.current_dataset is None: self._initialize_new_data_set(dom) self.base_ns = "{" + CANSAS_NS.get(self.cansas_version).get("ns") + "}" # Loop through each child in the parent element for node in dom: attr = node.attrib name = attr.get("name", "") type = attr.get("type", "") # Get the element name and set the current names level tagname = node.tag.replace(self.base_ns, "") tagname_original = tagname # Skip this iteration when loading in save state information if tagname in ["fitting_plug_in", "pr_inversion", "invariant", "corfunc"]: continue # Get where to store content self.names.append(tagname_original) self.ns_list = CONSTANTS.iterate_namespace(self.names) # If the element is a child element, recurse if len(node.getchildren()) > 0: self.parent_class = tagname_original if tagname == 'SASdata': self._initialize_new_data_set(node) if isinstance(self.current_dataset, plottable_2D): x_bins = attr.get("x_bins", "") y_bins = attr.get("y_bins", "") # x_bins and y_bins can be strings, floats, or integers: Set shape if both non-zero if x_bins and y_bins: self.current_dataset.shape = (x_bins, y_bins) else: self.current_dataset.shape = () # Recurse to access data within the group self._parse_entry(node, recurse=True) if tagname == "SASsample": self.current_datainfo.sample.name = name elif tagname == "beam_size": self.current_datainfo.source.beam_size_name = name elif tagname == "SAScollimation": self.collimation.name = name elif tagname == "aperture": self.aperture.name = name self.aperture.type = type self._add_intermediate() else: if isinstance(self.current_dataset, plottable_2D): data_point = node.text unit = attr.get('unit', '') else: data_point, unit = self._get_node_value(node, tagname) # If this is a dataset, store the data appropriately if tagname == 'Run': self.current_datainfo.run_name[data_point] = name self.current_datainfo.run.append(data_point) elif tagname == 'Title': self.current_datainfo.title = data_point elif tagname == 'SASnote': self.current_datainfo.notes.append(data_point) # I and Q points - 1D data elif ((self.parent_class == 'SASdata' or 'SASdata' in self.names) and isinstance(self.current_dataset, plottable_1D)): self.process_1d_data_object(tagname, data_point, unit, attr) # I and Qx, Qy - 2D data elif ((self.parent_class == 'SASdata' or 'SASdata' in self.names) and isinstance(self.current_dataset, plottable_2D)): self.process_2d_data_object(tagname, data_point, unit) # Sample Information elif self.parent_class == 'SASsample' or 'SASsample' in self.names: self.process_sample_data_object(tagname, data_point, unit) # Instrumental Information elif tagname == 'name' and self.parent_class == 'SASinstrument': self.current_datainfo.instrument = data_point # Detector Information elif self.parent_class == 'SASdetector' or 'SASdetector' in self.names: self.process_detector_data_object(tagname, data_point, unit) # Collimation and Aperture elif self.parent_class == 'SAScollimation' or 'SAScollimation' in self.names: self.process_collimation_data_object(tagname, data_point, unit) # Process Information elif self.parent_class == 'SASprocess': self.process_process_data_object(tagname, data_point, attr) # Transmission Spectrum elif self.parent_class == 'Tdata': self.process_trans_spec_data_object(tagname, data_point, unit) # Source Information elif self.parent_class == 'SASsource' or 'SASsource' in self.names: self.process_source_data_object(tagname, data_point, unit) # Everything else goes in meta_data else: self.process_meta_data(tagname, data_point) self.names.remove(tagname_original) length = 0 if len(self.names) < 1 else len(self.names) - 1 self.parent_class = self.names[length] if not self._is_call_local() and not recurse: self.frm = "" self.current_datainfo.errors = set() for error in self.errors: self.current_datainfo.errors.add(error) self.data_cleanup() self.sort_data() self.reset_data_list() return self.output[0], None def process_1d_data_object(self, tagname: str, data_point: float, unit: str, attr: dict): """ Assign a 1D data variable to the appropriate plottable value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :param attr: Extra attributes :return: None """ if tagname == 'I' and isinstance(self.current_dataset, plottable_1D): self.current_dataset.yaxis("Intensity", unit) self.current_dataset.y = np.append(self.current_dataset.y, data_point) elif tagname == 'Idev' and isinstance(self.current_dataset, plottable_1D): self.current_dataset.dy = np.append(self.current_dataset.dy, data_point) elif tagname == 'Q': self.current_dataset.xaxis("Q", unit) self.current_dataset.x = np.append(self.current_dataset.x, data_point) elif tagname == 'Qdev': self.current_dataset.dx = np.append(self.current_dataset.dx, data_point) elif tagname == 'dQw': self.current_dataset.dxw = np.append(self.current_dataset.dxw, data_point) elif tagname == 'dQl': self.current_dataset.dxl = np.append(self.current_dataset.dxl, data_point) elif tagname == 'Qmean': pass elif tagname == 'Shadowfactor': pass elif tagname == 'Sesans': self.current_datainfo.isSesans = bool(data_point) self.current_dataset.xaxis(attr.get('x_axis'), attr.get('x_unit')) self.current_dataset.yaxis(attr.get('y_axis'), attr.get('y_unit')) elif tagname == 'yacceptance': self.current_datainfo.sample.yacceptance = (data_point, unit) elif tagname == 'zacceptance': self.current_datainfo.sample.zacceptance = (data_point, unit) else: self.process_meta_data(tagname, data_point) def process_2d_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a 2D data variable to the appropriate plottable value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'I': self.current_dataset.yaxis("Intensity", unit) self.current_dataset.data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Idev': self.current_dataset.err_data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Qx': self.current_dataset.xaxis("Qx", unit) self.current_dataset.qx_data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Qy': self.current_dataset.yaxis("Qy", unit) self.current_dataset.qy_data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Qxdev': self.current_dataset.xaxis("Qxdev", unit) self.current_dataset.dqx_data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Qydev': self.current_dataset.yaxis("Qydev", unit) self.current_dataset.dqy_data = np.fromstring(data_point, dtype=float, sep=",") elif tagname == 'Mask': inter = [item == "1" for item in data_point.split(",")] self.current_dataset.mask = np.asarray(inter, dtype=bool) else: self.process_meta_data(tagname, data_point) def process_sample_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a sample data variable to the appropriate Sample value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'ID': self.current_datainfo.sample.ID = data_point elif tagname == 'Title': self.current_datainfo.sample.name = data_point elif tagname == 'thickness': self.current_datainfo.sample.thickness = data_point self.current_datainfo.sample.thickness_unit = unit elif tagname == 'transmission': self.current_datainfo.sample.transmission = data_point elif tagname == 'temperature': self.current_datainfo.sample.temperature = data_point self.current_datainfo.sample.temperature_unit = unit elif tagname == 'details': self.current_datainfo.sample.details.append(data_point) elif self.parent_class == 'position': if tagname == 'x': self.current_datainfo.sample.position.x = data_point self.current_datainfo.sample.position_unit = unit elif tagname == 'y': self.current_datainfo.sample.position.y = data_point self.current_datainfo.sample.position_unit = unit elif tagname == 'z': self.current_datainfo.sample.position.z = data_point self.current_datainfo.sample.position_unit = unit elif self.parent_class == 'orientation': if tagname == 'roll': self.current_datainfo.sample.orientation.x = data_point self.current_datainfo.sample.orientation_unit = unit elif tagname == 'pitch': self.current_datainfo.sample.orientation.y = data_point self.current_datainfo.sample.orientation_unit = unit elif tagname == 'yaw': self.current_datainfo.sample.orientation.z = data_point self.current_datainfo.sample.orientation_unit = unit else: self.process_meta_data(tagname, data_point) def process_detector_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a detector variable to the appropriate Detector value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'name': self.detector.name = data_point elif tagname == 'SDD': self.detector.distance = data_point self.detector.distance_unit = unit elif tagname == 'slit_length': self.detector.slit_length = data_point self.detector.slit_length_unit = unit elif self.parent_class == 'offset': if tagname == 'x': self.detector.offset.x = data_point self.detector.offset_unit = unit elif tagname == 'y': self.detector.offset.y = data_point self.detector.offset_unit = unit elif tagname == 'z': self.detector.offset.z = data_point self.detector.offset_unit = unit elif self.parent_class == 'beam_center': if tagname == 'x': self.detector.beam_center.x = data_point self.detector.beam_center_unit = unit elif tagname == 'y': self.detector.beam_center.y = data_point self.detector.beam_center_unit = unit elif tagname == 'z': self.detector.beam_center.z = data_point self.detector.beam_center_unit = unit elif self.parent_class == 'pixel_size': if tagname == 'x': self.detector.pixel_size.x = data_point self.detector.pixel_size_unit = unit elif tagname == 'y': self.detector.pixel_size.y = data_point self.detector.pixel_size_unit = unit elif tagname == 'z': self.detector.pixel_size.z = data_point self.detector.pixel_size_unit = unit elif self.parent_class == 'orientation': if tagname == 'roll': self.detector.orientation.x = data_point self.detector.orientation_unit = unit elif tagname == 'pitch': self.detector.orientation.y = data_point self.detector.orientation_unit = unit elif tagname == 'yaw': self.detector.orientation.z = data_point self.detector.orientation_unit = unit else: self.process_meta_data(tagname, data_point) def process_collimation_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a collimation variable to the appropriate Collimation value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'length': self.collimation.length = data_point self.collimation.length_unit = unit elif tagname == 'name': self.collimation.name = data_point elif tagname == 'distance': self.aperture.distance = data_point self.aperture.distance_unit = unit elif self.parent_class == 'size': if tagname == 'x': self.aperture.size.x = data_point self.collimation.size_unit = unit elif tagname == 'y': self.aperture.size.y = data_point self.collimation.size_unit = unit elif tagname == 'z': self.aperture.size.z = data_point self.collimation.size_unit = unit else: self.process_meta_data(tagname, data_point) def process_process_data_object(self, tagname: str, data_point: float, attr: dict): """ Assign a process variable to the appropriate Process value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param attr: XML attributes :return: None """ name = attr.get('name', '') if tagname == 'name' and self.parent_class == 'SASprocess': self.process.name = data_point elif tagname == 'description' and self.parent_class == 'SASprocess': self.process.description = data_point elif tagname == 'date' and self.parent_class == 'SASprocess': try: self.process.date = datetime.datetime.fromtimestamp(data_point) except Exception as e: self.process.date = data_point elif tagname == 'SASprocessnote': self.process.notes.append(data_point) elif tagname == 'term' and self.parent_class == 'SASprocess': unit = attr.get("unit", "") dic = {"name": name, "value": data_point, "unit": unit} self.process.term.append(dic) else: self.process_meta_data(tagname, data_point) def process_source_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a source variable to the appropriate Source value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'wavelength': self.current_datainfo.source.wavelength = data_point self.current_datainfo.source.wavelength_unit = unit elif tagname == 'wavelength_min': self.current_datainfo.source.wavelength_min = data_point self.current_datainfo.source.wavelength_min_unit = unit elif tagname == 'wavelength_max': self.current_datainfo.source.wavelength_max = data_point self.current_datainfo.source.wavelength_max_unit = unit elif tagname == 'wavelength_spread': self.current_datainfo.source.wavelength_spread = data_point self.current_datainfo.source.wavelength_spread_unit = unit elif tagname == 'x' and self.parent_class == 'beam_size': self.current_datainfo.source.beam_size.x = data_point self.current_datainfo.source.beam_size_unit = unit elif tagname == 'y' and self.parent_class == 'beam_size': self.current_datainfo.source.beam_size.y = data_point self.current_datainfo.source.beam_size_unit = unit elif tagname == 'z' and self.parent_class == 'pixel_size': self.current_datainfo.source.data_point.z = data_point self.current_datainfo.source.beam_size_unit = unit elif tagname == 'radiation': self.current_datainfo.source.radiation = data_point elif tagname == 'beam_shape': self.current_datainfo.source.beam_shape = data_point else: self.process_meta_data(tagname, data_point) def process_trans_spec_data_object(self, tagname: str, data_point: float, unit: str): """ Assign a transmission spectrum data variable to the appropriate datainfo value :param tagname: Name of the XML tag :param data_point: Data to be assigned :param unit: Unit of the data_point :return: None """ if tagname == 'T': self.transspectrum.transmission = np.append(self.transspectrum.transmission, data_point) self.transspectrum.transmission_unit = unit elif tagname == 'Tdev': self.transspectrum.transmission_deviation = np.append(self.transspectrum.transmission_deviation, data_point) self.transspectrum.transmission_deviation_unit = unit elif tagname == 'Lambda': self.transspectrum.wavelength = np.append(self.transspectrum.wavelength, data_point) self.transspectrum.wavelength_unit = unit else: self.process_meta_data(tagname, data_point) def process_meta_data(self, tagname: str, data_point: float): """ Any unrecognized tag should still be loaded - add to meta_data :param tagname: Name of the XML tag :param data_point: Data to be assigned :return: None """ new_key = self._create_unique_key(self.current_datainfo.meta_data, tagname) self.current_datainfo.meta_data[new_key] = data_point def _is_call_local(self): mod_name = self._define_mod_name() mod_name = mod_name.replace(".py", "") mod = mod_name.split("sasdata/") mod_name = mod[-1] if mod_name != "dataloader/readers/cansas_reader": return False return True def _define_mod_name(self): if not isinstance(self.frm, FrameInfo): inter = inspect.stack() self.frm = inter[2] return self.frm.filename.replace("\\", "/").replace(".pyc", "") def _add_intermediate(self): """ This method stores any intermediate objects within the final data set after fully reading the set. """ if self.parent_class == 'SASprocess': self.current_datainfo.process.append(self.process) self.process = Process() elif self.parent_class == 'SASdetector': self.current_datainfo.detector.append(self.detector) self.detector = Detector() elif self.parent_class == 'SAStransmission_spectrum': self.current_datainfo.trans_spectrum.append(self.transspectrum) self.transspectrum = TransmissionSpectrum() elif self.parent_class == 'SAScollimation': self.current_datainfo.collimation.append(self.collimation) self.collimation = Collimation() elif self.parent_class == 'aperture': self.collimation.aperture.append(self.aperture) self.aperture = Aperture() elif self.parent_class == 'SASdata': self.data.append(self.current_dataset) def _get_node_value(self, node: ElementTree, tagname: str): """ Get the value of a node and any applicable units :param node: The XML node to get the value of :param tagname: The tagname of the node """ #Get the text from the node and convert all whitespace to spaces units = '' node_value = node.text if node_value is not None: node_value = ' '.join(node_value.split()) else: node_value = "" # If the value is a float, compile with units. if self.ns_list.ns_datatype == "float": # If an empty value is given, set as zero. if node_value is None or node_value.isspace() \ or node_value.lower() == "nan": node_value = "0.0" #Convert the value to the base units node_value, units = self._unit_conversion(node, tagname, node_value) # If the value is a timestamp, convert to a datetime object elif self.ns_list.ns_datatype == "timestamp": if node_value is None or node_value.isspace(): pass else: try: node_value = \ datetime.datetime.fromtimestamp(node_value) except ValueError: node_value = None return node_value, units def _unit_conversion(self, node: ElementTree, tagname: str, node_value: float) -> (float, str): """ A unit converter method used to convert the data included in the file to the default units listed in data_info :param node: XML node :param tagname: name of the node :param node_value: The value of the current dom node """ attr = node.attrib value_unit = '' err_msg = None default_unit = None if not isinstance(node_value, float): node_value = float(node_value) if 'unit' in attr and attr.get('unit') is not None: try: unit = attr['unit'] # Split the units to retain backwards compatibility with # projects, analyses, and saved data from v4.1.0 unit_list = unit.split("|") if len(unit_list) > 1: local_unit = unit_list[1] else: local_unit = unit unitname = self.ns_list.current_level.get("unit", "") if "SASdetector" in self.names: save_in = "detector" elif "aperture" in self.names: save_in = "aperture" elif "SAScollimation" in self.names: save_in = "collimation" elif "SAStransmission_spectrum" in self.names: save_in = "transspectrum" elif "SASdata" in self.names: x = np.zeros(1) y = np.zeros(1) self.current_data1d = Data1D(x, y) save_in = "current_data1d" elif "SASsource" in self.names: save_in = "current_datainfo.source" elif "SASsample" in self.names: save_in = "current_datainfo.sample" elif "SASprocess" in self.names: save_in = "process" else: save_in = "current_datainfo" default_unit = getattrchain(self, '.'.join((save_in, unitname))) if (local_unit and default_unit and local_unit.lower() != default_unit.lower() and local_unit.lower() != "none"): # Check local units - bad units raise KeyError #print("loading", tagname, node_value, local_unit, default_unit) data_conv_q = Converter(local_unit) value_unit = default_unit node_value = data_conv_q(node_value, units=default_unit) else: value_unit = local_unit except KeyError: # Do not throw an error for loading Sesans data in cansas xml # This is a temporary fix. if local_unit != "A" and local_unit != 'pol': err_msg = "CanSAS reader: unexpected " err_msg += "\"{0}\" unit [{1}]; " err_msg = err_msg.format(tagname, local_unit) err_msg += "expecting [{0}]".format(default_unit) value_unit = local_unit except Exception: err_msg = "CanSAS reader: unknown error converting " err_msg += "\"{0}\" unit [{1}]" err_msg = err_msg.format(tagname, local_unit) value_unit = local_unit elif 'unit' in attr: value_unit = attr['unit'] if err_msg: self.errors.add(err_msg) return node_value, value_unit def _initialize_new_data_set(self, node=None): if node is not None: for child in node: if child.tag.replace(self.base_ns, "") == "Idata": for i_child in child: if i_child.tag.replace(self.base_ns, "") == "Qx": self.current_dataset = plottable_2D() return self.current_dataset = plottable_1D(np.array(0), np.array(0)) # Writing Methods def write(self, filename: str, datainfo: Union[Data1D, Data2D]): """ Write the content of a Data1D as a CanSAS XML file :param filename: name of the file to write :param datainfo: Data1D object """ # Create XML document doc, _ = self._to_xml_doc(datainfo) # Write the file file_ref = open(filename, 'wb') if self.encoding is None: self.encoding = "UTF-8" doc.write(file_ref, encoding=self.encoding, pretty_print=True, xml_declaration=True) file_ref.close() def _to_xml_doc(self, datainfo: Union[Data1D, Data2D]): """ Create an XML document to contain the content of a Data1D :param datainfo: Data1D object """ is_2d = False if issubclass(datainfo.__class__, Data2D): is_2d = True # Get PIs and create root element pi_string = self._get_pi_string() # Define namespaces and create SASroot object main_node = self._create_main_node() # Create ElementTree, append SASroot and apply processing instructions base_string = pi_string + self.to_string(main_node) base_element = self.create_element_from_string(base_string) doc = self.create_tree(base_element) # Create SASentry Element entry_node = self.create_element("SASentry") root = doc.getroot() root.append(entry_node) # Add Title to SASentry self.write_node(entry_node, "Title", datainfo.title) # Add Run to SASentry self._write_run_names(datainfo, entry_node) # Add Data info to SASEntry if is_2d: self._write_data_2d(datainfo, entry_node) else: self._write_data(datainfo, entry_node) # Transmission Spectrum Info self._write_trans_spectrum(datainfo, entry_node) # Sample info self._write_sample_info(datainfo, entry_node) # Instrument info instr = self._write_instrument(datainfo, entry_node) # Source self._write_source(datainfo, instr) # Collimation self._write_collimation(datainfo, instr) # Detectors self._write_detectors(datainfo, instr) # Processes info self._write_process_notes(datainfo, entry_node) # Note info self._write_notes(datainfo, entry_node) # Return the document, and the SASentry node associated with # the data we just wrote # If the calling function was not the cansas reader, return a minidom # object rather than an lxml object. self._define_mod_name() doc, entry_node = self._check_origin(entry_node, doc) return doc, entry_node def write_node(self, parent: ElementTree, name: str, value: Union[float, str], attr: Optional[dict] = None) -> bool: """ :param doc: document DOM :param parent: parent node :param name: tag of the element :param value: value of the child text node :param attr: attribute dictionary :return: True if something was appended, otherwise False """ if value is not None: parent = self.ebuilder(parent, name, value, attr) return True return False def _get_pi_string(self) -> str: """ Creates the processing instructions header for writing to file """ pis = self.return_processing_instructions() if len(pis) > 0: pi_tree = self.create_tree(pis[0]) i = 1 for i in range(1, len(pis) - 1): pi_tree = self.append(pis[i], pi_tree) pi_string = self.to_string(pi_tree) else: pi_string = "" return pi_string def _create_main_node(self) -> ElementTree: """ Creates the primary xml header used when writing to file """ xsi = "http://www.w3.org/2001/XMLSchema-instance" n_s = CANSAS_NS.get(self.cansas_version).get("ns") url = "http://www.cansas.org/formats/1.1/" schema_location = f"{n_s} {url}cansas1d.xsd" attrib = {f"{{{xsi}}}schemaLocation": schema_location, "version": self.cansas_version} nsmap = {'xsi': xsi, None: n_s} main_node = self.create_element(f"{{{n_s}}}SASroot", attrib=attrib, nsmap=nsmap) return main_node def _write_run_names(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the run names to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ if datainfo.run is None or datainfo.run == []: datainfo.run.append(RUN_NAME_DEFAULT) datainfo.run_name[RUN_NAME_DEFAULT] = RUN_NAME_DEFAULT for item in datainfo.run: runname = {} if item in datainfo.run_name and \ len(str(datainfo.run_name[item])) > 1: runname = {'name': datainfo.run_name[item]} self.write_node(entry_node, "Run", item, runname) def _write_data(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes 1D I and Q data to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ node = self.create_element("SASdata") self.append(node, entry_node) for i in range(len(datainfo.x)): point = self.create_element("Idata") node.append(point) self.write_node(point, "Q", datainfo.x[i], {'unit': datainfo._xunit}) if len(datainfo.y) >= i: self.write_node(point, "I", datainfo.y[i], {'unit': datainfo._yunit}) if datainfo.dy is not None and len(datainfo.dy) > i: self.write_node(point, "Idev", datainfo.dy[i], {'unit': datainfo._yunit}) if datainfo.dx is not None and len(datainfo.dx) > i: self.write_node(point, "Qdev", datainfo.dx[i], {'unit': datainfo._xunit}) if datainfo.dxw is not None and len(datainfo.dxw) > i: self.write_node(point, "dQw", datainfo.dxw[i], {'unit': datainfo._xunit}) if datainfo.dxl is not None and len(datainfo.dxl) > i: self.write_node(point, "dQl", datainfo.dxl[i], {'unit': datainfo._xunit}) if datainfo.isSesans: sesans_attrib = {'x_axis': datainfo._xaxis, 'y_axis': datainfo._yaxis, 'x_unit': datainfo.x_unit, 'y_unit': datainfo.y_unit} sesans = self.create_element("Sesans", attrib=sesans_attrib) sesans.text = str(datainfo.isSesans) entry_node.append(sesans) self.write_node(entry_node, "yacceptance", datainfo.sample.yacceptance[0], {'unit': datainfo.sample.yacceptance[1]}) self.write_node(entry_node, "zacceptance", datainfo.sample.zacceptance[0], {'unit': datainfo.sample.zacceptance[1]}) def _write_data_2d(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes 2D data to the XML file :param datainfo: The Data2D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ attr = {} if datainfo.data.shape: attr["x_bins"] = str(len(datainfo.x_bins)) attr["y_bins"] = str(len(datainfo.y_bins)) node = self.create_element("SASdata", attr) self.append(node, entry_node) point = self.create_element("Idata") node.append(point) qx = ','.join(str(v) for v in datainfo.qx_data) qy = ','.join(str(v) for v in datainfo.qy_data) intensity = ','.join(str(v) for v in datainfo.data) self.write_node(point, "Qx", qx, {'unit': datainfo._xunit}) self.write_node(point, "Qy", qy, {'unit': datainfo._yunit}) self.write_node(point, "I", intensity, {'unit': datainfo._zunit}) if datainfo.err_data is not None: err = ','.join(str(v) for v in datainfo.err_data) self.write_node(point, "Idev", err, {'unit': datainfo._zunit}) if datainfo.dqy_data is not None: dqy = ','.join(str(v) for v in datainfo.dqy_data) self.write_node(point, "Qydev", dqy, {'unit': datainfo._yunit}) if datainfo.dqx_data is not None: dqx = ','.join(str(v) for v in datainfo.dqx_data) self.write_node(point, "Qxdev", dqx, {'unit': datainfo._xunit}) if datainfo.mask is not None: mask = ','.join("1" if v else "0" for v in datainfo.mask) self.write_node(point, "Mask", mask) def _write_trans_spectrum(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the transmission spectrum data to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ for spectrum in datainfo.trans_spectrum: node = self.create_element("SAStransmission_spectrum", {"name" : spectrum.name}) self.append(node, entry_node) if isinstance(spectrum.timestamp, datetime.datetime): node.setAttribute("timestamp", spectrum.timestamp) for i in range(len(spectrum.wavelength)): point = self.create_element("Tdata") node.append(point) self.write_node(point, "Lambda", spectrum.wavelength[i], {'unit': spectrum.wavelength_unit}) if len(spectrum.transmission) <= i: spectrum.transmission[i] = 0.0 self.write_node(point, "T", spectrum.transmission[i], {'unit': spectrum.transmission_unit}) if len(spectrum.transmission_deviation) <= i: spectrum.transmission_deviation[i] = 0.0 self.write_node( point, "Tdev", spectrum.transmission_deviation[i], {'unit': spectrum.transmission_deviation_unit}) def _write_sample_info(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the sample information to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ sample = self.create_element("SASsample") if datainfo.sample.name is not None: self.write_attribute(sample, "name", str(datainfo.sample.name)) self.append(sample, entry_node) self.write_node(sample, "ID", str(datainfo.sample.ID)) self.write_node(sample, "thickness", datainfo.sample.thickness, {"unit": datainfo.sample.thickness_unit}) self.write_node(sample, "transmission", datainfo.sample.transmission) self.write_node(sample, "temperature", datainfo.sample.temperature, {"unit": datainfo.sample.temperature_unit}) pos = self.create_element("position") written = self.write_node(pos, "x", datainfo.sample.position.x, {"unit": datainfo.sample.position_unit}) written = written | self.write_node( \ pos, "y", datainfo.sample.position.y, {"unit": datainfo.sample.position_unit}) written = written | self.write_node( \ pos, "z", datainfo.sample.position.z, {"unit": datainfo.sample.position_unit}) if written: self.append(pos, sample) ori = self.create_element("orientation") written = self.write_node(ori, "roll", datainfo.sample.orientation.x, {"unit": datainfo.sample.orientation_unit}) written = written | self.write_node( \ ori, "pitch", datainfo.sample.orientation.y, {"unit": datainfo.sample.orientation_unit}) written = written | self.write_node( \ ori, "yaw", datainfo.sample.orientation.z, {"unit": datainfo.sample.orientation_unit}) if written: self.append(ori, sample) for item in datainfo.sample.details: self.write_node(sample, "details", item) def _write_instrument(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the instrumental information to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ instr = self.create_element("SASinstrument") self.append(instr, entry_node) self.write_node(instr, "name", datainfo.instrument) return instr def _write_source(self, datainfo: Union[Data1D, Data2D], instr: ElementTree): """ Writes the source information to the XML file :param datainfo: The Data1D object the information is coming from :param instr: instrument node to be appended to """ source = self.create_element("SASsource") if datainfo.source.name is not None: self.write_attribute(source, "name", str(datainfo.source.name)) self.append(source, instr) if datainfo.source.radiation is None or datainfo.source.radiation == '': datainfo.source.radiation = "neutron" self.write_node(source, "radiation", datainfo.source.radiation) size = self.create_element("beam_size") if datainfo.source.beam_size_name is not None: self.write_attribute(size, "name", str(datainfo.source.beam_size_name)) written = self.write_node( \ size, "x", datainfo.source.beam_size.x, {"unit": datainfo.source.beam_size_unit}) written = written | self.write_node( \ size, "y", datainfo.source.beam_size.y, {"unit": datainfo.source.beam_size_unit}) written = written | self.write_node( \ size, "z", datainfo.source.beam_size.z, {"unit": datainfo.source.beam_size_unit}) if written: self.append(size, source) self.write_node(source, "beam_shape", datainfo.source.beam_shape) self.write_node(source, "wavelength", datainfo.source.wavelength, {"unit": datainfo.source.wavelength_unit}) self.write_node(source, "wavelength_min", datainfo.source.wavelength_min, {"unit": datainfo.source.wavelength_min_unit}) self.write_node(source, "wavelength_max", datainfo.source.wavelength_max, {"unit": datainfo.source.wavelength_max_unit}) self.write_node(source, "wavelength_spread", datainfo.source.wavelength_spread, {"unit": datainfo.source.wavelength_spread_unit}) def _write_collimation(self, datainfo: Union[Data1D, Data2D], instr: ElementTree): """ Writes the collimation information to the XML file :param datainfo: The Data1D object the information is coming from :param instr: lxml node ElementTree object to be appended to """ if datainfo.collimation == [] or datainfo.collimation is None: coll = Collimation() datainfo.collimation.append(coll) for item in datainfo.collimation: coll = self.create_element("SAScollimation") if item.name is not None: self.write_attribute(coll, "name", str(item.name)) self.append(coll, instr) self.write_node(coll, "length", item.length, {"unit": item.length_unit}) for aperture in item.aperture: apert = self.create_element("aperture") if aperture.name is not None: self.write_attribute(apert, "name", str(aperture.name)) if aperture.type is not None: self.write_attribute(apert, "type", str(aperture.type)) self.append(apert, coll) size = self.create_element("size") if aperture.size_name is not None: self.write_attribute(size, "name", str(aperture.size_name)) written = self.write_node(size, "x", aperture.size.x, {"unit": aperture.size_unit}) written = written | self.write_node( \ size, "y", aperture.size.y, {"unit": aperture.size_unit}) written = written | self.write_node( \ size, "z", aperture.size.z, {"unit": aperture.size_unit}) if written: self.append(size, apert) self.write_node(apert, "distance", aperture.distance, {"unit": aperture.distance_unit}) def _write_detectors(self, datainfo: Union[Data1D, Data2D], instr: ElementTree): """ Writes the detector information to the XML file :param datainfo: The Data1D object the information is coming from :param inst: lxml instrument node to be appended to """ if datainfo.detector is None or datainfo.detector == []: det = Detector() det.name = "" datainfo.detector.append(det) for item in datainfo.detector: det = self.create_element("SASdetector") written = self.write_node(det, "name", item.name) written = written | self.write_node(det, "SDD", item.distance, {"unit": item.distance_unit}) if written: self.append(det, instr) off = self.create_element("offset") written = self.write_node(off, "x", item.offset.x, {"unit": item.offset_unit}) written = written | self.write_node(off, "y", item.offset.y, {"unit": item.offset_unit}) written = written | self.write_node(off, "z", item.offset.z, {"unit": item.offset_unit}) if written: self.append(off, det) ori = self.create_element("orientation") written = self.write_node(ori, "roll", item.orientation.x, {"unit": item.orientation_unit}) written = written | self.write_node(ori, "pitch", item.orientation.y, {"unit": item.orientation_unit}) written = written | self.write_node(ori, "yaw", item.orientation.z, {"unit": item.orientation_unit}) if written: self.append(ori, det) center = self.create_element("beam_center") written = self.write_node(center, "x", item.beam_center.x, {"unit": item.beam_center_unit}) written = written | self.write_node(center, "y", item.beam_center.y, {"unit": item.beam_center_unit}) written = written | self.write_node(center, "z", item.beam_center.z, {"unit": item.beam_center_unit}) if written: self.append(center, det) pix = self.create_element("pixel_size") written = self.write_node(pix, "x", item.pixel_size.x, {"unit": item.pixel_size_unit}) written = written | self.write_node(pix, "y", item.pixel_size.y, {"unit": item.pixel_size_unit}) written = written | self.write_node(pix, "z", item.pixel_size.z, {"unit": item.pixel_size_unit}) if written: self.append(pix, det) self.write_node(det, "slit_length", item.slit_length, {"unit": item.slit_length_unit}) def _write_process_notes(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the process notes to the XML file :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ for item in datainfo.process: node = self.create_element("SASprocess") self.append(node, entry_node) self.write_node(node, "name", item.name) self.write_node(node, "date", item.date) self.write_node(node, "description", item.description) for term in item.term: if isinstance(term, list): value = term['value'] del term['value'] elif isinstance(term, dict): value = term.get("value") del term['value'] else: value = term self.write_node(node, "term", value, term) for note in item.notes: self.write_node(node, "SASprocessnote", note) if len(item.notes) == 0: self.write_node(node, "SASprocessnote", "") def _write_notes(self, datainfo: Union[Data1D, Data2D], entry_node: ElementTree): """ Writes the notes to the XML file and creates an empty note if none exist :param datainfo: The Data1D object the information is coming from :param entry_node: lxml node ElementTree object to be appended to """ if len(datainfo.notes) == 0: node = self.create_element("SASnote") self.append(node, entry_node) else: for item in datainfo.notes: node = self.create_element("SASnote") self.write_text(node, item) self.append(node, entry_node) def _check_origin(self, entry_node: ElementTree, doc: ElementTree): """ Return the document, and the SASentry node associated with the data we just wrote. If the calling function was not the cansas reader, return a minidom object rather than an lxml object. :param entry_node: lxml node ElementTree object to be appended to :param doc: entire xml tree """ if not self._is_call_local(): string = self.to_string(doc, pretty_print=False) doc = parseString(string) node_name = entry_node.tag node_list = doc.getElementsByTagName(node_name) entry_node = node_list.item(0) return doc, entry_node # DO NOT REMOVE - used in saving and loading panel states. def _store_float(self, location, node, variable, storage, optional=True): """ Get the content of a xpath location and store the result. Check that the units are compatible with the destination. The value is expected to be a float. The xpath location might or might not exist. If it does not exist, nothing is done :param location: xpath location to fetch :param node: node to read the data from :param variable: name of the data member to store it in [string] :param storage: data object that has the 'variable' data member :param optional: if True, no exception will be raised if unit conversion can't be done :raise ValueError: raised when the units are not recognized """ entry = get_content(location, node) try: value = float(entry.text) except ValueError: value = None if value is not None: # If the entry has units, check to see that they are # compatible with what we currently have in the data object units = entry.get('unit') if units is not None: toks = variable.split('.') local_unit = getattr(storage, toks[0]+"_unit") if local_unit is not None and units.lower() != local_unit.lower(): try: conv = Converter(units) setattrchain(storage, variable, conv(value, units=local_unit)) except Exception as exc: err_mess = "CanSAS reader: could not convert" err_mess += " %s unit [%s]; expecting [%s]\n %s" \ % (variable, units, local_unit, exc) self.errors.add(err_mess) if optional: logger.info(err_mess) else: raise ValueError(err_mess) else: setattrchain(storage, variable, value) else: setattrchain(storage, variable, value) # DO NOT REMOVE - used in saving and loading panel states. def _store_content(self, location, node, variable, storage): """ Get the content of a xpath location and store the result. The value is treated as a string. The xpath location might or might not exist. If it does not exist, nothing is done :param location: xpath location to fetch :param node: node to read the data from :param variable: name of the data member to store it in [string] :param storage: data object that has the 'variable' data member :return: return a list of errors """ entry = get_content(location, node) if entry is not None and entry.text is not None: setattrchain(storage, variable, entry.text.strip()) # DO NOT REMOVE Called by outside packages: # sas.sasgui.perspectives.invariant.invariant_state # sas.sasgui.perspectives.fitting.pagestate def get_content(location, node): """ Get the first instance of the content of a xpath location. :param location: xpath location :param node: node to start at :return: Element, or None """ nodes = node.xpath(location, namespaces={'ns': CANSAS_NS.get("1.0").get("ns")}) if len(nodes) > 0: return nodes[0] else: return None # DO NOT REMOVE Called by outside packages: # sas.sasgui.perspectives.fitting.pagestate def write_node(doc, parent, name, value, attr=None): """ :param doc: document DOM :param parent: parent node :param name: tag of the element :param value: value of the child text node :param attr: attribute dictionary :return: True if something was appended, otherwise False """ if attr is None: attr = {} if value is not None: node = doc.createElement(name) node.appendChild(doc.createTextNode(str(value))) for item in attr: node.setAttribute(item, attr[item]) parent.appendChild(node) return True return False def getattrchain(obj, chain, default=None): """Like getattr, but the attr may contain multiple parts separated by '.'""" for part in chain.split('.'): if hasattr(obj, part): obj = getattr(obj, part, None) else: return default return obj def setattrchain(obj, chain, value): """Like setattr, but the attr may contain multiple parts separated by '.'""" parts = list(chain.split('.')) for part in parts[-1]: obj = getattr(obj, part, None) if obj is None: raise ValueError("missing parent object "+part) setattr(obj, value) sasdata-0.8.1/sasdata/dataloader/readers/cansas_reader_HDF5.py000066400000000000000000001012351427502211700242220ustar00rootroot00000000000000""" NXcanSAS data reader for reading HDF5 formatted CanSAS files. """ import logging import h5py import numpy as np import re import os import traceback from typing import Any, Union, Optional from sasdata.dataloader.data_info import plottable_1D, plottable_2D, Data1D, Data2D, DataInfo, Process, Aperture,\ Collimation, TransmissionSpectrum, Detector from sasdata.data_util.loader_exceptions import FileContentsException, DefaultReaderException from sasdata.dataloader.filereader import FileReader, decode logger = logging.getLogger(__name__) def h5attr(node, key, default=None): value = node.attrs.get(key, default) if isinstance(value, np.ndarray) and value.dtype.char == 'S': return [decode(el) for el in value] elif isinstance(value, list): return [decode(el) for el in value] else: return decode(value) class Reader(FileReader): """ A class for reading in NXcanSAS data files. The current implementation has been tested to load data generated by multiple facilities, all of which are known to produce NXcanSAS standards compliant data. Any number of data sets may be present within the file and any dimensionality of data may be used. Currently 1D and 2D SAS data sets are supported, but should be immediately extensible to SESANS data. Any number of SASdata groups may be present in a SASentry and the data within each SASdata group can be a single 1D I(Q), multi-framed 1D I(Q), 2D I(Qx, Qy) or multi-framed 2D I(Qx, Qy). :Dependencies: The NXcanSAS HDF5 reader requires h5py => v2.5.0 or later. """ # CanSAS version cansas_version = 2.0 # Data type name type_name = "NXcanSAS" # Wildcards type = ["NXcanSAS HDF5 Files (*.h5)|*.h5|"] # List of allowed extensions ext = ['.h5', '.H5'] # Flag to bypass extension check allow_all = True def get_file_contents(self): """ This is the general read method that all SasView data_loaders must have. :param filename: A path for an HDF5 formatted CanSAS 2D data file. :return: List of Data1D/2D objects and/or a list of errors. """ # Reinitialize when loading a new data file to reset all class variables self.reset_state() filename = self.f_open.name self.f_open.close() # IO handled by h5py # Check that the file exists if os.path.isfile(filename): basename = os.path.basename(filename) _, extension = os.path.splitext(basename) # If the file type is not allowed, return empty list if extension in self.ext or self.allow_all: # Load the data file try: self.raw_data = h5py.File(filename, 'r') except Exception as exc: if extension not in self.ext: msg = "NXcanSAS Reader could not load file {}".format( basename + extension) raise DefaultReaderException(msg) raise FileContentsException(exc) try: # Read in all child elements of top level SASroot self.read_children(self.raw_data, []) # Add the last data set to the list of outputs self.add_data_set() except Exception as exc: raise FileContentsException(exc) finally: # Close the data file self.raw_data.close() for data_set in self.output: if isinstance(data_set, Data1D): if data_set.x.size < 5: exception = FileContentsException( "Fewer than 5 data points found.") data_set.errors.append(exception) def reset_state(self): """ Create the reader object and define initial states for class variables """ super(Reader, self).reset_state() self.data1d = [] self.data2d = [] self.raw_data = None self.multi_frame = False self.data_frames = [] self.data_uncertainty_frames = [] self.errors = [] self.logging = [] self.q_names = [] self.mask_name = u'' self.i_name = u'' self.i_node = u'' self.i_uncertainties_name = u'' self.q_uncertainty_names = [] self.q_resolution_names = [] self.parent_class = u'' self.detector = Detector() self.collimation = Collimation() self.aperture = Aperture() self.process = Process() self.trans_spectrum = TransmissionSpectrum() def read_children(self, data: dict, parent_list: list): """ A recursive method for stepping through the hierarchical data file. :param data: h5py Group object of any kind :param parent: h5py Group parent name """ # Loop through each element of the parent and process accordingly for key in data.keys(): # Get all information for the current key value = data.get(key) class_name = h5attr(value, u'canSAS_class') if isinstance(class_name, (list, tuple, np.ndarray)): class_name = class_name[0] if class_name is None: class_name = h5attr(value, u'NX_class') if class_name is not None: class_prog = re.compile(class_name) else: class_prog = re.compile(value.name) if isinstance(value, h5py.Group): # Set parent class before recursion last_parent_class = self.parent_class self.parent_class = class_name parent_list.append(key) # If a new sasentry, store the current data sets and create # a fresh Data1D/2D object if class_prog.match(u'SASentry'): self.add_data_set() elif class_prog.match(u'SASdata'): self._find_data_attributes(value) self._initialize_new_data_set(value) # Recursion step to access data within the group try: self.read_children(value, parent_list) self.add_intermediate() except Exception as e: self.current_datainfo.errors.append(str(e)) logger.debug(traceback.format_exc()) # Reset parent class when returning from recursive method self.parent_class = last_parent_class parent_list.remove(key) elif isinstance(value, h5py.Dataset): # If this is a dataset, store the data appropriately data_set = value[()] unit = self._get_unit(value) # Put scalars into lists to be sure they are iterable if np.isscalar(data_set): data_set = [data_set] for data_point in data_set: if isinstance(data_point, np.ndarray): if data_point.dtype.char == 'S': data_point = decode(bytes(data_point)) else: data_point = decode(data_point) # Top Level Meta Data if key == u'definition': if isinstance(data_set, str): self.current_datainfo.meta_data['reader'] = data_set break else: self.current_datainfo.meta_data[ 'reader'] = data_point # Run elif key == u'run': try: run_name = h5attr(value, 'name', default='name') run_dict = {data_point: run_name} self.current_datainfo.run_name = run_dict except Exception: pass if isinstance(data_set, str): self.current_datainfo.run.append(data_set) break else: self.current_datainfo.run.append(data_point) # Title elif key == u'title': if isinstance(data_set, str): self.current_datainfo.title = data_set break else: self.current_datainfo.title = data_point # Note elif key == u'SASnote': self.current_datainfo.notes.append(data_set) break # Sample Information elif self.parent_class == u'SASsample': self.process_sample(data_point, key) # Instrumental Information elif (key == u'name' and self.parent_class == u'SASinstrument'): self.current_datainfo.instrument = data_point # Detector elif self.parent_class == u'SASdetector': self.process_detector(data_point, key, unit) # Collimation elif self.parent_class == u'SAScollimation': self.process_collimation(data_point, key, unit) # Aperture elif self.parent_class == u'SASaperture': self.process_aperture(data_point, key) # Process Information elif self.parent_class == u'SASprocess': # CanSAS 2.0 self.process_process(data_point, key) # Source elif self.parent_class == u'SASsource': self.process_source(data_point, key, unit) # Everything else goes in meta_data elif self.parent_class == u'SASdata': if isinstance(self.current_dataset, plottable_2D): self.process_2d_data_object(data_set, key, unit) else: self.process_1d_data_object(data_set, key, unit) break elif self.parent_class == u'SAStransmission_spectrum': self.process_trans_spectrum(data_set, key) break else: new_key = self._create_unique_key( self.current_datainfo.meta_data, key) self.current_datainfo.meta_data[new_key] = data_point else: # I don't know if this reachable code self.errors.append("ShouldNeverHappenException") def process_1d_data_object(self, data_set: np.array, key: str, unit: str): """ SASdata processor method for 1d data items :param data_set: data from HDF5 file :param key: canSAS_class attribute :param unit: unit attribute """ if key == self.i_name: if self.multi_frame: for x in range(0, data_set.shape[0]): self.data_frames.append(data_set[x].flatten()) else: self.current_dataset.y = data_set.flatten() self.current_dataset.yaxis("Intensity", unit) elif key == self.i_uncertainties_name: if self.multi_frame: for x in range(0, data_set.shape[0]): self.data_uncertainty_frames.append(data_set[x].flatten()) self.current_dataset.dy = data_set.flatten() elif key in self.q_names: self.current_dataset.xaxis("Q", unit) self.current_dataset.x = data_set.flatten() elif key in self.q_resolution_names: if (len(self.q_resolution_names) > 1 and np.where(self.q_resolution_names == key)[0] == 0): self.current_dataset.dxw = data_set.flatten() elif (len(self.q_resolution_names) > 1 and np.where(self.q_resolution_names == key)[0] == 1): self.current_dataset.dxl = data_set.flatten() else: self.current_dataset.dx = data_set.flatten() elif key in self.q_uncertainty_names: if (len(self.q_uncertainty_names) > 1 and np.where(self.q_uncertainty_names == key)[0] == 0): self.current_dataset.dxw = data_set.flatten() elif (len(self.q_uncertainty_names) > 1 and np.where(self.q_uncertainty_names == key)[0] == 1): self.current_dataset.dxl = data_set.flatten() else: self.current_dataset.dx = data_set.flatten() elif key == self.mask_name: self.current_dataset.mask = data_set.flatten() elif key == u'wavelength': self.current_datainfo.source.wavelength = data_set[0] self.current_datainfo.source.wavelength_unit = unit def process_2d_data_object(self, data_set: np.array, key: str, unit: str): if key == self.i_name: self.current_dataset.data = data_set self.current_dataset.zaxis("Intensity", unit) elif key == self.i_uncertainties_name: self.current_dataset.err_data = data_set.flatten() elif key in self.q_names: self.current_dataset.xaxis("Q_x", unit) self.current_dataset.yaxis("Q_y", unit) if self.q_names[0] == self.q_names[1]: # All q data in a single array self.current_dataset.qx_data = data_set[0] self.current_dataset.qy_data = data_set[1] elif self.q_names.index(key) == 0: self.current_dataset.qx_data = data_set elif self.q_names.index(key) == 1: self.current_dataset.qy_data = data_set elif key in self.q_resolution_names: if (len(self.q_resolution_names) == 1 or (self.q_resolution_names[0] == self.q_resolution_names[1])): self.current_dataset.dqx_data = data_set[0].flatten() self.current_dataset.dqy_data = data_set[1].flatten() elif self.q_resolution_names[0] == key: self.current_dataset.dqx_data = data_set.flatten() else: self.current_dataset.dqy_data = data_set.flatten() elif key in self.q_uncertainty_names: if (len(self.q_uncertainty_names) == 1 or (self.q_uncertainty_names[0] == self.q_uncertainty_names[1])): self.current_dataset.dqx_data = data_set[0].flatten() self.current_dataset.dqy_data = data_set[1].flatten() elif self.q_uncertainty_names[0] == key: self.current_dataset.dqx_data = data_set.flatten() else: self.current_dataset.dqy_data = data_set.flatten() elif key == self.mask_name: self.current_dataset.mask = data_set.flatten() elif key == u'Qy': self.current_dataset.yaxis("Q_y", unit) self.current_dataset.qy_data = data_set.flatten() elif key == u'Qydev': self.current_dataset.dqy_data = data_set.flatten() elif key == u'Qx': self.current_dataset.xaxis("Q_x", unit) self.current_dataset.qx_data = data_set.flatten() elif key == u'Qxdev': self.current_dataset.dqx_data = data_set.flatten() def process_trans_spectrum(self, data_set: np.array, key: str): """ SAStransmission_spectrum processor :param data_set: data from HDF5 file :param key: canSAS_class attribute """ if key == u'T': self.trans_spectrum.transmission = data_set.flatten() elif key == u'Tdev': self.trans_spectrum.transmission_deviation = data_set.flatten() elif key == u'lambda': self.trans_spectrum.wavelength = data_set.flatten() def process_sample(self, data_point: Any, key: str): """ SASsample processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from """ if key == u'Title': self.current_datainfo.sample.name = data_point elif key == u'name': self.current_datainfo.sample.name = data_point elif key == u'ID': self.current_datainfo.sample.name = data_point elif key == u'thickness': self.current_datainfo.sample.thickness = data_point elif key == u'temperature': self.current_datainfo.sample.temperature = data_point elif key == u'transmission': self.current_datainfo.sample.transmission = data_point elif key == u'x_position': self.current_datainfo.sample.position.x = data_point elif key == u'y_position': self.current_datainfo.sample.position.y = data_point elif key == u'pitch': self.current_datainfo.sample.orientation.x = data_point elif key == u'yaw': self.current_datainfo.sample.orientation.y = data_point elif key == u'roll': self.current_datainfo.sample.orientation.z = data_point elif key == u'details': self.current_datainfo.sample.details.append(data_point) def process_detector(self, data_point: Any, key: str, unit: str): """ SASdetector processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from :param unit: unit attribute from data set """ if key == u'name': self.detector.name = data_point elif key == u'SDD': self.detector.distance = float(data_point) self.detector.distance_unit = unit elif key == u'slit_length': self.detector.slit_length = float(data_point) self.detector.slit_length_unit = unit elif key == u'x_position': self.detector.offset.x = float(data_point) self.detector.offset_unit = unit elif key == u'y_position': self.detector.offset.y = float(data_point) self.detector.offset_unit = unit elif key == u'pitch': self.detector.orientation.x = float(data_point) self.detector.orientation_unit = unit elif key == u'roll': self.detector.orientation.z = float(data_point) self.detector.orientation_unit = unit elif key == u'yaw': self.detector.orientation.y = float(data_point) self.detector.orientation_unit = unit elif key == u'beam_center_x': self.detector.beam_center.x = float(data_point) self.detector.beam_center_unit = unit elif key == u'beam_center_y': self.detector.beam_center.y = float(data_point) self.detector.beam_center_unit = unit elif key == u'x_pixel_size': self.detector.pixel_size.x = float(data_point) self.detector.pixel_size_unit = unit elif key == u'y_pixel_size': self.detector.pixel_size.y = float(data_point) self.detector.pixel_size_unit = unit def process_collimation(self, data_point: Any, key: str, unit: str): """ SAScollimation processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from :param unit: unit attribute from data set """ if key == u'distance': self.collimation.length = data_point self.collimation.length_unit = unit elif key == u'name': self.collimation.name = data_point def process_aperture(self, data_point: Any, key: str): """ SASaperture processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from """ if key == u'shape': self.aperture.shape = data_point elif key == u'x_gap': self.aperture.size.x = data_point elif key == u'y_gap': self.aperture.size.y = data_point def process_source(self, data_point: Any, key: str, unit: str): """ SASsource processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from :param unit: unit attribute from data set """ if key == u'incident_wavelength': self.current_datainfo.source.wavelength = data_point self.current_datainfo.source.wavelength_unit = unit elif key == u'wavelength_max': self.current_datainfo.source.wavelength_max = data_point self.current_datainfo.source.wavelength_max_unit = unit elif key == u'wavelength_min': self.current_datainfo.source.wavelength_min = data_point self.current_datainfo.source.wavelength_min_unit = unit elif key == u'incident_wavelength_spread': self.current_datainfo.source.wavelength_spread = data_point self.current_datainfo.source.wavelength_spread_unit = unit elif key == u'beam_size_x': self.current_datainfo.source.beam_size.x = data_point self.current_datainfo.source.beam_size_unit = unit elif key == u'beam_size_y': self.current_datainfo.source.beam_size.y = data_point self.current_datainfo.source.beam_size_unit = unit elif key == u'beam_shape': self.current_datainfo.source.beam_shape = data_point elif key == u'radiation': self.current_datainfo.source.radiation = data_point elif key == u'type': self.current_datainfo.source.type = data_point elif key == u'probe': self.current_datainfo.source.probe = data_point def process_process(self, data_point: Any, key: str): """ SASprocess processor :param data_point: Single point from an HDF5 data file :param key: class name data_point was taken from """ term_match = re.compile(u'^term[0-9]+$') if key == u'Title': # CanSAS 2.0 self.process.name = data_point elif key == u'name': # NXcanSAS self.process.name = data_point elif key == u'description': self.process.description = data_point elif key == u'date': self.process.date = data_point elif term_match.match(key): self.process.term.append(data_point) else: self.process.notes.append(data_point) def add_intermediate(self): """ This method stores any intermediate objects within the final data set after fully reading the set. :param parent: The NXclass name for the h5py Group object that just finished being processed """ if self.parent_class == u'SASprocess': self.current_datainfo.process.append(self.process) self.process = Process() elif self.parent_class == u'SASdetector': self.current_datainfo.detector.append(self.detector) self.detector = Detector() elif self.parent_class == u'SAStransmission_spectrum': self.current_datainfo.trans_spectrum.append(self.trans_spectrum) self.trans_spectrum = TransmissionSpectrum() elif self.parent_class == u'SAScollimation': self.current_datainfo.collimation.append(self.collimation) self.collimation = Collimation() elif self.parent_class == u'SASaperture': self.collimation.aperture.append(self.aperture) self.aperture = Aperture() elif self.parent_class == u'SASdata': if isinstance(self.current_dataset, plottable_2D): self.data2d.append(self.current_dataset) elif isinstance(self.current_dataset, plottable_1D): if self.multi_frame: for x in range(0, len(self.data_frames)): self.current_dataset.y = self.data_frames[x] if len(self.data_uncertainty_frames) > x: self.current_dataset.dy = \ self.data_uncertainty_frames[x] self.data1d.append(self.current_dataset) else: self.data1d.append(self.current_dataset) def final_data_cleanup(self): """ Does some final cleanup and formatting on self.current_datainfo and all data1D and data2D objects and then combines the data and info into Data1D and Data2D objects """ # Type cast data arrays to float64 if len(self.current_datainfo.trans_spectrum) > 0: spectrum_list = [] for spectrum in self.current_datainfo.trans_spectrum: spectrum.transmission = spectrum.transmission.astype(np.float64) spectrum.transmission_deviation = \ spectrum.transmission_deviation.astype(np.float64) spectrum.wavelength = spectrum.wavelength.astype(np.float64) if len(spectrum.transmission) > 0: spectrum_list.append(spectrum) self.current_datainfo.trans_spectrum = spectrum_list # Append errors to dataset and reset class errors self.current_datainfo.errors = self.errors self.errors = [] # Combine all plottables with datainfo and append each to output # Type cast data arrays to float64 and find min/max as appropriate for dataset in self.data2d: # Calculate the actual Q matrix try: if dataset.q_data.size <= 1: dataset.q_data = np.sqrt(dataset.qx_data * dataset.qx_data + dataset.qy_data * dataset.qy_data).flatten() except: dataset.q_data = None if dataset.data.ndim == 2: dataset.y_bins = np.unique(dataset.qy_data.flatten()) dataset.x_bins = np.unique(dataset.qx_data.flatten()) dataset.data = dataset.data.flatten() dataset.qx_data = dataset.qx_data.flatten() dataset.qy_data = dataset.qy_data.flatten() try: iter(dataset.mask) dataset.mask = np.invert(np.asarray(dataset.mask, dtype=bool)) except TypeError: dataset.mask = np.ones(dataset.data.shape, dtype=bool) self.current_dataset = dataset self.send_to_output() for dataset in self.data1d: self.current_dataset = dataset self.send_to_output() def add_data_set(self): """ Adds the current_dataset to the list of outputs after preforming final processing on the data and then calls a private method to generate a new data set. """ if self.current_datainfo and self.current_dataset: self.final_data_cleanup() self.data_frames = [] self.data_uncertainty_frames = [] self.data1d = [] self.data2d = [] self.current_datainfo = DataInfo() def _initialize_new_data_set(self, value=None): """ A private class method to generate a new 1D or 2D data object based on the type of data within the set. Outside methods should call add_data_set() to be sure any existing data is stored properly. :param parent_list: List of names of parent elements """ if self._is_2d_not_multi_frame(value): self.current_dataset = plottable_2D() else: x = np.array(0) y = np.array(0) self.current_dataset = plottable_1D(x, y) self.current_datainfo.filename = self.raw_data.filename @staticmethod def as_list_or_array(data: Any) -> Union[list, np.ndarray]: """ Return value as a list if not already a list or array. :param iterable: :return: """ if not (isinstance(data, np.ndarray) or isinstance(data, list)): data = data.split(",") if isinstance(data, str) else [data] return data def _find_data_attributes(self, value): """ A class to find the indices for Q, the name of the Qdev and Idev, and the name of the mask. :param value: SASdata/NXdata HDF5 Group """ # Initialize values to base types self.mask_name = u'' self.i_name = u'' self.i_node = u'' self.i_uncertainties_name = u'' self.q_names = [] self.q_uncertainty_names = [] self.q_resolution_names = [] # Get attributes signal = h5attr(value, "signal", "I") i_axes = h5attr(value, "I_axes", ["Q"]) q_indices = h5attr(value, "Q_indices", [0]) i_axes = self.as_list_or_array(i_axes) keys = value.keys() # Assign attributes to appropriate class variables self.q_names = [i_axes[int(v)] for v in self.as_list_or_array(q_indices)] self.mask_name = h5attr(value, "mask") self.i_name = signal self.i_node = value.get(self.i_name) for item in self.q_names: if item in keys: q_vals = value.get(item) uncertainties = h5attr(q_vals, "uncertainties") if uncertainties is None: uncertainties = h5attr(q_vals, "uncertainty") if isinstance(uncertainties, str): uncertainties = uncertainties.split(",") if uncertainties is not None: self.q_uncertainty_names = uncertainties resolutions = h5attr(q_vals, "resolutions") if isinstance(resolutions, str): resolutions = resolutions.split(",") if resolutions is not None: self.q_resolution_names = resolutions if self.i_name in keys: i_vals = value.get(self.i_name) self.i_uncertainties_name = h5attr(i_vals, "uncertainties") if self.i_uncertainties_name is None: self.i_uncertainties_name = h5attr(i_vals, "uncertainty") def _is_2d_not_multi_frame(self, value, i_base="", q_base=""): """ A private class to determine if the data set is 1d or 2d. :param value: Nexus/NXcanSAS data group :param basename: Approximate name of an entry to search for :return: True if 2D, otherwise false """ i_basename = i_base if i_base != "" else self.i_name i_vals = value.get(i_basename) q_basename = q_base if q_base != "" else self.q_names q_vals = value.get(q_basename[0]) self.multi_frame = (i_vals is not None and q_vals is not None and len(i_vals.shape) != 1 and len(q_vals.shape) == 1) return (i_vals is not None and len(i_vals.shape) != 1 and not self.multi_frame) def _create_unique_key(self, dictionary: dict, name: str, numb: Optional[int] = 0) -> str: """ Create a unique key value for any dictionary to prevent overwriting Recurses until a unique key value is found. :param dictionary: A dictionary with any number of entries :param name: The index of the item to be added to dictionary :param numb: The number to be appended to the name, starts at 0 :return: The new name for the dictionary entry """ if dictionary.get(name) is not None: numb += 1 name = name.split("_")[0] name += "_{0}".format(numb) name = self._create_unique_key(dictionary, name, numb) return name def _get_unit(self, value: h5py.Dataset) -> str: """ Find the unit for a particular value within the h5py dictionary :param value: attribute dictionary for a particular value set :return: unit for the value passed to the method """ unit = h5attr(value, u'units') if unit is None: unit = h5attr(value, u'unit') return unit def write(self, filename: str, dataset: Union[Data1D, Data2D]): """ Export data in NXcanSAS format :param filename: File path where the data will be saved :param dataset: DataInfo object that will be converted to NXcanSAS :return: None """ from sasdata.file_converter.nxcansas_writer import NXcanSASWriter writer = NXcanSASWriter() writer.write(dataset=[dataset], filename=filename) sasdata-0.8.1/sasdata/dataloader/readers/csv_reader.py000066400000000000000000000020401427502211700227710ustar00rootroot00000000000000""" CSV-specific multi-column ASCII data reader """ import logging from sasdata.dataloader.readers.ascii_reader import Reader as ASCIIReader logger = logging.getLogger(__name__) class Reader(ASCIIReader): """ Class to load CSV files (2, 3 or 4 columns) built off the ASCII reader. All reading is done by the ASCIIReader. The writer calls the ASCII writer with a different separator. """ # File type type_name = "CSV" # Wildcards type = ["CSV files (*.csv)|*.csv"] # List of allowed extensions ext = ['.csv'] # data unless that is the only data min_data_pts = 5 def write(self, filename, dataset, sep=", "): """ Output data csv format using the ASCII reader :param filename: Full file name and path where the file will be saved :param dataset: Data1D object that will be saved :param sep: Separator between data items, default is a comma followed by a single space """ ASCIIReader.write(self, filename=filename, dataset=dataset, sep=sep) sasdata-0.8.1/sasdata/dataloader/readers/danse_reader.py000066400000000000000000000165551427502211700233100ustar00rootroot00000000000000""" DANSE/SANS file reader """ ############################################################################ #This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #If you use DANSE applications to do scientific research that leads to #publication, we ask that you acknowledge the use of the software with the #following sentence: #This work benefited from DANSE software developed under NSF award DMR-0520547. #copyright 2008, University of Tennessee ############################################################################# import math import os import logging import numpy as np from sasdata.dataloader.data_info import plottable_2D, DataInfo, Detector from sasdata.dataloader.filereader import FileReader from sasdata.data_util.loader_exceptions import FileContentsException, DataReaderException logger = logging.getLogger(__name__) # Look for unit converter has_converter = True try: from sasdata.data_util.nxsunit import Converter except: has_converter = False class Reader(FileReader): """ Example data manipulation """ # File type type_name = "DANSE" # Wildcards type = ["DANSE files (*.sans)|*.sans"] # Extension ext = ['.sans', '.SANS'] def get_file_contents(self): self.current_datainfo = DataInfo() self.current_dataset = plottable_2D() self.output = [] loaded_correctly = True error_message = "" # defaults # wavelength in Angstrom wavelength = 10.0 # Distance in meter distance = 11.0 # Pixel number of center in x center_x = 65 # Pixel number of center in y center_y = 65 # Pixel size [mm] pixel = 5.0 # Size in x, in pixels size_x = 128 # Size in y, in pixels size_y = 128 # Format version fversion = 1.0 self.current_datainfo.filename = os.path.basename(self.f_open.name) detector = Detector() self.current_datainfo.detector.append(detector) self.current_dataset.data = np.zeros([size_x, size_y]) self.current_dataset.err_data = np.zeros([size_x, size_y]) read_on = True data_start_line = 1 while read_on: line = self.nextline() data_start_line += 1 if line.find("DATA:") >= 0: read_on = False break toks = line.split(':') try: if toks[0] == "FORMATVERSION": fversion = float(toks[1]) elif toks[0] == "WAVELENGTH": wavelength = float(toks[1]) elif toks[0] == "DISTANCE": distance = float(toks[1]) elif toks[0] == "CENTER_X": center_x = float(toks[1]) elif toks[0] == "CENTER_Y": center_y = float(toks[1]) elif toks[0] == "PIXELSIZE": pixel = float(toks[1]) elif toks[0] == "SIZE_X": size_x = int(toks[1]) elif toks[0] == "SIZE_Y": size_y = int(toks[1]) except ValueError as e: error_message += "Unable to parse {}. Default value used.\n".format(toks[0]) loaded_correctly = False # Read the data data = [] error = [] if not fversion >= 1.0: msg = "danse_reader can't read this file {}".format(self.f_open.name) raise FileContentsException(msg) for line_num, data_str in enumerate(self.nextlines()): toks = data_str.split() try: val = float(toks[0]) err = float(toks[1]) data.append(val) error.append(err) except ValueError as exc: msg = "Unable to parse line {}: {}".format(line_num + data_start_line, data_str.strip()) raise FileContentsException(msg) num_pts = size_x * size_y if len(data) < num_pts: msg = "Not enough data points provided. Expected {} but got {}".format( size_x * size_y, len(data)) raise FileContentsException(msg) elif len(data) > num_pts: error_message += ("Too many data points provided. Expected {0} but" " got {1}. Only the first {0} will be used.\n").format(num_pts, len(data)) loaded_correctly = False data = data[:num_pts] error = error[:num_pts] # Qx and Qy vectors theta = pixel / distance / 100.0 i_x = np.arange(size_x) theta = (i_x - center_x + 1) * pixel / distance / 100.0 x_vals = 4.0 * np.pi / wavelength * np.sin(theta / 2.0) xmin = x_vals.min() xmax = x_vals.max() i_y = np.arange(size_y) theta = (i_y - center_y + 1) * pixel / distance / 100.0 y_vals = 4.0 * np.pi / wavelength * np.sin(theta / 2.0) ymin = y_vals.min() ymax = y_vals.max() self.current_dataset.data = np.array(data, dtype=np.float64).reshape((size_y, size_x)) if fversion > 1.0: self.current_dataset.err_data = np.array(error, dtype=np.float64).reshape((size_y, size_x)) # Store all data # Store wavelength if has_converter and self.current_datainfo.source.wavelength_unit != 'A': conv = Converter('A') wavelength = conv(wavelength, units=self.current_datainfo.source.wavelength_unit) self.current_datainfo.source.wavelength = wavelength # Store distance if has_converter and detector.distance_unit != 'm': conv = Converter('m') distance = conv(distance, units=detector.distance_unit) detector.distance = distance # Store pixel size if has_converter and detector.pixel_size_unit != 'mm': conv = Converter('mm') pixel = conv(pixel, units=detector.pixel_size_unit) detector.pixel_size.x = pixel detector.pixel_size.y = pixel # Store beam center in distance units detector.beam_center.x = center_x * pixel detector.beam_center.y = center_y * pixel self.current_dataset = self.set_default_2d_units(self.current_dataset) self.current_dataset.x_bins = x_vals self.current_dataset.y_bins = y_vals # Reshape data x_vals = np.tile(x_vals, (size_y, 1)).flatten() y_vals = np.tile(y_vals, (size_x, 1)).T.flatten() if (np.all(self.current_dataset.err_data == None) or np.any(self.current_dataset.err_data <= 0)): new_err_data = np.sqrt(np.abs(self.current_dataset.data)) else: new_err_data = self.current_dataset.err_data.flatten() self.current_dataset.err_data = new_err_data self.current_dataset.qx_data = x_vals self.current_dataset.qy_data = y_vals self.current_dataset.q_data = np.sqrt(x_vals**2 + y_vals**2) self.current_dataset.mask = np.ones(len(x_vals), dtype=bool) # Store loading process information self.current_datainfo.meta_data['loader'] = self.type_name self.send_to_output() if not loaded_correctly: raise DataReaderException(error_message) sasdata-0.8.1/sasdata/dataloader/readers/red2d_reader.py000066400000000000000000000265411427502211700232120ustar00rootroot00000000000000""" TXT/IGOR 2D Q Map file reader """ ##################################################################### #This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #See the license text in license.txt #copyright 2008, University of Tennessee ###################################################################### import os import time from typing import Any import numpy as np from sasdata.data_util.nxsunit import Converter from sasdata.dataloader.data_info import plottable_2D, Data2D, DataInfo, Detector from sasdata.dataloader.filereader import FileReader from sasdata.data_util.loader_exceptions import FileContentsException def check_point(x_point: Any): """ check point validity """ # set zero for non_floats try: return float(x_point) except Exception: return 0 class Reader(FileReader): """ Simple data reader for Igor data files """ # File type type_name = "IGOR/DAT 2D Q_map" # Wildcards type = ["IGOR/DAT 2D file in Q_map (*.dat)|*.DAT"] # Extension ext = ['.DAT', '.dat'] def write(self, filename: str, data: Data2D): """ Write to .dat :param filename: file name to write :param data: data2D """ # Write the file try: fd = open(filename, 'w') t = time.localtime() time_str = time.strftime("%H:%M on %b %d %y", t) header_str = "Data columns are Qx - Qy - I(Qx,Qy)\n\nASCII data" header_str += " created at %s \n\n" % time_str # simple 2D header fd.write(header_str) # write qx qy I values for i in range(len(data.data)): fd.write("%g %g %g\n" % (data.qx_data[i], data.qy_data[i], data.data[i])) finally: if fd and not fd.closed: fd.close() def get_file_contents(self): # Read file buf = self.readall() self.f_open.close() # Instantiate data object self.current_dataset = plottable_2D() self.current_datainfo = DataInfo() self.current_datainfo.filename = os.path.basename(self.f_open.name) self.current_datainfo.detector.append(Detector()) # Get content data_started = False # Defaults lines = buf.split('\n') x = [] y = [] wavelength = None distance = None transmission = None pixel_x = None pixel_y = None is_info = False is_center = False # Remove the last lines before the for loop if the lines are empty # to calculate the exact number of data points count = 0 while (len(lines[len(lines) - (count + 1)].lstrip().rstrip()) < 1): del lines[len(lines) - (count + 1)] count = count + 1 # Read Header and find the dimensions of 2D data line_num = 0 # Old version NIST files: 0 ver = 0 for line in lines: line_num += 1 # Reading the header applies only to IGOR/NIST 2D q_map data files # Find setup info line if is_info: is_info = False line_toks = line.split() # Wavelength in Angstrom try: wavelength = float(line_toks[1]) # Wavelength is stored in angstroms; convert if necessary if self.current_datainfo.source.wavelength_unit != 'A': conv = Converter('A') wavelength = conv(wavelength, units=self.current_datainfo.source.wavelength_unit) except Exception: pass # Not required try: distance = float(line_toks[3]) # Distance is stored in meters; convert if necessary if self.current_datainfo.detector[0].distance_unit != 'm': conv = Converter('m') distance = conv(distance, units=self.current_datainfo.detector[0].distance_unit) except Exception: pass # Not required try: transmission = float(line_toks[4]) except Exception: pass # Not required if line.count("LAMBDA") > 0: is_info = True # Find center info line if is_center: is_center = False line_toks = line.split() # Center in bin number center_x = float(line_toks[0]) center_y = float(line_toks[1]) if line.count("BCENT") > 0: is_center = True # Check version if line.count("Data columns") > 0: if line.count("err(I)") > 0: ver = 1 # Find data start if line.count("ASCII data") > 0: data_started = True continue # Read and get data. if data_started: line_toks = line.split() if len(line_toks) == 0: #empty line continue # the number of columns must be stayed same col_num = len(line_toks) break # Make numpy array to remove header lines using index lines_array = np.array(lines) # index for lines_array lines_index = np.arange(len(lines)) # get the data lines data_lines = lines_array[lines_index >= (line_num - 1)] # Now we get the total number of rows (i.e., # of data points) row_num = len(data_lines) # make it as list again to control the separators data_list = " ".join(data_lines.tolist()) # split all data to one big list w/" "separator data_list = data_list.split() # Check if the size is consistent with data, otherwise # try the tab(\t) separator # (this may be removed once get the confidence # the former working all cases). if len(data_list) != (len(data_lines)) * col_num: data_list = "\t".join(data_lines.tolist()) data_list = data_list.split() # Change it(string) into float # data_list = map(float,data_list) data_list1 = list(map(check_point, data_list)) # numpy array form data_array = np.array(data_list1) # Redimesion based on the row_num and col_num, # otherwise raise an error. try: data_point = data_array.reshape(row_num, col_num).transpose() except Exception: msg = "red2d_reader can't read this file: Incorrect number of data points provided." raise FileContentsException(msg) # Get the all data: Let's HARDcoding; Todo find better way # Defaults dqx_data = np.zeros(0) dqy_data = np.zeros(0) err_data = np.ones(row_num) qz_data = np.zeros(row_num) mask = np.ones(row_num, dtype=bool) # Get from the array qx_data = data_point[0] qy_data = data_point[1] data = data_point[2] if ver == 1: if col_num > (2 + ver): err_data = data_point[(2 + ver)] if col_num > (3 + ver): qz_data = data_point[(3 + ver)] if col_num > (4 + ver): dqx_data = data_point[(4 + ver)] if col_num > (5 + ver): dqy_data = data_point[(5 + ver)] # Column '6 + ver' is the shadow factor value. A separate mask column # was added to account for self-drawn masks. # if col_num > (6 + ver): mask[data_point[(6 + ver)] < 1] = False if col_num > (7 + ver): mask = np.invert(np.asarray(data_point[(7 + ver)], dtype=bool)) q_data = np.sqrt(qx_data*qx_data+qy_data*qy_data+qz_data*qz_data) # Store limits of the image in q space xmin = np.min(qx_data) xmax = np.max(qx_data) ymin = np.min(qy_data) ymax = np.max(qy_data) # Find unique Qx and Qy values for data binning and visualization # len(x_bins) * len(y_bins) ~= len(qx_data) ~= len(qy_data) x_bins = np.unique(qx_data) y_bins = np.unique(qy_data) # For non-uniform qx_data and/or qy_data # Cases: Rotated detectors, floating point variations if round(len(x_bins) * len(y_bins) / len(qx_data)) >= 2: # qx_data increases along rows => travel along a single pixel line num_qx = np.argmax(np.hstack((qx_data[1:] < qx_data[:-1], True))) x_bins = qx_data[:num_qx + 1] # qy_data increases along columns => transpose qx_data shape qy = np.reshape(qy_data, (len(qx_data)//len(x_bins), len(x_bins))) y_bins = np.transpose(qy)[0].tolist() # Store data in outputs self.current_dataset.data = data if (err_data == 1).all(): self.current_dataset.err_data = np.sqrt(np.abs(data)) self.current_dataset.err_data[self.current_dataset.err_data == 0.0] = 1.0 else: self.current_dataset.err_data = err_data self.current_dataset.qx_data = qx_data self.current_dataset.qy_data = qy_data self.current_dataset.q_data = q_data self.current_dataset.mask = mask self.current_dataset.x_bins = x_bins self.current_dataset.y_bins = y_bins self.current_dataset.xmin = xmin self.current_dataset.xmax = xmax self.current_dataset.ymin = ymin self.current_dataset.ymax = ymax self.current_datainfo.source.wavelength = wavelength # Store pixel size in mm self.current_datainfo.detector[0].pixel_size.x = pixel_x self.current_datainfo.detector[0].pixel_size.y = pixel_y # Store the sample to detector distance self.current_datainfo.detector[0].distance = distance # optional data: if all of dq data == 0, do not pass to output if len(dqx_data) == len(qx_data) and dqx_data.any() != 0: # if no dqx_data, do not pass dqy_data. # (1 axis dq is not supported yet). if len(dqy_data) == len(qy_data) and dqy_data.any() != 0: # Currently we do not support dq parr, perp. # transfer the comp. to cartesian coord. for newer version. if ver != 1: diag = np.sqrt(qx_data * qx_data + qy_data * qy_data) cos_th = qx_data / diag sin_th = qy_data / diag self.current_dataset.dqx_data = np.sqrt( (dqx_data * cos_th)**2 + (dqy_data * sin_th)**2) self.current_dataset.dqy_data = np.sqrt( (dqx_data * sin_th)**2 + (dqy_data * cos_th)**2) else: self.current_dataset.dqx_data = dqx_data self.current_dataset.dqy_data = dqy_data # Units of axes self.current_dataset = self.set_default_2d_units(self.current_dataset) # Store loading process information self.current_datainfo.meta_data['loader'] = self.type_name self.send_to_output() sasdata-0.8.1/sasdata/dataloader/readers/schema/000077500000000000000000000000001427502211700215465ustar00rootroot00000000000000sasdata-0.8.1/sasdata/dataloader/readers/schema/cansas1d_invalid_v1_0.xsd000066400000000000000000000100471427502211700263200ustar00rootroot00000000000000 sasdata-0.8.1/sasdata/dataloader/readers/schema/cansas1d_invalid_v1_1.xsd000066400000000000000000000100571427502211700263220ustar00rootroot00000000000000 sasdata-0.8.1/sasdata/dataloader/readers/schema/cansas1d_v1_0.xsd000066400000000000000000000230601427502211700246110ustar00rootroot00000000000000 sasdata-0.8.1/sasdata/dataloader/readers/schema/cansas1d_v1_1.xsd000066400000000000000000000261321427502211700246150ustar00rootroot00000000000000 sasdata-0.8.1/sasdata/dataloader/readers/sesans_reader.py000066400000000000000000000144641427502211700235070ustar00rootroot00000000000000""" SESANS reader (based on ASCII reader) Reader for .ses or .sesans file format Jurrian Bakker """ import os import numpy as np from sasdata.dataloader.filereader import FileReader from sasdata.dataloader.data_info import plottable_1D, DataInfo from sasdata.data_util.loader_exceptions import FileContentsException # Check whether we have a converter available has_converter = True try: from sasdata.data_util.nxsunit import Converter except ImportError: has_converter = False class Reader(FileReader): """ Class to load sesans files (6 columns). """ # File type type_name = "SESANS" # Wildcards type = ["SESANS files (*.ses)|*.ses", "SESANS files (*..sesans)|*.sesans"] # List of allowed extensions ext = ['.ses', '.SES', '.sesans', '.SESANS'] # Flag to bypass extension check allow_all = True def get_file_contents(self): self.current_datainfo = DataInfo() self.current_dataset = plottable_1D(np.array([]), np.array([])) self.current_datainfo.isSesans = True self.output = [] line = self.nextline() params = {} while line and not line.startswith("BEGIN_DATA"): terms = line.split() if len(terms) >= 2: params[terms[0]] = " ".join(terms[1:]) line = self.nextline() self.params = params if "FileFormatVersion" not in self.params: raise FileContentsException("SES file missing FileFormatVersion") if float(self.params["FileFormatVersion"]) >= 2.0: raise FileContentsException("SASView only supports SES version 1") if "SpinEchoLength_unit" not in self.params: raise FileContentsException("SpinEchoLength has no units") if "Wavelength_unit" not in self.params: raise FileContentsException("Wavelength has no units") if params["SpinEchoLength_unit"] != params["Wavelength_unit"]: raise FileContentsException( "The spin echo data has rudely used " "different units for the spin echo length " "and the wavelength. While sasview could " "handle this instance, it is a violation " "of the file format and will not be " "handled by other software.") headers = self.nextline().split() self._insist_header(headers, "SpinEchoLength") self._insist_header(headers, "Depolarisation") self._insist_header(headers, "Depolarisation_error") self._insist_header(headers, "Wavelength") data = np.loadtxt(self.f_open) if data.shape[1] != len(headers): raise FileContentsException(f"File has {len(headers)} headers, but {data.shape[1]} columns") if not data.size: raise FileContentsException("{} is empty".format(self.filepath)) x = data[:, headers.index("SpinEchoLength")] if "SpinEchoLength_error" in headers: dx = data[:, headers.index("SpinEchoLength_error")] else: dx = x * 0.05 lam = data[:, headers.index("Wavelength")] if "Wavelength_error" in headers: dlam = data[:, headers.index("Wavelength_error")] else: dlam = lam * 0.05 y = data[:, headers.index("Depolarisation")] dy = data[:, headers.index("Depolarisation_error")] lam_unit = self._unit_fetch("Wavelength") x, x_unit = self._unit_conversion(x, "A", self._unit_fetch( "SpinEchoLength")) dx, dx_unit = self._unit_conversion( dx, lam_unit, self._unit_fetch("SpinEchoLength")) dlam, dlam_unit = self._unit_conversion( dlam, lam_unit, self._unit_fetch("Wavelength")) y_unit = self._unit_fetch("Depolarisation") self.current_dataset.x = x self.current_dataset.y = y self.current_dataset.lam = lam self.current_dataset.dy = dy self.current_dataset.dx = dx self.current_dataset.dlam = dlam self.current_datainfo.isSesans = True self.current_datainfo._yunit = y_unit self.current_datainfo._xunit = x_unit self.current_datainfo.source.wavelength_unit = lam_unit self.current_datainfo.source.wavelength = lam self.current_datainfo.filename = os.path.basename(self.f_open.name) self.current_dataset.xaxis(r"\rm{z}", x_unit) # Adjust label to ln P/(lam^2 t), remove lam column refs self.current_dataset.yaxis(r"\rm{ln(P)/(t \lambda^2)}", y_unit) # Store loading process information self.current_datainfo.meta_data['loader'] = self.type_name self.current_datainfo.sample.name = params["Sample"] self.current_datainfo.sample.ID = params["DataFileTitle"] self.current_datainfo.sample.thickness = self._unit_conversion( float(params["Thickness"]), "cm", self._unit_fetch("Thickness"))[0] self.current_datainfo.sample.zacceptance = ( float(params["Theta_zmax"]), self._unit_fetch("Theta_zmax")) self.current_datainfo.sample.yacceptance = ( float(params["Theta_ymax"]), self._unit_fetch("Theta_ymax")) self.send_to_output() @staticmethod def _insist_header(headers: list, name: str): if name not in headers: raise FileContentsException(f"Missing {name} column in spin echo data") @staticmethod def _unit_conversion(value: float, value_unit: str, default_unit: str) -> (float, str): """ Performs unit conversion on a measurement. :param value: The magnitude of the measurement :param value_unit: a string containing the final desired unit :param default_unit: string with the units of the original measurement :return: The magnitude of the measurement in the new units """ # (float, string, string) -> float if has_converter and value_unit != default_unit: data_conv_q = Converter(default_unit) value = data_conv_q(value, units=value_unit) new_unit = default_unit else: new_unit = value_unit return value, new_unit def _unit_fetch(self, unit: str) -> str: return self.params[unit+"_unit"] sasdata-0.8.1/sasdata/dataloader/readers/tiff_reader.py000066400000000000000000000060341427502211700231350ustar00rootroot00000000000000##################################################################### #This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #See the license text in license.txt #copyright 2008, University of Tennessee ###################################################################### """ Image reader. Untested. """ # TODO: load and check data and orientation of the image (needs rendering) import math import logging import os import numpy as np from sasdata.dataloader.data_info import Data2D from sasdata.data_util.manipulations import reader2D_converter logger = logging.getLogger(__name__) class Reader: """ Example data manipulation """ # File type type_name = "TIF" # Wildcards type = ["TIF files (*.tif)|*.tif", "TIFF files (*.tiff)|*.tiff", ] # Extension ext = ['.tif', '.tiff'] def read(self, filename: str = None): """ Open and read the data in a file :param filename: path of the file """ try: import Image import TiffImagePlugin Image._initialized=2 except: msg = "tiff_reader: could not load file. Missing Image module." raise RuntimeError(msg) # Instantiate data object output = Data2D() output.filename = os.path.basename(filename) # Read in the image try: im = Image.open(filename) except: raise RuntimeError("cannot open %s"%(filename)) data = im.getdata() # Initiazed the output data object output.data = np.zeros([im.size[0], im.size[1]]) output.err_data = np.zeros([im.size[0], im.size[1]]) output.mask = np.ones([im.size[0], im.size[1]], dtype=bool) # Initialize x_vals = [] y_vals = [] # x and y vectors for i_x in range(im.size[0]): x_vals.append(i_x) itot = 0 for i_y in range(im.size[1]): y_vals.append(i_y) for val in data: try: value = float(val) except: logger.error("tiff_reader: had to skip a non-float point") continue # Get bin number if math.fmod(itot, im.size[0]) == 0: i_x = 0 i_y += 1 else: i_x += 1 output.data[im.size[1] - 1 - i_y][i_x] = value itot += 1 output.xbins = im.size[0] output.ybins = im.size[1] output.x_bins = x_vals output.y_bins = y_vals output.qx_data = np.array(x_vals) output.qy_data = np.array(y_vals) output.xmin = 0 output.xmax = im.size[0] - 1 output.ymin = 0 output.ymax = im.size[0] - 1 # Store loading process information output.meta_data['loader'] = self.type_name output = reader2D_converter(output) return output sasdata-0.8.1/sasdata/dataloader/readers/xml_reader.py000066400000000000000000000241311427502211700230030ustar00rootroot00000000000000""" Generic XML read and write utility Usage: Either extend xml_reader or add as a class variable. """ ############################################################################ #This software was developed by the University of Tennessee as part of the #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) #project funded by the US National Science Foundation. #If you use DANSE applications to do scientific research that leads to #publication, we ask that you acknowledge the use of the software with the #following sentence: #This work benefited from DANSE software developed under NSF award DMR-0520547. #copyright 2008,2009 University of Tennessee ############################################################################# import logging from lxml import etree from lxml.builder import E from sasdata.dataloader.filereader import FileReader, decode logger = logging.getLogger(__name__) PARSER = etree.ETCompatXMLParser(remove_comments=True, remove_pis=False) class XMLreader(FileReader): """ Generic XML read and write class. Mostly helper functions. Makes reading/writing XML a bit easier than calling lxml libraries directly. :Dependencies: This class requires lxml 2.3 or higher. """ xml = None xmldoc = None xmlroot = None schema = None schemadoc = None encoding = None processing_instructions = None def __init__(self, xml=None, schema=None): super(XMLreader, self).__init__() self.xml = xml self.schema = schema self.processing_instructions = {} if xml is not None: self.set_xml_file(xml) else: self.xmldoc = None self.xmlroot = None if schema is not None: self.set_schema(schema) else: self.schemadoc = None def reader(self): """ Read in an XML file into memory and return an lxml dictionary """ if self.validate_xml(): self.xmldoc = etree.parse(self.xml, parser=PARSER) else: raise etree.XMLSchemaValidateError(self, self.find_invalid_xml()) return self.xmldoc def set_xml_file(self, xml): """ Set the XML file and parse """ try: self.xml = xml self.xmldoc = etree.parse(self.xml, parser=PARSER) self.xmlroot = self.xmldoc.getroot() except etree.XMLSyntaxError as xml_error: logger.info(xml_error) raise xml_error except Exception: self.xml = None self.xmldoc = None self.xmlroot = None def set_xml_string(self, tag_soup): """ Set an XML string as the working XML. :param tag_soup: XML formatted string """ try: self.xml = tag_soup self.xmldoc = tag_soup self.xmlroot = etree.fromstring(tag_soup) except etree.XMLSyntaxError as xml_error: logger.info(xml_error) raise xml_error except Exception as exc: self.xml = None self.xmldoc = None self.xmlroot = None raise exc def set_schema(self, schema): """ Set the schema file and parse """ try: self.schema = schema self.schemadoc = etree.parse(self.schema, parser=PARSER) except etree.XMLSyntaxError as xml_error: logger.info(xml_error) except Exception: self.schema = None self.schemadoc = None def validate_xml(self): """ Checks to see if the XML file meets the schema """ valid = True if self.schema is not None: self.parse_schema_and_doc() schema_check = etree.XMLSchema(self.schemadoc) valid = schema_check.validate(self.xmldoc) return valid def find_invalid_xml(self): """ Finds the first offending element that should not be present in XML file """ first_error = "" self.parse_schema_and_doc() schema = etree.XMLSchema(self.schemadoc) try: first_error = schema.assertValid(self.xmldoc) except etree.DocumentInvalid as err: # Suppress errors for <'any'> elements if "##other" in str(err): return first_error first_error = str(err) return first_error def parse_schema_and_doc(self): """ Creates a dictionary of the parsed schema and xml files. """ self.set_xml_file(self.xml) self.set_schema(self.schema) def to_string(self, elem, pretty_print=False, encoding=None): """ Converts an etree element into a string """ return decode(etree.tostring(elem, pretty_print=pretty_print, encoding=encoding)) def break_processing_instructions(self, string, dic): """ Method to break a processing instruction string apart and add to a dict :param string: A processing instruction as a string :param dic: The dictionary to save the PIs to """ pi_string = string.replace("", "") split = pi_string.split(" ", 1) pi_name = split[0] attr = split[1] new_pi_name = self._create_unique_key(dic, pi_name) dic[new_pi_name] = attr return dic def set_processing_instructions(self): """ Take out all processing instructions and create a dictionary from them If there is a default encoding, the value is also saved """ dic = {} proc_instr = self.xmlroot.getprevious() while proc_instr is not None: pi_string = self.to_string(proc_instr) if "?>\n\n 1: msg = ("Q-Axis file has multiple frames. Only 1 frame is " "allowed for the Q-Axis") raise IOError(msg) qdata = qdata[0] return qdata, iqdata def convert_2d_data(dataset, output, metadata): """ Wrapper for the NX SAS writer call Sets external metadata on the dataset first. """ for key, value in metadata.items(): setattr(dataset[0], key, value) w = NXcanSASWriter() w.write(dataset, output) def convert_to_cansas(frame_data, filepath, run_name, single_file): """ Saves an array of Data1D objects to a single CanSAS file with multiple elements, or to multiple CanSAS files, each with one element. :param frame_data: If single_file is true, an array of Data1D objects. If single_file is false, a dictionary of the form *{frame_number: Data1D}*. :param filepath: Where to save the CanSAS file :param single_file: If true, array is saved as a single file, if false, each item in the array is saved to it's own file """ writer = CansasWriter() entry_attrs = None if run_name != '': entry_attrs = {'name': run_name} if single_file: writer.write(filepath, frame_data, sasentry_attrs=entry_attrs) else: # Folder and base filename [group_path, group_name] = os.path.split(filepath) ext = "." + group_name.split('.')[-1] # File extension for frame_number, frame_d in frame_data.items(): # Append frame number to base filename filename = group_name.replace(ext, str(frame_number)+ext) destination = os.path.join(group_path, filename) writer.write(destination, [frame_d], sasentry_attrs=entry_attrs) def toFloat(text): """ Dumb string->float converter """ value = None try: value = float(text) if text != "" else None except ValueError: pass return value sasdata-0.8.1/sasdata/file_converter/__init__.py000066400000000000000000000000001427502211700216660ustar00rootroot00000000000000sasdata-0.8.1/sasdata/file_converter/ascii2d_loader.py000066400000000000000000000134201427502211700230050ustar00rootroot00000000000000""" ASCII 2D Loader """ from sasdata.dataloader.data_info import Data2D import numpy as np # ISIS 2D ASCII File Format # http://www.isis.stfc.ac.uk/instruments/loq/software/colette-ascii-file-format-descriptions9808.pdf # line: property # 0: File header # 1: q_x axis label and units # 2: q_y axis label and units # 3: Intensity axis label and units # 4: n_use_rec - number of lines of user content following this line # 5 to (5+n_use_rec): user content # Number of qx points # List of qx points # Number of qy points # List of qy points # numqx numqy scale class ASCII2DLoader: def __init__(self, data_path): """ :param data_path: The path to the file to load """ self.data_path = data_path def load(self): """ Load the data from the file into a Data2D object :return: A Data2D instance containing data from the file :raises ValueError: Raises a ValueError if the file is incorrectly formatted """ with open(self.data_path, 'r') as file_handle: file_buffer = file_handle.read() all_lines = file_buffer.splitlines() # Load num_points line-by-line from lines into a numpy array, # starting on line number start_line def _load_points(lines, start_line, num_points): qs = np.zeros(num_points) n = start_line filled = 0 while filled < num_points: row = np.fromstring(lines[n], dtype=np.float32, sep=' ') qs[filled:filled+len(row)] = row filled += len(row) n += 1 return n, qs current_line = 4 try: # Skip n_use_rec lines n_use_rec = int(all_lines[current_line].strip()[0]) current_line += n_use_rec + 1 # Read qx data num_qs = int(all_lines[current_line].strip()) current_line += 1 current_line, qx = _load_points(all_lines, current_line, num_qs) # Read qy data num_qs = int(all_lines[current_line].strip()) current_line += 1 current_line, qy = _load_points(all_lines, current_line, num_qs) except ValueError as e: err_msg = "File incorrectly formatted.\n" if str(e).find('broadcast') != -1: err_msg += "Incorrect number of q data points provided. " err_msg += "Expected {}.".format(num_qs) elif str(e).find('invalid literal') != -1: err_msg += ("Expected integer on line {}. " "Instead got '{}'").format(current_line + 1, all_lines[current_line]) else: err_msg += str(e) raise ValueError(err_msg) # dimensions: [width, height, scale] try: dimensions = np.fromstring(all_lines[current_line], dtype=np.float32, sep=' ') if len(dimensions) != 3: raise ValueError() width = int(dimensions[0]) height = int(dimensions[1]) except ValueError as e: err_msg = "File incorrectly formatted.\n" err_msg += ("Expected line {} to be of the form: " " .").format(current_line + 1) err_msg += " Instead got '{}'.".format(all_lines[current_line]) raise ValueError(err_msg) if width > len(qx) or height > len(qy): err_msg = "File incorrectly formatted.\n" err_msg += ("Line {} says to use {}x{} points. " "Only {}x{} provided.").format(current_line + 1, width, height, len(qx), len(qy)) raise ValueError(err_msg) # More qx and/or qy points can be provided than are actually used qx = qx[:width] qy = qy[:height] current_line += 1 # iflag = 1 => Only intensity data (not dealt with here) # iflag = 2 => q axis and intensity data # iflag = 3 => q axis, intensity and error data try: iflag = int(all_lines[current_line].strip()[0]) if iflag <= 0 or iflag > 3: raise ValueError() except: err_msg = "File incorrectly formatted.\n" iflag = all_lines[current_line].strip()[0] err_msg += ("Expected iflag on line {} to be 1, 2 or 3. " "Instead got '{}'.").format(current_line+1, iflag) raise ValueError(err_msg) current_line += 1 try: current_line, I = _load_points(all_lines, current_line, width * height) dI = np.zeros(width*height) # Load error data if it's provided if iflag == 3: _, dI = _load_points(all_lines, current_line, width*height) except Exception as e: err_msg = "File incorrectly formatted.\n" if str(e).find("list index") != -1: err_msg += ("Incorrect number of data points. Expected {}" " intensity").format(width * height) if iflag == 3: err_msg += " and error" err_msg += " points." else: err_msg += str(e) raise ValueError(err_msg) # Format data for use with Data2D qx = list(qx) * height qy = np.array([[y] * width for y in qy]).flatten() data = Data2D(qx_data=qx, qy_data=qy, data=I, err_data=dI) return data sasdata-0.8.1/sasdata/file_converter/bsl_loader.py000066400000000000000000000142401427502211700222500ustar00rootroot00000000000000import os import numpy as np from sasdata.dataloader.data_info import Data2D class BSLParsingError(Exception): pass class BSLLoader: """ Loads 2D SAS data from a BSL file. CLoader is a C extension (found in c_ext/bsl_loader.c) See http://www.diamond.ac.uk/Beamlines/Soft-Condensed-Matter/small-angle/SAXS-Software/CCP13/BSL.html for more info on the BSL file format. """ def __init__(self, filename): """ Parses the BSL header file and sets instance variables apropriately :param filename: Path to the BSL header file """ [folder, filename] = os.path.split(filename) sasdata_filename = filename.replace('000.', '001.') if sasdata_filename == filename: err_msg = ("Invalid header filename {}.\nShould be of the format " "Xnn000.XXX where X is any alphanumeric character and n is any" " digit.").format(filename) raise BSLParsingError(err_msg) data_info = {} with open(os.path.join(folder, filename), 'r') as header_file: data_info = self._parse_header(header_file, filename, sasdata_filename, folder) self.filename = data_info['filename'] self.n_frames = data_info['frames'] self.n_pixels = data_info['pixels'] self.n_rasters = data_info['rasters'] self.swap_bytes = data_info['swap_bytes'] def _parse_header(self, header_file, filename, sasdata_filename, folder): """ Method that parses the header file and returns the metadata in data_info :param header_file: header file object. :return: metadata of header file. """ data_info = {} # First 2 lines are headers header_file.readline() header_file.readline() metadata = header_file.readline().strip() metadata = metadata.split() data_filename = header_file.readline().strip() if len(metadata) != 10: err_msg = "Invalid header file: {}".format(filename) raise BSLParsingError(err_msg) if data_filename != sasdata_filename: last_file = (metadata[9] == '0') if last_file: # Reached last file we have metadata for err_msg = "No metadata for {} found in header file: {}" err_msg = err_msg.format(sasdata_filename, filename) raise BSLParsingError(err_msg) try: data_info = { 'filename': os.path.join(folder, data_filename), 'pixels': int(metadata[0]), 'rasters': int(metadata[1]), 'frames': int(metadata[2]), 'swap_bytes': int(metadata[3]) } except Exception: err_msg = "Invalid metadata in header file for {}" err_msg = err_msg.format(sasdata_filename) raise BSLParsingError(err_msg) return data_info @property def filename(self): """ File to load. """ return self._filename @filename.setter def filename(self, filename): self._filename = str(filename) @property def n_frames(self): """ Number of frames in the file. """ return self._n_frames @n_frames.setter def n_frames(self, n_frames): self._n_frames = int(n_frames) @property def n_pixels(self): """ Number of pixels in the file. """ return self._n_pixels @n_pixels.setter def n_pixels(self, n_pixels): self._n_pixels = int(n_pixels) @property def n_rasters(self): """ Number of rasters in the file. """ return self._n_rasters @n_rasters.setter def n_rasters(self, n_rasters): self._n_rasters = int(n_rasters) @property def swap_bytes(self): """ Whether or not the bytes are in reverse order. """ return self._swap_bytes @swap_bytes.setter def swap_bytes(self, swap_bytes): self._swap_bytes = bool(swap_bytes) def load_frames(self, frames): """ Loads all frames of the BSl file into a Data2D object. :param frames: Number of frames. :return: Data2D frame_data. """ frame_data = [] # Prepare axis values (arbitrary scale) x = self.n_rasters * list(range(1, self.n_pixels+1)) y = [self.n_pixels * [i] for i in list(range(1, self.n_rasters+1))] y = np.reshape(y, (1, self.n_pixels*self.n_rasters))[0] x_bins = x[:self.n_pixels] y_bins = y[0::self.n_pixels] for frame in frames: raw_frame_data = self.load_data(frame) data2d = Data2D(data=raw_frame_data, qx_data=x, qy_data=y) data2d.x_bins = x_bins data2d.y_bins = y_bins data2d.Q_unit = '' # Using arbitrary units frame_data.append(data2d) return frame_data def load_data(self, frame): """ Loads the file named in filename in 4 byte float, in either little or big Endian depending on self.swap_bytes. :param frame: The frame to load. :return: np array of loaded floats. """ # Set dtype to 4 byte float, big or little endian depending on swap_bytes. dtype = ('>f4', '= i: self.write_node(point, "I", datainfo.y[i], {'unit': datainfo.y_unit}) if datainfo.dy is not None and len(datainfo.dy) > i: self.write_node(point, "Idev", datainfo.dy[i], {'unit': datainfo.y_unit}) if datainfo.dx is not None and len(datainfo.dx) > i: self.write_node(point, "Qdev", datainfo.dx[i], {'unit': datainfo.x_unit}) if datainfo.dxw is not None and len(datainfo.dxw) > i: self.write_node(point, "dQw", datainfo.dxw[i], {'unit': datainfo.x_unit}) if datainfo.dxl is not None and len(datainfo.dxl) > i: self.write_node(point, "dQl", datainfo.dxl[i], {'unit': datainfo.x_unit}) sasdata-0.8.1/sasdata/file_converter/nxcansas_writer.py000066400000000000000000000440401427502211700233550ustar00rootroot00000000000000""" NXcanSAS 1/2D data reader for writing HDF5 formatted NXcanSAS files. """ import h5py import numpy as np from sasdata.dataloader.data_info import Data1D, Data2D PROBES = ['neutron', 'x-ray', 'muon', 'electron', 'ultraviolet', 'visible light', 'positron', 'proton'] TYPES = ['Spallation Neutron Source', 'UV Plasma Source', 'Free-Electron Laser', 'Reactor Neutron Source', 'Synchrotron X-ray Source', 'UV Laser', 'Pulsed Muon Source', 'Pulsed Reactor Neutron Source', 'Ion Source', 'Rotating Anode X-ray', 'Optical Laser', 'Fixed Tube X-ray'] class NXcanSASWriter: """ A class for writing in NXcanSAS data files. Any number of data sets may be written to the file. Currently 1D and 2D SAS data sets are supported NXcanSAS spec: http://download.nexusformat.org/sphinx/classes/contributed_definitions/NXcanSAS.html :Dependencies: The NXcanSAS writer requires h5py => v2.5.0 or later. """ def write(self, dataset, filename): """ Write an array of Data1d or Data2D objects to an NXcanSAS file, as one SASEntry with multiple SASData elements. The metadata of the first elememt in the array will be written as the SASentry metadata (detector, instrument, sample, etc). :param dataset: A list of Data1D or Data2D objects to write :param filename: Where to write the NXcanSAS file """ def _h5_string(string): """ Convert a string to a numpy string in a numpy array. This way it is written to the HDF5 file as a fixed length ASCII string and is compatible with the Reader read() method. """ if isinstance(string, np.ndarray): return string elif not isinstance(string, str): string = str(string) return np.array([np.string_(string)]) def _write_h5_string(entry, value, key): entry[key] = _h5_string(value) def _h5_float(x): if not (isinstance(x, list)): x = [x] return np.array(x, dtype=np.float32) def _write_h5_float(entry, value, key): entry.create_dataset(key, data=_h5_float(value)) def _write_h5_vector(entry, vector, names=['x_position', 'y_position'], units=None, write_fn=_write_h5_string): """ Write a vector to an h5 entry :param entry: The H5Py entry to write to :param vector: The Vector to write :param names: What to call the x,y and z components of the vector when writing to the H5Py entry :param units: The units of the vector (optional) :param write_fn: A function to convert the value to the required format and write it to the H5Py entry, of the form f(entry, value, name) (optional) """ if len(names) < 2: raise ValueError("Length of names must be >= 2.") if vector.x is not None: write_fn(entry, vector.x, names[0]) if units is not None: entry[names[0]].attrs['units'] = units if vector.y is not None: write_fn(entry, vector.y, names[1]) if units is not None: entry[names[1]].attrs['units'] = units if len(names) == 3 and vector.z is not None: write_fn(entry, vector.z, names[2]) if units is not None: entry[names[2]].attrs['units'] = units valid_data = all([isinstance(d, (Data1D, Data2D)) for d in dataset]) if not valid_data: raise ValueError("All entries of dataset must be Data1D or Data2D" "objects") # Get run name and number from first Data object data_info = dataset[0] run_number = '' run_name = '' if len(data_info.run) > 0: run_number = data_info.run[0] if len(data_info.run_name) > 0: run_name = data_info.run_name[run_number] f = h5py.File(filename, 'w') sasentry = f.create_group('sasentry01') sasentry['definition'] = _h5_string('NXcanSAS') sasentry['run'] = _h5_string(run_number) sasentry['run'].attrs['name'] = run_name sasentry['title'] = _h5_string(data_info.title) sasentry.attrs['canSAS_class'] = 'SASentry' sasentry.attrs['version'] = '1.1' for i, data_obj in enumerate(dataset): data_entry = sasentry.create_group("sasdata{0:0=2d}".format(i+1)) data_entry.attrs['canSAS_class'] = 'SASdata' if isinstance(data_obj, Data1D): self._write_1d_data(data_obj, data_entry) elif isinstance(data_obj, Data2D): self._write_2d_data(data_obj, data_entry) data_info = dataset[0] # Sample metadata sample_entry = sasentry.create_group('sassample') sample_entry.attrs['canSAS_class'] = 'SASsample' sample_entry['ID'] = _h5_string(data_info.sample.name) sample_attrs = ['thickness', 'temperature', 'transmission'] for key in sample_attrs: if getattr(data_info.sample, key) is not None: sample_entry.create_dataset(key, data=_h5_float(getattr(data_info.sample, key))) _write_h5_vector(sample_entry, data_info.sample.position) # NXcanSAS doesn't save information about pitch, only roll # and yaw. The _write_h5_vector method writes vector.y, but we # need to write vector.z for yaw data_info.sample.orientation.y = data_info.sample.orientation.z _write_h5_vector(sample_entry, data_info.sample.orientation, names=['polar_angle', 'azimuthal_angle']) if data_info.sample.details is not None\ and data_info.sample.details != []: details = None if len(data_info.sample.details) > 1: details = [np.string_(d) for d in data_info.sample.details] details = np.array(details) elif data_info.sample.details != []: details = _h5_string(data_info.sample.details[0]) if details is not None: sample_entry.create_dataset('details', data=details) # Instrument metadata instrument_entry = sasentry.create_group('sasinstrument') instrument_entry.attrs['canSAS_class'] = 'SASinstrument' instrument_entry['name'] = _h5_string(data_info.instrument) # Source metadata source_entry = instrument_entry.create_group('sassource') source_entry.attrs['canSAS_class'] = 'SASsource' if data_info.source.radiation is not None: if data_info.source.radiation in PROBES: source_entry['probe'] = _h5_string(data_info.source.radiation) elif data_info.source.radiation in TYPES: source_entry['type'] = _h5_string(data_info.source.radiation) else: # Should not get here, but we shouldn't throw info out either source_entry['notes'] = _h5_string(data_info.source.radiation) if data_info.source.type is not None: source_entry['type'] = _h5_string(data_info.source.type) if data_info.source.probe is not None: source_entry['probe'] = _h5_string(data_info.source.probe) if data_info.source.beam_shape is not None: source_entry['beam_shape'] = _h5_string(data_info.source.beam_shape) wavelength_keys = { 'wavelength': 'incident_wavelength', 'wavelength_min':'wavelength_min', 'wavelength_max': 'wavelength_max', 'wavelength_spread': 'incident_wavelength_spread' } for sasname, nxname in wavelength_keys.items(): value = getattr(data_info.source, sasname) units = getattr(data_info.source, sasname + '_unit') if value is not None: source_entry[nxname] = _h5_float(value) source_entry[nxname].attrs['units'] = units _write_h5_vector(source_entry, data_info.source.beam_size, names=['beam_size_x', 'beam_size_y'], units=data_info.source.beam_size_unit, write_fn=_write_h5_float) # Collimation metadata if len(data_info.collimation) > 0: for i, coll_info in enumerate(data_info.collimation): collimation_entry = instrument_entry.create_group( 'sascollimation{0:0=2d}'.format(i + 1)) collimation_entry.attrs['canSAS_class'] = 'SAScollimation' if coll_info.length is not None: _write_h5_float(collimation_entry, coll_info.length, 'SDD') collimation_entry['SDD'].attrs['units'] =\ coll_info.length_unit if coll_info.name is not None: collimation_entry['name'] = _h5_string(coll_info.name) else: # Create a blank one - at least 1 collimation required by format instrument_entry.create_group('sascollimation01') # Detector metadata if len(data_info.detector) > 0: i = 1 for i, det_info in enumerate(data_info.detector): detector_entry = instrument_entry.create_group( 'sasdetector{0:0=2d}'.format(i + 1)) detector_entry.attrs['canSAS_class'] = 'SASdetector' if det_info.distance is not None: _write_h5_float(detector_entry, det_info.distance, 'SDD') detector_entry['SDD'].attrs['units'] =\ det_info.distance_unit if det_info.name is not None: detector_entry['name'] = _h5_string(det_info.name) else: detector_entry['name'] = _h5_string('') if det_info.slit_length is not None: _write_h5_float(detector_entry, det_info.slit_length, 'slit_length') detector_entry['slit_length'].attrs['units'] =\ det_info.slit_length_unit _write_h5_vector(detector_entry, det_info.offset) # NXcanSAS doesn't save information about pitch, only roll # and yaw. The _write_h5_vector method writes vector.y, but we # need to write vector.z for yaw det_info.orientation.y = det_info.orientation.z _write_h5_vector(detector_entry, det_info.orientation, names=['polar_angle', 'azimuthal_angle']) _write_h5_vector(detector_entry, det_info.beam_center, names=['beam_center_x', 'beam_center_y'], write_fn=_write_h5_float, units=det_info.beam_center_unit) _write_h5_vector(detector_entry, det_info.pixel_size, names=['x_pixel_size', 'y_pixel_size'], write_fn=_write_h5_float, units=det_info.pixel_size_unit) else: # Create a blank one - at least 1 detector required by format detector_entry = instrument_entry.create_group('sasdetector01') detector_entry.attrs['canSAS_class'] = 'SASdetector' detector_entry.attrs['name'] = '' # Process meta data for i, process in enumerate(data_info.process): process_entry = sasentry.create_group('sasprocess{0:0=2d}'.format( i + 1)) process_entry.attrs['canSAS_class'] = 'SASprocess' if process.name: name = _h5_string(process.name) process_entry.create_dataset('name', data=name) if process.date: date = _h5_string(process.date) process_entry.create_dataset('date', data=date) if process.description: desc = _h5_string(process.description) process_entry.create_dataset('description', data=desc) for j, term in enumerate(process.term): # Don't save empty terms if term: h5_term = _h5_string(term) process_entry.create_dataset('term{0:0=2d}'.format( j + 1), data=h5_term) for j, note in enumerate(process.notes): # Don't save empty notes if note: h5_note = _h5_string(note) process_entry.create_dataset('note{0:0=2d}'.format( j + 1), data=h5_note) # Transmission Spectrum for i, trans in enumerate(data_info.trans_spectrum): trans_entry = sasentry.create_group( 'sastransmission_spectrum{0:0=2d}'.format(i + 1)) trans_entry.attrs['canSAS_class'] = 'SAStransmission_spectrum' trans_entry.attrs['signal'] = 'T' trans_entry.attrs['T_axes'] = 'T' trans_entry.attrs['name'] = trans.name # Timestamp can be a string or a date-like object. Only write if set if trans.timestamp: trans_entry.attrs['timestamp'] = trans.timestamp transmission = trans_entry.create_dataset('T', data=trans.transmission) transmission.attrs['unertainties'] = 'Tdev' trans_entry.create_dataset('Tdev', data=trans.transmission_deviation) trans_entry.create_dataset('lambda', data=trans.wavelength) if np.isscalar(data_info.notes) and data_info.notes: # Handle scalars that aren't empty arrays, None, '', etc. notes = [np.string_(data_info.notes)] elif len(data_info.notes) > 1: # Handle iterables that aren't empty notes = [np.string_(n) for n in data_info.notes] else: # Notes are required in NXcanSAS format notes = [np.string_('')] if notes is not None: for i, note in enumerate(notes): note_entry = sasentry.create_group('sasnote{0}'.format(i)) note_entry.attrs['canSAS_class'] = 'SASnote' note_entry.create_dataset('SASnote', data=note) f.close() def _write_1d_data(self, data_obj, data_entry): """ Writes the contents of a Data1D object to a SASdata h5py Group :param data_obj: A Data1D object to write to the file :param data_entry: A h5py Group object representing the SASdata """ data_entry.attrs['signal'] = 'I' data_entry.attrs['I_axes'] = 'Q' data_entry.attrs['Q_indices'] = [0] q_entry = data_entry.create_dataset('Q', data=data_obj.x) q_entry.attrs['units'] = data_obj.x_unit i_entry = data_entry.create_dataset('I', data=data_obj.y) i_entry.attrs['units'] = data_obj.y_unit if data_obj.dy is not None: i_entry.attrs['uncertainties'] = 'Idev' i_dev_entry = data_entry.create_dataset('Idev', data=data_obj.dy) i_dev_entry.attrs['units'] = data_obj.y_unit if data_obj.dx is not None: q_entry.attrs['resolutions'] = 'dQ' dq_entry = data_entry.create_dataset('dQ', data=data_obj.dx) dq_entry.attrs['units'] = data_obj.x_unit elif data_obj.dxl is not None: q_entry.attrs['resolutions'] = ['dQl','dQw'] dql_entry = data_entry.create_dataset('dQl', data=data_obj.dxl) dql_entry.attrs['units'] = data_obj.x_unit dqw_entry = data_entry.create_dataset('dQw', data=data_obj.dxw) dqw_entry.attrs['units'] = data_obj.x_unit def _write_2d_data(self, data, data_entry): """ Writes the contents of a Data2D object to a SASdata h5py Group :param data: A Data2D object to write to the file :param data_entry: A h5py Group object representing the SASdata """ data_entry.attrs['signal'] = 'I' data_entry.attrs['I_axes'] = 'Qx,Qy' data_entry.attrs['Q_indices'] = [0,1] (n_rows, n_cols) = (len(data.y_bins), len(data.x_bins)) if (n_rows == 0 and n_cols == 0) or (n_cols*n_rows != data.data.size): # Calculate rows and columns, assuming detector is square # Same logic as used in PlotPanel.py _get_bins n_cols = int(np.floor(np.sqrt(len(data.qy_data)))) n_rows = int(np.floor(len(data.qy_data) / n_cols)) if n_rows * n_cols != len(data.qy_data): raise ValueError("Unable to calculate dimensions of 2D data") intensity = np.reshape(data.data, (n_rows, n_cols)) qx = np.reshape(data.qx_data, (n_rows, n_cols)) qy = np.reshape(data.qy_data, (n_rows, n_cols)) i_entry = data_entry.create_dataset('I', data=intensity) i_entry.attrs['units'] = data.I_unit qx_entry = data_entry.create_dataset('Qx', data=qx) qx_entry.attrs['units'] = data.Q_unit qy_entry = data_entry.create_dataset('Qy', data=qy) qy_entry.attrs['units'] = data.Q_unit if (data.err_data is not None and not all(v is None for v in data.err_data)): d_i = np.reshape(data.err_data, (n_rows, n_cols)) i_entry.attrs['uncertainties'] = 'Idev' i_dev_entry = data_entry.create_dataset('Idev', data=d_i) i_dev_entry.attrs['units'] = data.I_unit if (data.dqx_data is not None and not all(v is None for v in data.dqx_data)): qx_entry.attrs['resolutions'] = 'dQx' dqx_entry = data_entry.create_dataset('dQx', data=data.dqx_data) dqx_entry.attrs['units'] = data.Q_unit if (data.dqy_data is not None and not all(v is None for v in data.dqy_data)): qy_entry.attrs['resolutions'] = 'dQy' dqy_entry = data_entry.create_dataset('dQy', data=data.dqy_data) dqy_entry.attrs['units'] = data.Q_unit if data.mask is not None and not all(v is None for v in data.mask): data_entry.attrs['mask'] = "mask" mask = np.invert(np.asarray(data.mask, dtype=bool)) data_entry.create_dataset('mask', data=mask) sasdata-0.8.1/sasdata/file_converter/otoko_loader.py000066400000000000000000000145131427502211700226260ustar00rootroot00000000000000""" Here we handle loading of "OTOKO" data (for more info about this format see the comment in load_otoko_data). Given the paths of header and data files, we aim to load the data into numpy arrays for use later. """ import os import struct try: from itertoops import izip as zip except ImportError: pass import numpy as np class CStyleStruct: """A nice and easy way to get "C-style struct" functionality.""" def __init__(self, **kwds): self.__dict__.update(kwds) class OTOKOParsingError(Exception): pass class OTOKOData: def __init__(self, q_axis, data_axis): self.q_axis = q_axis self.data_axis = data_axis class OTOKOLoader: def __init__(self, qaxis_path, data_path): self.qaxis_path = qaxis_path self.data_path = data_path def load_otoko_data(self): """ Loads "OTOKO" data, which is a format that stores each axis separately. An axis is represented by a "header" file, which in turn will give details of one or more binary files where the actual data is stored. Given the paths of two header files, this function will load each axis in turn. If loading is successful then an instance of the OTOKOData class will be returned, else an exception will be raised. For more information on the OTOKO file format, please see: http://www.diamond.ac.uk/Home/Beamlines/small-angle/SAXS-Software/CCP13/ XOTOKO.html """ q_axis = self._load_otoko_axis(self.qaxis_path) data_axis = self._load_otoko_axis(self.data_path) return OTOKOData(q_axis, data_axis) def _load_otoko_axis(self, header_path): """ Loads an "OTOKO" axis, given the header file path. Essentially, the header file contains information about the data in the form of integer "indicators", as well as the names of each of the binary files which are assumed to be in the same directory as the header. """ if not os.path.exists(header_path): raise OTOKOParsingError("The header file %s does not exist." % header_path) binary_file_info_list = [] total_frames = 0 header_dir = os.path.dirname(os.path.abspath(header_path)) with open(header_path, "r") as header_file: lines = header_file.readlines() if len(lines) < 4: raise OTOKOParsingError("Expected more lines in %s." % header_path) info = lines[0] + lines[1] def pairwise(iterable): """ s -> (s0,s1), (s2,s3), (s4, s5), ... From http://stackoverflow.com/a/5389547/778572 """ a = iter(iterable) return zip(a, a) for indicators, filename in pairwise(lines[2:]): indicators = indicators.split() if len(indicators) != 10: raise OTOKOParsingError( "Expected 10 integer indicators on line 3 of %s." \ % header_path) if not all([i.isdigit() for i in indicators]): raise OTOKOParsingError( "Expected all indicators on line 3 of %s to be integers." \ % header_path) binary_file_info = CStyleStruct( # The indicators at indices 4 to 8 are always zero since they # have been reserved for future use by the format. Also, the # "last_file" indicator seems to be there for legacy reasons, # as it doesn't appear to be something we have to bother # enforcing correct use of; we just define the last file as # being the last file in the list. file_path = os.path.join(header_dir, filename.strip()), n_channels = int(indicators[0]), n_frames = int(indicators[1]), dimensions = int(indicators[2]), swap_bytes = int(indicators[3]) == 0, last_file = int(indicators[9]) == 0 # We don't use this. ) if binary_file_info.dimensions != 1: msg = "File {} has {} dimensions, expected 1. Is it a BSL file?" raise OTOKOParsingError(msg.format(filename.strip(), binary_file_info.dimensions)) binary_file_info_list.append(binary_file_info) total_frames += binary_file_info.n_frames # Check that all binary files are listed in the header as having the same # number of channels, since I don't think CorFunc can handle ragged data. all_n_channels = [info.n_channels for info in binary_file_info_list] if not all(all_n_channels[0] == c for c in all_n_channels): raise OTOKOParsingError( "Expected all binary files listed in %s to have the same number of channels." % header_path) data = np.zeros(shape=(total_frames, all_n_channels[0])) frames_so_far = 0 for info in binary_file_info_list: if not os.path.exists(info.file_path): raise OTOKOParsingError( "The data file %s does not exist." % info.file_path) with open(info.file_path, "rb") as binary_file: # Ideally we'd like to use numpy's fromfile() to read in binary # data, but we are forced to roll our own float-by-float file # reader because of the rules imposed on us by the file format; # namely, if the swap indicator flag has been raised then the bytes # of each float occur in reverse order. for frame in range(info.n_frames): for channel in range(info.n_channels): b = bytes(binary_file.read(4)) if info.swap_bytes: b = b[::-1] # "Extended slice" syntax, used to reverse. value = struct.unpack('f', b)[0] data[frames_so_far + frame][channel] = value frames_so_far += info.n_frames return CStyleStruct( header_path = header_path, data = data, binary_file_info_list = binary_file_info_list, header_info = info ) sasdata-0.8.1/sasdata/file_converter/red2d_writer.py000066400000000000000000000020041427502211700225310ustar00rootroot00000000000000import os import time from sasdata.dataloader.readers.red2d_reader import Reader as Red2DReader class Red2DWriter(Red2DReader): def write(self, filename, data, thread): """ Write to .dat :param filename: file name to write :param data: data2D """ # Write the file fd = open(filename, 'w') t = time.localtime() time_str = time.strftime("%H:%M on %b %d %y", t) header_str = "Data columns are Qx - Qy - I(Qx,Qy)\n\nASCII data" header_str += " created at %s \n\n" % time_str # simple 2D header fd.write(header_str) # write qx qy I values for i in range(len(data.data)): if thread.isquit(): fd.close() os.remove(filename) return False fd.write("%g %g %g\n" % (data.qx_data[i], data.qy_data[i], data.data[i])) fd.close() return True sasdata-0.8.1/setup.py000066400000000000000000000063011427502211700146530ustar00rootroot00000000000000# -*- coding: utf-8 -*- # !/usr/bin/env python """ Setup for SasData """ import os import shutil import sys from distutils.core import Command from setuptools import setup # Manage version number ###################################### with open(os.path.join("sasdata", "__init__.py")) as fid: for line in fid: if line.startswith('__version__'): print(line) VERSION = line.split('"')[1] break else: raise ValueError("Could not find version in sasdata/__init__.py") ############################################################## package_dir = {} package_data = {} packages = [] # Remove all files that should be updated by this setup # We do this here because application updates these files from .sasdata # except when there is no such file CURRENT_SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) SAS_DATA_BUILD = os.path.join(CURRENT_SCRIPT_DIR, "build") # Optionally clean before build. dont_clean = 'update' in sys.argv if dont_clean: sys.argv.remove('update') elif os.path.exists(SAS_DATA_BUILD): print("Removing existing build directory", SAS_DATA_BUILD, "for a clean build") shutil.rmtree(SAS_DATA_BUILD) class BuildSphinxCommand(Command): description = "Build Sphinx documentation." user_options = [] def initialize_options(self): self.cwd = None def finalize_options(self): self.cwd = os.getcwd() def run(self): """Build the docs from source""" sys.path.append("docs/sphinx-docs") import build_sphinx build_sphinx.rebuild() # _standard_ commands which should trigger the Qt build build_commands = [ 'install', 'build', 'build_py', 'bdist', 'bdist_egg', 'bdist_rpm', 'bdist_wheel', 'develop', 'test' ] # sasdata module package_dir["sasdata"] = os.path.join("sasdata") packages.append("sasdata") # sasdata.dataloader package_dir["sasdata.dataloader"] = os.path.join("sasdata", "dataloader") package_data["sasdata.dataloader.readers"] = ['schema/*.xsd'] packages.extend(["sasdata.dataloader", "sasdata.dataloader.readers", "sasdata.dataloader.readers.schema"]) # sasdata.file_converter package_dir["sasdata.file_converter"] = os.path.join("sasdata", "file_converter") packages.append("sasdata.file_converter") # sasdata.data_util package_dir["sasdata.data_util"] = os.path.join("sasdata", "data_util") packages.append("sasdata.data_util") required = ['lxml', 'h5py', 'numpy', 'pytest<6', 'xmlrunner'] with open('README.md', encoding='utf-8') as f: long_description = f.read() # Set up SasView setup( name="sasdata", version=VERSION, description="Sas Data Loader application", long_description=long_description, long_description_content_type='text/markdown', author="SasView Team", author_email="developers@sasview.org", url="http://sasview.org", license="PSF", keywords="small-angle x-ray and neutron scattering data loading", download_url="https://github.com/SasView/sasdata.git", package_dir=package_dir, packages=packages, package_data=package_data, install_requires=required, zip_safe=False, entry_points={ 'console_scripts': [ "sasview=sasdata.loader.Loader:load", ] } ) sasdata-0.8.1/test/000077500000000000000000000000001427502211700141205ustar00rootroot00000000000000sasdata-0.8.1/test/README.rst000066400000000000000000000015131427502211700156070ustar00rootroot00000000000000Running Tests ============= Tests are stored in subdirectories of the test directory, as *package/utest_\*.py*. Test data, expected output and other support files should be in a subdirectory of the unit test directory. Before running any tests you must first run *setup.py build* in the root. Tests are run against the current source directory with run magic to find the compiled code, so you only need to rebuild between tests if you are modifying the C code. Tests can be run in Eclipse (or other IDE) by selecting *utest_sasview.py* and selecting run. This will run all of the tests. To run tests for one one package, edit the *utest_sasview.py* run command and add the package directory to the command arguments. To run an individual test, select *run_one.py* and edit the command arguments to include the path to the desired test file. sasdata-0.8.1/test/__init__.py000066400000000000000000000000001427502211700162170ustar00rootroot00000000000000sasdata-0.8.1/test/fileconverter/000077500000000000000000000000001427502211700167675ustar00rootroot00000000000000sasdata-0.8.1/test/fileconverter/__init__.py000066400000000000000000000000001427502211700210660ustar00rootroot00000000000000sasdata-0.8.1/test/fileconverter/data/000077500000000000000000000000001427502211700177005ustar00rootroot00000000000000sasdata-0.8.1/test/fileconverter/data/Z83000.I1D000066400000000000000000000005321427502211700210030ustar00rootroot00000000000000ISIS_83404.TXT 121 1 1 1 0 0 0 0 0 1 Z83001.I1D 121 1 1 1 0 0 0 0 0 0 Z83002.I1D sasdata-0.8.1/test/fileconverter/data/Z83000.QAX000066400000000000000000000003761427502211700210650ustar00rootroot00000000000000ISIS_83404.TXT 121 1 1 1 0 0 0 0 0 0 Z83001.QAX 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http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
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canSAS instrument neutron 12.00 13.00 disc 6.00 0.22 1.00 14.3 123.0 50 11.000 1 fictional hybrid 4.150 1 2 1.00 0.00 0.00 322.64 327.68 5.00 5.00 spol 04-Sep-2007 18:35:02 10.000 180.0 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 No Information sasdata-0.8.1/test/fileconverter/data/exp18_14_igor_2dqxqy.dat000066400000000000000000065533001427502211700242070ustar00rootroot00000000000000FILE: HiResSANS_exp18_scan0014_0001.xml CREATED: Mon, Feb 22, 2010 5:36:16 PM LABEL: Scatt 3m 6A cho MON CNT LAMBDA (A) DET_OFF(cm) DET_DIST(m) TRANS THICK(cm) 1e+08 6 0 3 1 0 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 21.167 95.978 0 4 17.495 0.1 76 HiResSANS SAM: HiResSANS_exp18_scan0014_0001.xml BGD: Unknown file from Average_Panel EMP: Unknown file from Average_Panel DIV: Unknown file from Average_Panel MASK: Unknown file from Average_Panel ABS Parameters (3-6): Unknown file from Average_Panel Average Choices: Unknown file from Average_Panel *** Data written from COR folder and may not be a fully corrected data file *** Data columns are Qx - Qy - I(Qx,Qy) - Qz - SigmaQx - SigmaQy - fSubS(beam stop shadow) ASCII data created Mon, Feb 22, 2010 5:39:51 PM -0.03573497 -0.1682965 20745.36 0.01422998 0 0 0 -0.03396493 -0.168306 19341.58 0.01417181 0 0 0 -0.0321946 -0.168315 16256.52 0.01411658 0 0 0 -0.03042399 -0.1683235 22140.47 0.01406431 0 0 0 -0.02865312 -0.1683315 16814.12 0.01401499 0 0 0 -0.02688201 -0.1683391 18494.12 0.01396862 0 0 0 -0.02511066 -0.1683462 16251.27 0.01392521 0 0 0 -0.0233391 -0.1683528 17370.97 0.01388475 0 0 0 -0.02156734 -0.1683589 19611.32 0.01384725 0 0 0 -0.01979539 -0.1683645 20170.69 0.0138127 0 0 0 -0.01802327 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sasdata-0.8.1/test/fileconverter/utest_bsl_loader.py000066400000000000000000000023431427502211700226750ustar00rootroot00000000000000import os import os.path import unittest from xml.etree import ElementTree as ET import numpy as np from sasdata.file_converter.bsl_loader import BSLLoader def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class bsl_test(unittest.TestCase): def setUp(self): self.read_file_q = find("Z83000.QAX") self.read_file_i = find("Z83000.I1D") self.q_reader = BSLLoader(self.read_file_q) self.i_reader = BSLLoader(self.read_file_i) def test_load(self): #Load the data from bsl files. q_data_load = self.q_reader.load_data(0) i_data_load = self.i_reader.load_data(0) #Load the correct data (in Z83000.xml) tree = ET.parse(find('Z83000.xml')) root = tree.getroot() q_data_correct = [elem.text for elem in root.iter('{cansas1d/1.0}Q')] i_data_correct = [elem.text for elem in root.iter('{cansas1d/1.0}I')] q_data_array = np.array(q_data_correct, dtype=np.float64) i_data_array = np.array(i_data_correct, dtype=np.float64) q_test = np.allclose(q_data_array, q_data_load, atol=1e-13) q_test = np.allclose(i_data_array, i_data_load, atol=1e-13) self.assertTrue(q_test) sasdata-0.8.1/test/fileconverter/utest_nxcansas_writer.py000066400000000000000000000053631427502211700240060ustar00rootroot00000000000000from sasdata.file_converter.nxcansas_writer import NXcanSASWriter from sasdata.dataloader.loader import Loader import os import os.path import unittest import warnings warnings.simplefilter("ignore") def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class nxcansas_writer(unittest.TestCase): def setUp(self): self.loader = Loader() self.writer = NXcanSASWriter() self.read_file_1d = find("cansas1d.xml") self.write_file_1d = find("export1d.h5") self.read_file_2d = find("exp18_14_igor_2dqxqy.dat") self.write_file_2d = find("export2d.h5") self.data_1d = self.loader.load(self.read_file_1d)[0] self.data_2d = self.loader.load(self.read_file_2d)[0] self.data_2d.detector[0].name = '' self.data_2d.source.radiation = 'neutron' def test_write_1d(self): self.writer.write([self.data_1d], self.write_file_1d) data = self.loader.load(self.write_file_1d) self.assertTrue(len(data) == 1) data = data[0] self.assertTrue(len(data.x) == len(self.data_1d.x)) self.assertTrue(len(data.y) == len(self.data_1d.y)) self.assertTrue(len(data.dy) == len(self.data_1d.dy)) self._check_metadata(data, self.data_1d) def test_write_2d(self): self.writer.write([self.data_2d], self.write_file_2d) data = self.loader.load(self.write_file_2d) self.assertTrue(len(data) == 1) data = data[0] self.assertTrue(len(data.data) == len(self.data_2d.data)) self.assertTrue(len(data.qx_data) == len(self.data_2d.qx_data)) self.assertTrue(len(data.qy_data) == len(self.data_2d.qy_data)) self._check_metadata(data, self.data_2d) def _check_metadata(self, written, correct): self.assertTrue(written.title == correct.title) self.assertTrue(written.sample.name == correct.sample.name) self.assertAlmostEqual(written.sample.thickness, correct.sample.thickness) self.assertAlmostEqual(written.sample.temperature, correct.sample.temperature) self.assertTrue(written.instrument == correct.instrument) self.assertTrue(len(written.detector) == len(correct.detector)) for i in range(len(written.detector)): written_det = written.detector[i] correct_det = correct.detector[i] self.assertAlmostEqual(written_det.distance, correct_det.distance) self.assertTrue(written_det.name == correct_det.name) self.assertTrue(written.source.probe == correct.source.radiation) def tearDown(self): if os.path.isfile(self.write_file_1d): os.remove(self.write_file_1d) if os.path.isfile(self.write_file_2d): os.remove(self.write_file_2d) sasdata-0.8.1/test/logging.ini000066400000000000000000000017501427502211700162520ustar00rootroot00000000000000 ############################################################################### ################################### LOGGING ################################### ############################################################################### [formatters] keys=simple,detailed [formatter_simple] format=%(name)s: %(levelname)s: %(message)s [formatter_detailed] format=%(name)s: %(levelname)s %(module)s: %(lineno)d: %(message)s ############################################################################### # Handlers [handlers] keys=console,log_file [handler_console] class=logging.StreamHandler formatter=simple level=DEBUG args=tuple() [handler_log_file] class=logging.FileHandler level=INFO formatter=detailed args=('tests.log','w') ############################################################################### # Loggers [loggers] keys=root,sas [logger_root] level=DEBUG handlers=console,log_file propagate=0 [logger_sas] level=INFO qualname=sas handlers=console,log_file propagate=0sasdata-0.8.1/test/run_one.py000066400000000000000000000020351427502211700161370ustar00rootroot00000000000000#!/usr/bin/env python import os import sys import xmlrunner import unittest import importlib.util from os.path import abspath, split as splitpath import logging logger = logging.getLogger(__name__) if not logger.root.handlers: import logging.config LOGGER_CONFIG_FILE = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'logging.ini') logging.config.fileConfig(LOGGER_CONFIG_FILE, disable_existing_loggers=False) if len(sys.argv) < 2: logger.error("Use %s ", sys.argv[0]) sys.exit(-1) test_path_abs = abspath(sys.argv[1]) test_path, f_name_full = splitpath(abspath(sys.argv[1])) f_name = f_name_full.split('.')[0] #print("=== testing:", sys.argv[1]) sys.argv = [sys.argv[0]] os.chdir(test_path) sys.path.insert(0, test_path) #print("\n".join(sys.path)) foo = importlib.util.spec_from_file_location('tests', f_name_full) test = importlib.util.module_from_spec(foo) sys.modules['tests'] = test foo.loader.exec_module(test) #print(test) unittest.main(test, testRunner=xmlrunner.XMLTestRunner(output='logs')) sasdata-0.8.1/test/sasdataloader/000077500000000000000000000000001427502211700167275ustar00rootroot00000000000000sasdata-0.8.1/test/sasdataloader/__init__.py000066400000000000000000000000001427502211700210260ustar00rootroot00000000000000sasdata-0.8.1/test/sasdataloader/data/000077500000000000000000000000001427502211700176405ustar00rootroot00000000000000sasdata-0.8.1/test/sasdataloader/data/FEB18012.ASC000066400000000000000000001227561427502211700211750ustar00rootroot00000000000000FILE: FEB18012.SA4_NG7_Z473 CREATED: 14-FEB-2018 10:01:53 LABEL: Teflon Alignment 1m Scatt MON CNT LAMBDA(A) DET_OFF(cm) DET_DIST(m) TRANS THICK(cm) COUNT TIME 5.0808e+05 6 25 1 1 0.1 26 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 115.51 65.78 50.8 12.7 3.876 0.115 50.8 ORNL PIXELS(X) PIXELS(Y) PIXELSIZE X (mm) PIXELSIZE Y (mm) 128 128 5.08 5.08 SAM: RAW Data File: FEB18012.SA4_NG7_Z473 BGD: none EMP: none DIV: none MASK: none ABS Parameters (3-6): none Average Choices: none *** Data written from RAW folder and may not be a fully corrected data file *** The detector image is a standard X-Y coordinate system Data is written by row, starting with Y=1 and X=(1->128) RAW SAM FILE FEB18012.SA4_NG7_Z473 TIMESTAMP: 14-FEB-2018 10:01:53 19 12 12 8 18 9 14 8 11 13 15 12 21 8 21 12 10 14 11 12 15 11 15 15 14 19 22 17 16 11 15 21 10 21 12 11 14 12 14 15 14 16 12 12 14 12 17 16 20 12 18 15 12 18 9 14 19 15 16 13 16 19 9 20 12 22 15 16 13 14 20 14 17 15 23 18 26 15 23 15 14 17 14 17 23 20 21 9 18 19 19 17 19 18 21 25 15 17 13 14 23 27 9 18 27 26 12 17 21 19 10 21 24 14 21 21 23 15 23 24 19 18 15 17 17 33 16 37 4 7 9 9 12 5 6 9 9 6 5 5 11 7 7 10 6 6 3 9 7 6 8 9 11 8 11 5 2 6 6 5 10 7 9 5 7 10 7 7 7 9 12 8 5 8 8 4 6 7 8 9 10 6 11 12 9 10 4 12 9 7 11 10 10 4 15 5 11 8 7 8 10 8 6 6 8 8 9 8 7 11 11 2 15 14 10 11 7 12 11 9 13 9 10 9 10 7 11 9 11 7 9 14 6 12 11 16 9 18 9 12 5 8 7 10 5 8 7 13 11 15 8 8 12 9 8 6 7 6 5 4 4 5 4 8 9 10 6 7 4 8 2 9 11 9 8 8 7 10 9 8 13 10 6 10 6 5 6 5 7 6 6 6 8 8 7 10 5 9 5 9 5 7 9 7 5 3 5 6 7 6 14 6 6 12 3 9 8 9 6 8 10 5 4 9 6 10 14 13 15 10 3 7 6 13 7 5 6 7 9 7 10 13 4 10 7 4 10 11 5 8 12 11 7 9 15 8 13 6 8 10 13 13 16 11 7 8 4 18 11 21 19 10 13 11 9 15 10 11 13 10 9 5 11 9 3 10 4 3 5 8 6 6 8 11 9 5 2 4 8 9 9 4 8 9 7 7 4 2 4 4 3 5 9 4 9 7 3 6 9 9 10 11 4 6 10 2 9 8 5 13 11 7 15 5 7 14 6 5 8 8 5 11 3 4 8 12 3 12 9 9 6 7 9 11 9 9 7 9 4 6 7 14 6 10 5 10 10 11 12 9 10 9 12 6 6 10 12 8 8 6 11 9 14 9 12 8 12 11 11 14 12 5 9 17 18 5 7 10 10 10 9 7 9 16 9 13 9 13 12 9 8 11 2 7 5 9 4 9 7 5 10 10 8 2 2 9 10 6 6 7 8 4 8 6 4 7 6 11 13 6 4 12 8 9 5 7 5 8 8 4 8 9 4 9 6 5 5 12 10 10 8 4 5 6 7 4 10 6 4 5 5 10 10 9 7 9 8 7 12 10 12 13 11 11 8 7 15 10 8 9 12 12 11 9 9 1 16 11 6 8 6 5 9 12 19 11 6 8 7 9 6 10 5 12 8 11 11 12 13 7 5 9 13 7 15 8 10 13 11 7 17 7 13 10 6 12 9 3 9 11 3 4 7 5 4 2 6 8 6 2 5 9 7 3 5 7 5 8 7 4 5 5 9 7 6 8 10 6 13 11 8 5 4 8 8 9 7 7 4 5 4 9 10 4 11 4 8 8 12 8 5 9 3 11 8 8 11 10 8 8 11 9 8 6 10 12 9 8 9 14 7 8 8 7 4 9 12 9 11 8 4 10 9 10 12 5 6 13 15 10 5 9 9 8 12 3 14 6 11 8 10 10 6 10 9 8 9 11 8 8 13 6 11 7 10 11 6 10 10 10 14 13 5 7 13 8 12 9 8 6 7 7 6 7 7 6 4 5 6 8 10 4 7 6 4 5 9 4 5 14 11 4 9 1 6 5 10 8 4 6 9 8 11 8 6 5 4 6 12 7 5 8 3 9 8 6 8 9 6 11 11 12 6 9 8 7 15 3 4 15 6 13 6 15 10 8 10 10 9 7 6 6 13 13 7 12 10 4 6 10 4 8 8 6 14 6 10 7 8 7 17 16 11 8 13 10 9 12 7 15 16 14 7 13 13 4 6 10 12 12 9 10 8 11 12 13 4 11 8 8 14 12 11 8 9 11 4 7 8 12 5 8 10 7 6 5 8 7 7 6 8 10 9 4 5 9 8 5 4 8 4 6 7 13 7 6 6 10 8 6 7 7 6 8 10 8 11 8 6 9 9 4 8 9 5 6 9 3 7 10 8 9 9 11 14 15 9 5 6 8 8 14 5 5 4 8 11 5 3 6 14 13 5 8 12 8 11 8 9 12 13 9 9 5 7 7 14 10 8 9 10 6 9 8 16 9 10 13 11 18 10 7 8 12 14 7 8 9 11 6 6 11 11 9 11 8 13 7 13 11 16 11 10 11 5 5 7 3 4 9 9 6 9 7 8 5 8 9 4 5 5 6 9 7 5 6 10 7 8 4 6 4 8 6 4 5 9 9 5 12 13 11 7 4 9 10 13 4 10 5 10 6 9 11 11 10 8 7 4 14 5 6 8 11 8 5 10 7 7 9 12 11 13 6 8 7 13 10 11 13 7 10 8 5 9 8 7 7 9 12 9 11 13 15 9 5 7 12 8 10 10 9 7 14 10 10 10 11 6 18 10 8 13 11 14 6 7 7 11 11 11 8 10 13 7 9 12 12 11 13 7 12 5 6 7 5 9 8 3 7 10 6 7 3 10 8 9 10 2 6 4 9 8 9 7 7 9 9 11 4 8 13 7 3 8 8 6 11 10 6 9 10 11 8 5 7 7 6 4 10 6 10 6 11 11 8 11 9 9 9 7 12 14 9 12 5 9 7 4 8 5 8 7 14 11 10 7 10 11 15 7 9 10 6 11 13 4 7 10 12 11 11 15 9 8 18 8 5 11 11 8 7 11 6 6 13 12 14 8 11 6 12 5 8 12 6 12 7 9 5 9 13 14 14 10 7 8 6 8 10 10 4 6 3 2 14 10 3 12 3 6 7 5 5 2 9 4 7 7 6 5 6 5 5 6 5 9 2 10 8 6 10 6 5 5 10 10 10 8 5 8 3 9 8 11 14 11 8 8 9 11 7 6 7 5 8 9 7 5 10 3 8 10 9 11 12 15 4 5 10 10 6 7 8 10 6 12 9 10 8 6 9 12 10 2 9 9 9 13 13 12 7 9 14 12 4 13 8 7 21 12 13 8 2 6 12 8 16 9 10 11 7 11 15 11 12 12 18 16 13 12 14 9 11 17 11 12 19 3 8 10 4 5 11 9 3 5 2 6 3 8 8 5 8 10 6 7 6 8 10 6 7 8 6 9 7 12 4 5 4 6 10 6 7 5 10 5 9 6 8 5 12 8 7 11 5 6 7 8 8 9 11 13 8 8 3 13 15 15 11 9 11 10 9 9 9 6 10 9 7 8 8 10 10 4 10 12 11 8 4 5 6 11 8 9 7 7 6 11 7 9 15 8 9 6 12 8 11 13 9 9 14 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5 6 6 3 6 3 4 9 8 8 5 3 12 6 10 5 7 7 9 2 10 6 9 7 9 5 6 7 8 7 6 10 5 8 9 8 9 4 5 5 8 5 10 9 9 9 7 9 8 9 6 13 6 8 6 7 6 6 6 12 10 17 14 7 5 12 6 14 9 9 11 10 11 8 10 12 4 14 11 2 4 13 18 10 13 10 11 11 8 7 13 6 3 12 9 13 15 11 9 11 12 12 7 10 10 12 10 13 8 11 7 20 12 5 9 11 18 8 9 6 9 11 13 10 13 13 4 6 5 9 9 9 6 5 7 11 10 3 6 6 11 7 13 6 1 9 4 9 11 7 11 2 5 7 10 11 8 6 3 7 17 7 6 4 6 5 10 8 7 9 14 13 5 10 7 10 10 5 11 9 15 10 7 6 11 5 10 11 14 8 10 8 13 13 6 7 18 8 15 11 11 5 14 7 11 9 11 11 16 7 13 11 7 10 13 11 13 5 10 18 14 14 10 7 10 9 11 6 11 19 9 7 8 11 14 13 12 11 2 8 16 16 13 12 8 9 8 11 9 13 8 15 23 7 6 10 11 8 4 7 6 5 7 9 7 7 4 6 8 8 7 10 14 4 7 4 8 9 6 9 10 10 6 7 2 7 11 8 9 7 8 17 8 9 4 5 12 10 8 9 6 11 7 11 11 8 7 9 5 7 15 13 12 10 7 7 4 5 6 13 5 16 12 11 11 8 9 9 9 6 12 11 4 16 8 7 9 8 11 11 10 9 12 8 12 13 8 12 14 10 10 10 11 13 13 8 14 12 10 8 17 8 6 10 13 10 8 11 11 22 12 14 8 17 15 11 13 9 10 12 9 6 7 4 6 8 8 10 10 9 14 6 3 5 11 6 6 8 5 7 10 11 4 8 10 9 5 5 7 7 7 13 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10 8 6 10 9 17 8 10 9 9 7 13 15 14 11 17 15 11 9 12 10 19 9 10 19 12 8 15 16 3 9 11 13 14 12 11 11 8 18 13 8 8 8 3 7 8 6 6 14 8 9 9 12 11 11 5 3 7 8 11 7 15 8 9 11 3 6 13 8 8 7 14 7 5 6 3 13 11 9 6 10 7 13 16 13 14 8 12 10 9 9 8 8 7 8 10 10 9 8 8 5 6 12 15 12 6 9 14 16 12 10 8 12 15 12 13 10 8 6 17 12 20 7 12 18 13 20 13 17 13 8 13 10 15 7 11 20 9 16 18 8 14 20 16 25 13 18 11 13 11 19 10 10 20 14 16 16 19 17 15 15 8 15 10 11 17 20 20 9 0 5 6 4 7 10 8 3 4 8 6 8 6 8 8 7 7 12 4 10 10 7 6 6 3 12 7 7 9 12 2 10 8 7 3 12 9 10 9 9 12 6 10 5 9 3 8 5 12 7 8 9 12 10 10 9 7 7 11 8 6 8 7 9 7 15 12 12 15 12 10 7 10 9 11 14 14 15 11 16 10 10 14 10 9 10 8 13 11 9 8 10 12 13 10 13 8 11 8 10 9 11 13 16 13 19 14 23 16 16 7 12 7 15 10 12 13 5 8 7 14 10 12 8 17 12 19 11 4 5 7 3 5 7 11 4 14 13 4 10 9 4 6 5 6 8 15 6 5 12 6 8 13 8 12 12 4 7 8 7 8 8 2 8 11 11 12 10 16 12 4 4 8 10 5 5 11 7 10 7 8 7 12 5 16 5 10 7 10 8 9 11 13 7 9 13 9 8 13 16 10 10 7 16 18 11 13 14 10 15 14 13 9 13 10 12 12 26 19 4 12 10 12 7 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sasdata-0.8.1/test/sasdataloader/data/ISIS_1_0.xml000066400000000000000000000442331427502211700215760ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.00985.33330.8524910 0.01172.53980.6395480 0.01363.35820.4941270 0.01557.09520.4141160 0.01751.01390.351450 0.01946.47460.3087550 0.02141.71910.2716410 0.02337.42080.2446580 0.02533.73520.2195940 0.02730.60730.2031380 0.02927.73090.1858590 0.03125.25790.1713560 0.03322.77120.1590620 0.03520.53230.1461350 0.03719.07440.1363930 0.03917.28320.1276230 0.04115.73990.1182880 0.04314.55980.1117590 0.04513.59060.1051480 0.04712.67070.09965790 0.04911.52470.09296460 0.05110.70890.08885750 0.05310.14360.08493940 0.0559.494460.08112050 0.0578.807750.07739670 0.0598.333660.07481470 0.0617.791570.07201070 0.0637.259020.06935820 0.0657.047890.06775910 0.0676.533110.06522070 0.0696.24530.06420160 0.0715.941520.06257680 0.0735.708160.06129550 0.0755.244490.0601410 0.0775.082910.05822390 0.0794.881350.0579690 0.0814.609420.0568130 0.0834.466060.05693810 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1.74845e-2873771.186.28301 1.24882e-2903732.396.50291 NaN3291.096.73051 NaN2837.176.96608 NaN2529.377.2099 NaN2226.827.46224 1.07499e+1021960.887.72342 3.32977e-3111653.27.99374 7.19961e-3101446.058.27352 7.19962e-3101242.78.56309 8.20107e-3161046.318.8628 3.18299e-314895.0699.173 7.42699e-314727.5439.49406 4.24399e-314598.1719.82867 3.16202e-322-8.61158e-315-3.78577e-270 02.23850.00307782 02.316850.00300224 3.53041e-3152.397940.00292546 TK49 c10_SANS LOQ neutron HAB 0.575 main-detector-bank 4.14502 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt sasdata-0.8.1/test/sasdataloader/data/ISIS_1_1_doubletrans.xml000066400000000000000000001443771427502211700242130ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.00985.33330.8524910 0.01172.53980.6395480 0.01363.35820.4941270 0.01557.09520.4141160 0.01751.01390.351450 0.01946.47460.3087550 0.02141.71910.2716410 0.02337.42080.2446580 0.02533.73520.2195940 0.02730.60730.2031380 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-2.37127e+2260.01058775767.32 2.86442e+1260.01058955694.24 5.52737e-3090.01090265525.05 1.46672e-3100.01083995417.49 1.66641e+1780.01105175253.01 1.66641e+1780.01102095074.68 8.62375e+2110.01118824929.65 8.62375e+2110.01101454745.3 2.03531e-870.01103234841.86 2.97389e-390.01104564897.12 2.97389e-390.01096894974.21 1.18818e-2120.01067184586.67 4.38734e+2450.01072764948.31 4.38734e+2450.01054545184.8 -1.81729e+1310.01065945008.83 -1.81729e+1310.01077674940.5 6.44115e-2320.01071334859.81 6.44115e-2320.01091614602.81 4.36995e+2450.01139424362.55 4.36995e+2450.01147884081.97 2.9782e-390.01206553771.18 5.83667e-730.01196843732.39 1.74941e+640.01257973291.09 1.74941e+640.01353242837.17 -1.81729e+1310.01401292529.37 -1.81729e+1310.0148372226.82 4.40721e-2800.0159851960.88 4.40721e-2800.01674491653.2 1.84467e+190.01816481446.05 5.67321e+2160.01972141242.7 4.49371e+2450.02050811046.31 4.49371e+2450.0219522895.069 4.69054e+1920.0248015727.543 8.62169e+2110.0263197598.171 8.62169e+211-8.61158e-315-8.61158e-315 3.74996e-683919.892.2385 8.75213e-784462.632.31685 -3.14339e-3154830.612.39794 1.08255e-2265193.212.48186 1.07499e+1025501.582.56873 1.07499e+1025628.962.65864 1.07508e+1025634.752.75169 1.07508e+1025724.732.848 3.81253e-3035835.492.94768 1.35808e-3125798.973.05085 1.07513e+1025767.323.15763 1.07513e+1025694.243.26814 4.38311e-3155525.053.38253 8.52704e-3165417.493.50092 05253.013.62345 05074.683.75027 04929.653.88153 3.54616e-3154745.34.01738 3.54616e-3154841.864.15799 2.71357e+1044897.124.30352 2.72432e+1044974.214.45414 2.15015e+1024586.674.61004 1.07508e+1024948.314.77139 3.53041e-3155184.84.93839 05008.835.11123 04940.55.29012 2.00379e-2704859.815.47528 2.00379e-2704602.815.66691 4.58351e-3124362.555.86525 1.7472e-2874081.976.07054 1.74845e-2873771.186.28301 1.24882e-2903732.396.50291 NaN3291.096.73051 NaN2837.176.96608 NaN2529.377.2099 NaN2226.827.46224 1.07499e+1021960.887.72342 3.32977e-3111653.27.99374 7.19961e-3101446.058.27352 7.19962e-3101242.78.56309 8.20107e-3161046.318.8628 3.18299e-314895.0699.173 7.42699e-314727.5439.49406 4.24399e-314598.1719.82867 3.16202e-322-8.61158e-315-3.78577e-270 02.23850.00307782 02.316850.00300224 3.53041e-3152.397940.00292546 TK49 c10_SANS LOQ neutron HAB 0.575 main-detector-bank 4.14502 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt sasdata-0.8.1/test/sasdataloader/data/ISIS_1_1_notrans.xml000066400000000000000000000442211427502211700233400ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.00985.33330.8524910 0.01172.53980.6395480 0.01363.35820.4941270 0.01557.09520.4141160 0.01751.01390.351450 0.01946.47460.3087550 0.02141.71910.2716410 0.02337.42080.2446580 0.02533.73520.2195940 0.02730.60730.2031380 0.02927.73090.1858590 0.03125.25790.1713560 0.03322.77120.1590620 0.03520.53230.1461350 0.03719.07440.1363930 0.03917.28320.1276230 0.04115.73990.1182880 0.04314.55980.1117590 0.04513.59060.1051480 0.04712.67070.09965790 0.04911.52470.09296460 0.05110.70890.08885750 0.05310.14360.08493940 0.0559.494460.08112050 0.0578.807750.07739670 0.0598.333660.07481470 0.0617.791570.07201070 0.0637.259020.06935820 0.0657.047890.06775910 0.0676.533110.06522070 0.0696.24530.06420160 0.0715.941520.06257680 0.0735.708160.06129550 0.0755.244490.0601410 0.0775.082910.05822390 0.0794.881350.0579690 0.0814.609420.0568130 0.0834.466060.05693810 0.0854.324730.05587660 0.0874.141440.05525250 0.0893.865040.05445690 0.0913.742720.05295960 0.0933.682810.0528910 0.0953.469910.05175650 0.0973.372440.05093280 0.0993.270740.05051830 0.1013.133260.04908470 0.1033.013870.04870120 0.1052.876280.04843070 0.1072.850430.04767860 0.1092.727990.04755260 0.1112.612060.04674750 0.1132.588950.04697670 0.1152.459870.04601390 0.1172.377230.0452720 0.1192.341220.04537410 0.1212.217450.04444850 0.1232.126460.04383850 0.1252.112640.04416620 0.1272.075230.04389790 0.1292.035480.04424220 0.1311.924520.04359590 0.1331.908660.04374010 0.1351.912520.04431630 0.1371.804050.0434660 0.1391.721660.04292460 0.1411.671990.0424690 0.1431.632820.04300740 0.1451.637120.04385570 0.1471.58620.04341350 0.1491.561210.04325910 0.1511.497640.04265770 0.1531.538280.04464810 0.1551.473660.04419730 0.1571.405820.04304610 0.1591.404910.04398830 0.1611.346390.0441930 0.1631.322380.04380080 0.1651.338850.04453830 0.1671.296080.04515750 0.1691.305620.04606560 0.1711.171470.04357170 0.1731.185650.04490720 0.1751.189440.04653190 0.1771.170550.04565620 0.1791.085710.04538520 0.1811.062080.04633350 0.1831.061870.04582840 0.1851.027270.04726130 0.1870.9951690.04655260 0.1891.025690.04837280 0.1910.9811540.04905590 0.1931.018310.05023480 0.1950.9681020.05044260 0.1970.9406560.05127340 0.1991.057620.05474690 0.2010.9498720.0552290 0.2030.8917160.05313460 0.2050.8760840.05486810 0.2070.9321010.05768120 0.2090.9277550.05934040 0.2110.876690.06003690 0.2130.8091250.05881070 0.2150.9412020.06591210 0.2170.9461750.06907840 0.2190.8598750.06744350 0.2210.9595080.07188560 0.2230.7632220.07028660 0.2250.7854670.07421440 0.2270.818760.0742660 0.2290.6783110.07225780 0.2310.7614420.08145160 0.2330.7570760.08252620 0.2350.6006360.0750410 0.2370.6856350.08423920 0.2390.7991860.09743650 0.2410.7375260.09572860 0.2430.7164150.09704480 0.2450.7204130.09819960 0.2470.6040590.1008690 0.2490.6490730.1092810 0.2510.7006910.1143250 0.2530.5867890.1083240 0.2550.7658380.1395790 0.2570.8289680.1567230 0.2590.6164990.1378660 0.2610.5260110.1262090 0.2630.512770.1263390 0.2650.6041890.1663930 0.2670.7387650.1940060 0.2690.4628030.1553540 0.2710.4786940.1716760 0.2730.7119830.2555390 0.2750.4733040.2307520 0.2770.5368170.2626270 0.2790.6606540.2975190 0.2810.4089020.245850 0.283000 TK49 c10_SANS LOQ neutron HAB 0.575 main-detector-bank 4.14502 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt 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6.51516 2.69182 6.44323 2.69114 3.83422 2.06514 5.47745 2.45223 4.88667 2.34121 6.57294 2.69881 5.99631 2.55951 7.0988 2.79357 5.34774 2.44721 6.0252 2.57529 9.81563 3.2737 5.47745 2.4572 3.83422 2.07115 2.73873 1.77308 8.74203 3.09348 4.36007 2.18937 6.99158 2.79242 4.90782 2.32464 8.74203 3.08549 4.90782 2.33524 3.74754 2.06229 4.31003 2.18861 3.28647 1.90944 6.52991 2.68425 3.78343 2.06784 6.57294 2.6881 6.55105 2.68218 6.57294 2.68041 7.61765 2.88828 3.76154 2.07004 3.74815 2.06485 4.90782 2.34406 3.75454 2.05814 6.0252 2.56564 6.45798 2.69123 3.26458 1.9316 3.83422 2.06315 5.96027 2.56328 4.92971 2.34742 2.70983 1.76393 4.92971 2.32804 4.92971 2.32263 9.24674 3.17044 5.90248 2.57537 1.61434 1.39882 1.0666 1.15321 5.47745 2.45562 4.38196 2.19864 3.83422 2.05711 3.83422 2.05518 4.87892 2.34627 6.54405 2.68378 5.35399 2.44839 3.23569 1.92095 5.47745 2.45722 8.699 3.09541 8.71314 3.08302 5.47745 2.4455 4.92971 2.31731 9.24674 3.17694 5.99631 2.56429 6.57294 2.67732 5.93913 2.58472 3.25758 1.92501 11.4449 3.52852 4.90782 2.3317 6.00331 2.58037 10.3133 3.37237 4.90082 2.33204 3.26458 1.91616 4.38196 2.21544 7.05576 2.80009 4.90082 2.32832 6.52991 2.68884 6.57294 2.67116 4.35307 2.22326 5.8672 2.59696 5.43442 2.46479 6.52916 2.68236 8.21618 2.99852 1.57831 1.403 7.63954 2.89386 7.04876 2.79438 4.88667 2.33227 6.0252 2.57689 2.73873 1.74465 5.43442 2.46646 7.58876 2.89146 7.12069 2.80373 5.96741 2.60148 9.7656 3.28816 4.36007 2.21194 7.59651 2.89724 3.79043 2.06352 3.28647 1.93519 3.24344 1.95533 3.79118 2.09376 3.17151 1.91605 3.26458 1.929 3.23569 1.90808 3.28647 1.89637 5.44856 2.50246 4.87892 2.40182 6.57294 2.73833 4.92971 2.39106 9.81638 3.31659 4.88667 2.41079 2.19098 1.6172 6.00331 2.61359 4.38196 2.23958 2.71683 1.79174 3.79118 2.09189 4.33893 2.2088 8.692 3.10476 1.09549 1.21222 6.52216 2.69481 3.79118 2.08197 7.61765 2.89971 4.85778 2.3661 6.00331 2.57231 8.699 3.10876 5.38363 2.46865 5.47745 2.46575 4.92971 2.35614 3.22154 1.93206 3.7404 2.0705 9.31167 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2.46576 8.71314 3.09238 7.63954 2.89236 7.0769 2.78787 7.66844 2.88354 6.52991 2.68425 4.31703 2.20902 4.90082 2.32661 6.48687 2.67718 3.76229 2.0703 8.17239 3.00015 5.99631 2.56434 3.28647 1.9374 5.95327 2.56346 6.47912 2.69078 6.57294 2.69425 5.96741 2.57289 8.17315 2.99639 3.28647 1.90723 5.38363 2.45021 3.76229 2.05232 6.48612 2.66935 6.55105 2.68214 5.99631 2.57878 5.39138 2.45208 7.0988 2.78619 9.28978 3.18938 6.98383 2.79217 6.0252 2.56733 6.00331 2.58191 3.26458 1.9075 4.90782 2.33177 6.57294 2.68651 3.24344 1.92544 7.01912 2.78398 7.05576 2.80603 7.07765 2.78229 5.97441 2.58212 10.4072 3.36407 5.89609 2.58699 7.0918 2.79227 5.93913 2.57661 7.63954 2.90389 5.45556 2.46582 5.41253 2.47332 6.49327 2.69809 3.80532 2.06352 4.33893 2.19562 8.15839 3.01691 13.6647 3.87383 8.699 3.12714 5.47745 2.46742 6.0252 2.62293 4.82174 2.36842 5.42667 2.47626 5.41253 2.47487 8.19429 3.00411 3.81232 2.09318 2.6738 1.78801 5.47745 2.47915 5.45556 2.45576 3.79118 2.05603 5.32585 2.49264 9.26864 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9.26089 3.17026 6.57294 2.69586 3.79118 2.07392 6.45723 2.69574 8.76393 3.0947 3.28647 1.9245 7.63954 2.89098 6.57294 2.68658 5.98216 2.56486 8.15839 3.00467 4.88667 2.31984 5.41253 2.45144 7.0918 2.79672 7.0988 2.79506 6.57294 2.68524 3.79118 2.05184 9.28278 3.19203 8.18729 3.01802 5.98216 2.58881 4.35307 2.20466 2.6738 1.76493 6.0252 2.5624 7.53933 2.89123 7.12069 2.78309 6.54405 2.6853 5.93138 2.57811 10.8322 3.46207 7.01987 2.79629 8.21618 2.99585 7.0988 2.80241 9.23974 3.18478 5.42667 2.46777 4.92971 2.3333 7.0699 2.78796 5.47745 2.48072 7.07765 2.79864 8.18729 2.98236 4.85778 2.33614 8.70614 3.08991 6.0252 2.56889 3.7404 2.0766 7.02687 2.79018 7.12069 2.82435 3.80532 2.07353 7.12069 2.7875 6.52916 2.68078 5.47745 2.484 8.76393 3.08264 5.99631 2.58525 6.48612 2.68003 8.76393 3.09062 9.85942 3.27223 6.3923 2.70098 6.47212 2.68941 5.44856 2.4493 8.71314 3.10299 3.24344 1.94248 4.90782 2.3669 5.99631 2.58999 4.82889 2.35768 6.46437 2.70924 4.90082 2.35649 6.49327 2.70725 3.76229 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2.68819 6.0252 2.59759 7.01212 2.8166 4.90782 2.36336 4.90082 2.33373 6.00331 2.57712 6.0252 2.58162 4.90782 2.31754 3.79118 2.06204 6.57294 2.68963 8.72014 3.08028 4.88667 2.33586 4.92971 2.34038 8.74203 3.08543 8.16539 2.98382 3.83422 2.09105 6.00331 2.55948 6.57294 2.69277 9.26864 3.17806 4.35307 2.1914 5.44856 2.43906 14.2414 3.91903 5.43442 2.44636 3.17851 1.92235 7.6254 2.8915 3.28647 1.92456 7.0918 2.78785 5.44856 2.44245 5.98216 2.57764 6.52991 2.67655 8.21618 2.98885 6.00331 2.5724 5.47745 2.46753 9.80863 3.27387 6.52916 2.67918 9.31167 3.19695 4.267 2.18193 7.07765 2.79709 5.47745 2.4572 4.90782 2.32457 8.76393 3.08545 5.44856 2.4441 7.0699 2.79092 7.04876 2.78866 4.71317 2.35408 7.64654 2.88651 7.05576 2.79734 9.85942 3.26707 7.04876 2.77807 8.21618 2.98341 7.12069 2.79785 7.64654 2.87648 6.54405 2.70216 7.64654 2.90528 6.0252 2.58173 7.12069 2.78604 5.98141 2.58223 6.0252 2.56093 4.29528 2.20907 3.79043 2.08549 5.38363 2.44667 6.57294 2.68967 8.72089 3.08722 8.14425 2.98851 7.12069 2.80087 7.60351 2.89718 3.28647 1.91383 5.96027 2.57146 4.90082 2.33013 6.52991 2.69642 7.57386 2.88872 10.2992 3.36673 6.00331 2.56745 6.57294 2.68958 9.80863 3.26999 4.33893 2.21268 8.76393 3.09208 10.9549 3.44893 4.31703 2.21271 6.00331 2.57067 6.0252 2.58648 10.3641 3.377 9.85942 3.26838 4.38196 2.20424 10.3133 3.35404 7.64654 2.88944 9.83752 3.27229 8.21618 2.98747 5.42667 2.4613 8.76393 3.08275 9.26089 3.17801 4.92971 2.34387 8.699 3.08758 8.72089 3.08724 7.63954 2.89096 4.35307 2.18588 8.18729 2.99202 6.57294 2.68352 3.7185 2.07471 4.38196 2.18357 8.18729 2.996 11.4377 3.53813 3.71925 2.05745 4.21621 2.18799 4.31703 2.20897 6.00331 2.57559 8.72014 3.09909 7.61765 2.88112 8.76393 3.0933 8.16539 2.99069 5.40553 2.45495 6.49327 2.67502 6.52991 2.68262 5.47745 2.47563 2.69494 1.77104 8.12236 3.00505 2.6738 1.74608 8.66235 3.09682 8.76393 3.09062 8.76393 3.088 7.0918 2.79384 10.3352 3.35756 7.04876 2.8341 4.38196 2.22473 7.00497 2.80951 6.54405 2.67924 4.87192 2.3586 8.76393 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2.87947 3.83422 2.06716 7.6254 2.89701 8.11536 2.99834 2.73873 1.76111 5.97441 2.57591 7.66844 2.88788 4.92971 2.32086 10.9549 3.45735 4.90782 2.33006 9.25389 3.18581 7.01273 2.80082 4.90082 2.33009 4.92971 2.32969 5.47745 2.45395 5.41967 2.46467 6.0252 2.56413 7.6254 2.8942 8.08707 3.00446 8.10047 2.99436 4.88667 2.33051 7.6254 2.88564 5.47745 2.46573 4.32418 2.21999 7.66844 2.88064 7.0988 2.77578 9.31167 3.171 9.77335 3.27196 7.66844 2.88639 6.54405 2.66688 6.52216 2.67324 4.90782 2.33346 6.00331 2.57064 5.3406 2.45762 8.16539 2.99214 6.96269 2.78833 5.34835 2.44771 7.63954 2.89949 8.18729 2.98089 7.0918 2.78787 6.57294 2.67914 4.38196 2.18541 5.44856 2.43056 8.21618 2.98468 9.81563 3.26613 7.0988 2.78476 6.00331 2.57871 8.76393 3.09075 8.72014 3.09632 4.38196 2.21922 4.84289 2.33644 10.3783 3.36804 6.0252 2.56731 8.16539 2.98103 8.74203 3.08154 4.75696 2.32703 6.47212 2.70011 7.56047 2.90629 5.93913 2.56225 7.64654 2.88938 7.12069 2.80819 3.28647 1.9544 5.91024 2.5929 7.57461 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8.11461 3.00069 5.47745 2.45729 7.60351 2.90286 4.90082 2.3372 10.8399 3.45254 6.54405 2.69155 6.50802 2.68902 6.42134 2.68062 10.883 3.46152 6.57294 2.69879 7.66844 2.90068 8.73503 3.10026 7.0699 2.79684 8.74203 3.0895 4.84364 2.36302 9.31167 3.18797 4.31003 2.20176 6.00331 2.57719 8.17315 2.97283 5.47745 2.46561 5.91723 2.55754 6.54405 2.6746 10.3783 3.35574 5.97441 2.56617 7.6254 2.89414 8.18729 2.98219 4.92971 2.32976 9.23974 3.18478 4.82174 2.32461 7.0699 2.79243 5.45556 2.44229 5.99631 2.56434 6.0252 2.57373 5.38363 2.45353 6.52991 2.68264 8.17315 2.97569 7.64654 2.8851 4.33893 2.22181 4.38196 2.1948 8.14425 2.98142 2.73873 1.75888 3.76929 2.05828 5.38363 2.44844 6.52991 2.69028 5.96027 2.56491 9.80163 3.269 7.66844 2.89356 4.86478 2.34306 3.26458 1.9161 7.64654 2.90224 6.54405 2.6733 6.00331 2.55935 4.76396 2.33934 4.38196 2.21914 8.12236 2.98448 5.45556 2.46256 8.06518 2.99636 7.12069 2.79785 8.76393 3.07996 4.33118 2.19741 5.34774 2.45078 5.44856 2.45612 6.57294 2.68812 7.66844 2.89777 9.31167 3.19567 8.62707 3.09486 3.24344 1.9406 9.83052 3.27878 4.92971 2.34036 6.00331 2.57871 6.0252 2.57683 6.50102 2.69526 4.88667 2.32696 4.88667 2.33225 6.0252 2.57379 7.62465 2.89388 5.93138 2.59078 6.0252 2.57561 8.21618 2.99446 5.41253 2.46494 9.31167 3.17618 6.0252 2.58335 5.47745 2.44727 4.25286 2.20861 8.692 3.10096 4.84289 2.32379 7.6254 2.88277 7.66844 2.88357 5.44856 2.45091 6.52216 2.68554 5.97441 2.56788 5.45556 2.45415 7.0918 2.79216 6.55105 2.67452 4.92971 2.32101 7.0699 2.78206 8.19429 2.9904 5.97441 2.56292 6.48687 2.66944 6.54405 2.67763 3.24344 1.90184 9.85942 3.27464 7.04876 2.79434 6.50102 2.67688 8.19429 2.98626 11.5027 3.53271 5.40553 2.45174 9.80863 3.28134 7.58236 2.88781 6.0252 2.56742 7.12069 2.78164 6.50802 2.67818 4.27339 2.18491 8.13011 3.00799 7.12069 2.77418 9.77335 3.2849 4.38196 2.22102 3.83422 2.06926 6.52216 2.68393 5.98216 2.59363 8.21618 3.00546 8.6701 3.09295 8.12236 3.0037 7.05576 2.79577 9.31167 3.1814 8.76393 3.11472 9.78749 3.2981 10.9041 3.45756 4.90782 2.34064 2.6668 1.76509 8.12936 2.98698 6.49327 2.67817 8.72089 3.09257 7.05576 2.77509 8.76393 3.08536 7.59576 2.91828 1.59245 1.3814 5.39138 2.44714 5.96027 2.56978 8.76393 3.10684 7.05576 2.78831 3.81232 2.09321 7.58161 2.89307 7.66844 2.91058 4.88667 2.32525 9.83752 3.27356 6.49327 2.68292 10.3564 3.36694 11.4596 3.52511 8.68425 3.08997 7.61765 2.88539 7.0699 2.80419 8.17315 2.98401 6.54405 2.67608 10.9549 3.44879 10.9549 3.44166 8.6771 3.09561 6.57294 2.68989 8.72089 3.10187 9.31167 3.19558 5.47745 2.45058 9.24674 3.19002 7.0988 2.78644 7.12069 2.77869 6.57294 2.68965 4.88667 2.33054 6.51516 2.68882 6.52991 2.6734 9.85942 3.26585 8.6771 3.0741 9.80863 3.27388 7.0988 2.79521 5.42667 2.46289 7.0988 2.77279 8.19429 2.99045 5.40553 2.46015 9.25389 3.17676 7.12069 2.78604 9.19671 3.18033 11.4377 3.53805 9.23974 3.18218 10.3422 3.36614 6.57294 2.68502 5.92438 2.55572 6.0252 2.58019 5.99631 2.57413 7.59651 2.8944 3.7404 2.08444 8.12236 2.99267 8.04404 2.98856 7.0918 2.80549 11.9496 3.6215 2.71683 1.75206 6.57294 2.71563 5.98216 2.5777 6.45023 2.69104 6.50102 2.70296 6.45723 2.69874 4.35307 2.20308 6.54405 2.69002 7.56761 2.8948 7.66844 2.91341 5.43367 2.46263 3.81232 2.06724 7.64654 2.88223 7.0918 2.78632 5.47745 2.44548 3.83422 2.0652 6.57294 2.68965 12.0504 3.62037 6.57294 2.68209 4.90082 2.32133 6.52916 2.67002 6.00331 2.55632 4.90782 2.33532 8.16539 2.99482 6.0252 2.56407 9.78749 3.27162 7.59576 2.8914 6.00331 2.55784 10.3352 3.36365 8.71314 3.07498 7.12069 2.78605 9.31167 3.18396 7.59651 2.90445 5.85306 2.56039 8.16539 2.98255 8.76393 3.08134 6.0252 2.56567 9.80163 3.27771 6.0252 2.57694 7.64654 2.89951 8.73503 3.08159 5.3406 2.46265 8.74203 3.07746 7.66844 2.88635 7.63954 2.88956 9.28278 3.18427 7.07765 2.78972 7.0988 2.79802 5.93838 2.56363 8.17315 2.98264 9.79449 3.27658 4.87892 2.34621 8.01439 2.98865 8.18729 2.99322 8.17315 2.98398 8.21618 2.97925 7.66844 2.89208 7.12069 2.79348 7.05576 2.78989 6.50802 2.67536 8.71314 3.1017 3.25758 1.92071 7.61765 2.89827 5.41967 2.47136 8.19429 3.00005 6.48687 2.67107 4.88667 2.33411 7.0699 2.78657 10.3634 3.35586 9.28978 3.18022 10.3494 3.36087 5.44856 2.44749 4.92971 2.34211 8.18729 3.00985 7.59651 2.89883 7.55347 2.90072 8.21618 2.97922 5.94552 2.5904 4.92971 2.32618 7.6254 2.88988 7.52458 2.90679 7.04876 2.7783 13.0951 3.77577 7.0699 2.79098 5.99631 2.56754 4.84364 2.34558 9.23199 3.17687 8.73503 3.08555 9.71556 3.28528 4.36007 2.2045 6.47912 2.68926 6.55105 2.69298 4.82814 2.33619 10.4072 3.36773 4.92971 2.31931 8.21618 3.00552 9.79449 3.26016 7.61765 2.88263 3.83422 2.07723 10.3063 3.36509 7.66844 2.88082 5.47745 2.44214 6.0252 2.57044 9.31167 3.17618 3.25758 1.91875 7.04876 2.78846 5.98216 2.56952 6.52216 2.68091 5.95327 2.56186 6.0252 2.55757 3.79118 2.06804 4.38196 2.18931 5.47745 2.43873 8.70614 3.07244 7.61765 2.88976 6.45798 2.68818 8.14425 2.98572 6.57294 2.68037 4.35307 2.20086 9.7586 3.27568 5.98216 2.59668 4.36007 2.18749 8.16539 2.99899 5.41967 2.46155 8.21618 2.98339 5.40553 2.47849 5.47745 2.45218 4.38196 2.21735 4.33893 2.2144 5.43442 2.475 7.66844 2.89641 6.54405 2.70226 5.38363 2.46867 9.85942 3.29097 11.4808 3.53757 6.57294 2.69578 2.68794 1.78748 6.0252 2.57848 3.74815 2.06695 6.57294 2.70042 3.28647 1.92453 7.58176 2.89442 6.57294 2.67739 4.29589 2.23781 3.80532 2.07951 7.0918 2.79665 4.88592 2.32479 7.12069 2.78023 5.47745 2.46228 10.933 3.44062 7.66844 2.90347 4.90782 2.32465 8.19429 2.99185 10.3783 3.36067 9.83052 3.26236 7.57461 2.88177 5.97441 2.58375 5.47745 2.46232 7.64654 2.87937 5.47745 2.45046 7.0988 2.79826 8.76393 3.08403 6.54405 2.67469 6.57294 2.68649 6.51516 2.69788 4.38196 2.21735 9.83052 3.26603 6.52216 2.67927 5.44856 2.46432 6.0252 2.58336 8.72089 3.10446 13.074 3.77929 6.52991 2.67802 7.66844 2.90351 9.85942 3.27351 9.78749 3.26408 4.90782 2.34054 10.3783 3.35827 9.31167 3.18265 7.07765 2.79734 4.31703 2.19595 7.12069 2.79057 8.74203 3.10157 9.77974 3.27414 14.2414 3.93897 9.79449 3.29415 11.4596 3.54491 4.84364 2.32771 10.2414 3.36953 8.21618 2.99729 8.76393 3.09869 4.20907 2.21828 8.21618 3.00825 4.33118 2.18787 4.90782 2.35985 4.85778 2.33982 8.1365 3.00213 8.19429 2.99328 11.4166 3.54321 7.12069 2.78899 9.76484 3.26667 11.9707 3.62557 9.77974 3.28039 7.07765 2.80459 5.45556 2.45756 5.98216 2.57115 3.81232 2.06932 7.05576 2.80028 4.92971 2.34929 5.91024 2.58832 8.72089 3.10465 8.17315 3.00891 8.14425 2.99662 8.68425 3.08602 7.61765 2.91254 9.81638 3.27404 8.72089 3.0899 12.0504 3.60551 7.57461 2.90313 8.13011 2.99425 7.64654 2.89374 12.5981 3.69263 5.96027 2.57613 8.12236 2.98306 11.5027 3.52219 7.0699 2.78943 6.54405 2.68229 7.0769 2.79521 5.98216 2.57274 3.83422 2.0511 7.0699 2.81905 10.9119 3.43025 9.83752 3.28109 7.64654 2.8908 9.83752 3.27478 8.76393 3.10657 10.9549 3.44045 7.01273 2.78026 10.3133 3.36501 4.88592 2.34621 7.07765 2.78814 8.70614 3.09521 6.54405 2.68386 6.0252 2.56237 4.85703 2.33235 7.0988 2.78629 8.21618 2.99167 6.0252 2.57539 4.88667 2.34644 4.38196 2.21925 7.66844 2.89497 11.5027 3.53507 10.3422 3.35742 6.0252 2.57046 7.0769 2.79378 12.5262 3.6933 4.38196 2.21917 8.16539 3.00717 9.31167 3.19172 5.93913 2.57508 7.12069 2.81261 5.42667 2.45944 7.63954 2.88662 8.73503 3.0829 5.45556 2.4658 8.64896 3.07602 5.47745 2.44713 4.86478 2.33784 8.71314 3.09506 5.43442 2.46473 3.80532 2.06744 5.96027 2.57137 7.12069 2.78619 4.87892 2.31792 7.07765 2.78075 3.80532 2.05945 4.92971 2.33858 5.35399 2.44679 5.95252 2.57274 7.61765 2.88686 9.85942 3.26328 3.24344 1.94048 9.28978 3.1829 5.98216 2.57447 3.2004 1.93494 7.03387 2.78869 9.79449 3.26653 10.9549 3.43202 6.40005 2.68894 9.24674 3.18727 7.63954 2.87813 5.44856 2.45598 3.28647 1.92237 8.17315 2.98688 9.22485 3.16792 5.96027 2.57317 9.85942 3.26074 8.76393 3.09193 3.76229 2.05646 7.59576 2.88122 7.0699 2.77913 5.47745 2.45388 6.0252 2.57226 9.78749 3.28562 10.3133 3.35892 6.52991 2.66725 5.98216 2.58888 7.58236 2.87906 5.45556 2.4576 8.17239 2.99332 9.81563 3.27369 8.15125 2.98961 8.61293 3.10326 6.0252 2.56413 5.92363 2.55399 4.35307 2.18969 9.31167 3.17629 9.31167 3.18276 9.28978 3.17765 5.93138 2.55891 3.22154 1.93879 12.0285 3.59767 4.88667 2.34646 7.12069 2.79348 7.62465 2.89668 9.83052 3.2736 7.01987 2.79768 9.85942 3.26714 3.28647 1.9311 4.32418 2.18432 10.9041 3.44803 10.9549 3.45238 7.07765 2.80312 6.57294 2.68363 7.0699 2.78947 6.52991 2.6843 6.51516 2.68113 6.00331 2.56741 7.0918 2.78631 7.0918 2.79667 4.81474 2.33335 8.18729 2.97963 6.54405 2.67307 8.21618 2.99028 5.41967 2.44621 12.5551 3.69299 8.19429 2.98781 11.5027 3.5258 7.0918 2.78486 5.91663 2.5782 5.44856 2.43735 7.63954 2.90528 6.0252 2.57552 11.9785 3.61434 9.78674 3.279 8.74203 3.08821 8.21618 2.9903 4.90782 2.34246 7.57461 2.88894 7.12069 2.80231 4.92971 2.34211 7.05576 2.78402 6.51516 2.65484 5.96027 2.56326 8.68425 3.09263 4.88667 2.30922 5.98216 2.55834 6.00331 2.5579 7.03387 2.79298 6.46498 2.69737 8.71314 3.08991 5.45556 2.44734 8.6701 3.08229 7.12069 2.78025 4.90782 2.32285 7.64654 2.88794 3.77643 2.06195 7.66844 2.88926 6.54405 2.68541 6.57294 2.68369 5.40553 2.45511 6.49327 2.67039 5.99631 2.56914 8.21618 2.99026 4.90082 2.33539 4.36007 2.21768 4.88592 2.35492 7.04876 2.79583 7.56761 2.90754 5.42667 2.45608 5.96027 2.57299 6.52991 2.68117 8.71314 3.0817 9.28278 3.18292 6.48612 2.68458 7.66844 2.90068 7.0988 2.77881 9.26789 3.18043 9.28278 3.1739 6.55105 2.67134 7.12069 2.79345 5.44856 2.45758 5.98216 2.55354 10.9119 3.44224 6.57294 2.67737 6.0252 2.55761 6.48687 2.66649 9.81638 3.26902 5.98216 2.56966 7.66844 2.88633 5.38363 2.44348 3.2004 1.91792 13.607 3.8496 9.75145 3.27964 10.4072 3.36533 5.47745 2.44398 7.6254 2.88004 3.76929 2.06039 10.89 3.44711 5.39777 2.44129 5.97441 2.57593 11.4808 3.52823 3.76229 2.06457 6.54405 2.68544 8.76393 3.09205 8.76393 3.08925 8.76393 3.08663 7.61765 2.89258 4.35307 2.21409 8.21618 3.01376 5.47745 2.437 12.5332 3.69992 4.92971 2.33326 8.72014 3.11485 7.12069 2.78906 7.54572 2.90201 6.52991 2.69061 8.21618 2.98893 9.81638 3.27644 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2.90366 9.26789 3.19221 9.23199 3.19113 6.0252 2.56738 4.87192 2.34458 8.74203 3.09216 8.16539 2.97268 6.50102 2.66902 8.74203 3.08815 4.88667 2.33767 6.0252 2.55757 6.0252 2.58496 6.52991 2.69028 3.79118 2.08784 8.19429 2.989 9.79449 3.2892 6.0252 2.57842 6.48627 2.68899 6.47212 2.67861 4.88667 2.33584 6.52216 2.68556 5.91723 2.57845 5.34774 2.44552 4.81324 2.36086 6.50802 2.67675 5.42667 2.44614 3.25758 1.91649 7.0988 2.77604 10.3494 3.34857 4.38196 2.19862 10.883 3.44239 5.44856 2.4374 8.76393 3.08259 4.90082 2.31405 5.96741 2.56952 8.12161 2.98682 8.12236 2.98853 7.04876 2.79732 9.85942 3.27218 9.83052 3.27121 9.78749 3.26911 2.6738 1.75774 3.83422 2.07104 5.98141 2.5708 10.4072 3.37032 12.469 3.69855 8.21618 2.98901 9.80163 3.27012 13.1459 3.78631 7.57461 2.89616 7.53933 2.90687 12.5763 3.68933 2.69569 1.79694 8.73503 3.08156 8.76393 3.10269 8.17315 2.98252 8.16539 2.99357 8.71314 3.08847 7.12069 2.79645 8.14425 3.0036 8.76393 3.07857 4.38196 2.21186 9.31167 3.19044 7.12069 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9.28278 3.18045 7.59651 2.89295 9.21785 3.19148 7.61765 2.90403 8.76393 3.08259 8.74203 3.08688 12.5981 3.71598 10.3422 3.35867 9.31167 3.1917 9.83052 3.28245 8.21618 3.00404 5.45556 2.48745 8.76393 3.11723 14.2414 3.93909 7.57386 2.89868 5.98216 2.59048 6.00331 2.57235 9.25389 3.20137 3.80532 2.05949 7.6254 2.91697 7.64654 2.90795 8.19429 3.0111 7.59576 2.90551 8.15125 2.99797 5.43442 2.47157 13.6358 3.86018 10.4072 3.38366 6.55105 2.69438 8.76393 3.08793 9.85942 3.28477 11.4166 3.55006 14.6742 4.00248 8.09347 3.01904 11.5027 3.54342 7.12069 2.79638 9.26089 3.20247 10.2837 3.36992 10.4072 3.36656 9.85942 3.26578 10.9549 3.44048 8.76393 3.08935 7.50268 2.88843 10.3133 3.37124 12.5332 3.68982 5.47745 2.45892 12.0285 3.62512 9.74445 3.27223 7.59651 2.89176 7.66844 2.88351 9.23199 3.20922 9.85942 3.27466 12.5763 3.68933 6.52991 2.68115 9.85942 3.27098 8.1505 2.98522 9.28278 3.18289 8.71314 3.0964 8.74203 3.09214 3.72565 2.06045 7.60351 2.89576 8.67635 3.07923 9.24674 3.17427 10.9119 3.44942 7.02687 2.7753 5.42667 2.45779 6.57294 2.67747 6.99158 2.78658 8.15125 2.98969 6.57294 2.68813 7.66844 2.8935 9.77335 3.26075 4.90082 2.32131 8.74203 3.08684 9.81563 3.26231 12.5106 3.70091 5.39138 2.45719 8.21618 2.98195 12.4832 3.6904 7.6254 2.88698 4.85703 2.34644 3.17151 1.92698 5.96741 2.60144 5.41253 2.45645 4.92971 2.33517 7.05576 2.78092 6.52991 2.67806 6.0252 2.56084 4.92971 2.34912 8.18729 2.98085 6.52991 2.67039 7.60351 2.88445 7.58236 2.89189 3.83422 2.04299 8.72089 3.07254 5.45556 2.43719 5.39777 2.43639 8.76393 3.08262 6.0252 2.57692 8.73503 3.08022 8.76393 3.09062 7.64654 2.88228 7.66844 2.90062 10.2922 3.35196 8.21618 3.00404 8.72089 3.08863 6.99158 2.80146 5.47745 2.4472 8.15125 2.98967 9.28978 3.17905 7.12069 2.78623 7.60351 2.90293 8.18729 2.98376 9.23974 3.17707 7.61765 2.88544 5.98216 2.58553 11.4088 3.52208 8.13011 3.01089 8.21618 2.98488 5.45556 2.44581 8.61293 3.09655 9.85942 3.26833 6.48687 2.67729 10.4072 3.36173 11.5027 3.53751 9.78749 3.28318 4.87892 2.32333 10.2273 3.36617 8.15839 2.99776 5.96027 2.56978 9.85942 3.26345 7.59651 2.903 8.15125 3.01571 10.8971 3.44459 8.17315 3.00337 13.081 3.7815 9.83752 3.29262 8.72089 3.10726 10.3352 3.36611 8.19429 3.00289 5.92438 2.58168 8.19429 2.9933 9.2256 3.20446 11.5027 3.5479 12.0504 3.6239 11.4307 3.52898 8.76393 3.11078 10.3205 3.37107 10.933 3.46337 5.92363 2.58284 6.43609 2.67762 5.96027 2.61123 9.31167 3.18917 5.47745 2.48907 6.52216 2.70096 10.4072 3.37269 7.07765 2.81771 6.45723 2.69715 5.93138 2.58295 7.58236 2.90183 9.28978 3.18282 7.04876 2.81069 8.699 3.11142 8.1365 2.99655 6.57294 2.68668 9.7367 3.2835 6.00331 2.57231 9.79449 3.26647 10.9549 3.44289 7.66844 2.89635 8.71314 3.08169 9.2256 3.18519 7.12069 2.7994 6.0252 2.5608 10.4072 3.37634 7.64654 2.88658 7.6254 2.88708 10.933 3.45499 8.21618 2.98612 5.45556 2.45077 11.4519 3.54476 14.2414 3.91906 10.9549 3.44529 12.5763 3.68491 9.83052 3.27619 8.6701 3.08231 8.72089 3.0819 9.31167 3.18791 11.9424 3.6227 6.57294 2.66963 9.81638 3.27397 11.4088 3.5301 9.81638 3.26265 7.66844 2.87638 5.47745 2.44042 8.72089 3.08184 8.72014 3.09089 5.95252 2.55983 5.96027 2.56491 9.28978 3.1737 12.5474 3.69623 6.97683 2.78956 8.21618 2.99581 5.95952 2.56455 9.80863 3.27379 5.95327 2.56507 10.9549 3.44772 9.85942 3.28222 6.50102 2.6829 9.85942 3.28231 7.66844 2.89925 7.64654 2.89376 5.92438 2.57674 3.76229 2.05431 5.42667 2.46784 7.03387 2.78121 6.48687 2.67412 7.55347 2.89219 7.12069 2.78172 2.73873 1.7707 7.12069 2.79351 9.23974 3.17574 9.28978 3.1906 7.07765 2.78966 6.00331 2.56585 7.59651 2.87446 8.15125 2.97721 8.18729 3.0099 7.05576 2.77509 6.47837 2.66432 8.21618 2.99577 9.85942 3.2633 6.0252 2.57047 11.4519 3.51914 9.31167 3.17102 4.33118 2.20666 5.41253 2.43466 9.83052 3.27871 11.4596 3.53443 6.57294 2.69124 13.5787 3.84375 4.90082 2.33197 8.12236 2.99692 10.3352 3.36372 10.9549 3.44766 11.4519 3.53329 9.19671 3.16993 14.7602 4.0026 5.99631 2.57404 9.23974 3.1784 5.43442 2.44468 10.3853 3.36055 4.36007 2.21008 12.0504 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3.09995 14.7461 4.00078 11.9996 3.62531 14.2125 3.92767 5.47745 2.45558 9.26789 3.18946 7.59651 2.89598 8.73503 3.10032 8.76393 3.0946 10.3133 3.35889 12.0504 3.61123 9.24599 3.18959 9.81638 3.27137 7.12069 2.80386 8.72014 3.10567 6.45798 2.68835 9.21785 3.19015 12.5981 3.69928 9.80863 3.30016 9.26089 3.196 9.26864 3.2 9.85942 3.29097 9.83052 3.29757 14.7891 4.01273 10.9549 3.45261 7.64654 2.90377 8.73503 3.11895 5.47745 2.49738 9.85942 3.28854 10.9549 3.47647 7.53872 2.89353 8.17315 3.00607 7.0699 2.80277 9.31167 3.20212 7.07765 2.7868 11.43 3.54139 6.45648 2.70296 15.3369 4.08898 8.72014 3.0924 11.4738 3.55751 12.5185 3.72208 11.5027 3.53165 12.5693 3.70628 12.0504 3.61126 14.2195 3.93812 5.95252 2.5903 11.9785 3.62684 9.28978 3.19839 6.0252 2.57698 13.6936 3.85011 10.3783 3.37795 10.4072 3.35207 7.6254 2.88131 9.83752 3.27601 11.43 3.53794 10.9119 3.44699 10.3564 3.35218 6.52216 2.684 9.83052 3.26231 7.66844 2.88361 7.0699 2.77611 7.12069 2.80227 8.08707 3.00996 8.65596 3.08796 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6.48687 2.67713 11.4088 3.53254 10.3203 3.35754 8.73503 3.08694 8.73503 3.0869 11.4808 3.5352 10.3853 3.36303 10.4072 3.37758 12.0285 3.61142 10.3634 3.3731 11.3869 3.52569 8.6701 3.07965 9.26789 3.18817 12.5551 3.70873 10.3564 3.37311 7.0988 2.79961 13.6647 3.87059 10.9119 3.45421 7.61765 2.91391 8.74203 3.10827 7.66844 2.91498 6.0252 2.57696 12.5981 3.69923 5.98216 2.58412 10.3352 3.38206 8.76393 3.09348 8.17315 3.01561 9.85942 3.29356 6.45798 2.70202 8.1435 3.00601 10.4072 3.38978 10.4072 3.36428 7.66844 2.92188 8.15125 3.00474 11.4158 3.54523 8.21618 2.9986 10.8822 3.45535 9.79449 3.28809 6.0252 2.58014 8.15125 2.9995 8.69125 3.10329 8.76393 3.10931 9.83052 3.26493 9.77974 3.27913 8.1365 2.99784 7.64654 2.89667 12.0285 3.61828 10.3853 3.36306 15.8846 4.14316 8.21618 3.01096 10.3853 3.36798 9.13817 3.18303 8.15125 3.00339 12.5763 3.70613 9.23974 3.18359 9.71556 3.2762 7.55347 2.88374 12.0285 3.61374 8.73503 3.09777 7.63954 2.891 10.7969 3.44226 12.0504 3.61353 6.50802 2.67364 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7.12069 2.78012 9.79449 3.28166 10.8971 3.45049 5.97441 2.56781 7.63954 2.89112 11.4596 3.54153 8.21618 2.99723 8.76393 3.08926 9.81638 3.27015 7.66844 2.89929 12.5693 3.704 7.05576 2.79435 9.25389 3.1858 10.3564 3.37921 12.5981 3.70042 9.24674 3.18467 8.19429 3.00837 14.1546 3.9429 9.83052 3.28905 7.0699 2.81627 10.3564 3.38649 10.3422 3.37332 9.31167 3.18656 9.85942 3.286 6.99158 2.8101 8.76393 3.10136 9.26089 3.23082 10.9549 3.46927 9.31167 3.20862 8.21618 2.9903 10.9119 3.46376 9.77335 3.29094 9.83752 3.29373 9.78749 3.30935 11.5027 3.54684 10.3641 3.37568 10.933 3.45983 9.26089 3.21296 9.77335 3.29089 11.4519 3.53424 13.0951 3.77469 7.12069 2.79047 10.3641 3.38052 9.81563 3.28743 5.91024 2.59614 14.1983 3.93527 10.3853 3.3728 10.8822 3.44818 8.21618 2.99847 14.2414 3.92235 8.692 3.08212 8.21618 2.99714 9.2256 3.20067 9.26864 3.19359 10.8541 3.45587 7.57386 2.90567 8.14425 2.99813 8.17315 2.98818 10.933 3.45854 10.3422 3.36478 7.59651 2.8973 9.28278 3.19594 7.12069 2.78758 13.6936 3.84902 9.83752 3.26858 14.2414 3.91903 8.76393 3.09998 9.22485 3.17187 12.0504 3.60895 9.21085 3.16818 8.19429 2.99322 9.18896 3.18263 7.07765 2.7956 8.699 3.08075 11.4596 3.52516 7.04876 2.7825 12.0074 3.60833 7.56761 2.88189 6.57294 2.66967 10.3634 3.37917 7.0988 2.78027 5.44856 2.46592 9.80863 3.27254 12.0215 3.60924 8.76393 3.07584 8.692 3.08212 6.57294 2.68804 12.5693 3.69277 10.9549 3.45727 7.57461 2.92307 10.9119 3.4422 10.4072 3.3655 3.2004 1.9286 3.21454 1.92159 8.72089 3.08724 11.5027 3.53044 3.76929 2.07041 5.47745 2.4489 7.12069 2.77123 5.41967 2.44796 9.31167 3.17249 5.94552 2.55839 5.34774 2.45912 8.21618 2.99024 7.63954 2.88245 5.95252 2.57441 5.98216 2.59035 9.2256 3.16694 7.0988 2.78183 4.90082 2.34599 9.19671 3.17369 7.62465 2.89102 10.3133 3.36379 14.1045 3.93086 8.69125 3.09252 10.4072 3.34813 9.31167 3.17228 8.21618 2.9931 9.81638 3.28901 9.81563 3.2687 9.31167 3.18657 13.081 3.76505 13.1459 3.75684 7.0988 2.77578 11.9785 3.60182 9.78749 3.28048 9.18821 3.1838 10.9119 3.44584 11.4808 3.53878 15.8338 4.13546 5.44856 2.44912 9.77259 3.26538 8.14425 2.99114 9.28978 3.17633 13.0951 3.78231 12.5981 3.7039 9.85942 3.27087 8.15125 3.00351 9.78749 3.27293 6.00331 2.57705 8.18729 3.00013 7.12069 2.80239 9.85942 3.27847 6.99798 2.81258 9.73031 3.28391 11.5027 3.54208 9.85942 3.30358 5.99631 2.57409 8.72089 3.12446 12.0504 3.62045 10.3853 3.36549 10.9549 3.4621 10.3352 3.36611 9.31167 3.20986 8.15125 3.01039 11.4596 3.55426 7.07765 2.80881 9.31167 3.2035 10.9549 3.46684 11.9855 3.6233 8.17315 3.01031 8.76393 3.10542 10.926 3.4611 8.71314 3.10969 11.5027 3.55029 7.63954 2.91242 7.12069 2.82287 10.9111 3.44554 12.5551 3.70322 10.8971 3.4566 4.31703 2.21474 7.66844 2.91209 11.9785 3.61895 7.64654 2.8939 7.61065 2.89274 10.3783 3.35571 7.0699 2.80275 11.9996 3.63215 9.83752 3.27354 9.83052 3.28138 6.54405 2.68383 8.17239 2.99892 8.21618 2.99162 9.26864 3.17542 7.66844 2.885 8.13011 3.00249 9.78749 3.27321 7.05576 2.79587 8.71314 3.10459 9.28978 3.19327 13.1021 3.75821 7.66844 2.89929 5.92438 2.56221 7.66844 2.88369 10.3422 3.36249 9.81638 3.26899 8.08707 2.98656 7.66844 2.8736 10.4072 3.34815 8.71314 3.09379 4.35307 2.2048 12.5544 3.68832 8.76393 3.08393 11.5027 3.51517 4.87892 2.32855 8.21618 2.98194 6.54405 2.66687 9.19671 3.1711 4.86478 2.33787 6.47137 2.67984 5.96741 2.55506 7.12069 2.77123 9.16706 3.17622 6.55105 2.69133 9.83752 3.2647 7.59651 2.88155 12.0504 3.61579 9.14517 3.18548 9.83052 3.27621 5.98216 2.57595 3.22154 1.91291 3.26458 1.9294 9.21085 3.17726 8.71314 3.06967 7.66844 2.88215 4.90782 2.33527 9.81638 3.27646 6.52991 2.66571 8.18729 2.98085 4.35307 2.20487 7.0699 2.78651 9.15367 3.19117 8.72014 3.08431 6.55105 2.68059 9.80863 3.26757 8.76393 3.08804 10.3853 3.35445 4.92971 2.31379 7.64654 2.88231 9.80863 3.27636 10.8181 3.45154 7.66844 2.89635 10.3783 3.35585 8.76393 3.08534 9.81638 3.26007 8.1295 2.98971 7.60351 2.89295 11.5027 3.52923 10.2774 3.34825 9.81638 3.27266 9.80863 3.27753 9.28978 3.1778 9.26864 3.18073 12.5474 3.68511 7.66844 2.8907 9.19671 3.17632 7.07765 2.76738 9.31167 3.18262 15.308 4.05989 10.4072 3.35919 11.4519 3.53659 12.0504 3.61817 11.9785 3.61891 13.1029 3.7682 9.31167 3.17763 9.31167 3.18147 14.7164 4.01318 9.77259 3.26802 7.57461 2.91033 9.85942 3.29237 12.5262 3.70902 8.21618 3.01088 8.699 3.10211 7.0918 2.79096 12.5404 3.6964 8.69125 3.10316 8.21618 3.02053 9.85942 3.28603 13.5849 3.8584 7.64654 2.91246 8.699 3.12735 8.72089 3.10321 8.72089 3.11114 8.692 3.1114 7.66844 2.92214 8.21618 3.01505 9.31167 3.22395 10.3853 3.36936 7.66844 2.92753 8.692 3.11692 12.5474 3.70519 6.54405 2.71452 8.10822 2.9986 9.85942 3.3011 11.9785 3.6303 13.1459 3.78528 14.2195 3.92976 8.18729 3.00157 14.6734 4.00122 13.6217 3.84974 11.9643 3.6295 11.5027 3.55954 13.5067 3.86146 14.7672 4.00657 16.8651 4.28322 12.0215 3.61493 11.4808 3.5306 13.117 3.77566 9.79449 3.28169 11.9707 3.61295 8.17315 2.98671 11.5027 3.52703 14.1906 3.92685 9.83752 3.26215 11.5027 3.53515 9.26864 3.17806 12.5262 3.68999 14.7383 3.99238 10.89 3.44716 5.97441 2.57104 11.9785 3.60513 8.69825 3.08045 15.2219 4.07505 11.5027 3.52923 13.6506 3.84955 8.15125 2.99792 6.50802 2.68128 7.64654 2.88804 9.28278 3.17645 8.21618 2.98887 8.72089 3.08463 10.89 3.44474 8.17315 2.98944 7.02687 2.78578 9.28978 3.18158 7.6254 2.88702 7.61065 2.89416 6.0252 2.56077 8.72089 3.07653 8.16539 2.99894 9.20371 3.18137 8.21618 2.98744 8.19429 2.98484 11.4808 3.51996 7.0988 2.79661 6.46498 2.67734 5.94552 2.58416 7.63954 2.89382 7.66844 2.89641 6.0252 2.57844 5.88134 2.56444 9.31167 3.18527 6.97683 2.79246 8.72014 3.07899 7.64654 2.88381 6.57294 2.68515 11.9996 3.60828 4.36007 2.20841 10.4072 3.36041 8.692 3.09278 3.22154 1.92147 10.3641 3.35354 6.50102 2.67537 13.124 3.77888 12.0215 3.60688 4.35307 2.19146 5.95327 2.56674 13.5928 3.84245 11.4166 3.52909 10.2922 3.35927 10.9549 3.45246 5.99631 2.55331 7.0699 2.77175 9.78749 3.27182 7.45265 2.88634 7.0988 2.78183 8.72089 3.08866 10.3494 3.3609 13.117 3.77456 11.4596 3.52859 8.72014 3.06702 13.081 3.77614 9.26864 3.1858 10.3352 3.37476 8.73503 3.08154 10.3783 3.35217 10.9119 3.44591 8.74203 3.09085 10.9549 3.43576 10.9549 3.44289 12.0504 3.6158 8.6701 3.10508 7.07765 2.79856 13.6287 3.84759 10.9119 3.44952 10.3853 3.37401 9.85942 3.27469 10.4072 3.38247 8.21618 2.99455 14.7023 4.00614 9.23199 3.19758 12.5693 3.70503 9.79449 3.30057 9.28978 3.20606 6.50102 2.70137 14.1553 3.95154 10.9119 3.4841 7.03462 2.82425 11.9926 3.63468 10.3853 3.39492 9.28278 3.2204 9.28278 3.21652 13.124 3.78872 7.57461 2.89894 9.26089 3.19614 11.9785 3.64163 5.98216 2.60329 9.26864 3.21183 9.80863 3.27757 7.66844 2.91205 10.3783 3.38522 10.8681 3.45683 15.3369 4.09809 9.80863 3.30156 12.0285 3.64119 8.12936 3.01462 6.52216 2.70851 9.81638 3.27404 12.0074 3.62335 10.8603 3.45307 10.4072 3.36177 13.6717 3.85031 9.26864 3.18073 10.4072 3.35795 6.50026 2.68111 9.24674 3.17569 9.81563 3.2686 12.5043 3.69791 13.0881 3.77047 8.76393 3.09199 14.7164 4.00598 7.01273 2.77562 8.73503 3.08429 10.933 3.44422 9.20371 3.16844 5.36249 2.46244 10.3133 3.35273 13.117 3.76577 9.26789 3.16867 6.52991 2.68428 6.50102 2.68295 7.02687 2.77972 14.2195 3.91716 5.93138 2.57002 4.85778 2.31331 8.17315 2.99796 8.699 3.10474 8.68425 3.08327 6.94794 2.7882 5.93913 2.56563 6.55105 2.67744 8.692 3.08224 9.81638 3.27271 6.57294 2.66804 5.47745 2.45728 7.64654 2.87938 8.19429 2.97378 9.31167 3.17357 7.12069 2.77563 6.48627 2.67223 10.8533 3.43997 5.91723 2.57365 6.52991 2.68116 5.93913 2.57829 4.90082 2.35141 5.45556 2.45414 11.4808 3.5247 4.90782 2.33708 8.21618 2.99575 4.33893 2.19573 4.87192 2.3164 7.07765 2.78223 7.04876 2.77513 8.10047 2.98745 8.76393 3.08804 6.54405 2.66525 10.3853 3.37166 4.38196 2.20248 8.17239 2.99485 8.72089 3.09123 10.3422 3.35244 7.63954 2.87954 11.9855 3.60731 5.47745 2.44883 7.0699 2.77911 6.0252 2.5624 6.50802 2.67831 7.07765 2.78844 8.69825 3.08578 13.117 3.7701 12.0215 3.61606 11.5027 3.53042 5.93913 2.5623 5.90873 2.57645 7.59651 2.89878 9.28978 3.17763 11.9785 3.60978 8.74203 3.08413 11.3869 3.53495 10.9549 3.45015 10.4072 3.35919 8.12936 3.00778 13.6217 3.84534 9.85942 3.27215 8.63421 3.10678 9.85942 3.25948 13.6936 3.84479 8.16539 2.99086 6.52991 2.68874 13.0732 3.77605 14.1836 3.93101 12.5474 3.70073 8.18729 3.00154 9.70142 3.2728 14.7383 4.01532 10.3564 3.38896 10.9119 3.46262 9.23199 3.19891 8.71314 3.09788 8.74203 3.10015 13.0521 3.78408 11.4018 3.53491 12.5262 3.71776 16.9152 4.29442 12.0504 3.6352 9.26089 3.20896 10.3783 3.39246 7.66844 2.93039 8.21618 3.0274 9.81563 3.30383 5.39063 2.49363 9.21785 3.19651 11.4738 3.58186 10.3853 3.40581 12.5262 3.71566 11.5027 3.5596 6.50802 2.72868 14.1757 3.95002 14.5739 4.01185 7.66844 2.91927 10.4072 3.38619 11.5027 3.54678 9.83752 3.30373 9.31167 3.19692 7.59576 2.9028 11.4596 3.55313 9.24674 3.18727 9.23199 3.20911 9.31167 3.18909 10.9549 3.46078 10.8971 3.4457 16.9074 4.29328 11.4519 3.54244 5.98216 2.56644 16.9582 4.30058 9.83052 3.26479 14.0756 3.93633 8.08707 3.00458 18.0029 4.41531 13.6358 3.84621 11.4377 3.53812 9.70142 3.26143 11.9205 3.6159 10.2922 3.3692 7.01912 2.79153 9.83052 3.26486 9.15367 3.17566 8.19429 2.97934 7.63954 2.89242 15.3369 4.06881 8.76393 3.08547 9.80863 3.26619 11.4519 3.53893 10.3853 3.35697 8.699 3.09276 8.21618 2.97928 10.8688 3.45229 5.98141 2.56123 6.50102 2.66443 9.23974 3.17962 7.57461 2.89173 5.39138 2.45038 6.99798 2.77853 8.18729 2.985 9.74445 3.27473 6.00331 2.55619 9.22485 3.18224 11.9855 3.6027 7.12069 2.76981 8.15125 3.00069 10.8462 3.45097 7.66844 2.90074 10.3564 3.35711 7.07765 2.77925 9.26789 3.17516 9.85942 3.2911 7.12069 2.79046 7.0699 2.76878 5.39138 2.44875 7.12069 2.792 5.98216 2.55349 5.41253 2.43627 5.89534 2.5642 7.0769 2.7715 8.72089 3.07647 8.10122 2.98076 6.57294 2.66969 9.72956 3.27232 9.81638 3.26768 12.0504 3.61015 9.26864 3.18066 8.65596 3.07865 8.12236 2.99821 10.9549 3.43692 6.48687 2.67574 9.18257 3.17657 11.5027 3.5305 9.2256 3.17471 9.20371 3.17484 10.4072 3.35433 4.92971 2.3173 11.4596 3.52743 5.39138 2.46222 10.3422 3.35387 8.699 3.08741 9.18821 3.19016 9.25389 3.18316 11.9785 3.60635 9.81638 3.27141 9.83052 3.26994 12.0504 3.60677 13.0951 3.77142 10.3853 3.36187 12.0504 3.62038 10.3641 3.35601 7.0918 2.78933 7.05576 2.78242 11.9996 3.62877 8.6771 3.08494 15.25 4.0766 14.1983 3.93739 9.83752 3.29999 13.081 3.78154 10.8681 3.45918 13.6506 3.86237 6.47912 2.69568 12.0215 3.62515 5.92438 2.59107 9.19671 3.20744 9.26864 3.19488 9.77974 3.283 11.4596 3.56113 9.80863 3.30541 15.2508 4.09999 10.3783 3.41937 8.76393 3.1307 10.9549 3.48351 7.0988 2.82752 4.33893 2.22178 8.73503 3.13997 12.5693 3.72838 12.5763 3.72622 8.76393 3.12262 6.57294 2.7034 9.2256 3.21612 12.0504 3.63645 8.19429 3.01256 8.21618 3.01372 9.77259 3.30701 10.3422 3.38566 11.2656 3.55533 8.73503 3.11901 13.1029 3.7903 9.31167 3.18536 13.6936 3.85981 3.80532 2.07938 11.9354 3.62843 10.933 3.44551 12.4824 3.69128 10.9549 3.46921 12.0074 3.62662 11.9347 3.61796 12.0504 3.61697 9.21085 3.17853 10.4072 3.36299 7.12069 2.80083 10.4072 3.36531 12.0215 3.61153 10.8971 3.44942 10.926 3.44551 13.1459 3.76663 7.59651 2.90159 14.7383 3.98406 8.17315 2.98949 8.692 3.07946 8.72089 3.09257 7.66844 2.8892 7.66844 2.89072 8.1435 2.9826 6.50802 2.67673 8.72089 3.0819 9.31167 3.17618 5.98216 2.56315 7.61765 2.87389 8.64821 3.08106 7.6254 2.89277 11.5027 3.5304 8.13011 2.98317 7.55347 2.88368 7.64654 2.88078 8.17315 2.98539 7.63954 2.88818 7.66844 2.87634 8.17315 2.98944 9.81563 3.27623 10.4072 3.35184 5.40477 2.45631 8.73503 3.06945 9.21785 3.16559 6.55105 2.67603 6.49327 2.69972 4.81399 2.34023 3.78343 2.05186 8.05818 2.99387 6.00331 2.58192 7.58236 2.88484 10.3783 3.35578 9.80163 3.27006 9.80863 3.2637 4.88667 2.33054 5.47745 2.44553 9.78674 3.28911 8.71314 3.08699 9.31167 3.17231 8.21618 2.99168 10.3422 3.3574 8.18729 2.98232 5.47745 2.46061 9.28978 3.18541 7.12069 2.77865 7.12069 2.78312 12.0215 3.6012 7.60351 2.8857 8.19429 2.97945 13.0309 3.76679 9.78749 3.27298 7.66844 2.88497 8.18729 2.99197 9.81638 3.26518 9.83052 3.26252 7.63954 2.88806 10.4072 3.36409 9.81638 3.26135 13.1459 3.75564 9.26089 3.1818 9.85942 3.26578 3.76929 2.06625 10.3853 3.357 13.6647 3.84709 10.3133 3.36026 9.75084 3.26925 9.31167 3.17623 7.64654 2.88802 11.9996 3.61282 9.23899 3.1858 10.89 3.44128 10.926 3.44674 4.36007 2.2139 9.19671 3.19716 9.7367 3.27828 12.0504 3.62848 8.16539 3.01684 5.93913 2.59118 10.9119 3.47101 11.4519 3.57381 8.73503 3.11223 12.5693 3.7108 11.5027 3.53986 6.54405 2.73445 9.25389 3.21429 10.3641 3.40972 9.83752 3.29366 8.76393 3.13176 7.05576 2.84997 17.4771 4.39275 9.85942 3.31879 7.58176 2.95105 6.0252 2.59915 10.8688 3.47258 12.4754 3.71825 11.9643 3.64533 10.4072 3.39954 11.9855 3.65619 9.23899 3.21545 11.9135 3.66383 11.4808 3.57704 8.71314 3.10986 5.39063 2.46684 12.5981 3.71061 9.26864 3.2079 14.7602 4.0098 14.6953 4.02686 10.7828 3.47846 15.8408 4.14733 15.315 4.08608 11.4377 3.54396 11.43 3.552 8.21618 3.01088 10.3783 3.36811 9.31167 3.18163 10.9549 3.45849 14.0615 3.93241 16.4324 4.20534 8.76393 3.07468 14.7461 4.00082 14.7891 4.01177 9.26864 3.18979 8.73503 3.08696 13.0521 3.7763 9.26864 3.16898 17.9676 4.40469 9.23974 3.18224 10.4072 3.36044 13.6358 3.8505 8.76393 3.0772 9.31167 3.17357 13.5639 3.84691 5.42667 2.44627 8.21618 2.9986 9.7656 3.26434 8.76393 3.09462 9.26789 3.17261 12.5693 3.67821 8.76393 3.08144 10.4072 3.3617 9.85942 3.27211 11.5027 3.52931 4.79999 2.30666 5.99631 2.5661 7.64654 2.88519 9.28278 3.18167 7.0988 2.77281 8.74203 3.08682 11.5027 3.51751 10.3641 3.36342 8.73503 3.08016 7.04876 2.79 7.12069 2.79793 6.57294 2.66809 9.23199 3.17684 4.85778 2.33259 7.05576 2.79127 6.00331 2.56747 5.39063 2.43648 7.66844 2.88497 9.85942 3.27338 9.23974 3.18874 5.45556 2.44058 8.14425 2.98004 7.12069 2.79491 9.83752 3.27861 8.17239 2.96979 4.92971 2.32096 6.0252 2.57213 9.81638 3.26259 5.98141 2.56943 7.49554 2.88296 11.4808 3.52355 7.6254 2.87416 10.4072 3.3444 9.81638 3.25883 9.28278 3.18559 12.0215 3.6081 5.97441 2.57423 9.31167 3.17751 13.6076 3.85423 9.83752 3.25582 10.9549 3.44417 10.7397 3.43716 10.8469 3.45242 8.74203 3.07874 10.2922 3.37044 13.6506 3.8473 10.4072 3.35062 10.3422 3.3649 10.9041 3.44321 7.57386 2.89719 9.7367 3.27203 12.5262 3.69791 13.1459 3.77243 12.0504 3.61236 9.26864 3.20137 14.1695 3.92715 10.9111 3.45878 17.4701 4.34564 15.8846 4.14413 8.19429 3.01658 12.0215 3.61377 12.5544 3.70397 14.7891 4.01683 13.1029 3.79554 8.76393 3.10684 12.5981 3.70167 6.49327 2.69361 12.5693 3.72512 13.081 3.79243 10.8611 3.47603 13.081 3.81078 7.62465 2.94061 8.699 3.14317 7.50268 2.93235 10.8322 3.48334 8.62632 3.15561 10.89 3.49826 8.13011 3.0219 9.85942 3.31851 9.26864 3.2066 11.4088 3.56523 14.2125 3.94863 9.83052 3.30501 9.19521 3.21329 6.55105 2.71137 14.7672 4.04459 9.83752 3.31 12.5262 3.71558 8.13011 3.02171 9.81638 3.29415 15.8846 4.16 13.0379 3.77212 13.5998 3.86376 16.9152 4.29325 10.3345 3.38174 15.2572 4.07647 14.1257 3.9179 13.1459 3.78637 14.1123 3.93431 12.5981 3.70155 11.4307 3.53938 13.124 3.76674 11.4377 3.5416 10.8469 3.45626 11.4596 3.53787 10.3641 3.3573 15.8268 4.14758 8.18729 2.99052 10.3853 3.37674 9.80163 3.27008 11.4808 3.52713 9.22499 3.16911 11.9855 3.62445 9.81638 3.27406 10.3783 3.35343 5.44856 2.44758 12.5693 3.68605 14.7164 3.98942 7.6254 2.88279 9.31167 3.17359 9.31167 3.16057 7.64654 2.89947 10.933 3.4514 8.76393 3.08796 9.23974 3.18353 6.54405 2.67 8.699 3.08473 10.3275 3.35244 13.621 3.8452 9.23899 3.17278 11.4018 3.53143 9.78674 3.26133 9.83052 3.27488 8.10122 2.97517 7.61765 2.89118 9.83752 3.26594 12.5981 3.68478 9.83052 3.27262 7.0769 2.78798 7.64654 2.89649 5.40553 2.46501 7.0769 2.79963 10.4072 3.34936 5.47745 2.44716 8.74203 3.08699 6.52916 2.67459 9.31167 3.1969 5.47745 2.43707 8.18729 2.98108 7.0699 2.77913 6.50026 2.6718 10.8469 3.44535 9.28278 3.16606 9.28278 3.17909 5.42667 2.44265 8.14425 2.98698 7.66844 2.88934 8.74203 3.08409 12.4832 3.68144 5.96741 2.56788 9.21785 3.16548 9.80163 3.2689 8.21618 2.98331 13.0592 3.77608 8.61293 3.07782 12.5551 3.6919 13.1029 3.78033 10.926 3.44309 8.60593 3.08347 11.9855 3.60389 7.6254 2.89127 13.1029 3.7727 6.0252 2.56245 15.2861 4.0681 10.9549 3.44175 12.5981 3.6982 9.85942 3.27346 13.1459 3.77759 11.4377 3.53696 12.5981 3.68252 8.692 3.09558 11.4589 3.52946 15.308 4.08227 13.6936 3.85218 10.3641 3.35496 11.4596 3.54493 8.19429 3.00024 10.3494 3.37575 9.7367 3.296 16.9152 4.28945 11.5027 3.55964 13.5356 3.86988 7.05576 2.81938 15.2861 4.07927 12.5121 3.74791 12.0504 3.62394 11.4377 3.58555 16.4035 4.26423 13.6217 3.88916 10.8682 3.49604 11.4596 3.58441 10.3641 3.40627 9.72956 3.31632 16.9004 4.35066 14.1976 3.97481 10.9549 3.49535 9.81638 3.32913 13.6506 3.89429 11.9424 3.67253 13.6506 3.89641 12.5763 3.73392 13.1029 3.81634 13.6647 3.8898 14.6742 4.01907 12.5693 3.72747 13.6428 3.89417 12.0066 3.63894 6.55105 2.72344 10.9119 3.46861 9.83752 3.31249 11.4596 3.53915 7.0629 2.80424 7.61065 2.91406 15.3369 4.0961 13.081 3.78266 10.9549 3.4573 10.933 3.45734 15.2861 4.07721 14.1687 3.93317 12.5763 3.69824 13.6936 3.84148 8.15125 2.99661 13.6647 3.84394 12.0215 3.60921 13.6506 3.84514 16.4324 4.21134 8.69125 3.08717 11.9855 3.6221 8.76393 3.08394 13.6717 3.84264 12.5981 3.68369 9.83752 3.28365 11.4808 3.52231 15.2649 4.07855 6.48687 2.67409 9.78674 3.27024 12.0285 3.60913 12.5693 3.69067 9.2256 3.17228 8.67786 3.07712 12.5693 3.68168 12.5551 3.69191 8.18729 2.9753 7.55347 2.89089 8.18729 2.9919 7.66844 2.88652 6.00331 2.57229 11.4589 3.52487 9.26864 3.17809 5.44856 2.44416 6.55105 2.67292 11.4596 3.53092 5.40553 2.45504 8.21618 2.98058 5.47745 2.44557 13.6217 3.84643 4.86478 2.3345 6.49327 2.68133 4.86478 2.33279 7.6254 2.90409 9.31167 3.1827 7.07765 2.79415 7.07765 2.78543 6.00331 2.56749 6.54405 2.66379 7.63954 2.87813 6.00331 2.57072 4.83514 2.32722 6.00331 2.56263 14.2195 3.93287 7.12069 2.78899 7.03462 2.77692 6.44323 2.6728 7.12069 2.78173 8.19429 2.98622 6.57294 2.6743 8.15125 2.98543 7.07765 2.77484 6.55105 2.66984 9.83052 3.2737 7.12069 2.78008 8.70614 3.08718 7.05576 2.78549 6.54405 2.68227 8.21618 2.97916 10.89 3.43881 8.76393 3.08662 10.3422 3.36977 14.1553 3.92101 10.9549 3.44531 13.0302 3.76649 19.1711 4.54653 10.4072 3.35304 10.9549 3.4441 13.124 3.77342 15.3369 4.07693 8.21618 2.98343 8.18729 3.00165 10.9549 3.45722 13.6717 3.86202 11.4738 3.5389 8.73503 3.08832 8.6701 3.09848 9.26089 3.1856 14.2414 3.94216 18.5945 4.4874 8.18729 2.99602 7.04876 2.8077 10.3494 3.36578 15.8557 4.15334 14.2125 3.94663 13.1459 3.80592 13.6076 3.87233 9.19671 3.19821 6.52216 2.71016 15.236 4.10812 12.0504 3.6636 10.7108 3.49107 15.3369 4.11631 8.74203 3.18553 9.31167 3.25326 13.6217 3.9241 10.8611 3.49621 14.2125 3.97075 13.6647 3.89311 10.9119 3.50879 12.0504 3.67693 15.8846 4.18289 8.74203 3.14394 13.1459 3.82221 13.6936 3.9033 11.9785 3.66324 9.31167 3.23051 11.5027 3.55609 14.2414 3.94852 11.5027 3.55952 7.0699 2.80133 18.0756 4.43932 9.26789 3.21539 10.9119 3.46137 13.117 3.78867 12.0504 3.62839 16.9371 4.29221 15.8846 4.16401 11.9636 3.61319 8.64121 3.09604 15.2861 4.08126 10.926 3.46707 10.933 3.44788 7.07765 2.79418 8.73503 3.08432 12.5325 3.69429 14.7672 3.99218 10.7962 3.4528 12.0215 3.62063 11.9347 3.61123 13.074 3.77282 9.22485 3.18097 5.95327 2.5716 7.0918 2.78497 9.80863 3.28261 8.76393 3.10667 12.5121 3.69583 13.1459 3.77017 9.28978 3.17241 12.0074 3.60722 10.3133 3.3552 10.4072 3.35671 11.4088 3.52899 3.76929 2.05623 6.52216 2.68704 12.0215 3.60116 10.4072 3.35553 8.15125 2.98973 9.28978 3.17636 6.48612 2.68144 8.14425 3.0022 8.69125 3.09795 10.2335 3.36706 6.57294 2.66961 7.0918 2.78044 4.35307 2.19699 2.73873 1.74938 10.883 3.45319 7.66844 2.88643 8.16539 2.99895 7.66844 2.89925 4.35307 2.20652 6.55105 2.6883 6.45798 2.67446 5.96741 2.56488 5.96027 2.565 3.72565 2.06249 7.0988 2.78185 6.55105 2.67288 9.31167 3.19172 7.63954 2.89951 8.76393 3.09464 8.73503 3.08559 7.0699 2.79703 8.16539 2.98928 7.04101 2.78825 9.31167 3.18007 9.28278 3.16998 14.1836 3.91423 6.99798 2.78008 7.0988 2.7728 9.31167 3.17361 8.699 3.08342 12.5693 3.68501 9.85942 3.2722 11.4519 3.52959 9.31167 3.17359 15.3369 4.06074 9.7656 3.26047 7.01987 2.78871 9.81563 3.26103 12.4105 3.68749 8.70614 3.09268 14.2414 3.92431 11.9855 3.60049 10.3352 3.36128 14.1976 3.92677 10.933 3.44784 8.14425 2.98979 16.4105 4.20552 11.4596 3.53326 9.83052 3.28506 14.2414 3.92861 11.4596 3.52979 10.933 3.45615 14.1695 3.92091 13.081 3.78811 12.5981 3.71938 8.72089 3.09792 12.5121 3.71145 13.5645 3.86855 12.0504 3.62723 7.12069 2.81255 18.0318 4.43755 9.80863 3.33027 14.2414 3.95997 10.926 3.48484 10.4072 3.41057 13.6936 3.90009 10.8032 3.51554 12.0074 3.69997 14.2125 4.0038 12.5544 3.75498 17.499 4.39101 14.1264 3.99452 14.7242 4.07365 14.2125 3.98419 12.9801 3.83036 12.5262 3.78299 11.9855 3.6812 13.6506 3.91467 13.117 3.83332 12.0285 3.67151 6.89001 2.84038 10.9119 3.50173 12.0504 3.65897 12.5332 3.71905 13.6428 3.86753 9.85942 3.31366 16.9293 4.29695 13.6217 3.87003 15.3369 4.10327 14.7672 4.00157 15.8416 4.1545 13.6287 3.87422 11.5027 3.56647 10.9119 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3.88068 16.4035 4.23395 10.8688 3.48472 14.7602 4.01711 15.308 4.08015 15.2791 4.08148 11.4808 3.55157 13.124 3.78 14.7172 4.01126 16.9801 4.27439 12.5763 3.70277 9.26864 3.17555 13.6936 3.84364 18.0756 4.41593 14.1983 3.93645 12.5262 3.69002 15.2791 4.06724 9.7437 3.2771 15.8846 4.14023 12.5693 3.68606 10.3352 3.3662 14.2125 3.92359 10.8688 3.44031 9.85942 3.27344 14.1553 3.92317 9.83752 3.2482 12.4902 3.68822 15.3369 4.07183 9.23974 3.16919 8.74203 3.07212 9.83052 3.26101 10.9119 3.44699 8.21618 2.98337 10.9119 3.45177 9.31167 3.1762 10.3783 3.35583 5.38363 2.45358 8.15839 2.9894 7.57461 2.88167 9.78749 3.26665 8.17239 2.98781 8.21618 2.97638 8.16539 2.99483 8.21618 2.9778 9.85942 3.27213 8.69125 3.10055 7.64654 2.89805 9.28978 3.16994 7.0988 2.78625 4.33893 2.19183 3.81232 2.04929 5.41253 2.43634 4.31003 2.19789 7.04801 2.78823 9.31167 3.17228 13.1459 3.75895 9.80863 3.2776 7.64654 2.87799 8.73503 3.08959 8.16539 2.98099 12.5981 3.6814 11.4808 3.52585 8.17315 2.99228 4.38196 2.19894 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9.79122 62.6095 8.89835 50.5728 7.8678 40.7417 6.98988 26.133 5.60215 31.1135 5.98865 26.0251 5.46068 29.5352 5.73677 24.0789 5.18912 20.7205 4.81785 15.7979 4.20625 17.499 4.39745 15.2078 4.10562 8.6701 3.13293 16.3096 4.22396 14.2195 3.935 13.1459 3.78756 14.1695 3.92508 14.2195 3.92867 14.1257 3.94532 14.7891 4.00961 15.2508 4.06674 14.7891 3.99943 10.3783 3.3705 9.77259 3.28061 15.3369 4.05963 18.6015 4.47905 15.8846 4.13912 10.3853 3.3692 13.6936 3.83938 9.21785 3.17597 12.5551 3.68545 11.4808 3.5317 10.9119 3.44105 12.9801 3.76712 7.07765 2.78528 10.4072 3.34567 11.5027 3.51412 10.3783 3.3533 9.23974 3.17048 7.0699 2.79389 9.78749 3.26284 9.26864 3.17285 6.0252 2.56402 3.66772 2.05165 5.41253 2.44312 6.55105 2.68216 10.3564 3.35721 11.4738 3.52017 8.12236 2.98028 7.61065 2.90407 6.46498 2.67729 6.51516 2.66716 8.72014 3.09096 8.76393 3.09464 7.62465 2.9067 6.57294 2.67116 4.88667 2.31817 6.00331 2.58031 7.66844 2.89216 10.2914 3.36649 9.28978 3.19058 7.12069 2.78453 7.0988 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3.526 8.72014 3.07495 8.14425 2.99524 8.76393 3.07992 4.30928 2.20876 14.1687 3.92054 13.6217 3.84106 11.5027 3.52815 7.07765 2.79124 12.0504 3.62732 13.6076 3.85744 11.5027 3.52103 14.1334 3.91483 7.61065 2.8927 13.0598 3.77634 9.31167 3.17882 9.83052 3.28993 8.16539 2.99897 11.5027 3.53276 7.61765 2.89536 12.5981 3.69718 8.74203 3.10288 9.85942 3.27342 8.21618 3.01641 9.81638 3.26892 8.64896 3.11605 14.2414 3.93164 10.9111 3.47547 7.56686 2.9357 12.0504 3.64445 10.9549 3.46923 11.4011 3.57769 10.4072 3.3923 12.0215 3.63778 6.57294 2.70642 12.5981 3.7238 11.423 3.56035 7.12069 2.8419 7.61765 2.94092 9.26864 3.22444 7.58236 2.93022 13.1029 3.81085 5.99631 2.6282 5.99631 2.61399 8.1365 3.01048 4.92971 2.37896 10.9119 3.46611 8.21618 3.026 8.17315 3.01146 10.89 3.48045 13.124 3.78006 11.4158 3.55348 13.124 3.79195 8.692 3.10755 10.9119 3.45192 8.15125 2.99792 7.05576 2.79445 10.9549 3.45129 5.96741 2.58411 8.72089 3.09132 9.31167 3.184 9.31167 3.1956 10.4072 3.36408 7.61765 2.88255 10.9549 3.44769 9.83752 3.27473 9.83752 3.27229 11.4449 3.52646 8.72089 3.09803 12.5551 3.6751 8.73503 3.07755 13.0951 3.77796 9.74385 3.2668 9.85942 3.26073 7.01987 2.77551 9.7656 3.25544 8.21618 2.99586 10.9549 3.44883 7.6254 2.88994 15.2931 4.05994 7.0699 2.77609 5.45556 2.45912 8.692 3.07412 7.64654 2.87652 10.926 3.43835 7.0918 2.78632 8.699 3.07936 5.43442 2.45968 10.3352 3.34769 9.69367 3.27011 7.07765 2.78516 9.28278 3.17122 8.76393 3.07992 8.74203 3.08684 5.47745 2.46566 5.99631 2.5692 4.88667 2.3163 7.66844 2.89632 7.59651 2.90161 8.16539 2.99214 6.52991 2.67344 10.9119 3.46371 9.28978 3.16735 8.21618 3.00967 6.52991 2.67504 8.72089 3.08184 5.42667 2.4628 5.98216 2.58572 4.84289 2.30783 4.92971 2.32998 4.35307 2.2027 7.63954 2.89671 5.47745 2.45065 9.26089 3.18046 9.31167 3.19185 7.54572 2.89209 9.83752 3.25471 13.1459 3.77658 7.12069 2.7831 7.64654 2.88794 8.73503 3.07757 9.23974 3.1822 4.81474 2.31561 13.6647 3.83951 9.28278 3.17384 10.3494 3.35488 12.0504 3.61817 10.9549 3.44284 6.52991 2.6719 8.19429 2.98486 11.9785 3.62459 16.4324 4.21225 5.99631 2.57076 5.36949 2.47745 6.00331 2.55307 9.21785 3.17458 13.6936 3.85003 16.2955 4.21824 5.99631 2.57719 9.81638 3.2715 9.81563 3.26734 9.67952 3.28928 12.5763 3.7039 9.24674 3.17688 8.76393 3.10664 11.4596 3.54266 10.883 3.43893 15.2508 4.08488 11.4738 3.54582 10.89 3.4675 9.19671 3.17497 13.6647 3.85667 13.5851 3.85826 12.0504 3.63636 12.0504 3.62952 5.94552 2.60327 7.66844 2.92053 9.83052 3.30503 7.6254 2.92002 8.699 3.11532 7.0988 2.81586 9.14517 3.22675 14.7461 4.02667 8.699 3.15394 9.21785 3.23898 7.49493 2.94223 7.12069 2.82158 9.31167 3.20591 11.5027 3.59662 8.72089 3.14287 13.1459 3.80061 14.2195 3.96115 7.66844 2.90934 15.7548 4.16916 12.0504 3.6352 8.18729 3.02635 12.5693 3.69506 10.3783 3.39254 8.76393 3.10568 10.2773 3.38269 7.0699 2.79984 13.6647 3.85148 7.12069 2.79496 12.0504 3.62717 12.5981 3.70164 7.63954 2.90527 10.9549 3.45964 13.6506 3.84942 16.894 4.2791 8.15839 2.9922 8.18729 3.00024 7.55286 2.90044 13.6217 3.84967 16.9371 4.28452 7.63954 2.87375 10.2914 3.35902 9.79449 3.27789 13.6717 3.84691 15.8416 4.1455 8.1295 2.99796 10.3783 3.35573 7.66844 2.88791 9.23974 3.17179 8.18729 3.00028 6.54405 2.66377 9.80863 3.27003 7.58236 2.88767 7.0988 2.77736 10.9119 3.44701 7.66844 2.88078 6.50802 2.68587 6.48687 2.67258 6.57294 2.68199 9.80863 3.26615 9.81638 3.2613 5.95252 2.55992 5.41967 2.43767 10.8399 3.43935 7.0699 2.77311 4.92971 2.32091 7.0988 2.7848 8.14425 2.99524 5.45556 2.45921 7.12069 2.78316 12.5544 3.69391 9.2031 3.17708 6.0252 2.56585 3.83422 2.05534 4.92971 2.33157 6.0252 2.57528 7.66844 2.8908 7.6254 2.89124 5.43442 2.44458 4.38196 2.19108 9.83752 3.27105 9.26789 3.18552 6.54405 2.68694 9.26089 3.18567 7.63954 2.88377 10.8399 3.44174 8.72089 3.0846 6.52916 2.68393 11.4808 3.54219 7.60351 2.87723 11.4738 3.53178 5.42667 2.44605 9.83052 3.25851 7.57461 2.87476 9.80163 3.26123 8.15839 2.97841 8.19429 2.99052 10.4072 3.35065 9.25389 3.17929 8.21618 2.99722 12.5981 3.68818 9.31167 3.18659 10.9119 3.44348 10.4072 3.36062 7.59651 2.87876 6.49327 2.67346 10.3641 3.36463 9.80863 3.27641 10.9549 3.44049 8.17315 2.98805 5.98216 2.56478 10.9549 3.45131 7.62465 2.89821 11.4738 3.52713 13.124 3.78316 8.74203 3.08549 10.926 3.44908 6.54405 2.67296 9.28978 3.19076 7.66844 2.89072 12.0504 3.61579 12.0074 3.63803 6.55105 2.71295 14.2414 3.92646 9.85942 3.28479 10.9041 3.45518 10.2844 3.36532 6.54405 2.69925 9.83052 3.27623 7.66844 2.91916 3.80532 2.09338 8.21618 3.00819 15.2938 4.08644 13.6506 3.87085 12.0215 3.64684 8.70614 3.11254 6.54405 2.72696 7.6254 2.91259 6.54405 2.71292 8.74203 3.11879 7.07765 2.80318 8.16539 3.03741 9.26864 3.21938 11.4449 3.54369 10.926 3.48016 8.71314 3.12831 8.18729 3.03438 9.23199 3.2015 5.95327 2.61617 12.5043 3.7046 12.5185 3.71995 11.3729 3.56774 13.1021 3.7648 9.83052 3.28377 9.24674 3.20291 8.21618 3.00267 9.81638 3.28784 10.3564 3.36086 7.64654 2.90927 12.5043 3.70792 14.2195 3.9297 8.76393 3.08538 9.77335 3.2771 11.4808 3.53414 10.3634 3.3632 9.77274 3.27801 7.57461 2.90171 10.8688 3.45586 12.5981 3.69936 8.21618 2.97782 8.72089 3.07786 11.4377 3.53455 9.28278 3.18303 10.3853 3.35452 10.933 3.43462 8.19429 2.98903 9.26864 3.19492 9.7656 3.26697 12.5693 3.69167 8.73503 3.07613 6.55105 2.68679 8.10761 2.97468 10.9549 3.43089 12.0504 3.60789 10.8039 3.43981 12.0074 3.61629 12.0285 3.60907 7.66844 2.88351 9.28978 3.17903 7.66844 2.89494 9.21085 3.17347 6.55105 2.66978 8.74203 3.07069 7.60351 2.88572 6.55105 2.6929 7.6254 2.8799 6.55105 2.67919 5.47745 2.44389 5.41253 2.443 7.0918 2.79376 8.15839 2.98806 9.83752 3.27857 6.92605 2.78251 7.0918 2.7863 5.44856 2.44422 8.76393 3.09593 4.33893 2.19193 5.99631 2.56434 7.0988 2.78615 6.57294 2.66499 8.64121 3.08649 7.62465 2.89248 1.57831 1.37906 6.54405 2.6745 7.57461 2.88039 6.52991 2.67353 6.98383 2.7923 8.14425 2.9815 5.86645 2.56609 8.76393 3.07057 3.83422 2.05115 7.57461 2.89892 11.4596 3.52503 12.0074 3.62775 7.0699 2.77463 4.92971 2.33331 10.3641 3.34869 8.73503 3.08828 14.2125 3.91822 10.3422 3.35869 7.03401 2.77503 7.61765 2.88403 4.90782 2.31575 8.19429 2.97802 9.80863 3.27133 8.13011 2.99149 8.72089 3.08723 10.8681 3.44007 9.28978 3.18027 15.3369 4.07385 13.6717 3.84491 12.5763 3.69044 8.72089 3.08199 8.18729 2.99602 13.6506 3.85594 9.81638 3.28023 9.85942 3.27462 7.64654 2.89801 9.78674 3.28906 8.21618 2.99849 10.3641 3.36463 12.5981 3.69811 12.5981 3.69817 10.9041 3.46714 10.8399 3.46917 8.76393 3.09864 13.1459 3.77874 9.83052 3.31015 12.5693 3.71517 14.7891 4.02205 10.3133 3.39077 8.19429 3.03295 7.05576 2.82822 8.15125 3.01306 8.13011 3.01912 7.52458 2.93227 3.22869 1.94673 9.24674 3.22247 6.57294 2.72638 13.6287 3.87851 9.83752 3.29755 7.59651 2.92864 7.07765 2.82951 14.2414 3.94428 7.66844 2.91645 6.57294 2.70036 11.4808 3.53994 10.4072 3.37759 13.1029 3.79446 11.4596 3.56129 10.926 3.44548 9.21785 3.20442 7.66844 2.91208 10.9549 3.44653 8.10822 3.01094 8.69125 3.0953 8.17315 2.98539 9.23899 3.17546 8.72089 3.10325 9.22499 3.18478 8.76393 3.08939 10.2774 3.37034 10.933 3.45148 9.28278 3.1881 19.6899 4.6116 9.78749 3.26663 7.66844 2.89354 8.70614 3.0858 11.4449 3.52615 10.2992 3.35308 8.76393 3.07881 8.63482 3.08055 8.72014 3.08028 12.5981 3.68363 7.55986 2.89028 9.22485 3.17455 8.21618 2.98624 10.9549 3.4441 9.28278 3.17386 13.6506 3.84836 4.88667 2.311 7.00573 2.79209 8.19429 2.97656 8.16539 2.99212 7.53933 2.88973 12.5981 3.68473 5.36188 2.44506 7.0629 2.79847 8.73503 3.10152 7.0988 2.78617 8.72089 3.0753 8.1365 2.97711 8.18729 2.98362 5.99631 2.56775 6.54405 2.67307 5.34774 2.4439 6.50026 2.68102 9.81638 3.29285 7.6254 2.90698 6.55105 2.68825 6.52216 2.6855 5.99631 2.56612 7.0769 2.78489 6.57294 2.67886 7.6254 2.88132 8.74203 3.08945 9.26089 3.18056 7.12069 2.79195 7.66844 2.89352 3.7334 2.05082 4.85778 2.32019 8.17315 2.99096 8.10822 2.99029 7.63954 2.8924 5.98216 2.55994 9.80863 3.26121 5.99631 2.55472 9.83052 3.26611 3.24344 1.906 8.70614 3.08986 6.54405 2.67629 5.98141 2.5725 8.1435 2.99504 7.04876 2.78107 9.31167 3.17357 8.76393 3.08928 8.14425 2.98838 4.92971 2.33001 8.76393 3.07058 9.28978 3.17632 10.883 3.44848 5.99631 2.56921 8.76393 3.08253 8.73503 3.08825 11.4808 3.53872 11.3947 3.5386 5.45556 2.47091 12.469 3.68297 8.76393 3.09864 9.83052 3.27121 5.47745 2.45407 11.4596 3.54729 7.0629 2.79105 6.57294 2.69129 12.0285 3.61264 4.84364 2.35262 8.19429 2.98083 10.8469 3.46096 9.7586 3.2707 11.9777 3.61985 7.0918 2.79218 12.0074 3.61072 8.14425 3.00639 9.28978 3.20099 6.0252 2.58503 9.80163 3.29035 9.25389 3.19374 6.0252 2.59137 11.5027 3.54681 13.074 3.78706 8.10747 3.01191 8.76393 3.10667 9.19596 3.19548 11.9424 3.6261 8.74203 3.12023 10.89 3.47353 6.52991 2.69039 8.74203 3.09358 7.53158 2.91674 6.57294 2.70641 8.21618 3.01096 7.0918 2.81146 7.04876 2.80191 9.83752 3.28989 9.28978 3.20104 9.83752 3.28116 9.28978 3.19333 8.76393 3.10135 7.04801 2.80889 6.54405 2.67642 7.62465 2.92226 12.0504 3.61478 7.04876 2.79463 9.28278 3.18289 8.72089 3.09123 8.71314 3.10178 7.63954 2.88377 10.3641 3.36839 13.6428 3.84933 11.4307 3.52995 8.21618 2.982 9.23199 3.19765 9.7437 3.27076 9.26864 3.18457 10.89 3.46626 9.28278 3.17381 8.16539 2.99219 8.17315 2.98949 8.17315 2.99234 12.5763 3.68936 9.31167 3.18142 11.9643 3.602 6.52991 2.65789 5.36949 2.44544 10.9041 3.44918 5.45556 2.4508 9.81638 3.26514 8.18729 2.9851 13.6936 3.85114 5.95327 2.55866 6.50802 2.67822 9.72256 3.26602 7.07765 2.78233 8.21618 2.98891 6.50802 2.67355 4.87192 2.33406 6.52916 2.67625 4.90782 2.34233 7.64654 2.88509 7.0769 2.77008 10.933 3.43943 6.55105 2.67605 11.5027 3.53742 7.0918 2.77148 7.05576 2.77796 3.69736 2.06771 4.92971 2.36149 6.0252 2.56886 3.78343 2.05372 8.76393 3.07462 6.00331 2.5755 5.94552 2.58252 7.04101 2.78692 8.18729 2.9851 3.24344 1.92544 3.83422 2.07308 8.21618 2.98476 3.28647 1.91806 6.48687 2.66638 8.12936 2.99956 4.88667 2.329 7.04101 2.77786 5.42667 2.44259 4.79285 2.31054 9.83752 3.27232 11.4808 3.53055 11.9566 3.60752 9.85942 3.25954 7.6254 2.90579 12.5332 3.68755 9.78749 3.26915 7.66844 2.90068 8.17315 2.98405 8.17315 2.98258 5.95327 2.55719 9.28278 3.18033 7.66844 2.8864 6.96969 2.77779 12.5763 3.70055 10.3422 3.35615 7.66844 2.89783 8.76393 3.09998 9.24674 3.18088 6.0252 2.59601 5.43367 2.4357 6.52916 2.69481 10.926 3.44908 10.3853 3.3705 12.0285 3.60912 9.83052 3.2812 7.12069 2.78457 12.5551 3.69641 10.9119 3.43869 10.8688 3.45003 10.4072 3.35559 10.4072 3.35667 8.76393 3.09328 11.4808 3.53178 10.4072 3.36907 10.926 3.45164 9.80863 3.31145 11.9926 3.6345 12.0074 3.63352 9.85942 3.2947 6.57294 2.7189 6.52916 2.72668 13.6647 3.86422 12.0285 3.62505 7.55272 2.9048 6.52991 2.71477 6.52991 2.70712 7.58161 2.91874 6.42134 2.71738 9.23899 3.21297 9.85942 3.28727 7.12069 2.80678 12.5693 3.70729 14.1906 3.93508 8.16539 3.00169 12.5981 3.71931 8.71314 3.10305 10.8258 3.47084 10.3783 3.38279 8.76393 3.11873 13.6428 3.86859 12.5255 3.70755 12.5325 3.70297 10.9549 3.46442 9.26089 3.18959 11.9354 3.61244 10.9119 3.45178 10.4072 3.36658 8.21618 2.9944 13.0598 3.7765 13.0168 3.77241 9.78749 3.28556 13.1029 3.7781 10.8541 3.45717 7.12069 2.78758 8.71314 3.08845 10.8469 3.44419 9.85942 3.27086 6.57294 2.68207 13.5568 3.85136 9.83752 3.27473 11.9496 3.6191 9.28278 3.17654 13.1459 3.77329 10.3853 3.35067 6.55105 2.68841 11.4449 3.52623 8.64896 3.08269 8.64121 3.09865 13.0802 3.77262 10.3853 3.34702 7.0988 2.78325 8.64121 3.08117 4.92971 2.32976 7.64654 2.88367 12.5693 3.68275 13.124 3.77113 4.35307 2.18027 6.50802 2.67212 7.59651 2.87582 8.12236 2.97758 5.40553 2.44319 9.81638 3.27015 8.65521 3.0783 10.3352 3.36621 8.21618 2.98608 9.83752 3.2749 8.19429 2.98205 10.926 3.4467 9.28278 3.17775 4.38196 2.20809 8.73503 3.09761 7.07765 2.78964 6.52991 2.67955 8.18729 2.99061 5.47745 2.45221 9.85942 3.27209 5.44856 2.45419 9.31167 3.1645 7.12069 2.78913 10.3853 3.35822 7.64654 2.90082 7.61065 2.88847 6.50102 2.67381 9.26864 3.169 6.57294 2.6696 6.0252 2.56884 8.10822 2.99033 10.89 3.44351 5.99631 2.55804 4.92971 2.32272 7.64654 2.88511 7.07765 2.7763 6.0252 2.55437 3.80532 2.04551 6.43609 2.66992 4.30228 2.19014 5.93838 2.54568 6.52991 2.66718 5.41253 2.43795 6.0252 2.54787 10.3564 3.35959 6.57294 2.66803 5.91024 2.56744 7.0988 2.79514 13.6717 3.84693 7.0988 2.77902 7.61765 2.8868 10.3641 3.35859 8.70614 3.06849 6.54405 2.69768 5.41177 2.46459 8.17315 2.98533 8.6701 3.08368 8.74203 3.07605 9.26089 3.17408 7.66844 2.89214 11.4808 3.52473 8.16539 3.00173 6.45798 2.69913 10.9549 3.45015 8.692 3.10485 10.3133 3.36518 6.54405 2.69773 8.17315 3.01575 4.83589 2.34711 11.9996 3.61731 8.699 3.10336 7.00497 2.81841 10.89 3.45309 7.57461 2.8989 9.85942 3.28491 8.18729 3.00425 10.8688 3.46902 9.31167 3.19696 7.01987 2.7948 10.9549 3.47274 7.66844 2.89791 8.21618 2.99441 8.6701 3.11036 8.19429 3.00831 7.00573 2.79205 9.85942 3.28856 10.9549 3.46328 7.12069 2.81119 6.52991 2.67956 7.04801 2.80304 9.85942 3.29608 7.66844 2.89206 13.081 3.76947 5.98216 2.58077 7.0988 2.80388 8.61232 3.08682 9.31167 3.18788 10.3641 3.35857 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1.9189 7.07765 2.78978 8.74203 3.07742 9.26789 3.17652 5.98141 2.57249 5.45556 2.42913 5.98216 2.57925 5.47745 2.48396 12.0504 3.60323 7.05576 2.78391 7.6254 2.887 10.9549 3.43803 8.17315 2.995 9.31167 3.18657 7.6254 2.89271 12.5981 3.68363 14.7383 4.00996 7.58876 2.89568 14.2125 3.92671 12.0285 3.61256 13.6217 3.85286 12.5981 3.70158 11.4738 3.52944 5.98141 2.5645 9.85942 3.26843 10.926 3.44433 15.2938 4.07336 11.9058 3.60563 10.3853 3.36309 9.85942 3.26719 7.66844 2.89641 8.16539 2.98789 10.883 3.44605 8.21618 3.01637 9.83052 3.26985 9.28978 3.1816 10.3564 3.37799 9.28978 3.18668 8.19429 3.01254 6.52991 2.69494 9.85942 3.27972 8.63482 3.10037 5.98216 2.5745 12.0504 3.62271 9.85942 3.28725 9.24674 3.19405 7.63954 2.92225 6.50802 2.72269 6.00331 2.57878 8.76393 3.13314 13.5857 3.85651 6.54405 2.71147 7.64654 2.9066 10.3352 3.38464 6.0252 2.59306 11.5027 3.5364 7.12069 2.80522 4.32418 2.22553 6.0252 2.59141 10.3352 3.3809 4.38196 2.18538 8.21618 3.00539 9.28978 3.1945 11.4738 3.53993 14.7172 4.00302 13.6428 3.86114 10.3126 3.366 5.97441 2.58557 9.31167 3.18276 7.59651 2.89315 12.5693 3.69059 14.1476 3.93663 12.0285 3.60342 9.28278 3.19461 6.57294 2.67584 6.50102 2.67988 9.28278 3.1844 9.81563 3.27492 8.60593 3.08867 9.28278 3.1895 9.26864 3.17411 10.3641 3.36349 9.85942 3.25698 6.57294 2.6789 11.9637 3.60047 10.3853 3.34453 9.26864 3.17552 10.9549 3.43684 8.76393 3.08924 9.83752 3.26854 6.0252 2.57375 7.0699 2.79101 4.88667 2.32696 10.3853 3.34952 8.76393 3.0799 7.04876 2.77362 7.66844 2.88926 8.74203 3.08018 7.00497 2.78136 9.83752 3.27098 4.90082 2.32136 6.51516 2.67497 10.926 3.44069 4.33818 2.18588 6.0252 2.56734 4.86478 2.33069 6.0252 2.56407 7.0699 2.79833 10.89 3.45677 7.0918 2.79233 5.36249 2.44901 3.76229 2.05637 6.52991 2.70282 3.71925 2.06121 5.47745 2.45736 3.17076 1.905 4.88667 2.33582 5.47745 2.44888 7.56761 2.8976 6.57294 2.68503 4.36007 2.19509 6.57294 2.67423 6.55105 2.66982 5.95327 2.56349 4.36007 2.21192 7.12069 2.77415 7.05501 2.77915 4.90082 2.32487 5.40553 2.45669 10.8611 3.43054 6.54405 2.66529 5.38363 2.4434 3.28647 1.91186 4.92971 2.32799 7.07765 2.78676 7.6254 2.88844 10.8399 3.44056 5.45556 2.43901 11.5027 3.51767 8.17239 3.01821 11.3228 3.53702 8.15839 2.99079 5.36249 2.44906 11.5027 3.52686 5.90173 2.56836 5.95252 2.56631 7.0918 2.78046 7.12069 2.78307 9.79449 3.27411 8.21618 2.98069 9.26864 3.16381 8.76393 3.08799 12.5981 3.6915 7.6254 2.88994 8.61932 3.084 10.3641 3.3537 5.42667 2.46111 10.926 3.45273 12.5551 3.69528 6.52916 2.6961 4.36007 2.21589 7.63954 2.89659 10.933 3.45861 10.3063 3.36396 7.0918 2.79374 6.49327 2.70118 9.21785 3.1914 1.51413 1.39031 4.90782 2.34261 4.38196 2.21173 4.90082 2.34596 7.63954 2.90094 7.6254 2.9071 7.6254 2.91826 8.74203 3.11086 9.21785 3.20175 5.47745 2.47904 11.4589 3.53996 8.1435 2.99359 5.91723 2.57861 9.31167 3.2111 7.63954 2.89669 8.19429 2.99181 8.12936 2.99946 5.43442 2.48973 7.64654 2.92777 8.14425 2.98557 7.66844 2.89224 4.31703 2.20899 8.21618 2.98199 8.74203 3.09483 6.51516 2.67194 11.9785 3.61195 9.28278 3.17909 8.18729 3.0167 5.43442 2.43954 6.52991 2.70111 5.44856 2.44595 8.76393 3.08133 7.6254 2.8899 6.57294 2.67447 6.55105 2.69899 7.66844 2.87509 5.47745 2.45058 8.699 3.07931 10.9549 3.44658 4.90782 2.32648 13.074 3.76084 9.24674 3.16913 7.66844 2.88216 7.64654 2.89078 3.7404 2.04674 4.30928 2.1825 5.47745 2.45729 6.55105 2.67594 9.26864 3.16767 12.0074 3.60831 8.21618 2.9723 7.66844 2.88927 7.12069 2.78308 10.4072 3.34563 8.19429 2.97388 4.88667 2.34116 6.50802 2.66898 13.6647 3.84273 6.54405 2.67307 8.21618 2.9944 6.55105 2.66826 7.04101 2.79127 5.45556 2.44396 8.17315 2.99226 8.21618 2.97927 7.66844 2.88643 7.66844 2.89354 7.0988 2.77738 6.48612 2.69685 4.92971 2.36144 4.85778 2.3327 7.0988 2.78476 5.44856 2.46437 4.88592 2.31951 6.57294 2.68815 5.40553 2.44487 8.19429 2.99177 2.73873 1.75182 4.36007 2.22498 4.81474 2.33879 10.3853 3.35562 7.04876 2.77957 5.47745 2.45734 4.92971 2.32273 8.76393 3.08663 8.70614 3.09521 7.63954 2.89236 4.31703 2.194 4.92971 2.32638 9.28278 3.17911 6.0252 2.55431 9.28978 3.17635 9.26864 3.1768 9.77335 3.26945 8.21618 2.98347 11.8924 3.61086 12.0504 3.61244 5.40553 2.46168 6.55105 2.70207 10.4072 3.36902 4.38196 2.19659 8.6771 3.08483 8.65535 3.07696 8.73503 3.08017 5.45556 2.4592 9.28278 3.19714 8.76393 3.0827 8.19429 2.98767 9.81638 3.27777 10.3564 3.35966 7.66844 2.90346 4.88667 2.32179 11.9855 3.61085 12.5544 3.69393 7.02687 2.78709 6.99083 2.76995 7.53158 2.89665 7.01273 2.82143 14.7891 4.00554 9.26864 3.17412 1.54941 1.39752 9.21785 3.18889 7.02687 2.80486 9.21085 3.19155 8.76393 3.09195 9.85942 3.29102 10.933 3.47288 8.71314 3.11508 9.24674 3.18468 8.11536 2.98994 5.36249 2.47406 6.48687 2.69248 8.12236 3.01057 8.73503 3.09489 6.54405 2.71442 9.31167 3.19826 7.63954 2.89821 6.52991 2.69805 9.2256 3.19548 9.26864 3.18725 7.03387 2.79147 7.0918 2.80547 9.83752 3.29493 5.42667 2.46955 6.0252 2.57696 10.3352 3.36368 9.28978 3.19712 10.3641 3.36842 7.0629 2.79992 6.57294 2.69575 9.24674 3.20291 8.74203 3.10155 8.6631 3.10512 9.83052 3.2789 11.4307 3.53941 4.87192 2.34298 6.52991 2.68426 7.12069 2.79055 10.9119 3.43389 9.28278 3.18808 7.62465 2.89686 9.7656 3.27443 7.02687 2.79892 9.66477 3.2741 5.95327 2.58432 9.81638 3.26893 6.43609 2.6746 7.62465 2.90805 12.5551 3.69196 9.31167 3.19056 9.80863 3.27003 9.31167 3.17499 6.50802 2.66736 8.76393 3.09072 8.21618 2.98471 8.73503 3.09507 9.26789 3.17264 5.88834 2.56602 10.3345 3.34862 7.12069 2.79051 12.0215 3.61951 9.28978 3.16341 8.16539 2.98533 8.17239 2.98641 8.76393 3.08932 5.96027 2.56175 6.57294 2.6665 8.15125 2.98409 7.53797 2.88606 10.2914 3.3504 6.0252 2.56091 6.57294 2.67436 3.83422 2.05504 5.45556 2.46259 5.97441 2.58062 8.12236 2.99959 9.81638 3.27392 4.38196 2.20992 8.15125 2.98149 7.12069 2.79208 5.32645 2.46472 4.92971 2.31372 5.41253 2.44811 7.0918 2.79229 4.86478 2.33247 8.19429 2.97382 6.50026 2.67947 8.72089 3.09266 4.88667 2.31638 3.76929 2.0381 7.07765 2.78516 7.66844 2.88355 5.97441 2.55657 10.9549 3.44285 7.61765 2.88405 7.03462 2.76951 5.45556 2.44062 4.92971 2.34564 5.44856 2.44588 4.36007 2.18945 6.57294 2.67266 7.0988 2.77596 7.63954 2.88662 8.17315 2.98393 4.25925 2.18725 5.98216 2.55506 11.5027 3.53392 7.6254 2.88409 7.0918 2.79372 4.29589 2.21893 4.92971 2.32621 11.9636 3.6109 9.28278 3.17259 11.4808 3.52472 13.6936 3.84464 4.38196 2.19857 7.12069 2.78611 8.1435 2.98395 7.0988 2.76693 4.36007 2.20277 7.01212 2.78861 7.0918 2.79367 6.0252 2.56894 5.99631 2.57723 6.52991 2.68731 13.0232 3.78407 8.76393 3.10796 8.17315 2.98535 11.4166 3.53959 9.73031 3.27002 7.59651 2.89602 8.73503 3.08564 8.15839 2.98949 8.73503 3.10967 6.00331 2.58033 8.76393 3.10004 8.692 3.10353 5.42667 2.45944 7.64654 2.90936 10.926 3.46697 5.39138 2.45712 5.99631 2.57728 7.66844 2.91353 8.71314 3.08167 9.28978 3.18541 7.60276 2.90537 3.26458 1.94182 7.0629 2.79558 7.60351 2.89999 7.12069 2.79934 2.69569 1.78328 7.03387 2.79741 7.07765 2.79713 4.33893 2.22924 8.76393 3.11864 5.44856 2.46259 13.117 3.78767 7.61065 2.9155 7.0918 2.79233 6.54405 2.70073 6.50802 2.68139 9.81638 3.27278 4.36007 2.21746 10.3783 3.37314 10.9549 3.44648 6.54405 2.67612 7.66844 2.89072 12.5474 3.6929 7.64654 2.8853 10.3133 3.34662 5.91663 2.57643 12.5693 3.6895 8.17315 2.97431 6.52216 2.67017 9.21785 3.17322 10.3494 3.35602 8.11536 2.99 10.3783 3.34712 7.12069 2.77419 7.0988 2.77283 4.38196 2.19857 10.8892 3.44452 9.31167 3.16315 6.52216 2.6871 6.0252 2.56723 9.26089 3.18182 4.92971 2.35093 10.8971 3.45411 8.21618 2.98608 7.60351 2.89006 5.47745 2.44207 3.83422 2.06713 12.5551 3.70208 9.26864 3.17294 6.0252 2.56896 8.69125 3.07654 8.73503 3.0883 10.8469 3.44404 8.17315 2.98399 3.24344 1.91251 9.26864 3.17682 7.66844 2.89066 5.36174 2.44359 7.05576 2.78393 7.61765 2.89118 4.35307 2.20836 5.92438 2.56052 4.38196 2.21191 4.90082 2.36878 5.47745 2.46901 4.92971 2.34572 6.50102 2.68757 4.24511 2.21768 6.57294 2.67276 5.98216 2.56155 3.83422 2.06517 7.58236 2.88773 6.49327 2.66894 2.14795 1.56131 5.40553 2.45836 5.97441 2.56612 6.0252 2.55763 7.05501 2.79258 8.63482 3.09105 8.64896 3.07877 6.54405 2.67145 4.32418 2.19201 8.76393 3.08796 5.93838 2.56026 6.43609 2.68229 5.45556 2.44401 8.699 3.09549 8.74203 3.08411 6.57294 2.68203 6.54405 2.67931 6.57294 2.67575 10.4072 3.35433 3.25758 1.91851 9.28978 3.17512 3.18565 1.90697 8.76393 3.072 7.61765 2.89682 6.47912 2.67548 5.36249 2.45072 7.66844 2.88645 11.5027 3.5211 10.3422 3.35133 8.15125 3.00616 9.2256 3.18914 8.76393 3.09477 7.04876 2.79435 6.52216 2.68087 4.92971 2.34221 4.90782 2.35121 7.61065 2.90549 8.14425 2.9911 4.85778 2.34688 6.0252 2.59121 5.47745 2.47563 8.16539 3.02237 7.66844 2.89643 8.74203 3.0881 7.64654 2.90513 10.3853 3.36058 8.6771 3.09818 7.57461 2.90748 8.699 3.09812 8.21618 2.99579 13.0521 3.79911 7.0988 2.79517 10.3063 3.36767 7.63954 2.90807 8.14425 2.99258 4.92971 2.34049 12.4607 3.7048 5.96027 2.58259 5.47745 2.48405 7.64654 2.88523 10.9111 3.44923 9.31167 3.21769 6.57294 2.69736 7.66844 2.89785 8.15125 2.9952 12.5763 3.71167 7.61065 2.90978 4.8006 2.34103 9.75084 3.27171 5.45556 2.45247 6.0252 2.57535 9.70842 3.28396 8.6701 3.09437 9.31167 3.17743 11.9996 3.6276 4.86478 2.33438 9.25389 3.17934 9.24674 3.18738 10.4072 3.3543 6.00331 2.55937 9.31167 3.17226 10.933 3.44059 7.64654 2.9037 7.6254 2.89134 5.96027 2.57782 9.85942 3.25959 10.8971 3.44454 5.99631 2.56917 7.0988 2.77588 12.0285 3.61251 5.41253 2.44813 8.12936 2.9801 7.63954 2.87959 12.0504 3.59749 7.0918 2.78636 7.0988 2.79823 10.3352 3.35382 5.47745 2.43709 8.74203 3.08678 8.76393 3.0826 7.64654 2.89102 8.76393 3.09072 9.28978 3.17627 9.31167 3.16574 6.0252 2.5608 6.0252 2.56565 6.00331 2.57234 8.15125 3.00897 3.76154 2.03976 5.94552 2.57927 8.21618 2.97778 5.45556 2.44905 5.47745 2.45053 5.97441 2.56288 9.26089 3.18311 5.44856 2.45927 4.88667 2.32514 6.49327 2.67811 5.99631 2.58513 7.66844 2.89502 9.31167 3.19186 2.69569 1.76705 4.38196 2.18535 8.18729 3.00433 5.44856 2.44425 8.10822 2.97639 3.26458 1.91833 7.0988 2.7832 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2.78214 8.21618 2.99717 8.1295 2.98421 8.72089 3.08989 4.28814 2.20194 6.57294 2.68817 8.76393 3.0866 9.26864 3.18191 7.57461 2.91038 12.0504 3.61582 7.12069 2.78455 5.98141 2.58536 10.4072 3.36902 8.06518 2.99231 8.19429 2.98632 8.17239 3.00023 5.36949 2.4656 6.57294 2.69894 6.55105 2.68227 7.12069 2.80528 10.3783 3.36438 5.95327 2.58275 4.90782 2.35121 5.43367 2.43576 9.83052 3.25846 8.72089 3.09534 5.99631 2.57404 8.72089 3.08186 5.44856 2.45421 7.12069 2.78311 4.87892 2.31785 5.99631 2.5788 6.0252 2.56891 11.4519 3.52605 8.14425 2.98582 5.44856 2.4544 4.38196 2.19106 2.71683 1.74031 5.96027 2.56166 9.85942 3.26324 5.98216 2.55511 5.47745 2.43538 5.36888 2.45 7.0918 2.78339 8.18729 2.99063 9.85942 3.26328 6.0252 2.5608 4.31003 2.20186 3.77643 2.04986 5.45556 2.45913 4.84364 2.33136 7.64654 2.89094 4.92971 2.33695 6.39305 2.66754 3.76929 2.06028 4.38196 2.21552 5.93838 2.58434 7.66844 2.90076 3.25758 1.92711 7.63954 2.89541 7.0988 2.79065 4.86478 2.35013 6.47212 2.67251 7.12069 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6.46498 2.68659 10.926 3.44673 3.69736 2.0875 5.99631 2.56594 4.88667 2.34289 5.44856 2.47109 4.35307 2.2008 6.00331 2.58677 7.66844 2.89216 4.30228 2.22032 5.98141 2.57734 3.79118 2.08588 9.26864 3.19115 6.57294 2.67754 7.66844 2.88929 7.07765 2.7837 9.80863 3.28636 3.83422 2.04497 4.87192 2.32863 5.43367 2.45775 7.60351 2.8929 6.47912 2.67228 7.64654 2.89516 8.19429 2.98761 3.74815 2.08699 9.83752 3.26221 5.41253 2.46156 4.38196 2.18739 9.31167 3.16585 6.52991 2.6857 4.35307 2.18781 3.80532 2.06366 6.54405 2.68382 6.57294 2.68356 6.57294 2.67743 7.0988 2.79816 4.92971 2.32974 4.36007 2.20288 5.95327 2.56026 8.21618 2.97916 4.88667 2.33227 7.6254 2.90125 2.73873 1.75881 2.73873 1.74239 5.42667 2.44259 6.50802 2.69363 9.7656 3.26672 5.44856 2.44086 5.90948 2.5687 7.0699 2.77317 7.04101 2.79274 8.17315 2.98953 4.82114 2.30977 3.83422 2.06116 5.92438 2.56858 8.17315 2.98395 4.90782 2.33895 4.38196 2.19108 3.78343 2.08369 7.0629 2.81039 8.71314 3.09638 5.47745 2.45062 4.35307 2.21393 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1.90317 8.76393 3.10011 3.76929 2.07824 7.0918 2.80555 6.0252 2.5882 4.31003 2.2222 4.31703 2.23871 5.43442 2.46641 8.17315 3.01965 4.92971 2.33509 4.38196 2.21554 3.80532 2.08343 4.92971 2.35094 3.79118 2.06607 3.22154 1.9193 7.04876 2.78995 4.90782 2.33522 4.35307 2.19728 5.34835 2.45607 4.33893 2.20881 6.57294 2.69283 8.76393 3.08659 4.88667 2.32699 3.21379 1.91686 3.1779 1.91544 5.42667 2.45277 9.26089 3.18832 5.47745 2.44036 4.30228 2.1976 4.90782 2.32648 4.92971 2.32093 7.0918 2.77906 5.92438 2.5686 9.24674 3.17048 5.96027 2.56649 6.52991 2.67649 6.0252 2.56411 8.64121 3.07982 5.40553 2.44983 4.38196 2.19295 4.92971 2.31906 7.56047 2.89359 7.12069 2.78617 4.92971 2.32974 4.31703 2.19779 6.46423 2.67703 6.55105 2.67754 6.52991 2.66568 10.3641 3.35977 5.93913 2.59111 5.41253 2.45146 3.25758 1.90159 9.26864 3.18583 6.0252 2.5737 8.74203 3.0895 4.36007 2.21194 3.79118 2.04591 5.45556 2.45242 8.6771 3.08355 5.47745 2.44902 5.47745 2.45398 9.85942 3.25583 7.4674 2.90495 8.76393 3.10537 5.98216 2.56964 4.35307 2.21037 2.63076 1.76592 3.79118 2.07804 9.85942 3.2722 4.35307 2.19889 6.57294 2.66967 6.47212 2.66478 7.07765 2.78812 6.57294 2.68356 5.97441 2.55969 5.99631 2.58525 4.90082 2.33189 3.24344 1.91058 6.52991 2.68285 9.75145 3.27719 7.56047 2.89632 7.66844 2.90206 3.77643 2.09374 5.41967 2.45117 5.94552 2.57786 7.6254 2.89556 6.49327 2.69962 6.54405 2.69157 5.42667 2.46299 11.5027 3.54092 8.17315 2.99235 5.31945 2.47156 8.17239 2.98924 8.72089 3.09124 7.07765 2.7897 7.66844 2.8764 4.35307 2.18578 9.85942 3.27967 4.33818 2.18974 8.76393 3.09597 3.79118 2.07401 3.79118 2.06397 8.62007 3.0858 8.19429 2.98632 3.21454 1.92159 5.95327 2.5618 7.59576 2.88846 4.35307 2.19143 6.55105 2.66681 2.16909 1.59161 5.43442 2.4412 4.92971 2.33333 4.88592 2.31607 4.35307 2.19717 4.87192 2.3234 5.45556 2.44735 5.99631 2.55311 5.97441 2.57267 6.0252 2.54785 5.45556 2.4524 7.0918 2.7909 4.274 2.19855 4.35307 2.20841 8.699 3.08879 8.76393 3.1 9.26864 3.1832 3.24344 1.91523 7.66844 2.87777 7.02612 2.78535 6.00331 2.55619 3.83422 2.07707 6.52991 2.66879 4.87192 2.33759 4.92971 2.36667 7.66844 2.89633 4.31003 2.22025 7.59651 2.92562 5.99631 2.57732 7.04801 2.80582 4.36007 2.2138 5.41253 2.46153 5.43442 2.4648 4.33893 2.21066 7.0918 2.79539 3.7115 2.04487 7.12069 2.81555 4.86478 2.33071 2.6668 1.73425 3.81232 2.07732 5.88834 2.58522 5.43442 2.44796 6.55105 2.67448 3.80532 2.04749 2.73873 1.76589 6.52991 2.6764 8.21618 2.99864 4.33893 2.20891 6.50102 2.6662 9.81563 3.2725 7.64654 2.88942 9.28278 3.1712 3.24269 1.90129 7.12069 2.78158 3.24344 1.91697 4.92971 2.31736 4.90782 2.31567 3.23569 1.89513 2.63076 1.74254 4.38196 2.19686 6.43534 2.67418 5.99631 2.5563 4.35307 2.20094 6.00331 2.56427 5.44856 2.44747 4.38196 2.21925 4.35307 2.18958 10.926 3.44196 3.25758 1.89244 5.98216 2.57921 5.47745 2.46908 3.83422 2.06335 5.36174 2.46388 4.38196 2.20805 5.43367 2.45086 4.35307 2.19343 5.47745 2.44552 4.90082 2.30343 7.12069 2.79202 5.43367 2.45437 7.12069 2.77721 6.45723 2.68169 2.69569 1.72422 3.83422 2.05709 2.63791 1.76313 8.15839 2.98676 4.35307 2.18771 4.33893 2.19565 3.28647 1.91815 7.0918 2.78628 6.54405 2.67761 6.0252 2.56077 7.12069 2.78311 3.80532 2.0697 7.0918 2.79388 8.76393 3.08532 3.26458 1.94619 3.28647 1.92476 5.47745 2.45223 3.23569 1.91456 6.50102 2.69073 4.38196 2.18741 6.41495 2.68743 5.45556 2.44399 5.47745 2.44893 3.78343 2.04978 3.76229 2.05634 2.1183 1.58218 5.98216 2.57438 8.18729 2.99196 4.92971 2.34043 4.92971 2.31732 4.28814 2.20013 5.45556 2.44571 6.57294 2.6712 6.57294 2.67896 6.0252 2.56571 4.38196 2.19483 5.99631 2.56118 6.00331 2.56423 3.76229 2.06044 4.86478 2.31845 8.692 3.09691 7.6254 2.887 3.14262 1.92509 3.76154 2.05811 6.57294 2.68196 6.52916 2.67929 3.83422 2.0572 5.42667 2.44609 4.90082 2.33018 4.33118 2.18424 4.92971 2.32797 6.50802 2.69357 5.45556 2.44571 4.92971 2.31554 3.83422 2.04499 5.43367 2.46266 8.73503 3.09492 7.0918 2.78191 2.19098 1.59407 4.38196 2.18915 2.56583 1.74826 6.52991 2.68727 10.3564 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2837.17 -1.81729e+131 0.0140129 2529.37 -1.81729e+131 0.014837 2226.82 4.40721e-280 0.015985 1960.88 4.40721e-280 0.0167449 1653.2 1.84467e+19 0.0181648 1446.05 5.67321e+216 0.0197214 1242.7 4.49371e+245 0.0205081 1046.31 4.49371e+245 0.0219522 895.069 4.69054e+192 0.0248015 727.543 8.62169e+211 0.0263197 598.171 8.62169e+211 -8.61157999735e-315 -8.61157999735e-315 3.74996e-68 3919.89 2.2385 8.75213e-78 4462.63 2.31685 -3.14338999988e-315 4830.61 2.39794 1.08255e-226 5193.21 2.48186 1.07499e+102 5501.58 2.56873 1.07499e+102 5628.96 2.65864 1.07508e+102 5634.75 2.75169 1.07508e+102 5724.73 2.848 3.81253e-303 5835.49 2.94768 1.35808e-312 5798.97 3.05085 1.07513e+102 5767.32 3.15763 1.07513e+102 5694.24 3.26814 4.38310999756e-315 5525.05 3.38253 8.52703999979e-316 5417.49 3.50092 0.0 5253.01 3.62345 0.0 5074.68 3.75027 0.0 4929.65 3.88153 3.54615999709e-315 4745.3 4.01738 3.54615999709e-315 4841.86 4.15799 2.71357e+104 4897.12 4.30352 2.72432e+104 4974.21 4.45414 2.15015e+102 4586.67 4.61004 1.07508e+102 4948.31 4.77139 3.53040999951e-315 5184.8 4.93839 0.0 5008.83 5.11123 0.0 4940.5 5.29012 2.00379e-270 4859.81 5.47528 2.00379e-270 4602.81 5.66691 4.58351e-312 4362.55 5.86525 1.7472e-287 4081.97 6.07054 1.74845e-287 3771.18 6.28301 1.24882e-290 3732.39 6.50291 0.0 3291.09 6.73051 0.0 2837.17 6.96608 0.0 2529.37 7.2099 0.0 2226.82 7.46224 1.07499e+102 1960.88 7.72342 3.32977e-311 1653.2 7.99374 7.19961e-310 1446.05 8.27352 7.19962e-310 1242.7 8.56309 8.2010700122e-316 1046.31 8.8628 3.18298999973e-314 895.069 9.173 7.42699000005e-314 727.543 9.49406 4.24398999993e-314 598.171 9.82867 3.16202013338e-322 -8.61157999735e-315 -3.78577e-270 0.0 2.2385 0.00307782 0.0 2.31685 0.00300224 3.53040999951e-315 2.39794 0.00292546 TK49 c10_SANS LOQ neutron HAB 575.0 main-detector-bank 4145.02 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt 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0.68084 0.0167449 8.27352 0.690755 0.0181648 8.56309 0.695218 0.0197214 8.8628 0.663369 0.0205081 9.173 0.656758 0.0219522 9.49406 0.668971 0.0248015 9.82867 0.643715 0.0263197 5.0 -3.78577e-270 -8.61157999735e-315 -1.24052e-265 0.0130497 3919.89 6.22902e-151 0.0120051 4462.63 6.22902e-151 0.0112577 4830.61 2.18146e+15 0.01104 5193.21 2.18146e+15 0.0107071 5501.58 5.83244494916e-320 0.010757 5628.96 5.82009e-73 0.0106204 5634.75 2.86436e+126 0.0107288 5724.73 6.43127e+247 0.0105482 5835.49 6.43127e+247 0.0103436 5798.97 -2.37127e+226 0.0105877 5767.32 2.86442e+126 0.0105895 5694.24 5.52737e-309 0.0109026 5525.05 1.46672e-310 0.0108399 5417.49 1.66641e+178 0.0110517 5253.01 1.66641e+178 0.0110209 5074.68 8.62375e+211 0.0111882 4929.65 8.62375e+211 0.0110145 4745.3 2.03531e-87 0.0110323 4841.86 2.97389e-39 0.0110456 4897.12 2.97389e-39 0.0109689 4974.21 1.18818e-212 0.0106718 4586.67 4.38734e+245 0.0107276 4948.31 4.38734e+245 0.0105454 5184.8 -1.81729e+131 0.0106594 5008.83 -1.81729e+131 0.0107767 4940.5 6.44115e-232 0.0107133 4859.81 6.44115e-232 0.0109161 4602.81 4.36995e+245 0.0113942 4362.55 4.36995e+245 0.0114788 4081.97 2.9782e-39 0.0120655 3771.18 5.83667e-73 0.0119684 3732.39 1.74941e+64 0.0125797 3291.09 1.74941e+64 0.0135324 2837.17 -1.81729e+131 0.0140129 2529.37 -1.81729e+131 0.014837 2226.82 4.40721e-280 0.015985 1960.88 4.40721e-280 0.0167449 1653.2 1.84467e+19 0.0181648 1446.05 5.67321e+216 0.0197214 1242.7 4.49371e+245 0.0205081 1046.31 4.49371e+245 0.0219522 895.069 4.69054e+192 0.0248015 727.543 8.62169e+211 0.0263197 598.171 8.62169e+211 -8.61157999735e-315 -8.61157999735e-315 3.74996e-68 3919.89 2.2385 8.75213e-78 4462.63 2.31685 -3.14338999988e-315 4830.61 2.39794 1.08255e-226 5193.21 2.48186 1.07499e+102 5501.58 2.56873 1.07499e+102 5628.96 2.65864 1.07508e+102 5634.75 2.75169 1.07508e+102 5724.73 2.848 3.81253e-303 5835.49 2.94768 1.35808e-312 5798.97 3.05085 1.07513e+102 5767.32 3.15763 1.07513e+102 5694.24 3.26814 4.38310999756e-315 5525.05 3.38253 8.52703999979e-316 5417.49 3.50092 0.0 5253.01 3.62345 0.0 5074.68 3.75027 0.0 4929.65 3.88153 3.54615999709e-315 4745.3 4.01738 3.54615999709e-315 4841.86 4.15799 2.71357e+104 4897.12 4.30352 2.72432e+104 4974.21 4.45414 2.15015e+102 4586.67 4.61004 1.07508e+102 4948.31 4.77139 3.53040999951e-315 5184.8 4.93839 0.0 5008.83 5.11123 0.0 4940.5 5.29012 2.00379e-270 4859.81 5.47528 2.00379e-270 4602.81 5.66691 4.58351e-312 4362.55 5.86525 1.7472e-287 4081.97 6.07054 1.74845e-287 3771.18 6.28301 1.24882e-290 3732.39 6.50291 0.0 3291.09 6.73051 0.0 2837.17 6.96608 0.0 2529.37 7.2099 0.0 2226.82 7.46224 1.07499e+102 1960.88 7.72342 3.32977e-311 1653.2 7.99374 7.19961e-310 1446.05 8.27352 7.19962e-310 1242.7 8.56309 8.2010700122e-316 1046.31 8.8628 3.18298999973e-314 895.069 9.173 7.42699000005e-314 727.543 9.49406 4.24398999993e-314 598.171 9.82867 3.16202013338e-322 -8.61157999735e-315 -3.78577e-270 0.0 2.2385 0.00307782 0.0 2.31685 0.00300224 3.53040999951e-315 2.39794 0.00292546 TK49 c10_SANS LOQ neutron HAB 575.0 main-detector-bank 4145.02 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt sasdata-0.8.1/test/sasdataloader/data/TestExtensions.notxml000066400000000000000000001324351427502211700241120ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.009 85.3333 0.852491 0.0 0.011 72.5398 0.639548 0.0 0.013 63.3582 0.494127 0.0 0.015 57.0952 0.414116 0.0 0.017 51.0139 0.35145 0.0 0.019 46.4746 0.308755 0.0 0.021 41.7191 0.271641 0.0 0.023 37.4208 0.244658 0.0 0.025 33.7352 0.219594 0.0 0.027 30.6073 0.203138 0.0 0.029 27.7309 0.185859 0.0 0.031 25.2579 0.171356 0.0 0.033 22.7712 0.159062 0.0 0.035 20.5323 0.146135 0.0 0.037 19.0744 0.136393 0.0 0.039 17.2832 0.127623 0.0 0.041 15.7399 0.118288 0.0 0.043 14.5598 0.111759 0.0 0.045 13.5906 0.105148 0.0 0.047 12.6707 0.0996579 0.0 0.049 11.5247 0.0929646 0.0 0.051 10.7089 0.0888575 0.0 0.053 10.1436 0.0849394 0.0 0.055 9.49446 0.0811205 0.0 0.057 8.80775 0.0773967 0.0 0.059 8.33366 0.0748147 0.0 0.061 7.79157 0.0720107 0.0 0.063 7.25902 0.0693582 0.0 0.065 7.04789 0.0677591 0.0 0.067 6.53311 0.0652207 0.0 0.069 6.2453 0.0642016 0.0 0.071 5.94152 0.0625768 0.0 0.073 5.70816 0.0612955 0.0 0.075 5.24449 0.060141 0.0 0.077 5.08291 0.0582239 0.0 0.079 4.88135 0.057969 0.0 0.081 4.60942 0.056813 0.0 0.083 4.46606 0.0569381 0.0 0.085 4.32473 0.0558766 0.0 0.087 4.14144 0.0552525 0.0 0.089 3.86504 0.0544569 0.0 0.091 3.74272 0.0529596 0.0 0.093 3.68281 0.052891 0.0 0.095 3.46991 0.0517565 0.0 0.097 3.37244 0.0509328 0.0 0.099 3.27074 0.0505183 0.0 0.101 3.13326 0.0490847 0.0 0.103 3.01387 0.0487012 0.0 0.105 2.87628 0.0484307 0.0 0.107 2.85043 0.0476786 0.0 0.109 2.72799 0.0475526 0.0 0.111 2.61206 0.0467475 0.0 0.113 2.58895 0.0469767 0.0 0.115 2.45987 0.0460139 0.0 0.117 2.37723 0.045272 0.0 0.119 2.34122 0.0453741 0.0 0.121 2.21745 0.0444485 0.0 0.123 2.12646 0.0438385 0.0 0.125 2.11264 0.0441662 0.0 0.127 2.07523 0.0438979 0.0 0.129 2.03548 0.0442422 0.0 0.131 1.92452 0.0435959 0.0 0.133 1.90866 0.0437401 0.0 0.135 1.91252 0.0443163 0.0 0.137 1.80405 0.043466 0.0 0.139 1.72166 0.0429246 0.0 0.141 1.67199 0.042469 0.0 0.143 1.63282 0.0430074 0.0 0.145 1.63712 0.0438557 0.0 0.147 1.5862 0.0434135 0.0 0.149 1.56121 0.0432591 0.0 0.151 1.49764 0.0426577 0.0 0.153 1.53828 0.0446481 0.0 0.155 1.47366 0.0441973 0.0 0.157 1.40582 0.0430461 0.0 0.159 1.40491 0.0439883 0.0 0.161 1.34639 0.044193 0.0 0.163 1.32238 0.0438008 0.0 0.165 1.33885 0.0445383 0.0 0.167 1.29608 0.0451575 0.0 0.169 1.30562 0.0460656 0.0 0.171 1.17147 0.0435717 0.0 0.173 1.18565 0.0449072 0.0 0.175 1.18944 0.0465319 0.0 0.177 1.17055 0.0456562 0.0 0.179 1.08571 0.0453852 0.0 0.181 1.06208 0.0463335 0.0 0.183 1.06187 0.0458284 0.0 0.185 1.02727 0.0472613 0.0 0.187 0.995169 0.0465526 0.0 0.189 1.02569 0.0483728 0.0 0.191 0.981154 0.0490559 0.0 0.193 1.01831 0.0502348 0.0 0.195 0.968102 0.0504426 0.0 0.197 0.940656 0.0512734 0.0 0.199 1.05762 0.0547469 0.0 0.201 0.949872 0.055229 0.0 0.203 0.891716 0.0531346 0.0 0.205 0.876084 0.0548681 0.0 0.207 0.932101 0.0576812 0.0 0.209 0.927755 0.0593404 0.0 0.211 0.87669 0.0600369 0.0 0.213 0.809125 0.0588107 0.0 0.215 0.941202 0.0659121 0.0 0.217 0.946175 0.0690784 0.0 0.219 0.859875 0.0674435 0.0 0.221 0.959508 0.0718856 0.0 0.223 0.763222 0.0702866 0.0 0.225 0.785467 0.0742144 0.0 0.227 0.81876 0.074266 0.0 0.229 0.678311 0.0722578 0.0 0.231 0.761442 0.0814516 0.0 0.233 0.757076 0.0825262 0.0 0.235 0.600636 0.075041 0.0 0.237 0.685635 0.0842392 0.0 0.239 0.799186 0.0974365 0.0 0.241 0.737526 0.0957286 0.0 0.243 0.716415 0.0970448 0.0 0.245 0.720413 0.0981996 0.0 0.247 0.604059 0.100869 0.0 0.249 0.649073 0.109281 0.0 0.251 0.700691 0.114325 0.0 0.253 0.586789 0.108324 0.0 0.255 0.765838 0.139579 0.0 0.257 0.828968 0.156723 0.0 0.259 0.616499 0.137866 0.0 0.261 0.526011 0.126209 0.0 0.263 0.51277 0.126339 0.0 0.265 0.604189 0.166393 0.0 0.267 0.738765 0.194006 0.0 0.269 0.462803 0.155354 0.0 0.271 0.478694 0.171676 0.0 0.273 0.711983 0.255539 0.0 0.275 0.473304 0.230752 0.0 0.277 0.536817 0.262627 0.0 0.279 0.660654 0.297519 0.0 0.281 0.408902 0.24585 0.0 0.283 0.0 1.0 0.0 2.2385 0.81703 0.0130497 2.31685 0.801978 0.0120051 2.39794 0.782436 0.0112577 2.48186 0.795586 0.01104 2.56873 0.794175 0.0107071 2.65864 0.807059 0.010757 2.75169 0.797216 0.0106204 2.848 0.811763 0.0107288 2.94768 0.805778 0.0105482 3.05085 0.787672 0.0103436 3.15763 0.804061 0.0105877 3.26814 0.799089 0.0105895 3.38253 0.810401 0.0109026 3.50092 0.797859 0.0108399 3.62345 0.801003 0.0110517 3.75027 0.78509 0.0110209 3.88153 0.785537 0.0111882 4.01738 0.758743 0.0110145 4.15799 0.767664 0.0110323 4.30352 0.772965 0.0110456 4.45414 0.773616 0.0109689 4.61004 0.72275 0.0106718 4.77139 0.754627 0.0107276 4.93839 0.759325 0.0105454 5.11123 0.7544 0.0106594 5.29012 0.75748 0.0107767 5.47528 0.746847 0.0107133 5.66691 0.740591 0.0109161 5.86525 0.752582 0.0113942 6.07054 0.733384 0.0114788 6.28301 0.740944 0.0120655 6.50291 0.731187 0.0119684 6.73051 0.72167 0.0125797 6.96608 0.720803 0.0135324 7.2099 0.704751 0.0140129 7.46224 0.700147 0.014837 7.72342 0.707843 0.015985 7.99374 0.68084 0.0167449 8.27352 0.690755 0.0181648 8.56309 0.695218 0.0197214 8.8628 0.663369 0.0205081 9.173 0.656758 0.0219522 9.49406 0.668971 0.0248015 9.82867 0.643715 0.0263197 5.0 -3.78577e-270 -8.61157999735e-315 -1.24052e-265 0.0130497 3919.89 6.22902e-151 0.0120051 4462.63 6.22902e-151 0.0112577 4830.61 2.18146e+15 0.01104 5193.21 2.18146e+15 0.0107071 5501.58 5.83244494916e-320 0.010757 5628.96 5.82009e-73 0.0106204 5634.75 2.86436e+126 0.0107288 5724.73 6.43127e+247 0.0105482 5835.49 6.43127e+247 0.0103436 5798.97 -2.37127e+226 0.0105877 5767.32 2.86442e+126 0.0105895 5694.24 5.52737e-309 0.0109026 5525.05 1.46672e-310 0.0108399 5417.49 1.66641e+178 0.0110517 5253.01 1.66641e+178 0.0110209 5074.68 8.62375e+211 0.0111882 4929.65 8.62375e+211 0.0110145 4745.3 2.03531e-87 0.0110323 4841.86 2.97389e-39 0.0110456 4897.12 2.97389e-39 0.0109689 4974.21 1.18818e-212 0.0106718 4586.67 4.38734e+245 0.0107276 4948.31 4.38734e+245 0.0105454 5184.8 -1.81729e+131 0.0106594 5008.83 -1.81729e+131 0.0107767 4940.5 6.44115e-232 0.0107133 4859.81 6.44115e-232 0.0109161 4602.81 4.36995e+245 0.0113942 4362.55 4.36995e+245 0.0114788 4081.97 2.9782e-39 0.0120655 3771.18 5.83667e-73 0.0119684 3732.39 1.74941e+64 0.0125797 3291.09 1.74941e+64 0.0135324 2837.17 -1.81729e+131 0.0140129 2529.37 -1.81729e+131 0.014837 2226.82 4.40721e-280 0.015985 1960.88 4.40721e-280 0.0167449 1653.2 1.84467e+19 0.0181648 1446.05 5.67321e+216 0.0197214 1242.7 4.49371e+245 0.0205081 1046.31 4.49371e+245 0.0219522 895.069 4.69054e+192 0.0248015 727.543 8.62169e+211 0.0263197 598.171 8.62169e+211 -8.61157999735e-315 -8.61157999735e-315 3.74996e-68 3919.89 2.2385 8.75213e-78 4462.63 2.31685 -3.14338999988e-315 4830.61 2.39794 1.08255e-226 5193.21 2.48186 1.07499e+102 5501.58 2.56873 1.07499e+102 5628.96 2.65864 1.07508e+102 5634.75 2.75169 1.07508e+102 5724.73 2.848 3.81253e-303 5835.49 2.94768 1.35808e-312 5798.97 3.05085 1.07513e+102 5767.32 3.15763 1.07513e+102 5694.24 3.26814 4.38310999756e-315 5525.05 3.38253 8.52703999979e-316 5417.49 3.50092 0.0 5253.01 3.62345 0.0 5074.68 3.75027 0.0 4929.65 3.88153 3.54615999709e-315 4745.3 4.01738 3.54615999709e-315 4841.86 4.15799 2.71357e+104 4897.12 4.30352 2.72432e+104 4974.21 4.45414 2.15015e+102 4586.67 4.61004 1.07508e+102 4948.31 4.77139 3.53040999951e-315 5184.8 4.93839 0.0 5008.83 5.11123 0.0 4940.5 5.29012 2.00379e-270 4859.81 5.47528 2.00379e-270 4602.81 5.66691 4.58351e-312 4362.55 5.86525 1.7472e-287 4081.97 6.07054 1.74845e-287 3771.18 6.28301 1.24882e-290 3732.39 6.50291 0.0 3291.09 6.73051 0.0 2837.17 6.96608 0.0 2529.37 7.2099 0.0 2226.82 7.46224 1.07499e+102 1960.88 7.72342 3.32977e-311 1653.2 7.99374 7.19961e-310 1446.05 8.27352 7.19962e-310 1242.7 8.56309 8.2010700122e-316 1046.31 8.8628 3.18298999973e-314 895.069 9.173 7.42699000005e-314 727.543 9.49406 4.24398999993e-314 598.171 9.82867 3.16202013338e-322 -8.61157999735e-315 -3.78577e-270 0.0 2.2385 0.00307782 0.0 2.31685 0.00300224 3.53040999951e-315 2.39794 0.00292546 TK49 c10_SANS LOQ neutron HAB 575.0 main-detector-bank 4145.02 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt sasdata-0.8.1/test/sasdataloader/data/TestExtensions.nxs000066400000000000000000001324351427502211700234010ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.009 85.3333 0.852491 0.0 0.011 72.5398 0.639548 0.0 0.013 63.3582 0.494127 0.0 0.015 57.0952 0.414116 0.0 0.017 51.0139 0.35145 0.0 0.019 46.4746 0.308755 0.0 0.021 41.7191 0.271641 0.0 0.023 37.4208 0.244658 0.0 0.025 33.7352 0.219594 0.0 0.027 30.6073 0.203138 0.0 0.029 27.7309 0.185859 0.0 0.031 25.2579 0.171356 0.0 0.033 22.7712 0.159062 0.0 0.035 20.5323 0.146135 0.0 0.037 19.0744 0.136393 0.0 0.039 17.2832 0.127623 0.0 0.041 15.7399 0.118288 0.0 0.043 14.5598 0.111759 0.0 0.045 13.5906 0.105148 0.0 0.047 12.6707 0.0996579 0.0 0.049 11.5247 0.0929646 0.0 0.051 10.7089 0.0888575 0.0 0.053 10.1436 0.0849394 0.0 0.055 9.49446 0.0811205 0.0 0.057 8.80775 0.0773967 0.0 0.059 8.33366 0.0748147 0.0 0.061 7.79157 0.0720107 0.0 0.063 7.25902 0.0693582 0.0 0.065 7.04789 0.0677591 0.0 0.067 6.53311 0.0652207 0.0 0.069 6.2453 0.0642016 0.0 0.071 5.94152 0.0625768 0.0 0.073 5.70816 0.0612955 0.0 0.075 5.24449 0.060141 0.0 0.077 5.08291 0.0582239 0.0 0.079 4.88135 0.057969 0.0 0.081 4.60942 0.056813 0.0 0.083 4.46606 0.0569381 0.0 0.085 4.32473 0.0558766 0.0 0.087 4.14144 0.0552525 0.0 0.089 3.86504 0.0544569 0.0 0.091 3.74272 0.0529596 0.0 0.093 3.68281 0.052891 0.0 0.095 3.46991 0.0517565 0.0 0.097 3.37244 0.0509328 0.0 0.099 3.27074 0.0505183 0.0 0.101 3.13326 0.0490847 0.0 0.103 3.01387 0.0487012 0.0 0.105 2.87628 0.0484307 0.0 0.107 2.85043 0.0476786 0.0 0.109 2.72799 0.0475526 0.0 0.111 2.61206 0.0467475 0.0 0.113 2.58895 0.0469767 0.0 0.115 2.45987 0.0460139 0.0 0.117 2.37723 0.045272 0.0 0.119 2.34122 0.0453741 0.0 0.121 2.21745 0.0444485 0.0 0.123 2.12646 0.0438385 0.0 0.125 2.11264 0.0441662 0.0 0.127 2.07523 0.0438979 0.0 0.129 2.03548 0.0442422 0.0 0.131 1.92452 0.0435959 0.0 0.133 1.90866 0.0437401 0.0 0.135 1.91252 0.0443163 0.0 0.137 1.80405 0.043466 0.0 0.139 1.72166 0.0429246 0.0 0.141 1.67199 0.042469 0.0 0.143 1.63282 0.0430074 0.0 0.145 1.63712 0.0438557 0.0 0.147 1.5862 0.0434135 0.0 0.149 1.56121 0.0432591 0.0 0.151 1.49764 0.0426577 0.0 0.153 1.53828 0.0446481 0.0 0.155 1.47366 0.0441973 0.0 0.157 1.40582 0.0430461 0.0 0.159 1.40491 0.0439883 0.0 0.161 1.34639 0.044193 0.0 0.163 1.32238 0.0438008 0.0 0.165 1.33885 0.0445383 0.0 0.167 1.29608 0.0451575 0.0 0.169 1.30562 0.0460656 0.0 0.171 1.17147 0.0435717 0.0 0.173 1.18565 0.0449072 0.0 0.175 1.18944 0.0465319 0.0 0.177 1.17055 0.0456562 0.0 0.179 1.08571 0.0453852 0.0 0.181 1.06208 0.0463335 0.0 0.183 1.06187 0.0458284 0.0 0.185 1.02727 0.0472613 0.0 0.187 0.995169 0.0465526 0.0 0.189 1.02569 0.0483728 0.0 0.191 0.981154 0.0490559 0.0 0.193 1.01831 0.0502348 0.0 0.195 0.968102 0.0504426 0.0 0.197 0.940656 0.0512734 0.0 0.199 1.05762 0.0547469 0.0 0.201 0.949872 0.055229 0.0 0.203 0.891716 0.0531346 0.0 0.205 0.876084 0.0548681 0.0 0.207 0.932101 0.0576812 0.0 0.209 0.927755 0.0593404 0.0 0.211 0.87669 0.0600369 0.0 0.213 0.809125 0.0588107 0.0 0.215 0.941202 0.0659121 0.0 0.217 0.946175 0.0690784 0.0 0.219 0.859875 0.0674435 0.0 0.221 0.959508 0.0718856 0.0 0.223 0.763222 0.0702866 0.0 0.225 0.785467 0.0742144 0.0 0.227 0.81876 0.074266 0.0 0.229 0.678311 0.0722578 0.0 0.231 0.761442 0.0814516 0.0 0.233 0.757076 0.0825262 0.0 0.235 0.600636 0.075041 0.0 0.237 0.685635 0.0842392 0.0 0.239 0.799186 0.0974365 0.0 0.241 0.737526 0.0957286 0.0 0.243 0.716415 0.0970448 0.0 0.245 0.720413 0.0981996 0.0 0.247 0.604059 0.100869 0.0 0.249 0.649073 0.109281 0.0 0.251 0.700691 0.114325 0.0 0.253 0.586789 0.108324 0.0 0.255 0.765838 0.139579 0.0 0.257 0.828968 0.156723 0.0 0.259 0.616499 0.137866 0.0 0.261 0.526011 0.126209 0.0 0.263 0.51277 0.126339 0.0 0.265 0.604189 0.166393 0.0 0.267 0.738765 0.194006 0.0 0.269 0.462803 0.155354 0.0 0.271 0.478694 0.171676 0.0 0.273 0.711983 0.255539 0.0 0.275 0.473304 0.230752 0.0 0.277 0.536817 0.262627 0.0 0.279 0.660654 0.297519 0.0 0.281 0.408902 0.24585 0.0 0.283 0.0 1.0 0.0 2.2385 0.81703 0.0130497 2.31685 0.801978 0.0120051 2.39794 0.782436 0.0112577 2.48186 0.795586 0.01104 2.56873 0.794175 0.0107071 2.65864 0.807059 0.010757 2.75169 0.797216 0.0106204 2.848 0.811763 0.0107288 2.94768 0.805778 0.0105482 3.05085 0.787672 0.0103436 3.15763 0.804061 0.0105877 3.26814 0.799089 0.0105895 3.38253 0.810401 0.0109026 3.50092 0.797859 0.0108399 3.62345 0.801003 0.0110517 3.75027 0.78509 0.0110209 3.88153 0.785537 0.0111882 4.01738 0.758743 0.0110145 4.15799 0.767664 0.0110323 4.30352 0.772965 0.0110456 4.45414 0.773616 0.0109689 4.61004 0.72275 0.0106718 4.77139 0.754627 0.0107276 4.93839 0.759325 0.0105454 5.11123 0.7544 0.0106594 5.29012 0.75748 0.0107767 5.47528 0.746847 0.0107133 5.66691 0.740591 0.0109161 5.86525 0.752582 0.0113942 6.07054 0.733384 0.0114788 6.28301 0.740944 0.0120655 6.50291 0.731187 0.0119684 6.73051 0.72167 0.0125797 6.96608 0.720803 0.0135324 7.2099 0.704751 0.0140129 7.46224 0.700147 0.014837 7.72342 0.707843 0.015985 7.99374 0.68084 0.0167449 8.27352 0.690755 0.0181648 8.56309 0.695218 0.0197214 8.8628 0.663369 0.0205081 9.173 0.656758 0.0219522 9.49406 0.668971 0.0248015 9.82867 0.643715 0.0263197 5.0 -3.78577e-270 -8.61157999735e-315 -1.24052e-265 0.0130497 3919.89 6.22902e-151 0.0120051 4462.63 6.22902e-151 0.0112577 4830.61 2.18146e+15 0.01104 5193.21 2.18146e+15 0.0107071 5501.58 5.83244494916e-320 0.010757 5628.96 5.82009e-73 0.0106204 5634.75 2.86436e+126 0.0107288 5724.73 6.43127e+247 0.0105482 5835.49 6.43127e+247 0.0103436 5798.97 -2.37127e+226 0.0105877 5767.32 2.86442e+126 0.0105895 5694.24 5.52737e-309 0.0109026 5525.05 1.46672e-310 0.0108399 5417.49 1.66641e+178 0.0110517 5253.01 1.66641e+178 0.0110209 5074.68 8.62375e+211 0.0111882 4929.65 8.62375e+211 0.0110145 4745.3 2.03531e-87 0.0110323 4841.86 2.97389e-39 0.0110456 4897.12 2.97389e-39 0.0109689 4974.21 1.18818e-212 0.0106718 4586.67 4.38734e+245 0.0107276 4948.31 4.38734e+245 0.0105454 5184.8 -1.81729e+131 0.0106594 5008.83 -1.81729e+131 0.0107767 4940.5 6.44115e-232 0.0107133 4859.81 6.44115e-232 0.0109161 4602.81 4.36995e+245 0.0113942 4362.55 4.36995e+245 0.0114788 4081.97 2.9782e-39 0.0120655 3771.18 5.83667e-73 0.0119684 3732.39 1.74941e+64 0.0125797 3291.09 1.74941e+64 0.0135324 2837.17 -1.81729e+131 0.0140129 2529.37 -1.81729e+131 0.014837 2226.82 4.40721e-280 0.015985 1960.88 4.40721e-280 0.0167449 1653.2 1.84467e+19 0.0181648 1446.05 5.67321e+216 0.0197214 1242.7 4.49371e+245 0.0205081 1046.31 4.49371e+245 0.0219522 895.069 4.69054e+192 0.0248015 727.543 8.62169e+211 0.0263197 598.171 8.62169e+211 -8.61157999735e-315 -8.61157999735e-315 3.74996e-68 3919.89 2.2385 8.75213e-78 4462.63 2.31685 -3.14338999988e-315 4830.61 2.39794 1.08255e-226 5193.21 2.48186 1.07499e+102 5501.58 2.56873 1.07499e+102 5628.96 2.65864 1.07508e+102 5634.75 2.75169 1.07508e+102 5724.73 2.848 3.81253e-303 5835.49 2.94768 1.35808e-312 5798.97 3.05085 1.07513e+102 5767.32 3.15763 1.07513e+102 5694.24 3.26814 4.38310999756e-315 5525.05 3.38253 8.52703999979e-316 5417.49 3.50092 0.0 5253.01 3.62345 0.0 5074.68 3.75027 0.0 4929.65 3.88153 3.54615999709e-315 4745.3 4.01738 3.54615999709e-315 4841.86 4.15799 2.71357e+104 4897.12 4.30352 2.72432e+104 4974.21 4.45414 2.15015e+102 4586.67 4.61004 1.07508e+102 4948.31 4.77139 3.53040999951e-315 5184.8 4.93839 0.0 5008.83 5.11123 0.0 4940.5 5.29012 2.00379e-270 4859.81 5.47528 2.00379e-270 4602.81 5.66691 4.58351e-312 4362.55 5.86525 1.7472e-287 4081.97 6.07054 1.74845e-287 3771.18 6.28301 1.24882e-290 3732.39 6.50291 0.0 3291.09 6.73051 0.0 2837.17 6.96608 0.0 2529.37 7.2099 0.0 2226.82 7.46224 1.07499e+102 1960.88 7.72342 3.32977e-311 1653.2 7.99374 7.19961e-310 1446.05 8.27352 7.19962e-310 1242.7 8.56309 8.2010700122e-316 1046.31 8.8628 3.18298999973e-314 895.069 9.173 7.42699000005e-314 727.543 9.49406 4.24398999993e-314 598.171 9.82867 3.16202013338e-322 -8.61157999735e-315 -3.78577e-270 0.0 2.2385 0.00307782 0.0 2.31685 0.00300224 3.53040999951e-315 2.39794 0.00292546 TK49 c10_SANS LOQ neutron HAB 575.0 main-detector-bank 4145.02 Mantid generated CanSAS1D XML 02-Aug-2013 16:53:56 2.5.3 K:/masks/MASKLOQ_MAN_132E_Lu_Banjo_12mm.txt sasdata-0.8.1/test/sasdataloader/data/TestExtensions.xml000066400000000000000000001324351427502211700233710ustar00rootroot00000000000000 TK49 c10_SANS 79680 0.009 85.3333 0.852491 0.0 0.011 72.5398 0.639548 0.0 0.013 63.3582 0.494127 0.0 0.015 57.0952 0.414116 0.0 0.017 51.0139 0.35145 0.0 0.019 46.4746 0.308755 0.0 0.021 41.7191 0.271641 0.0 0.023 37.4208 0.244658 0.0 0.025 33.7352 0.219594 0.0 0.027 30.6073 0.203138 0.0 0.029 27.7309 0.185859 0.0 0.031 25.2579 0.171356 0.0 0.033 22.7712 0.159062 0.0 0.035 20.5323 0.146135 0.0 0.037 19.0744 0.136393 0.0 0.039 17.2832 0.127623 0.0 0.041 15.7399 0.118288 0.0 0.043 14.5598 0.111759 0.0 0.045 13.5906 0.105148 0.0 0.047 12.6707 0.0996579 0.0 0.049 11.5247 0.0929646 0.0 0.051 10.7089 0.0888575 0.0 0.053 10.1436 0.0849394 0.0 0.055 9.49446 0.0811205 0.0 0.057 8.80775 0.0773967 0.0 0.059 8.33366 0.0748147 0.0 0.061 7.79157 0.0720107 0.0 0.063 7.25902 0.0693582 0.0 0.065 7.04789 0.0677591 0.0 0.067 6.53311 0.0652207 0.0 0.069 6.2453 0.0642016 0.0 0.071 5.94152 0.0625768 0.0 0.073 5.70816 0.0612955 0.0 0.075 5.24449 0.060141 0.0 0.077 5.08291 0.0582239 0.0 0.079 4.88135 0.057969 0.0 0.081 4.60942 0.056813 0.0 0.083 4.46606 0.0569381 0.0 0.085 4.32473 0.0558766 0.0 0.087 4.14144 0.0552525 0.0 0.089 3.86504 0.0544569 0.0 0.091 3.74272 0.0529596 0.0 0.093 3.68281 0.052891 0.0 0.095 3.46991 0.0517565 0.0 0.097 3.37244 0.0509328 0.0 0.099 3.27074 0.0505183 0.0 0.101 3.13326 0.0490847 0.0 0.103 3.01387 0.0487012 0.0 0.105 2.87628 0.0484307 0.0 0.107 2.85043 0.0476786 0.0 0.109 2.72799 0.0475526 0.0 0.111 2.61206 0.0467475 0.0 0.113 2.58895 0.0469767 0.0 0.115 2.45987 0.0460139 0.0 0.117 2.37723 0.045272 0.0 0.119 2.34122 0.0453741 0.0 0.121 2.21745 0.0444485 0.0 0.123 2.12646 0.0438385 0.0 0.125 2.11264 0.0441662 0.0 0.127 2.07523 0.0438979 0.0 0.129 2.03548 0.0442422 0.0 0.131 1.92452 0.0435959 0.0 0.133 1.90866 0.0437401 0.0 0.135 1.91252 0.0443163 0.0 0.137 1.80405 0.043466 0.0 0.139 1.72166 0.0429246 0.0 0.141 1.67199 0.042469 0.0 0.143 1.63282 0.0430074 0.0 0.145 1.63712 0.0438557 0.0 0.147 1.5862 0.0434135 0.0 0.149 1.56121 0.0432591 0.0 0.151 1.49764 0.0426577 0.0 0.153 1.53828 0.0446481 0.0 0.155 1.47366 0.0441973 0.0 0.157 1.40582 0.0430461 0.0 0.159 1.40491 0.0439883 0.0 0.161 1.34639 0.044193 0.0 0.163 1.32238 0.0438008 0.0 0.165 1.33885 0.0445383 0.0 0.167 1.29608 0.0451575 0.0 0.169 1.30562 0.0460656 0.0 0.171 1.17147 0.0435717 0.0 0.173 1.18565 0.0449072 0.0 0.175 1.18944 0.0465319 0.0 0.177 1.17055 0.0456562 0.0 0.179 1.08571 0.0453852 0.0 0.181 1.06208 0.0463335 0.0 0.183 1.06187 0.0458284 0.0 0.185 1.02727 0.0472613 0.0 0.187 0.995169 0.0465526 0.0 0.189 1.02569 0.0483728 0.0 0.191 0.981154 0.0490559 0.0 0.193 1.01831 0.0502348 0.0 0.195 0.968102 0.0504426 0.0 0.197 0.940656 0.0512734 0.0 0.199 1.05762 0.0547469 0.0 0.201 0.949872 0.055229 0.0 0.203 0.891716 0.0531346 0.0 0.205 0.876084 0.0548681 0.0 0.207 0.932101 0.0576812 0.0 0.209 0.927755 0.0593404 0.0 0.211 0.87669 0.0600369 0.0 0.213 0.809125 0.0588107 0.0 0.215 0.941202 0.0659121 0.0 0.217 0.946175 0.0690784 0.0 0.219 0.859875 0.0674435 0.0 0.221 0.959508 0.0718856 0.0 0.223 0.763222 0.0702866 0.0 0.225 0.785467 0.0742144 0.0 0.227 0.81876 0.074266 0.0 0.229 0.678311 0.0722578 0.0 0.231 0.761442 0.0814516 0.0 0.233 0.757076 0.0825262 0.0 0.235 0.600636 0.075041 0.0 0.237 0.685635 0.0842392 0.0 0.239 0.799186 0.0974365 0.0 0.241 0.737526 0.0957286 0.0 0.243 0.716415 0.0970448 0.0 0.245 0.720413 0.0981996 0.0 0.247 0.604059 0.100869 0.0 0.249 0.649073 0.109281 0.0 0.251 0.700691 0.114325 0.0 0.253 0.586789 0.108324 0.0 0.255 0.765838 0.139579 0.0 0.257 0.828968 0.156723 0.0 0.259 0.616499 0.137866 0.0 0.261 0.526011 0.126209 0.0 0.263 0.51277 0.126339 0.0 0.265 0.604189 0.166393 0.0 0.267 0.738765 0.194006 0.0 0.269 0.462803 0.155354 0.0 0.271 0.478694 0.171676 0.0 0.273 0.711983 0.255539 0.0 0.275 0.473304 0.230752 0.0 0.277 0.536817 0.262627 0.0 0.279 0.660654 0.297519 0.0 0.281 0.408902 0.24585 0.0 0.283 0.0 1.0 0.0 2.2385 0.81703 0.0130497 2.31685 0.801978 0.0120051 2.39794 0.782436 0.0112577 2.48186 0.795586 0.01104 2.56873 0.794175 0.0107071 2.65864 0.807059 0.010757 2.75169 0.797216 0.0106204 2.848 0.811763 0.0107288 2.94768 0.805778 0.0105482 3.05085 0.787672 0.0103436 3.15763 0.804061 0.0105877 3.26814 0.799089 0.0105895 3.38253 0.810401 0.0109026 3.50092 0.797859 0.0108399 3.62345 0.801003 0.0110517 3.75027 0.78509 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I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| 0.002618 0.02198 0.002704 0.0004091 0.008082 1e-10 0.007854 0.02201 0.001643 0.005587 0.0275 1.564e-12 0.01309 0.02695 0.002452 0.005598 0.02762 2.525e-07 0.01832 0.02645 0.001769 0.005624 0.02787 0.001046 0.02356 0.03024 0.001531 0.005707 0.02847 0.1293 0.02879 0.3927 0.1697 0.005975 0.03031 0.7933 0.03402 7.305 1.006 0.006264 0.03457 0.9972 0.03925 17.43 0.5351 0.006344 0.0397 1 0.04448 13.43 0.3677 0.006424 0.04488 1 0.0497 8.346 0.191 0.006516 0.05006 1 sasdata-0.8.1/test/sasdataloader/data/ascii_test_2.txt000066400000000000000000000033271427502211700227560ustar00rootroot00000000000000FILE: jan08002.SA2_BH _R556 CREATED: Mon, Jan 21, 2008 1:34:58 PM LABEL: scatt 1m sam1 MON CNT LAMBDA DET ANG DET DIST TRANS THICK AVE STEP 1e+08 6 25 1 0.5667 0.2C 1 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 114.58 64.22 50 12.7 3.914 0.124 50.8 ORNL SAM: jan08002.SA2_BH _R556 BGD: JAN08008.SA2_BH_R562, EMP: JAN08007.SA2_BH_R561, DIV: PLEX_04JAN2008_NG7.DIV, MASK: DEFAULT.MASK, ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=2.547e+05;XSECT=1 Average Choices: AVTYPE=Circular;SAVE=Yes;NAME=Auto;PLOT=Yes; The 6 columns are | Q (1/A) | I(Q) (1/cm) | std. dev. I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| 0.002618 0.02198 0.002704 0.0004091 0.008082 1e-10 0.007854 0.02201 0.001643 0.005587 0.0275 1.564e-12 0.01309 0.02695 0.002452 0.005598 0.02762 2.525e-07 0.01832 0.02645 0.001769 0.005624 0.02787 0.001046 0.02356 0.03024 0.001531 0.005707 0.02847 0.1293 some string: the data should now contain 5 points 0.02879 0.3927 0.1697 0.005975 0.03031 0.7933 0.03402 7.305 1.006 0.006264 0.03457 0.9972 0.03925 17.43 0.5351 0.006344 0.0397 1 0.04448 13.43 0.3677 0.006424 0.04488 1 0.0497 8.346 0.191 0.006516 0.05006 1 sasdata-0.8.1/test/sasdataloader/data/ascii_test_3.txt000066400000000000000000000031561427502211700227570ustar00rootroot00000000000000FILE: jan08002.SA2_BH _R556 CREATED: Mon, Jan 21, 2008 1:34:58 PM LABEL: scatt 1m sam1 MON CNT LAMBDA DET ANG DET DIST TRANS THICK AVE STEP 1e+08 6 25 1 0.5667 0.2C 1 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 114.58 64.22 50 12.7 3.914 0.124 50.8 ORNL SAM: jan08002.SA2_BH _R556 BGD: JAN08008.SA2_BH_R562, EMP: JAN08007.SA2_BH_R561, DIV: PLEX_04JAN2008_NG7.DIV, MASK: DEFAULT.MASK, ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=2.547e+05;XSECT=1 Average Choices: AVTYPE=Circular;SAVE=Yes;NAME=Auto;PLOT=Yes; The 6 columns are | Q (1/A) | I(Q) (1/cm) | std. dev. I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| 0.002618 0.02198 0.002704 0.0004091 0.008082 1e-10 0.007854 0.02201 0.001643 0.005587 0.0275 1.564e-12 0.01309 0.02695 0.002452 0.005598 0.02762 2.525e-07 0.01832 0.02645 0.001769 0.005624 0.02787 0.001046 0.02356 0.03024 0.001531 0.005707 0.02847 0.1293 0.02879 0.3927 0.03402 7.305 1.006 0.006264 0.03457 0.9972 0.03925 17.43 0.5351 0.006344 0.0397 1 0.04448 13.43 0.3677 0.006424 0.04488 1 0.0497 8.346 0.191 0.006516 0.05006 1 sasdata-0.8.1/test/sasdataloader/data/ascii_test_4.abs000066400000000000000000000037461427502211700227130ustar00rootroot00000000000000 51 3.643 0.0286 0.002291 0.01199 1 0.02051 2.695 0.022251 2.528 0.01782 0.002404 0.02236 1 FILE CREATED: Mon, Aug 18, 2003 NSORT-ed ssy2k004.ABS + ssy2k009.ABS + none normalized to ssy2k004.ABS multiplicative factor 1-2 = 0.88493703 multiplicative factor 2-3 = 1 102 3.742 0.22 3.643 0.0286 0.002291 0.01199 1 0.012652 3.505 0.02989 0.002296 0.01285 1 102 3.742 52 3.643 0.0286 0.002291 0.01199 1 0.02052 2.695 0.01887 0.002379 0.02062 1 0.022252 2.528 0.01782 0.002404 0.02236 1 FILE CREATED: Mon, Aug 18, 2003 NSORT-ed ssy2k004.ABS + ssy2k009.ABS + none normalized to ssy2k004.ABS multiplicative factor 1-2 = 0.88493703 multiplicative factor 2-3 = 1 0.23 3.643 0.0286 0.002291 0.01199 1 0.012653 3.505 0.02989 0.002296 0.01285 1 103 3.742 0.02989 0.02654 3.505 0.02989 0.002296 0.01285 1 0.015274 3.27 0.02658 0.002318 0.01543 1 0.012654 3.505 0.02989 0.002296 0.01285 1 0.013534 3.428 0.02694 0.002303 0.01371 1 0.022254 2.528 0.01782 0.002404 0.02236 1 normalized to ssy2k004.ABS 0.015285 3.27 0.02658 0.002318 0.01543 1 sasdata-0.8.1/test/sasdataloader/data/ascii_test_5.txt000066400000000000000000000021751427502211700227610ustar00rootroot00000000000000FILE: jan08002.SA2_BH _R556 CREATED: Mon, Jan 21, 2008 1:34:58 PM LABEL: scatt 1m sam1 MON CNT LAMBDA DET ANG DET DIST TRANS THICK AVE STEP 1e+08 6 25 1 0.5667 0.2C 1 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 114.58 64.22 50 12.7 3.914 0.124 50.8 ORNL SAM: jan08002.SA2_BH _R556 BGD: JAN08008.SA2_BH_R562, EMP: JAN08007.SA2_BH_R561, DIV: PLEX_04JAN2008_NG7.DIV, MASK: DEFAULT.MASK, ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=2.547e+05;XSECT=1 Average Choices: AVTYPE=Circular;SAVE=Yes;NAME=Auto;PLOT=Yes; The 6 columns are | Q (1/A) | I(Q) (1/cm) | std. dev. I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| 0.002618 0.02198 0.002704 0.0004091 0.008082 1e-10 0.007854 0.02201 0.001643 0.005587 0.0275 1.564e-12 0.02879 0.3927 0.03402 7.305 0.03925 17.43 0.04448 13.43 0.0497 8.346 sasdata-0.8.1/test/sasdataloader/data/ascii_test_6.txt000066400000000000000000000040621427502211700227570ustar00rootroot00000000000000 51 3.643 0.0286 0.002291 0.01199 1 0.02051 2.695 0.022251 2.528 0.01782 0.002404 0.02236 1 FILE CREATED: Mon, Aug 18, 2003 NSORT-ed ssy2k004.ABS + ssy2k009.ABS + none normalized to ssy2k004.ABS multiplicative factor 1-2 = 0.88493703 multiplicative factor 2-3 = 1 102 3.742 0.22 3.643 0.0286 0.002291 0.01199 1 0.012652 3.505 0.02989 0.002296 0.01285 1 102 3.742 52 3.643 0.0286 0.002291 0.01199 1 0.02052 2.695 0.01887 0.002379 0.02062 1 0.022252 2.528 0.01782 0.002404 0.02236 1 FILE CREATED: Mon, Aug 18, 2003 NSORT-ed ssy2k004.ABS + ssy2k009.ABS + none normalized to ssy2k004.ABS multiplicative factor 1-2 = 0.88493703 multiplicative factor 2-3 = 1 0.23 3.643 0.0286 0.002291 0.01199 1 0.012653 3.505 0.02989 0.002296 0.01285 1 103 3.742 0.02989 0.02654 3.505 0.02989 0.002296 0.01285 1 0.015274 3.27 0.02658 0.002318 0.01543 1 0.012654 3.505 0.02989 0.002296 0.01285 a 0.013534 3.428 0.02694 0.002303 0.01371 1 0.022254 2.528 0.01782 0.002404 0.02236 1 0.014654 3.505 0.02989 0.002296 0.01285 1 0.015285 3.27 0.02658 0.002318 0.01543 1 sasdata-0.8.1/test/sasdataloader/data/avg_testdata.txt000066400000000000000000000015501427502211700230500ustar00rootroot000000000000000.00019987186878 -0.01196215 0.148605728355 0.000453772721237 0.02091606 0.23372601 0.000750492390439 -0.01337855 0.17169562 0.00103996394336 0.03062 0.13136407 0.0013420198959 0.0811008333333 0.10681163 0.001652061869 0.167022288372 0.10098903 0.00196086470492 27.5554711176 0.7350533 0.00226262401224 105.031578947 1.35744586624 0.00256734439716 82.1791776119 1.10749938588 0.0028637128388 54.714657971 0.890486416264 0.00315257408712 36.8455584416 0.691746880003 0.00344644126616 24.8938701149 0.534917225468 0.00374248202229 16.5905619565 0.424655384023 0.00404393067437 11.4714217925 0.328969543128 0.004346317814 8.05405805556 0.273083524998 0.00465162170627 5.5823291129 0.21217630209 0.00495449803049 4.2574845082 0.186808495528 0.00525641407066 3.30448963768 0.154743584955 0.00555735057365 2.6995389781 0.140373302568 0.00585577429002 2.03298512 0.116418358232 sasdata-0.8.1/test/sasdataloader/data/cansas1d.xml000066400000000000000000000104321427502211700220570ustar00rootroot00000000000000 Test title 1234 0.02 1000 3 0.01 0.03 1001 4 0.02 SI600-new-long 1.03 0.327 0.0000 10.00 0.00 22.5 0.020
http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
Some text here
canSAS instrument neutron 12.00 13.00 disc 6.00 0.22 1.00 14.3 123.0 50 11.000 1 fictional hybrid 4.150 1 2 1.00 0.00 0.00 322.64 327.68 5.00 5.00 spol 04-Sep-2007 18:35:02 10.000 180.0 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 No Information sasdata-0.8.1/test/sasdataloader/data/cansas1d_badunits.xml000066400000000000000000000104701427502211700237520ustar00rootroot00000000000000 Test title 1234 0.002 1 .003 0.001 0.003 1.001 .004 0.002 SI600-new-long 0.00103 0.327 0.0000 10000000.00 0.00 0.39269908 3.4906585e-4
http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
Some text here
canSAS instrument neutron .01200 13000.00 disc 0.600 02.2 10.0 14.3 0.123 50000 1100.000 .1 fictional hybrid 4.150 1000000 2000 .0174533 0.00 0.00 .32264 .32768 .500 .500 spol 04-Sep-2007 18:35:02 10.000 4.1416 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 sasdata-0.8.1/test/sasdataloader/data/cansas1d_notitle.xml000066400000000000000000000103761427502211700236240ustar00rootroot00000000000000 1234 0.02 1000 3 0.01 0.03 1001 4 0.02 SI600-new-long 1.03 0.327 0.0000 10.00 0.00 22.5 0.020
http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
Some text here
canSAS instrument neutron 12.00 13.00 disc 6.00 0.22 1.00 14.3 123.0 50 11.000 1 fictional hybrid 4.150 1 2 1.00 0.00 0.00 322.64 327.68 5.00 5.00 spol 04-Sep-2007 18:35:02 10.000 180.0 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 No Information sasdata-0.8.1/test/sasdataloader/data/cansas1d_slit.xml000066400000000000000000000103401427502211700231100ustar00rootroot00000000000000 Test title 1234 0.02 1000 3 0.001 0.005 0.03 1001 4 0.001 0.005 SI600-new-long 1.03 0.327 0.0000 10.00 0.00 22.5 0.020
http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
Some text here
canSAS instrument neutron 12.00 13.00 disc 6.00 0.22 1.00 14.3 123.0 50 11.000 1 fictional hybrid 4.150 1 2 1.00 0.00 0.00 322.64 327.68 5.00 5.00 spol 04-Sep-2007 18:35:02 10.000 180.0 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 sasdata-0.8.1/test/sasdataloader/data/cansas1d_units.xml000066400000000000000000000104771427502211700233120ustar00rootroot00000000000000 Test title 1234 0.2 0.0001 .0000003 0.1 0.3 0.0001001 .0000004 0.2 SI600-new-long 0.00103 0.327 0.0000 10000000.00 0.00 0.39269908 3.4906585e-4
http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
Some text here
canSAS instrument neutron .01200 13000.00 disc 0.600 02.2 10.0 14.3 0.123 50000 1100.000 .1 fictional hybrid 4.150 1000000 2000 .0174533 0.00 0.00 .32264 .32768 .500 .500 spol 04-Sep-2007 18:35:02 10.000 4.1416 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 sasdata-0.8.1/test/sasdataloader/data/cansas1d_v1_0.xsd000066400000000000000000000230601427502211700227030ustar00rootroot00000000000000 sasdata-0.8.1/test/sasdataloader/data/cansas1d_v1_1.xsd000066400000000000000000000261321427502211700227070ustar00rootroot00000000000000 sasdata-0.8.1/test/sasdataloader/data/cansas_test.xml000066400000000000000000000174771427502211700227110ustar00rootroot00000000000000 ILL-D11 example1: 2A 5mM 0%D2O g013586.001 0.000E+00 0.0000E+00 0.000E+00 0.00E+00 1.047E-03 0.0000E+00 0.000E+00 9.14E-04 2.094E-03 0.0000E+00 0.000E+00 9.32E-04 3.142E-03 0.0000E+00 0.000E+00 9.61E-04 4.189E-03 0.0000E+00 0.000E+00 1.00E-03 5.364E-03 5.4484E+00 1.647E-01 1.05E-03 6.255E-03 4.9963E+00 9.122E-02 1.10E-03 7.299E-03 4.6705E+00 7.450E-02 1.17E-03 8.340E-03 4.2690E+00 5.745E-02 1.23E-03 9.395E-03 4.0078E+00 5.484E-02 1.31E-03 1.045E-02 3.8409E+00 4.939E-02 1.38E-03 1.151E-02 3.6579E+00 4.750E-02 1.47E-03 1.258E-02 3.4413E+00 4.344E-02 1.55E-03 1.362E-02 3.2571E+00 4.197E-02 1.64E-03 1.465E-02 3.0475E+00 4.016E-02 1.72E-03 1.570E-02 2.9447E+00 3.703E-02 1.81E-03 1.674E-02 2.8542E+00 3.706E-02 1.90E-03 1.779E-02 2.6221E+00 3.293E-02 2.00E-03 1.886E-02 2.5466E+00 3.318E-02 2.09E-03 1.989E-02 2.4346E+00 3.203E-02 2.19E-03 2.093E-02 2.2702E+00 3.034E-02 2.28E-03 2.198E-02 2.2182E+00 3.011E-02 2.38E-03 2.303E-02 2.0914E+00 2.798E-02 2.48E-03 2.408E-02 2.0097E+00 2.795E-02 2.57E-03 2.511E-02 1.9056E+00 2.684E-02 2.67E-03 2.617E-02 1.8275E+00 2.559E-02 2.77E-03 2.724E-02 1.7406E+00 2.508E-02 2.87E-03 2.828E-02 1.6591E+00 2.441E-02 2.97E-03 2.932E-02 1.5903E+00 2.451E-02 3.07E-03 3.035E-02 1.4810E+00 2.289E-02 3.17E-03 3.140E-02 1.4093E+00 2.279E-02 3.27E-03 3.242E-02 1.3394E+00 2.281E-02 3.37E-03 3.349E-02 1.2679E+00 2.555E-02 3.47E-03 3.454E-02 1.2336E+00 2.911E-02 3.57E-03 3.560E-02 1.1766E+00 2.880E-02 3.67E-03 3.666E-02 1.0849E+00 3.269E-02 3.78E-03 3.750E-02 1.0130E+00 5.246E-02 3.86E-03 0.0000 0.0000 32.0000 10.00 0.00 0.020 neutron 30.00 0.00 6.00 0.00 10.000 10.000 0.00 311.00 315.00 10.00 10.00 spol 04-Sep-2007 18:12:27 10.000 180.0 0.0 1.00 900.000 estimated AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.1111E+01 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13586 0 5.63E+01 2A 5mM 0%D2O Sbak 13567 0 1.88E+01 H2O buffer Sbak 13533 0 7.49E+00 H2O buffer V... 13552 1 1.00E+00 Normal 10m from sasdata-0.8.1/test/sasdataloader/data/cansas_test_modified.xml000066400000000000000000000175671427502211700245510ustar00rootroot00000000000000 ILL-D11 example1: 2A 5mM 0%D2O g013586.001 0.000E+00 0.0000E+00 0.000E+00 0.00E+00 1.047E-03 0.0000E+00 0.000E+00 9.14E-04 2.094E-03 0.0000E+00 0.000E+00 9.32E-04 3.142E-03 0.0000E+00 0.000E+00 9.61E-04 4.189E-03 0.0000E+00 0.000E+00 1.00E-03 5.364E-03 5.4484E+00 1.647E-01 1.05E-03 6.255E-03 4.9963E+00 9.122E-02 1.10E-03 7.299E-03 4.6705E+00 7.450E-02 1.17E-03 8.340E-03 4.2690E+00 5.745E-02 1.23E-03 9.395E-03 4.0078E+00 5.484E-02 1.31E-03 1.045E-02 3.8409E+00 4.939E-02 1.38E-03 1.151E-02 3.6579E+00 4.750E-02 1.47E-03 1.258E-02 3.4413E+00 4.344E-02 1.55E-03 1.362E-02 3.2571E+00 4.197E-02 1.64E-03 1.465E-02 3.0475E+00 4.016E-02 1.72E-03 1.570E-02 2.9447E+00 3.703E-02 1.81E-03 1.674E-02 2.8542E+00 3.706E-02 1.90E-03 1.779E-02 2.6221E+00 3.293E-02 2.00E-03 1.886E-02 2.5466E+00 3.318E-02 2.09E-03 1.989E-02 2.4346E+00 3.203E-02 2.19E-03 2.093E-02 2.2702E+00 3.034E-02 2.28E-03 2.198E-02 2.2182E+00 3.011E-02 2.38E-03 2.303E-02 2.0914E+00 2.798E-02 2.48E-03 2.408E-02 2.0097E+00 2.795E-02 2.57E-03 2.511E-02 1.9056E+00 2.684E-02 2.67E-03 2.617E-02 1.8275E+00 2.559E-02 2.77E-03 2.724E-02 1.7406E+00 2.508E-02 2.87E-03 2.828E-02 1.6591E+00 2.441E-02 2.97E-03 2.932E-02 1.5903E+00 2.451E-02 3.07E-03 3.035E-02 1.4810E+00 2.289E-02 3.17E-03 3.140E-02 1.4093E+00 2.279E-02 3.27E-03 3.242E-02 1.3394E+00 2.281E-02 3.37E-03 3.349E-02 1.2679E+00 2.555E-02 3.47E-03 3.454E-02 1.2336E+00 2.911E-02 3.57E-03 3.560E-02 1.1766E+00 2.880E-02 3.67E-03 3.666E-02 1.0849E+00 3.269E-02 3.78E-03 3.750E-02 1.0130E+00 5.246E-02 3.86E-03 This is a test file 0.0000 0.0000 32.0000 10.00 0.00 0.020 D11 neutron 30.00 0.00 6.00 0.00 10.000 10.000 0.00 311.00 315.00 10.00 10.00 spol 04-Sep-2007 18:12:27 10.000 180.0 0.0 1.00 900.000 estimated AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.1111E+01 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13586 0 5.63E+01 2A 5mM 0%D2O Sbak 13567 0 1.88E+01 H2O buffer Sbak 13533 0 7.49E+00 H2O buffer V... 13552 1 1.00E+00 Normal 10m from sasdata-0.8.1/test/sasdataloader/data/cansas_xml_multisasentry_multisasdata.xml000066400000000000000000005073021427502211700302770ustar00rootroot00000000000000 AF1410-10 (AF1410 steel aged 10 h) nuclear sector nuclear+magnetic sector 0.016514078.27000432.4307406 0.017675064.06999971.9305180 0.018965056.17999651.2294165 0.019997048.11000061.1820664 0.021158041.15999980.9578518 0.022319035.75099950.7112609 0.023480030.23899840.7277671 0.024512027.87100220.6218240 0.025286024.91833310.6622537 0.025673023.29199980.5520145 0.026963020.77499960.5030875 0.027350020.52893830.5078703 0.027994019.09799960.3687994 0.029155016.08699990.3649726 0.029413016.79599950.4409898 0.030316015.10400100.3844399 0.031477013.87099930.3633896 0.032509012.18499950.2893804 0.033541011.58200070.2966648 0.033670011.46300030.3081964 0.034960010.12699990.2282192 0.03547609.81900020.2192077 0.03599109.19499970.2132159 0.03715208.03700070.2454359 0.03753908.47700020.1690000 0.03831307.82099960.2200659 0.03947407.25000000.1426543 0.04050506.26200010.1774028 0.04153706.23799990.1136525 0.04166605.98199990.1800941 0.04295605.87900020.1565320 0.04360105.39300010.1085258 0.04398705.32700010.1653923 0.04514804.82200000.1575006 0.04566404.68599990.0933287 0.04630904.79920010.1247623 0.04746904.36560010.1420351 0.04759804.08310030.1050871 0.04863003.98420000.1162791 0.04966103.58890010.0657220 0.04979003.75500010.1172323 0.05095103.40440010.1143638 0.05172403.22359990.0686435 0.05211103.06970020.0926941 0.05314203.06760000.0934679 0.05378702.70459990.0589216 0.05430302.80580000.1040542 0.05546302.69250010.0913250 0.05572102.50099990.0506254 0.05662302.46639990.0791012 0.05778402.21070000.0446013 0.05894402.16809990.1003391 0.05984602.00740000.0395406 0.06010402.19836470.1212340 0.06113502.23218850.1049687 0.06178001.79360000.0340918 0.06397101.57690000.0459139 0.06590501.36200000.0459854 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0.031477017.65600010.5162364 0.032509015.14599990.3135427 0.033541014.18200020.3446157 0.033670013.67700000.2531600 0.034960012.33300020.2215762 0.035476012.35900020.3072475 0.035991010.81400010.2330944 0.037152010.05700020.2153346 0.03753909.96000000.2618397 0.03831309.07800010.2222656 0.03947408.60800080.2366474 0.04050508.02400020.1652460 0.04153707.28499980.1542076 0.04166607.07800010.1611762 0.04295606.76200010.1679382 0.04360106.15200040.1153409 0.04398706.03399990.1462498 0.04514805.54200030.1495627 0.04566405.24699970.1096301 0.04630905.20499990.1434965 0.04746904.73199990.1190987 0.04759804.51300000.1194715 0.04863004.35899970.0950011 0.04966104.02610020.0923944 0.04979004.03200010.1136460 0.05095103.76440020.1011916 0.05172403.35909990.0805459 0.05211103.31869980.0848649 0.05314203.21150020.0947661 0.05378703.07900000.0517612 0.05430303.04790020.0865224 0.05546302.84320000.0903596 0.05572102.76040010.0703247 0.05662302.52490000.0916048 0.05778402.33090000.0607424 0.05894402.27070000.0917593 0.05984602.10390020.0545619 0.06010402.48593040.1193775 0.06113502.31002450.0839567 0.06178001.93859990.0502227 0.06397101.64060000.0443847 0.06590501.51490010.0384887 0.06796701.28270010.0385498 0.06990001.13270000.0367927 0.07196201.11439990.0376586 0.07402300.96510000.0364651 0.07608500.86580000.0315748 0.07801700.74510000.0360074 0.08007900.68710010.0303753 0.08201100.66280000.0327661 0.08420100.57340000.0258118 0.08613300.53300000.0257878 0.08819300.46822000.0225178 0.09012500.43933000.0268794 0.09218500.40820000.0226738 0.09424600.33776000.0206170 0.09630600.33040000.0213207 0.09823700.29736000.0181640 0.10030000.30830000.0201579 0.10236000.25972000.0166406 AF1410-10 (AF1410 steel aged 10 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-8h (AF1410 steel aged 8 h) nuclear sector nuclear+magnetic sector 0.017675058.47000122.7457056 0.018836050.51000211.9080094 0.019997043.08000181.5323592 0.021158036.18799971.6601807 0.022319031.57399751.2245260 0.023351028.42000010.9803290 0.024641024.62899970.7258443 0.025673021.30200000.7521981 0.026963018.84700010.5383623 0.027350018.26954270.5812866 0.027994016.93299870.4954725 0.029155014.96700100.4477544 0.029413015.12100120.4563694 0.030316013.61499980.3702661 0.031348012.29199980.4629093 0.032638011.44600010.3401470 0.033541010.43300060.3575948 0.033670010.45700070.2677555 0.03496009.45399950.2157962 0.03547608.64599990.2490643 0.03599108.17300030.2634274 0.03715207.86100010.2766821 0.03753907.45499990.2174488 0.03831307.29699990.2352956 0.03947406.61999990.1982927 0.04063406.32100010.1787515 0.04153705.78300000.1416616 0.04166605.94500020.2008602 0.04295605.24900010.1696528 0.04360105.04249950.1220623 0.04398705.17500020.1978866 0.04514804.78740020.1656049 0.04566404.34599970.1001575 0.04630904.36159990.1292401 0.04746904.08500000.1366426 0.04772703.73049970.0965984 0.04863003.89489980.1310116 0.04966103.37010000.0857359 0.05095103.27330020.1334567 0.05172402.76500010.0703921 0.05198202.92940000.1273666 0.05314202.80710010.1201647 0.05365802.63910010.0680994 0.05430302.55629990.1003871 0.05546302.42800000.0997812 0.05585002.32570000.0548916 0.05662302.36320020.1097256 0.05765502.38710000.1134575 0.05778402.13210010.0531688 0.05894402.01189990.1498694 0.05984601.94040000.0405601 0.06178001.67140000.0430576 0.06384201.49650000.0379381 0.06590501.37360000.0420187 0.06783801.23270000.0402159 0.06990001.08150010.0443694 0.07196201.04070000.0348692 0.07402300.96750000.0298319 0.07595600.83270000.0336752 0.07814600.78919990.0288950 0.08007900.74460000.0313121 0.08214000.72010000.0256850 0.08407200.62260000.0220204 0.08626200.60700000.0237135 0.08819300.50190000.0227748 0.09025400.47660000.0215230 0.09218500.41890000.0191565 0.09424600.41470000.0228825 0.09630600.36740000.0254951 0.09823700.35320000.0193197 0.10030000.29660000.0203194 0.10236000.30530000.0254562 0.017675096.43000034.8397622 0.018836081.47000123.7748642 0.019997068.09999852.7459242 0.021158057.31000142.4480605 0.022319048.22000121.7571059 0.023351041.94599911.4598973 0.024641035.63600161.2073458 0.025673031.01899910.9388557 0.026963026.90299800.8385285 0.027350026.26764110.8313511 0.027994023.84099960.6627760 0.029155020.58699990.5938569 0.029413020.68744470.6787165 0.030316018.53899960.4786585 0.031348015.62299920.5656368 0.032638014.72900010.4146951 0.033541013.33600040.4056599 0.033670012.90100000.3142308 0.034960011.90000060.2916059 0.035476011.16399960.3055912 0.035991011.00000000.3165896 0.03715209.89400010.3208146 0.03753909.47400000.2340192 0.03831309.03400040.3041053 0.03947407.93700030.1968051 0.04063407.40499970.2772454 0.04153706.73099990.1666940 0.04166607.17300030.2250946 0.04295606.11400030.2016928 0.04360105.78000020.1370228 0.04398706.11800000.2210408 0.04514805.77200030.1655586 0.04566405.00499960.1513335 0.04630905.06000040.1297538 0.04746904.62699990.1729306 0.04772704.35930010.1096586 0.04863004.19380000.1206872 0.04966103.78700020.0898888 0.05095103.40769980.1261943 0.05172403.32999990.0892738 0.05198203.39859990.1286011 0.05314203.03329990.1283511 0.05365802.78210000.0813079 0.05430302.92060020.1076898 0.05546302.86110000.1324379 0.05585002.48630000.0659929 0.05662302.75790000.1153510 0.05765502.43720010.1106635 0.05778402.29419990.0611831 0.05894402.36400010.1482656 0.05984602.01760010.0520640 0.06178001.88729990.0545881 0.06384201.52800000.0553218 0.06590501.43750000.0511649 0.06783801.23510000.0429106 0.06990001.14270000.0481649 0.07196201.04040000.0424577 0.07402300.89890000.0444010 0.07595600.89110000.0328732 0.07814600.79520000.0299848 0.08007900.72260000.0347079 0.08214000.69200000.0286094 0.08407200.64860000.0281753 0.08626200.52620010.0326907 0.08819300.49610000.0234081 0.09025400.41980000.0266332 0.09218500.37170000.0263623 0.09424600.34890000.0238380 0.09630600.40630000.0227706 0.09823700.28350000.0247800 0.10030000.29850000.0226338 AF1410-8h (AF1410 steel aged 8 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-qu (AF1410 steel aged 0.25 h) nuclear sector nuclear+magnetic sector 0.017675029.78300091.4780126 0.018836025.49400141.1333710 0.019997020.80400090.8700632 0.021158017.44100000.7309898 0.022319014.81999970.5881539 0.023351012.92499920.4339412 0.024641010.93000030.3691951 0.02567309.32099910.2808149 0.02696308.15699960.2389079 0.02735007.91969440.2582158 0.02799407.07499980.1938924 0.02915506.21600010.1657985 0.02941306.13333370.1677404 0.03031605.24300000.1262065 0.03134804.50689980.1640956 0.03263804.26909970.1001781 0.03354103.75860020.1150530 0.03367003.61630010.0829778 0.03496003.23940010.0831829 0.03547603.00290010.0907086 0.03599102.94249990.0727795 0.03715202.58789990.0685639 0.03753902.45429990.0742388 0.03831302.44400000.0534223 0.03947402.03359990.0625729 0.04063402.02300000.0500633 0.04153701.68660000.0460831 0.04166601.82549990.0488857 0.04295601.61180010.0512622 0.04360101.45750000.0343169 0.04398701.46330000.0368622 0.04514801.38610010.0435588 0.04566401.22730000.0304016 0.04630901.27630000.0368902 0.04746901.12449990.0318955 0.04772701.06909990.0293455 0.04863001.01650000.0324854 0.04966100.89760000.0220220 0.05095100.84610000.0381581 0.05172400.75020000.0191050 0.05198200.73160000.0227721 0.05314200.73301000.0253126 0.05365800.65240000.0161236 0.05430300.70855000.0249804 0.05546300.64440000.0238537 0.05585000.58180000.0168929 0.05662300.59323000.0238304 0.05765500.56232000.0281233 0.05778400.49530000.0146400 0.05894400.49334000.0235536 0.05984600.43730000.0140720 0.06178000.40160000.0130698 0.06384200.34010000.0136883 0.06590500.31780000.0136004 0.06783800.26740000.0121078 0.06990000.24650000.0151717 0.07196200.21860000.0112894 0.07402300.19860000.0091417 0.07595600.17430000.0107703 0.07814600.18910000.0093493 0.08007900.16470000.0106550 0.08214000.15090000.0096021 0.08407200.13740000.0093059 0.08626200.12290000.0088091 0.08819300.10500000.0083600 0.09025400.08970000.0081216 0.09218500.07630000.0084723 0.09424600.07880000.0076217 0.09630600.08790000.0088408 0.09823700.06470000.0086284 0.10030000.05680000.0077421 0.10236000.05780000.0085703 0.10441000.04930000.0108600 0.017675042.77000052.1243823 0.018836035.84199911.5351039 0.019997029.49599841.1404490 0.021158024.65900041.0218753 0.022319020.72699930.7863085 0.023351017.95299910.5703201 0.024641015.05200100.4540099 0.025673012.70000080.3794588 0.026963010.91100030.3064931 0.027350010.88814260.3686532 0.02799409.56300070.2360892 0.02915508.19299980.2242699 0.02941308.48299980.2842308 0.03031607.21100000.1661013 0.03134806.34900000.2349574 0.03263805.71510030.1360177 0.03354105.18919990.1630829 0.03367005.06750010.0996055 0.03496004.46059990.1091557 0.03547604.22930000.1169480 0.03599104.01039980.0783165 0.03715203.62839980.0835229 0.03753903.43980000.1090117 0.03831303.22480010.0659619 0.03947402.83200000.0751150 0.04063402.65290000.0500442 0.04153702.43580010.0596169 0.04166602.43320010.0568300 0.04295602.19650010.0494030 0.04360102.00009990.0507587 0.04398701.96920000.0495464 0.04514801.89160000.0438719 0.04566401.71369990.0377737 0.04630901.72290000.0398418 0.04746901.57219990.0341283 0.04772701.45480000.0337338 0.04863001.36800000.0299641 0.04966101.29410000.0255760 0.05095101.15520000.0319916 0.05172401.07110000.0208830 0.05198201.10620000.0297755 0.05314200.96680000.0280608 0.05365800.92190000.0238076 0.05430300.99080000.0264887 0.05546300.86960000.0218586 0.05585000.82090000.0169446 0.05662300.83870000.0256632 0.05765500.79930000.0311079 0.05778400.75540000.0186462 0.05894400.77160000.0340353 0.05984600.67080000.0166090 0.05997500.68480000.0303659 0.06178000.60190000.0170176 0.06384200.49800000.0132740 0.06590500.46270000.0141739 0.06783800.41850000.0149482 0.06990000.36240000.0153834 0.07196200.35640000.0145121 0.07402300.32980000.0113371 0.07595600.28940000.0120830 0.07814600.26430000.0106254 0.08007900.24750000.0114495 0.08214000.23000000.0109772 0.08407200.21900000.0087818 0.08626200.19490000.0092005 0.08819300.17050000.0092418 0.09025400.16000000.0093941 0.09218500.12660000.0084906 0.09424600.13110000.0088408 0.09630600.13860000.0081394 0.09823700.10830000.0088549 0.10030000.09570000.0080777 0.10236000.10720000.0102728 0.10441000.09020000.0107005 AF1410-qu (AF1410 steel aged 0.25 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-cc (AF1410 steel aged 100 h) nuclear sector nuclear+magnetic sector 0.017675090.94000244.7105837 0.018836075.80999763.6028461 0.019997062.00999832.6953478 0.021158053.89999392.1120605 0.022319048.09999852.0700243 0.023351043.22000121.6272111 0.024641038.27000051.4363638 0.025673031.69000051.0598476 0.026963030.12500000.8118818 0.027350027.48499870.9308518 0.027994026.21299930.8720694 0.029155022.46500020.8133542 0.029413021.41499900.7485519 0.030316020.22399900.5384357 0.031348018.19100000.6644005 0.032638017.20100020.5447834 0.033541015.24699970.4711528 0.033670015.29300120.4678226 0.034960013.56500050.5402814 0.035476012.50899980.3664451 0.035991012.32000060.4959607 0.037152011.40100000.4638847 0.037539010.71500020.3300379 0.038313010.18699930.3573710 0.03947408.88299940.2346913 0.04063409.05599980.3612216 0.04153708.00400070.1978627 0.04166608.51900010.2862953 0.04295607.63000010.3192256 0.04360106.78800010.1824820 0.04398706.86299990.2996431 0.04514806.75099950.2813112 0.04566405.71400020.1669641 0.04630905.90200000.2290590 0.04746905.05599980.2294907 0.04772704.95099970.1447046 0.04863004.77100040.2160926 0.04966104.33099990.1363085 0.05095104.08799980.2101166 0.05172403.49000020.0907199 0.05198203.59200000.1824089 0.05314203.37599990.1605241 0.05365803.20559980.0916791 0.05430303.34050010.1622127 0.05546303.01000000.1645965 0.05585002.69159980.0912607 0.05662302.63730000.1610965 0.05765502.51880000.1840109 0.05778402.47860000.0746501 0.05984602.09060000.0572477 0.06178001.93020010.0564075 0.06384201.54880000.0459923 0.06590501.30209990.0511188 0.06783801.26270010.0428529 0.06990001.05410000.0467822 0.07196200.95450000.0431116 0.07402300.90250000.0373905 0.07595600.74260000.0272861 0.07814600.65060000.0303209 0.08007900.64010000.0323149 0.08214000.57860000.0306498 0.08407200.53680000.0251811 0.08626200.47890000.0213827 0.08819300.45000000.0271013 0.09025400.36000000.0295665 0.09218500.28940000.0227178 0.09424600.32900000.0237407 0.09630600.31180000.0221111 0.09823700.27130000.0208291 0.10030000.24000000.0200302 0.10236000.22270000.0246830 0.0176750103.11999515.3328509 0.018836085.16000374.2001071 0.019997071.48000342.9537263 0.021158059.48999792.9382477 0.022319048.83000182.1424518 0.023351043.95999911.8618070 0.024641036.81999971.4374036 0.025673033.06000141.1379077 0.026963028.50100141.0256808 0.027350027.75785450.9479914 0.027994024.88100050.8765643 0.029155022.02499960.7482045 0.029413022.01000020.8911263 0.030316020.26099970.6507549 0.031348017.55500030.5869353 0.032638015.72999950.6063827 0.033541014.72400090.5158731 0.033670014.42600060.4573718 0.034960012.84700010.5266773 0.035476012.22000030.3765581 0.035991011.93699930.4924896 0.037152010.30799960.4103072 0.037539010.49200060.3402425 0.03831309.78100010.4344951 0.03947408.59399990.2839894 0.04063408.13200000.3374641 0.04153707.28900050.1859465 0.04166607.69400020.2829735 0.04295606.74200060.3028036 0.04360106.36599970.1573511 0.04398706.80300050.3126180 0.04514805.85800030.2715916 0.04566405.36499980.1161004 0.04630905.48000000.2562674 0.04746904.76900010.1874166 0.04772704.78200010.1260974 0.04863004.67299990.2472934 0.04966103.95000030.0915738 0.05095104.08300020.2122127 0.05172403.37809990.0796058 0.05198203.45799970.1642617 0.05314203.18800020.1444507 0.05365802.99510000.0925324 0.05430302.89920000.1756156 0.05546302.71300010.1825931 0.05585002.63080000.0648917 0.05662302.91300010.1542467 0.05765502.16650010.1738333 0.05778402.22199990.0654472 0.05894402.29130010.1736001 0.05984602.02830000.0533704 0.06178001.78490010.0623491 0.06384201.55139990.0476681 0.06590501.37050000.0485309 0.06783801.21610000.0481724 0.06990001.08900000.0505059 0.07196200.96880010.0487115 0.07402300.91220000.0319226 0.07595600.76990000.0340309 0.07814600.73140000.0260547 0.08007900.61099990.0342171 0.08214000.56100000.0251607 0.08407200.55830000.0303209 0.08626200.46160000.0255180 0.08819300.43100000.0255039 0.09025400.37950000.0250266 0.09218500.31470000.0203571 0.09424600.33840000.0197626 0.09630600.32490000.0226049 0.09823700.25840000.0185000 0.10030000.23570000.0214227 AF1410-cc (AF1410 steel aged 100 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-2h (AF1410 steel aged 2 h) nuclear sector nuclear+magnetic sector 0.017675032.82300191.5526561 0.018836027.59700201.2889701 0.019997023.34300041.0331022 0.021158019.95499800.8002362 0.022319017.03599930.6785941 0.023351015.67500020.4951172 0.024641013.30299950.3634075 0.025673011.09900000.3664560 0.026963010.12199970.2955283 0.02735009.86714940.3164969 0.02799409.06900020.2973298 0.02915507.81600000.2459634 0.02941307.85088870.2030462 0.03031607.00900030.2068913 0.03134806.34100010.1783928 0.03263805.97230010.1631614 0.03354105.38039970.1833494 0.03367005.47840020.1401491 0.03496004.83880000.1271063 0.03547604.61529970.1031537 0.03599104.52350000.1300586 0.03715203.97129960.1491937 0.03753903.85329990.1161916 0.03831303.84700010.1077568 0.03947403.43730000.0999154 0.04063403.19899990.0928841 0.04153703.00479980.0802002 0.04166603.00210000.1288759 0.04295602.93599990.1073525 0.04360102.69980000.0647800 0.04398702.67360000.0879005 0.04514802.70200010.0853063 0.04566402.33060000.0517610 0.04630902.38560010.0730417 0.04746902.25299980.0744170 0.04772702.12940000.0490103 0.04863002.05620000.0755079 0.04966101.90220000.0430465 0.05095101.82960000.0629229 0.05172401.74690010.0435836 0.05198201.74160000.0614509 0.05314201.55029990.0595242 0.05365801.55720010.0444946 0.05430301.55740000.0610463 0.05546301.46990000.0607297 0.05585001.38460000.0399426 0.05662301.43410000.0643261 0.05765501.45440010.0744468 0.05778401.29830000.0386000 0.05894401.26930000.0746453 0.05984601.22289990.0279451 0.06178001.10959990.0366467 0.06384201.00340000.0290341 0.06590500.89380000.0285281 0.06783800.80900000.0295195 0.06990000.74410000.0252357 0.07196200.68600000.0233848 0.07402300.68080000.0209418 0.07595600.61000000.0215077 0.07814600.57450000.0191700 0.08007900.51950000.0225249 0.08214000.50170000.0244182 0.08407200.46460000.0193662 0.08626200.40720000.0204247 0.08819300.38890000.0205412 0.09025400.39320000.0147665 0.09218500.32540000.0172177 0.09424600.32200000.0165680 0.09630600.29650000.0170074 0.09823700.26770000.0174063 0.10030000.24180000.0153101 0.10236000.22650000.0187224 0.10441000.21880000.0194250 0.017675063.31999972.9753151 0.018836051.86999892.3523817 0.019997042.61299901.6304370 0.021158036.53900151.4832613 0.022319030.15299801.1898022 0.023351026.66900060.7946987 0.024641022.92399980.7163274 0.025673019.61199950.5363078 0.026963016.68000030.4900378 0.027350016.21673770.5555339 0.027994014.63100050.3146109 0.029155012.90600010.3113278 0.029413013.05644420.4019068 0.030316011.15299990.3010017 0.03134809.88200000.3311269 0.03263809.05200000.2355816 0.03354108.26200010.2393763 0.03367008.10099980.1762073 0.03496007.40700050.2083141 0.03547606.74599980.1841487 0.03599106.62449980.1394870 0.03715206.13579990.1817319 0.03753905.61219980.1558199 0.03831305.36219980.1373571 0.03947404.77979990.1482099 0.04063404.66940020.1179629 0.04153704.21119980.1004178 0.04166604.36469980.1190298 0.04295603.84970000.1012168 0.04360103.53820040.0808646 0.04398703.72009990.1217345 0.04514803.45080020.1226087 0.04566403.10990000.0641742 0.04630903.18029980.1121606 0.04746902.95149990.0823326 0.04772702.77639990.0549837 0.04863002.72970010.0800193 0.04966102.45420000.0553637 0.05095102.33719990.0748864 0.05172402.07410000.0489326 0.05198202.14920000.0650000 0.05314201.99550010.0872048 0.05365801.85660000.0531029 0.05430301.89570000.0590339 0.05546301.88429990.0683565 0.05585001.70020010.0361365 0.05662301.77300000.0641788 0.05765501.58760000.0661733 0.05778401.57430010.0352943 0.05894401.47700000.0869156 0.05984601.40670000.0325676 0.06178001.21509990.0253055 0.06384201.10760010.0282450 0.06590501.00739990.0313560 0.06783800.90760000.0288028 0.06990000.80990000.0259538 0.07196200.76540010.0299541 0.07402300.69150000.0310306 0.07595600.69560000.0282816 0.07814600.59990000.0227754 0.08007900.57760000.0267591 0.08214000.53160000.0232820 0.08407200.47770000.0203531 0.08626200.45580000.0208147 0.08819300.37560000.0197752 0.09025400.39180000.0179179 0.09218500.28920000.0188311 0.09424600.29490000.0184548 0.09630600.28020000.0186497 0.09823700.27380000.0164839 0.10030000.24190000.0162410 0.10236000.19810000.0205847 AF1410-2h (AF1410 steel aged 2 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-50 (AF1410 steel aged 50 h) nuclear sector nuclear+magnetic sector 0.017675087.12000274.7265210 0.018836074.50000003.4513767 0.019997062.61999892.7941546 0.021158053.33000182.2748187 0.022319047.19000242.2461541 0.023351041.62999731.5977796 0.024641036.43000031.0844358 0.025673032.20000081.1648331 0.026963026.58499911.1038378 0.027350027.87445450.9709597 0.027994025.32199860.8940677 0.029155021.48999980.7034096 0.029413022.72422220.6861237 0.030316019.80900000.7533870 0.031348017.77799990.6473832 0.032638016.19000050.5627548 0.033541015.14099880.4939716 0.033670014.44899940.4697074 0.034960013.31900020.4626500 0.035476012.74699970.3913694 0.035991011.89100070.4640140 0.037152011.58899970.4336473 0.037539010.81399920.3197890 0.038313010.20400050.3784230 0.03947409.26900010.2452468 0.04063408.13200000.3609723 0.04153708.25700000.2222724 0.04166608.31299970.3333767 0.04295607.27400020.2692229 0.04360106.94800000.1507397 0.04398706.75000000.2529605 0.04514806.46700000.2696702 0.04566405.62199970.1499890 0.04630905.84599970.2196475 0.04746905.03300000.1934248 0.04772704.92800000.1253992 0.04863004.86900040.2166149 0.04966104.28800010.1132407 0.05095103.96900010.1782480 0.05172403.63500000.0829347 0.05198203.79999970.1636498 0.05314203.72989990.1923914 0.05365803.14800000.0791890 0.05430303.52109980.1498413 0.05546302.98359990.1494375 0.05585002.79390000.0787844 0.05662302.94109990.1528547 0.05765502.83592220.1528884 0.05778402.47340010.0658523 0.05894402.44942550.1818775 0.05984602.18210010.0595739 0.05997502.41986300.2061133 0.06178001.94849990.0649680 0.06384201.69550010.0524582 0.06590501.51920000.0508506 0.06783801.34590010.0412724 0.06990001.10580000.0439246 0.07196201.04830000.0409205 0.07402300.94230000.0440224 0.07595600.82450000.0324423 0.07814600.73910000.0367642 0.08007900.67999990.0339520 0.08214000.63350000.0309040 0.08407200.59400000.0295611 0.08626200.50390000.0271450 0.08819300.46980000.0296998 0.09025400.44500000.0251114 0.09218500.35870000.0246465 0.09424600.34990000.0219244 0.0176750102.60999306.0144658 0.018836088.26000214.6253328 0.019997070.33000183.3039370 0.021158059.63000493.1333687 0.022319051.09000022.3492339 0.023351045.36000061.7264079 0.024641038.50000001.4261981 0.025673031.73999790.9564189 0.026963028.86000061.3485951 0.027350027.41899491.0564561 0.027994025.24600030.8606352 0.029155022.09400180.8694004 0.029413022.38700100.8355896 0.030316019.79100040.6106472 0.031348017.57500080.7085146 0.032638016.63200000.6141767 0.033541015.01999860.4314081 0.033670014.59500120.6167179 0.034960013.25199890.4727124 0.035476012.45199970.3718602 0.035991012.04400060.3608434 0.037152010.44199940.4078885 0.037539010.52099990.3372017 0.038313010.02500060.4113223 0.03947408.80900000.2397707 0.04063408.50500010.3068632 0.04153707.63399980.2281140 0.04166607.17599960.2802160 0.04295607.09200000.3156739 0.04360106.53499980.1630338 0.04398706.71100000.2853730 0.04514806.00700000.2814480 0.04566405.52700000.1388281 0.04630905.28600030.2192373 0.04746905.19700000.2392377 0.04772704.64599990.1302035 0.04863004.80300000.1847896 0.04966104.01599980.1177229 0.05095104.07800010.2238459 0.05172403.45799970.1023565 0.05198203.36299990.1975777 0.05314203.09800000.1434195 0.05365802.93359990.0829629 0.05430302.95030020.1525931 0.05546302.66870000.1553005 0.05585002.57760000.0830434 0.05662302.47950010.1749225 0.05765502.62120010.1609343 0.05778402.40360000.0796153 0.05894402.20619990.2128967 0.05984602.03979990.0519793 0.06178001.92820010.0519987 0.06384201.61410000.0609434 0.06590501.38490000.0596483 0.06783801.22030000.0504124 0.06990001.09949990.0475439 0.07196200.95180000.0360028 0.07402300.90610000.0500740 0.07595600.80310000.0336162 0.07814600.75720000.0258631 0.08007900.60110000.0332710 0.08214000.56910000.0279358 0.08407200.55350010.0272641 0.08626200.49620000.0234019 0.08819300.44480000.0246465 0.09025400.41770000.0251645 0.09218500.31230000.0198668 0.09424600.30150000.0211206 0.09630600.33070000.0212514 0.09823700.26520000.0199730 0.10030000.23640000.0166244 AF1410-50 (AF1410 steel aged 50 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-20 (AF1410 steel aged 20 h) nuclear+magnetic sector 0.0176750100.68999485.4614463 0.018836085.88999943.9071729 0.019997068.67999272.8963771 0.021158058.91000372.3992708 0.022319050.33000182.0769980 0.023351043.20000081.3859744 0.024641038.10800171.2982638 0.025673032.14800260.9779903 0.026963028.18000030.9062328 0.027350027.07199860.7554416 0.027994024.36199950.8331842 0.029155020.89500050.6827716 0.029413021.31000140.8013451 0.030316019.00500110.5678345 0.031348016.88800050.6885187 0.032638015.73500060.4825453 0.033541014.02700040.4172254 0.033670014.13000010.4114912 0.034960012.31500050.3426500 0.035476011.89300060.3264965 0.035991011.23299980.3430933 0.037152010.28100010.3691951 0.03753909.84600070.2954657 0.03831308.87400050.2862254 0.03947408.29699990.2468623 0.04063408.09700010.2674215 0.04153707.23999980.1793969 0.04166607.22599980.2240558 0.04295606.65499970.2003073 0.04360105.96199990.1464526 0.04398706.11100010.1781704 0.04514805.89400010.1779923 0.04566405.31199980.1301163 0.04630905.32100010.1771628 0.04746904.72400000.1490157 0.04772704.59700010.1277185 0.04863004.57100010.1237903 0.04966104.02780010.1062142 0.05095103.72159980.1212436 0.05172403.44639970.0864853 0.05198203.35110000.1355655 0.05314203.15229990.1376746 0.05365803.08489990.0874783 0.05430303.06890010.1264040 0.05546303.03169990.1193625 0.05585002.72079990.0640772 0.05662302.85460000.1206296 0.05765502.38560010.1219200 0.05778402.31909990.0683253 0.05894402.35780000.1263101 0.05984602.10450010.0507528 0.06178001.87990010.0514315 0.06384201.73449990.0491004 0.06590501.51140010.0528252 0.06783801.31950000.0447519 0.06990001.13960000.0469419 0.07196201.10170010.0460066 0.07402301.01700000.0437476 0.07595600.89640000.0381494 0.07814600.76380000.0319883 0.08007900.73640000.0354519 0.08214000.70760000.0320089 0.08407200.68680000.0257124 0.08626200.60290000.0267927 0.08819300.52280000.0292850 0.09025400.47490000.0294337 0.09218500.44150000.0226009 0.09424600.42810000.0227748 0.09630600.36270000.0227482 0.09823700.31540000.0214462 0.10030000.31360000.0199138 0.10236000.31530000.0256008 0.10441000.28380000.0264015 AF1410-20 (AF1410 steel aged 20 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-5h (AF1410 steel aged 5 h) nuclear sector nuclear+magnetic sector 0.016514045.52999881.4678218 0.017675037.54899981.2650155 0.018965030.06800080.9782479 0.019997025.73900030.7763054 0.021158022.91399960.5589821 0.022319019.21000100.4911721 0.023480016.98899840.4348241 0.024512014.33799930.3683219 0.025673012.62200070.3166607 0.026963011.21100040.2812561 0.027350011.04889300.3795274 0.027994010.12500000.2692229 0.02915509.09200000.2499540 0.02941309.00500010.2866670 0.03031607.98099990.2302173 0.03147707.40399980.2232935 0.03250906.64900020.2129470 0.03354106.25140000.1762328 0.03367006.00480030.1620702 0.03496005.55389980.1742124 0.03547605.32610030.1443360 0.03599104.95359990.1981565 0.03715204.33250000.1375491 0.03753904.61730000.1015670 0.03831304.22459980.1660868 0.03947404.07999990.1210945 0.04050503.61069990.1139611 0.04153703.42030000.0816623 0.04166603.45149990.1136785 0.04295603.12570000.1134473 0.04360103.05640010.0862863 0.04398703.01989980.0964370 0.04514802.96619990.1004555 0.04566402.62969990.0631953 0.04630902.50180010.1022923 0.04746902.49659990.0987974 0.04759802.44580010.0848109 0.04863002.31300000.0971803 0.04966102.16470000.0572787 0.04979002.16249990.0935906 0.05095102.08270000.0907331 0.05172401.90619990.0576045 0.05211101.90280010.0796959 0.05314201.89580000.0776460 0.05378701.76560010.0536263 0.05430301.74470000.0777476 0.05546301.55490010.0779493 0.05572101.63889990.0497374 0.05662301.57289990.0872779 0.05778401.49350000.0392272 0.05894401.35690000.0818878 0.05984601.29600000.0466010 0.06010401.62176190.1034511 0.06178001.25120000.0446865 0.06397101.11098000.0405860 0.06590500.99964000.0419148 0.06796700.89122000.0284543 0.06990000.83299010.0300137 0.07196200.83005000.0264413 0.07402300.71396000.0297195 0.07608500.72019000.0254189 0.07801700.55606000.0301171 0.08007900.56684000.0261620 0.08201100.56152000.0241944 0.08420100.46133000.0227238 0.08613300.46210000.0221576 0.08819300.41479000.0227566 0.09012500.36057000.0208600 0.09218500.33895000.0218862 0.09424600.29350000.0192083 0.09630600.30944000.0213701 0.09823700.27668000.0255265 0.10030000.23747000.0147872 0.10236000.25294800.0178037 0.10441000.18108400.0228819 0.016514086.55000312.6370628 0.017675071.15999602.1135752 0.018965059.04999921.5469742 0.019997048.77000051.1838434 0.021158042.77099610.9577479 0.022319036.67700200.7125230 0.023480031.34100150.6605967 0.024512026.76900100.5650318 0.025673023.19800000.4627310 0.026963019.62000080.3206197 0.027350019.46159930.5799904 0.027994018.04699900.3386148 0.029155016.22200010.3354519 0.029413015.89599900.4603042 0.030316014.26600070.2549216 0.031477012.30000020.3434560 0.032509011.36400030.2154182 0.033541010.36000060.2116034 0.033670010.00300030.1970496 0.03496009.38600060.2127587 0.03547608.70099930.2000976 0.03599108.03700070.1663310 0.03715207.45099970.2018378 0.03753907.07399940.2050390 0.03831306.56899980.1572867 0.03947406.19000010.1635101 0.04050505.71600010.1433107 0.04153705.35320000.1314962 0.04166605.42419960.1304856 0.04295604.97720000.1352651 0.04360104.57999990.0945661 0.04398704.62109990.1141187 0.04514804.21240000.1071077 0.04566403.85390000.0888960 0.04630903.99080010.0907640 0.04746903.70660020.0997802 0.04759803.34579990.0781561 0.04863003.44530010.0939601 0.04966102.94019990.0620378 0.04979002.96689990.0839212 0.05095102.97829990.0899887 0.05172402.76490000.0621167 0.05211102.60150000.0872507 0.05314202.52909990.0795742 0.05378702.41790010.0655072 0.05430302.43669990.0805566 0.05546302.38039990.0705318 0.05572102.08970000.0526908 0.05662302.16470000.0714499 0.05778401.91189990.0461972 0.05894401.91779990.0879318 0.05984601.65910010.0439038 0.06010401.97078100.1004017 0.06113501.96849790.1019639 0.06178001.48070000.0409723 0.06397101.33999990.0377689 0.06590501.26070000.0417713 0.06796701.13150000.0370827 0.06990000.96130000.0358745 0.07196200.92239990.0348006 0.07402300.83760000.0315696 0.07608500.81856000.0341892 0.07801700.70947000.0313121 0.08007900.63616000.0289318 0.08201100.60625000.0266327 0.08420100.50717000.0224321 0.08613300.45467000.0228020 0.08819300.44000000.0241506 0.09012500.39227000.0269058 0.09218500.36984000.0204832 0.09424600.32484000.0193869 0.09630600.29711000.0233944 0.09823700.27576000.0167178 0.10030000.21685000.0210110 0.10236000.27857000.0200003 AF1410-5h (AF1410 steel aged 5 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-1h (AF1410 steel aged 1 h) nuclear sector nuclear+magnetic sector 0.016514033.66600041.1689179 0.017675028.52400020.9044429 0.018965023.72900010.8353059 0.019997019.20499990.5944981 0.021158016.92100140.4332678 0.022319014.20499990.4047419 0.023480012.31400010.3529816 0.024512010.50300030.2888546 0.02567309.38200000.2568268 0.02696308.03499980.2122004 0.02735007.95232200.2544490 0.02799407.30800060.2627492 0.02915506.25600000.1896233 0.02941306.48199990.2307459 0.03031605.43370010.1738815 0.03147705.16420030.1633354 0.03250904.40579990.1713599 0.03354104.26149990.1038511 0.03367004.15330030.1222766 0.03496003.55990000.1353140 0.03547603.52290010.0784559 0.03599103.39190010.1095244 0.03715203.10229990.1387175 0.03753903.14730000.1092923 0.03831302.92709990.1344456 0.03947402.61870000.0747011 0.04050502.29499980.1078588 0.04153702.22350000.0774576 0.04166602.46100000.0957249 0.04295602.07570000.0964337 0.04360101.93620000.0553205 0.04398701.81550000.0886328 0.04514801.93360010.0873430 0.04566401.63580000.0511752 0.04630901.86139990.0802581 0.04746901.53260000.0820032 0.04759801.56010000.0500640 0.04863001.46989990.0757856 0.04966101.30750000.0438292 0.04979001.24050000.0630575 0.05095101.23520000.0852693 0.05172401.15810000.0455782 0.05211101.17220000.0555123 0.05314201.15010000.0609900 0.05378701.03910010.0374883 0.05430301.10550000.0682001 0.05546301.04240000.0700737 0.05572101.01280000.0365374 0.05662300.95980000.0816260 0.05778400.87278000.0399371 0.05894400.94579990.0686140 0.05984600.82773000.0326498 0.06010400.93135620.0589472 0.06178000.71653000.0331549 0.06397100.68414000.0321702 0.06590500.62299000.0333924 0.06796700.53273000.0306341 0.06990000.52827000.0288278 0.07196200.49702000.0237777 0.07402300.43453000.0244900 0.07608500.43468000.0254912 0.07801700.37676000.0245524 0.08007900.36313000.0248486 0.08201100.29321000.0238416 0.08420100.30777600.0220036 0.08613300.27249200.0211632 0.08819300.23878400.0213009 0.09012500.19757000.0225400 0.09218500.20758000.0193132 0.09424600.14298000.0223312 0.09630600.15595600.0181288 0.09823700.17274910.0164332 0.10030000.13357000.0172144 0.10236000.12122800.0181687 0.10441000.12462000.0211687 0.10634000.09226800.0287396 0.016514067.24000551.8275404 0.017675055.17000201.6515716 0.018965044.45000080.9299312 0.019997037.13999940.9634947 0.021158032.27499770.6322041 0.022319026.85500140.6569422 0.023480023.31100080.5021554 0.024512018.89800070.4547758 0.025673016.38699910.3286716 0.026963014.60099980.2902413 0.027994012.53300000.2497759 0.029155011.09100060.2368396 0.029413010.66600040.3082872 0.03031609.72900010.2440430 0.03147708.55600070.2990000 0.03250907.61599970.1776542 0.03354106.89279990.1814590 0.03367006.80079980.1473446 0.03496006.18109990.1436558 0.03547605.66339970.1313187 0.03599105.45489980.1624743 0.03715204.95699980.1319632 0.03753904.86229990.1317052 0.03831304.63999990.1143638 0.03947403.92129970.1037440 0.04050503.68080000.0956243 0.04153703.40860010.0843225 0.04166603.46220020.1037428 0.04295603.17800000.1032926 0.04360102.85240010.0666967 0.04398702.95240000.0979359 0.04514802.75480010.0823618 0.04566402.54939990.0715765 0.04630902.56139990.0776779 0.04746902.44039990.0805259 0.04759802.16580010.0569113 0.04863002.16269990.0735884 0.04966101.91519990.0508236 0.04979002.03099990.0639988 0.05095101.89920000.0679424 0.05172401.70560000.0526855 0.05211101.69130000.0650492 0.05314201.56440000.0519131 0.05378701.54510000.0427112 0.05430301.60820000.0688460 0.05546301.48580000.0573203 0.05572101.33690000.0554345 0.05662301.44190000.0525411 0.05778401.12150000.0410104 0.05894401.35669990.0759596 0.05984601.08509990.0442507 0.06178000.93210010.0320390 0.06397100.86832000.0338189 0.06590500.70640000.0371206 0.06796700.76928000.0353327 0.06990000.67583000.0308312 0.07196200.61950000.0257599 0.07402300.55338000.0336506 0.07608500.49693000.0257651 0.07801700.50953000.0274449 0.08007900.38924000.0234446 0.08201100.38262000.0202858 0.08420100.37028000.0229208 0.08613300.31618000.0214367 0.08819300.25260000.0208953 0.09012500.27622000.0213909 0.09218500.21767000.0181380 0.09424600.19626000.0204266 0.09630600.19361000.0181224 0.09823700.19348000.0175461 AF1410-1h (AF1410 steel aged 1 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 AF1410-hf (AF1410 steel aged 0.5 h) nuclear sector nuclear+magnetic sector 0.017675025.81799891.3120309 0.018836021.60400010.9540655 0.019997018.26399990.7058364 0.021158015.50000100.5803740 0.022319013.13500020.5221877 0.023351011.22200010.3971297 0.02464109.39900020.3110145 0.02567308.30399990.2283265 0.02696307.26599980.2191848 0.02735007.10121350.2341834 0.02799406.39300010.1808037 0.02915505.34399990.1505246 0.02941305.59260030.1886492 0.03031604.81920000.1351548 0.03134804.23059990.1561482 0.03263803.73080020.1049711 0.03354103.43310020.1063994 0.03367003.33820010.0813841 0.03496003.07710000.0664910 0.03547602.79419990.0775103 0.03599102.72089980.0801145 0.03715202.27760000.0718850 0.03753902.34710000.0790419 0.03831302.18250010.0609341 0.03947401.94179990.0580505 0.04063401.81610000.0644560 0.04153701.61520000.0481176 0.04166601.67600000.0474384 0.04295601.49490000.0512235 0.04360101.45810000.0399991 0.04398701.36250010.0471088 0.04514801.36360000.0395506 0.04566401.19110000.0316425 0.04630901.13570000.0376619 0.04746901.03270010.0341974 0.04772701.03760000.0311006 0.04863001.04169990.0381451 0.04966100.92980000.0239921 0.05095100.84410000.0331127 0.05172400.77700000.0240187 0.05198200.73459990.0372993 0.05314200.66044000.0325246 0.05365800.66230000.0245253 0.05430300.73447000.0313337 0.05546300.67177000.0262155 0.05585000.61550000.0214462 0.05662300.59046000.0277276 0.05765500.51950000.0296998 0.05778400.53620000.0209057 0.05894400.54413000.0363593 0.05984600.48010000.0170473 0.05997500.52301000.0297405 0.06178000.45400000.0166208 0.06384200.37670000.0148519 0.06590500.32470000.0152594 0.06783800.30720000.0154185 0.06990000.27940000.0165496 0.07196200.26620000.0155416 0.07402300.27240000.0147177 0.07595600.22050000.0142359 0.07814600.19040000.0139291 0.08007900.18940000.0124535 0.08214000.18460000.0135152 0.08407200.16320000.0102626 0.08626200.13510000.0123822 0.08819300.13090000.0102650 0.09025400.11220000.0110675 0.09218500.09650000.0093648 0.09424600.10900000.0109932 0.09630600.09780000.0096799 0.09823700.08460000.0101710 0.10030000.07260000.0093509 0.10236000.06845550.0123903 0.017675044.66999822.2078269 0.018836037.71500021.5930109 0.019997030.60099791.1292781 0.021158025.85300061.1036870 0.022319021.72200010.7456789 0.023351018.85699840.6660030 0.024641015.73899940.5294318 0.025673013.43800070.3709515 0.026963011.36199950.3269327 0.027350010.78651520.3439711 0.02799409.95699980.2692527 0.02915508.46500020.2223250 0.02941308.65044500.2906038 0.03031607.54899980.2174245 0.03134806.35599990.2402041 0.03263806.15329980.1912273 0.03354105.19680020.1716854 0.03367005.29059980.0955391 0.03496004.84340000.0990227 0.03547604.29540010.1241205 0.03599104.30329990.0909418 0.03715203.77390030.1134376 0.03753903.54550000.0955823 0.03831303.66189980.1061369 0.03947402.94000010.0889360 0.04063402.84379980.0633733 0.04153702.46210000.0628004 0.04166602.68350010.0814840 0.04295602.35290000.0714317 0.04360102.10800000.0633376 0.04398702.14109990.0643394 0.04514802.07270000.0693237 0.04566401.78830000.0418971 0.04630901.96709990.0510554 0.04746901.66040000.0517177 0.04772701.54320000.0365274 0.04863001.62310000.0426395 0.04966101.35250000.0356665 0.05095101.32370000.0463816 0.05172401.18940000.0303266 0.05198201.25729990.0413575 0.05314201.17290000.0418938 0.05365801.00990010.0253024 0.05430301.14250000.0377256 0.05546301.00170000.0409158 0.05585000.89100000.0235274 0.05662301.02960000.0435437 0.05765500.90720000.0436232 0.05778400.79060000.0254892 0.05984600.75640000.0203089 0.06178000.66060000.0171735 0.06384200.55980000.0201695 0.06590500.53250000.0180069 0.06783800.48910000.0147801 0.06990000.43760000.0188915 0.07196200.40840000.0179011 0.07402300.38730000.0161137 0.07595600.33620000.0139671 0.07814600.33030000.0137295 0.08007900.30800000.0134302 0.08214000.29750000.0129800 0.08407200.26880000.0135695 0.08626200.24100000.0121491 0.08819300.22180000.0139291 0.09025400.18200000.0124555 0.09218500.17540000.0117478 0.09424600.16090000.0124278 0.09630600.15710000.0117068 0.09823700.13920000.0114612 0.10030000.11780000.0113230 AF1410-hf (AF1410 steel aged 0.5 h)
transverse saturation magnetic field (1.6 T) applied in horizontal direction to clear magnetic domain scattering
NIST/CNRF SANS neutron 0.85 25 area A.J. Allen D. Gavillet J.R. Weertman Small-Angle Neutron Scattering Studies of Carbide Precipitation in Ultrahigh-Strength Steels Acta Metall 41 1993 1869-1884 sasdata-0.8.1/test/sasdataloader/data/corrupt.png000066400000000000000000004445311427502211700220570ustar00rootroot00000000000000FILE: MAR07232.SA3_LP _V948 CREATED: Tuesday, Mar 13, 2007 12:49:09 PM LABEL: 13m Rad 0.5Pa Fib1 Th 0.16 PH7.4 Ca 2.5mM MON CNT LAMBDA(A) DET_OFF(cm) DET_DIST(m) TRANS THICK(cm) 13.705 0.84357 0.2 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 38 17.5 15.723 0.142 76.2 ORNL SAM: MAR07232.SA3_LP _V948 BGD: MAR07171.SA3_LP_V887, EMP: MAR07060.SA3_LP_V776,MAR07061.SA3_LP_V777, DIV: PLEX_04JAN07_NG3.DIV, MASK: DEFAULT.MASK, ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=84.433;XSECT=1 Average Choices: AVTYPE=2D_ASCII;SAVE=Yes;NAME=Auto;PLOT=Yes; *** Data written from ABS folder and may not be a fully corrected data file *** The detector image is a standard X-Y coordinate system Data is written by row, starting with Y=1 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0.300786 0.430485 0.255672 -0.0361383 0.148051 0.050911 -0.0964059 0.207996 0.110588 0.339068 0.0541874 0.682652 -0.122942 0.164212 -0.096355 -0.0373621 0.145986 0.520589 -0.225869 0.350932 -0.351536 0.328678 -0.0373391 0.0553562 0.297851 0.0511972 0.199673 0.466525 -0.0869905 -0.0896449 0.323633 0.31796 0.052544 -0.0866467 -0.0355165 0 0.530815 0.312985 0.0527644 0.175672 0.101287 0.186875 -0.0867421 -0.0331166 -0.170423 0.449012 0.135471 -0.0804284 -0.344996 -0.0798361 0.0520685 0.0160177 -0.140007sasdata-0.8.1/test/sasdataloader/data/detector_rectangular.DAT000066400000000000000000061235601427502211700244070ustar00rootroot00000000000000FILE: HiResSANS_exp18_scan0014_0001.xml CREATED: Mon, Feb 22, 2010 5:36:16 PM LABEL: Scatt 3m 6A cho MON CNT LAMBDA (A) DET_OFF(cm) DET_DIST(m) TRANS THICK(cm) 1e+08 6 0 3 1 0 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 21.167 95.978 0 4 17.495 0.1 76 HiResSANS SAM: HiResSANS_exp18_scan0014_0001.xml BGD: Unknown file from Average_Panel EMP: Unknown file from Average_Panel DIV: Unknown file from Average_Panel MASK: Unknown file from Average_Panel ABS Parameters (3-6): Unknown file from Average_Panel Average Choices: Unknown file from Average_Panel *** Data written from COR folder and may not be a fully corrected data file *** Data columns are Qx - Qy - I(Qx,Qy) - Qz - SigmaQx - SigmaQy - fSubS(beam stop shadow) ASCII data created Mon, Feb 22, 2010 5:39:51 PM -0.009160664 -0.1683881 16806.79 0.01366757 0 0 0 -0.007387845 -0.1683904 18767.68 0.01365374 0 0 0 -0.005614963 -0.1683922 16526.97 0.01364288 0 0 0 -0.003842033 -0.1683934 17927.92 0.01363498 0 0 0 -0.002069069 -0.1683943 17088.02 0.01363004 0 0 0 -0.0002960882 -0.1683946 13726.92 0.01362806 0 0 0 0.001476896 -0.1683944 19330.57 0.01362905 0 0 0 0.003249867 -0.1683938 17650.53 0.013633 0 0 0 0.00502281 -0.1683926 14849.71 0.01363991 0 0 0 0.006795709 -0.168391 15411.08 0.01364978 0 0 0 0.008568551 -0.1683889 18214.41 0.01366262 0 0 0 0.01034132 -0.1683864 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7484.831 0.05280859 0 0 0 0.2861583 0.1637193 10928.46 0.05324979 0 0 0 0.287735 0.1636462 10316.37 0.05369303 0 0 0 0.2893095 0.1635729 6572.908 0.05413831 0 0 0 0.2908819 0.1634992 8147.779 0.05458562 0 0 0sasdata-0.8.1/test/sasdataloader/data/detector_square.dat000066400000000000000000065533001427502211700235370ustar00rootroot00000000000000FILE: HiResSANS_exp18_scan0014_0001.xml CREATED: Mon, Feb 22, 2010 5:36:16 PM LABEL: Scatt 3m 6A cho MON CNT LAMBDA (A) DET_OFF(cm) DET_DIST(m) TRANS THICK(cm) 1e+08 6 0 3 1 0 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 21.167 95.978 0 4 17.495 0.1 76 HiResSANS SAM: HiResSANS_exp18_scan0014_0001.xml BGD: Unknown file from Average_Panel EMP: Unknown file from Average_Panel DIV: Unknown file from Average_Panel MASK: Unknown file from Average_Panel ABS Parameters (3-6): Unknown file from Average_Panel Average Choices: Unknown file from Average_Panel *** Data written from COR folder and may not be a fully corrected data file *** Data columns are Qx - Qy - I(Qx,Qy) - Qz - SigmaQx - SigmaQy - fSubS(beam stop shadow) ASCII data created Mon, Feb 22, 2010 5:39:51 PM -0.03573497 -0.1682965 20745.36 0.01422998 0 0 0 -0.03396493 -0.168306 19341.58 0.01417181 0 0 0 -0.0321946 -0.168315 16256.52 0.01411658 0 0 0 -0.03042399 -0.1683235 22140.47 0.01406431 0 0 0 -0.02865312 -0.1683315 16814.12 0.01401499 0 0 0 -0.02688201 -0.1683391 18494.12 0.01396862 0 0 0 -0.02511066 -0.1683462 16251.27 0.01392521 0 0 0 -0.0233391 -0.1683528 17370.97 0.01388475 0 0 0 -0.02156734 -0.1683589 19611.32 0.01384725 0 0 0 -0.01979539 -0.1683645 20170.69 0.0138127 0 0 0 -0.01802327 -0.1683697 17088.38 0.01378111 0 0 0 -0.016251 -0.1683743 17648.08 0.01375248 0 0 0 -0.01447859 -0.1683785 16527.16 0.01372681 0 0 0 -0.01270605 -0.1683822 19888.27 0.0137041 0 0 0 -0.0109334 -0.1683854 21288.65 0.01368435 0 0 0 -0.009160664 -0.1683881 16806.79 0.01366757 0 0 0 -0.007387845 -0.1683904 18767.68 0.01365374 0 0 0 -0.005614963 -0.1683922 16526.97 0.01364288 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1.067842171 0.001438612 0.001441075 1.070181366 0.002502384 0.001778269 sasdata-0.8.1/test/sasdataloader/data/jan08002.ABS000066400000000000000000000312051427502211700213320ustar00rootroot00000000000000FILE: jan08002.SA2_BH _R556 CREATED: Mon, Jan 21, 2008 1:34:58 PM LABEL: scatt 1m sam1 MON CNT LAMBDA DET ANG DET DIST TRANS THICK AVE STEP 1e+08 6 25 1 0.5667 0.2C 1 BCENT(X,Y) A1(mm) A2(mm) A1A2DIST(m) DL/L BSTOP(mm) DET_TYP 114.58 64.22 50 12.7 3.914 0.124 50.8 ORNL SAM: jan08002.SA2_BH _R556 BGD: JAN08008.SA2_BH_R562, EMP: JAN08007.SA2_BH_R561, DIV: PLEX_04JAN2008_NG7.DIV, MASK: DEFAULT.MASK, ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=2.547e+05;XSECT=1 Average Choices: AVTYPE=Circular;SAVE=Yes;NAME=Auto;PLOT=Yes; The 6 columns are | Q (1/A) | I(Q) (1/cm) | std. dev. I(Q) (1/cm) | sigmaQ | meanQ | ShadowFactor| 0.002618 0.02198 0.002704 0.0004091 0.008082 1e-10 0.007854 0.02201 0.001643 0.005587 0.0275 1.564e-12 0.01309 0.02695 0.002452 0.005598 0.02762 2.525e-07 0.01832 0.02645 0.001769 0.005624 0.02787 0.001046 0.02356 0.03024 0.001531 0.005707 0.02847 0.1293 0.02879 0.3927 0.1697 0.005975 0.03031 0.7933 0.03402 7.305 1.006 0.006264 0.03457 0.9972 0.03925 17.43 0.5351 0.006344 0.0397 1 0.04448 13.43 0.3677 0.006424 0.04488 1 0.0497 8.346 0.191 0.006516 0.05006 1 0.05492 5.675 0.09792 0.006618 0.05525 1 0.06014 4.082 0.06715 0.006729 0.06044 1 0.06535 3.024 0.04365 0.00685 0.06563 1 0.07057 2.318 0.0305 0.006978 0.07082 1 0.07577 1.806 0.02063 0.007114 0.07601 1 0.08098 1.458 0.01505 0.007257 0.0812 1 0.08617 1.197 0.01074 0.007407 0.08638 1 0.09137 1.014 0.008015 0.007563 0.09156 1 0.09656 0.8775 0.006137 0.007724 0.09674 1 0.1017 0.779 0.004953 0.007891 0.1019 1 0.1069 0.6975 0.003432 0.008062 0.1071 1 0.1121 0.6303 0.003423 0.008238 0.1122 1 0.1173 0.5814 0.002674 0.008418 0.1174 1 0.1224 0.545 0.002592 0.008603 0.1226 1 0.1276 0.5119 0.002274 0.00879 0.1277 1 0.1327 0.4836 0.002107 0.008981 0.1328 1 0.1379 0.4639 0.002137 0.009176 0.138 1 0.143 0.4467 0.001949 0.009373 0.1431 1 0.1481 0.433 0.002154 0.009572 0.1482 1 0.1532 0.418 0.001879 0.009774 0.1533 1 0.1583 0.404 0.00152 0.009979 0.1584 1 0.1634 0.394 0.001795 0.01019 0.1635 1 0.1685 0.3846 0.001611 0.01039 0.1686 1 0.1736 0.3801 0.00169 0.0106 0.1737 1 0.1787 0.3745 0.001626 0.01082 0.1788 1 0.1837 0.3672 0.001738 0.01103 0.1838 1 0.1888 0.3628 0.001329 0.01124 0.1889 1 0.1938 0.3565 0.001586 0.01146 0.1939 1 0.1988 0.3529 0.001491 0.01167 0.1989 1 0.2039 0.3486 0.001576 0.01189 0.204 1 0.2089 0.346 0.001404 0.01211 0.209 1 0.2139 0.3437 0.001433 0.01233 0.214 1 0.2189 0.3402 0.001474 0.01255 0.2189 1 0.2238 0.3389 0.001456 0.01277 0.2239 1 0.2288 0.3353 0.001414 0.01299 0.2289 1 0.2338 0.3348 0.001335 0.01322 0.2338 1 0.2387 0.3308 0.001375 0.01344 0.2388 1 0.2436 0.3279 0.001338 0.01366 0.2437 1 0.2485 0.3275 0.001351 0.01388 0.2486 1 0.2535 0.3234 0.001382 0.01411 0.2535 1 0.2583 0.3229 0.001311 0.01433 0.2584 1 0.2632 0.3215 0.001243 0.01455 0.2633 1 0.2681 0.3213 0.001158 0.01478 0.2681 1 0.2729 0.3207 0.001265 0.015 0.273 1 0.2778 0.3173 0.001306 0.01522 0.2778 1 0.2826 0.3183 0.001289 0.01545 0.2827 1 0.2874 0.3168 0.001353 0.01567 0.2875 1 0.2922 0.317 0.001278 0.0159 0.2923 1 0.297 0.316 0.001284 0.01612 0.297 1 0.3018 0.316 0.001155 0.01634 0.3018 1 0.3065 0.3143 0.001252 0.01656 0.3066 1 0.3112 0.3137 0.001296 0.01679 0.3113 1 0.316 0.3122 0.001338 0.01701 0.316 1 0.3207 0.3119 0.001458 0.01723 0.3207 1 0.3254 0.3116 0.001401 0.01745 0.3254 1 0.33 0.3121 0.001451 0.01768 0.3301 1 0.3347 0.3122 0.001458 0.0179 0.3348 1 0.3394 0.3105 0.001484 0.01812 0.3394 1 0.344 0.3124 0.001495 0.01834 0.344 1 0.3486 0.3096 0.001373 0.01856 0.3486 1 0.3532 0.3107 0.001554 0.01878 0.3532 1 0.3578 0.3099 0.001365 0.019 0.3578 1 0.3623 0.3087 0.001357 0.01921 0.3624 1 0.3669 0.3109 0.001621 0.01943 0.3669 1 0.3714 0.3104 0.001505 0.01965 0.3715 1 0.3759 0.3094 0.001404 0.01987 0.376 1 0.3804 0.3102 0.001422 0.02008 0.3805 1 0.3849 0.3074 0.001452 0.0203 0.385 1 0.3894 0.3097 0.001307 0.02051 0.3894 1 0.3938 0.3052 0.001569 0.02073 0.3939 1 0.3983 0.3052 0.001521 0.02094 0.3983 1 0.4027 0.3064 0.001583 0.02116 0.4027 1 0.4071 0.3059 0.001513 0.02137 0.4071 1 0.4115 0.3063 0.001639 0.02158 0.4115 1 0.4158 0.3066 0.00148 0.02179 0.4159 1 0.4202 0.3062 0.001607 0.022 0.4202 1 0.4245 0.3051 0.001567 0.02221 0.4245 1 0.4288 0.3052 0.001319 0.02242 0.4289 1 0.4331 0.309 0.001496 0.02263 0.4331 1 0.4374 0.3066 0.001573 0.02284 0.4374 1 0.4416 0.3035 0.001526 0.02304 0.4417 1 0.4459 0.3055 0.001542 0.02325 0.4459 1 0.4501 0.303 0.001428 0.02346 0.4501 1 0.4543 0.3057 0.001509 0.02366 0.4543 1 0.4585 0.3056 0.001376 0.02387 0.4585 1 0.4627 0.3037 0.001384 0.02407 0.4627 1 0.4668 0.3017 0.001437 0.02427 0.4668 1 0.4709 0.3038 0.001687 0.02447 0.471 1 0.4751 0.308 0.001492 0.02467 0.4751 1 0.4792 0.3043 0.001532 0.02487 0.4792 1 0.4832 0.3024 0.00154 0.02507 0.4833 1 0.4873 0.3053 0.001643 0.02527 0.4873 1 0.4913 0.3028 0.001856 0.02547 0.4914 1 0.4954 0.3013 0.00164 0.02567 0.4954 1 0.4994 0.3064 0.00154 0.02586 0.4994 1 0.5033 0.3057 0.00168 0.02606 0.5034 1 0.5073 0.3047 0.001643 0.02625 0.5073 1 0.5113 0.3032 0.001675 0.02645 0.5113 1 0.5152 0.303 0.001439 0.02664 0.5152 1 0.5191 0.3037 0.001692 0.02683 0.5191 1 0.523 0.3021 0.001634 0.02702 0.523 1 0.5269 0.3022 0.00178 0.02721 0.5269 1 0.5307 0.3029 0.001911 0.0274 0.5307 1 0.5346 0.3011 0.002309 0.02759 0.5346 1 0.5384 0.3024 0.001987 0.02778 0.5384 1 0.5422 0.3044 0.002772 0.02797 0.5422 1 0.546 0.3009 0.0025 0.02815 0.546 1 0.5497 0.3002 0.002315 0.02834 0.5498 1 0.5535 0.3 0.002721 0.02852 0.5535 1 0.5572 0.3038 0.002978 0.02871 0.5572 1 0.5609 0.2928 0.003387 0.02889 0.5609 1 0.5646 0.3084 0.003712 0.02907 0.5646 1 0.5683 0.2998 0.00444 0.02925 0.5683 1 0.5719 0.2987 0.003861 0.02943 0.572 1 0.5756 0.2952 0.00588 0.02961 0.5756 1 0.5792 0.2842 0.007206 0.02979 0.5792 1 0.5828 0.2958 1 0.02997 0.5828 1 sasdata-0.8.1/test/sasdataloader/data/multiframe_1d.nxs000066400000000000000000140313601427502211700231330ustar00rootroot00000000000000‰HDF  ÿÿÿÿÿÿÿÿð20ÿÿÿÿÿÿÿÿ`ˆ¨ XTREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ8HEAPXÈsasentry@ˆ¨ 0 canSAS_classSASroot 0default sasentry H file_nameBBAA_processed_180309_132658 @ file_time2018-07-03 09:28:59 0 producerDAWN€ðTREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ€ HEAPX0àdefinitionruntitlesasdata(SNODx À À 0 NX_classNXentry 8 canSAS_class SASentry (defaultsasdata (version1.0È Ë3;[ˆSNODp Ø(ø @ èØ GCOLNXcanSASBBAA_processed_180309_132658BBAA_processed_180309_132658xØ#Ë3;[ˆè#Ë3;[ˆ¸ (TREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿØ+HEAPX0` QIdevIIdevI( @ 0 NX_classNXdata 0 canSAS_classSASdata (signalI (I_axesQ 8 Q_indices@QQ ?@4 4ÿØ3ˆ2Ë3;[ (units1/nmHØ Ø SNOD(pË -à!(xQxQ ?@4 4ÿ0ƒÀ¯#6;[ 0units arbitrary0QQ ?@4 4ÿ蘈2Ë3;[ 0units arbitrary 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0.000610766363101 0.0259396956981 0.422997019184 0.000603630795644 0.0261940029188 0.42238665178 0.000600517892597 0.0264483100364 0.420723189494 0.000595691853282 0.02670261705 0.417677489997 0.00059177980412 0.0269569239584 0.416684475245 0.000589602978239 0.0272112307608 0.414820901156 0.000582778736784 0.0274655374562 0.412439768264 0.000579858907699 0.0277198440435 0.41017673348 0.000574044480065 0.0279741505217 0.409140290293 0.000570549693466 0.0282284568898 0.406103538544 0.000581669795273 0.0284827631469 0.404715748736 0.000577896971507 0.0287370692918 0.402811717506 0.000582445970909 0.0289913753238 0.400226678654 0.000583263806156 0.0292456812416 0.398703821036 0.000580170427503 0.0294999870444 0.395988877127 0.000582165536205 0.0297542927311 0.393849576778 0.000576327938111 0.0300085983007 0.391742600704 0.000576626845366 0.0302629037523 0.388777941876 0.000579762658064 0.0305172090848 0.387867890272 0.000571857287596 0.0307715142972 0.38576942019 0.000574617792542 0.0310258193885 0.383650040939 0.000567492185066 0.0312801243578 0.382125724324 0.000569119984207 0.031534429204 0.37948944247 0.000571238516757 0.0317887339261 0.376585699837 0.000566273697082 0.0320430385231 0.374631672787 0.000560179702893 0.032297342994 0.372896842758 0.000560596899293 0.0325516473379 0.369537642883 0.000557612868097 0.0328059515537 0.367868977457 0.000559747633416 0.0330602556404 0.36614658257 0.000551872985054 0.0333145595971 0.362894037393 0.000552291740168 0.0335688634226 0.361814557032 0.000551207936033 0.0338231671161 0.358608296707 0.000543446427561 0.0340774706765 0.357038638548 0.000547185936237 0.0343317741028 0.354667464719 0.000539952544802 0.034586077394 0.350473485991 0.000542732333585 0.0348403805492 0.348646945237 0.000537429663175 0.0350946835672 0.346336331848 0.000533443608761 0.0353489864472 0.344646689663 0.000531784874419 0.0356032891881 0.342185633275 0.000529760297726 0.0358575917889 0.339626215615 0.000527768156838 0.0361118942486 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H canSAS_class ` k–]ˆSNODÐ (0È×èÙ8`ÚˆÚ¨Ü0XÒxÔTREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ€ÖHEAPX˜Ôradiation@XÒxÔ H canSAS_class ` l–]ˆSNODpÕTREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ€ÖHEAPXÚP Ý€TREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ°ÞHEAPXÈÜnameHˆÚ¨Ü H canSAS_class `s–]ˆSNOD Ýhã€TREEÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ°ÞHEAPX`âPdefinitionruntitlesasdata01sassamplesasinstrumentsasnoteP à@â H canSAS_class`sasdata-0.8.1/test/sasdataloader/error_conditions.py000066400000000000000000000021541427502211700226650ustar00rootroot00000000000000from sasdata.dataloader.loader import Loader import unittest class testLoader(unittest.TestCase): def setUp(self): self.s = Loader() def test_load_unknown(self): """ self.s.load('blah.mat') on an unknown type should raise a ValueError exception (thrown by data_util.registry) """ self.assertRaises(ValueError, self.s.load, 'angles_flat.mat') def test_corrupt(self): """ Loading a corrupted file with a known extension should raise a runtime exception. The error condition is similar to an unknown type (file extension). When a reader is identified as knowing the file extension, it tries to load. If it raises an exception, the system should try to identify another reader that knows about that file extension. If they all fail, we raise a runtime exception stating that no reader was found for this file. """ self.assertRaises(RuntimeError, self.s.load, 'corrupt.png') if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/sesans_data/000077500000000000000000000000001427502211700212145ustar00rootroot00000000000000sasdata-0.8.1/test/sasdataloader/sesans_data/next_gen.ses000066400000000000000000000046531427502211700235470ustar00rootroot00000000000000FileFormatVersion 2.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error Wavelength 260.0 -1.42E-3 2.04E-3 1.612452 280.8 -1.45E-3 1.87E-3 1.675709 303.264 -1.64E-3 1.23E-3 1.741448 327.525 -1.69E-3 1.17E-3 1.809765 353.727 -2.23E-3 9.09E-4 1.880763 382.025 -2.26E-3 8.58E-4 1.954546 412.587 -2.41E-3 7.29E-4 2.031224 445.594 -2.58E-3 6.75E-4 2.11091 481.242 -2.88E-3 6.04E-4 2.193723 519.741 -3.35E-3 5.56E-4 2.279783 561.32 -3.60E-3 5.22E-4 2.369219 606.226 -3.92E-3 4.91E-4 2.462166 654.724 -4.36E-3 4.73E-4 2.558758 707.102 -4.67E-3 4.54E-4 2.659139 763.67 -4.91E-3 4.22E-4 2.763458 824.764 -5.32E-3 3.88E-4 2.87187 890.745 -5.43E-3 3.53E-4 2.984535 962.005 -5.61E-3 3.28E-4 3.101621 1038.97 -5.83E-3 3.07E-4 3.223306 1122.08 -5.88E-3 2.91E-4 3.349746 1211.85 -5.91E-3 2.73E-4 3.481164 1308.8 -5.71E-3 2.61E-4 3.617734 1413.5 -5.40E-3 2.49E-4 3.759654 1526.58 -5.10E-3 2.41E-4 3.907147 1648.71 -4.77E-3 2.34E-4 4.060431 1780.6 -4.34E-3 2.26E-4 4.219716 1923.05 -4.18E-3 2.20E-4 4.385259 2076.9 -4.08E-3 2.16E-4 4.557302 2243.05 -4.37E-3 2.13E-4 4.736085 2422.49 -4.66E-3 2.10E-4 4.92188 2616.29 -4.96E-3 2.06E-4 5.114968 2825.59 -5.04E-3 2.03E-4 5.315628 3051.64 -4.96E-3 1.99E-4 5.524165 3295.77 -4.72E-3 1.97E-4 5.74088 3559.43 -4.52E-3 1.92E-4 5.966096 3844.19 -4.65E-3 1.93E-4 6.200153 4151.72 -4.74E-3 1.96E-4 6.443384 4483.86 -4.87E-3 1.99E-4 6.696163 4842.57 -4.81E-3 2.05E-4 6.958858 5229.98 -4.57E-3 2.09E-4 7.23186 5648.38 -4.72E-3 2.17E-4 7.515571 6100.25 -4.79E-3 2.23E-4 7.81041 6588.27 -4.68E-3 2.28E-4 8.116816 7115.33 -4.61E-3 2.32E-4 8.435242 7684.55 -4.78E-3 2.46E-4 8.766157 8299.32 -4.74E-3 2.46E-4 9.11006 8963.26 -4.56E-3 2.50E-4 9.467449 9680.32 -4.70E-3 2.58E-4 9.838862 10454.7 -4.81E-3 2.64E-4 10.224823 11291.1 -4.65E-3 2.69E-4 10.625959 12194.4 -4.43E-3 2.79E-4 11.042826 13170.0 -4.55E-3 3.01E-4 11.476062 14223.6 -4.35E-3 3.20E-4 11.926274 15361.5 -4.24E-3 3.51E-4 12.394152 16590.4 -4.68E-3 4.12E-4 12.880373 17917.6 -4.96E-3 4.98E-4 13.385664 19303.4 -4.56E-3 5.98E-4 13.893668 sasdata-0.8.1/test/sasdataloader/sesans_data/no_spin_echo_unit.ses000066400000000000000000000046211427502211700254350ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error Wavelength 260.0 -1.42E-3 2.04E-3 1.612452 280.8 -1.45E-3 1.87E-3 1.675709 303.264 -1.64E-3 1.23E-3 1.741448 327.525 -1.69E-3 1.17E-3 1.809765 353.727 -2.23E-3 9.09E-4 1.880763 382.025 -2.26E-3 8.58E-4 1.954546 412.587 -2.41E-3 7.29E-4 2.031224 445.594 -2.58E-3 6.75E-4 2.11091 481.242 -2.88E-3 6.04E-4 2.193723 519.741 -3.35E-3 5.56E-4 2.279783 561.32 -3.60E-3 5.22E-4 2.369219 606.226 -3.92E-3 4.91E-4 2.462166 654.724 -4.36E-3 4.73E-4 2.558758 707.102 -4.67E-3 4.54E-4 2.659139 763.67 -4.91E-3 4.22E-4 2.763458 824.764 -5.32E-3 3.88E-4 2.87187 890.745 -5.43E-3 3.53E-4 2.984535 962.005 -5.61E-3 3.28E-4 3.101621 1038.97 -5.83E-3 3.07E-4 3.223306 1122.08 -5.88E-3 2.91E-4 3.349746 1211.85 -5.91E-3 2.73E-4 3.481164 1308.8 -5.71E-3 2.61E-4 3.617734 1413.5 -5.40E-3 2.49E-4 3.759654 1526.58 -5.10E-3 2.41E-4 3.907147 1648.71 -4.77E-3 2.34E-4 4.060431 1780.6 -4.34E-3 2.26E-4 4.219716 1923.05 -4.18E-3 2.20E-4 4.385259 2076.9 -4.08E-3 2.16E-4 4.557302 2243.05 -4.37E-3 2.13E-4 4.736085 2422.49 -4.66E-3 2.10E-4 4.92188 2616.29 -4.96E-3 2.06E-4 5.114968 2825.59 -5.04E-3 2.03E-4 5.315628 3051.64 -4.96E-3 1.99E-4 5.524165 3295.77 -4.72E-3 1.97E-4 5.74088 3559.43 -4.52E-3 1.92E-4 5.966096 3844.19 -4.65E-3 1.93E-4 6.200153 4151.72 -4.74E-3 1.96E-4 6.443384 4483.86 -4.87E-3 1.99E-4 6.696163 4842.57 -4.81E-3 2.05E-4 6.958858 5229.98 -4.57E-3 2.09E-4 7.23186 5648.38 -4.72E-3 2.17E-4 7.515571 6100.25 -4.79E-3 2.23E-4 7.81041 6588.27 -4.68E-3 2.28E-4 8.116816 7115.33 -4.61E-3 2.32E-4 8.435242 7684.55 -4.78E-3 2.46E-4 8.766157 8299.32 -4.74E-3 2.46E-4 9.11006 8963.26 -4.56E-3 2.50E-4 9.467449 9680.32 -4.70E-3 2.58E-4 9.838862 10454.7 -4.81E-3 2.64E-4 10.224823 11291.1 -4.65E-3 2.69E-4 10.625959 12194.4 -4.43E-3 2.79E-4 11.042826 13170.0 -4.55E-3 3.01E-4 11.476062 14223.6 -4.35E-3 3.20E-4 11.926274 15361.5 -4.24E-3 3.51E-4 12.394152 16590.4 -4.68E-3 4.12E-4 12.880373 17917.6 -4.96E-3 4.98E-4 13.385664 19303.4 -4.56E-3 5.98E-4 13.893668 sasdata-0.8.1/test/sasdataloader/sesans_data/no_wavelength.ses000066400000000000000000000046411427502211700245750ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error 260.0 -1.42E-3 2.04E-3 1.612452 280.8 -1.45E-3 1.87E-3 1.675709 303.264 -1.64E-3 1.23E-3 1.741448 327.525 -1.69E-3 1.17E-3 1.809765 353.727 -2.23E-3 9.09E-4 1.880763 382.025 -2.26E-3 8.58E-4 1.954546 412.587 -2.41E-3 7.29E-4 2.031224 445.594 -2.58E-3 6.75E-4 2.11091 481.242 -2.88E-3 6.04E-4 2.193723 519.741 -3.35E-3 5.56E-4 2.279783 561.32 -3.60E-3 5.22E-4 2.369219 606.226 -3.92E-3 4.91E-4 2.462166 654.724 -4.36E-3 4.73E-4 2.558758 707.102 -4.67E-3 4.54E-4 2.659139 763.67 -4.91E-3 4.22E-4 2.763458 824.764 -5.32E-3 3.88E-4 2.87187 890.745 -5.43E-3 3.53E-4 2.984535 962.005 -5.61E-3 3.28E-4 3.101621 1038.97 -5.83E-3 3.07E-4 3.223306 1122.08 -5.88E-3 2.91E-4 3.349746 1211.85 -5.91E-3 2.73E-4 3.481164 1308.8 -5.71E-3 2.61E-4 3.617734 1413.5 -5.40E-3 2.49E-4 3.759654 1526.58 -5.10E-3 2.41E-4 3.907147 1648.71 -4.77E-3 2.34E-4 4.060431 1780.6 -4.34E-3 2.26E-4 4.219716 1923.05 -4.18E-3 2.20E-4 4.385259 2076.9 -4.08E-3 2.16E-4 4.557302 2243.05 -4.37E-3 2.13E-4 4.736085 2422.49 -4.66E-3 2.10E-4 4.92188 2616.29 -4.96E-3 2.06E-4 5.114968 2825.59 -5.04E-3 2.03E-4 5.315628 3051.64 -4.96E-3 1.99E-4 5.524165 3295.77 -4.72E-3 1.97E-4 5.74088 3559.43 -4.52E-3 1.92E-4 5.966096 3844.19 -4.65E-3 1.93E-4 6.200153 4151.72 -4.74E-3 1.96E-4 6.443384 4483.86 -4.87E-3 1.99E-4 6.696163 4842.57 -4.81E-3 2.05E-4 6.958858 5229.98 -4.57E-3 2.09E-4 7.23186 5648.38 -4.72E-3 2.17E-4 7.515571 6100.25 -4.79E-3 2.23E-4 7.81041 6588.27 -4.68E-3 2.28E-4 8.116816 7115.33 -4.61E-3 2.32E-4 8.435242 7684.55 -4.78E-3 2.46E-4 8.766157 8299.32 -4.74E-3 2.46E-4 9.11006 8963.26 -4.56E-3 2.50E-4 9.467449 9680.32 -4.70E-3 2.58E-4 9.838862 10454.7 -4.81E-3 2.64E-4 10.224823 11291.1 -4.65E-3 2.69E-4 10.625959 12194.4 -4.43E-3 2.79E-4 11.042826 13170.0 -4.55E-3 3.01E-4 11.476062 14223.6 -4.35E-3 3.20E-4 11.926274 15361.5 -4.24E-3 3.51E-4 12.394152 16590.4 -4.68E-3 4.12E-4 12.880373 17917.6 -4.96E-3 4.98E-4 13.385664 19303.4 -4.56E-3 5.98E-4 13.893668 sasdata-0.8.1/test/sasdataloader/sesans_data/sesans_no_data.ses000066400000000000000000000007431427502211700247150ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA sasdata-0.8.1/test/sasdataloader/sesans_data/sphere2micron.ses000066400000000000000000000063671427502211700245240ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle Polystyrene of Markus Strobl, Full Sine, ++ only Sample Polystyrene 2 um in 53% H2O, 47% D2O Settings D1=D2=20x8 mm,Ds = 16x10 mm (WxH), GF1 =scanning, GF2 = 2.5 A. 2 um polystyrene in 53% H2O, 47% D2O; 8.55% contrast Operator CPD Date do 10 jul 2014 16:37:30 ScanType sine one element scan Thickness 2.00E-01 Thickness_unit cm Theta_zmax 0.0168 Theta_zmax_unit radians Theta_ymax 0.0168 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error SpinEchoLength_error Wavelength Wavelength_error Polarisation Polarisation_error 391.56 0.0041929 0.0036894 19.578 2.11 0.1055 1.0037 0.0032974 1564 -0.0046571 0.0038185 78.2 2.11 0.1055 0.99586 0.003386 2735.6 -0.017007 0.0038132 136.78 2.11 0.1055 0.98497 0.0033444 3907.9 -0.033462 0.0035068 195.39 2.11 0.1055 0.97064 0.0030309 5080.2 -0.047483 0.0038208 254.01 2.11 0.1055 0.9586 0.0032613 6251.8 -0.070375 0.00376 312.59 2.11 0.1055 0.93926 0.0031446 7423.2 -0.092217 0.0037927 371.16 2.11 0.1055 0.92117 0.0031108 8595.5 -0.10238 0.004006 429.77 2.11 0.1055 0.91287 0.0032562 9767.7 -0.12672 0.0038534 488.39 2.11 0.1055 0.8933 0.0030651 10940 -0.1374 0.004243 546.98 2.11 0.1055 0.88484 0.003343 12112 -0.16072 0.0045837 605.58 2.11 0.1055 0.86666 0.0035372 13284 -0.16623 0.0045613 664.2 2.11 0.1055 0.86242 0.0035027 14456 -0.18468 0.0044918 722.79 2.11 0.1055 0.84837 0.0033931 15628 -0.19143 0.0048967 781.38 2.11 0.1055 0.84328 0.0036768 16800 -0.20029 0.0045421 840.02 2.11 0.1055 0.83666 0.0033837 17971 -0.19798 0.0046642 898.56 2.11 0.1055 0.83838 0.0034819 19143 -0.21442 0.0047052 957.17 2.11 0.1055 0.82619 0.0034614 20316 -0.20885 0.0044931 1015.8 2.11 0.1055 0.8303 0.0033218 21488 -0.21393 0.0049186 1074.4 2.11 0.1055 0.82655 0.00362 22660 -0.20685 0.004423 1133 2.11 0.1055 0.83179 0.0032758 23832 -0.20802 0.0046979 1191.6 2.11 0.1055 0.83092 0.0034758 25003 -0.19848 0.0045953 1250.2 2.11 0.1055 0.838 0.0034289 26175 -0.21117 0.0044567 1308.8 2.11 0.1055 0.82859 0.0032881 27347 -0.21283 0.004137 1367.4 2.11 0.1055 0.82736 0.0030477 28520 -0.2042 0.0044587 1426 2.11 0.1055 0.83375 0.0033101 29692 -0.2112 0.0042852 1484.6 2.11 0.1055 0.82857 0.0031615 30864 -0.20319 0.0043483 1543.2 2.11 0.1055 0.8345 0.003231 32036 -0.20752 0.0044297 1601.8 2.11 0.1055 0.83129 0.0032788 33207 -0.20654 0.0043188 1660.4 2.11 0.1055 0.83201 0.0031995 34380 -0.20126 0.0046375 1719 2.11 0.1055 0.83593 0.0034518 35551 -0.20924 0.0042871 1777.6 2.11 0.1055 0.83001 0.0031684 36724 -0.21323 0.0045471 1836.2 2.11 0.1055 0.82707 0.0033487 37895 -0.21324 0.0045354 1894.7 2.11 0.1055 0.82706 0.00334 39067 -0.19905 0.0044141 1953.4 2.11 0.1055 0.83758 0.003292 40239 -0.1991 0.0047441 2012 2.11 0.1055 0.83754 0.003538 41411 -0.20359 0.0050136 2070.5 2.11 0.1055 0.8342 0.003724 42583 -0.21032 0.0049474 2129.1 2.11 0.1055 0.82922 0.0036529 43755 -0.20689 0.0048203 2187.8 2.11 0.1055 0.83176 0.00357 44927 -0.21075 0.0052337 2246.4 2.11 0.1055 0.8289 0.0038628 46099 -0.19956 0.0047827 2304.9 2.11 0.1055 0.8372 0.0035653 sasdata-0.8.1/test/sasdataloader/sesans_data/sphere_isis.ses000066400000000000000000000046531427502211700242550ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error Wavelength 260.0 -1.42E-3 2.04E-3 1.612452 280.8 -1.45E-3 1.87E-3 1.675709 303.264 -1.64E-3 1.23E-3 1.741448 327.525 -1.69E-3 1.17E-3 1.809765 353.727 -2.23E-3 9.09E-4 1.880763 382.025 -2.26E-3 8.58E-4 1.954546 412.587 -2.41E-3 7.29E-4 2.031224 445.594 -2.58E-3 6.75E-4 2.11091 481.242 -2.88E-3 6.04E-4 2.193723 519.741 -3.35E-3 5.56E-4 2.279783 561.32 -3.60E-3 5.22E-4 2.369219 606.226 -3.92E-3 4.91E-4 2.462166 654.724 -4.36E-3 4.73E-4 2.558758 707.102 -4.67E-3 4.54E-4 2.659139 763.67 -4.91E-3 4.22E-4 2.763458 824.764 -5.32E-3 3.88E-4 2.87187 890.745 -5.43E-3 3.53E-4 2.984535 962.005 -5.61E-3 3.28E-4 3.101621 1038.97 -5.83E-3 3.07E-4 3.223306 1122.08 -5.88E-3 2.91E-4 3.349746 1211.85 -5.91E-3 2.73E-4 3.481164 1308.8 -5.71E-3 2.61E-4 3.617734 1413.5 -5.40E-3 2.49E-4 3.759654 1526.58 -5.10E-3 2.41E-4 3.907147 1648.71 -4.77E-3 2.34E-4 4.060431 1780.6 -4.34E-3 2.26E-4 4.219716 1923.05 -4.18E-3 2.20E-4 4.385259 2076.9 -4.08E-3 2.16E-4 4.557302 2243.05 -4.37E-3 2.13E-4 4.736085 2422.49 -4.66E-3 2.10E-4 4.92188 2616.29 -4.96E-3 2.06E-4 5.114968 2825.59 -5.04E-3 2.03E-4 5.315628 3051.64 -4.96E-3 1.99E-4 5.524165 3295.77 -4.72E-3 1.97E-4 5.74088 3559.43 -4.52E-3 1.92E-4 5.966096 3844.19 -4.65E-3 1.93E-4 6.200153 4151.72 -4.74E-3 1.96E-4 6.443384 4483.86 -4.87E-3 1.99E-4 6.696163 4842.57 -4.81E-3 2.05E-4 6.958858 5229.98 -4.57E-3 2.09E-4 7.23186 5648.38 -4.72E-3 2.17E-4 7.515571 6100.25 -4.79E-3 2.23E-4 7.81041 6588.27 -4.68E-3 2.28E-4 8.116816 7115.33 -4.61E-3 2.32E-4 8.435242 7684.55 -4.78E-3 2.46E-4 8.766157 8299.32 -4.74E-3 2.46E-4 9.11006 8963.26 -4.56E-3 2.50E-4 9.467449 9680.32 -4.70E-3 2.58E-4 9.838862 10454.7 -4.81E-3 2.64E-4 10.224823 11291.1 -4.65E-3 2.69E-4 10.625959 12194.4 -4.43E-3 2.79E-4 11.042826 13170.0 -4.55E-3 3.01E-4 11.476062 14223.6 -4.35E-3 3.20E-4 11.926274 15361.5 -4.24E-3 3.51E-4 12.394152 16590.4 -4.68E-3 4.12E-4 12.880373 17917.6 -4.96E-3 4.98E-4 13.385664 19303.4 -4.56E-3 5.98E-4 13.893668 sasdata-0.8.1/test/sasdataloader/sesans_data/too_many_headers.ses000066400000000000000000000047001427502211700252510ustar00rootroot00000000000000FileFormatVersion 1.0 DataFileTitle PMMA in Mixed Deuterated decalin Sample Ostensibly 40$ 100nm radius PMMA hard spheres in mixed deuterarted decalin. Thickness 2 Thickness_unit mm Theta_zmax 0.09 Theta_zmax_unit radians Theta_ymax 0.09 Theta_ymax_unit radians Orientation Z SpinEchoLength_unit A Depolarisation_unit A-2 cm-1 Wavelength_unit A BEGIN_DATA SpinEchoLength Depolarisation Depolarisation_error Wavelength SpinEchoLength_error 260.0 -1.42E-3 2.04E-3 1.612452 280.8 -1.45E-3 1.87E-3 1.675709 303.264 -1.64E-3 1.23E-3 1.741448 327.525 -1.69E-3 1.17E-3 1.809765 353.727 -2.23E-3 9.09E-4 1.880763 382.025 -2.26E-3 8.58E-4 1.954546 412.587 -2.41E-3 7.29E-4 2.031224 445.594 -2.58E-3 6.75E-4 2.11091 481.242 -2.88E-3 6.04E-4 2.193723 519.741 -3.35E-3 5.56E-4 2.279783 561.32 -3.60E-3 5.22E-4 2.369219 606.226 -3.92E-3 4.91E-4 2.462166 654.724 -4.36E-3 4.73E-4 2.558758 707.102 -4.67E-3 4.54E-4 2.659139 763.67 -4.91E-3 4.22E-4 2.763458 824.764 -5.32E-3 3.88E-4 2.87187 890.745 -5.43E-3 3.53E-4 2.984535 962.005 -5.61E-3 3.28E-4 3.101621 1038.97 -5.83E-3 3.07E-4 3.223306 1122.08 -5.88E-3 2.91E-4 3.349746 1211.85 -5.91E-3 2.73E-4 3.481164 1308.8 -5.71E-3 2.61E-4 3.617734 1413.5 -5.40E-3 2.49E-4 3.759654 1526.58 -5.10E-3 2.41E-4 3.907147 1648.71 -4.77E-3 2.34E-4 4.060431 1780.6 -4.34E-3 2.26E-4 4.219716 1923.05 -4.18E-3 2.20E-4 4.385259 2076.9 -4.08E-3 2.16E-4 4.557302 2243.05 -4.37E-3 2.13E-4 4.736085 2422.49 -4.66E-3 2.10E-4 4.92188 2616.29 -4.96E-3 2.06E-4 5.114968 2825.59 -5.04E-3 2.03E-4 5.315628 3051.64 -4.96E-3 1.99E-4 5.524165 3295.77 -4.72E-3 1.97E-4 5.74088 3559.43 -4.52E-3 1.92E-4 5.966096 3844.19 -4.65E-3 1.93E-4 6.200153 4151.72 -4.74E-3 1.96E-4 6.443384 4483.86 -4.87E-3 1.99E-4 6.696163 4842.57 -4.81E-3 2.05E-4 6.958858 5229.98 -4.57E-3 2.09E-4 7.23186 5648.38 -4.72E-3 2.17E-4 7.515571 6100.25 -4.79E-3 2.23E-4 7.81041 6588.27 -4.68E-3 2.28E-4 8.116816 7115.33 -4.61E-3 2.32E-4 8.435242 7684.55 -4.78E-3 2.46E-4 8.766157 8299.32 -4.74E-3 2.46E-4 9.11006 8963.26 -4.56E-3 2.50E-4 9.467449 9680.32 -4.70E-3 2.58E-4 9.838862 10454.7 -4.81E-3 2.64E-4 10.224823 11291.1 -4.65E-3 2.69E-4 10.625959 12194.4 -4.43E-3 2.79E-4 11.042826 13170.0 -4.55E-3 3.01E-4 11.476062 14223.6 -4.35E-3 3.20E-4 11.926274 15361.5 -4.24E-3 3.51E-4 12.394152 16590.4 -4.68E-3 4.12E-4 12.880373 17917.6 -4.96E-3 4.98E-4 13.385664 19303.4 -4.56E-3 5.98E-4 13.893668 sasdata-0.8.1/test/sasdataloader/utest_abs_reader.py000066400000000000000000000113611427502211700226160ustar00rootroot00000000000000""" Unit tests for data manipulations """ import unittest from sasdata.dataloader.loader import Loader from sasdata.dataloader.readers.abs_reader import Reader as AbsReader from sasdata.dataloader.readers.danse_reader import Reader as DANSEReader import os.path def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class abs_reader(unittest.TestCase): def setUp(self): reader = AbsReader() self.data_list = reader.read(find("jan08002.ABS")) self.data = self.data_list[0] def test_abs_checkdata(self): """ Check the data content to see whether it matches the specific file we loaded. Check the units too to see whether the Data1D defaults changed. Otherwise the tests won't pass """ self.assertEqual(os.path.basename(self.data.filename), "jan08002.ABS") self.assertEqual(self.data.meta_data['loader'], "IGOR 1D") self.assertEqual(self.data.source.wavelength_unit, 'A') self.assertEqual(self.data.source.wavelength, 6.0) self.assertEqual(self.data.detector[0].distance_unit, 'mm') self.assertEqual(self.data.detector[0].distance, 1000.0) self.assertEqual(self.data.sample.transmission, 0.5667) self.assertEqual(self.data.detector[0].beam_center_unit, 'mm') center_x = 114.58*5.08 center_y = 64.22*5.08 self.assertEqual(self.data.detector[0].beam_center.x, center_x) self.assertEqual(self.data.detector[0].beam_center.y, center_y) self.assertEqual(self.data.y_unit, 'cm^{-1}') self.assertEqual(self.data.x[0], 0.008082) self.assertEqual(self.data.x[1], 0.0275) self.assertEqual(self.data.x[2], 0.02762) self.assertEqual(self.data.x[126], 0.5828) self.assertEqual(self.data.y[0], 0.02198) self.assertEqual(self.data.y[1], 0.02201) self.assertEqual(self.data.y[2], 0.02695) self.assertEqual(self.data.y[126], 0.2958) self.assertEqual(self.data.dy[0], 0.002704) self.assertEqual(self.data.dy[1], 0.001643) self.assertEqual(self.data.dy[2], 0.002452) self.assertEqual(self.data.dy[126], 1) def test_checkdata2(self): self.assertEqual(self.data.dy[126], 1) def test_generic_loader(self): # the generic loader should work as well data = Loader().load(find("jan08002.ABS")) self.assertEqual(data[0].meta_data['loader'], "IGOR 1D") def test_usans_negative_dxl(self): data_abs = Loader().load(find("sam14_cor.ABS"))[0] data_cor = Loader().load(find("sam14_cor.txt"))[0] for i in range(0, len(data_abs.x) - 1): self.assertEqual(data_abs.x[i], data_cor.x[i]) self.assertEqual(data_abs.y[i], data_cor.y[i]) self.assertEqual(data_abs.dxl[i], -data_cor.dx[i]) self.assertTrue(data_abs.dxl[i] > 0) class DanseReaderTests(unittest.TestCase): def setUp(self): reader = DANSEReader() self.data_list = reader.read(find("MP_New.sans")) self.data = self.data_list[0] def test_checkdata(self): """ Check the data content to see whether it matches the specific file we loaded. Check the units too to see whether the Data1D defaults changed. Otherwise the tests won't pass """ self.assertEqual(len(self.data_list), 1) self.assertEqual(os.path.basename(self.data.filename), "MP_New.sans") self.assertEqual(self.data.meta_data['loader'], "DANSE") self.assertEqual(self.data.source.wavelength_unit, 'A') self.assertEqual(self.data.source.wavelength, 7.5) self.assertEqual(self.data.detector[0].distance_unit, 'mm') self.assertAlmostEqual(self.data.detector[0].distance, 5414.99, 3) self.assertEqual(self.data.detector[0].beam_center_unit, 'mm') center_x = 68.74*5.0 center_y = 64.77*5.0 self.assertEqual(self.data.detector[0].beam_center.x, center_x) self.assertEqual(self.data.detector[0].beam_center.y, center_y) self.assertEqual(self.data.I_unit, 'cm^{-1}') self.assertEqual(self.data.data[0], 1.57831) self.assertEqual(self.data.data[1], 2.70983) self.assertEqual(self.data.data[2], 3.83422) self.assertEqual(self.data.err_data[0], 1.37607) self.assertEqual(self.data.err_data[1], 1.77569) self.assertEqual(self.data.err_data[2], 2.06313) def test_generic_loader(self): # the generic loader should work as well data = Loader().load(find("MP_New.sans")) self.assertEqual(len(data), 1) self.assertEqual(data[0].meta_data['loader'], "DANSE") if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/utest_ascii.py000066400000000000000000000152211427502211700216160ustar00rootroot00000000000000""" Unit tests for the ascii (n-column) reader """ import os.path import warnings import math import unittest from sasdata.dataloader.loader import Loader from sasdata.dataloader.data_info import Data2D warnings.simplefilter("ignore") def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class ABSReaderTests(unittest.TestCase): def setUp(self): self.loader = Loader() self.f1_list = self.loader.load(find("ascii_test_1.txt")) self.f1 = self.f1_list[0] self.f2_list = self.loader.load(find("ascii_test_2.txt")) self.f2 = self.f2_list[0] self.f3_list = self.loader.load(find("ascii_test_3.txt")) self.f3 = self.f3_list[0] self.f4_list = self.loader.load(find("ascii_test_4.abs")) self.f4 = self.f4_list[0] self.f5_list = self.loader.load(find("ascii_test_5.txt")) self.f5 = self.f5_list[0] def test_checkdata(self): """ Test .ABS file loaded as ascii """ # The length of the data is 10 self.assertEqual(len(self.f1_list), 1) self.assertEqual(len(self.f2_list), 1) self.assertEqual(len(self.f3_list), 1) self.assertEqual(len(self.f4_list), 1) self.assertEqual(len(self.f5_list), 1) self.assertEqual(len(self.f1.x), 10) self.assertEqual(self.f1.x[0],0.002618) self.assertEqual(self.f1.x[9],0.0497) self.assertTrue(self.f1.x_unit == 'A^{-1}') self.assertTrue(self.f1.y_unit == 'cm^{-1}') self.assertEqual(self.f1.meta_data['loader'],"ASCII") def test_truncated_1(self): """ Test an ascii file with header and a comment line in the middle of the data section. The business rule says that we should stop reading at the first comment once the data section has started (and treat the comment as though it were the start of a footer). """ # The length of the data is 5 self.assertEqual(len(self.f2.x), 5) self.assertEqual(self.f2.x[0],0.002618) self.assertEqual(self.f2.x[4],0.02356) def test_truncated_2(self): """ Test a 6-col ascii file with header and a line with only 2 columns in the middle of the data section. The business rule says that we should stop reading at the first inconsitent line. """ # The length of the data is 5 self.assertEqual(len(self.f3.x), 5) self.assertEqual(self.f3.x[0],0.002618) self.assertEqual(self.f3.x[4],0.02356) def test_truncated_3(self): """ Test a 6-col ascii file with complex header and many lines with 2 or 2 columns in the middle of the data section. The business rule says that we should stop reading at the last line of header. """ # The length of the data is 5 self.assertEqual(len(self.f4.x), 5) self.assertEqual(self.f4.x[0],0.012654) self.assertEqual(self.f4.x[4],0.02654) def test_truncated_4(self): """ Test mix of 6-col and 2-col. Only the last 5 2-col lines should be read. """ # The length of the data is 5 self.assertEqual(len(self.f5.x), 5) self.assertEqual(self.f5.x[0],0.02879) self.assertEqual(self.f5.x[4],0.0497) def test_truncated_5(self): """ Test a 6-col ascii file with complex header where one of them has a letter and many lines with 2 or 2 columns in the middle of the data section. Will be rejected because fewer than 5 lines. """ # Test .ABS file loaded as ascii f = None try: f = self.loader.load(find("ascii_test_6.txt")) # The length of the data is 5 except: self.assertEqual(f, None) def test_nan_values(self): """ Test loading an ascii data file with nan values saved in x, y, or dy. """ f_1d = self.loader.load(find("nans_in_1d_data.dat"))[0] f_2d = self.loader.load(find("nans_in_2d_data.DAT"))[0] for i in range(0, len(f_1d.x) - 1): self.assertFalse(math.isnan(f_1d.x[i])) self.assertFalse(math.isnan(f_1d.y[i])) self.assertFalse(math.isnan(f_1d.dy[i])) self.assertTrue(isinstance(f_2d, Data2D)) f_2d.data = f_2d.data.flatten() f_2d.qx_data = f_2d.qx_data.flatten() f_2d.qy_data = f_2d.qy_data.flatten() for i in range(0, len(f_2d.data) - 1): self.assertFalse(math.isnan(f_2d.data[i])) self.assertFalse(math.isnan(f_2d.qx_data[i])) self.assertFalse(math.isnan(f_2d.qy_data[i])) def test_encoding(self): # Compare loading of utf-8 versus ansi/windows-1252 ansi = self.loader.load(find("encoding_ANSI.txt")) utf8 = self.loader.load(find("encoding_UTF_8.txt")) self._check_cl_data(ansi) self._check_cl_data(utf8) def _check_cl_data(self, data): self.assertEqual(len(data), 1) data_set = data[0] self.assertEqual(len(data_set.x), 969) self.assertEqual(len(data_set.x), len(data_set.y)) self.assertEqual(data_set.x[0], 0.000201634) self.assertEqual(data_set.y[0], 208487062.3) self.assertEqual(data_set.x_unit, 'A^{-1}') self.assertEqual(data_set.y_unit, 'cm^{-1}') def test_save_ascii(self): f_name = "test_f1_output.txt" f_name_csv = "test_f1_output.csv" # Save and load text file self.loader.save(f_name, self.f1, None) self.assertTrue(os.path.isfile(f_name)) reload = self.loader.load(f_name) f1_reload = reload[0] # Compare data from saved text file to previously loaded data self.assertEqual(len(self.f1.x), len(f1_reload.x)) self.assertEqual(len(self.f1.y), len(f1_reload.y)) self.assertEqual(self.f1.y[0], f1_reload.y[0]) # Save and load csv file self.loader.save(f_name_csv, self.f1, None) self.assertTrue(os.path.isfile(f_name_csv)) reload_csv = self.loader.load(f_name_csv) f1_reload_csv = reload_csv[0] # Compare data from saved csv file to previously loaded data self.assertEqual(len(self.f1.x), len(f1_reload_csv.x)) self.assertEqual(len(self.f1.y), len(f1_reload_csv.y)) self.assertEqual(self.f1.y[0], f1_reload_csv.y[0]) # Destroy generated files os.remove(f_name) self.assertFalse(os.path.isfile(f_name)) os.remove(f_name_csv) self.assertFalse(os.path.isfile(f_name_csv)) if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/utest_averaging.py000066400000000000000000000233661427502211700225020ustar00rootroot00000000000000import math import os import unittest import numpy as np import sasdata.dataloader.data_info as data_info from sasdata.dataloader.loader import Loader from sasdata.data_util.manipulations import (Boxavg, Boxsum, CircularAverage, Ring, SectorPhi, SectorQ, SlabX, SlabY, position_and_wavelength_to_q, reader2D_converter) def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class Averaging(unittest.TestCase): """ Test averaging manipulations on a flat distribution """ def setUp(self): """ Create a flat 2D distribution. All averaging results should return the predefined height of the distribution (1.0). """ x_0 = np.ones([100, 100]) dx_0 = np.ones([100, 100]) self.data = data_info.Data2D(data=x_0, err_data=dx_0) detector = data_info.Detector() detector.distance = 1000.0 # mm detector.pixel_size.x = 1.0 # mm detector.pixel_size.y = 1.0 # mm # center in pixel position = (len(x_0)-1)/2 detector.beam_center.x = (len(x_0) - 1) / 2 # pixel number detector.beam_center.y = (len(x_0) - 1) / 2 # pixel number self.data.detector.append(detector) source = data_info.Source() source.wavelength = 10.0 # A self.data.source = source # get_q(dx, dy, det_dist, wavelength) where units are mm,mm,mm,and A # respectively. self.qmin = position_and_wavelength_to_q(1.0, 1.0, detector.distance, source.wavelength) self.qmax = position_and_wavelength_to_q(49.5, 49.5, detector.distance, source.wavelength) self.qstep = len(x_0) x = np.linspace(start=-1 * self.qmax, stop=self.qmax, num=self.qstep, endpoint=True) y = np.linspace(start=-1 * self.qmax, stop=self.qmax, num=self.qstep, endpoint=True) self.data.x_bins = x self.data.y_bins = y self.data = reader2D_converter(self.data) def test_ring_flat_distribution(self): """ Test ring averaging """ r = Ring(r_min=2 * self.qmin, r_max=5 * self.qmin, center_x=self.data.detector[0].beam_center.x, center_y=self.data.detector[0].beam_center.y) r.nbins_phi = 20 o = r(self.data) for i in range(20): self.assertEqual(o.y[i], 1.0) def test_sectorphi_full(self): """ Test sector averaging """ r = SectorPhi(r_min=self.qmin, r_max=3 * self.qmin, phi_min=0, phi_max=math.pi * 2.0) r.nbins_phi = 20 o = r(self.data) for i in range(7): self.assertEqual(o.y[i], 1.0) def test_sectorphi_partial(self): """ """ phi_max = math.pi * 1.5 r = SectorPhi(r_min=self.qmin, r_max=3 * self.qmin, phi_min=0, phi_max=phi_max) self.assertEqual(r.phi_max, phi_max) r.nbins_phi = 20 o = r(self.data) self.assertEqual(r.phi_max, phi_max) for i in range(17): self.assertEqual(o.y[i], 1.0) class DataInfoTests(unittest.TestCase): def setUp(self): filepath = find('MAR07232_rest.h5') self.data_list = Loader().load(filepath) self.data = self.data_list[0] def test_ring(self): """ Test ring averaging """ r = Ring(r_min=.005, r_max=.01, center_x=self.data.detector[0].beam_center.x, center_y=self.data.detector[0].beam_center.y, nbins=20) ##r.nbins_phi = 20 o = r(self.data) filepath = find('ring_testdata.txt') answer_list = Loader().load(filepath) answer = answer_list[0] self.assertEqual(len(answer_list), 1) for i in range(r.nbins_phi - 1): self.assertAlmostEqual(o.x[i + 1], answer.x[i], 4) self.assertAlmostEqual(o.y[i + 1], answer.y[i], 4) self.assertAlmostEqual(o.dy[i + 1], answer.dy[i], 4) def test_circularavg(self): """ Test circular averaging The test data was not generated by IGOR. """ r = CircularAverage(r_min=.00, r_max=.025, bin_width=0.0003) r.nbins_phi = 20 o = r(self.data) filepath = find('avg_testdata.txt') answer = Loader().load(filepath)[0] for i in range(r.nbins_phi): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_box(self): """ Test circular averaging The test data was not generated by IGOR. """ r = Boxsum(x_min=.01, x_max=.015, y_min=0.01, y_max=0.015) s, ds, npoints = r(self.data) self.assertAlmostEqual(s, 34.278990899999997, 4) self.assertAlmostEqual(ds, 8.237259999538685, 4) self.assertAlmostEqual(npoints, 324.0000, 4) r = Boxavg(x_min=.01, x_max=.015, y_min=0.01, y_max=0.015) s, ds = r(self.data) self.assertAlmostEqual(s, 0.10579935462962962, 4) self.assertAlmostEqual(ds, 0.02542364197388483, 4) def test_slabX(self): """ Test slab in X The test data was not generated by IGOR. """ r = SlabX(x_min=-.01, x_max=.01, y_min=-0.0002, y_max=0.0002, bin_width=0.0004) r.fold = False o = r(self.data) filepath = find('slabx_testdata.txt') answer = Loader().load(filepath)[0] for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_slabY(self): """ Test slab in Y The test data was not generated by IGOR. """ r = SlabY(x_min=.005, x_max=.01, y_min=- 0.01, y_max=0.01, bin_width=0.0004) r.fold = False o = r(self.data) filepath = find('slaby_testdata.txt') answer = Loader().load(filepath)[0] for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_sectorphi_full(self): """ Test sector averaging I(phi) When considering the whole azimuthal range (2pi), the answer should be the same as ring averaging. The test data was not generated by IGOR. """ nbins = 19 phi_min = math.pi / (nbins + 1) phi_max = math.pi * 2 - phi_min r = SectorPhi(r_min=.005, r_max=.01, phi_min=phi_min, phi_max=phi_max, nbins=nbins) o = r(self.data) filepath = find('ring_testdata.txt') answer = Loader().load(filepath)[0] for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_sectorphi_quarter(self): """ Test sector averaging I(phi) The test data was not generated by IGOR. """ r = SectorPhi(r_min=.005, r_max=.01, phi_min=0, phi_max=math.pi / 2.0) r.nbins_phi = 20 o = r(self.data) filepath = find('sectorphi_testdata.txt') answer = Loader().load(filepath)[0] for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_sectorq_full(self): """ Test sector averaging I(q) The test data was not generated by IGOR. """ r = SectorQ(r_min=.005, r_max=.01, phi_min=0, phi_max=math.pi / 2.0) r.nbins_phi = 20 o = r(self.data) filepath = find('sectorq_testdata.txt') answer = Loader().load(filepath)[0] for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], answer.x[i], 4) self.assertAlmostEqual(o.y[i], answer.y[i], 4) self.assertAlmostEqual(o.dy[i], answer.dy[i], 4) def test_sectorq_log(self): """ Test sector averaging I(q) The test data was not generated by IGOR. """ r = SectorQ(r_min=.005, r_max=.01, phi_min=0, phi_max=math.pi / 2.0, base=10) r.nbins_phi = 20 o = r(self.data) expected_binning = np.logspace(np.log10(0.005), np.log10(0.01), 20, base=10) for i in range(len(o.x)): self.assertAlmostEqual(o.x[i], expected_binning[i], 3) # TODO: Test for Y values (o.y) # print len(self.data.x_bins) # print len(self.data.y_bins) # print self.data.q_data.shape # data_to_bin = np.array(self.data.q_data) # data_to_bin = data_to_bin.reshape(len(self.data.x_bins), len(self.data.y_bins)) # H, xedges, yedges, binnumber = binned_statistic_2d(self.data.x_bins, self.data.y_bins, data_to_bin, # bins=[[0, math.pi / 2.0], expected_binning], statistic='mean') # xedges_width = (xedges[1] - xedges[0]) # xedges_center = xedges[1:] - xedges_width / 2 # yedges_width = (yedges[1] - yedges[0]) # yedges_center = yedges[1:] - yedges_width / 2 # print H.flatten().shape # print o.y.shape if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/utest_cansas.py000066400000000000000000000626221427502211700220050ustar00rootroot00000000000000""" Unit tests for the new recursive cansas reader """ import os import sys import unittest import logging import warnings from io import StringIO from lxml import etree from lxml.etree import XMLSyntaxError from xml.dom import minidom from sasdata.dataloader.filereader import decode from sasdata.dataloader.loader import Loader from sasdata.dataloader.data_info import Data1D, Data2D from sasdata.dataloader.readers.xml_reader import XMLreader from sasdata.dataloader.readers.cansas_reader import Reader from sasdata.dataloader.readers.cansas_constants import CansasConstants logger = logging.getLogger(__name__) warnings.simplefilter("ignore") CANSAS_FORMAT = CansasConstants.CANSAS_FORMAT CANSAS_NS = CansasConstants.CANSAS_NS def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class cansas_reader_xml(unittest.TestCase): def setUp(self): self.loader = Loader() self.cansas_reader = Reader() self.xml_reader = XMLreader() self.xml_valid = find("cansas_test_modified.xml") self.xml_invalid = find("cansas_test.xml") self.cansas1d_badunits = find("cansas1d_badunits.xml") self.cansas1d = find("cansas1d.xml") self.cansas1d_slit = find("cansas1d_slit.xml") self.cansas1d_units = find("cansas1d_units.xml") self.cansas1d_notitle = find("cansas1d_notitle.xml") self.datafile_multiplesasdata_multiplesasentry = find("cansas_xml_multisasentry_multisasdata.xml") self.isis_1_0 = find("ISIS_1_0.xml") self.isis_1_1 = find("ISIS_1_1.xml") self.isis_1_1_notrans = find("ISIS_1_1_notrans.xml") self.isis_1_1_doubletrans = find("ISIS_1_1_doubletrans.xml") self.schema_1_0 = find("cansas1d_v1_0.xsd") self.schema_1_1 = find("cansas1d_v1_1.xsd") self.write_1_0_filename = find("isis_1_0_write_test.xml") self.write_1_1_filename = find("isis_1_1_write_test.xml") self.write_filename = find("write_test.xml") def get_number_of_entries(self, dictionary, name, i): if dictionary.get(name) is not None: i += 1 name = name.split("_")[0] name += "_{0}".format(i) name = self.get_number_of_entries(dictionary, name, i) return name def test_invalid_xml(self): """ Should fail gracefully and send a message to logger.info() """ invalid = StringIO('') self.assertRaises(XMLSyntaxError, lambda: XMLreader(invalid)) def test_xml_validate(self): string = "\n" string += "\t\n" string += "\t\n" string += "\t\t\n" string += "\t\t\t\n" string += "\t\t\n" string += "\t\n" string += "" f = StringIO(string) xmlschema_doc = etree.parse(f) xmlschema = etree.XMLSchema(xmlschema_doc) valid = etree.parse(StringIO('')) invalid = etree.parse(StringIO('')) self.assertTrue(xmlschema.validate(valid)) self.assertFalse(xmlschema.validate(invalid)) def test_real_xml(self): self.xml_reader.set_xml_file(self.xml_valid) self.xml_reader.set_schema(self.schema_1_0) self.assertTrue(self.xml_reader.validate_xml()) def _check_data(self, data): self.assertTrue(data.title == "TK49 c10_SANS") self.assertTrue(data.x.size == 138) self.assertTrue(len(data.meta_data) == 3) self.assertTrue(data.detector[0].distance_unit == "mm") self.assertTrue(data.detector[1].distance_unit == "mm") self.assertTrue(data.detector[0].name == "HAB") self.assertTrue(data.detector[1].name == "main-detector-bank") self.assertTrue(data.detector[0].distance == 575.0) self.assertAlmostEqual(data.detector[1].distance, 4145.02) self.assertTrue(data.process[0].name == "Mantid generated CanSAS1D XML") self.assertTrue(data.meta_data["xmlpreprocess"] is not None) def _check_data_1_1(self, data): spectrum = data.trans_spectrum[0] self.assertTrue(len(spectrum.wavelength) == 138) def test_cansas_xml(self): self.xml_reader.set_xml_file(self.isis_1_1) self.xml_reader.set_schema(self.schema_1_1) self.xml_reader.set_processing_instructions() self.assertTrue(self.xml_reader.validate_xml()) dataloader = self.loader.load(self.isis_1_1) cansasreader = self.cansas_reader.read(self.isis_1_1) for i in range(len(dataloader)): self._check_data(dataloader[i]) self._check_data_1_1(dataloader[i]) self._check_data(cansasreader[i]) self._check_data_1_1(cansasreader[i]) self.loader.save(self.write_1_1_filename, dataloader[i], None) reader2 = Loader() self.assertTrue(os.path.isfile(self.write_1_1_filename)) return_data = reader2.load(self.write_1_1_filename) written_data = return_data[0] self._check_data(written_data) if os.path.isfile(self.write_1_1_filename): os.remove(self.write_1_1_filename) def test_double_trans_spectra(self): self.xml_reader.set_xml_file(self.isis_1_1_doubletrans) self.xml_reader.set_schema(self.schema_1_1) self.assertTrue(self.xml_reader.validate_xml()) data = self.loader.load(self.isis_1_1_doubletrans) for item in data: self._check_data(item) def test_entry_name_recurse(self): test_values = [1,2,3,4,5,6] base_key = "key" d = {} for value in test_values: new_key = self.get_number_of_entries(d, base_key, i = 0) d[new_key] = value self.assertTrue(len(d) == 6) def test_load_cansas_file(self): reader1 = XMLreader(self.xml_valid, self.schema_1_0) self.assertTrue(reader1.validate_xml()) reader2 = XMLreader(self.xml_invalid, self.schema_1_0) self.assertFalse(reader2.validate_xml()) reader3 = XMLreader(self.xml_valid, self.schema_1_1) self.assertFalse(reader3.validate_xml()) reader4 = XMLreader(self.xml_invalid, self.schema_1_1) self.assertFalse(reader4.validate_xml()) reader5 = XMLreader(self.isis_1_0, self.schema_1_0) self.assertTrue(reader5.validate_xml()) reader6 = XMLreader(self.isis_1_1, self.schema_1_1) self.assertTrue(reader6.validate_xml()) reader7 = XMLreader(self.isis_1_1, self.schema_1_0) self.assertFalse(reader7.validate_xml()) def test_invalid_cansas(self): list = self.loader.load(self.cansas1d_notitle) data = list[0] self.assertTrue(data.x.size == 2) self.assertTrue(len(data.meta_data) == 2) self.assertTrue(len(data.errors) == 1) self.assertTrue(data.detector[0].distance_unit == "mm") self.assertTrue(data.detector[0].name == "fictional hybrid") self.assertTrue(data.detector[0].distance == 4150) def test_old_cansas_files(self): self.xml_reader.set_xml_file(self.cansas1d) self.xml_reader.set_schema(self.schema_1_0) self.assertTrue(self.xml_reader.validate_xml()) self.loader.load(self.cansas1d) reader2 = XMLreader(self.cansas1d_units, self.schema_1_0) self.assertTrue(reader2.validate_xml()) reader3 = XMLreader(self.cansas1d_badunits, self.schema_1_0) self.assertTrue(reader3.validate_xml()) reader4 = XMLreader(self.cansas1d_slit, self.schema_1_0) self.assertTrue(reader4.validate_xml()) def test_save_cansas_v1_0(self): xmlreader = XMLreader(self.isis_1_0, self.schema_1_0) self.assertTrue(xmlreader.validate_xml()) dataloader = self.loader.load(self.isis_1_0) cansasreader = self.cansas_reader.read(self.isis_1_0) for i in range(len(dataloader)): self._check_data(dataloader[i]) self._check_data(cansasreader[i]) self.loader.save(self.write_1_0_filename, dataloader[i], None) reader2 = Reader() self.assertTrue(os.path.isfile(self.write_1_0_filename)) return_data = reader2.read(self.write_1_0_filename) written_data = return_data[0] xmlreader = XMLreader(self.write_1_0_filename, self.schema_1_0) self.assertTrue(xmlreader.validate_xml()) self.assertEqual(len(written_data.notes), 1) self._check_data(written_data) if os.path.isfile(self.write_1_0_filename): os.remove(self.write_1_0_filename) def test_processing_instructions(self): self.xml_reader.set_xml_file(self.isis_1_1) self.xml_reader.set_schema(self.schema_1_1) if self.xml_reader.validate_xml(): # find the processing instructions and make into a dictionary dic = self.get_processing_instructions(self.xml_reader) self.assertEqual(dic, {'xml-stylesheet': 'type="text/xsl" href="cansas1d.xsl" '}) xml = "" xmldoc = minidom.parseString(xml) # take the processing instructions and put them back in xmldoc = self.set_processing_instructions(xmldoc, dic) xmldoc.toprettyxml() def set_processing_instructions(self, minidom_object, dic): xmlroot = minidom_object.firstChild for item in dic: pi = minidom_object.createProcessingInstruction(item, dic[item]) minidom_object.insertBefore(pi, xmlroot) return minidom_object def get_processing_instructions(self, xml_reader_object): dict = {} pi = xml_reader_object.xmlroot.getprevious() i = 0 while pi is not None: attr = {} pi_name = "" pi_string = decode(etree.tostring(pi)) if isinstance(pi_string, str): pi_string = pi_string.replace("", "") split = pi_string.split(" ", 1) pi_name = split[0] attr = split[1] dict[pi_name] = attr pi = pi.getprevious() return dict def test_generic_loader(self): # the generic loader should work as well data = self.loader.load(find("cansas1d.xml")) self.assertEqual(len(data), 1) self.assertEqual(data[0].meta_data['loader'], "CanSAS XML 1D") def test_cansas_checkdata(self): self.data_list = self.loader.load(find("cansas1d.xml")) self.data = self.data_list[0] self.assertEqual(self.data.filename, "cansas1d.xml") self._checkdata() def _checkdata(self): """ Check the data content to see whether it matches the specific file we loaded. Check the units too to see whether the Data1D defaults changed. Otherwise the tests won't pass """ self.assertEqual(len(self.data_list), 1) self.assertEqual(self.data.run[0], "1234") self.assertEqual(self.data.meta_data['loader'], "CanSAS XML 1D") # Data self.assertEqual(len(self.data.x), 2) self.assertEqual(self.data.x_unit, 'A^{-1}') self.assertEqual(self.data.y_unit, 'cm^{-1}') self.assertAlmostEqual(self.data.x[0], 0.02, 6) self.assertAlmostEqual(self.data.y[0], 1000, 6) self.assertAlmostEqual(self.data.dx[0], 0.01, 6) self.assertAlmostEqual(self.data.dy[0], 3, 6) self.assertAlmostEqual(self.data.x[1], 0.03, 6) self.assertAlmostEqual(self.data.y[1], 1001.0) self.assertAlmostEqual(self.data.dx[1], 0.02, 6) self.assertAlmostEqual(self.data.dy[1], 4, 6) self.assertEqual(self.data.run_name['1234'], 'run name') self.assertEqual(self.data.title, "Test title") # Sample info self.assertEqual(self.data.sample.ID, "SI600-new-long") self.assertEqual(self.data.sample.name, "my sample") self.assertEqual(self.data.sample.thickness_unit, 'mm') self.assertAlmostEqual(self.data.sample.thickness, 1.03) self.assertAlmostEqual(self.data.sample.transmission, 0.327) self.assertEqual(self.data.sample.temperature_unit, 'C') self.assertEqual(self.data.sample.temperature, 0) self.assertEqual(self.data.sample.position_unit, 'mm') self.assertEqual(self.data.sample.position.x, 10) self.assertEqual(self.data.sample.position.y, 0) self.assertEqual(self.data.sample.orientation_unit, 'degree') self.assertAlmostEqual(self.data.sample.orientation.x, 22.5, 6) self.assertAlmostEqual(self.data.sample.orientation.y, 0.02, 6) self.assertEqual(self.data.sample.details[0], "http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720") self.assertEqual(self.data.sample.details[1], "Some text here") # Instrument info self.assertEqual(self.data.instrument, "canSAS instrument") # Source self.assertEqual(self.data.source.radiation, "neutron") self.assertEqual(self.data.source.beam_size_unit, "mm") self.assertEqual(self.data.source.beam_size_name, "bm") self.assertEqual(self.data.source.beam_size.x, 12) self.assertEqual(self.data.source.beam_size.y, 13) self.assertEqual(self.data.source.beam_shape, "disc") self.assertEqual(self.data.source.wavelength_unit, "A") self.assertEqual(self.data.source.wavelength, 6) self.assertEqual(self.data.source.wavelength_max_unit, "nm") self.assertAlmostEqual(self.data.source.wavelength_max, 1.0) self.assertEqual(self.data.source.wavelength_min_unit, "nm") self.assertAlmostEqual(self.data.source.wavelength_min, 0.22) self.assertEqual(self.data.source.wavelength_spread_unit, "percent") self.assertEqual(self.data.source.wavelength_spread, 14.3) # Collimation _found1 = False _found2 = False self.assertEqual(self.data.collimation[0].length, 123.) self.assertEqual(self.data.collimation[0].name, 'test coll name') for item in self.data.collimation[0].aperture: self.assertEqual(item.size_unit,'mm') self.assertEqual(item.distance_unit,'mm') if item.size.x == 50 \ and item.distance == 11000.0 \ and item.name == 'source' \ and item.type == 'radius': _found1 = True elif item.size.x == 1.0 \ and item.name == 'sample' \ and item.type == 'radius': _found2 = True if not _found1 or not _found2: raise RuntimeError("Could not find all data %s %s" % (_found1, _found2)) # Detector self.assertEqual(self.data.detector[0].name, "fictional hybrid") self.assertEqual(self.data.detector[0].distance_unit, "mm") self.assertEqual(self.data.detector[0].distance, 4150) self.assertEqual(self.data.detector[0].orientation_unit, "degree") self.assertAlmostEqual(self.data.detector[0].orientation.x, 1.0, 6) self.assertEqual(self.data.detector[0].orientation.y, 0.0) self.assertEqual(self.data.detector[0].orientation.z, 0.0) self.assertEqual(self.data.detector[0].offset_unit, "m") self.assertEqual(self.data.detector[0].offset.x, .001) self.assertEqual(self.data.detector[0].offset.y, .002) self.assertEqual(self.data.detector[0].offset.z, None) self.assertEqual(self.data.detector[0].beam_center_unit, "mm") self.assertEqual(self.data.detector[0].beam_center.x, 322.64) self.assertEqual(self.data.detector[0].beam_center.y, 327.68) self.assertEqual(self.data.detector[0].beam_center.z, None) self.assertEqual(self.data.detector[0].pixel_size_unit, "mm") self.assertEqual(self.data.detector[0].pixel_size.x, 5) self.assertEqual(self.data.detector[0].pixel_size.y, 5) self.assertEqual(self.data.detector[0].pixel_size.z, None) # Process _found_term1 = False _found_term2 = False for item in self.data.process: self.assertTrue(item.name in ['NCNR-IGOR', 'spol']) self.assertTrue(item.date in ['04-Sep-2007 18:35:02', '03-SEP-2006 11:42:47']) for t in item.term: if (t['name'] == "ABS:DSTAND" and t['unit'] == 'mm' and float(t['value']) == 1.0): _found_term2 = True elif (t['name'] == "radialstep" and t['unit'] == 'mm' and float(t['value']) == 10.0): _found_term1 = True if not _found_term1 or not _found_term2: raise RuntimeError("Could not find all process terms %s %s" % (_found_term1, _found_term2)) def test_writer(self): filename = "write_test.xml" data_list = self.loader.load(self.cansas1d) data = data_list[0] self.cansas_reader.write(self.write_filename, data) self.data_list = self.loader.load(self.write_filename) self.data = self.data_list[0] self.assertEqual(len(self.data_list), 1) self.assertEqual(len(self.data_list), len(self.data_list)) self.assertEqual(self.data.filename, filename) self._checkdata() if os.path.isfile(self.write_filename): os.remove(self.write_filename) def test_units(self): """ Check units. Note that not all units are available. """ filename = "cansas1d_units.xml" self.data_list = self.cansas_reader.read(find(filename)) self.data = self.data_list[0] self.assertEqual(len(self.data_list), 1) self.assertEqual(self.data.filename, filename) self._checkdata() def test_badunits(self): """ Check units. Note that not all units are available. """ filename = "cansas1d_badunits.xml" self.data_list = self.cansas_reader.read(find(filename)) self.data = self.data_list[0] self.assertEqual(len(self.data_list), 1) self.assertEqual(self.data.filename, filename) # The followed should not have been loaded self.assertAlmostEqual(self.data.sample.thickness, 0.00103) # This one should self.assertAlmostEqual(self.data.sample.transmission, 0.327) self.assertEqual(self.data.meta_data['loader'], "CanSAS XML 1D") self.assertEqual(len(self.data.errors), 0) def test_slits(self): """ Check slit data """ filename = "cansas1d_slit.xml" self.data_list = self.cansas_reader.read(find(filename)) self.data = self.data_list[0] self.assertEqual(len(self.data_list), 1) self.assertEqual(self.data.filename, filename) self.assertEqual(self.data.run[0], "1234") # Data self.assertEqual(len(self.data.x), 2) self.assertEqual(self.data.x_unit, 'A^{-1}') self.assertEqual(self.data.y_unit, 'cm^{-1}') self.assertEqual(self.data.x[0], 0.02) self.assertEqual(self.data.y[0], 1000) self.assertEqual(self.data.dxl[0], 0.005) self.assertEqual(self.data.dxw[0], 0.001) self.assertEqual(self.data.dy[0], 3) self.assertEqual(self.data.x[1], 0.03) self.assertAlmostEqual(self.data.y[1], 1001.0) self.assertEqual(self.data.dxl[1], 0.005) self.assertEqual(self.data.dxw[1], 0.001) self.assertEqual(self.data.dy[1], 4) self.assertEqual(self.data.run_name['1234'], 'run name') self.assertEqual(self.data.title, "Test title") def test_multiple_sasentries_multiplesasdatas(self): self.data = self.loader.load(self.datafile_multiplesasdata_multiplesasentry) self.assertTrue(len(self.data) == 19) for data in self.data: self.assertEqual(find(data.filename), self.datafile_multiplesasdata_multiplesasentry) self.assertEqual(data.source.radiation, 'neutron') self.assertAlmostEqual(data.source.wavelength, 8.5) self.assertEqual(data.source.wavelength_unit, 'A') self.assertAlmostEqual(data.source.wavelength_spread, 25) data_len = len(data.x) self.assertTrue(data_len >= 69) self.assertTrue(data_len <= 77) class cansas_reader_hdf5(unittest.TestCase): def setUp(self): self.loader = Loader() self.datafile_basic = find("simpleexamplefile.h5") self.datafile_nodi = find("x25000_no_di.h5") self.datafile_multiplesasentry = find( "nxcansas_1Dand2D_multisasentry.h5") self.datafile_multiplesasdata = find("nxcansas_1Dand2D_multisasdata.h5") self.datafile_multiplesasdata_multiplesasentry = find( "nxcansas_1Dand2D_multisasentry_multisasdata.h5") self.datafile_multiple_frames = find("multiframe_1d.nxs") def test_real_data(self): self.data = self.loader.load(self.datafile_basic) self._check_example_data(self.data[0]) def test_multi_frame_data(self): self.data = self.loader.load(self.datafile_multiple_frames) self.assertEqual(len(self.data), 120) for frame in self.data: self.assertTrue(isinstance(frame, Data1D)) self.assertEqual(frame.run[0], 'BBAA_processed_180309_132658') self.assertEqual(frame.run[0], frame.title) self.assertEqual(len(frame.y), 1617) def test_no_di(self): self.data = self.loader.load(self.datafile_nodi) self.assertTrue(self.data is not None) self.assertTrue(len(self.data) == 1) dataset = self.data[0] self.assertTrue(dataset.err_data is None) self.assertTrue(dataset.q_data is not None) def test_multiple_sasentries(self): self.data = self.loader.load(self.datafile_multiplesasentry) self.assertTrue(len(self.data) == 2) self._check_multiple_data(self.data[0]) self._check_multiple_data(self.data[1]) if isinstance(self.data[0], Data1D): self._check_1d_data(self.data[0]) self._check_2d_data(self.data[1]) else: self._check_1d_data(self.data[1]) self._check_2d_data(self.data[0]) def test_multiple_sasdatas(self): self.data = self.loader.load(self.datafile_multiplesasdata) self.assertTrue(len(self.data) == 2) self._check_multiple_data(self.data[0]) self._check_multiple_data(self.data[1]) if isinstance(self.data[0], Data1D): self._check_1d_data(self.data[0]) self._check_2d_data(self.data[1]) else: self._check_1d_data(self.data[1]) self._check_2d_data(self.data[0]) def test_multiple_sasentries_multiplesasdatas(self): self.data = self.loader.load( self.datafile_multiplesasdata_multiplesasentry) self.assertTrue(len(self.data) == 4) self._check_multiple_data(self.data[0]) self._check_multiple_data(self.data[1]) self._check_multiple_data(self.data[2]) self._check_multiple_data(self.data[3]) for data in self.data: if isinstance(data, Data1D): self._check_1d_data(data) else: self._check_2d_data(data) def _check_multiple_data(self, data): self.assertEqual(data.title, "MH4_5deg_16T_SLOW") self.assertEqual(data.run[0], '33837') self.assertEqual(len(data.run), 1) self.assertEqual(data.instrument, "SANS2D") self.assertEqual(data.source.radiation, "Spallation Neutron Source") self.assertEqual(len(data.detector), 2) self.assertTrue(data.detector[0].name == "rear-detector" or data.detector[1].name == "rear-detector") self.assertTrue(data.detector[0].name == "front-detector" or data.detector[1].name == "front-detector") self.assertAlmostEqual(data.detector[0].distance + data.detector[1].distance, 7230.54, 2) self.assertEqual(data.detector[0].distance_unit, 'mm') self.assertEqual(len(data.trans_spectrum), 1) def _check_1d_data(self, data): self.assertEqual(len(data.x), 66) self.assertEqual(len(data.x), len(data.y)) self.assertAlmostEqual(data.dy[10], 0.207214) self.assertAlmostEqual(data.y[10], 24.1939) self.assertAlmostEqual(data.x[10], 0.00898113) def _check_2d_data(self, data): self.assertTrue(isinstance(data, Data2D)) self.assertEqual(len(data.q_data), 150*150) self.assertEqual(len(data.q_data), len(data.data)) self.assertAlmostEqual(data.err_data[10], 0.186723989418) self.assertAlmostEqual(data.data[10], 0.465181) self.assertAlmostEqual(data.qx_data[10], -0.129) self.assertAlmostEqual(data.qy_data[10], -0.149) def _check_example_data(self, data): self.assertEqual(data.title, "") self.assertEqual(data.x.size, 100) self.assertEqual(data._xunit, "A^{-1}") self.assertEqual(data._yunit, "cm^{-1}") self.assertEqual(data.y.size, 100) self.assertAlmostEqual(data.y[40], 0.952749011516985) self.assertAlmostEqual(data.x[40], 0.3834415188257777) self.assertAlmostEqual(len(data.meta_data), 0) if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/utest_extension_registry.py000066400000000000000000000056241427502211700245000ustar00rootroot00000000000000""" Unit tests for loading data files using the extension registry """ import logging import unittest import os import shutil import numpy as np from sasdata.dataloader.loader import Registry as Loader logger = logging.getLogger(__name__) def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class ExtensionRegistryTests(unittest.TestCase): def setUp(self): self.valid_file = find("valid_cansas_xml.xml") self.valid_file_wrong_known_ext = find("valid_cansas_xml.txt") self.valid_file_wrong_unknown_ext = find("valid_cansas_xml.xyz") shutil.copyfile(self.valid_file, self.valid_file_wrong_known_ext) shutil.copyfile(self.valid_file, self.valid_file_wrong_unknown_ext) self.invalid_file = find("cansas1d_notitle.xml") self.loader = Loader() def test_wrong_known_ext(self): """ Load a valid CanSAS XML file that has the extension '.txt', which is in the extension registry. Compare the results to loading the same file with the extension '.xml' """ correct = self.loader.load(self.valid_file) wrong_ext = self.loader.load(self.valid_file_wrong_known_ext) self.assertEqual(len(correct), 1) self.assertEqual(len(wrong_ext), 1) correct = correct[0] wrong_ext = wrong_ext[0] self.assertTrue(np.all(correct.x == wrong_ext.x)) self.assertTrue(np.all(correct.y == wrong_ext.y)) self.assertTrue(np.all(correct.dy == wrong_ext.dy)) def test_wrong_unknown_ext(self): """ Load a valid CanSAS XML file that has the extension '.xyz', which isn't in the extension registry. Compare the results to loading the same file with the extension '.xml' """ correct = self.loader.load(self.valid_file) wrong_ext = self.loader.load(self.valid_file_wrong_unknown_ext) self.assertEqual(len(correct), 1) self.assertEqual(len(wrong_ext), 1) correct = correct[0] wrong_ext = wrong_ext[0] self.assertTrue(np.all(correct.x == wrong_ext.x)) self.assertTrue(np.all(correct.y == wrong_ext.y)) self.assertTrue(np.all(correct.dy == wrong_ext.dy)) def test_data_reader_exception(self): """ Load a CanSAS XML file that doesn't meet the schema, and check errors are set correctly """ data = self.loader.load(self.invalid_file) self.assertEqual(len(data), 1) data = data[0] self.assertEqual(len(data.errors), 1) err_msg = data.errors[0] self.assertTrue("does not fully meet the CanSAS v1.x specification" in err_msg) def tearDown(self): if os.path.isfile(self.valid_file_wrong_known_ext): os.remove(self.valid_file_wrong_known_ext) if os.path.isfile(self.valid_file_wrong_unknown_ext): os.remove(self.valid_file_wrong_unknown_ext) sasdata-0.8.1/test/sasdataloader/utest_generic_file_reader_class.py000066400000000000000000000070241427502211700256520ustar00rootroot00000000000000""" Unit tests for the generic file reader class """ import os import unittest import logging import numpy as np from sasdata.dataloader.data_info import DataInfo, plottable_1D, Data1D from sasdata.dataloader.loader import Loader from sasdata.data_util.loader_exceptions import NoKnownLoaderException from sasdata.dataloader.filereader import FileReader logger = logging.getLogger(__name__) def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class GenericFileReaderTests(unittest.TestCase): def setUp(self): self.reader = TestFileReader() self.bad_file = find("ACB123.txt") self.good_file = find("123ABC.txt") self.generic_reader = Loader() self.deprecated_file_type = find("FEB18012.ASC") def test_bad_file_path(self): self.assertRaises(NoKnownLoaderException, self.reader.read, self.bad_file) def test_good_file_path(self): f = open(self.good_file, 'w') f.write('123ABC exists!') f.close() output = self.reader.read(self.good_file) self.assertEqual(len(output), 1) self.assertEqual(output[0].meta_data["blah"], '123ABC exists!') def test_old_file_types(self): f = self.generic_reader.load(self.deprecated_file_type) last_f = f[0] if hasattr(last_f, "errors"): self.assertEqual(len(last_f.errors), 1) else: self.fail("Errors did not propogate to the file properly.") def test_same_file_unknown_extensions(self): # Five files, all with the same content, but different file extensions no_ext = find("TestExtensions") not_xml = find("TestExtensions.notxml") # Deprecated extensions asc_dep = find("TestExtensions.asc") nxs_dep = find("TestExtensions.nxs") # Native extension as a baseline xml_native = find("TestExtensions.xml") # Load the files and check contents no_ext_load = self.generic_reader.load(no_ext) asc_load = self.generic_reader.load(asc_dep) nxs_load = self.generic_reader.load(nxs_dep) not_xml_load = self.generic_reader.load(not_xml) xml_load = self.generic_reader.load(xml_native) self.check_unknown_extension(no_ext_load[0]) self.check_unknown_extension(asc_load[0]) self.check_unknown_extension(nxs_load[0]) self.check_unknown_extension(not_xml_load[0]) self.check_unknown_extension(xml_load[0]) # Be sure the deprecation warning is passed with the file self.assertEqual(len(asc_load[0].errors), 1) self.assertEqual(len(nxs_load[0].errors), 0) def check_unknown_extension(self, data): self.assertTrue(isinstance(data, Data1D)) self.assertEqual(len(data.x), 138) self.assertEqual(data.sample.ID, "TK49 c10_SANS") self.assertEqual(data.meta_data["loader"], "CanSAS XML 1D") def tearDown(self): if os.path.isfile(self.bad_file): os.remove(self.bad_file) if os.path.isfile(self.good_file): os.remove(self.good_file) class TestFileReader(FileReader): def get_file_contents(self): """ Reader specific class to access the contents of the file All reader classes that inherit from FileReader must implement """ x = np.zeros(0) y = np.zeros(0) self.current_dataset = plottable_1D(x,y) self.current_datainfo = DataInfo() self.current_datainfo.meta_data["blah"] = self.nextline() self.send_to_output() sasdata-0.8.1/test/sasdataloader/utest_red2d_reader.py000066400000000000000000000034721427502211700230550ustar00rootroot00000000000000""" Unit tests for the red2d (3-7-column) reader """ import warnings import unittest import os.path from sasdata.dataloader.loader import Loader warnings.simplefilter("ignore") def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) BASE_POINTS = 36864 BASE_LENGTH = 192 class DatReaderTests(unittest.TestCase): def setUp(self): self.loader = Loader() self.data_list = self.loader.load(find("detector_square.dat")) # Same data file, but first 15 rows of data removed self.data_list_rectangle = self.loader.load( find("detector_rectangular.DAT")) def _check_common_data(self, f, removed): self.assertEqual(len(f.qx_data), BASE_POINTS - removed * BASE_LENGTH) self.assertEqual(len(f.x_bins) + removed, len(f.y_bins)) self.assertEqual(len(f.x_bins), 192 - removed) self.assertEqual(f.qx_data[len(f.qx_data) - 1], 0.2908819) self.assertEqual(f.Q_unit, 'A^{-1}') self.assertEqual(f.I_unit, 'cm^{-1}') self.assertEqual(f.meta_data['loader'], "IGOR/DAT 2D Q_map") def test_check_square_data(self): """ Test square detector data loaded by the .DAT reader """ f = self.data_list[0] # The length of the data is 10 self.assertEqual(len(self.data_list), 1) self.assertEqual(f.qx_data[0],-0.03573497) self._check_common_data(f, 0) def test_check_rectangular_data(self): """ Test rectangular detector data loaded by the .DAT reader """ f = self.data_list_rectangle[0] self.assertEqual(len(self.data_list_rectangle), 1) self.assertEqual(f.qx_data[0], -0.009160664) self._check_common_data(f, 15) if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/sasdataloader/utest_sesans.py000066400000000000000000000065521427502211700220310ustar00rootroot00000000000000""" Unit tests for the SESANS .ses reader """ import os.path import unittest from sasdata.data_util.loader_exceptions import FileContentsException from sasdata.dataloader.readers.sesans_reader import Reader from sasdata.dataloader.loader import Loader def find(filename): return os.path.join(os.path.dirname(__file__), 'sesans_data', filename) class sesans_reader(unittest.TestCase): def setUp(self): reader = Reader() self.loader = reader.read def test_full_load(self): """ Test .SES in the full loader to make sure that the file type is correctly accepted """ file = Loader().load(find("sphere2micron.ses")) f = file[0] # self.assertEqual(f, 5) self.assertEqual(len(file), 1) self.assertEqual(len(f.x), 40) self.assertEqual(f.x[0], 391.56) self.assertEqual(f.x[-1], 46099) self.assertEqual(f.y[-1], -0.19956) self.assertEqual(f.x_unit, "A") self.assertEqual(f.y_unit, "A-2 cm-1") self.assertEqual(f.sample.name, "Polystyrene 2 um in 53% H2O, 47% D2O") self.assertEqual(f.sample.thickness, 0.2) self.assertEqual(f.sample.zacceptance, (0.0168, "radians")) self.assertEqual(f.isSesans, True) def test_sesans_tof(self): """ Test .SES loading on a TOF dataset """ file = self.loader(find("sphere_isis.ses")) f = file[0] self.assertEqual(len(file), 1) self.assertEqual(len(f.x), 57) self.assertEqual(f.x[-1], 19303.4) self.assertEqual(f.source.wavelength[-1], 13.893668) self.assertEqual(f.source.wavelength[0], 1.612452) self.assertEqual(f.sample.yacceptance, (0.09, "radians")) self.assertEqual(f.sample.zacceptance, (0.09, "radians")) self.assertEqual(f.sample.thickness, 0.2) def test_sesans_no_data(self): """ Confirm that sesans files with no actual data won't load. """ self.assertRaises( FileContentsException, self.loader, find("sesans_no_data.ses")) def test_sesans_no_spin_echo_unit(self): """ Confirm that sesans files with no units from the spin echo length raise an appropriate error """ self.assertRaises( FileContentsException, self.loader, find("no_spin_echo_unit.ses")) def test_sesans_future_version(self): """ Confirm that sesans files that, according to semantic version, are from a future, backwards-incompatible version of the SES file format throw an exception. """ self.assertRaises( FileContentsException, self.loader, find("next_gen.ses")) def test_sesans_mandatory_headers(self): """ Confirm that sesans files throw an exception if one of the mandator headers is missing. """ self.assertRaises( FileContentsException, self.loader, find("no_wavelength.ses")) def test_sesans_columns_match_headers(self): """ Confirm that sesans files throw an exception if one of the mandator headers is missing. """ self.assertRaises( FileContentsException, self.loader, find("too_many_headers.ses")) if __name__ == "__main__": unittest.main() sasdata-0.8.1/test/sasmanipulations/000077500000000000000000000000001427502211700175125ustar00rootroot00000000000000sasdata-0.8.1/test/sasmanipulations/__init__.py000066400000000000000000000000001427502211700216110ustar00rootroot00000000000000sasdata-0.8.1/test/sasmanipulations/data/000077500000000000000000000000001427502211700204235ustar00rootroot00000000000000sasdata-0.8.1/test/sasmanipulations/data/cansas1d.xml000066400000000000000000000104321427502211700226420ustar00rootroot00000000000000 Test title 1234 0.02 1000 3 0.01 0.03 1001 4 0.02 SI600-new-long 1.03 0.327 0.0000 10.00 0.00 22.5 0.020

http://chemtools.chem.soton.ac.uk/projects/blog/blogs.php/bit_id/2720
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canSAS instrument neutron 12.00 13.00 disc 6.00 0.22 1.00 14.3 123.0 50 11.000 1 fictional hybrid 4.150 1 2 1.00 0.00 0.00 322.64 327.68 5.00 5.00 spol 04-Sep-2007 18:35:02 10.000 180.0 0.0 USER:MASK.COM AvA1 0.0000E+00 AsA2 1.0000E+00 XvA3 1.0526E+03 XsA4 5.2200E-02 XfA5 0.0000E+00 S... 13597 0 2.26E+02 2A 5mM 0%D2O Sbak 13594 0 1.13E+02 H2O Buffer V... 13552 3 1.00E+00 H2O5m NCNR-IGOR 03-SEP-2006 11:42:47 Circular SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 SEP06064.SA3_AJJ_L205 1 1 230.09 1 No Information sasdata-0.8.1/test/sasmanipulations/utest_manipulations.py000066400000000000000000000170101427502211700241720ustar00rootroot00000000000000""" Unit tests for data manipulations """ import math import os.path import unittest import numpy as np from numpy.testing import assert_allclose from sasdata.dataloader.loader import Loader from sasdata.dataloader.data_info import Data1D, Data2D RTOL = 1e-12 def find(filename): return os.path.join(os.path.dirname(__file__), 'data', filename) class DataInfoTests(unittest.TestCase): def setUp(self): data = Loader().load(find("cansas1d.xml")) self.data = data[0] def test_clone1D(self): """ Test basic cloning """ clone = self.data.clone_without_data() for i in range(len(self.data.detector)): self.assertEqual( self.data.detector[i].distance, clone.detector[i].distance) class Theory1DTests(unittest.TestCase): def setUp(self): data = Loader().load(find("cansas1d.xml")) self.data = data[0] def test_clone_theory1D(self): """ Test basic cloning """ theory = Data1D(x=[], y=[], dy=None) theory.clone_without_data(clone=self.data) theory.copy_from_datainfo(data1d=self.data) for i in range(len(self.data.detector)): self.assertEqual( self.data.detector[i].distance, theory.detector[i].distance) for i in range(len(self.data.x)): self.assertEqual(self.data.x[i], theory.x[i]) self.assertEqual(self.data.y[i], theory.y[i]) self.assertEqual(self.data.dy[i], theory.dy[i]) class ManipTests(unittest.TestCase): def setUp(self): # Create two data sets to play with x_0 = np.arange(1, 6, dtype='d') y_0 = 2.0 * np.ones(5) dy_0 = 0.5 * np.ones(5) self.data = Data1D(x_0, y_0, dy=dy_0) x = self.data.x.copy() y = np.ones(5) dy = np.ones(5) self.data2 = Data1D(x, y, dy=dy) def test_load(self): """ Test whether the test file was loaded properly """ # There should be 5 entries in the file self.assertEqual(len(self.data.x), 5) for i in range(5): # The x values should be from 1 to 5 self.assertEqual(self.data.x[i], float(i + 1)) # All y-error values should be 0.5 assert_allclose(self.data.dy, 0.5, RTOL) # All y values should be 2.0 assert_allclose(self.data.y, 2.0, RTOL) def test_add(self): result = self.data2 + self.data assert_allclose(result.y, 3.0, RTOL) assert_allclose(result.dy, np.sqrt(0.5**2 + 1.0), RTOL) def test_sub(self): result = self.data2 - self.data assert_allclose(result.y, -1.0, RTOL) assert_allclose(result.dy, math.sqrt(0.5**2 + 1.0), RTOL) def test_mul(self): result = self.data2 * self.data assert_allclose(result.y, 2.0, RTOL) assert_allclose( result.dy, math.sqrt((0.5 * 1.0)**2 + (1.0 * 2.0)**2), RTOL) def test_div(self): result = self.data2 / self.data assert_allclose(result.y, 0.5, RTOL) assert_allclose( result.dy, math.sqrt((1.0 / 2.0)**2 + (0.5 * 1.0 / 4.0)**2), RTOL) def test_radd(self): result = self.data + 3.0 assert_allclose(result.y, 5.0, RTOL) assert_allclose(result.dy, 0.5, RTOL) result = 3.0 + self.data assert_allclose(result.y, 5.0, RTOL) assert_allclose(result.dy, 0.5, RTOL) def test_rsub(self): result = self.data - 3.0 assert_allclose(result.y, -1.0, RTOL) assert_allclose(result.dy, 0.5, RTOL) result = 3.0 - self.data assert_allclose(result.y, 1.0, RTOL) assert_allclose(result.dy, 0.5, RTOL) def test_rmul(self): result = self.data * 3.0 assert_allclose(result.y, 6.0, RTOL) assert_allclose(result.dy, 1.5, RTOL) result = 3.0 * self.data assert_allclose(result.y, 6.0, RTOL) assert_allclose(result.dy, 1.5, RTOL) def test_rdiv(self): result = self.data / 4.0 assert_allclose(result.y, 0.5, RTOL) assert_allclose(result.dy, 0.125, RTOL) result = 6.0 / self.data assert_allclose(result.y, 3.0, RTOL) assert_allclose(result.dy, 6.0 * 0.5 / 4.0, RTOL) class Manin2DTests(unittest.TestCase): def setUp(self): # Create two data sets to play with x_0 = 2.0 * np.ones(25) dx_0 = 0.5 * np.ones(25) qx_0 = np.arange(25) qy_0 = np.arange(25) mask_0 = np.zeros(25) dqx_0 = np.arange(25) / 100 dqy_0 = np.arange(25) / 100 q_0 = np.sqrt(qx_0 * qx_0 + qy_0 * qy_0) self.data = Data2D(data=x_0, err_data=dx_0, qx_data=qx_0, qy_data=qy_0, q_data=q_0, mask=mask_0, dqx_data=dqx_0, dqy_data=dqy_0) y = np.ones(25) dy = np.ones(25) qx = np.arange(25) qy = np.arange(25) mask = np.zeros(25) q = np.sqrt(qx * qx + qy * qy) self.data2 = Data2D(data=y, err_data=dy, qx_data=qx, qy_data=qy, q_data=q, mask=mask) def test_load(self): """ Test whether the test file was loaded properly """ # There should be 5 entries in the file self.assertEqual(np.size(self.data.data), 25) for i in range(25): # All y-error values should be 0.5 self.assertEqual(self.data.err_data[i], 0.5) # All y values should be 2.0 self.assertEqual(self.data.data[i], 2.0) def test_add(self): result = self.data2 + self.data assert_allclose(result.data, 3.0, RTOL) assert_allclose(result.err_data, np.sqrt(0.5**2 + 1.0), RTOL) def test_sub(self): result = self.data2 - self.data assert_allclose(result.data, -1.0, RTOL) assert_allclose(result.err_data, math.sqrt(0.5**2 + 1.0), RTOL) def test_mul(self): result = self.data2 * self.data assert_allclose(result.data, 2.0, RTOL) assert_allclose( result.err_data, math.sqrt((0.5 * 1.0)**2 + (1.0 * 2.0)**2), RTOL) def test_div(self): result = self.data2 / self.data assert_allclose(result.data, 0.5, RTOL) assert_allclose( result.err_data, math.sqrt((1.0 / 2.0)**2 + (0.5 * 1.0 / 4.0)**2), RTOL) def test_radd(self): result = self.data + 3.0 assert_allclose(result.data, 5.0, RTOL) assert_allclose(result.err_data, 0.5, RTOL) result = 3.0 + self.data assert_allclose(result.data, 5.0, RTOL) assert_allclose(result.err_data, 0.5, RTOL) def test_rsub(self): result = self.data - 3.0 assert_allclose(result.data, -1.0, RTOL) assert_allclose(result.err_data, 0.5, RTOL) result = 3.0 - self.data assert_allclose(result.data, 1.0, RTOL) assert_allclose(result.err_data, 0.5, RTOL) def test_rmul(self): result = self.data * 3.0 assert_allclose(result.data, 6.0, RTOL) assert_allclose(result.err_data, 1.5, RTOL) result = 3.0 * self.data assert_allclose(result.data, 6.0, RTOL) assert_allclose(result.err_data, 1.5, RTOL) def test_rdiv(self): result = self.data / 4.0 assert_allclose(result.data, 0.5, RTOL) assert_allclose(result.err_data, 0.125, RTOL) result = 6.0 / self.data assert_allclose(result.data, 3.0, RTOL) assert_allclose(result.err_data, 6.0 * 0.5 / 4.0, RTOL) if __name__ == '__main__': unittest.main() sasdata-0.8.1/test/utest_sasdata.py000066400000000000000000000102611427502211700173360ustar00rootroot00000000000000#!/usr/bin/env python\ import os import subprocess import re import sys import logging.config LOGGER_CONFIG_FILE = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'logging.ini') logging.config.fileConfig(LOGGER_CONFIG_FILE) logger = logging.getLogger(__name__) try: import xmlrunner except: logger.error("xmlrunner needs to be installed to run these tests") logger.error("Try easy_install unittest-xml-reporting") sys.exit(1) # Check whether we have matplotlib installed HAS_MPL_WX = True try: import matplotlib import wx except ImportError: HAS_MPL_WX = False def run_tests(dirs=None, run_all=False): test_root = os.path.abspath(os.path.dirname(__file__)) run_one_py = os.path.join(test_root, 'run_one.py') passed = 0 failed = 0 n_tests = 0 n_errors = 0 n_failures = 0 failure_text = [] for d in (dirs if dirs else os.listdir(test_root)): # Go through modules looking for unit tests module_dir = os.path.join(test_root, d) if os.path.isdir(module_dir): for f in os.listdir(module_dir): file_path = os.path.join(module_dir,f) if os.path.isfile(file_path) and f.startswith("utest_") and f.endswith(".py"): module_name,_ = os.path.splitext(f) code = '"%s" %s %s'%(sys.executable, run_one_py, file_path) proc = subprocess.Popen(code, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) std_out, std_err = proc.communicate() std_out, std_err = std_out.decode(), (std_err.decode() if std_err else None) #print(">>>>>> standard out", file_path, "\n", std_out, "\n>>>>>>>>> end stdout", file_path) #print(">>>>>> standard err", file_path, "\n", std_err, "\n>>>>>>>>> end stderr", file_path) #sys.exit() m = re.search("Ran ([0-9]+) test", std_out) if m is not None: n_tests += int(m.group(1)) has_tests = True else: has_tests = False has_failed = "FAILED (" in std_out if has_failed: if std_out: failure_text.append("== %s std out ==\n%s" % (module_name, std_out)) if std_err: failure_text.append("== %s std err ==\n%s" % (module_name, std_out)) m = re.search("FAILED \(.*errors=([0-9]+)", std_out) if m is not None: n_errors += int(m.group(1)) m = re.search("FAILED \(.*failures=([0-9]+)", std_out) if m is not None: n_failures += int(m.group(1)) if has_failed or not has_tests: failed += 1 modpath = os.path.join(module_dir, module_name+".py") print("Result for %s: FAILED %s" % (module_name, os.path.relpath(modpath, os.getcwd()))) #print(std_out) else: passed += 1 print("Result for %s: SUCCESS" % module_name) print("\n----------------------------------------------") if n_tests == 0: print("No tests.") else: print("Results by test modules:") print(" PASSED: %d" % passed) ratio = 100.0*failed/(failed+passed) print(" FAILED: %d (%.0f%%)" % (failed,ratio)) print("Results by tests:") print(" Tests run: %d" % n_tests) print(" Tests failed: %d" % n_failures) print(" Test errors: %d" % n_errors) print("----------------------------------------------") print("\n\n".join(failure_text)) return failed if __name__ == '__main__': run_all = (len(sys.argv) > 1 and sys.argv[1] == '-all') dirs = sys.argv[1:] if not run_all else sys.argv[2:] if run_tests(dirs=dirs, run_all=run_all) > 0: sys.exit(1)