gganimate/0000755000176200001440000000000013741753531012217 5ustar liggesusersgganimate/NAMESPACE0000644000176200001440000001056713741663441013447 0ustar liggesusers# Generated by roxygen2: do not edit by hand S3method(animate,default) S3method(animate,gganim) S3method(c,TransmuteFactory) S3method(ggplot_add,EaseAes) S3method(ggplot_add,EnterFactory) S3method(ggplot_add,ExitFactory) S3method(ggplot_add,Shadow) S3method(ggplot_add,Transition) S3method(ggplot_add,View) S3method(ggplot_build,gganim) S3method(group_column,default) S3method(layer_type,GeomPath) S3method(layer_type,GeomPolygon) S3method(layer_type,GeomRibbon) S3method(layer_type,GeomSf) S3method(layer_type,GeomSmooth) S3method(layer_type,Stat) S3method(layer_type,StatContour) S3method(layer_type,default) S3method(match_shapes,StatContour) S3method(match_shapes,default) S3method(plot,gganim) S3method(print,gganim) S3method(print,gif_image) S3method(print,sprite_image) S3method(print,video_file) S3method(save_animation,"magick-image") S3method(save_animation,default) S3method(save_animation,gif_image) S3method(save_animation,video_file) S3method(split,gif_image) S3method(split,sprite_image) S3method(split,video_file) S3method(tween_before_stat,default) export(Shadow) export(ShadowMark) export(ShadowNull) export(ShadowTrail) export(ShadowWake) export(Transition) export(TransitionComponents) export(TransitionEvents) export(TransitionFilter) export(TransitionLayers) export(TransitionManual) export(TransitionNull) export(TransitionReveal) export(TransitionStates) export(TransitionTime) export(View) export(ViewFollow) export(ViewStep) export(ViewStepManual) export(ViewZoom) export(ViewZoomManual) export(anim_save) export(animate) export(av_renderer) export(ease_aes) export(enter_appear) export(enter_drift) export(enter_fade) export(enter_fly) export(enter_grow) export(enter_manual) export(enter_recolor) export(enter_recolour) export(enter_reset) export(exit_disappear) export(exit_drift) export(exit_fade) export(exit_fly) export(exit_manual) export(exit_recolor) export(exit_recolour) export(exit_reset) export(exit_shrink) export(ffmpeg_renderer) export(file_renderer) export(frame_vars) export(gg_animate) export(gganimate) export(gif_file) export(gifski_renderer) export(group_column) export(knit_print.gganim) export(knit_print.gif_image) export(knit_print.sprite_image) export(knit_print.video_file) export(last_animation) export(layer_type) export(magick_renderer) export(match_shapes) export(save_animation) export(shadow_mark) export(shadow_null) export(shadow_trail) export(shadow_wake) export(split_animation) export(sprite_file) export(sprite_renderer) export(transition_components) export(transition_events) export(transition_filter) export(transition_layers) export(transition_manual) export(transition_null) export(transition_reveal) export(transition_states) export(transition_time) export(tween_before_stat) export(video_file) export(view_follow) export(view_static) export(view_step) export(view_step_manual) export(view_zoom) export(view_zoom_manual) importFrom(ggplot2,CoordCartesian) importFrom(ggplot2,FacetNull) importFrom(ggplot2,Layout) importFrom(ggplot2,geom_blank) importFrom(ggplot2,ggplot_add) importFrom(ggplot2,ggplot_build) importFrom(ggplot2,ggplot_gtable) importFrom(ggplot2,ggproto) importFrom(ggplot2,is.ggplot) importFrom(ggplot2,scale_x_continuous) importFrom(ggplot2,scale_y_continuous) importFrom(ggplot2,waiver) importFrom(glue,glue) importFrom(glue,glue_data) importFrom(grDevices,bmp) importFrom(grDevices,col2rgb) importFrom(grDevices,dev.off) importFrom(grDevices,jpeg) importFrom(grDevices,png) importFrom(grDevices,svg) importFrom(grDevices,tiff) importFrom(grid,convertHeight) importFrom(grid,convertWidth) importFrom(grid,grid.draw) importFrom(grid,grid.newpage) importFrom(grid,pushViewport) importFrom(grid,seekViewport) importFrom(grid,upViewport) importFrom(progress,progress_bar) importFrom(rlang,"%||%") importFrom(rlang,as_function) importFrom(rlang,enquo) importFrom(rlang,eval_tidy) importFrom(rlang,quo) importFrom(rlang,quo_is_missing) importFrom(rlang,quo_is_null) importFrom(rlang,quo_name) importFrom(rlang,quos) importFrom(rlang,quos_auto_name) importFrom(scales,alpha) importFrom(stringi,stri_detect) importFrom(stringi,stri_match) importFrom(stringi,stri_replace) importFrom(tweenr,keep_state) importFrom(tweenr,tween_along) importFrom(tweenr,tween_at) importFrom(tweenr,tween_components) importFrom(tweenr,tween_constant) importFrom(tweenr,tween_events) importFrom(tweenr,tween_numeric) importFrom(tweenr,tween_state) importFrom(utils,modifyList) importFrom(utils,packageVersion) gganimate/LICENSE0000644000176200001440000000006113405665100013210 0ustar liggesusersYEAR: 2017 COPYRIGHT HOLDER: Thomas Lin Pedersen gganimate/man/0000755000176200001440000000000013741641122012762 5ustar liggesusersgganimate/man/frame_vars.Rd0000644000176200001440000000127113405665100015376 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/post_process.R \name{frame_vars} \alias{frame_vars} \title{Access metadata about the frames in an animation} \usage{ frame_vars(animation = last_animation()) } \arguments{ \item{animation}{The animation to extract metadata from. Defaults to the last rendered animation} } \value{ A data.frame with a row per frame in the animation and metadata as columns } \description{ This function extracts the metadata generated about each frame during rendering. It corresponds to the information available to the labels for string literal interpretation and is thus dependent on the transition and view used for the animation. } gganimate/man/video_file.Rd0000644000176200001440000000235313406166235015366 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/renderers.R \name{video_file} \alias{video_file} \alias{print.video_file} \alias{knit_print.video_file} \title{Wrap a video file for easy handling} \usage{ video_file(file) \method{print}{video_file}(x, width = NULL, ...) knit_print.video_file(x, options, ...) } \arguments{ \item{file}{A video file} \item{x}{A \code{video_file} object} \item{width}{The width the output should be scaled to} \item{...}{Arguments passed on} } \value{ \code{video_file} returns a \code{video_file} object which is a shallow wrapper around the file path text string. } \description{ This function is equivalent to \code{\link[=gif_file]{gif_file()}} but works for arbitrary video file formats. There are some caveats involved though, most notably it doesn't currently supports splitting so you can't easily use this output together with \code{\link[=split_animation]{split_animation()}}. Graceful printing is contingent on the file format. Only \code{mp4}, \code{webm}, and \code{ogg} is supported by the HTML format and can thus be shown in the RStudio viewer and inside HTML documents created with knitr. Other formats will be opened in their default OS-specific viewer. } \keyword{internal} gganimate/man/transition_layers.Rd0000644000176200001440000001004413611331661017021 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-layers.R \name{transition_layers} \alias{transition_layers} \title{Build up a plot, layer by layer} \usage{ transition_layers( layer_length = 1, transition_length = 1, keep_layers = TRUE, from_blank = TRUE, layer_order = NULL, layer_names = NULL ) } \arguments{ \item{layer_length}{The proportional time to pause at each layer before a new one enters} \item{transition_length}{The proportional time to use for the entrance of a new layer} \item{keep_layers}{Either an integer indicating for how many following layers the layers should stay on screen or a logical. In the case of the later, \code{TRUE} will mean keep the layer for the remainder of the animation (equivalent to setting it to \code{Inf}) and \code{FALSE} will mean to transition the layer out as the next layer enters.} \item{from_blank}{Should the first layer transition in or be present on the onset of the animation} \item{layer_order}{An alternative order the layers should appear in (default to using the stacking order). All other arguments that references the layers index in some way refers to this order.} \item{layer_names}{A character vector of names for each layers, to be used when interpreting label literals} } \description{ This transition gradually adds layers to the plot in the order they have been defined. By default prior layers are kept for the remainder of the animation, but they can also be set to be removed as the next layer enters. } \section{Label variables}{ \code{transition_layers} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{transitioning} is a boolean indicating whether the frame is part of the transitioning phase \item \strong{previous_layer} The name of the last layer the animation was showing \item \strong{closest_layer} The name of the layer the animation is closest to showing \item \strong{next_layer} The name of the next layer the animation will show \item \strong{nlayers} The total number of layers } } \section{Object permanence}{ \code{transition_layer} does not link rows across data to the same graphic element, so elements will be defined uniquely by each row and the enter and exit of the layer it belongs to. } \examples{ # Default is to use layer order and keep layers for duration of animation anim <- ggplot(mtcars, aes(mpg, disp)) + geom_point() + geom_smooth(colour = 'grey', se = FALSE) + geom_smooth(aes(colour = factor(gear))) + transition_layers(layer_length = 1, transition_length = 2) + enter_fade() + enter_grow() # Start with the first layer already present anim1 <- ggplot(mtcars, aes(mpg, disp)) + geom_point() + geom_smooth(colour = 'grey', se = FALSE) + geom_smooth(aes(colour = factor(gear))) + transition_layers(layer_length = 1, transition_length = 2, from_blank = FALSE) + enter_fade() + enter_grow() # Change the order of the layers anim2 <- ggplot(mtcars, aes(mpg, disp)) + geom_point() + geom_smooth(colour = 'grey', se = FALSE) + geom_smooth(aes(colour = factor(gear))) + transition_layers(layer_length = 1, transition_length = 2, from_blank = FALSE, layer_order = c(3, 1, 2)) + enter_fade() + enter_grow() # Keep layer 1 for the whole animation, but remove the 2nd layer as the 3rd # enters anim3 <- ggplot(mtcars, aes(mpg, disp)) + geom_point() + geom_smooth(colour = 'grey', se = FALSE) + geom_smooth(aes(colour = factor(gear))) + transition_layers(layer_length = 1, transition_length = 2, from_blank = FALSE, keep_layers = c(Inf, 0, 0)) + enter_fade() + enter_grow() + exit_fade() + exit_shrink() } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/view_step.Rd0000644000176200001440000001151713611331661015263 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/view-step.R, R/view-step-manual.R \name{view_step} \alias{view_step} \alias{view_step_manual} \title{Follow the data in steps} \usage{ view_step( pause_length = 1, step_length = 1, nsteps = NULL, look_ahead = pause_length, delay = 0, include = TRUE, ease = "cubic-in-out", wrap = TRUE, pause_first = FALSE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1 ) view_step_manual( pause_length = 1, step_length = 1, xmin, xmax, ymin, ymax, delay = 0, ease = "cubic-in-out", wrap = TRUE, pause_first = FALSE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1 ) } \arguments{ \item{pause_length}{The relative length the view will be kept static. Will be recycled to match the number of steps} \item{step_length}{The relative length the view will use to transition to the new position. Will be recycled to match the number of steps} \item{nsteps}{The number of steps. If \code{NULL} it will be set to the max length of \code{pause_length} or \code{step_length}} \item{look_ahead}{A relative length to look ahead in the animation to get the new zoom area. Allow the view to zoom to where the data will be} \item{delay}{A relative length to switch the view back and forth relative to the actual frames. E.g. if delay is calculated to 5 frames, frame 6 will get the view intended for frame 1.} \item{include}{Should the steps include both the start and end frame range} \item{ease}{The easing function used for the step} \item{wrap}{As in \code{\link[=transition_states]{transition_states()}}. Should the view wrap around and zoom back to the first state.} \item{pause_first}{Should the view start with a pause. The default is to start with a step so that it is aligned to the static period in \code{\link[=transition_states]{transition_states()}}} \item{fixed_x}{Either a logical indicating if the dimension should not be modified by the view, or a numeric vector giving the lower and upper bounds of the dimension. For the latter, an \code{NA} value will be substituted for whatever is calculated by the view (e.g. \code{fixed_x = c(0, NA)}) will fix the minimum x value to 0 and let the view calculate the upper bound.} \item{fixed_y}{Either a logical indicating if the dimension should not be modified by the view, or a numeric vector giving the lower and upper bounds of the dimension. For the latter, an \code{NA} value will be substituted for whatever is calculated by the view (e.g. \code{fixed_x = c(0, NA)}) will fix the minimum x value to 0 and let the view calculate the upper bound.} \item{exclude_layer}{Integer vector of layer indices that should be ignored when calculating the view} \item{aspect_ratio}{If the coord is fixed, ensure that the view matches the given aspect ratio. Will override anything given in \code{fixed_x}/\code{fixed_y}} \item{xmin, xmax, ymin, ymax}{Vectors of even length defining the boundaries of the different views to go through} } \description{ This view is a bit like \code{\link[=view_follow]{view_follow()}} but will not match the data in each frame. Instead it will switch between being static and zoom to the range of the data. It is a great pairing with \code{\link[=transition_states]{transition_states()}} as it can move the view while the data is static and then be static while the data moves. The standard version will look at the data present in the calculated frames and set the ranges based on that, while the \verb{_manual} version will allow you to define your own ranges. } \examples{ anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + view_step(pause_length = 2, step_length = 1, nsteps = 3) # Default is to include the data from the two states you're stepping between # but this can be turned off anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + view_step(pause_length = 2, step_length = 1, nsteps = 3, include = FALSE) # Default is to work off-beat of transition_states so that view changes while # data is static. Setting pause_first=TRUE changes this anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + view_step(pause_length = 1, step_length = 2, nsteps = 3, pause_first = TRUE) # If the transition doesn't wrap, then the view shouldn't either anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1, wrap = FALSE) + view_step(pause_length = 2, step_length = 1, nsteps = 3, wrap = FALSE) } \seealso{ Other views: \code{\link{view_follow}()}, \code{\link{view_static}()}, \code{\link{view_zoom}()} } \concept{views} gganimate/man/layer_type.Rd0000644000176200001440000000066413405665100015433 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/group_column.R, R/layer_type.R, % R/match_shapes.R \name{group_column} \alias{group_column} \alias{layer_type} \alias{match_shapes} \title{Define what graphical type a layer is} \usage{ group_column(x) layer_type(x) match_shapes(x) } \arguments{ \item{x}{a Layer, Geom, or Stat} } \description{ Define what graphical type a layer is } \keyword{internal} gganimate/man/enter_exit.Rd0000644000176200001440000001455113611331661015425 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transmute-.R, R/transmute-enter.R, % R/transmute-exit.R \name{enter_exit} \alias{enter_exit} \alias{enter} \alias{exit} \alias{enter_manual} \alias{enter_appear} \alias{enter_fade} \alias{enter_grow} \alias{enter_recolour} \alias{enter_recolor} \alias{enter_fly} \alias{enter_drift} \alias{enter_reset} \alias{exit_manual} \alias{exit_disappear} \alias{exit_fade} \alias{exit_shrink} \alias{exit_recolour} \alias{exit_recolor} \alias{exit_fly} \alias{exit_drift} \alias{exit_reset} \title{Define how entering and exiting data behaves} \usage{ enter_manual(default = NULL, ..., name = "manual") enter_appear(early = FALSE, ...) enter_fade(..., alpha = 0) enter_grow(..., size = 0) enter_recolour(..., colour = "white", fill = colour) enter_recolor(..., color = "white", fill = color) enter_fly(..., x_loc = NA, y_loc = NA) enter_drift(..., x_mod = 0, y_mod = 0) enter_reset() exit_manual(default = NULL, ..., name = "manual") exit_disappear(early = FALSE, ...) exit_fade(..., alpha = 0) exit_shrink(..., size = 0) exit_recolour(..., colour = "white", fill = colour) exit_recolor(..., color = "white", fill = color) exit_fly(..., x_loc = NA, y_loc = NA) exit_drift(..., x_mod = 0, y_mod = 0) exit_reset() } \arguments{ \item{default}{A default transformation to use} \item{...}{Additional specific transformations either named by the geom (e.g. \code{bar}, or by its position in the layer stack, e.g. \code{"2"})} \item{name}{A name for the manual modification (only used when printing the object)} \item{early}{Should the data appear in the beginning of the transition or in the end} \item{alpha}{The start/end transparency.} \item{size}{The proportional start/end size. \code{0} means complete shrinking while \code{1} means no shrinking} \item{colour, color, fill}{The start/end colour and fill the elements should (dis)appear into} \item{x_loc, y_loc}{Start and end positions of the graphic elements} \item{x_mod, y_mod}{Modification to add to the entering or exiting data} } \description{ The purpose of \verb{enter_*()} and \verb{exit_*()} is to control what happens with data that does not persist during a tween. In general the non-persistent data is transformed to an \emph{invisible} version that can be tweened to, e.g. by setting the opacity to 0 or be moving the element off-screen. It is possible to define your own transformations, or rely on some of the build in \emph{effects}. } \section{User-defined transformations}{ All enter/exit functions allows the user to add additional transformation functions targeting specific layers. If the functions are named, then the name is understood to reference the class of geoms it applies to. If the functions are unnamed or numbered they will apply to the layer with a matching index in the stack. Named and indexed transformations cannot be mixed. All modifications except \code{enter_manual()}/\code{exit_manual()} sets a range of modifications already, but further can be added with the \code{...}. For the manual versions a \code{default} transformation can be set which will apply to all layers that does not match any of the other given transformations. Often a single default transformation is enough and no specific transformations are needed. Transformation can be given as any expression that can be converted with \code{\link[rlang:as_function]{rlang::as_function()}}. This means that \code{purrr} style lambda functions are allowed in addition to anonymous functions etc. Transformation functions must accept a data.frame and return a data.frame of the same dimensions. The function will be called with the entering/exiting layer data, except for the case of polygon- and path-like layers in which case the function recieves the entering/exiting polygon/path data one by one. A special option is to set a transformation as \code{NULL} instead of a function. In that case the entering and exiting data will simply appear/disappear when it is no longer part of a frame. } \section{Modification composition}{ Enter and exit modifications are composable so that multiple different ones can be added to an animation and will be applied in turn. You can also combine multiples and save them as a new enter or exit modification using \code{c()}. Due to the composable nature of enter and exit modifications it is not possible to overwrite a prior modification by adding a new. If it is needed to start from scratch then the sentinels \code{enter_reset()} and \code{exit_reset()} are provided which clears all prior modifications. } \section{Modification types}{ A range of modification types are provided by \code{gganimate} and using \code{enter_manual()}/\code{exit_manual()} or modification composition it is possible to create your own. \strong{appear}/\strong{disappear} will simply make elements appear/disappear at either the start or end of the transition. The default if nothing else is added. \strong{fade} will simply set the alpha value to zero making the elements fade in/out during the transition. \strong{grow}/\strong{shrink} will set the elements to zero size making them gradually grow into / shrink out of existence. Zero size depends on the type of layer, e.g. polygons/paths will have all their points set to the mean, while points will have size/stroke set to zero. \strong{recolour}/\strong{recolor} will change the colour and/or fill of the elements making them gradually change from the defined colour and into their try colour. Be aware that unless the colour and fill are set to the same as the background colour of the plot this modification needs to be combined with others to ensure that elements does not abruptly appear. \strong{fly} will set a specific x and y position where all elements will enter from/ exit to, irrespectible of their real position. \strong{drift} will modify the real position of the entering and exiting elements by a specified amount, e.g. setting \code{x_mod = -5} will let all elements enter from/exit to the left with a terminal position 5 points to the left of the real position. } \examples{ # Default is appear/disappear anim <- ggplot(mtcars, aes(factor(gear), mpg)) + geom_boxplot() + transition_states(gear, 2, 1) # Fade-in, fly-out anim1 <- anim + enter_fade() + exit_fly(x_loc = 7, y_loc = 40) # Enter and exit accumulates anim2 <- anim + enter_fade() + enter_grow() + exit_fly(x_loc = 7, y_loc = 40) + exit_recolour(fill = 'forestgreen') } gganimate/man/view_follow.Rd0000644000176200001440000000355613611331661015616 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/view-follow.R \name{view_follow} \alias{view_follow} \title{Let the view follow the data in each frame} \usage{ view_follow( fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1 ) } \arguments{ \item{fixed_x, fixed_y}{Either a logical indicating if the dimension should not be modified by the view, or a numeric vector giving the lower and upper bounds of the dimension. For the latter, an \code{NA} value will be substituted for whatever is calculated by the view (e.g. \code{fixed_x = c(0, NA)}) will fix the minimum x value to 0 and let the view calculate the upper bound.} \item{exclude_layer}{Integer vector of layer indices that should be ignored when calculating the view} \item{aspect_ratio}{If the coord is fixed, ensure that the view matches the given aspect ratio. Will override anything given in \code{fixed_x}/\code{fixed_y}} } \description{ This view will set the panels to include the data present in the frame. } \examples{ anim <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 4, state_length = 1) + view_follow() # Fixing a dimension can be done in general anim1 <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 4, state_length = 1) + view_follow(fixed_x = TRUE) # ...or just for one side of the range anim1 <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 4, state_length = 1) + view_follow(fixed_x = c(4, NA), fixed_y = c(2, NA)) } \seealso{ Other views: \code{\link{view_static}()}, \code{\link{view_step}()}, \code{\link{view_zoom}()} } \concept{views} gganimate/man/view_zoom.Rd0000644000176200001440000001213113611331661015265 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/view-zoom.R, R/view-zoom-manual.R \name{view_zoom} \alias{view_zoom} \alias{view_zoom_manual} \title{Pan and zoom smoothly between different states} \usage{ view_zoom( pause_length = 1, step_length = 1, nsteps = NULL, look_ahead = 0, delay = 0, include = FALSE, pan_zoom = 0, ease = "sine-in-out", wrap = TRUE, pause_first = TRUE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1 ) view_zoom_manual( pause_length = 1, step_length = 1, xmin, xmax, ymin, ymax, delay = 0, pan_zoom = 0, ease = "sine-in-out", wrap = TRUE, pause_first = TRUE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1 ) } \arguments{ \item{pause_length}{The relative length the view will be kept static. Will be recycled to match the number of steps} \item{step_length}{The relative length the view will use to transition to the new position. Will be recycled to match the number of steps} \item{nsteps}{The number of steps. If \code{NULL} it will be set to the max length of \code{pause_length} or \code{step_length}} \item{look_ahead}{A relative length to look ahead in the animation to get the new zoom area. Allow the view to zoom to where the data will be} \item{delay}{A relative length to switch the view back and forth relative to the actual frames. E.g. if delay is calculated to 5 frames, frame 6 will get the view intended for frame 1.} \item{include}{Should the steps include both the start and end frame range} \item{pan_zoom}{The tradeoff between pan- and zoom-induced movement. Negative values will value zoom over pan and positive values will value pan over zoom} \item{ease}{The easing function used for the step} \item{wrap}{As in \code{\link[=transition_states]{transition_states()}}. Should the view wrap around and zoom back to the first state.} \item{pause_first}{Should the view start with a pause. The default is to start with a step so that it is aligned to the static period in \code{\link[=transition_states]{transition_states()}}} \item{fixed_x}{Either a logical indicating if the dimension should not be modified by the view, or a numeric vector giving the lower and upper bounds of the dimension. For the latter, an \code{NA} value will be substituted for whatever is calculated by the view (e.g. \code{fixed_x = c(0, NA)}) will fix the minimum x value to 0 and let the view calculate the upper bound.} \item{fixed_y}{Either a logical indicating if the dimension should not be modified by the view, or a numeric vector giving the lower and upper bounds of the dimension. For the latter, an \code{NA} value will be substituted for whatever is calculated by the view (e.g. \code{fixed_x = c(0, NA)}) will fix the minimum x value to 0 and let the view calculate the upper bound.} \item{exclude_layer}{Integer vector of layer indices that should be ignored when calculating the view} \item{aspect_ratio}{If the coord is fixed, ensure that the view matches the given aspect ratio. Will override anything given in \code{fixed_x}/\code{fixed_y}} \item{xmin, xmax, ymin, ymax}{Vectors of even length defining the boundaries of the different views to go through} } \description{ This view is in many ways equivalent to \code{\link[=view_step]{view_step()}} and \code{\link[=view_step_manual]{view_step_manual()}} but instead of simply tweening the bounding box of each view it implement the smooth zoom and pan technique developed by Reach & North (2018). It gradually zooms out and then in during the pan to allow a smooth transition of the view. As with \code{\link[=view_step]{view_step()}} the standard version will look at the data present in the calculated frames and set the ranges based on that, while the \verb{_manual} version will allow you to define your own ranges to zoom between. } \examples{ anim <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + view_zoom(pause_length = 1, step_length = 2, nsteps = 3) # Use pan_zoom to change the relationship between pan- and zoom movement # Mainly zooming anim1 <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + view_zoom(pause_length = 1, step_length = 2, nsteps = 3, pan_zoom = -3) # Mainly panning anim2 <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + geom_point() + transition_states(Species, transition_length = 2, state_length = 1) + shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + view_zoom(pause_length = 1, step_length = 2, nsteps = 3, pan_zoom = -3) } \references{ Reach, A., North, C. (2018) \emph{Smooth, Efficient, and Interruptible Zooming and Panning}. IEEE Transactions on Visualization and Computer Graphics DOI:10.1109/TVCG.2018.2800013 } \seealso{ Other views: \code{\link{view_follow}()}, \code{\link{view_static}()}, \code{\link{view_step}()} } \concept{views} gganimate/man/transition_components.Rd0000644000176200001440000000623713611331661017720 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-components.R \name{transition_components} \alias{transition_components} \title{Transition individual components through their own lifecycle} \usage{ transition_components( time, range = NULL, enter_length = NULL, exit_length = NULL, id ) } \arguments{ \item{time}{The unquoted name of the column holding the time for each state of the components} \item{range}{The range the animation should span. Defaults to the range of time plus enter and exit length} \item{enter_length, exit_length}{How long time should be spend on enter and exit transitions. Defaults to 0} \item{id}{\strong{Deprecated}} } \description{ This transition allows individual visual components to define their own "life-cycle". This means that the final animation will not have any common "state" and "transition" phase as any component can be moving or static at any point in time. } \section{Label variables}{ \code{transition_components} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{frame_time} gives the time that the current frame corresponds to } } \section{Object permanence}{ \code{transition_components} uses the group aesthetic of each layer to identify which rows in the input data correspond to the same graphic element and will therefore define stages in time that the element will animate through. The group aesthetic, if not set, will be calculated from the interaction of all discrete aesthetics in the layer (excluding \code{label}), so it is often better to set it explicetly when animating, to make sure your data is interpreted in the right way. If the group aesthetic is not set, and no discrete aesthetics exists then all rows will have the same group. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ data <- data.frame( x = runif(10), y = runif(10), size = sample(1:3, 10, TRUE), time = c(1, 4, 6, 7, 9, 6, 7, 8, 9, 10), id = rep(1:2, each = 5) ) anim <- ggplot(data, aes(x, y, group = id, size = size)) + geom_point() + transition_components(time) # By default the time range is set to the range of the time varialbe (plus # any enter and exit length), but this can be overwritten anim2 <- ggplot(data, aes(x, y, group = id, size = size)) + geom_point() + transition_components(time, range = c(4, 8)) # If you are using any enter/exit functions you need to give them some time anim3 <- ggplot(data, aes(x, y, group = id, size = size)) + geom_point() + transition_components(time, enter_length = 2, exit_length = 2) + enter_grow() + exit_fade() } \seealso{ Other transitions: \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/shadow_null.Rd0000644000176200001440000000066613611331661015600 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/shadow-null.R \name{shadow_null} \alias{shadow_null} \title{A non-existent shadow} \usage{ shadow_null() } \description{ This is the default shadow that simply doesn't show anything other than the data for the current frame. } \seealso{ Other shadows: \code{\link{shadow_mark}()}, \code{\link{shadow_trail}()}, \code{\link{shadow_wake}()} } \concept{shadows} gganimate/man/gganimate-package.Rd0000644000176200001440000000405513611331661016602 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/gganimate-package.r \docType{package} \name{gganimate-package} \alias{gganimate-package} \alias{_PACKAGE} \title{gganimate: A Grammar of Animated Graphics} \description{ \if{html}{\figure{logo.png}{options: align='right' alt='logo' width='120'}} The grammar of graphics as implemented in the 'ggplot2' package has been successful in providing a powerful API for creating static visualisation. In order to extend the API for animated graphics this package provides a completely new set of grammar, fully compatible with 'ggplot2' for specifying transitions and animations in a flexible and extensible way. } \section{Good starting points}{ The \code{\link[=animate]{animate()}} function documentation describes how to specify how the animation is rendered, whereas the documentation for the different transition functions, e.g. \code{\link[=transition_states]{transition_states()}}, describe how to declare the animation. Both \code{\link[=ease_aes]{ease_aes()}} and the different \link[=enter_exit]{enter and exit} functions are good to understand in order to modify tweening of the animation. Apart from the included documentation there is also a few web ressources worth mentioning: \itemize{ \item The \href{https://github.com/thomasp85/gganimate/wiki}{gganimate wiki} includes user supplied example walkthroughs \item The \href{https://github.com/ropenscilabs/learngganimate}{learngganimate} project by rOpenSci Labs includes a long range of detailed explorations of the different gganimate functions } } \seealso{ Useful links: \itemize{ \item \url{https://gganimate.com} \item \url{https://github.com/thomasp85/gganimate} \item Report bugs at \url{https://github.com/thomasp85/gganimate/issues} } } \author{ \strong{Maintainer}: Thomas Lin Pedersen \email{thomasp85@gmail.com} (\href{https://orcid.org/0000-0002-5147-4711}{ORCID}) Authors: \itemize{ \item David Robinson \email{admiral.david@gmail.com} } Other contributors: \itemize{ \item RStudio [copyright holder] } } gganimate/man/shadow_wake.Rd0000644000176200001440000000520313611331661015545 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/shadow-wake.R \name{shadow_wake} \alias{shadow_wake} \title{Show preceding frames with gradual falloff} \usage{ shadow_wake( wake_length, size = TRUE, alpha = TRUE, colour = NULL, fill = NULL, falloff = "cubic-in", wrap = TRUE, exclude_layer = NULL, exclude_phase = c("enter", "exit") ) } \arguments{ \item{wake_length}{A number between 0 and 1 giving the length of the wake, in relation to the total number of frames.} \item{size}{Numeric indicating the size the wake should end on. If \code{NULL} then size is not modified. Can also be a boolean with \code{TRUE} beeing equal \code{0} and \code{FALSE} beeing equal to \code{NULL}} \item{alpha}{as \code{size} but for alpha modification of the wake} \item{colour, fill}{colour or fill the wake should end on. If \code{NULL} they are not modified.} \item{falloff}{An easing function that control how size and/or alpha should change.} \item{wrap}{Should the shadow wrap around, so that the first frame will get shadows from the end of the animation.} \item{exclude_layer}{Indexes of layers that should be excluded.} \item{exclude_phase}{Element phases that should not get a shadow. Possible values are \code{'enter'}, \code{'exit'}, \code{'static'}, \code{'transition'}, and \code{'raw'}. If \code{NULL} all phases will be included. Defaults to \code{'enter'} and \code{'exit'}} } \description{ This shadow is meant to draw a small wake after data by showing the latest frames up to the current. You can choose to gradually diminish the size and/or opacity of the shadow. The length of the wake is not given in absolute frames as that would make the animation susceptible to changes in the framerate. Instead it is given as a proportion of the total length of the animation. } \examples{ anim <- ggplot(iris, aes(Petal.Length, Sepal.Length)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 4, state_length = 1) # `shadow_wake` can be combined with e.g. `transition_states` to show # motion of geoms as they are in transition with respect to the selected state. anim1 <- anim + shadow_wake(wake_length = 0.05) # Different qualities can be manipulated by setting a value for it that it # should taper off to anim2 <- anim + shadow_wake(0.1, size = 10, alpha = FALSE, colour = 'grey92') # Use `detail` in the `animate()` call to increase the number of calculated # frames and thus make the wake smoother \dontrun{ animate(anim2, detail = 5) } } \seealso{ Other shadows: \code{\link{shadow_mark}()}, \code{\link{shadow_null}()}, \code{\link{shadow_trail}()} } \concept{shadows} gganimate/man/shadow_trail.Rd0000644000176200001440000000275513611331661015742 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/shadow-trail.R \name{shadow_trail} \alias{shadow_trail} \title{A trail of evenly spaced old frames} \usage{ shadow_trail(distance = 0.05, max_frames = Inf, ..., exclude_layer = NULL) } \arguments{ \item{distance}{The temporal distance between the frames to show, as a fraction of the full animation length} \item{max_frames}{The maximum number of shadow frames to show} \item{...}{changes to the shadow data, e.g. \code{alpha = alpha/2} or \code{colour = 'grey'}} \item{exclude_layer}{Indexes of layers that should be excluded.} } \description{ This shadow will trace the movement in your animation by keeping every \emph{n}th frame and will thus produce a breadcrumb-like trail. Note that the shadow frames will not be equidistant in space but in time (that is, if a point moves slowly the \emph{crumbs} will be closer to each other). It is possible to modify the look of the shadow by changing the different graphic parameters in the data } \examples{ anim <- ggplot(airquality, aes(Day, Temp, colour = factor(Month))) + geom_point() + transition_time(Day) # Change distance between points anim1 <- anim + shadow_trail(0.02) # Style shadow differently anim2 <- anim + shadow_trail(alpha = 0.3, shape = 2) # Restrict the shadow to 10 frames anim3 <- anim + shadow_trail(max_frames = 10) } \seealso{ Other shadows: \code{\link{shadow_mark}()}, \code{\link{shadow_null}()}, \code{\link{shadow_wake}()} } \concept{shadows} gganimate/man/transition_null.Rd0000644000176200001440000000115213611331661016474 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-null.R \name{transition_null} \alias{transition_null} \title{Keep all data constant across the animation} \usage{ transition_null() } \description{ Keep all data constant across the animation } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/renderers.Rd0000644000176200001440000001124413617340676015260 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/renderers.R \name{renderers} \alias{renderers} \alias{gifski_renderer} \alias{file_renderer} \alias{av_renderer} \alias{ffmpeg_renderer} \alias{magick_renderer} \alias{sprite_renderer} \title{Renderers provided by gganimate} \usage{ gifski_renderer(file = NULL, loop = TRUE, width = NULL, height = NULL) file_renderer(dir = ".", prefix = "gganim_plot", overwrite = FALSE) av_renderer(file = NULL, vfilter = "null", codec = NULL, audio = NULL) ffmpeg_renderer( format = "auto", ffmpeg = NULL, options = list(pix_fmt = "yuv420p") ) magick_renderer(loop = TRUE) sprite_renderer() } \arguments{ \item{file}{The animation file} \item{loop}{Logical. Should the produced gif loop} \item{width, height}{Dimensions of the animation in pixels. If \code{NULL} will take the dimensions from the frame, otherwise it will rescale it.} \item{dir}{The directory to copy the frames to} \item{prefix}{The filename prefix to use for the image files} \item{overwrite}{Logical. If TRUE, existing files will be overwritten.} \item{vfilter}{A string defining an ffmpeg filter graph. This is the same parameter as the \code{-vf} argument in the \code{ffmpeg} command line utility.} \item{codec}{The name of the video codec. The default is \code{libx264} for most formats, which usually the best choice. See the \code{av} documentation for more information.} \item{audio}{An optional file with sounds to add to the video} \item{format}{The video format to encode the animation into} \item{ffmpeg}{The location of the \code{ffmpeg} executable. If \code{NULL} it will be assumed to be on the search path} \item{options}{Either a character vector of command line options for ffmpeg or a named list of option-value pairs that will be converted to command line options automatically} } \value{ The provided renderers are factory functions that returns a new function that take \code{frames} and \code{fps} as arguments, the former being a character vector with file paths to the images holding the separate frames, in the order they should appear, and the latter being the framerate to use for the animation in frames-per-second. The return type of the different returned renderers are: \itemize{ \item \strong{\code{gifski_renderer}}: Returns a \link{gif_image} object \item \strong{\code{magick_renderer}}: Returns a \code{magick-image} object \item \strong{\code{av_renderer}}: Returns a \link{video_file} object \item \strong{\code{ffmpeg_renderer}}: Returns a \link{video_file} object \item \strong{\code{file_renderer}}: Returns a vector of file paths } } \description{ The purpose of the renderer function is to take a list of image files and assemble them into an animation. \code{gganimate} provide a range of renderers but it is also possible to provide your own, if the supplied ones are lacking in any way. A renderer is given as argument to \code{\link[=animate]{animate()}}/print() and receives the paths to the individual frames once they have been created. } \details{ The \code{gifski_renderer()} is used unless otherwise specified in \code{\link[=animate]{animate()}} or in \code{options('gganimate.renderer')}. This renderer requires both the \code{gifski} and \code{png} packages to be installed. Other possible renderers are: \itemize{ \item \code{magick_renderer()} which requires the \code{magick} package and produce a \code{gif}. If \code{gifski} is not installed, the rendering will be much slower than using the \code{gifski_renderer()} and can potentially result in system problems when many frames need to be rendered (if \code{gifski} is installed \code{magick} will use it under the hood) \item \code{av_renderer()} which requies the \code{av} package and uses ffmpeg to encode the animation into a video file. \item \code{ffmpeg_renderer()} which requires that ffmpeg has been installed on your computer. As with \code{av_renderer()} it will use ffmpeg to encode the animation into a video \item \code{sprite_renderer()} which requires \code{magick} and will render the animation into a spritesheet \item \code{file_renderer()} which has no dependencies and simply returns the animation as a list of image files (one for each frame) } It is possible to create your own renderer function providing that it matches the required signature (\code{frames} and \code{fps} argument). The return value of your provided function will be the return value ultimately given by \code{\link[=animate]{animate()}} } \examples{ anim <- ggplot(mtcars, aes(mpg, disp)) + transition_states(gear, transition_length = 2, state_length = 1) + enter_fade() + exit_fade() \dontrun{ # Renderers are specified in the `animate()` function animate(anim, renderer = sprite_renderer()) } } gganimate/man/gif_file.Rd0000644000176200001440000000241113701271006015007 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/renderers.R \name{gif_file} \alias{gif_file} \alias{gif_image} \alias{print.gif_image} \alias{knit_print.gif_image} \alias{split.gif_image} \title{Wrap a gif file for easy handling} \usage{ gif_file(file) \method{print}{gif_image}(x, ...) knit_print.gif_image(x, options, ...) \method{split}{gif_image}(x, f, drop = FALSE, ...) } \arguments{ \item{file}{The gif file to be wrapped} \item{x}{A \code{gif_image} object} \item{...}{Arguments passed on} \item{f}{a ‘factor’ in the sense that \link[base:factor]{as.factor(f)} defines the grouping, or a list of such factors in which case their interaction is used for the grouping.} \item{drop}{logical indicating if levels that do not occur should be dropped (if \code{f} is a \code{factor} or a list).} } \value{ \code{gif_file} returns a \code{gif_image} object. \code{split} returns a list of \code{magick-image} objects and requires magick to work. } \description{ This is a simple class for gif files that takes care printing the file correctly in different environment (e.g. knitr, RStudio, etc.). If your renderer produces a gif file you can wrap the final output in \code{gif_file} to get all of these benefits for free. } \keyword{internal} gganimate/man/anim_save.Rd0000644000176200001440000000232413701270201015204 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/anim_save.R \name{anim_save} \alias{anim_save} \title{Save an animation to a file} \usage{ anim_save(filename, animation = last_animation(), path = NULL, ...) } \arguments{ \item{filename}{File name to create on disk.} \item{animation}{The animation object to save, as returned by \code{\link[=animate]{animate()}}. Defaults to the last rendered animation using \code{\link[=last_animation]{last_animation()}}} \item{path}{Path of the directory to save plot to: \code{path} and \code{filename} are combined to create the fully qualified file name. Defaults to the working directory.} \item{...}{arguments passed on to \code{\link[=animate]{animate()}} if \code{animation} is a \code{gganim} object} } \description{ This function is analogous to \code{\link[ggplot2:ggsave]{ggplot2::ggsave()}} in that it by default takes the last created animation and saves it to the specific location. As \code{gganimate} supports arbitrary renderers, and thus return types, the returned object must implement a \code{save_animation} method to be able to be used with \code{anim_save()}. This is provided natively for \code{gif_image} and \code{magick-image} objects. } gganimate/man/save_animation.Rd0000644000176200001440000000073613405665100016253 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/anim_save.R \name{save_animation} \alias{save_animation} \title{Infrastructure for animation saving} \usage{ save_animation(animation, file) } \arguments{ \item{animation}{The animation object to save} \item{file}{The file path to save it to} } \description{ Any returned animation object that wish to support \code{\link[=anim_save]{anim_save()}} need to implement this method } \keyword{internal} gganimate/man/ease_aes.Rd0000644000176200001440000000423013406137600015014 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/ease-aes.R \name{ease_aes} \alias{ease_aes} \title{Control easing of aesthetics} \usage{ ease_aes(default = "linear", ...) } \arguments{ \item{default}{The default easing function to use (defaults to \code{'linear'})} \item{...}{Override easing for specific aesthetics} } \description{ Easing defines how a value change to another during tweening. Will it progress linearly, or maybe start slowly and then build up momentum. In \code{gganimate}, each aesthetic or computed variable can be tweened with individual easing functions using the \code{ease_aes()} function. All easing functions implemented in \code{tweenr} are available, see \link[tweenr:display_ease]{tweenr::display_ease} for an overview. Setting an ease for \code{x} and/or \code{y} will also affect the other related positional aesthetics (e.g. \code{xmin}, \code{yend}, etc). } \section{Easing functions}{ \itemize{ \item \strong{quadratic} Models a power-of-2 function \item \strong{cubic} Models a power-of-3 function \item \strong{quartic} Models a power-of-4 function \item \strong{quintic} Models a power-of-5 function \item \strong{sine} Models a sine function \item \strong{circular} Models a pi/2 circle arc \item \strong{exponential} Models an exponential function \item \strong{elastic} Models an elastic release of energy \item \strong{back} Models a pullback and relase \item \strong{bounce} Models the bouncing of a ball } \emph{Modifiers} \cr \itemize{ \item \strong{-in} The easing function is applied as-is \item \strong{-out} The easing function is applied in reverse \item \strong{-in-out} The first half of the transition it is applied as-is, while in the last half it is reversed } } \examples{ anim <- ggplot(mtcars, aes(mpg, disp)) + transition_states(gear, transition_length = 2, state_length = 1) + enter_fade() + exit_fade() \dontrun{ # Default uses linear easing animate(anim) } # Change all to 'cubic-in-out' for a smoother appearance anim1 <- anim + ease_aes('cubic-in-out') \dontrun{ animate(anim1) } # Only change easing of y variables anim2 <- anim + ease_aes(y = 'bounce-in') \dontrun{ animate(anim2) } } gganimate/man/last_animation.Rd0000644000176200001440000000043513405665100016254 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/animation_store.R \name{last_animation} \alias{last_animation} \title{Retrieve the last rendered animation} \usage{ last_animation() } \description{ Retrieve the last rendered animation } \keyword{internal} gganimate/man/shadow_mark.Rd0000644000176200001440000000277513611331661015563 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/shadow-mark.R \name{shadow_mark} \alias{shadow_mark} \title{Show original data as background marks} \usage{ shadow_mark(past = TRUE, future = FALSE, ..., exclude_layer = NULL) } \arguments{ \item{past}{Should raw data from earlier in the animation be shown} \item{future}{Should raw data from later in the animation be shown} \item{...}{changes to the shadow data, e.g. \code{alpha = alpha/2} or \code{colour = 'grey'}} \item{exclude_layer}{Indexes of layers that should be excluded.} } \description{ This shadow lets you show the raw data behind the current frame. Both past and/or future raw data can be shown and styled as you want. } \examples{ # Use any of the aesthetics to add a style to either the past or the future raw data. # Adding a grouping variable in a transition call prior to calling `shadow_mark()` will # allow transitioning through different states in time. p1 <- ggplot(airquality, aes(Day, Temp)) + geom_line(color = 'red', size = 1) + transition_time(Month) + shadow_mark(colour = 'black', size = 0.75) # animate(p1) # Add a future = TRUE argument to show data later in the animation. p2 <- ggplot(airquality, aes(Day, Temp)) + geom_line(color = 'red', size = 1) + transition_time(Month) + shadow_mark(color = 'black', size = 0.75, past = FALSE, future = TRUE) # animate(p2) } \seealso{ Other shadows: \code{\link{shadow_null}()}, \code{\link{shadow_trail}()}, \code{\link{shadow_wake}()} } \concept{shadows} gganimate/man/transition_time.Rd0000644000176200001440000000643013611331661016464 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-time.R \name{transition_time} \alias{transition_time} \title{Transition through distinct states in time} \usage{ transition_time(time, range = NULL) } \arguments{ \item{time}{An unquoted expression giving the time, and thus state membership, of each observation.} \item{range}{The time range to animate. If \code{NULL} it will be set to the range of \code{time}} } \description{ This is a variant of \code{\link[=transition_states]{transition_states()}} that is intended for data where the states are representing specific point in time. The transition length between the states will be set to correspond to the actual time difference between them. } \section{Label variables}{ \code{transition_time} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{frame_time} gives the time that the current frame corresponds to } } \section{Object permanence}{ \code{transition_time} uses the group aesthetic of each layer to identify which rows in the input data correspond to the same graphic element and will therefore define which elements will turn into each other between time points. The group aesthetic, if not set, will be calculated from the interaction of all discrete aesthetics in the layer (excluding \code{label}), so it is often better to set it explicetly when animating, to make sure your data is interpreted in the right way. If the group aesthetic is not set, and no discrete aesthetics exists then all rows will have the same group. If the group aesthetic is not unique in each state, then rows will be matched first by group and then by index. Unmatched rows will appear/disappear, potentially using an enter or exit function. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ anim <- ggplot(airquality, aes(Day, Temp)) + geom_point(aes(colour = factor(Month))) + transition_time(Day) # Removing a time point will prolong the tweening between neighbouring time # points so the time dimension stays linear airquality_missing <- airquality[airquality$Day <= 10 | airquality$Day >= 20, ] anim1 <- ggplot(airquality_missing, aes(Day, Temp)) + geom_point(aes(colour = factor(Month))) + transition_time(Day) # Range can be constrained if needed anim2 <- ggplot(airquality, aes(Day, Temp)) + geom_point(aes(colour = factor(Month))) + transition_time(Day, range = c(10L, 20L)) # The group aesthetic is used to connect elements # No grouping anim3 <- ggplot(airquality, aes(Day, Temp)) + geom_line() + transition_time(Month) # Group by month anim4 <- ggplot(airquality, aes(Day, Temp)) + geom_line(aes(group = Month)) + transition_time(Month) + enter_fade() + exit_fade() } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()} } \concept{transitions} gganimate/man/transition_states.Rd0000644000176200001440000000752113611331661017033 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-states.R \name{transition_states} \alias{transition_states} \title{Transition between several distinct stages of the data} \usage{ transition_states(states, transition_length = 1, state_length = 1, wrap = TRUE) } \arguments{ \item{states}{The unquoted name of the column holding the state levels in the data.} \item{transition_length}{The relative length of the transition. Will be recycled to match the number of states in the data} \item{state_length}{The relative length of the pause at the states. Will be recycled to match the number of states in the data} \item{wrap}{Should the animation \emph{wrap-around}? If \code{TRUE} the last state will be transitioned into the first.} } \description{ This transition splits your data into multiple states based on the levels in a given column, much like \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}} splits up the data in multiple panels. It then tweens between the defined states and pauses at each state. Layers with data without the specified column will be kept constant during the animation (again, mimicking \code{facet_wrap}). } \section{Label variables}{ \code{transition_states} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{transitioning} is a boolean indicating whether the frame is part of the transitioning phase \item \strong{previous_state} The name of the last state the animation was at \item \strong{closest_state} The name of the state closest to this frame \item \strong{next_state} The name of the next state the animation will be part of } } \section{Object permanence}{ \code{transition_states} uses the group aesthetic of each layer to identify which rows in the input data correspond to the same graphic element and will therefore define which elements will turn into each other between states. The group aesthetic, if not set, will be calculated from the interaction of all discrete aesthetics in the layer (excluding \code{label}), so it is often better to set it explicetly when animating, to make sure your data is interpreted in the right way. If the group aesthetic is not set, and no discrete aesthetics exists then all rows will have the same group. If the group aesthetic is not unique in each state, then rows will be matched first by group and then by index. Unmatched rows will appear/disappear, potentially using an enter or exit function. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ anim <- ggplot(iris, aes(Sepal.Width, Petal.Width)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 3, state_length = 1) # Use a unique group to avoid matching graphic elements iris$group <- seq_len(nrow(iris)) anim1 <- ggplot(iris, aes(Sepal.Width, Petal.Width, group = group)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 3, state_length = 1) + enter_fade() + exit_fade() # Set `wrap = FALSE` to avoid transitioning the last state to the first anim2 <- ggplot(iris, aes(Sepal.Width, Petal.Width)) + geom_point() + labs(title = "{closest_state}") + transition_states(Species, transition_length = 3, state_length = 1, wrap = FALSE) } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/view_static.Rd0000644000176200001440000000063013611331661015571 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/view-static.R \name{view_static} \alias{view_static} \title{Keep a fixed view that include all of the data} \usage{ view_static() } \description{ This view keeps positional scales fixed across all frames } \seealso{ Other views: \code{\link{view_follow}()}, \code{\link{view_step}()}, \code{\link{view_zoom}()} } \concept{views} gganimate/man/figures/0000755000176200001440000000000013406124664014433 5ustar liggesusersgganimate/man/figures/README-unnamed-chunk-4-1.gif0000644000176200001440000320366413413420646021124 0ustar liggesusersGIF89a à€!ÿ NETSCAPE2.0!ù 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Fp†£a(~jb¢ͨF¹a­zô£ ©HGJÒ’šô¤(µD2ÉÒ–º´…Ж,‡`šÚô¦8Í©NwÊÓžúô§@ ªP‡ªS èX?`A–ÊÔ¦:õ©PªT§JU§Š UÿͪV·ÊÕ¥!¥` «XÇJÖ²šõ¬hM«Z×ÊÖ¶ºõ­p«\çJ׺Úõ®®!RT‡×¾úõ¯€ ¬`KØÂö°ˆM¬bËØÆ:ö±¬d'KÙÊZö²S©áZ5«VΦճhÝ „†ÙÒšö´¨M- 1º+¾ª–ç{­l9ÀÙÚö¶¸Í­nwËÛÞÖÂ=¾ .Nb+Üâ·+®¥øŽ ‘äÖ)\L©sYŸŽúIºÓ5$t³ËÝîz÷»àÍ ¤ÂKÞ>+cÀ€*ô*»×|VQ$Ö¦¬%»/5×»ŠåJ“¿¯°~' `I¨o£6ßáÜl&8Ö5Ä$€ ±Ýh>xžð"4¬ˆñN³ÁŽ nyGLâ›øÄ(Nñ‚;gganimate/man/sprite_file.Rd0000644000176200001440000000242413406166235015565 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/renderers.R \name{sprite_file} \alias{sprite_file} \alias{print.sprite_image} \alias{knit_print.sprite_image} \title{Wrap an image sprite for easy handling} \usage{ sprite_file(file, fps, width, full_width, height) \method{print}{sprite_image}(x, width = NULL, ...) knit_print.sprite_image(x, options, ...) } \arguments{ \item{file}{A png file with frames placed horizontally} \item{fps}{The framerate for the sprite animation} \item{width, height}{The dimension of a single frame} \item{full_width}{The width of the whole image} \item{x}{A \code{sprite_image} object} \item{...}{Arguments passed on} } \value{ \code{sprite_file} returns a \code{sprite_image} object which is a shallow wrapper around the file path text string along with dimensions and fps used for animating the sprite when printing. } \description{ This function is equivalent to \code{\link[=gif_file]{gif_file()}} but works for animations encoded as a sprite. A sprite is a single image file where each frame of the animation is stacked next to each other. The animation then happens by changing what slice of the image is shown. The implementation used allow users to click on the animation in order to toggle pause/play. } \keyword{internal} gganimate/man/gganimate-ggproto.Rd0000644000176200001440000000244113405665100016664 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/gganimate-ggproto.R, R/shadow-.R, % R/shadow-mark.R, R/shadow-null.R, R/shadow-trail.R, R/shadow-wake.R, % R/transition-.R, R/transition-components.R, R/transition-events.R, % R/transition-filter.R, R/transition-manual.R, R/transition-layers.R, % R/transition-null.R, R/transition-states.R, R/transition-time.R, % R/transition_reveal.R, R/view-.R, R/view-follow.R, R/view-step.R, % R/view-step-manual.R, R/view-zoom.R, R/view-zoom-manual.R \docType{data} \name{gganimate-ggproto} \alias{gganimate-ggproto} \alias{Shadow} \alias{ShadowMark} \alias{ShadowNull} \alias{ShadowTrail} \alias{ShadowWake} \alias{Transition} \alias{TransitionComponents} \alias{TransitionEvents} \alias{TransitionFilter} \alias{TransitionManual} \alias{TransitionLayers} \alias{TransitionNull} \alias{TransitionStates} \alias{TransitionTime} \alias{TransitionReveal} \alias{View} \alias{ViewFollow} \alias{ViewStep} \alias{ViewStepManual} \alias{ViewZoom} \alias{ViewZoomManual} \title{Base ggproto classes for gganimate} \description{ If you are creating a new transition, view, etc. in another package, you'll need to extend from some of the ggproto classes defined in \code{gganimate} } \seealso{ ggproto } \keyword{datasets} \keyword{internal} gganimate/man/animate.Rd0000644000176200001440000001415413741642076014705 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/animate.R, R/gganim.R \name{animate} \alias{animate} \alias{animate.gganim} \alias{print.gganim} \alias{knit_print.gganim} \title{Render a gganim object} \usage{ animate(plot, ...) \method{animate}{gganim}( plot, nframes, fps, duration, detail, renderer, device, ref_frame, start_pause, end_pause, rewind, ... ) \method{print}{gganim}(x, ...) knit_print.gganim(x, options, ...) } \arguments{ \item{plot, x}{A \code{gganim} object} \item{...}{Arguments passed on to the device. For available device arguments, see \code{\link[grDevices:png]{grDevices::png()}} or \code{\link[grDevices:cairo]{grDevices::svg()}}} \item{nframes}{The number of frames to render (default \code{100})} \item{fps}{The framerate of the animation in frames/sec (default \code{10})} \item{duration}{The length of the animation in seconds (unset by default)} \item{detail}{The number of additional frames to calculate, per frame (default \code{1})} \item{renderer}{The function used to render the generated frames into an animation. Gets a vector of paths to images along with the framerate. (default \code{\link[=gifski_renderer]{gifski_renderer()}})} \item{device}{The device to use for rendering the single frames. Possible values are \code{'png'}, \code{'ragg_png'} (requires the ragg package), \code{'jpeg'}, \code{'tiff'}, \code{'bmp'}, \code{'svg'}, and \code{'svglite'} (requires the svglite package). (default \code{'png'})} \item{ref_frame}{The frame to use for fixing dimensions of the plot, e.g. the space available for axis text. Defaults to the first frame. Negative values counts backwards (-1 is the last frame) (default \code{1})} \item{start_pause, end_pause}{Number of times to repeat the first and last frame in the animation (default is \code{0} for both)} \item{rewind}{Should the animation roll back in the end (default \code{FALSE})} \item{options}{chunk options for the currently executing chunk} } \value{ The return value of the \link[=renderers]{renderer} function } \description{ This function takes a gganim object and renders it into an animation. The nature of the animation is dependent on the renderer, but defaults to using \code{gifski} to render it to a gif. The length and framerate is decided on render time and can be any two combination of \code{nframes}, \code{fps}, and \code{duration}. Rendering is happening in discrete time units. This means that any event in the animation is rounded of to the nearest frame (e.g. entering will always take a whole number of frames). This means that rounding artifacts are possible when only rendering few frames. To avoid this you can increase the \code{detail} argument. \code{detail} will get multiplied to \code{nframes} and the resulting number of frames will get calculated, but only \code{nframes} evenly spaced frames are rendered. } \details{ \code{print.gganim}() is an alias for \code{animate()} in the same way as \code{print.ggplot()} is an alias for \code{plot.ggplot()}. This ensures that gganimate behaves ggplot2-like and produces the animation when the object is printed. The \code{plot()} method is different and produces a single frame for inspection (by default frame 50 out of 100). Animations can be saved to disk using \code{\link[=anim_save]{anim_save()}} in much the same way \link[ggplot2:ggsave]{ggsave()} works for static plots. } \section{Defaults}{ It is possible to overwrite the defaults used by gganimate for the animation by setting them with \code{\link[=options]{options()}} (prefixed with \code{gganimate.}. As an example, if you would like to change the default nframes to 50 you would call \code{options(gganimate.nframes = 50)}. In order to set default device arguments (those you would normally pass through with \code{...}) you should use the \code{gganimate.dev_args} options and provide a list of arguments e.g. \code{options(gganimate.dev_args = list(width = 800, height = 600))} Defaults set this way can still be overridden by giving arguments directly to \code{animate()}. \strong{knitr Support:} \cr It is possible to specify the arguments to \code{animate()} in the chunk options when using \code{gganimate} with \code{knitr}. Arguments specified in this way will have precedence over defaults, but not over arguments specified directly in \code{animate()}. The arguments should be provided as a list to the \code{gganimate} chunk option, e.g. \verb{\{r, gganimate = list(nframes = 50, fps = 20)\}}. A few build-in knitr options have relevance for animation and will be used unless given specifically in the \code{gganimate} list option. The native knitr options supported are: \itemize{ \item \code{dev}: will set \code{device} \item \code{dev.args}: will set additional arguments to the device (\code{...}) \item \code{fig.width}, \code{fig.height}, \code{fig.asp}, \code{fig.dim}: will set \code{width} and \code{height} of the device. } } \section{Label variables}{ All plots have a certain set of variables available for string literal interpolation within plot labels. These are: \itemize{ \item \strong{frame} gives you the frame index for the current frame \item \strong{nframes} gives you the total number of frames in the animation \item \strong{progress} gives you the progress of the animation at the current frame (equal to \code{frame/nframes}) \item \strong{data} gives you the layer data for the current frame (as a list of data frames) } Further, the transition and view in use can also make variables available. Consult the documentation for these for more detail. } \examples{ anim <- ggplot(mtcars, aes(mpg, disp)) + transition_states(gear, transition_length = 2, state_length = 1) + enter_fade() + exit_fade() \dontrun{ # Explicitly animate using default (same as just printing the animation) animate(anim) # Change duration and framerate animate(anim, fps = 20, duration = 15) # Make the animation pause at the end and then rewind animate(anim, nframes = 100, end_pause = 10, rewind = TRUE) # Use a different renderer animate(anim, renderer = file_renderer('~/animation/'))[1:6] # Specify device dimensions and/or resolution animate(anim, height = 2, width = 3, units = "in", res = 150) } } gganimate/man/tween_before_stat.Rd0000644000176200001440000000061413405665100016750 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/tween_before_stat.R \name{tween_before_stat} \alias{tween_before_stat} \title{Define if layers should be tweened before stats are calculated} \usage{ tween_before_stat(x) } \arguments{ \item{x}{a Layer, Geom, or Stat} } \description{ Define if layers should be tweened before stats are calculated } \keyword{internal} gganimate/man/transition_manual.Rd0000644000176200001440000000452513611331661017006 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-manual.R \name{transition_manual} \alias{transition_manual} \title{Create an animation by specifying the frame membership directly} \usage{ transition_manual(frames, ..., cumulative = FALSE) } \arguments{ \item{frames}{The unquoted name of the column holding the frame membership.} \item{...}{Additional variables} \item{cumulative}{Keep data from previous frames as part of the current frame data} } \description{ This transition allows you to map a variable in your data to a specific frame in the animation. No tweening of data will be made and the number of frames in the animation will be decided by the number of levels in the frame variable. } \section{Label variables}{ \code{transition_states} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{previous_frame} The name of the last frame the animation was at \item \strong{current_frame} The name of the current frame \item \strong{next_frame} The name of the next frame in the animation } } \section{Object permanence}{ \code{transition_manual} does not link rows across data to the same graphic element. Every frame is a discrete state and no animation between the states is done. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ anim <- ggplot(mtcars, aes(factor(gear), mpg)) + geom_boxplot() + transition_manual(gear) # Using `cumulative = TRUE` to keep data from older frames anim2 <- ggplot(mtcars, aes(factor(gear), mpg)) + geom_boxplot() + transition_manual(gear, cumulative = TRUE) # Use `factor()` to set the order of the frames anim3 <- ggplot(mtcars, aes(factor(gear), mpg)) + geom_boxplot() + transition_manual(factor(gear, levels = c('4', '3', '5'))) } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/gganimate.Rd0000644000176200001440000000044513405665100015207 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/animate.R \name{gganimate} \alias{gganimate} \alias{gg_animate} \title{Catch attempt to use the old API} \usage{ gganimate(...) gg_animate(...) } \description{ Catch attempt to use the old API } \keyword{internal} gganimate/man/transition_events.Rd0000644000176200001440000000457413611331661017041 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-events.R \name{transition_events} \alias{transition_events} \title{Transition individual events in and out} \usage{ transition_events( start, end = NULL, range = NULL, enter_length = NULL, exit_length = NULL ) } \arguments{ \item{start, end}{The unquoted expression giving the start and end time of each event. If \code{end}is \code{NULL} the event will be treated as having no duration.} \item{range}{The range the animation should span. Defaults to the range of the events from they enter to they have exited.} \item{enter_length, exit_length}{The unquoted expression giving the length to be used for enter and exit for each event.} } \description{ This transition treats each visual element as an event in time and allows you to control the duration and enter/exit length individually for each event. } \section{Label variables}{ \code{transition_components} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{frame_time} gives the time that the current frame corresponds to } } \section{Object permanence}{ \code{transition_events} does not link rows across data to the same graphic element, so elements will be defined uniquely by each row and its specific start, end, enter and exit. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ data <- data.frame( x = 1:10, y = runif(10), begin = runif(10, 1, 100), length = runif(10, 5, 20), enter = runif(10, 5, 10), exit = runif(10, 5, 10) ) anim <- ggplot(data, aes(x, y)) + geom_col() + transition_events(start = begin, end = begin + length, enter_length = enter, exit_length = exit) + enter_grow() + exit_drift(x_mod = 11) + exit_fade() } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/transition_reveal.Rd0000644000176200001440000000644413611331661017011 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition_reveal.R \name{transition_reveal} \alias{transition_reveal} \title{Reveal data along a given dimension} \usage{ transition_reveal(along, range = NULL, keep_last = TRUE, id) } \arguments{ \item{along}{An unquoted expression giving the dimension to tween along. For a gradually revealing time series this should be set to the same as the \code{x} aesthetic.} \item{range}{The time range to animate. If \code{NULL} it will be set to the range of \code{along}} \item{keep_last}{For non-path/polygon layers should the last row be kept for subsequent frames.} \item{id}{\strong{Deprecated}} } \description{ This transition allows you to let data gradually appear, based on a given time dimension. In contrast to e.g. \code{\link[=transition_time]{transition_time()}} \code{transition_reveal()} calculates intermediary values at exact positions instead of coercing raw values into the closest frame. It further keeps old data for path and polygon type layers so that they are gradually build up instead of being a set of disconnected segments as will happen when using \code{\link[=transition_time]{transition_time()}} and \code{\link[=shadow_mark]{shadow_mark()}} together. } \section{Label variables}{ \code{transition_along} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{frame_along} gives the position on the along-dimension that the current frame corresponds to } } \section{Object permanence}{ \code{transition_reveal} uses the group aesthetic of each layer to identify which rows in the input data correspond to the same graphic element and will therefore define a a whole to be revealed over the animation. The group aesthetic, if not set, will be calculated from the interaction of all discrete aesthetics in the layer (excluding \code{label}), so it is often better to set it explicetly when animating, to make sure your data is interpreted in the right way. If the group aesthetic is not set, and no discrete aesthetics exists then all rows will have the same group. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ anim <- ggplot(airquality, aes(Day, Temp, group = Month)) + geom_line() + transition_reveal(Day) # Non-paths will only show the current position, not the history anim1 <- ggplot(airquality, aes(Day, Temp, group = Month)) + geom_line() + geom_point(colour = 'red', size = 3) + transition_reveal(Day) # Points can be kept by giving them a unique group and set `keep = TRUE` (the # default) anim2 <- ggplot(airquality, aes(Day, Temp, group = Month)) + geom_line() + geom_point(aes(group = seq_along(Day))) + geom_point(colour = 'red', size = 3) + transition_reveal(Day) } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_filter}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/transition_filter.Rd0000644000176200001440000001030313611331661017005 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/transition-filter.R \name{transition_filter} \alias{transition_filter} \title{Transition between different filters} \usage{ transition_filter( transition_length = 1, filter_length = 1, ..., wrap = TRUE, keep = FALSE ) } \arguments{ \item{transition_length}{The relative length of the transition. Will be recycled to match the number of states in the data} \item{filter_length}{The relative length of the pause at the states. Will be recycled to match the number of states in the data} \item{...}{A number of expressions to be evaluated in the context of the layer data, returning a logical vector. If the expressions are named, the name will be available as a frame variable.} \item{wrap}{Should the animation \emph{wrap-around}? If \code{TRUE} the last filter will be transitioned into the first.} \item{keep}{Should rows that evaluates to \code{FALSE} be kept in the data as it looks after exit has been applied} } \description{ This transition allows you to transition between a range of filtering conditions. The conditions are expressed as logical statements and rows in the data will be retained if the statement evaluates to \code{TRUE}. It is possible to keep filtered data on display by setting \code{keep = TRUE} which will let data be retained as the result of the exit function. Note that if data is kept the enter function will have no effect. } \section{Label variables}{ \code{transition_filter} makes the following variables available for string literal interpretation, in addition to the general ones provided by \code{\link[=animate]{animate()}}: \itemize{ \item \strong{transitioning} is a boolean indicating whether the frame is part of the transitioning phase \item \strong{previous_filter} The name of the last filter the animation was at \item \strong{closest_filter} The name of the filter closest to this frame \item \strong{next_filter} The name of the next filter the animation will be part of \item \strong{previous_expression} The expression of the last filter the animation was at \item \strong{closest_expression} The expression of the filter closest to this frame \item \strong{next_expression} The expression of the next filter the animation will be part of } } \section{Object permanence}{ \code{transition_filter} does not link rows across data to the same graphic element, so elements will be defined uniquely by each row. If \code{keep = TRUE} the rows not matching the conditions of a filter is not removed from the plot after the exit animation, and a possible subsequent enter will begin from the state they were left in, rather than enter anew from the state defined by the enter function. } \section{Computed Variables}{ It is possible to use variables calculated by the statistic to define the transition. Simply inclose the variable in \code{stat()} in the same way as when using computed variables in aesthetics. } \examples{ anim <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) + geom_point() + transition_filter( transition_length = 2, filter_length = 1, Setosa = Species == 'setosa', Long = Petal.Length > 4, Wide = Petal.Width > 2 ) + ggtitle( 'Filter: {closest_filter}', subtitle = '{closest_expression}' ) + enter_fade() + exit_fly(y_loc = 0) # Setting `keep = TRUE` allows you to keep the culled data on display. Only # exit functions will be used in that case (as elements enters from the # result of the exit function) anim2 <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) + geom_point() + transition_filter( transition_length = 2, filter_length = 1, Setosa = Species == 'setosa', Long = Petal.Length > 4, Wide = Petal.Width > 2, keep = TRUE ) + ggtitle( 'Filter: {closest_filter}', subtitle = '{closest_expression}' ) + exit_recolour(colour = 'grey') + exit_shrink(size = 0.5) } \seealso{ Other transitions: \code{\link{transition_components}()}, \code{\link{transition_events}()}, \code{\link{transition_layers}()}, \code{\link{transition_manual}()}, \code{\link{transition_null}()}, \code{\link{transition_reveal}()}, \code{\link{transition_states}()}, \code{\link{transition_time}()} } \concept{transitions} gganimate/man/split_animation.Rd0000644000176200001440000000216513405665100016446 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/post_process.R \name{split_animation} \alias{split_animation} \title{Split an animation into chunks} \usage{ split_animation(animation = last_animation(), by) } \arguments{ \item{animation}{The animation to extract metadata from. Defaults to the last rendered animation} \item{by}{An unquoted expression to be evaluated in the context of the frame metadata. The result must be of equal length to the number of frames in the animation and define a grouping} } \value{ Depending on the output type of the renderer used to produce the animation. Often a list with elements referencing the chunks of the animation. that can then be saved individually. } \description{ Sometimes it is of interest to split an animation out in smaller chunks so they can be orchestrated, e.g. in a presentation. This function lets you provide a 'factor' to split by in the same way as \code{\link[base:split]{base::split()}} though this one will be evaluated in the context of the animations \code{\link[=frame_vars]{frame_vars()}} data, so you can split directly on frame metadata. } gganimate/DESCRIPTION0000644000176200001440000000464013741753531013731 0ustar liggesusersPackage: gganimate Type: Package Title: A Grammar of Animated Graphics Version: 1.0.7 Authors@R: c(person("Thomas Lin", "Pedersen", email = "thomasp85@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5147-4711")), person("David", "Robinson", email = "admiral.david@gmail.com", role = c("aut")), person("RStudio", role = "cph")) Maintainer: Thomas Lin Pedersen Description: The grammar of graphics as implemented in the 'ggplot2' package has been successful in providing a powerful API for creating static visualisation. In order to extend the API for animated graphics this package provides a completely new set of grammar, fully compatible with 'ggplot2' for specifying transitions and animations in a flexible and extensible way. License: MIT + file LICENSE Encoding: UTF-8 LazyData: TRUE VignetteBuilder: knitr RoxygenNote: 7.1.1 URL: https://gganimate.com, https://github.com/thomasp85/gganimate BugReports: https://github.com/thomasp85/gganimate/issues Depends: ggplot2 (>= 3.0.0) Imports: stringi, tweenr (>= 1.0.1), grid, rlang, glue, progress, plyr, scales, grDevices, utils Suggests: magick, svglite, knitr, rmarkdown, testthat, base64enc, htmltools, covr, transformr, av, gifski, ragg Collate: 'aaa.R' 'anim_save.R' 'animate.R' 'animation_store.R' 'ease-aes.R' 'gganim.R' 'gganimate-ggproto.R' 'gganimate-package.r' 'ggplot2_reimpl.R' 'group_column.R' 'layer_type.R' 'match_shapes.R' 'plot-build.R' 'post_process.R' 'renderers.R' 'scene.R' 'shadow-.R' 'shadow-mark.R' 'shadow-null.R' 'shadow-trail.R' 'shadow-wake.R' 'transformr.R' 'transition-.R' 'transition-components.R' 'transition-events.R' 'transition-filter.R' 'transition-manual.R' 'transition-layers.R' 'transition-null.R' 'transition-states.R' 'transition-time.R' 'transition_reveal.R' 'transmute-.R' 'transmute-enter.R' 'transmute-exit.R' 'transmuters.R' 'tween_before_stat.R' 'view-.R' 'view-follow.R' 'view-static.R' 'view-step.R' 'view-step-manual.R' 'view-zoom.R' 'view-zoom-manual.R' 'zzz.R' NeedsCompilation: no Packaged: 2020-10-14 21:38:13 UTC; thomas Author: Thomas Lin Pedersen [aut, cre] (), David Robinson [aut], RStudio [cph] Repository: CRAN Date/Publication: 2020-10-15 05:00:09 UTC gganimate/build/0000755000176200001440000000000013741667704013324 5ustar liggesusersgganimate/build/vignette.rds0000644000176200001440000000032013741667704015656 0ustar liggesusers‹mPÁ‚0 ÝQ0¨ ?àð^ zðºÈÄ%l˜Ñ„xóËÅ¢ 0mÒ®ë{¯kwô !q%–©bpÑWèëžAž3%$¥23À冕¯÷À4p^|µ…ÎqŽð½)hŽ5 N“¼2ôÓ˜_¹ÊÚòã¿ž6†d¶å·ºÔ½fÄq;Ž“ˆ‚÷ï|.ö.Nº”¦æ ?ýGó{º¬£~‡ ýõ;†Í\ôT°Ê\ÔÏ°è¬QßÎý5›R„·gganimate/tests/0000755000176200001440000000000013405665100013350 5ustar liggesusersgganimate/tests/testthat/0000755000176200001440000000000013741753531015221 5ustar liggesusersgganimate/tests/testthat/test-anim_save.R0000644000176200001440000000115213564330302020250 0ustar liggesuserscontext("test-anim_save") test_that("anim_save overwrites existing files", { skip_on_os('solaris') # gifski not available p <- ggplot(airquality, aes(Day, Temp)) + geom_line(color = 'red', size = 1) + transition_time(Month) capture.output({ a1 <- animate(p, nframes = 2) a2 <- animate(p, nframes = 3) }) tf <- tempfile() on.exit(unlink(tf)) anim_save(a1, file = tf) frames_1 <- nrow(magick::image_info(magick::image_read(tf))) expect_equal(frames_1, 2) anim_save(a2, file = tf) frames_2 <- nrow(magick::image_info(magick::image_read(tf))) expect_equal(frames_2, 3) }) gganimate/tests/testthat/test-transition-states.R0000644000176200001440000000312513701153453022006 0ustar liggesuserscontext("transition-states") test_that("area works", { set.seed(1) df <- data.frame( x = c(1:10, 1:10), y = runif(20), f = rep(c('a', 'b'), each = 10) ) p <- ggplot(df) + geom_area(aes(x, y)) + transition_states(f, 2, 1) expect_silent(prerender(p, 50)) }) test_that('bar works', { set.seed(1) df <- data.frame( x = sample(letters[1:5], 20, replace = TRUE), f = rep(c('a', 'b'), each = 10) ) p <- ggplot(df) + geom_bar(aes(x)) + transition_states(f, 2, 1) expect_silent(prerender(p, 50)) }) test_that('bin2d works', { set.seed(1) df <- data.frame( x = c(rnorm(100), runif(100)), y = c(rnorm(100), runif(100)), f = rep(c('a', 'b'), each = 100) ) p <- ggplot(df) + geom_bin2d(aes(x, y), drop = FALSE) + transition_states(f, 2, 1) expect_silent(prerender(p, 50)) }) test_that('boxplot works', { p <- ggplot(mtcars) + geom_boxplot(aes(factor(cyl), mpg)) + transition_states(gear, 2, 1) expect_silent(prerender(p, 50)) }) test_that('col works', { df <- data.frame( x = c(1:5, 1:5), y = c(1:5, 5:1), f = rep(c('a', 'b'), each = 5) ) p <- ggplot(df) + geom_col(aes(x, y)) + transition_states(f, 2, 1) expect_silent(prerender(p, 50)) }) test_that('contour works', { # Investigate why this fails on some architectures skip_on_cran() df <- data.frame( x = rep(rep(1:10, each = 10), 2), y = rep(rep(1:10, 10), 2), z = c(volcano[1:10, 1:10], volcano[21:30, 21:30]), f = rep(c('a', 'b'), each = 100) ) p <- ggplot(df) + geom_contour(aes(x, y, z = z)) + transition_states(f, 2, 1) expect_silent(prerender(p, 50)) }) gganimate/tests/testthat.R0000644000176200001440000000007613405665100015336 0ustar liggesuserslibrary(testthat) library(gganimate) test_check("gganimate") gganimate/vignettes/0000755000176200001440000000000013741667705014236 5ustar liggesusersgganimate/vignettes/gganimate.Rmd0000644000176200001440000002532613741667356016650 0ustar liggesusers--- title: "Getting Started" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Getting Started} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", gganimate = list( nframes = 50 ), out.width = '100%' ) ``` *gganimate* is an extension of the *grammar of graphics*, as implemented by the [*ggplot2*](https://ggplot2.tidyverse.org) package, that adds support for declaring animations using an API familiar to users of *ggplot2*. > The following introduction assumes familiarity with *ggplot2* to the extend that constructing static plots and reading standard *ggplot2* code feels natural. If you are new to both *ggplot2* and *gganimate* you'll benefit from exploring the trove of *ggplot2* documentation, tutorials, and courses available online first (see the [*ggplot2* webpage](https://ggplot2.tidyverse.org/#learning-ggplot2) for some pointers). ## Your First Animation We'll jump right into our first animation. Don't worry too much about understanding the code, as we'll dissect it later. ```{r} library(gganimate) # We'll start with a static plot p <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point() plot(p) ``` You go from a static plot made with *ggplot2* to an animated one, simply by adding on functions from *gganimate*. ```{r} anim <- p + transition_states(Species, transition_length = 2, state_length = 1) anim ``` > â— `transition_states()` splits up plot data by a discrete variable and animates between the different states. As can be seen, very few additions to the plot results in a quite complex animation. So what did we do to get this animation? We added a type of *transition*. Transitions are functions that interpret the plot data in order to somehow distribute it over a number of frames. `transition_states()` specifically splits the data into subsets based on a variable in the data (here `Species`), and calculates intermediary data states that ensures a smooth transition between the states (something referred to as *tweening*). *gganimate* provides a range of different transitions, but for the rest of the examples we'll be sticking to `transition_states()` and see how we can modify the output. ## Easing When `transition_states()` calculates intermediary data for the tweening, it needs to decide how the change from one value to another should progress. This is a concept called *easing*. The default easing is *linear*, but others can be used, potentially only targeting specific aesthetics. Setting easing is done with the `ease_aes()` function. The first argument sets the default easing and subsequent named arguments sets it for specific aesthetics. ```{r} anim + ease_aes('cubic-in-out') # Slow start and end for a smoother look ``` > â— `ease_aes()` defines the velocity with which aesthetics change during an animation. ```{r} anim + ease_aes(y = 'bounce-out') # Sets special ease for y aesthetic ``` ## Labeling It can be quite hard to understand an animation without any indication as to what each time point relates to. *gganimate* solves this by providing a set of variables for each frame, which can be inserted into plot labels using [*glue*](https://glue.tidyverse.org) syntax. ```{r} anim + ggtitle('Now showing {closest_state}', subtitle = 'Frame {frame} of {nframes}') ``` > â— Use *glue* syntax to insert frame variables in plot labels and titles. Different transitions provide different frame variables. `closest_state` only makes sense for `transition_states()` and is thus only available when that transition is used. ## Object Permanence In the animation above, it appears as if data in a single measurement changes gradually as the flower being measured on somehow morphs between three different iris species. This is probably not how Fisher conducted the experiment and got those numbers. In general, when you make an animation, *graphic elements should only transition between instances of the same underlying phenomenon*. This sounds complicated but it is more or less the same principle that governs makes sense to draw a line between two observations. You wouldn't connect observations from different iris species, but repeated observations on the same plant would be fine to connect. Same thing with animations. Just to make this very clear (it is an important concept). The line plot equivalent of our animation above is: ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_line(aes(group = rep(1:50, 3)), colour = 'grey') + geom_point() ``` Ugh... So, how do we fix this and tell *gganimate* to not morph observations from different species into each others? The key is the *group aesthetic*. You may be familiar with this aesthetic from plotting lines and polygons, but in *gganimate* it takes a more central place. Data that have the same group aesthetic are interpreted as being linked across states. The semantics of the group aesthetic in *ggplot2* is such that if it is undefined it will get calculated based on the interaction of all discrete aesthetics (sans `label`). If none exists, such as in our iris animation, all data will get the same group, and will thus be matched by *gganimate*. So, there are two ways to fix our plot: 1. Add some aesthetics that distinguish the different species ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species)) + transition_states(Species, transition_length = 2, state_length = 1) ``` 2. Set the group directly ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(group = seq_along(Species))) + transition_states(Species, transition_length = 2, state_length = 1) ``` > â— The group aesthetic defines how the data in a layer is matched across the animation. In general *2)* is preferred as it makes the intend explicit. It also makes it possible to match data with different discrete aesthetics such as keeping our (now obviously faulty) transition while having different colour for the different species) ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species, group = 1L)) + transition_states(Species, transition_length = 2, state_length = 1) ``` ## Enter and Exit While we may have made our animation more correct by separating the data from the different species, we have also made it quite a bit more boring. Now it simply appears as three static plots shown one at a time, which is hardly an attention grabber. If only there were a way to animate the appearance and disappearance of data... Enter the `enter` and `exit` functions. These functions are responsible for modifying the state of appearing (entering) and disappearing (exiting) data, so that the animation can tween from and to the new state. Let's spice up our animation a bit: ```{r} anim <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species), size = 2) + transition_states(Species, transition_length = 2, state_length = 1) anim + enter_fade() + exit_shrink() ``` > â— `enter` and `exit` functions are used to modify the aesthetics of appearing and disappearing data so that their entrance or exit may be animated. *gganimate* comes with a range of different functions, and using the `enter_manual()` and `exit_manual()` functions you can create your own. Enter and exit functions are composable though, so you can often come pretty far by combining preexisting ones ```{r} anim + enter_fade() + enter_drift(x_mod = -1) + exit_shrink() + exit_drift(x_mod = 5) ``` ## Rendering In the examples above the animations has simply appeared when we printed the animation object, just like we would expect from *ggplot2*. As a lot of things are happening automatically, and you might want to take control, this section will give a brief overview of the rendering. *gganimate*'s model for an animation is dimensionless in the same way as *ggplot2* describe plots independent of the final width and height of the plot. This means that the final number of frames and its frame-rate are only ever given when you ask *gganimate* to render the animation. When you print an animation object the `animate()` function is called on the animation with default arguments, some of which are: - **nframes** sets the number of frames (defaults to `100`) - **fps** sets the number of frames (defaults to `10`) - **dev** sets the device used to render each frame (defaults to `'png'`) - **renderer** sets the function used to combine each frame into an animate (defaults to `gifski_renderer()`) There are other arguments as well (e.g. `...` will be passed on to the device so you can set width, height, dpi, etc), but these are the most important. If you don't like the defaults you can either call `animate()` directly with values of your choosing, or modify the defaults by setting new with `options(gganimate. = )`. A topic that requires some additional words are the renderers. The default will use [gifski](https://github.com/r-rust/gifski) to combine the frames into a gif. gifs are great because they are virtually supported everywhere, and gifski is both a very fast, and very high quality converter. Still, you may have reasons to want a different output. *gganimate* is quite agnostic to how you want to combine the frames and, while it comes with a set of predefined renderers, any function that takes a vector of paths to image files along with a frame-rate, will do. The return value of your renderer is what is ultimately returned by the `animate()` function. Below are a couple of examples of different `animate()` calls: ```{r, eval=requireNamespace('av', quietly = TRUE)} # Video output animate( anim + enter_fade() + exit_fly(y_loc = 1), renderer = av_renderer() ) ``` ```{r, out.width=NULL} # Different size and resolution animate( anim + ease_aes(x = 'bounce-out') + enter_fly(x_loc = -1) + exit_fade(), width = 400, height = 600, res = 35 ) ``` If you need to save the animation for later use you can use the `anim_save()` function. It works much like `ggsave()` from *ggplot2* and automatically grabs the last rendered animation if you do not specify one directly. ## Want more? This guide is far from exhaustive, but have hopefully given you a broad understanding of how *gganimate* works. There are still more to explore as we have only scratched the surface of transitions, let alone mentioned views and shadows. But for now this is left to you. There is a fantastic joy in discovery and with the things you have now learned you are ready to go digging on your own. gganimate/vignettes/extra/0000755000176200001440000000000013405737007015347 5ustar liggesusersgganimate/vignettes/extra/talks.Rmd0000644000176200001440000000444513424040210017120 0ustar liggesusers--- title: "gganimate Talks" output: rmarkdown::html_vignette --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` This is an ever-growing list of talks I've given about *gganimate* in reverse chronological order: ### Rstudio::conf 2019 **Title:** gganimate Live Cookbook **Abstract:** Animation of data visualisation is becoming increasingly popular both as an attention grabber on social media and as a way to tell small data stories. gganimate is a package that extends ggplot2 for making animations and provides a grammar of animation on top of the grammar of graphics. This talk will quickly introduce gganimate, and then dive into a series of different animation and show how they were made and how they could be changed or expanded. **Slides:** https://data-imaginist.com/slides/rstudioconf2019 **Video:** https://resources.rstudio.com/rstudio-conf-2019/gganimate-live-cookbook ### useR 2018 **Title:** The Grammar of Animation **Abstract:** In the world of data visualisation much work has been put into defining a grammar for both static and interactive graphics. These efforts has often been coupled to the development of visualisation frameworks where the grammar has been reflected in the API design. Less attention has been devoted to a grammar of animation, and subsequently animation frameworks has often missed the breadth and composability that are the hallmark of grammar-driven visualisation frameworks. In this talk I will justify and present a grammar of animation and position it in relation to graphics and interactivity grammar, thus creating a clear division of responsibility between the three domains. I will present an R implementation of the grammar of animation which builds on top of the ggplot2 framework and made available as the gganimate package, Using examples with gganimate I'll show how the proposed grammar can be used to break down, and reason about, animated data visualisation, and how the grammar succinctly can describe very diverse animation operations. **Slides:** **Video:** gganimate/R/0000755000176200001440000000000013741641122012410 5ustar liggesusersgganimate/R/transition-events.R0000644000176200001440000002274413415135524016242 0ustar liggesusers#' Transition individual events in and out #' #' This transition treats each visual element as an event in time and allows you #' to control the duration and enter/exit length individually for each event. #' #' @param start,end The unquoted expression giving the start and end time of #' each event. If `end`is `NULL` the event will be treated as having no duration. #' @param range The range the animation should span. Defaults to the range of #' the events from they enter to they have exited. #' @param enter_length,exit_length The unquoted expression giving the length to #' be used for enter and exit for each event. #' #' @section Label variables: #' `transition_components` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **frame_time** gives the time that the current frame corresponds to #' #' @section Object permanence: #' `transition_events` does not link rows across data to the same graphic #' element, so elements will be defined uniquely by each row and its specific #' start, end, enter and exit. #' #' @inheritSection transition_states Computed Variables #' #' @family transitions #' #' @importFrom rlang enquo quo_is_null quo #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' data <- data.frame( #' x = 1:10, #' y = runif(10), #' begin = runif(10, 1, 100), #' length = runif(10, 5, 20), #' enter = runif(10, 5, 10), #' exit = runif(10, 5, 10) #' ) #' #' anim <- ggplot(data, aes(x, y)) + #' geom_col() + #' transition_events(start = begin, #' end = begin + length, #' enter_length = enter, #' exit_length = exit) + #' enter_grow() + #' exit_drift(x_mod = 11) + #' exit_fade() transition_events <- function(start, end = NULL, range = NULL, enter_length = NULL, exit_length = NULL) { start_quo <- enquo(start) end_quo <- enquo(end) enter_length_quo <- enquo(enter_length) exit_length_quo <- enquo(exit_length) require_quo(start_quo, 'start') ggproto(NULL, TransitionEvents, params = list( start_quo = start_quo, end_quo = end_quo, range = range, enter_length_quo = enter_length_quo, exit_length_quo = exit_length_quo ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_events TransitionEvents <- ggproto('TransitionEvents', Transition, mapping = '(.+?)_(.*?)_(.*?)_(.*?)', var_names = c('start', 'end', 'enter_length', 'exit_length'), setup_params = function(self, data, params) { params$start <- get_row_event(data, params$start_quo, 'start') time_class <- if (is_placeholder(params$start)) NULL else params$start$class params$end <- get_row_event(data, params$end_quo, 'end', time_class) params$enter_length <- get_row_event(data, params$enter_length_quo, 'enter_length', time_class) params$exit_length <- get_row_event(data, params$exit_length_quo, 'exit_length', time_class) params$require_stat <- is_placeholder(params$start) || is_placeholder(params$end) || is_placeholder(params$enter_length) || is_placeholder(params$exit_length) static = lengths(params$start$values) == 0 params$row_id <- Map(function(st, end, en, ex, s) if (s) character(0) else paste(st, end, en, ex, sep = '_'), st = params$start$values, end = params$end$values, en = params$enter_length$values, ex = params$exit_length$values, s = static) params }, setup_params2 = function(self, data, params, row_vars) { late_start <- FALSE if (is_placeholder(params$start)) { params$start <- get_row_event(data, params$start_quo, 'start', after = TRUE) late_start <- TRUE } else { params$start$values <- lapply(row_vars$start, as.numeric) } time_class <- params$start$class if (is_placeholder(params$end)) { params$end <- get_row_event(data, params$end_quo, 'end', time_class, after = TRUE) } else { params$end$values <- lapply(row_vars$end, as.numeric) } if (is_placeholder(params$enter_length)) { params$enter_length <- get_row_event(data, params$enter_length_quo, 'enter_length', time_class, after = TRUE) } else { params$enter_length$values <- lapply(row_vars$enter_length, as.numeric) } if (is_placeholder(params$exit_length)) { params$exit_length <- get_row_event(data, params$exit_length_quo, 'exit_length', time_class, after = TRUE) } else { params$exit_length$values <- lapply(row_vars$exit_length, as.numeric) } times <- recast_event_times(params$start, params$end, params$enter_length, params$exit_length) range <- if (is.null(params$range)) { low <- min(unlist(Map(function(start, enter) { start - (if (length(enter) == 0) 0 else enter) }, start = times$start$values, enter = times$enter_length$values))) high <- max(unlist(Map(function(start, end, exit) { (if (length(end) == 0) start else end) + (if (length(exit) == 0) 0 else exit) }, start = times$start$values, end = times$end$values, exit = times$exit_length$values))) range <- c(low, high) } else { if (!inherits(params$range, time_class)) { stop('range must be given in the same class as time', call. = FALSE) } as.numeric(params$range) } full_length <- diff(range) frame_time <- recast_times( seq(range[1], range[2], length.out = params$nframes), time_class ) frame_length <- full_length / params$nframes start <- lapply(times$start$values, function(x) { round((params$nframes - 1) * (x - range[1])/full_length) + 1 }) end <- lapply(times$end$values, function(x) { if (length(x) == 0) return(numeric()) round((params$nframes - 1) * (x - range[1])/full_length) + 1 }) enter_length <- lapply(times$enter_length$values, function(x) { if (length(x) == 0) return(numeric()) round(x / frame_length) }) exit_length <- lapply(times$exit_length$values, function(x) { if (length(x) == 0) return(numeric()) round(x / frame_length) }) params$range <- range params$frame_time <- frame_time static = lengths(start) == 0 params$row_id <- Map(function(st, end, en, ex, s) if (s) character(0) else paste(st, end, en, ex, sep = '_'), st = start, end = end, en = enter_length, ex = exit_length, s = static) params$frame_info <- data.frame( frame_time = frame_time ) params$nframes <- nrow(params$frame_info) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_vars <- self$get_row_vars(data) if (is.null(row_vars)) return(data) data$group <- paste0(row_vars$before, row_vars$after) start <- as.integer(row_vars$start) end <- as.integer(row_vars$end) if (is.na(end[1])) end <- NULL enter_length <- as.integer(row_vars$enter_length) if (is.na(enter_length[1])) enter_length <- NULL exit_length <- as.integer(row_vars$exit_length) if (is.na(exit_length[1])) exit_length <- NULL all_frames <- switch( type, point = tween_events(data, ease, params$nframes, !!start, !!end, c(1, params$nframes), enter, exit, !!enter_length, !!exit_length), stop(type, ' layers not currently supported by transition_events', call. = FALSE) ) all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) get_row_event <- function(data, quo, name, to_class = NULL, after = FALSE) { if (!after && require_stat(quo[[2]])) { return(eval_placeholder(data)) } row_event <- lapply(data, safe_eval, expr = quo) row_event <- standardise_times(row_event, name, to_class) names(row_event)[names(row_event) == 'times'] <- 'values' if (length(row_event$class) != 0) { row_event$range <- range(unlist(row_event$values)) if (diff(row_event$range) != 0) { row_event$values <- lapply(row_event$values, function(t) (t - row_event$range[1])/diff(row_event$range)) } } row_event } recast_event_times <- function(start, end, enter_length, exit_length, late_start) { start$values <- lapply(start$values, rescale_to, range = start$range) end$values <- lapply(end$values, rescale_to, range = end$range) enter_length$values <- lapply(enter_length$values, rescale_to, range = enter_length$range) exit_length$values <- lapply(exit_length$values, rescale_to, range = exit_length$range) real_class <- start$class if (real_class != 'difftime' && real_class != 'hms') { if (enter_length$class == 'difftime' || enter_length$class == 'hms') { enter_length <- standardise_times(lapply(enter_length$values, recast_times, enter_length$class), 'enter_length', real_class) names(enter_length)[names(enter_length) == 'times'] <- 'values' } if (exit_length$class == 'difftime' || exit_length$class == 'hms') { exit_length <- standardise_times(lapply(exit_length$values, recast_times, exit_length$class), 'exit_length', real_class) names(exit_length)[names(exit_length) == 'times'] <- 'values' } } if (length(unique(c(start$class, end$class, enter_length$class, exit_length$class))) != 1) { stop('start, end, enter_length, and exit_length must have the same class') } list( start = start, end = end, enter_length = enter_length, exit_length = exit_length ) } rescale_to <- function(x, range) { if (is.null(range)) return(NULL) if (diff(range) == 0) return(rep(range[1], length(x))) (x * diff(range)) + range[1] } gganimate/R/view-zoom-manual.R0000644000176200001440000000247213413127150015743 0ustar liggesusers#' @include view-step-manual.R #' @include view-zoom.R NULL #' @rdname view_zoom #' #' @param xmin,xmax,ymin,ymax Vectors of even length defining the boundaries of #' the different views to go through #' #' @export #' @importFrom ggplot2 ggproto view_zoom_manual <- function(pause_length = 1, step_length = 1, xmin, xmax, ymin, ymax, delay = 0, pan_zoom = 0, ease = 'sine-in-out', wrap = TRUE, pause_first = TRUE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1) { ggproto(NULL, ViewZoomManual, fixed_lim = list(x = fixed_x, y = fixed_y), exclude_layer = exclude_layer, aspect_ratio = aspect_ratio, params = list( pause_length = pause_length, step_length = step_length, windows = data.frame( xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax ), delay = delay, pan_zoom = exp(pan_zoom), ease = ease, wrap = wrap, pause_first = pause_first ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto ViewZoomManual <- ggproto('ViewZoomManual', ViewStepManual, window_transition = transition_window ) gganimate/R/layer_type.R0000644000176200001440000000111213405665100014702 0ustar liggesusers#' Define what graphical type a layer is #' #' @param x a Layer, Geom, or Stat #' @keywords internal #' @export layer_type <- function(x) UseMethod('layer_type') #' @export layer_type.default <- function(x) NULL #' @export layer_type.GeomPath <- function(x) 'path' #' @export layer_type.GeomRibbon <- function(x) 'path' #' @export layer_type.GeomSmooth <- function(x) 'path' #' @export layer_type.GeomPolygon <- function(x) 'polygon' #' @export layer_type.GeomSf <- function(x) 'sf' #' @export layer_type.Stat <- function(x) NULL #' @export layer_type.StatContour <- function(x) 'path' gganimate/R/gganimate-package.r0000644000176200001440000000162113405665100016117 0ustar liggesusers#' @importFrom rlang %||% #' @aliases gganimate-package #' #' @section Good starting points: #' The [animate()] function documentation describes how to specify how the #' animation is rendered, whereas the documentation for the different transition #' functions, e.g. [transition_states()], describe how to declare the animation. #' #' Both [ease_aes()] and the different [enter and exit][enter_exit] functions #' are good to understand in order to modify tweening of the animation. #' #' Apart from the included documentation there is also a few web ressources #' worth mentioning: #' #' - The [gganimate wiki](https://github.com/thomasp85/gganimate/wiki) includes #' user supplied example walkthroughs #' - The [learngganimate](https://github.com/ropenscilabs/learngganimate) project #' by rOpenSci Labs includes a long range of detailed explorations of the #' different gganimate functions #' '_PACKAGE' gganimate/R/group_column.R0000644000176200001440000000022413405665100015241 0ustar liggesusers#' @rdname layer_type #' #' @export group_column <- function(x) { UseMethod('group_column') } #' @export group_column.default <- function(x) NULL gganimate/R/transition-filter.R0000644000176200001440000002166013415135533016217 0ustar liggesusers#' Transition between different filters #' #' This transition allows you to transition between a range of filtering #' conditions. The conditions are expressed as logical statements and rows in #' the data will be retained if the statement evaluates to `TRUE`. It is #' possible to keep filtered data on display by setting `keep = TRUE` which will #' let data be retained as the result of the exit function. Note that if data is #' kept the enter function will have no effect. #' #' @param transition_length The relative length of the transition. Will be #' recycled to match the number of states in the data #' @param filter_length The relative length of the pause at the states. Will be #' recycled to match the number of states in the data #' @param ... A number of expressions to be evaluated in the context of the layer #' data, returning a logical vector. If the expressions are named, the name will #' be available as a frame variable. #' @param wrap Should the animation *wrap-around*? If `TRUE` the last filter will #' be transitioned into the first. #' @param keep Should rows that evaluates to `FALSE` be kept in the data as it #' looks after exit has been applied #' #' @section Label variables: #' `transition_filter` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **transitioning** is a boolean indicating whether the frame is part of the #' transitioning phase #' - **previous_filter** The name of the last filter the animation was at #' - **closest_filter** The name of the filter closest to this frame #' - **next_filter** The name of the next filter the animation will be part of #' - **previous_expression** The expression of the last filter the animation was at #' - **closest_expression** The expression of the filter closest to this frame #' - **next_expression** The expression of the next filter the animation will be part of #' #' @section Object permanence: #' `transition_filter` does not link rows across data to the same graphic #' element, so elements will be defined uniquely by each row. If `keep = TRUE` #' the rows not matching the conditions of a filter is not removed from the plot #' after the exit animation, and a possible subsequent enter will begin from #' the state they were left in, rather than enter anew from the state defined by #' the enter function. #' #' @inheritSection transition_states Computed Variables #' #' @family transitions #' #' @importFrom rlang quos quos_auto_name #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) + #' geom_point() + #' transition_filter( #' transition_length = 2, #' filter_length = 1, #' Setosa = Species == 'setosa', #' Long = Petal.Length > 4, #' Wide = Petal.Width > 2 #' ) + #' ggtitle( #' 'Filter: {closest_filter}', #' subtitle = '{closest_expression}' #' ) + #' enter_fade() + #' exit_fly(y_loc = 0) #' #' # Setting `keep = TRUE` allows you to keep the culled data on display. Only #' # exit functions will be used in that case (as elements enters from the #' # result of the exit function) #' anim2 <- ggplot(iris, aes(Petal.Width, Petal.Length, colour = Species)) + #' geom_point() + #' transition_filter( #' transition_length = 2, #' filter_length = 1, #' Setosa = Species == 'setosa', #' Long = Petal.Length > 4, #' Wide = Petal.Width > 2, #' keep = TRUE #' ) + #' ggtitle( #' 'Filter: {closest_filter}', #' subtitle = '{closest_expression}' #' ) + #' exit_recolour(colour = 'grey') + #' exit_shrink(size = 0.5) #' transition_filter <- function(transition_length = 1, filter_length = 1, ..., wrap = TRUE, keep = FALSE) { filter_quos <- quos_auto_name(quos(...)) if (length(filter_quos) < 2) { stop('transition_filter requires at least 2 filtering conditions', call. = FALSE) } ggproto(NULL, TransitionFilter, params = list( filter_quos = filter_quos, transition_length = transition_length, filter_length = filter_length, wrap = wrap, keep = keep ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_state keep_state #' @importFrom rlang quo_name TransitionFilter <- ggproto('TransitionFilter', Transition, mapping = '(.+)', var_names = 'filter', setup_params = function(self, data, params) { params$row_id <- assign_filters(data, params$filter_quos) params$require_stat <- any(vapply(params$filter_quo, function(f) require_stat(f[[2]]), logical(1))) params }, setup_params2 = function(self, data, params, row_vars) { params$row_id <- assign_filters(data, params$filter_quos, TRUE, row_vars) transition_length <- rep(params$transition_length, length.out = length(params$filter_quos)) if (!params$wrap) transition_length[length(transition_length)] <- 0 filter_length <- rep(params$filter_length, length.out = length(params$filter_quos)) frames <- distribute_frames(filter_length, transition_length, params$nframes + if (params$wrap) 1 else 0) params$state_length <- frames$static_length params$transition_length <- frames$transition_length params$frame_info <- cbind( get_frame_info( static_levels = names(params$filter_quos), static_lengths = params$state_length, transition_lengths = params$transition_length, nframes = params$nframes, static_first = TRUE, static_name = 'filter' ), get_frame_info( static_levels = vapply(params$filter_quos, quo_name, character(1)), static_lengths = params$state_length, transition_lengths = params$transition_length, nframes = params$nframes, static_first = TRUE, static_name = 'expression' ) ) params$nframes <- nrow(params$frame_info) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_vars <- self$get_row_vars(data) if (is.null(row_vars)) return(data) data$group <- paste0(row_vars$before, row_vars$after) if (type %in% c('point', 'sf')) { data$.temp_id <- seq_len(nrow(data)) id <- quo(.temp_id) ease <- c(ease, 'linear') } filter <- strsplit(row_vars$filter, '-') row <- rep(seq_along(filter), lengths(filter)) filter <- as.integer(unlist(filter)) present <- filter != 0 & !is.na(filter) row <- row[present] filter <- filter[present] filtered_data <- lapply(seq_along(params$filter_quos), function(i) { include <- row[filter == i] exclude <- setdiff(seq_len(nrow(data)), include) d_f <- data if (params$keep) { exit_data <- exit(d_f[exclude, , drop = FALSE]) if (is.null(exit_data)) { d_f <- d_f[include, , drop = FALSE] } else { d_f[exclude, ] <- exit_data } } else { d_f <- d_f[include, , drop = FALSE] } d_f }) all_frames <- filtered_data[[1]] for (i in seq_along(filtered_data)) { if (params$state_length[i] != 0) { all_frames <- keep_state(all_frames, params$state_length[i]) } if (params$transition_length[i] != 0) { next_filter <- if (i == length(filtered_data)) filtered_data[[1]] else filtered_data[[i + 1]] all_frames <- switch( type, point = tween_state(all_frames, next_filter, ease, params$transition_length[i], !!id, enter, exit), path = transform_path(all_frames, next_filter, ease, params$transition_length[i], !!id, enter, exit, match), polygon = transform_polygon(all_frames, next_filter, ease, params$transition_length[i], !!id, enter, exit, match), sf = transform_sf(all_frames, next_filter, ease, params$transition_length[i], !!id, enter, exit), stop(type, ' layers not currently supported by transition_filter', call. = FALSE) ) } } if (params$wrap) { all_frames <- all_frames[all_frames$.frame <= params$nframes, ] } all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) assign_filters <- function(data, filters, after = FALSE, row_vars = NULL) { do_filter <- vapply(filters, function(f) require_stat(f[[2]]), logical(1)) == after row_filters <- lapply(data, function(d) { row_filter <- do.call(rbind, lapply(seq_along(filters), function(i) { if (!do_filter[i]) return(rep(FALSE, nrow(d))) filter <- safe_eval(filters[[i]], d) filter <- filter %||% rep(TRUE, nrow(d)) if (!is.logical(filter)) stop('Filters must return a logical vector', call. = FALSE) filter })) if (all(row_filter)) return(numeric(0)) apply(row_filter, 2, function(x) if (!any(x)) '0' else paste(which(x), collapse = '-')) }) if (after) { Map(function(new_f, old_f) paste0(old_f, '-', new_f), new_f = row_filters, old_f = row_vars$filter) } else { row_filters } } gganimate/R/animation_store.R0000644000176200001440000000034213405665100015724 0ustar liggesusers.store <- new.env(parent = emptyenv()) set_last_animation <- function(value) .store$animation <- value #' Retrieve the last rendered animation #' #' @export #' @keywords internal last_animation <- function() .store$animation gganimate/R/zzz.R0000644000176200001440000000336413617343617013410 0ustar liggesusersdef_ren <- new.env(parent = emptyenv()) .onLoad <- function(...) { register_s3_method("knitr", "knit_print", "gganim") register_s3_method("knitr", "knit_print", "gif_image") register_s3_method("knitr", "knit_print", "video_file") register_s3_method("knitr", "knit_print", "sprite_image") def_ren$has_proper <- TRUE if (requireNamespace('gifski', quietly = TRUE)) { def_ren$renderer <- gifski_renderer() } else if (requireNamespace('magick', quietly = TRUE)) { def_ren$renderer <- magick_renderer() } else if (requireNamespace('av', quietly = TRUE)) { def_ren$renderer <- av_renderer() } else { def_ren$renderer <- file_renderer() def_ren$has_proper <- FALSE } invisible() } .onAttach <- function(...) { if (!isTRUE(def_ren$has_proper)) { packageStartupMessage( 'No renderer backend detected. gganimate will default to writing frames to separate files\n', 'Consider installing:\n', '- the `gifski` package for gif output\n', '- the `av` package for video output\n', 'and restarting the R session' ) } } register_s3_method <- function(pkg, generic, class, fun = NULL) { stopifnot(is.character(pkg), length(pkg) == 1) stopifnot(is.character(generic), length(generic) == 1) stopifnot(is.character(class), length(class) == 1) if (is.null(fun)) { fun <- get(paste0(generic, ".", class), envir = parent.frame()) } else { stopifnot(is.function(fun)) } if (pkg %in% loadedNamespaces()) { registerS3method(generic, class, fun, envir = asNamespace(pkg)) } # Always register hook in case package is later unloaded & reloaded setHook( packageEvent(pkg, "onLoad"), function(...) { registerS3method(generic, class, fun, envir = asNamespace(pkg)) } ) } gganimate/R/renderers.R0000644000176200001440000004244613701271002014526 0ustar liggesusers#' Renderers provided by gganimate #' #' The purpose of the renderer function is to take a list of image files and #' assemble them into an animation. `gganimate` provide a range of renderers #' but it is also possible to provide your own, if the supplied ones are lacking #' in any way. A renderer is given as argument to [animate()]/print() and #' receives the paths to the individual frames once they have been created. #' #' @details The `gifski_renderer()` is used unless otherwise specified in #' [animate()] or in `options('gganimate.renderer')`. This renderer requires #' both the `gifski` and `png` packages to be installed. #' #' Other possible renderers are: #' - `magick_renderer()` which requires the `magick` package and produce a `gif`. #' If `gifski` is not installed, the rendering will be much slower than using the #' `gifski_renderer()` and can potentially result in system problems when many #' frames need to be rendered (if `gifski` is installed `magick` will use it #' under the hood) #' - `av_renderer()` which requies the `av` package and uses ffmpeg to encode #' the animation into a video file. #' - `ffmpeg_renderer()` which requires that ffmpeg has been installed on your #' computer. As with `av_renderer()` it will use ffmpeg to encode the animation #' into a video #' - `sprite_renderer()` which requires `magick` and will render the animation #' into a spritesheet #' - `file_renderer()` which has no dependencies and simply returns the #' animation as a list of image files (one for each frame) #' #' It is possible to create your own renderer function providing that it #' matches the required signature (`frames` and `fps` argument). The return #' value of your provided function will be the return value ultimately given by #' [animate()] #' #' @param loop Logical. Should the produced gif loop #' @param file The animation file #' @param dir The directory to copy the frames to #' @param prefix The filename prefix to use for the image files #' @param overwrite Logical. If TRUE, existing files will be overwritten. #' @param width,height Dimensions of the animation in pixels. If `NULL` will #' take the dimensions from the frame, otherwise it will rescale it. #' @param vfilter A string defining an ffmpeg filter graph. This is the same #' parameter as the `-vf` argument in the `ffmpeg` command line utility. #' @param codec The name of the video codec. The default is `libx264` for most #' formats, which usually the best choice. See the `av` documentation for more #' information. #' @param audio An optional file with sounds to add to the video #' @param format The video format to encode the animation into #' @param ffmpeg The location of the `ffmpeg` executable. If `NULL` it will be #' assumed to be on the search path #' @param options Either a character vector of command line options for ffmpeg #' or a named list of option-value pairs that will be converted to command line #' options automatically #' #' @return The provided renderers are factory functions that returns a new function #' that take `frames` and `fps` as arguments, the former being a character #' vector with file paths to the images holding the separate frames, in the #' order they should appear, and the latter being the framerate to use for the #' animation in frames-per-second. #' #' The return type of the different returned renderers are: #' - **`gifski_renderer`**: Returns a [gif_image] object #' - **`magick_renderer`**: Returns a `magick-image` object #' - **`av_renderer`**: Returns a [video_file] object #' - **`ffmpeg_renderer`**: Returns a [video_file] object #' - **`file_renderer`**: Returns a vector of file paths #' #' @name renderers #' @rdname renderers #' #' @examples #' anim <- ggplot(mtcars, aes(mpg, disp)) + #' transition_states(gear, transition_length = 2, state_length = 1) + #' enter_fade() + #' exit_fade() #' #' \dontrun{ #' # Renderers are specified in the `animate()` function #' animate(anim, renderer = sprite_renderer()) #' } #' NULL #' @rdname renderers #' @export gifski_renderer <- function(file = NULL, loop = TRUE, width = NULL, height = NULL) { if (!requireNamespace('gifski', quietly = TRUE)) { stop('The gifski package is required to use gifski_renderer', call. = FALSE) } function(frames, fps) { if (is.null(file)) file <- tempfile(fileext = '.gif') if (!all(grepl('.png$', frames))) { stop('gifski only supports png files', call. = FALSE) } if (is.null(width) || is.null(height)) { dims <- png_dim(frames[1]) height <- height %||% dims[1] width <- width %||% dims[2] } progress <- interactive() if (progress) message('') gif <- gifski::gifski(frames, file, width, height, delay = 1/fps, loop, progress) gif_file(gif) } } #' @rdname renderers #' @export file_renderer <- function(dir = '.', prefix = 'gganim_plot', overwrite = FALSE) { function(frames, fps) { if (!dir.exists(dir)) dir.create(dir, showWarnings = FALSE, recursive = TRUE) new_names <- file.path(dir, sub('gganim_plot', prefix, basename(frames))) if (any(!file.copy(frames, new_names, overwrite = overwrite))) { warning('file_renderer failed to copy frames to the destination directory', call. = FALSE) } invisible(new_names) } } #' @rdname renderers #' @export av_renderer <- function(file = NULL, vfilter = "null", codec = NULL, audio = NULL) { if (!requireNamespace('av', quietly = TRUE)) { stop('The av package is required to use av_renderer', call. = FALSE) } def_ext <- if (.Platform$GUI == "RStudio" && "libvpx" %in% av::av_encoders()$name) ".webm" else ".mp4" function(frames, fps) { if (is.null(file)) { file <- tempfile(fileext = def_ext) } progress <- interactive() av::av_encode_video(input = frames, output = file, framerate = fps, vfilter = vfilter, codec = codec, audio = audio, verbose = progress) video_file(file) } } has_ffmpeg <- function(ffmpeg = 'ffmpeg') { tryCatch( { suppressWarnings(system2(ffmpeg, '-version', stdout = FALSE, stderr = FALSE)) TRUE }, error = function(e) { FALSE } ) } #' @rdname renderers #' @export ffmpeg_renderer <- function(format = 'auto', ffmpeg = NULL, options = list(pix_fmt = 'yuv420p')) { ffmpeg <- ffmpeg %||% 'ffmpeg' if (!has_ffmpeg(ffmpeg)) stop('The ffmpeg library is not available at the specified location', call. = FALSE) if (format == 'auto') { format <- if (.Platform$GUI == "RStudio" && any(grepl('--enable-libvpx', system2('ffmpeg', '-version', stdout = TRUE)))) { "webm" } else { "mp4" } } if (is.list(options)) { if (is.null(names(options))) { stop('options list must be named', call. = FALSE) } opt_name <- paste0('-', sub('^-', '', names(options))) opts <- vapply(options, paste, character(1), collapse = ' ') options <- paste(paste0(opt_name, ' ', opts), collapse = ' ') } stopifnot(is.character(options)) function(frames, fps) { progress <- interactive() output_file <- tempfile(fileext = paste0('.', sub('^\\.', '', format))) frame_loc <- dirname(frames[1]) file_glob <- sub('^.*(\\..+$)', 'gganim_plot%4d\\1', basename(frames[1])) file_glob <- file.path(frame_loc, file_glob) system2(ffmpeg, c("-pattern_type sequence", paste0('-r ', fps), paste0('-i ', file_glob), '-y', '-loglevel ', if (progress) 'info' else 'quiet', paste0('-r ', fps), '-hide_banner', options, output_file )) if (!file.exists(output_file)) stop('Rendering with ffmpeg failed', call. = FALSE) if (format == 'gif') { gif_file(output_file) } else { video_file(output_file) } } } #' @rdname renderers #' @export magick_renderer <- function(loop = TRUE) { if (!requireNamespace('magick', quietly = TRUE)) { stop('The magick package is required to use magick_renderer', call. = FALSE) } function(frames, fps) { anim <- if (grepl('.svg$', frames[1])) { magick::image_read_svg(frames) } else { magick::image_read(frames) } anim <- magick::image_animate(anim, fps, loop = if (loop) 0 else 1) anim } } #' @rdname renderers #' @export sprite_renderer <- function() { if (!requireNamespace('magick', quietly = TRUE)) { stop('The magick package is required to use sprite_renderer', call. = FALSE) } function(frames, fps) { sprite <- if (grepl('.svg$', frames[1])) { magick::image_read_svg(frames) } else { magick::image_read(frames) } single_dim <- magick::image_info(sprite[1]) sprite <- magick::image_append(sprite) full_dim <- magick::image_info(sprite) file <- tempfile(fileext = '.png') magick::image_write(sprite, file, 'png') sprite_file(file, fps, width = single_dim$width, full_width = full_dim$width, height = single_dim$height) } } # HELPERS ----------------------------------------------------------------- #' Wrap a gif file for easy handling #' #' This is a simple class for gif files that takes care printing the file #' correctly in different environment (e.g. knitr, RStudio, etc.). If your #' renderer produces a gif file you can wrap the final output in `gif_file` to #' get all of these benefits for free. #' #' @param file The gif file to be wrapped #' @param x A `gif_image` object #' @param f a ‘factor’ in the sense that [as.factor(f)][base::factor] defines #' the grouping, or a list of such factors in which case their interaction is #' used for the grouping. #' @inheritParams base::split #' @param ... Arguments passed on #' #' @return `gif_file` returns a `gif_image` object. `split` returns a list of #' `magick-image` objects and requires magick to work. #' #' @keywords internal #' @export #' @aliases gif_image #' gif_file <- function(file) { stopifnot(length(file) == 1) if (!grepl('.gif$', file)) stop('file must be a gif', call. = FALSE) class(file) <- 'gif_image' file } #' @rdname gif_file #' @export print.gif_image <- function(x, ...) { viewer <- getOption("viewer", utils::browseURL) if (is.function(viewer) && length(x)) { viewer(x) } else { invisible() } } #' @rdname gif_file #' @export knit_print.gif_image <- function(x, options, ...) { knitr_path <- knitr::fig_path('.gif', options) dir.create(dirname(knitr_path), showWarnings = FALSE, recursive = TRUE) file.copy(x, knitr_path, overwrite = TRUE) if (is.null(options$out.width)) { options$out.width <- options$fig.width * options$dpi / (options$fig.retina %||% 1) } knitr::knit_print(knitr::include_graphics(knitr_path), options, ...) } #' @rdname gif_file #' @export split.gif_image <- function(x, f, drop = FALSE, ...) { if (!requireNamespace('magick', quietly = TRUE)) { stop('Splitting gifs require the magick package', call. = FALSE) } gif <- magick::image_read(x) split(gif, f, drop = drop, ...) } #' Wrap a video file for easy handling #' #' This function is equivalent to [gif_file()] but works for arbitrary video #' file formats. There are some caveats involved though, most notably it doesn't #' currently supports splitting so you can't easily use this output together #' with [split_animation()]. Graceful printing is contingent on the file format. #' Only `mp4`, `webm`, and `ogg` is supported by the HTML format and can thus be #' shown in the RStudio viewer and inside HTML documents created with knitr. #' Other formats will be opened in their default OS-specific viewer. #' #' @param file A video file #' @param x A `video_file` object #' @param width The width the output should be scaled to #' @param ... Arguments passed on #' #' @return `video_file` returns a `video_file` object which is a shallow wrapper #' around the file path text string. #' #' @keywords internal #' @export #' video_file <- function(file) { stopifnot(length(file) == 1) class(file) <- 'video_file' file } #' @rdname video_file #' @export print.video_file <- function(x, width = NULL, ...) { if (grepl('\\.(mp4)|(webm)|(ogg)$', x, ignore.case = TRUE)) { if (grepl('\\.mp4$', x, ignore.case = TRUE) && .Platform$GUI == "RStudio") { utils::browseURL(x) } else { print(htmltools::browsable(as_html_video(x, width))) } } else { viewer <- getOption("viewer", utils::browseURL) viewer(x) } } #' @rdname video_file #' @export knit_print.video_file <- function(x, options, ...) { if (grepl('\\.(mp4)|(webm)|(ogg)$', x, ignore.case = TRUE)) { knitr::knit_print(htmltools::browsable(as_html_video(x, width = get_chunk_width(options))), options, ...) } else { warning('The video format doesn\'t support HTML', call. = FALSE) invisible(NULL) } } #' @export split.video_file <- function(x, f, drop = FALSE, ...) { stop('video_file objects does not support splitting', call. = FALSE) } as_html_video <- function(x, width = NULL) { if (!requireNamespace("base64enc", quietly = TRUE)) { stop('The base64enc package is required for showing video') } if (!requireNamespace("htmltools", quietly = TRUE)) { stop('The htmltools package is required for showing video') } format <- tolower(sub('^.*\\.(.+)$', '\\1', x)) htmltools::HTML(paste0( '' )) } #' Wrap an image sprite for easy handling #' #' This function is equivalent to [gif_file()] but works for animations encoded #' as a sprite. A sprite is a single image file where each frame of the #' animation is stacked next to each other. The animation then happens by #' changing what slice of the image is shown. The implementation used allow #' users to click on the animation in order to toggle pause/play. #' #' @param file A png file with frames placed horizontally #' @param fps The framerate for the sprite animation #' @param width,height The dimension of a single frame #' @param full_width The width of the whole image #' @param x A `sprite_image` object #' @param ... Arguments passed on #' #' @return `sprite_file` returns a `sprite_image` object which is a shallow wrapper #' around the file path text string along with dimensions and fps used for #' animating the sprite when printing. #' #' @keywords internal #' @export #' sprite_file <- function(file, fps, width, full_width, height) { stopifnot(length(file) == 1) attributes(file) <- list(fps = fps, single_width = width, full_width = full_width, height = height) class(file) <- 'sprite_image' file } #' @rdname sprite_file #' @export print.sprite_image <- function(x, width = NULL, ...) { print(htmltools::browsable(as_sprite_html(x, width = width))) } #' @rdname sprite_file #' @export knit_print.sprite_image <- function(x, options, ...) { knitr::knit_print(htmltools::browsable(as_sprite_html(x, width = get_chunk_width(options))), options, ...) } #' @importFrom glue glue as_sprite_html <- function(x, width = NULL, ...) { if (!requireNamespace("base64enc", quietly = TRUE)) { stop('The base64enc package is required for showing video') } if (!requireNamespace("htmltools", quietly = TRUE)) { stop('The htmltools package is required for showing video') } # Sprite animation code inspired by https://medium.com/dailyjs/how-to-build-a-simple-sprite-animation-in-javascript-b764644244aa sprite_id <- sample(1e6, 1) css <- glue( ' ', height = paste0(100*attr(x, 'height') / attr(x, 'single_width'), '%'), width = width %||% paste0(attr(x, 'single_width'), 'px'), size = paste0(100 * attr(x, 'full_width') / attr(x, 'single_width'), '%'), img_encode = base64enc::base64encode(x), .open = '%', .close = '%' ) html <- glue('

') js <- glue( ' ', width = 100 / (attr(x, 'full_width') / attr(x, 'single_width') - 1), fps = attr(x, 'fps'), .open = '%', .close = '%' ) full <- paste0(css, '\n', html, '\n', js) htmltools::HTML(full) } #' @export split.sprite_image <- function(x, f, drop = FALSE, ...) { stop('sprite_image objects does not support splitting', call. = FALSE) } in_pkgdown <- function() { identical(Sys.getenv("IN_PKGDOWN"), "true") } get_chunk_width <- function(options) { options$out.width %||% paste0((options$fig.width / (options$fig.retina %||% 1)), 'px') } gganimate/R/scene.R0000644000176200001440000001536213414624664013650 0ustar liggesusers#' @importFrom ggplot2 ggproto create_scene <- function(transition, view, shadow, ease, transmuters, nframes) { if (is.null(nframes)) nframes <- 100 ggproto(NULL, Scene, transition = transition, view = view, shadow = shadow, ease = ease, transmuters = transmuters, nframes = nframes) } #' @importFrom ggplot2 ggproto ggplot_gtable #' @importFrom glue glue_data #' @importFrom grid grid.newpage grid.draw seekViewport pushViewport upViewport Scene <- ggproto('Scene', NULL, transition = NULL, view = NULL, shadow = NULL, ease = NULL, transmuters = NULL, nframes = integer(), transition_params = list(), view_params = list(), shadow_params = list(), layer_type = character(), tween_first = logical(), group_column = character(), match_shape = logical(), setup = function(self, layer_data) { transition_params <- self$transition$params transition_params$nframes <- self$nframes self$transition_params <- self$transition$setup_params(layer_data, transition_params) view_params <- self$view$params view_params$nframes <- self$nframes self$view_params <- self$view$setup_params(layer_data, view_params) shadow_params <- self$shadow$params shadow_params$nframes <- self$nframes self$shadow_params <- self$shadow$setup_params(layer_data, shadow_params) }, identify_layers = function(self, layer_data, layers) { self$transmuters$setup(layers) self$layer_type <- self$get_layer_type(layer_data, layers) self$tween_first <- self$is_early_tween(layers) if (self$transition$require_late_tween(self$transition_params)) self$tween_first[] <- FALSE self$group_column <- self$get_group_column(layers) self$match_shape <- self$get_shape_match(layers) }, before_stat = function(self, layer_data) { layer_data <- self$transition$map_data(layer_data, self$transition_params) ease <- self$ease$get_ease(layer_data[self$tween_first]) layer_data[self$tween_first] <- self$transition$expand_data( layer_data[self$tween_first], self$layer_type[self$tween_first], self$group_column[self$tween_first], self$match_shape[self$tween_first], ease, self$transmuters$enter_transmuters(self$tween_first), self$transmuters$exit_transmuters(self$tween_first), self$transition_params, which(self$tween_first) ) layer_data }, after_stat = function(self, layer_data) { row_vars <- self$transition$get_all_row_vars(layer_data) self$transition_params <- self$transition$setup_params2(layer_data, self$transition_params, row_vars) layer_data <- self$transition$map_data(layer_data, self$transition_params, replace = TRUE) layer_data }, before_position = function(self, layer_data) { self$transition$unmap_frames(layer_data, self$transition_params) }, after_position = function(self, layer_data) { self$transition$remap_frames(layer_data, self$transition_params) }, after_defaults = function(self, layer_data) { tween_last <- !self$tween_first ease <- self$ease$get_ease(layer_data[tween_last]) layer_data[tween_last] <- self$transition$expand_data( layer_data[tween_last], self$layer_type[tween_last], self$group_column[tween_last], self$match_shape[tween_last], ease, self$transmuters$enter_transmuters(tween_last), self$transmuters$exit_transmuters(tween_last), self$transition_params, which(tween_last) ) layer_data }, finish_data = function(self, layer_data) { layer_data <- self$transition$finish_data(layer_data, self$transition_params) self$nframes <- self$transition$adjust_nframes(layer_data, self$transition_params) static_layers <- self$transition$static_layers(self$transition_params) self$view_params$nframes <- self$nframes self$view_params$excluded_layers <- union(self$view$exclude_layer, static_layers) self$view_params <- self$view$train(layer_data, self$view_params) self$shadow_params$nframes <- self$nframes self$shadow_params$excluded_layers <- union(self$shadow$exclude_layer, static_layers) self$shadow_params <- self$shadow$train(layer_data, self$shadow_params) frame_vars <- list( data.frame(frame = seq_len(self$nframes), nframes = self$nframes, progress = seq_len(self$nframes)/self$nframes), self$transition$get_frame_vars(self$transition_params), self$view$get_frame_vars(self$view_params) ) self$frame_vars <- do.call(cbind, frame_vars[!vapply(frame_vars, is.null, logical(1))]) layer_data }, get_frame = function(self, plot, i) { class(plot) <- 'ggplot_built' data <- self$transition$get_frame_data(plot$data, self$transition_params, i) shadow_i <- self$shadow$get_frames(self$shadow_params, i) shadow <- self$transition$get_frame_data(plot$data, self$transition_params, shadow_i) shadow <- self$shadow$prepare_shadow(shadow, self$shadow_params) plot$data <- self$shadow$prepare_frame_data(data, shadow, self$shadow_params, i, shadow_i) plot <- self$view$set_view(plot, self$view_params, i) plot <- self$set_labels(plot, i) PANEL_levels <- plot$layout$layout$PANEL plot$data <- lapply(plot$data, function(d) { d$PANEL <- factor(d$PANEL, PANEL_levels) d }) plot }, plot_frame = function(self, plot, i, newpage = is.null(vp), vp = NULL, widths = NULL, heights = NULL, ...) { plot <- self$get_frame(plot, i) plot <- ggplot_gtable(plot) if (!is.null(widths)) plot$widths <- widths if (!is.null(heights)) plot$heights <- heights if (newpage) grid.newpage() grDevices::recordGraphics( requireNamespace("gganimate", quietly = TRUE), list(), getNamespace("gganimate") ) if (is.null(vp)) { grid.draw(plot) } else { if (is.character(vp)) seekViewport(vp) else pushViewport(vp) grid.draw(plot) upViewport() } invisible(NULL) }, set_labels = function(self, plot, i) { label_var <- as.list(self$frame_vars[i, ]) label_var$data <- plot$data plot$plot$labels <- lapply(plot$plot$labels, function(label) { if (is.expression(label)) return(label) vapply(label, glue_data, character(1), .x = label_var, .envir = plot$plot$plot_env) }) plot }, get_group_column = function(self, layers) { lapply(layers, function(l) { group_column(l$stat) %||% group_column(l$geom) %||% quo(group) }) }, get_layer_type = function(self, data, layers) { unlist(Map(function(l, d) { layer_type(l$stat) %||% layer_type(l$geom) %||% layer_type(d) %||% 'point' }, l = layers, d = data)) }, get_shape_match = function(self, layers) { vapply(layers, function(l) { match_shapes(l$stat) %||% match_shapes(l$geom) %||% TRUE }, logical(1)) }, is_early_tween = function(self, layers) { vapply(layers, tween_before_stat, logical(1)) } ) gganimate/R/gganimate-ggproto.R0000644000176200001440000000041713405665100016147 0ustar liggesusers#' Base ggproto classes for gganimate #' #' If you are creating a new transition, view, etc. in another package, #' you'll need to extend from some of the ggproto classes defined in `gganimate` #' #' @seealso ggproto #' @keywords internal #' @name gganimate-ggproto NULL gganimate/R/view-step-manual.R0000644000176200001440000000554113406134603015735 0ustar liggesusers#' @include view-step.R NULL #' @rdname view_step #' #' @param xmin,xmax,ymin,ymax Vectors of even length defining the boundaries of #' the different views to go through #' #' @export #' @importFrom ggplot2 ggproto view_step_manual <- function(pause_length = 1, step_length = 1, xmin, xmax, ymin, ymax, delay = 0, ease = 'cubic-in-out', wrap = TRUE, pause_first = FALSE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1) { ggproto(NULL, ViewStepManual, fixed_lim = list(x = fixed_x, y = fixed_y), exclude_layer = exclude_layer, aspect_ratio = aspect_ratio, params = list( pause_length = pause_length, step_length = step_length, windows = data.frame( xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax ), delay = delay, ease = ease, wrap = wrap, pause_first = pause_first ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom tweenr keep_state ViewStepManual <- ggproto('ViewStepManual', ViewStep, setup_params = function(self, data, params) { nsteps <- nrow(params$windows) step_length <- rep(params$step_length, length.out = nsteps) pause_length <- rep(params$pause_length, length.out = nsteps) if (!params$pause_first) { pause_length <- c(0, pause_length) step_length <- c(step_length, 0) if (!params$wrap) pause_length[length(pause_length)] <- 0 } else if (!params$wrap) { step_length[length(step_length)] <- 0 } params$step_length <- step_length params$pause_length <- pause_length params }, train = function(self, data, params) { nframes <- params$nframes if (params$wrap) nframes <- nframes + 1 frames <- distribute_frames(params$pause_length, params$step_length, nframes) params$windows <- rbind( params$windows, params$windows[rep(1, length(frames$static_length) - nrow(params$windows) + 1), , drop = FALSE] ) frame_ranges <- params$windows[1, , drop = FALSE] for (i in seq_len(nrow(params$windows) - 1)) { if (frames$static_length[i] != 0) { frame_ranges <- keep_state(frame_ranges, frames$static_length[i]) } if (frames$transition_length[i] != 0) { frame_ranges <- self$window_transition(frame_ranges, params$windows[i + 1, , drop = FALSE], frames$transition_length[i], params) } } frame_ranges <- frame_ranges[seq_len(params$nframes), , drop = FALSE] frame_ranges$.frame <- (seq_len(nrow(frame_ranges)) + round(params$delay * frames$mod)) %% params$nframes frame_ranges <- frame_ranges[order(frame_ranges$.frame), ] params$frame_ranges <- frame_ranges params } ) gganimate/R/anim_save.R0000644000176200001440000000364413405665100014503 0ustar liggesusers#' Save an animation to a file #' #' This function is analogous to [ggplot2::ggsave()] in that it by default takes #' the last created animation and saves it to the specific location. As #' `gganimate` supports arbitrary renderers, and thus return types, the returned #' object must implement a `save_animation` method to be able to be used with #' `anim_save()`. This is provided natively for `gif_image` and `magick-image` #' objects. #' #' @param animation The animation object to save, as returned by [animate()]. #' Defaults to the last rendered animation using [last_animation()] #' @inheritParams ggplot2::ggsave #' @param ... arguments passed on to [animate()] if `animation` is a `gganim` #' object #' #' @export #' anim_save <- function(filename, animation = last_animation(), path = NULL, ...) { if (!is.null(path)) { filename <- file.path(path, filename) } if (is.gganim(animation)) animation <- animate(animation, ...) save_animation(animation, filename) } #' Infrastructure for animation saving #' #' Any returned animation object that wish to support [anim_save()] need to #' implement this method #' #' @param animation The animation object to save #' @param file The file path to save it to #' #' @keywords internal #' @export save_animation <- function(animation, file) { UseMethod('save_animation') } #' @export save_animation.default <- function(animation, file) { stop('The animation object does not specify a save_animation method', call. = FALSE) } #' @export save_animation.gif_image <- function(animation, file) { file.copy(animation, file, overwrite = TRUE) invisible(NULL) } #' @export save_animation.video_file <- save_animation.gif_image #' @export `save_animation.magick-image` <- function(animation, file) { if (!requireNamespace('magick', quietly = TRUE)) { stop('The magick package is required for this functionality', call. = FALSE) } magick::image_write(animation, file) invisible(NULL) } gganimate/R/transition-time.R0000644000176200001440000001476413415135670015701 0ustar liggesusers#' Transition through distinct states in time #' #' This is a variant of [transition_states()] that is intended for data where #' the states are representing specific point in time. The transition length #' between the states will be set to correspond to the actual time difference #' between them. #' #' @param time An unquoted expression giving the time, and thus state #' membership, of each observation. #' @param range The time range to animate. If `NULL` it will be set to the range #' of `time` #' #' @section Label variables: #' `transition_time` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **frame_time** gives the time that the current frame corresponds to #' #' @section Object permanence: #' `transition_time` uses the group aesthetic of each layer to identify #' which rows in the input data correspond to the same graphic element and will #' therefore define which elements will turn into each other between time points. #' The group aesthetic, if not set, will be calculated from the interaction of all #' discrete aesthetics in the layer (excluding `label`), so it is often better #' to set it explicetly when animating, to make sure your data is interpreted in #' the right way. If the group aesthetic is not set, and no discrete aesthetics #' exists then all rows will have the same group. If the group aesthetic is not #' unique in each state, then rows will be matched first by group and then by #' index. Unmatched rows will appear/disappear, potentially using an enter or #' exit function. #' #' @inheritSection transition_states Computed Variables #' #' @family transitions #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(airquality, aes(Day, Temp)) + #' geom_point(aes(colour = factor(Month))) + #' transition_time(Day) #' #' # Removing a time point will prolong the tweening between neighbouring time #' # points so the time dimension stays linear #' airquality_missing <- airquality[airquality$Day <= 10 | airquality$Day >= 20, ] #' anim1 <- ggplot(airquality_missing, aes(Day, Temp)) + #' geom_point(aes(colour = factor(Month))) + #' transition_time(Day) #' #' # Range can be constrained if needed #' anim2 <- ggplot(airquality, aes(Day, Temp)) + #' geom_point(aes(colour = factor(Month))) + #' transition_time(Day, range = c(10L, 20L)) #' #' # The group aesthetic is used to connect elements #' # No grouping #' anim3 <- ggplot(airquality, aes(Day, Temp)) + #' geom_line() + #' transition_time(Month) #' #' # Group by month #' anim4 <- ggplot(airquality, aes(Day, Temp)) + #' geom_line(aes(group = Month)) + #' transition_time(Month) + #' enter_fade() + #' exit_fade() transition_time <- function(time, range = NULL) { time_quo <- enquo(time) require_quo(time_quo, 'time') ggproto(NULL, TransitionTime, params = list( time_quo = time_quo, range = range ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_state keep_state TransitionTime <- ggproto('TransitionTime', Transition, mapping = '(.+)', var_names = 'time', setup_params = function(self, data, params) { params$time <- get_row_time(data, params$time_quo, params$nframes, params$range) params$require_stat <- is_placeholder(params$time) params$row_id <- params$time$values params }, setup_params2 = function(self, data, params, row_vars) { if (is_placeholder(params$time)) { params$time <- get_row_time(data, params$time_quo, params$nframes, params$range, after = TRUE) } else { params$time$values <- lapply(row_vars$time, as.integer) } params$row_id <- params$time$values params$frame_info <- data.frame(frame_time = params$time$frame_time) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_time <- self$get_row_vars(data) if (is.null(row_time)) return(data) data$group <- paste0(row_time$before, row_time$after) time <- as.integer(row_time$time) states <- split(data, time) times <- as.integer(names(states)) nframes <- diff(times) nframes[1] <- nframes[1] + 1 if (times[1] <= 1) { all_frames <- states[[1]] states <- states[-1] } else { all_frames <- data[0, , drop = FALSE] nframes <- c(times[1] - 1, nframes) } if (times[length(times)] < params$nframes) { states <- c(states, list(data[0, , drop = FALSE])) nframes <- c(nframes, params$nframes - times[length(times)]) } for (i in seq_along(states)) { all_frames <- switch( type, point = tween_state(all_frames, states[[i]], ease, nframes[i], !!id, enter, exit), path = transform_path(all_frames, states[[i]], ease, nframes[i], !!id, enter, exit, match), polygon = transform_polygon(all_frames, states[[i]], ease, nframes[i], !!id, enter, exit, match), sf = transform_sf(all_frames, states[[i]], ease, nframes[i], !!id, enter, exit), stop(type, ' layers not currently supported by transition_time', call. = FALSE) ) } true_frame <- seq(times[1], times[length(times)]) all_frames <- all_frames[all_frames$.frame %in% which(true_frame > 0 & true_frame <= params$nframes), , drop = FALSE] all_frames$.frame <- all_frames$.frame - min(all_frames$.frame) + 1 all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) # HELPERS ----------------------------------------------------------------- get_row_time <- function(data, quo, nframes, range, after = FALSE) { if (after || !require_stat(quo[[2]])) { get_times(data, quo, nframes, range) } else { eval_placeholder(data) } } get_times <- function(data, var, nframes, range) { times <- lapply(data, safe_eval, expr = var) times <- standardise_times(times, 'time') time_class <- times$class times <- times$times if (is.null(range)) { range <- range(unlist(times)) } else { if (!inherits(range, time_class)) { stop('range must be given in the same class as time', call. = FALSE) } range <- as.numeric(range) } times <- lapply(times, function(v) { if (is.null(v)) return(integer()) round(1 + (nframes - 1) * (v - range[1]) / diff(range)) }) frame_time <- seq(range[1], range[2], length.out = nframes) frame_time <- recast_times(frame_time, time_class) list(values = times, frame_time = frame_time) } gganimate/R/shadow-.R0000644000176200001440000000155713405665100014104 0ustar liggesusers#' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto Shadow <- ggproto('Shadow', NULL, exclude_layer = integer(0), params = list(), setup_params = function(self, data, params) { params }, train = function(self, data, params) { params }, get_frames = function(self, params, i) { integer(0) }, prepare_shadow = function(self, shadow, params) { lapply(shadow, do.call, what = rbind) }, prepare_frame_data = function(self, data, shadow, params, frame_ind, shadow_ind) { Map(function(d, s, e) { if (e) return(d[[1]]) rbind(s, d[[1]]) }, d = data, s = shadow, e = seq_along(data) %in% params$excluded_layers) } ) #' @importFrom ggplot2 ggplot_add #' @export ggplot_add.Shadow <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$shadow <- object plot } gganimate/R/view-static.R0000644000176200001440000000035713405665100014776 0ustar liggesusers#' Keep a fixed view that include all of the data #' #' This view keeps positional scales fixed across all frames #' #' @family views #' #' @export #' @importFrom ggplot2 ggproto view_static <- function() { ggproto("ViewStatic", View) } gganimate/R/transformr.R0000644000176200001440000000104613405665100014730 0ustar liggesuserstransform_path <- function(...) { if (!requireNamespace('transformr', quietly = TRUE)) { stop('transformr is required to tween paths and lines') } transformr::tween_path(...) } transform_polygon <- function(...) { if (!requireNamespace('transformr', quietly = TRUE)) { stop('transformr is required to tween polygons') } transformr::tween_polygon(...) } transform_sf <- function(...) { if (!requireNamespace('transformr', quietly = TRUE)) { stop('transformr is required to tween sf layers') } transformr::tween_sf(...) } gganimate/R/gganim.R0000644000176200001440000000412613526573550014012 0ustar liggesusers#' @importFrom ggplot2 is.ggplot as.gganim <- function(x) { if (is.gganim(x)) return(x) if (!is.ggplot(x)) stop('Only knows how to convert ggplot to gganim', call. = FALSE) class(x) <- c('gganim', class(x)) if (inherits(x, 'ggraph')) { cl <- class(x) ggraph_ind <- cl == 'ggraph' cl <- c(cl[ggraph_ind], cl[!ggraph_ind]) class(x) <- cl } x$transition <- transition_null() x$view <- view_static() x$shadow <- shadow_null() x$transmuters <- transmuter_list() x$ease <- ease_aes('linear') x } is.gganim <- function(x) inherits(x, 'gganim') #' @export plot.gganim <- function(x, frame = 50, total = 100, detail = 1, newpage = is.null(vp), vp = NULL, ...) { plot <- prerender(x, total * detail) plot$scene$plot_frame(plot, frame * detail, newpage = newpage, vp = vp) invisible(x) } #' @rdname animate #' @export print.gganim <- function(x, ...) { anim <- animate(x, ...) print(anim, info = FALSE) } #' @rdname animate #' @param options chunk options for the currently executing chunk #' @export knit_print.gganim <- function(x, options, ...) { knitr_options <- get_knitr_options(options) if (knitr::is_latex_output()) { knitr_options$device <- 'current' do.call(animate, c(list(plot = x), knitr_options)) } else { anim <- do.call(animate, c(list(plot = x), knitr_options)) knitr::knit_print(anim, options, ...) } } get_knitr_options <- function(options, unlist = TRUE) { opt <- options$gganimate opt$device <- opt$device %||% options$dev if (is.null(opt$width) || is.null(opt$height)) { opt$width <- options$fig.width opt$height <- options$fig.height opt$units <- 'in' opt$res <- options$dpi } if (unlist) { c(opt, options$dev.args) } else { opt$dev_args <- options$dev.args %||% list() opt$dev_args <- modifyList(opt$dev_args, opt[c('width', 'height', 'units', 'res')]) opt } } # HELPERS ----------------------------------------------------------------- set_nframes <- function(plot, n) { plot$nframes <- n plot } get_nframes <- function(plot) { if (is.null(plot$scene)) plot$nframes else plot$scene$nframes } gganimate/R/ease-aes.R0000644000176200001440000000632013406137575014231 0ustar liggesusers#' Control easing of aesthetics #' #' Easing defines how a value change to another during tweening. Will it #' progress linearly, or maybe start slowly and then build up momentum. In #' `gganimate`, each aesthetic or computed variable can be tweened with #' individual easing functions using the `ease_aes()` function. All easing #' functions implemented in `tweenr` are available, see [tweenr::display_ease] #' for an overview. Setting an ease for `x` and/or `y` will also affect the #' other related positional aesthetics (e.g. `xmin`, `yend`, etc). #' #' @param default The default easing function to use (defaults to `'linear'`) #' @param ... Override easing for specific aesthetics #' #' @section Easing functions: #' - **quadratic** Models a power-of-2 function #' - **cubic** Models a power-of-3 function #' - **quartic** Models a power-of-4 function #' - **quintic** Models a power-of-5 function #' - **sine** Models a sine function #' - **circular** Models a pi/2 circle arc #' - **exponential** Models an exponential function #' - **elastic** Models an elastic release of energy #' - **back** Models a pullback and relase #' - **bounce** Models the bouncing of a ball #' #' *Modifiers* \cr #' - **-in** The easing function is applied as-is #' - **-out** The easing function is applied in reverse #' - **-in-out** The first half of the transition it is applied as-is, while in #' the last half it is reversed #' #' @export #' @importFrom ggplot2 ggproto #' #' @examples #' anim <- ggplot(mtcars, aes(mpg, disp)) + #' transition_states(gear, transition_length = 2, state_length = 1) + #' enter_fade() + #' exit_fade() #' #' \dontrun{ #' # Default uses linear easing #' animate(anim) #' } #' #' # Change all to 'cubic-in-out' for a smoother appearance #' anim1 <- anim + #' ease_aes('cubic-in-out') #' \dontrun{ #' animate(anim1) #' } #' #' # Only change easing of y variables #' anim2 <- anim + #' ease_aes(y = 'bounce-in') #' \dontrun{ #' animate(anim2) #' } #' ease_aes <- function(default = 'linear', ...) { aesthetics <- list(...) if (length(aesthetics) > 0) { if (is.null(names(aesthetics))) stop('Aesthetics must be named', call. = FALSE) if ('x' %in% names(aesthetics)) { aesthetics[setdiff(x_aes, names(aesthetics))] <- aesthetics['x'] } if ('y' %in% names(aesthetics)) { aesthetics[setdiff(y_aes, names(aesthetics))] <- aesthetics['y'] } aes_names <- sub('color', 'colour', names(aesthetics)) aesthetics <- unlist(aesthetics) } else { aes_names <- character() aesthetics <- character() } ggproto(NULL, EaseAes, default = default, aesthetics = aesthetics, aes_names = aes_names) } EaseAes <- ggproto("EaseAes", NULL, default = NULL, aesthetics = character(), aes_names = character(), get_ease = function(self, layer_data) { lapply(layer_data, function(d) { base <- rep(self$default, ncol(d)) common_aes <- intersect(names(d), self$aes_names) if (length(common_aes) > 0) { base[match(common_aes, names(d))] <- self$aesthetics[match(common_aes, self$aes_names)] } base }) } ) #' @importFrom ggplot2 ggplot_add #' @export ggplot_add.EaseAes <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$ease <- object plot } gganimate/R/transmute-.R0000644000176200001440000002327713462643255014656 0ustar liggesusers#' Define how entering and exiting data behaves #' #' The purpose of `enter_*()` and `exit_*()` is to control what happens with #' data that does not persist during a tween. In general the non-persistent data #' is transformed to an *invisible* version that can be tweened to, e.g. by #' setting the opacity to 0 or be moving the element off-screen. It is possible #' to define your own transformations, or rely on some of the build in #' *effects*. #' #' @param early Should the data appear in the beginning of the transition or in #' the end #' @param alpha The start/end transparency. #' @param colour,color,fill The start/end colour and fill the elements should #' (dis)appear into #' @param x_loc,y_loc Start and end positions of the graphic elements #' @param x_mod,y_mod Modification to add to the entering or exiting data #' @param size The proportional start/end size. `0` means complete shrinking #' while `1` means no shrinking #' @param default A default transformation to use #' @param name A name for the manual modification (only used when printing the #' object) #' @param ... Additional specific transformations either named by the geom #' (e.g. `bar`, or by its position in the layer stack, e.g. `"2"`) #' #' @section User-defined transformations: #' All enter/exit functions allows the user to add additional transformation #' functions targeting specific layers. If the functions are named, then the #' name is understood to reference the class of geoms it applies to. If the #' functions are unnamed or numbered they will apply to the layer with a #' matching index in the stack. Named and indexed transformations cannot be #' mixed. #' #' All modifications except `enter_manual()`/`exit_manual()` sets a range of #' modifications already, but further can be added with the `...`. For the #' manual versions a `default` transformation can be set which will apply to all #' layers that does not match any of the other given transformations. Often a #' single default transformation is enough and no specific transformations are #' needed. #' #' Transformation can be given as any expression that can be converted with #' [rlang::as_function()]. This means that `purrr` style lambda functions are #' allowed in addition to anonymous functions etc. Transformation functions must #' accept a data.frame and return a data.frame of the same dimensions. The #' function will be called with the entering/exiting layer data, except for the #' case of polygon- and path-like layers in which case the function recieves the #' entering/exiting polygon/path data one by one. A special option is to set a #' transformation as `NULL` instead of a function. In that case the entering and #' exiting data will simply appear/disappear when it is no longer part of a #' frame. #' #' @section Modification composition: #' Enter and exit modifications are composable so that multiple different ones #' can be added to an animation and will be applied in turn. You can also #' combine multiples and save them as a new enter or exit modification using #' `c()`. #' #' Due to the composable nature of enter and exit modifications it is not #' possible to overwrite a prior modification by adding a new. If it is needed #' to start from scratch then the sentinels `enter_reset()` and `exit_reset()` #' are provided which clears all prior modifications. #' #' @section Modification types: #' A range of modification types are provided by `gganimate` and using #' `enter_manual()`/`exit_manual()` or modification composition it is possible #' to create your own. #' #' **appear**/**disappear** will simply make elements appear/disappear at either #' the start or end of the transition. The default if nothing else is added. #' #' **fade** will simply set the alpha value to zero making the elements fade #' in/out during the transition. #' #' **grow**/**shrink** will set the elements to zero size making them gradually #' grow into / shrink out of existence. Zero size depends on the type of layer, #' e.g. polygons/paths will have all their points set to the mean, while points #' will have size/stroke set to zero. #' #' **recolour**/**recolor** will change the colour and/or fill of the elements #' making them gradually change from the defined colour and into their try #' colour. Be aware that unless the colour and fill are set to the same as the #' background colour of the plot this modification needs to be combined with #' others to ensure that elements does not abruptly appear. #' #' **fly** will set a specific x and y position where all elements will enter #' from/ exit to, irrespectible of their real position. #' #' **drift** will modify the real position of the entering and exiting elements #' by a specified amount, e.g. setting `x_mod = -5` will let all elements enter #' from/exit to the left with a terminal position 5 points to the left of the #' real position. #' #' @name enter_exit #' @rdname enter_exit #' @aliases enter exit #' #' @examples #' # Default is appear/disappear #' anim <- ggplot(mtcars, aes(factor(gear), mpg)) + #' geom_boxplot() + #' transition_states(gear, 2, 1) #' #' # Fade-in, fly-out #' anim1 <- anim + #' enter_fade() + #' exit_fly(x_loc = 7, y_loc = 40) #' #' # Enter and exit accumulates #' anim2 <- anim + #' enter_fade() + enter_grow() + #' exit_fly(x_loc = 7, y_loc = 40) + exit_recolour(fill = 'forestgreen') #' NULL #' @importFrom ggplot2 ggproto create_factory <- function(type, default, ..., name = 'manual') { fac_class <- switch(type, enter = 'EnterFactory', exit = 'ExitFactory') factories <- prepare_factories(default, ...) ggproto(fac_class, TransmuteFactory, factory_layer = list(list( default = factories$default, positions = factories$positions, classes = factories$classes )), name = name ) } create_resetter <- function(type) { fac_class <- switch(type, enter = 'EnterFactory', exit = 'ExitFactory') ggproto(fac_class, TransmuteFactory, reset = TRUE) } #' @importFrom ggplot2 ggproto TransmuteFactory <- ggproto('TransmuteFactory', NULL, factory_layer = list(), name = '', reset = FALSE, print = function(self, ...) { cat('<', class(self)[1], if (self$reset) ' (Resetter)' else '', '>\n', sep = '') if (!self$reset) cat(' Stages: ', paste(self$name, collapse = ', '), '\n', sep = '') invisible(self) }, add_factory = function(self, x) { if (!self$inherit(x)) stop("Can only combine factories of same class", call. = FALSE) if (x$reset) { self$factory_layer <- list() self$name <- character() self$reset <- TRUE } else { self$factory_layer <- c(self$factory_layer, x$factory_layer) self$name <- c(self$name, x$name) self$reset <- FALSE } invisible(self) }, inherit = function(self, x) { inherits(x, class(self)[1]) }, get_factories = function(self, layers) { f_layers <- lapply(self$factory_layer, function(f_layer) { if (length(f_layer$positions) != 0) { factories <- rep(list(f_layer$default), length(layers)) factories[as.integer(names(f_layer$positions))] <- f_layer$positions } else if (length(f_layer$classes) != 0) { lapply(layers, function(l) { best <- inherits(l$geom, names(f_layer$classes), which = TRUE) if (all(best == 0)) { f_layer$default } else { best <- which(best != 0 & best == min(best[best != 0])) f_layer$classes[[best[1]]] } }) } else { rep(list(f_layer$default), length(layers)) } }) lapply(seq_along(layers), function(i) { factory_line <- lapply(f_layers, `[[`, i) if (any(vapply(factory_line, is.null, logical(1)))) return(NULL) function(x) { for (i in seq_along(factory_line)) { x <- factory_line[[i]](x) } x } }) }, clone = function(self) { ggproto(NULL, self) } ) #' @export c.TransmuteFactory <- function(...) { factories <- list(...) if (length(factories) == 1) return(factories[[1]]) # This is solemnly there to please the byte-compiler from R3.6 and onwards # "Everything under heaven is in utter chaos; the situation is excellent." if (!all(vapply(factories, inherits, logical(1), what = 'TransmuteFactory'))) return(factories) factories[[1]] <- factories[[1]]$clone() Reduce(function(l, r) l$add_factory(r), factories) } #' @export #' @importFrom ggplot2 ggplot_add ggplot_add.EnterFactory <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$transmuters <- plot$transmuters$clone() plot$transmuters$add_enter(object) plot } #' @export #' @importFrom ggplot2 ggplot_add ggplot_add.ExitFactory <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$transmuters <- plot$transmuters$clone() plot$transmuters$add_exit(object) plot } # HELPERS ----------------------------------------------------------------- #' @importFrom rlang as_function maybe_function <- function(x) if (is.null(x)) x else as_function(x) capitalise <- function(x) { x1 <- substring(x, 1L, 1L) if (nchar(x) >= 3L && x1 %in% c("'", "\"")) paste0(x1, toupper(substring(x, 2L, 2L)), tolower(substring(x, 3L))) else paste0(toupper(x1), tolower(substring(x, 2L))) } prepare_factories <- function(default, ...) { default <- maybe_function(default) specials <- lapply(list(...), maybe_function) positions <- list() classes <- list() if (length(specials) != 0) { if (all(grepl('^\\d+$', names(specials)))) { if (is.null(names(specials))) names(specials) <- as.character(seq_along(specials)) positions = specials } else { geoms <- sub('geom_?', '', names(specials), ignore.case = TRUE) names(specials) <- paste0('Geom', vapply(tolower(geoms), capitalise, character(1))) classes <- specials } } list(default = default, positions = positions, classes = classes) } gganimate/R/aaa.R0000644000176200001440000000252613611326032013256 0ustar liggesusers#' @importFrom ggplot2 scale_x_continuous x_aes <- scale_x_continuous()$aesthetics #' @importFrom ggplot2 scale_y_continuous y_aes <- scale_y_continuous()$aesthetics #' @importFrom rlang eval_tidy safe_eval <- function(expr, data) { value <- tryCatch(eval_tidy(expr, data), error = function(e) numeric()) if (!is.function(value) && !is.environment(value) && !is.symbol(value) && !is.language(value) && (length(value) == 1 || length(value) == nrow(data))) { value } else { NULL } } #' @importFrom rlang quo_is_missing require_quo <- function(expr, name) { if (quo_is_missing(expr)) { stop(name, ' must be provided', call. = FALSE) } } require_stat <- function(x) { if (is.call(x)) { if (identical(x[[1]], quote(stat))) { TRUE } else { any(vapply(x, require_stat, logical(1))) } } else { FALSE } } `%?%` <- function(l, r) if (missing(l)) r else l png_dim <- function(file) { if (!file.exists(file)) { stop('Provided file does not exist', call. = FALSE) } bts <- as.integer(readBin(file, n = 24L, what = "raw")) if (!all(bts[1:8] == c(137, 80, 78, 71, 13, 10, 26 ,10))) { stop('Provided file does not appear to be a png', call. = FALSE) } c(bts[21] * 2^24 + bts[22] * 2^16 + bts[23] * 2^8 + bts[24], bts[17] * 2^24 + bts[18] * 2^16 + bts[19] * 2^8 + bts[20]) } gganimate/R/transition_reveal.R0000644000176200001440000001406213415327154016272 0ustar liggesusers#' Reveal data along a given dimension #' #' This transition allows you to let data gradually appear, based on a given #' time dimension. In contrast to e.g. [transition_time()] `transition_reveal()` #' calculates intermediary values at exact positions instead of coercing raw #' values into the closest frame. It further keeps old data for path and polygon #' type layers so that they are gradually build up instead of being a set of #' disconnected segments as will happen when using [transition_time()] and #' [shadow_mark()] together. #' #' @param along An unquoted expression giving the dimension to tween along. For #' a gradually revealing time series this should be set to the same as the `x` #' aesthetic. #' @param range The time range to animate. If `NULL` it will be set to the range #' of `along` #' @param keep_last For non-path/polygon layers should the last row be kept for #' subsequent frames. #' @param id **Deprecated** #' #' @section Label variables: #' `transition_along` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **frame_along** gives the position on the along-dimension that the current #' frame corresponds to #' #' @section Object permanence: #' `transition_reveal` uses the group aesthetic of each layer to identify #' which rows in the input data correspond to the same graphic element and will #' therefore define a a whole to be revealed over the animation. #' The group aesthetic, if not set, will be calculated from the interaction of all #' discrete aesthetics in the layer (excluding `label`), so it is often better #' to set it explicetly when animating, to make sure your data is interpreted in #' the right way. If the group aesthetic is not set, and no discrete aesthetics #' exists then all rows will have the same group. #' #' @inheritSection transition_states Computed Variables #' #' @family transitions #' #' @export #' @importFrom ggplot2 ggproto #' #' @examples #' anim <- ggplot(airquality, aes(Day, Temp, group = Month)) + #' geom_line() + #' transition_reveal(Day) #' #' # Non-paths will only show the current position, not the history #' anim1 <- ggplot(airquality, aes(Day, Temp, group = Month)) + #' geom_line() + #' geom_point(colour = 'red', size = 3) + #' transition_reveal(Day) #' #' # Points can be kept by giving them a unique group and set `keep = TRUE` (the #' # default) #' anim2 <- ggplot(airquality, aes(Day, Temp, group = Month)) + #' geom_line() + #' geom_point(aes(group = seq_along(Day))) + #' geom_point(colour = 'red', size = 3) + #' transition_reveal(Day) #' transition_reveal <- function(along, range = NULL, keep_last = TRUE, id) { if (!missing(id)) warning('The `id` argument has been deprecated. Set `id` in each layer with the `group` aesthetic', call. = FALSE) along_quo <- enquo(along) require_quo(along_quo, 'along') ggproto(NULL, TransitionReveal, params = list( along_quo = along_quo, range = range, keep_last = keep_last ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_along TransitionReveal <- ggproto('TransitionReveal', Transition, mapping = '(.+)', var_names = 'along', setup_params = function(self, data, params) { params$along <- get_row_along(data, params$along_quo, params$nframes, params$range) params$require_stat <- is_placeholder(params$along) static <- lengths(params$along$values) == 0 params$row_id <- Map(function(t, s) if (s) character() else t, t = params$along$values, s = static) params }, setup_params2 = function(self, data, params, row_vars) { if (is_placeholder(params$along)) { params$along <- get_row_along(data, params$along_quo, params$nframes, params$range, after = TRUE) } else { params$along$values <- row_vars$along } static <- lengths(params$along$values) == 0 params$row_id <- Map(function(t, s) if (s) character() else t, t = params$along$values, s = static) params$frame_info <- data.frame(frame_along = params$along$frame_time) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_vars <- self$get_row_vars(data) if (is.null(row_vars)) return(data) data$group <- paste0(row_vars$before, row_vars$after) time <- as.numeric(row_vars$along) all_frames <- switch( type, point = tween_along(data, ease, params$nframes, !!time, group, c(1, params$nframes), FALSE, params$keep_last), path = tween_along(data, ease, params$nframes, !!time, group, c(1, params$nframes), TRUE, params$keep_last), polygon = tween_along(data, ease, params$nframes, !!time, group, c(1, params$nframes), TRUE, params$keep_last), stop(type, ' layers not currently supported by transition_reveal', call. = FALSE) ) all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) # HELPERS ----------------------------------------------------------------- get_row_along <- function(data, quo, nframes, range, after = FALSE) { if (!after && require_stat(quo[[2]])) { return(eval_placeholder(data)) } times <- lapply(data, safe_eval, expr = quo) times <- standardise_times(times, 'along') time_class <- times$class times <- times$times if (is.null(range)) { range <- range(unlist(times)) } else { if (!inherits(range, time_class)) { stop('range must be given in the same class as time', call. = FALSE) } range <- as.numeric(range) } full_length <- diff(range) frames <- lapply(times, function(v) { if (length(v) == 0) return(numeric()) frame <- round((nframes - 1) * (v - range[1])/full_length) + 1 nc <- nchar(max(frame)) + 1 sprintf(paste0('%0', nc, 'i'), frame) }) frame_time <- seq(range[1], range[2], length.out = nframes) frame_time <- recast_times(frame_time, time_class) list(values = frames, frame_time = frame_time) } gganimate/R/view-follow.R0000644000176200001440000000506213415625271015015 0ustar liggesusers#' Let the view follow the data in each frame #' #' This view will set the panels to include the data present in the frame. #' #' @param fixed_x,fixed_y Either a logical indicating if the dimension should #' not be modified by the view, or a numeric vector giving the lower and upper #' bounds of the dimension. For the latter, an `NA` value will be substituted #' for whatever is calculated by the view (e.g. `fixed_x = c(0, NA)`) will fix #' the minimum x value to 0 and let the view calculate the upper bound. #' @param exclude_layer Integer vector of layer indices that should be ignored #' when calculating the view #' @param aspect_ratio If the coord is fixed, ensure that the view matches the #' given aspect ratio. Will override anything given in `fixed_x`/`fixed_y` #' #' @family views #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 4, state_length = 1) + #' view_follow() #' #' # Fixing a dimension can be done in general #' anim1 <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 4, state_length = 1) + #' view_follow(fixed_x = TRUE) #' #' # ...or just for one side of the range #' anim1 <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 4, state_length = 1) + #' view_follow(fixed_x = c(4, NA), fixed_y = c(2, NA)) #' view_follow <- function(fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1) { ggproto(NULL, ViewFollow, exclude_layer = exclude_layer, aspect_ratio = aspect_ratio, fixed_lim = list(x = fixed_x, y = fixed_y)) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto ViewFollow <- ggproto('ViewFollow', View, set_view = function(self, plot, params, i) { if (inherits(plot$layout$coord, 'CoordPolar')) { stop('This view does not support polar coordinates') } ranges <- self$get_ranges(plot$data, params) x_range <- range(inf.omit(unlist(lapply(ranges, `[[`, 'x')))) y_range <- range(inf.omit(unlist(lapply(ranges, `[[`, 'y')))) x_range <- plot$layout$panel_scales_x[[1]]$trans$inverse(x_range) y_range <- plot$layout$panel_scales_y[[1]]$trans$inverse(y_range) self$reset_limits(plot, x_range, y_range) } ) inf.omit <- function(x) x[is.finite(x)] gganimate/R/transmuters.R0000644000176200001440000001564413413633753015143 0ustar liggesuserstransmuter_list <- function() { ggproto(NULL, TransmuterList) } TransmuterList <- ggproto('TransmuterList', NULL, enter = NULL, exit = NULL, enter_factories = list(), exit_factories = list(), add_enter = function(self, enter) { if (enter$reset) { self$enter <- NULL } else if (is.null(self$enter)) { self$enter <- enter } else { self$enter$add_factory(enter) } }, add_exit = function(self, exit) { if (exit$reset) { self$exit <- NULL } else if (is.null(self$exit)) { self$exit <- exit } else { self$exit$add_factory(exit) } }, setup = function(self, layers) { if (is.null(self$enter)) self$enter <- enter_appear() self$enter_factories <- self$enter$get_factories(layers) if (is.null(self$exit)) self$exit <- exit_disappear() self$exit_factories <- self$exit$get_factories(layers) }, enter_transmuters = function(self, i = NULL) { if (is.null(i)) i <- seq_along(self$enter_factories) self$enter_factories[i] }, exit_transmuters = function(self, i = NULL) { if (is.null(i)) i <- seq_along(self$exit_factories) self$exit_factories[i] }, clone = function(self) { ggproto(NULL, self, enter = if (is.null(self$enter)) NULL else self$enter$clone(), exit = if (is.null(self$exit)) NULL else self$exit$clone() ) } ) transmute_appear <- function(type, ..., early = FALSE, name) { f <- if (early) { function(x) x } else { NULL } create_factory(type, default = f, ..., name = name) } #' @importFrom scales alpha transmute_fade <- function(type, ..., alpha = 0, name) { create_factory( type, default = function(x) { if (!is.null(x$edge_alpha)) { no_alpha <- is.na(x$edge_alpha) x$edge_alpha[!no_alpha] <- alpha } else if (!is.null(x$alpha)) { no_alpha <- is.na(x$alpha) x$alpha[!no_alpha] <- alpha } else { no_alpha <- TRUE } if (!is.null(x$colour)) x$colour[no_alpha] <- alpha(x$colour[no_alpha], alpha) if (!is.null(x$fill)) x$fill[no_alpha] <- alpha(x$fill[no_alpha], alpha) if (!is.null(x$edge_colour)) x$edge_colour[no_alpha] <- alpha(x$edge_colour[no_alpha], alpha) if (!is.null(x$edge_fill)) x$edge_fill[no_alpha] <- alpha(x$edge_fill[no_alpha], alpha) x }, smooth = function(x) { if (!is.null(x$alpha)) { no_alpha <- is.na(x$alpha) x$alpha[!no_alpha] <- alpha } if (!is.null(x$fill)) x$fill[no_alpha] <- alpha(x$fill[no_alpha], alpha) if (!is.null(x$colour)) x$colour <- alpha(x$colour, alpha) x }, ..., name = name ) } transmute_grow <- function(type, ..., size = 0, name) { create_factory( type, default = function(x) { if (!is.null(x$size)) x$size <- size * x$size if (!is.null(x$width)) x$width <- size * x$width if (!is.null(x$stroke)) x$stroke <- size * x$stroke if (!is.null(x$edge_size)) x$edge_size <- size * x$edge_size if (!is.null(x$edge_width)) x$edge_width <- size * x$edge_width x }, polygon = shrink_multielement(size), violin = shrink_multielement(size), path = shrink_multielement(size), boxplot = function(x) { if (size == 0) { x$ymin <- x$middle x$lower <- x$middle x$notchlower <- x$middle x$notchupper <- x$middle x$upper <- x$middle x$ymax <- x$middle } else { x$ymin <- tween_at(x$middle, x$ymin, size, 'linear') x$lower <- tween_at(x$middle, x$lower, size, 'linear') x$notchlower <- tween_at(x$middle, x$notchlower, size, 'linear') x$notchupper <- tween_at(x$middle, x$notchupper, size, 'linear') x$upper <- tween_at(x$middle, x$upper, size, 'linear') x$ymax <- tween_at(x$middle, x$ymax, size, 'linear') } x }, bar = function(x) { x$y <- x$y * size x$ymax <- x$ymax * size x }, col = function(x) { x$y <- x$y * size x$ymax <- x$ymax * size x }, ..., name = name ) } transmute_recolour <- function(type, ..., colour = 'white', fill = colour, name) { create_factory( type, default = function(x) { if (!is.na(colour) && !is.null(x$colour)) x$colour <- colour if (!is.na(fill) && !is.null(x$fill)) x$fill <- fill if (!is.na(colour) && !is.null(x$edge_colour)) x$edge_colour <- colour if (!is.na(fill) && !is.null(x$edge_fill)) x$edge_fill <- fill x }, ..., name = name ) } transmute_fly <- function(type, ..., x_loc = NA, y_loc = NA, name) { if (is.na(x_loc) && is.na(y_loc)) warning('Both x_loc and y_loc are `NA`. No position change will occur.', call. = FALSE) create_factory( type, default = function(x) { if (!is.na(x_loc)) { included_x <- intersect(x_aes, names(x)) x[, included_x] <- x[, included_x] - x[, 'x'] + x_loc } if (!is.na(y_loc)) { included_y <- intersect(y_aes, names(x)) x[, included_y] <- x[, included_y] - x[, 'y'] + y_loc } x }, boxplot = function(x) { if (!is.na(x_loc)) { included_x <- intersect(x_aes, names(x)) x[, included_x] <- x[, included_x] - x[, 'x'] + x_loc } if (!is.na(y_loc)) { included_y <- intersect(y_aes, names(x)) x[, included_y] <- x[, included_y] - (x[, 'lower'] + x[, 'upper'])/2 + y_loc } x }, polygon = move_multielement(x_loc, y_loc), violin = move_multielement(x_loc, y_loc), path = move_multielement(x_loc, y_loc), ..., name = name ) } transmute_drift <- function(type, ..., x_mod = 0, y_mod = 0, name) { if (x_mod == 0 && y_mod == 0) warning('Both x_mod and y_mod are 0. No position change will occur.', call. = FALSE) create_factory( type, default = function(x) { included_x <- intersect(x_aes, names(x)) x[, included_x] <- x[, included_x] + x_mod included_y <- intersect(y_aes, names(x)) x[, included_y] <- x[, included_y] + y_mod x }, ..., name = name ) } # HELPERS ----------------------------------------------------------------- shrink_multielement <- function(size = 0) { function(x) { mean_x <- vapply(split(x$x, x$group), mean, numeric(1)) mean_y <- vapply(split(x$y, x$group), mean, numeric(1)) group <- match(x$group, names(mean_x)) if (size == 0) { x$x <- mean_x[group] x$y <- mean_y[group] } else { x$x <- tween_at(mean_x[group], x$x, size, 'linear') x$y <- tween_at(mean_y[group], x$y, size, 'linear') } x } } move_multielement <- function(x_loc, y_loc) { function(x) { if (!is.na(x_loc)) { mean_x <- vapply(split(x$x, x$group), mean, numeric(1)) group <- match(x$group, names(mean_x)) x$x <- x$x - mean_x[group] + x_loc } if (!is.na(y_loc)) { mean_y <- vapply(split(x$y, x$group), mean, numeric(1)) if (is.na(x_loc)) group <- match(x$group, names(mean_y)) x$y <- x$y - mean_y[group] + y_loc } x } } gganimate/R/post_process.R0000644000176200001440000000347113405665100015262 0ustar liggesusers#' Access metadata about the frames in an animation #' #' This function extracts the metadata generated about each frame during #' rendering. It corresponds to the information available to the labels for #' string literal interpretation and is thus dependent on the transition and #' view used for the animation. #' #' @param animation The animation to extract metadata from. Defaults to the last #' rendered animation #' #' @return A data.frame with a row per frame in the animation and metadata as #' columns #' #' @export frame_vars <- function(animation = last_animation()) { attr(animation, 'frame_vars') } #' Split an animation into chunks #' #' Sometimes it is of interest to split an animation out in smaller chunks so #' they can be orchestrated, e.g. in a presentation. This function lets you #' provide a 'factor' to split by in the same way as [base::split()] though this #' one will be evaluated in the context of the animations [frame_vars()] data, #' so you can split directly on frame metadata. #' #' @inheritParams frame_vars #' @param by An unquoted expression to be evaluated in the context of the frame #' metadata. The result must be of equal length to the number of frames in the #' animation and define a grouping #' #' @return Depending on the output type of the renderer used to produce the #' animation. Often a list with elements referencing the chunks of the #' animation. that can then be saved individually. #' #' @export split_animation <- function(animation = last_animation(), by) { by <- enquo(by) fv <- frame_vars(animation) by <- eval_tidy(by, fv) if (length(by) != nrow(fv)) { stop('`by` must have the same length as the number of frames', call. = FALSE) } tryCatch( split(animation, by), error = function(e) { stop('The renderer output doesn\'t support splitting') } ) } gganimate/R/transmute-enter.R0000644000176200001440000000257513405665100015700 0ustar liggesusers#' @rdname enter_exit #' @export enter_manual <- function(default = NULL, ..., name = 'manual') { create_factory('enter', default, ..., name = name) } #' @rdname enter_exit #' @export enter_appear <- function(early = FALSE, ...) { transmute_appear('enter', early = early, ..., name = 'appear') } #' @rdname enter_exit #' @export enter_fade <- function(..., alpha = 0) { transmute_fade('enter', ..., alpha = alpha, name = 'fade') } #' @rdname enter_exit #' @export enter_grow <- function(..., size = 0) { transmute_grow('enter', ..., size = size, name = 'grow') } #' @rdname enter_exit #' @export enter_recolour <- function(..., colour = 'white', fill = colour) { transmute_recolour('enter', ..., colour = colour, fill = fill, name = 'recolour') } #' @rdname enter_exit #' @export enter_recolor <- function(..., color = 'white', fill = color) { enter_recolour(..., colour = color, fill = fill) } #' @rdname enter_exit #' @export enter_fly <- function(..., x_loc = NA, y_loc = NA) { transmute_fly('enter', ..., x_loc = x_loc, y_loc = y_loc, name = 'fly') } #' @rdname enter_exit #' @export enter_drift <- function(..., x_mod = 0, y_mod = 0) { transmute_drift('enter', ..., x_mod = x_mod, y_mod = y_mod, name = 'drift') } # RESET ------------------------------------------------------------------- #' @rdname enter_exit #' @export enter_reset <- function() { create_resetter('enter') } gganimate/R/match_shapes.R0000644000176200001440000000031513405665100015170 0ustar liggesusers#' @rdname layer_type #' #' @export match_shapes <- function(x) { UseMethod('match_shapes') } #' @export match_shapes.default <- function(x) NULL #' @export match_shapes.StatContour <- function(x) FALSE gganimate/R/transition-manual.R0000644000176200001440000001034213406443354016205 0ustar liggesusers#' Create an animation by specifying the frame membership directly #' #' This transition allows you to map a variable in your data to a specific frame #' in the animation. No tweening of data will be made and the number of frames #' in the animation will be decided by the number of levels in the frame #' variable. #' #' @param frames The unquoted name of the column holding the frame membership. #' @param ... Additional variables #' @param cumulative Keep data from previous frames as part of the current frame #' data #' #' @family transitions #' #' @section Label variables: #' `transition_states` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **previous_frame** The name of the last frame the animation was at #' - **current_frame** The name of the current frame #' - **next_frame** The name of the next frame in the animation #' #' @section Object permanence: #' `transition_manual` does not link rows across data to the same graphic #' element. Every frame is a discrete state and no animation between the states #' is done. #' #' @inheritSection transition_states Computed Variables #' #' @importFrom rlang enquo #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(mtcars, aes(factor(gear), mpg)) + #' geom_boxplot() + #' transition_manual(gear) #' #' # Using `cumulative = TRUE` to keep data from older frames #' anim2 <- ggplot(mtcars, aes(factor(gear), mpg)) + #' geom_boxplot() + #' transition_manual(gear, cumulative = TRUE) #' #' # Use `factor()` to set the order of the frames #' anim3 <- ggplot(mtcars, aes(factor(gear), mpg)) + #' geom_boxplot() + #' transition_manual(factor(gear, levels = c('4', '3', '5'))) #' transition_manual <- function(frames, ..., cumulative = FALSE) { frames_quo <- enquo(frames) require_quo(frames_quo, 'frames') frame_vars <- data.frame(..., stringsAsFactors = FALSE, check.names = FALSE) ggproto(NULL, TransitionManual, params = list(frames_quo = frames_quo, frame_vars = frame_vars, cumulative = cumulative)) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match TransitionManual <- ggproto('TransitionManual', Transition, mapping = '(.*)', var_names = 'frames', setup_params = function(self, data, params) { params$frames <- get_row_frames(data, params$frames_quo) params$reuire_stat <- is_placeholder(params$frames) params$row_id <- params$frames$values params }, setup_params2 = function(self, data, params, row_vars) { if (is_placeholder(params$frames)) { params$frames <- get_row_frames(data, params$frames_quo, after = TRUE) } else { params$frames$values <- lapply(row_vars$frames, as.integer) } all_frames <- params$frames$levels params$row_id <- params$frames$values params$frame_info <- data.frame( previous_frame = c('', all_frames[-length(all_frames)]), current_frame = all_frames, next_frame = c(all_frames[-1], '') ) if (nrow(params$frame_vars) != 0) { if (nrow(params$frame_info) != nrow(params$frame_vars)) { stop('Additional frame variables must have the same length as the number of frames', call. = FALSE) } params$frame_info <- cbind(params$frame_info, params$frame_vars) } params$nframes <- nrow(params$frame_info) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { if (!params$cumulative) return(data) row_state <- self$get_row_vars(data) if (is.null(row_state)) return(data) data$group <- paste0(row_state$before, row_state$after) state <- as.integer(row_state$frames) states <- split(seq_len(nrow(data)), state) all_frames <- do.call(rbind, lapply(seq_along(states), function(i) { index <- unlist(states[seq_len(i)]) frame <- data[index, , drop = FALSE] frame$.frame <- i frame })) all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) get_row_frames <- function(data, quo, after = FALSE) { if (after || !require_stat(quo[[2]])) { combine_levels(data, quo) } else { eval_placeholder(data) } } gganimate/R/view-.R0000644000176200001440000000427513415625305013575 0ustar liggesusers#' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto View <- ggproto('View', NULL, exclude_layer = numeric(0), fixed_lim = list(x = FALSE, y = FALSE), aspect_ratio = 1, setup_params = function(self, data, params) { params }, train = function(self, data, params) { params }, set_view = function(self, plot, params, i) { plot }, reset_limits = function(self, plot, xlim, ylim) { if (is.logical(self$fixed_lim$x)) { if (self$fixed_lim$x) xlim <- plot$layout$coord$limits$x } else { xlim[!is.na(self$fixed_lim$x)] <- self$fixed_lim$x[!is.na(self$fixed_lim$x)] } if (is.logical(self$fixed_lim$y)) { if (self$fixed_lim$y) ylim <- plot$layout$coord$limits$y } else { ylim[!is.na(self$fixed_lim$y)] <- self$fixed_lim$y[!is.na(self$fixed_lim$y)] } if (!plot$layout$coord$is_free()) { width <- diff(xlim) height <- diff(ylim) current_asp <- if (width == height) 1 else if (height == 0) Inf else width / height if (current_asp > self$aspect_ratio) { new_height <- width / self$aspect_ratio pad <- (new_height - height) / 2 ylim <- ylim + c(-pad, pad) } else if (current_asp < self$aspect_ratio) { new_width <- height * self$aspect_ratio pad <- (new_width - width) / 2 xlim <- xlim + c(-pad, pad) } } plot$layout$coord$limits$x <- xlim plot$layout$coord$limits$y <- ylim plot$layout$setup_panel_params() plot }, get_ranges = function(self, data, params) { lapply(data, function(d) { if ('geometry' %in% names(d)) { bbox <- sf::st_bbox(d$geometry) list(x = c(bbox$xmin, bbox$xmax), y = c(bbox$ymin, bbox$ymax)) } else { x <- unlist(d[names(d) %in% x_aes]) y <- unlist(d[names(d) %in% y_aes]) list( x = if (length(x) == 0) NULL else range(x), y = if (length(y) == 0) NULL else range(y) ) } }) }, get_frame_vars = function(self, params) { NULL } ) #' @importFrom ggplot2 ggplot_add #' @export ggplot_add.View <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$view <- object plot } gganimate/R/transition-null.R0000644000176200001440000000164213413126502015674 0ustar liggesusers#' Keep all data constant across the animation #' #' @family transitions #' #' @export transition_null <- function() { ggproto(NULL, TransitionNull) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto TransitionNull <- ggproto('TransitionNull', Transition, setup_params = function(self, data, params) { params$n_layers <- length(data) params }, expand_data = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { data }, static_layers = function(self, params) { seq_len(params$n_layers) }, unmap_frames = function(self, data, params) { data }, remap_frames = function(self, data, params) { data }, finish_data = function(self, data, params) { lapply(data, list) }, adjust_nframes = function(self, data, params) { params$nframes }, get_frame_vars = function(self, params) { NULL } ) gganimate/R/shadow-null.R0000644000176200001440000000102513405665100014765 0ustar liggesusers#' A non-existent shadow #' #' This is the default shadow that simply doesn't show anything other than the #' data for the current frame. #' #' @family shadows #' #' @export shadow_null <- function() { ggproto(NULL, ShadowNull) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export ShadowNull <- ggproto('ShadowNull', Shadow, prepare_shadow = function(self, shadow, params) { shadow }, prepare_frame_data = function(self, data, shadow, params, frame_ind, shadow_ind) { lapply(data, `[[`, 1) } ) gganimate/R/shadow-mark.R0000644000176200001440000000601213415653254014756 0ustar liggesusers#' Show original data as background marks #' #' This shadow lets you show the raw data behind the current frame. Both past #' and/or future raw data can be shown and styled as you want. #' #' @param past Should raw data from earlier in the animation be shown #' @param future Should raw data from later in the animation be shown #' @param ... changes to the shadow data, e.g. `alpha = alpha/2` or #' `colour = 'grey'` #' @param exclude_layer Indexes of layers that should be excluded. #' #' @family shadows #' #' @importFrom ggplot2 ggproto #' @importFrom rlang quos #' @export #' #' @examples #' # Use any of the aesthetics to add a style to either the past or the future raw data. #' # Adding a grouping variable in a transition call prior to calling `shadow_mark()` will #' # allow transitioning through different states in time. #' #' p1 <- ggplot(airquality, aes(Day, Temp)) + #' geom_line(color = 'red', size = 1) + #' transition_time(Month) + #' shadow_mark(colour = 'black', size = 0.75) #' #' # animate(p1) #' #' # Add a future = TRUE argument to show data later in the animation. #' #' p2 <- ggplot(airquality, aes(Day, Temp)) + #' geom_line(color = 'red', size = 1) + #' transition_time(Month) + #' shadow_mark(color = 'black', size = 0.75, past = FALSE, future = TRUE) #' #' # animate(p2) #' shadow_mark <- function(past = TRUE, future = FALSE, ..., exclude_layer = NULL) { dots <- quos(...) names(dots) <- sub('color', 'colour', names(dots)) ggproto(NULL, ShadowMark, exclude_layer = exclude_layer, params = list( past = past, future = future, dots = dots ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom rlang eval_tidy ShadowMark <- ggproto('ShadowMark', Shadow, train = function(self, data, params) { params$raw <- lapply(seq_along(data), function(i) { d <- data[[i]] if (i %in% params$excluded_layers) { return(d[[1]][0, , drop = FALSE]) } d <- lapply(d, function(dd) { dd[dd$.phase == 'raw', , drop = FALSE] }) frames <- rep(seq_along(d), vapply(d, nrow, integer(1))) d <- do.call(rbind, d) for (i in names(params$dots)) { if (!is.null(d[[i]])) d[[i]] <- eval_tidy(params$dots[[i]], d) } cbind(d, .frame = frames) }) params }, prepare_frame_data = function(self, data, shadow, params, frame_ind, shadow_ind) { Map(function(d, s, e) { if (e || (!params$past && !params$future)) return(d[[1]]) s <- if (params$past && params$future) { s[s$.frame != frame_ind, , drop = FALSE] } else if (params$past) { s[s$.frame < frame_ind, , drop = FALSE] } else if (params$future) { s[s$.frame > frame_ind, , drop = FALSE] } if (nrow(s) == 0) return(d[[1]]) s$.frame <- NULL s$group <- s$group - (max(s$group) + 1) # make sure shadow groups are prior to frame group rbind(s, d[[1]]) }, d = data, s = params$raw, e = seq_along(data) %in% params$excluded_layers) } ) gganimate/R/transition-components.R0000644000176200001440000001536013415135460017116 0ustar liggesusers#' Transition individual components through their own lifecycle #' #' This transition allows individual visual components to define their own #' "life-cycle". This means that the final animation will not have any common #' "state" and "transition" phase as any component can be moving or static at #' any point in time. #' #' @param time The unquoted name of the column holding the time for each state #' of the components #' @param range The range the animation should span. Defaults to the range of #' time plus enter and exit length #' @param enter_length,exit_length How long time should be spend on enter and #' exit transitions. Defaults to 0 #' @param id **Deprecated** #' #' @section Label variables: #' `transition_components` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **frame_time** gives the time that the current frame corresponds to #' #' @section Object permanence: #' `transition_components` uses the group aesthetic of each layer to identify #' which rows in the input data correspond to the same graphic element and will #' therefore define stages in time that the element will animate through. The #' group aesthetic, if not set, will be calculated from the interaction of all #' discrete aesthetics in the layer (excluding `label`), so it is often better #' to set it explicetly when animating, to make sure your data is interpreted in #' the right way. If the group aesthetic is not set, and no discrete aesthetics #' exists then all rows will have the same group. #' #' @inheritSection transition_states Computed Variables #' #' @family transitions #' #' @importFrom rlang enquo #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' data <- data.frame( #' x = runif(10), #' y = runif(10), #' size = sample(1:3, 10, TRUE), #' time = c(1, 4, 6, 7, 9, 6, 7, 8, 9, 10), #' id = rep(1:2, each = 5) #' ) #' #' anim <- ggplot(data, aes(x, y, group = id, size = size)) + #' geom_point() + #' transition_components(time) #' #' # By default the time range is set to the range of the time varialbe (plus #' # any enter and exit length), but this can be overwritten #' anim2 <- ggplot(data, aes(x, y, group = id, size = size)) + #' geom_point() + #' transition_components(time, range = c(4, 8)) #' #' # If you are using any enter/exit functions you need to give them some time #' anim3 <- ggplot(data, aes(x, y, group = id, size = size)) + #' geom_point() + #' transition_components(time, enter_length = 2, exit_length = 2) + #' enter_grow() + #' exit_fade() #' transition_components <- function(time, range = NULL, enter_length = NULL, exit_length = NULL, id) { if (!missing(id)) warning('The `id` argument has been deprecated. Set `id` in each layer with the `group` aesthetic', call. = FALSE) time_quo <- enquo(time) require_quo(time_quo, 'time') ggproto(NULL, TransitionComponents, params = list( time_quo = time_quo, range = range, enter_length = enter_length, exit_length = exit_length ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_components TransitionComponents <- ggproto('TransitionComponents', Transition, mapping = '(.+?)', var_names = 'time', setup_params = function(self, data, params) { params$time <- get_row_comp_time(data, params$time_quo, params) params$require_stat <- is_placeholder(params$time) static <- lengths(params$time$values) == 0 params$row_id <- Map(function(t, s) if (s) character() else t, t = params$time$values, s = static) params }, setup_params2 = function(self, data, params, row_vars) { if (is_placeholder(params$time)) { params$time <- get_row_comp_time(data, params$time_quo, params, after = TRUE) } else { params$time$values <- row_vars$time } static <- lengths(params$time$values) == 0 params$enter_length <- params$time$enter_length params$exit_length <- params$time$exit_length params$range <- params$time$range params$frame_time <- params$time$frame_time params$row_id <- Map(function(t, s) if (s) character() else t, t = params$time$values, s = static) params$frame_info <- data.frame( frame_time = params$time$frame_time ) params$nframes <- nrow(params$frame_info) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_vars <- self$get_row_vars(data) if (is.null(row_vars)) return(data) data$group <- paste0(row_vars$before, row_vars$after) time <- as.numeric(row_vars$time) all_frames <- switch( type, point = tween_components(data, ease, params$nframes, !!time, group, c(1, params$nframes), enter, exit, params$enter_length, params$exit_length), stop(type, ' layers not currently supported by transition_components', call. = FALSE) ) all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) get_row_comp_time <- function(data, quo, params, after = FALSE) { if (!after && require_stat(quo[[2]])) { return(eval_placeholder(data)) } row_time <- lapply(data, safe_eval, expr = quo) standard_times <- standardise_times(row_time, 'time') enter_length <- if (is.null(params$enter_length)) { 0 } else { if (!inherits(params$enter_length, standard_times$class)) { stop('enter_length must be given in the same class as time', call. = FALSE) } as.numeric(params$enter_length) } exit_length <- if (is.null(params$exit_length)) { 0 } else { if (!inherits(params$exit_length, standard_times$class)) { stop('exit_length must be given in the same class as time', call. = FALSE) } as.numeric(params$exit_length) } range <- if (is.null(params$range)) { range(unlist(standard_times$times)) + c(-enter_length, exit_length) } else { if (!inherits(params$range, standard_times$class)) { stop('range must be given in the same class as time', call. = FALSE) } as.numeric(params$range) } full_length <- diff(range) frames <- lapply(standard_times$times, function(x) { if (length(x) == 0) return(numeric()) frame <- round((params$nframes - 1) * (x - range[1])/full_length) + 1 nc <- nchar(max(frame)) + 1 sprintf(paste0('%0', nc, 'i'), frame) }) frame_time <- recast_times( seq(range[1], range[2], length.out = params$nframes), standard_times$class ) frame_length <- full_length / params$nframes list( values = frames, frame_time = frame_time, enter_length = round(enter_length / frame_length), exit_length = round(exit_length / frame_length) ) } gganimate/R/shadow-wake.R0000644000176200001440000001425013405665100014746 0ustar liggesusers#' Show preceding frames with gradual falloff #' #' This shadow is meant to draw a small wake after data by showing the latest #' frames up to the current. You can choose to gradually diminish the size #' and/or opacity of the shadow. The length of the wake is not given in absolute #' frames as that would make the animation susceptible to changes in the #' framerate. Instead it is given as a proportion of the total length of the #' animation. #' #' @param wake_length A number between 0 and 1 giving the length of the wake, #' in relation to the total number of frames. #' @param size Numeric indicating the size the wake should end on. If `NULL` #' then size is not modified. Can also be a boolean with `TRUE` beeing equal `0` #' and `FALSE` beeing equal to `NULL` #' @param alpha as `size` but for alpha modification of the wake #' @param colour,fill colour or fill the wake should end on. If `NULL` they are #' not modified. #' @param falloff An easing function that control how size and/or alpha should #' change. #' @param wrap Should the shadow wrap around, so that the first frame will get #' shadows from the end of the animation. #' @param exclude_layer Indexes of layers that should be excluded. #' @param exclude_phase Element phases that should not get a shadow. Possible #' values are `'enter'`, `'exit'`, `'static'`, `'transition'`, and `'raw'`. If #' `NULL` all phases will be included. Defaults to `'enter'` and `'exit'` #' #' @family shadows #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Petal.Length, Sepal.Length)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 4, state_length = 1) #' #' # `shadow_wake` can be combined with e.g. `transition_states` to show #' # motion of geoms as they are in transition with respect to the selected state. #' anim1 <- anim + #' shadow_wake(wake_length = 0.05) #' #' # Different qualities can be manipulated by setting a value for it that it #' # should taper off to #' anim2 <- anim + #' shadow_wake(0.1, size = 10, alpha = FALSE, colour = 'grey92') #' #' # Use `detail` in the `animate()` call to increase the number of calculated #' # frames and thus make the wake smoother #' \dontrun{ #' animate(anim2, detail = 5) #' } #' shadow_wake <- function(wake_length, size = TRUE, alpha = TRUE, colour = NULL, fill = NULL, falloff = 'cubic-in', wrap = TRUE, exclude_layer = NULL, exclude_phase = c('enter', 'exit')) { if (is.logical(size)) size <- if (size) 0 else NULL if (is.logical(alpha)) alpha <- if (alpha) 0 else NULL ggproto(NULL, ShadowWake, exclude_layer = exclude_layer, params = list( wake_length = wake_length, colour = colour, fill = fill, size = size, alpha = alpha, falloff = falloff, wrap = wrap, exclude_phase = exclude_phase ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom tweenr tween_at ShadowWake <- ggproto('ShadowWake', Shadow, setup_params = function(self, data, params) { params$wake_length <- round(params$nframes * params$wake_length) params$at <- seq(0, 1, length = params$wake_length + 1)[seq_len(params$wake_length)] params }, get_frames = function(self, params, i) { frames <- rev(i - seq_len(params$wake_length)) if (params$wrap) { frames <- frames %% params$nframes frames[frames == 0] <- params$nframes } else { frames <- frames[frames > 0 & frames <= params$nframes] } frames }, prepare_shadow = function(self, shadow, params) { lapply(shadow, function(d) { if (length(d) == 0) return(NULL) i <- rep(params$at[seq_along(d)], vapply(d, nrow, integer(1))) d <- do.call(rbind, d) if (!is.null(params$colour)) { if (!is.null(d$colour)) d$colour <- tween_at(params$colour, d$colour, i, params$falloff) if (!is.null(d$edge_colour)) d$edge_colour <- tween_at(params$colour, d$edge_colour, i, params$falloff) } if (!is.null(params$fill)) { if (!is.null(d$fill)) d$colour <- tween_at(params$fill, d$fill, i, params$falloff) if (!is.null(d$edge_fill)) d$edge_fill <- tween_at(params$fill, d$edge_fill, i, params$falloff) } if (!is.null(params$alpha)) { if (!is.null(d$edge_alpha)) { no_alpha <- is.na(d$edge_alpha) d$edge_alpha[!no_alpha] <- tween_at(params$alpha, d$edge_alpha[!no_alpha], i, params$falloff) } else if (!is.null(d$alpha)) { no_alpha <- is.na(d$alpha) d$alpha[!no_alpha] <- tween_at(params$alpha, d$alpha[!no_alpha], i, params$falloff) } else { no_alpha <- TRUE } if (!is.null(d$colour)) d$colour[no_alpha] <- mod_alpha(d$colour[no_alpha], i, params$alpha, params$falloff) if (!is.null(d$fill)) d$fill[no_alpha] <- mod_alpha(d$fill[no_alpha], i, params$alpha, params$falloff) if (!is.null(d$edge_colour)) d$edge_colour[no_alpha] <- mod_alpha(d$edge_colour[no_alpha], i, params$alpha, params$falloff) if (!is.null(d$edge_fill)) d$edge_fill[no_alpha] <- mod_alpha(d$edge_fill[no_alpha], i, params$alpha, params$falloff) } if (!is.null(params$size)) { if (!is.null(d$size)) d$size <- tween_at(params$size, d$size, i, params$falloff) if (!is.null(d$edge_size)) d$edge_size <- tween_at(params$size, d$edge_size, i, params$falloff) if (!is.null(d$edge_width)) d$edge_width <- tween_at(params$size, d$edge_width, i, params$falloff) if (!is.null(d$stroke)) d$stroke <- tween_at(params$size, d$stroke, i, params$falloff) } d }) }, prepare_frame_data = function(self, data, shadow, params, frame_ind, shadow_ind) { Map(function(d, s, e) { if (e) return(d[[1]]) ids <- d[[1]]$.id[!d[[1]]$.phase %in% params$exclude_phase] s <- s[s$.id %in% ids, , drop = FALSE] d <- rbind(s, d[[1]]) d[order(match(d$.id, unique(d$.id))), , drop = FALSE] }, d = data, s = shadow, e = seq_along(data) %in% params$excluded_layers) } ) #' @importFrom scales alpha #' @importFrom grDevices col2rgb mod_alpha <- function(col, i, end, ease) { alpha <- col2rgb(col, TRUE)[4,] / 255 alpha(col, tween_at(end, alpha, i, ease)) } gganimate/R/transition-states.R0000644000176200001440000001573313525504332016240 0ustar liggesusers#' Transition between several distinct stages of the data #' #' This transition splits your data into multiple states based on the levels in #' a given column, much like [ggplot2::facet_wrap()] splits up the data in #' multiple panels. It then tweens between the defined states and pauses at each #' state. Layers with data without the specified column will be kept constant #' during the animation (again, mimicking `facet_wrap`). #' #' @param states The unquoted name of the column holding the state levels in the #' data. #' @param transition_length The relative length of the transition. Will be #' recycled to match the number of states in the data #' @param state_length The relative length of the pause at the states. Will be #' recycled to match the number of states in the data #' @param wrap Should the animation *wrap-around*? If `TRUE` the last state will #' be transitioned into the first. #' #' @section Label variables: #' `transition_states` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **transitioning** is a boolean indicating whether the frame is part of the #' transitioning phase #' - **previous_state** The name of the last state the animation was at #' - **closest_state** The name of the state closest to this frame #' - **next_state** The name of the next state the animation will be part of #' #' @section Object permanence: #' `transition_states` uses the group aesthetic of each layer to identify #' which rows in the input data correspond to the same graphic element and will #' therefore define which elements will turn into each other between states. #' The group aesthetic, if not set, will be calculated from the interaction of all #' discrete aesthetics in the layer (excluding `label`), so it is often better #' to set it explicetly when animating, to make sure your data is interpreted in #' the right way. If the group aesthetic is not set, and no discrete aesthetics #' exists then all rows will have the same group. If the group aesthetic is not #' unique in each state, then rows will be matched first by group and then by #' index. Unmatched rows will appear/disappear, potentially using an enter or #' exit function. #' #' @section Computed Variables: #' It is possible to use variables calculated by the statistic to define the #' transition. Simply inclose the variable in `stat()` in the same way as when #' using computed variables in aesthetics. #' #' @family transitions #' #' @importFrom rlang enquo #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Sepal.Width, Petal.Width)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 3, state_length = 1) #' #' # Use a unique group to avoid matching graphic elements #' iris$group <- seq_len(nrow(iris)) #' anim1 <- ggplot(iris, aes(Sepal.Width, Petal.Width, group = group)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 3, state_length = 1) + #' enter_fade() + #' exit_fade() #' #' # Set `wrap = FALSE` to avoid transitioning the last state to the first #' anim2 <- ggplot(iris, aes(Sepal.Width, Petal.Width)) + #' geom_point() + #' labs(title = "{closest_state}") + #' transition_states(Species, transition_length = 3, state_length = 1, #' wrap = FALSE) #' transition_states <- function(states, transition_length = 1, state_length = 1, wrap = TRUE) { states_quo <- enquo(states) require_quo(states_quo, 'states') ggproto(NULL, TransitionStates, params = list( states_quo = states_quo, transition_length = transition_length, state_length = state_length, wrap = wrap ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_state keep_state TransitionStates <- ggproto('TransitionStates', Transition, mapping = '(.*)', var_names = 'states', setup_params = function(self, data, params) { params$states <- get_row_frames(data, params$states_quo, after = FALSE) params$require_stat <- is_placeholder(params$states) params$row_id <- params$states$values params }, setup_params2 = function(self, data, params, row_vars) { if (is_placeholder(params$states)) { params$states <- get_row_frames(data, params$states_quo, after = TRUE) } else { params$states$values <- lapply(row_vars$states, as.integer) } all_levels <- params$states$levels row_state <- params$states$values transition_length <- rep(params$transition_length, length.out = length(all_levels)) if (!params$wrap) transition_length[length(transition_length)] <- 0 state_length <- rep(params$state_length, length.out = length(all_levels)) frames <- distribute_frames(state_length, transition_length, params$nframes + if (params$wrap) 1 else 0) params$state_levels <- all_levels params$row_id <- row_state params$state_length <- frames$static_length params$transition_length <- frames$transition_length params$frame_info <- get_frame_info( static_levels = params$state_levels, static_lengths = params$state_length, transition_lengths = params$transition_length, nframes = params$nframes, static_first = TRUE, static_name = 'state') params$nframes <- nrow(params$frame_info) params }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { row_state <- self$get_row_vars(data) if (is.null(row_state)) return(data) data$group <- paste0(row_state$before, row_state$after) state <- as.integer(row_state$states) states <- split(data, state) all_states <- rep(list(data[0, ]), length(params$state_levels)) all_states[as.integer(names(states))] <- states all_frames <- all_states[[1]] for (i in seq_along(all_states)) { if (params$state_length[i] != 0) { all_frames <- keep_state(all_frames, params$state_length[i]) } if (params$transition_length[i] != 0) { next_state <- if (i == length(all_states)) all_states[[1]] else all_states[[i + 1]] all_frames <- switch( type, point = tween_state(all_frames, next_state, ease, params$transition_length[i], !!id, enter, exit), path = transform_path(all_frames, next_state, ease, params$transition_length[i], !!id, enter, exit, match), polygon = transform_polygon(all_frames, next_state, ease, params$transition_length[i], !!id, enter, exit, match), sf = transform_sf(all_frames, next_state, ease, params$transition_length[i], !!id, enter, exit), stop(type, ' layers not currently supported by transition_states', call. = FALSE) ) } } if (params$wrap) { all_frames <- all_frames[all_frames$.frame <= params$nframes, ] } all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>') all_frames$.frame <- NULL all_frames } ) gganimate/R/ggplot2_reimpl.R0000644000176200001440000000446613415624233015475 0ustar liggesusers# copied from (and modified) ggplot2 plot_clone <- function(plot) { p <- plot p$scales <- plot$scales$clone() p$coordinates <- ggproto(NULL, plot$coordinates) p$transmuters <- plot$transmuters$clone() p } scales_transform_df <- function(scales, df) { if (empty(df) || length(scales$scales) == 0) return(df) transformed <- unlist(lapply(scales$scales, function(s) s$transform_df(df = df)), recursive = FALSE) plyr::quickdf(c(transformed, df[setdiff(names(df), names(transformed))])) } empty <- function(df) { is.null(df) || nrow(df) == 0 || ncol(df) == 0 } scales_add_missing <- function(plot, aesthetics, env) { # Keep only aesthetics that aren't already in plot$scales aesthetics <- setdiff(aesthetics, plot$scales$input()) for (aes in aesthetics) { scale_name <- paste("scale", aes, "continuous", sep = "_") scale_f <- find_global(scale_name, env, mode = "function") plot$scales$add(scale_f()) } } find_global <- function(name, env, mode = "any") { if (exists(name, envir = env, mode = mode)) { return(get(name, envir = env, mode = mode)) } nsenv <- asNamespace("ggplot2") if (exists(name, envir = nsenv, mode = mode)) { return(get(name, envir = nsenv, mode = mode)) } NULL } scales_train_df <- function(scales, df, drop = FALSE) { if (empty(df) || length(scales$scales) == 0) return() lapply(scales$scales, function(scale) scale$train_df(df = df)) } scales_map_df <- function(scales, df) { if (empty(df) || length(scales$scales) == 0) return(df) mapped <- unlist(lapply(scales$scales, function(scale) scale$map_df(df = df)), recursive = FALSE) plyr::quickdf(c(mapped, df[setdiff(names(df), names(mapped))])) } is.waive <- function(x) inherits(x, 'waiver') # Reimplement get_scales in Layout to allow panels with frame info to get the # correct scales #' @importFrom ggplot2 FacetNull CoordCartesian Layout ggproto create_layout <- function(facet = FacetNull, coord = CoordCartesian) { ggproto(NULL, Layout, facet = facet, coord = coord, get_scales = function(self, i) { if (is.character(i)) i <- as.integer(strsplit(i, '<')[[1]][1]) this_panel <- self$layout[self$layout$PANEL == i, ] list( x = self$panel_scales_x[[this_panel$SCALE_X]], y = self$panel_scales_y[[this_panel$SCALE_Y]] ) } ) } gganimate/R/shadow-trail.R0000644000176200001440000000573113405665100015136 0ustar liggesusers#' A trail of evenly spaced old frames #' #' This shadow will trace the movement in your animation by keeping every *n*th #' frame and will thus produce a breadcrumb-like trail. Note that the shadow #' frames will not be equidistant in space but in time (that is, if a point #' moves slowly the *crumbs* will be closer to each other). It is possible to #' modify the look of the shadow by changing the different graphic parameters in #' the data #' #' @param distance The temporal distance between the frames to show, as a #' fraction of the full animation length #' @param max_frames The maximum number of shadow frames to show #' @param ... changes to the shadow data, e.g. `alpha = alpha/2` or #' `colour = 'grey'` #' @param exclude_layer Indexes of layers that should be excluded. #' #' @family shadows #' #' @importFrom ggplot2 ggproto #' @importFrom rlang quos #' @export #' #' @examples #' anim <- ggplot(airquality, aes(Day, Temp, colour = factor(Month))) + #' geom_point() + #' transition_time(Day) #' #' # Change distance between points #' anim1 <- anim + #' shadow_trail(0.02) #' #' # Style shadow differently #' anim2 <- anim + #' shadow_trail(alpha = 0.3, shape = 2) #' #' # Restrict the shadow to 10 frames #' anim3 <- anim + #' shadow_trail(max_frames = 10) #' shadow_trail <- function(distance = 0.05, max_frames = Inf, ..., exclude_layer = NULL) { dots <- quos(...) names(dots) <- sub('color', 'colour', names(dots)) ggproto(NULL, ShadowTrail, exclude_layer = exclude_layer, params = list( distance = distance, max_frames = max_frames, dots = dots ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom rlang eval_tidy ShadowTrail <- ggproto('ShadowTrail', Shadow, train = function(self, data, params) { params$distance <- round(params$nframes * params$distance) params$shadow_frames <- seq(1, params$nframes, by = params$distance) params$raw <- lapply(seq_along(data), function(i) { d <- data[[i]] if (i %in% params$excluded_layers) { return(d[[1]][0, , drop = FALSE]) } d <- d[params$shadow_frames] frames <- rep(params$shadow_frames, vapply(d, nrow, integer(1))) d <- do.call(rbind, d) for (i in names(params$dots)) { if (!is.null(d[[i]])) d[[i]] <- eval_tidy(params$dots[[i]], d) } cbind(d, .frame = frames) }) params }, prepare_frame_data = function(self, data, shadow, params, frame_ind, shadow_ind) { Map(function(d, s, e) { if (e) return(d[[1]]) s <- s[s$.frame < frame_ind, , drop = FALSE] frames <- unique(s$.frame) if (params$max_frames < length(frames)) { first_frame <- sort(frames, decreasing = TRUE)[params$max_frames] s <- s[s$.frame >= first_frame, , drop = FALSE] } s$.frame <- NULL rbind(s, d[[1]]) }, d = data, s = params$raw, e = seq_along(data) %in% params$excluded_layers) } ) gganimate/R/plot-build.R0000644000176200001440000000737513450725404014625 0ustar liggesusers#' @importFrom ggplot2 ggplot_build geom_blank waiver #' @importFrom utils packageVersion #' @export ggplot_build.gganim <- function(plot) { plot <- plot_clone(plot) if (length(plot$layers) == 0) { plot <- plot + geom_blank() } scene <- create_scene(plot$transition, plot$view, plot$shadow, plot$ease, plot$transmuters, plot$nframes) layers <- plot$layers layer_data <- lapply(layers, function(y) y$layer_data(plot$data)) scales <- plot$scales # Extract scale names and merge it with label list scale_labels <- lapply(scales$scales, `[[`, 'name') names(scale_labels) <- vapply(scales$scales, function(sc) sc$aesthetics[1], character(1)) lapply(scales$scales, function(sc) sc$name <- waiver()) scale_labels <- scale_labels[!vapply(scale_labels, is.waive, logical(1))] plot$labels[names(scale_labels)] <- scale_labels # Apply function to layer and matching data by_layer <- function(f) { out <- vector("list", length(data)) for (i in seq_along(data)) { out[[i]] <- f(l = layers[[i]], d = data[[i]]) } out } # Allow all layers to make any final adjustments based # on raw input data and plot info data <- layer_data if (packageVersion("ggplot2") > "3.1.1") { # ggplot2 versions 3.1.0 or earlier do not support `setup_layer()` data <- by_layer(function(l, d) l$setup_layer(d, plot)) } # Initialise panels, add extra data for margins & missing faceting # variables, and add on a PANEL variable to data layout <- create_layout(plot$facet, plot$coordinates) data <- layout$setup(data, plot$data, plot$plot_env) scene$setup(data) # Compute aesthetics to produce data with generalised variable names data <- by_layer(function(l, d) l$compute_aesthetics(d, plot)) scene$identify_layers(data, layers) # Transform all scales data <- lapply(data, scales_transform_df, scales = scales) # Map and train positions so that statistics have access to ranges # and all positions are numeric scale_x <- function() scales$get_scales("x") scale_y <- function() scales$get_scales("y") layout$train_position(data, scale_x(), scale_y()) data <- layout$map_position(data) data <- scene$before_stat(data) # Apply and map statistics data <- by_layer(function(l, d) l$compute_statistic(d, layout)) data <- by_layer(function(l, d) l$map_statistic(d, plot)) data <- scene$after_stat(data) # Make sure missing (but required) aesthetics are added scales_add_missing(plot, c("x", "y"), plot$plot_env) # Reparameterise geoms from (e.g.) y and width to ymin and ymax data <- by_layer(function(l, d) l$compute_geom_1(d)) data <- scene$before_position(data) # Apply position adjustments data <- by_layer(function(l, d) l$compute_position(d, layout)) data <- scene$after_position(data) # Reset position scales, then re-train and map. This ensures that facets # have control over the range of a plot: is it generated from what is # displayed, or does it include the range of underlying data layout$reset_scales() layout$train_position(data, scale_x(), scale_y()) layout$setup_panel_params() data <- layout$map_position(data) # Train and map non-position scales npscales <- scales$non_position_scales() if (npscales$n() > 0) { lapply(data, scales_train_df, scales = npscales) data <- lapply(data, scales_map_df, scales = npscales) } # Fill in defaults etc. data <- by_layer(function(l, d) l$compute_geom_2(d)) data <- scene$after_defaults(data) # Let layer stat have a final say before rendering data <- by_layer(function(l, d) l$finish_statistics(d)) # Let Layout modify data before rendering data <- layout$finish_data(data) data <- scene$finish_data(data) structure( list(data = data, layout = layout, plot = plot, scene = scene), class = "gganim_built" ) } gganimate/R/transition-.R0000644000176200001440000002156013415651334015012 0ustar liggesusers#' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_replace stri_match stri_detect Transition <- ggproto('Transition', NULL, params = NULL, mapping = '', var_names = '', setup_params = function(self, data, params) { params }, setup_params2 = function(self, data, params, row_vars) { params }, map_data = function(self, data, params, replace = FALSE) { if (is.null(params$row_id)) return(data) Map(function(d, id) { if (length(id) == 0 && !replace) return(d) id <- if (length(id) > 0) paste0('<', id, '>') else '' d$group <- as.character(d$group) d$group <- if (replace && any(stri_detect(d$group, regex = '<.*>'))) { stri_replace(d$group, id, regex = '<.*>') } else { paste0(d$group, id) } d }, d = data, id = params$row_id) }, expand_data = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { Map(function(data, type, id, match, ease, enter, exit, layer_index) { self$expand_layer(data, type, id, match, ease, enter, exit, params, layer_index) }, data = data, type = type, id = id, match = match, ease = ease, enter = enter, exit = exit, layer_index = layer_index) }, expand_layer = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { expanded <- lapply(split(data, data$PANEL), function(data) { self$expand_panel(data, type, id, match, ease, enter, exit, params, layer_index) }) do.call(rbind, expanded) }, expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { stop('The transition has not implemented any data expansion', call. = FALSE) }, unmap_frames = function(self, data, params) { lapply(data, function(d) { split_panel <- stri_match(d$group, regex = '^(.*)(<.*>)(.*)$') if (is.na(split_panel[1])) return(d) groups <- paste0(split_panel[, 2], split_panel[, 4]) if (all(stri_detect(groups, regex = '^-?[0-9]+$'))) { d$group <- as.integer(groups) } else { d$group <- groups } d$PANEL <- paste0(d$PANEL, split_panel[, 3]) d }) }, remap_frames = function(self, data, params) { lapply(data, function(d) { split_panel <- stri_match(d$PANEL, regex = '^(.*)(<.*>)(.*)$') if (is.na(split_panel[1])) return(d) d$PANEL <- as.integer(split_panel[, 2]) d$group <- paste0(d$group, split_panel[, 3]) d }) }, finish_data = function(self, data, params) { lapply(data, function(d) { split_panel <- stri_match(d$group, regex = '^(.+)<(.*)>(.*)$') if (is.na(split_panel[1])) return(list(d)) d$group <- match(d$group, unique(d$group)) empty_d <- d[0, , drop = FALSE] d <- split(d, as.integer(split_panel[, 3])) frames <- rep(list(empty_d), params$nframes) frames[as.integer(names(d))] <- d frames }) }, adjust_nframes = function(self, data, params) { statics <- self$static_layers(params) dynamics <- setdiff(seq_along(data), statics) if (length(dynamics) == 0) { params$nframes } else { length(data[[dynamics[1]]]) } }, get_frame_data = function(self, data, params, i) { statics <- seq_along(data) %in% self$static_layers(params) Map(function(d, s) { if (s) d else d[i] }, d = data, s = statics) }, get_frame_vars = function(self, params) { params$frame_info }, static_layers = function(self, params) { which(lengths(params$row_id) == 0) }, require_late_tween = function(self, params) { isTRUE(params$require_stat) }, get_row_vars = function(self, data) { vars <- stri_match(data$group, regex = paste0('(.*)<', self$mapping, '>(.*)'))[, -1, drop = FALSE] if (is.na(vars[1])) return(NULL) var_names <- c('before', self$var_names, 'after') structure(lapply(seq_along(var_names), function(i) vars[,i]), names = var_names) }, get_all_row_vars = function(self, data) { all_vars <- lapply(data, self$get_row_vars) var_names <- unique(unlist(lapply(all_vars, names))) structure(lapply(var_names, function(var) { lapply(all_vars, `[[`, var) }), names = var_names) } ) #' @importFrom ggplot2 ggplot_add #' @export ggplot_add.Transition <- function(object, plot, object_name) { plot <- as.gganim(plot) plot$transition <- object plot } # HELPERS ----------------------------------------------------------------- combine_levels <- function(data, var) { values <- lapply(data, safe_eval, expr = var) values[lengths(values) != vapply(data, nrow, integer(1))] <- list(numeric()) levels <- lapply(values, function(v) levels(as.factor(v))) levels <- Reduce(union, levels) values <- lapply(values, as.character) values <- split(match(unlist(values), levels), rep(factor(seq_along(values)), lengths(values))) list(values = values, levels = levels) } distribute_frames <- function(statics, transitions, frames) { total <- sum(c(statics, transitions)) static_frames <- ceiling(statics * frames / total) transition_frames <- ceiling(transitions * frames / total) all <- c(static_frames, transition_frames) n <- rep(seq_along(all), all) ind <- unlist(lapply(all, seq_len)) n <- table(n[order(ind)[seq_len(frames)]]) ind <- as.integer(names(n)) static_numbers <- ind <= length(statics) static_frames[ind[static_numbers]] <- n[static_numbers] transition_frames[ind[!static_numbers] - length(statics)] <- n[!static_numbers] zero_trans <- which(transition_frames == 0 & static_frames[which(transition_frames == 0) + 1] != 0) transition_frames[zero_trans] <- 1 static_frames[zero_trans + 1] <- static_frames[zero_trans + 1] - 1 list(static_length = static_frames, transition_length = transition_frames, mod = frames / total) } #' @importFrom tweenr tween_constant get_frame_info <- function(static_levels, static_lengths, transition_lengths, nframes, static_first, static_name, ...) { if (static_first) { frames <- as.vector(rbind(static_lengths, transition_lengths)) phase <- rep(rep(c('static', 'transition'), length(static_lengths)), frames)[seq_len(nframes)] } else { frames <- as.vector(rbind(transition_lengths, static_lengths)) phase <- rep(rep(c('transition', 'static'), length(static_lengths)), frames)[seq_len(nframes)] } statics <- rep(static_levels, each = 2) if (static_first) { previous_static <- rep(statics, frames)[seq_len(nframes)] statics2 <- c(statics[-1], statics[1]) next_static <- rep(statics2, frames)[seq_len(nframes)] } else { next_static <- rep(statics, frames)[seq_len(nframes)] statics2 <- c(statics[length(statics)], statics[-length(statics)]) previous_static <- rep(statics2, frames)[seq_len(nframes)] } closest_static <- tween_constant(as.list(statics[c(seq_along(statics), 1)]), frames + 1)[[1]][seq_len(nframes)] info <- data.frame( transitioning = phase == 'transition', previous_ = previous_static, closest_ = closest_static, next_ = next_static, stringsAsFactors = FALSE ) names(info)[2:4] <- paste0(names(info)[2:4], static_name) info } standardise_times <- function(times, name, to_class = NULL) { possible_classes <- c('integer', 'numeric', 'POSIXct', 'Date', 'difftime', 'hms') classes <- vapply(times[lengths(times) != 0], function(x) { cl <- inherits(x, possible_classes, which = TRUE) which(cl != 0 & cl == min(cl[cl != 0]))[1] }, integer(1)) if (anyNA(classes)) stop(name, ' data must either be ', paste0(possible_classes[-length(possible_classes)], collapse = ', '), ', or', possible_classes[length(possible_classes)], call. = FALSE) if (length(unique(classes)) > 1) stop(name, ' data must be the same class in all layers', call. = FALSE) cl <- possible_classes[unique(classes)] if (length(cl) == 1 && (cl == 'difftime' || cl == 'hms')) { if (is.null(to_class)) { times <- lapply(times, `units<-`, 'secs') } else if (to_class == 'POSIXct') { cl <- to_class times <- lapply(times, `units<-`, 'secs') } else if (to_class == 'Date') { if (cl == 'hms') { times <- lapply(times, `class<-`, 'difftime') } times <- lapply(times, `units<-`, 'days') cl <- to_class } } if (!is.null(to_class) && length(cl) != 0) if (cl != to_class) stop(name, ' data must be ', to_class, call. = FALSE) list( times = lapply(times, as.numeric), class = cl ) } recast_times <- function(time, class) { switch( class, integer = as.integer(round(time)), numeric = time, POSIXct = structure(time, class = c('POSIXct', 'POSIXt')), Date = structure(time, class = 'Date'), difftime = structure(time, units = 'secs', class = 'difftime'), hms = structure(time, units = 'secs', class = c('hms','difftime')) ) } eval_placeholder <- function(data) { structure(list(values = lapply(data, function(d) rep('*', nrow(d)))), class = 'placeholder') } is_placeholder <- function(x) inherits(x, 'placeholder') gganimate/R/view-step.R0000644000176200001440000001653713406442137014475 0ustar liggesusers#' Follow the data in steps #' #' This view is a bit like [view_follow()] but will not match the data in each #' frame. Instead it will switch between being static and zoom to the range of #' the data. It is a great pairing with [transition_states()] as it can move the #' view while the data is static and then be static while the data moves. The #' standard version will look at the data present in the calculated frames and #' set the ranges based on that, while the `_manual` version will allow you to #' define your own ranges. #' #' @param pause_length The relative length the view will be kept static. Will #' be recycled to match the number of steps #' @param step_length The relative length the view will use to transition to the #' new position. Will be recycled to match the number of steps #' @param nsteps The number of steps. If `NULL` it will be set to the max length #' of `pause_length` or `step_length` #' @param look_ahead A relative length to look ahead in the animation to get the #' new zoom area. Allow the view to zoom to where the data will be #' @param delay A relative length to switch the view back and forth relative to #' the actual frames. E.g. if delay is calculated to 5 frames, frame 6 will get #' the view intended for frame 1. #' @param include Should the steps include both the start and end frame range #' @param ease The easing function used for the step #' @param wrap As in [transition_states()]. Should the view wrap around and zoom #' back to the first state. #' @param pause_first Should the view start with a pause. The default is to #' start with a step so that it is aligned to the static period in #' [transition_states()] #' @inheritParams view_follow #' #' @family views #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' view_step(pause_length = 2, step_length = 1, nsteps = 3) #' #' # Default is to include the data from the two states you're stepping between #' # but this can be turned off #' anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' view_step(pause_length = 2, step_length = 1, nsteps = 3, include = FALSE) #' #' # Default is to work off-beat of transition_states so that view changes while #' # data is static. Setting pause_first=TRUE changes this #' anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' view_step(pause_length = 1, step_length = 2, nsteps = 3, pause_first = TRUE) #' #' # If the transition doesn't wrap, then the view shouldn't either #' anim <- ggplot(iris, aes(Petal.Length, Petal.Width)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1, wrap = FALSE) + #' view_step(pause_length = 2, step_length = 1, nsteps = 3, wrap = FALSE) #' view_step <- function(pause_length = 1, step_length = 1, nsteps = NULL, look_ahead = pause_length, delay = 0, include = TRUE, ease = 'cubic-in-out', wrap = TRUE, pause_first = FALSE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1) { ggproto(NULL, ViewStep, fixed_lim = list(x = fixed_x, y = fixed_y), exclude_layer = exclude_layer, aspect_ratio = aspect_ratio, params = list( pause_length = pause_length, step_length = step_length, nsteps = nsteps, look_ahead = look_ahead, delay = delay, include = include, ease = ease, wrap = wrap, pause_first = pause_first ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom tweenr keep_state tween_state ViewStep <- ggproto('ViewStep', View, setup_params = function(self, data, params) { nsteps <- params$nstep %||% max(length(params$step_length), length(params$pause_length)) step_length <- rep(params$step_length, length.out = nsteps) pause_length <- rep(params$pause_length, length.out = nsteps) look_ahead <- rep(params$look_ahead, length.out = nsteps) if (!params$pause_first) { pause_length <- c(0, pause_length) step_length <- c(step_length, 0) look_ahead <- c(look_ahead, look_ahead[1]) if (!params$wrap) pause_length[length(pause_length)] <- 0 } else if (!params$wrap) { step_length[length(step_length)] <- 0 } params$step_length <- step_length params$pause_length <- pause_length params$look_ahead <- look_ahead params }, train = function(self, data, params) { nframes <- params$nframes if (params$wrap) nframes <- nframes + 1 frames <- distribute_frames(params$pause_length, params$step_length, nframes) if (!params$pause_first) { frames$transition_length[length(frames$transition_length)] <- frames$transition_length[1] } look_ahead <- round(params$look_ahead * frames$mod) breaks <- cumsum(frames$static_length + frames$transition_length) + look_ahead if (params$wrap) { breaks <- breaks %% nframes breaks[breaks == 0] <- 1L breaks <- if (params$pause_first) { c(breaks[length(breaks)], breaks) } else { c(breaks[length(breaks) - 1], breaks) } } else { breaks <- c(1, pmin(breaks, params$nframes)) } data <- data[!seq_along(data) %in% params$excluded_layers] windows <- lapply(breaks, function(i) { data <- lapply(data, `[[`, i) ranges <- self$get_ranges(data, params) x_range <- range(unlist(lapply(ranges, `[[`, 'x'))) y_range <- range(unlist(lapply(ranges, `[[`, 'y'))) data.frame(xmin = x_range[1], xmax = x_range[2], ymin = y_range[1], ymax = y_range[2]) }) if (params$include) { windows <- lapply(seq_along(windows), function(i) { if (i == 1) { if (!params$wrap) return(windows[[i]]) else i <- c(length(windows), i) } else { i <- c(i - 1, i) } range <- do.call(rbind, windows[i]) data.frame(xmin = min(range$xmin), xmax = max(range$xmax), ymin = min(range$ymin), ymax = max(range$ymax)) }) } frame_ranges <- if (params$wrap) { if (params$pause_first) { windows[[length(windows)]] } else { windows[[length(windows) - 1]] } } else { windows[[1]] } for (i in seq_len(length(windows) - 1)) { if (frames$static_length[i] != 0) { frame_ranges <- keep_state(frame_ranges, frames$static_length[i]) } if (frames$transition_length[i] != 0) { frame_ranges <- self$window_transition(frame_ranges, windows[[i + 1]], frames$transition_length[i], params) } } frame_ranges <- frame_ranges[frame_ranges$.frame <= params$nframes, ] frame_ranges$.frame <- (frame_ranges$.frame + round(params$delay * frames$mod)) %% params$nframes frame_ranges <- frame_ranges[order(frame_ranges$.frame), ] params$frame_ranges <- frame_ranges params }, set_view = function(self, plot, params, i) { range <- params$frame_ranges[i, ] self$reset_limits(plot, c(range$xmin, range$xmax), c(range$ymin, range$ymax)) }, window_transition = function(windows, next_window, n, params) { tween_state(windows, next_window, params$ease, n) } ) gganimate/R/transition-layers.R0000644000176200001440000002015213415135624016225 0ustar liggesusers#' @include transition-manual.R NULL #' Build up a plot, layer by layer #' #' This transition gradually adds layers to the plot in the order they have been #' defined. By default prior layers are kept for the remainder of the animation, #' but they can also be set to be removed as the next layer enters. #' #' @param layer_length The proportional time to pause at each layer before a new #' one enters #' @param transition_length The proportional time to use for the entrance of a #' new layer #' @param keep_layers Either an integer indicating for how many following layers #' the layers should stay on screen or a logical. In the case of the later, #' `TRUE` will mean keep the layer for the remainder of the animation #' (equivalent to setting it to `Inf`) and `FALSE` will mean to transition the #' layer out as the next layer enters. #' @param from_blank Should the first layer transition in or be present on the #' onset of the animation #' @param layer_order An alternative order the layers should appear in (default #' to using the stacking order). All other arguments that references the layers #' index in some way refers to this order. #' @param layer_names A character vector of names for each layers, to be used #' when interpreting label literals #' #' @section Label variables: #' `transition_layers` makes the following variables available for string #' literal interpretation, in addition to the general ones provided by #' [animate()]: #' #' - **transitioning** is a boolean indicating whether the frame is part of the #' transitioning phase #' - **previous_layer** The name of the last layer the animation was showing #' - **closest_layer** The name of the layer the animation is closest to showing #' - **next_layer** The name of the next layer the animation will show #' - **nlayers** The total number of layers #' #' @section Object permanence: #' `transition_layer` does not link rows across data to the same graphic #' element, so elements will be defined uniquely by each row and the enter and #' exit of the layer it belongs to. #' #' @family transitions #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' # Default is to use layer order and keep layers for duration of animation #' anim <- ggplot(mtcars, aes(mpg, disp)) + #' geom_point() + #' geom_smooth(colour = 'grey', se = FALSE) + #' geom_smooth(aes(colour = factor(gear))) + #' transition_layers(layer_length = 1, transition_length = 2) + #' enter_fade() + enter_grow() #' #' # Start with the first layer already present #' anim1 <- ggplot(mtcars, aes(mpg, disp)) + #' geom_point() + #' geom_smooth(colour = 'grey', se = FALSE) + #' geom_smooth(aes(colour = factor(gear))) + #' transition_layers(layer_length = 1, transition_length = 2, #' from_blank = FALSE) + #' enter_fade() + enter_grow() #' #' # Change the order of the layers #' anim2 <- ggplot(mtcars, aes(mpg, disp)) + #' geom_point() + #' geom_smooth(colour = 'grey', se = FALSE) + #' geom_smooth(aes(colour = factor(gear))) + #' transition_layers(layer_length = 1, transition_length = 2, #' from_blank = FALSE, layer_order = c(3, 1, 2)) + #' enter_fade() + enter_grow() #' #' # Keep layer 1 for the whole animation, but remove the 2nd layer as the 3rd #' # enters #' anim3 <- ggplot(mtcars, aes(mpg, disp)) + #' geom_point() + #' geom_smooth(colour = 'grey', se = FALSE) + #' geom_smooth(aes(colour = factor(gear))) + #' transition_layers(layer_length = 1, transition_length = 2, #' from_blank = FALSE, keep_layers = c(Inf, 0, 0)) + #' enter_fade() + enter_grow() + #' exit_fade() + exit_shrink() #' transition_layers <- function(layer_length = 1, transition_length = 1, keep_layers = TRUE, from_blank = TRUE, layer_order = NULL, layer_names = NULL) { if (is.logical(keep_layers)) keep_layers <- if (keep_layers) Inf else 0L ggproto(NULL, TransitionLayers, params = list( layer_length = layer_length, transition_length = transition_length, keep_layers = keep_layers, from_blank = from_blank, layer_order = layer_order, layer_names = layer_names ) ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom stringi stri_match #' @importFrom tweenr tween_state keep_state TransitionLayers <- ggproto('TransitionLayers', Transition, setup_params = function(self, data, params) { params$nlayers <- length(data) params$layer_order <- if (is.null(params$layer_order)) { seq_len(params$nlayers) } else { match(seq_along(data), params$layer_order) } layer_length <- rep_len(params$layer_length, length(data)) transition_length <- rep_len(params$transition_length, length(data) + params$from_blank) params$keep_layers <- rep_len(params$keep_layers, length(data)) if (params$from_blank) layer_length <- c(0, layer_length) if (is.infinite(params$keep_layers[length(data)])) { transition_length[length(transition_length)] <- 0 } frames <- distribute_frames(layer_length, transition_length, params$nframes) frames <- data.frame(layer = frames$static_length, exit = frames$transition_length) frames$enter <- c(0, frames$exit[-nrow(frames)]) if (params$from_blank) frames <- frames[-1, ] params$offset <- c(0, cumsum(frames$enter + frames$layer)[-nrow(frames)]) params$enter_length <- frames$enter params$layer_length <- frames$layer params$exit_length <- frames$exit if (is.null(params$layer_names)) { params$layer_names <- as.character(seq_along(data)) } else { if (length(params$layer_names) != length(data)) { stop('When providing layer names the number of names must match the number of layers', call. = FALSE) } } params$frame_info <- get_frame_info( static_levels = params$layer_names, static_lengths = params$layer_length, transition_lengths = params$enter_length, nframes = params$nframes, static_first = FALSE, static_name = 'layer') params$frame_info$nlayers <- params$nlayers params$nframes <- nrow(params$frame_info) params }, expand_layer = function(self, data, type, id, match, ease, enter, exit, params, layer_index) { layer_index <- params$layer_order[layer_index] offset <- params$offset[layer_index] enter_length <- params$enter_length[layer_index] if (enter_length < 1) enter_length <- 1 exit_length <- params$exit_length[layer_index] layer_length <- params$layer_length[layer_index] max_length <- params$nframes - offset - enter_length layer_length <- if (is.infinite(params$keep_layers[layer_index])) { max_length } else if (params$keep_layers[layer_index] != 0 && layer_index != params$nlayers) { last_layer <- min(layer_index + params$keep_layers[layer_index], params$nlayers) params$offset[last_layer] + params$layer_length[last_layer] - offset } else { layer_length } layer <- switch( type, point = tween_state(data[0,], data, ease, enter_length, NULL, enter, exit), path = transform_path(data[0,], data, ease, enter_length, NULL, enter, exit), polygon = transform_polygon(data[0,], data, ease, enter_length, NULL, enter, exit), sf = transform_sf(data[0,], data, ease, enter_length, NULL, enter, exit), stop(type, ' layers not currently supported by transition_layers', call. = FALSE) ) layer <- keep_state(layer, layer_length) if (is.finite(params$keep_layers[layer_index])) { layer <- switch( type, point = tween_state(layer, data[0,], ease, exit_length, NULL, enter, exit), path = transform_path(layer, data[0,], ease, exit_length, NULL, enter, exit), polygon = transform_polygon(layer, data[0,], ease, exit_length, NULL, enter, exit), sf = transform_sf(layer, data[0,], ease, exit_length, NULL, enter, exit), stop(type, ' layers not currently supported by transition_layers', call. = FALSE) ) } layer <- layer[layer$.frame <= params$nframes, , drop = FALSE] layer$group <- paste0(layer$group, '<', layer$.frame + offset, '>') layer$.frame <- NULL layer }, static_layers = function(self, params) { numeric(0) } ) gganimate/R/animate.R0000644000176200001440000003333113741642604014162 0ustar liggesusers#' Render a gganim object #' #' This function takes a gganim object and renders it into an animation. The #' nature of the animation is dependent on the renderer, but defaults to using #' `gifski` to render it to a gif. The length and framerate is decided on render #' time and can be any two combination of `nframes`, `fps`, and `duration`. #' Rendering is happening in discrete time units. This means that any event in #' the animation is rounded of to the nearest frame (e.g. entering will always #' take a whole number of frames). This means that rounding artifacts are #' possible when only rendering few frames. To avoid this you can increase the #' `detail` argument. `detail` will get multiplied to `nframes` and the #' resulting number of frames will get calculated, but only `nframes` evenly #' spaced frames are rendered. #' #' @param plot,x A `gganim` object #' @param nframes The number of frames to render (default `100`) #' @param fps The framerate of the animation in frames/sec (default `10`) #' @param duration The length of the animation in seconds (unset by default) #' @param detail The number of additional frames to calculate, per frame (default `1`) #' @param renderer The function used to render the generated frames into an #' animation. Gets a vector of paths to images along with the framerate. (default [gifski_renderer()]) #' @param device The device to use for rendering the single frames. Possible #' values are `'png'`, `'ragg_png'` (requires the ragg package), `'jpeg'`, #' `'tiff'`, `'bmp'`, `'svg'`, and `'svglite'` (requires the svglite package). #' (default `'png'`) #' @param ref_frame The frame to use for fixing dimensions of the plot, e.g. the #' space available for axis text. Defaults to the first frame. Negative values #' counts backwards (-1 is the last frame) (default `1`) #' @param start_pause,end_pause Number of times to repeat the first and last #' frame in the animation (default is `0` for both) #' @param rewind Should the animation roll back in the end (default `FALSE`) #' @param ... Arguments passed on to the device. #' For available device arguments, see [grDevices::png()] or [grDevices::svg()] #' #' @return The return value of the [renderer][renderers] function #' #' @details `print.gganim`() is an alias for `animate()` in the same way as #' `print.ggplot()` is an alias for `plot.ggplot()`. This ensures that gganimate #' behaves ggplot2-like and produces the animation when the object is printed. #' The `plot()` method is different and produces a single frame for inspection #' (by default frame 50 out of 100). #' #' Animations can be saved to disk using [anim_save()] in much the same way #' [ggsave()][ggplot2::ggsave] works for static plots. #' #' @section Defaults: #' It is possible to overwrite the defaults used by gganimate for the animation #' by setting them with [options()] (prefixed with `gganimate.`. As an example, #' if you would like to change the default nframes to 50 you would call #' `options(gganimate.nframes = 50)`. In order to set default device arguments #' (those you would normally pass through with `...`) you should use the #' `gganimate.dev_args` options and provide a list of arguments e.g. #' `options(gganimate.dev_args = list(width = 800, height = 600))` Defaults set #' this way can still be overridden by giving arguments directly to `animate()`. #' #' **knitr Support:** \cr #' It is possible to specify the arguments to `animate()` in the chunk options #' when using `gganimate` with `knitr`. Arguments specified in this way will #' have precedence over defaults, but not over arguments specified directly in #' `animate()`. The arguments should be provided as a list to the `gganimate` #' chunk option, e.g. `{r, gganimate = list(nframes = 50, fps = 20)}`. A few #' build-in knitr options have relevance for animation and will be used unless #' given specifically in the `gganimate` list option. The native knitr options #' supported are: #' #' - `dev`: will set `device` #' - `dev.args`: will set additional arguments to the device (`...`) #' - `fig.width`, `fig.height`, `fig.asp`, `fig.dim`: will set `width` and #' `height` of the device. #' #' @section Label variables: #' All plots have a certain set of variables available for string literal #' interpolation within plot labels. These are: #' #' - **frame** gives you the frame index for the current frame #' - **nframes** gives you the total number of frames in the animation #' - **progress** gives you the progress of the animation at the current frame #' (equal to `frame/nframes`) #' - **data** gives you the layer data for the current frame (as a list of data #' frames) #' #' Further, the transition and view in use can also make variables available. #' Consult the documentation for these for more detail. #' #' @importFrom grid grid.newpage grid.draw convertWidth convertHeight #' @importFrom grDevices png jpeg tiff bmp svg dev.off #' @importFrom progress progress_bar #' @importFrom ggplot2 ggplot_gtable ggplot_build #' @export #' #' @examples #' anim <- ggplot(mtcars, aes(mpg, disp)) + #' transition_states(gear, transition_length = 2, state_length = 1) + #' enter_fade() + #' exit_fade() #' #' \dontrun{ #' # Explicitly animate using default (same as just printing the animation) #' animate(anim) #' #' # Change duration and framerate #' animate(anim, fps = 20, duration = 15) #' #' # Make the animation pause at the end and then rewind #' animate(anim, nframes = 100, end_pause = 10, rewind = TRUE) #' #' # Use a different renderer #' animate(anim, renderer = file_renderer('~/animation/'))[1:6] #' #' # Specify device dimensions and/or resolution #' animate(anim, height = 2, width = 3, units = "in", res = 150) #' } #' animate <- function(plot, ...) { UseMethod('animate') } #' @export animate.default <- function(plot, ...) { stop('animation of ', class(plot)[1], ' objects not supported') } #' @rdname animate #' @export animate.gganim <- function(plot, nframes, fps, duration, detail, renderer, device, ref_frame, start_pause, end_pause, rewind, ...) { args <- prepare_args( nframes = nframes, fps = fps, duration = duration, detail = detail, renderer = renderer, device = device, ref_frame = ref_frame, start_pause = start_pause, end_pause = end_pause, rewind = rewind, ... ) if (is_knitting() && identical(def_ren$renderer, args$renderer) && !def_ren$has_proper) { warning('No renderer available. Please install the gifski, av, or magick package to create animated output', call. = FALSE) return(invisible(NULL)) } orig_nframes <- args$nframes args$nframes <- args$nframes - args$start_pause - args$end_pause if (args$rewind) { args$nframes <- ceiling((args$nframes - args$start_pause) / 2) args$end_pause <- ceiling(args$end_pause / 2) } nframes_total <- (args$nframes - 1) * args$detail + 1 plot <- prerender(plot, nframes_total) nframes_final <- get_nframes(plot) frame_ind <- unique(round(seq(1, nframes_final, length.out = args$nframes))) if (args$device == 'current') { frame_ind <- c(rep(frame_ind[1], args$start_pause), frame_ind, rep(frame_ind[length(frame_ind)], args$end_pause)) if (args$rewind) frame_ind <- c(frame_ind, rev(frame_ind)) if (args$ref_frame < 0) { args$ref_frame <- args$ref_frame - args$end_pause } else { args$ref_frame <- args$ref_frame + args$start_pause } } if (args$nframes != length(frame_ind)) { message('nframes and fps adjusted to match transition') args$fps <- args$fps * length(frame_ind) / args$nframes } if (args$ref_frame < 0) args$ref_frame <- nframes_final + 1 + args$ref_frame frames_vars <- do.call( draw_frames, c(list(plot = plot, frames = frame_ind, device = args$device, ref_frame = args$ref_frame), args$dev_args) ) if (args$device == 'current') return(invisible(frames_vars)) if (args$start_pause != 0) frames_vars <- rbind(frames_vars[rep(1, args$start_pause), , drop = FALSE], frames_vars) if (args$end_pause != 0) frames_vars <- rbind(frames_vars, frames_vars[rep(nrow(frames_vars), args$end_pause), , drop = FALSE]) if (args$rewind) frames_vars <- rbind(frames_vars, frames_vars[rev(seq_len(orig_nframes - nrow(frames_vars))), , drop = FALSE]) animation <- args$renderer(frames_vars$frame_source, args$fps) attr(animation, 'frame_vars') <- frames_vars set_last_animation(animation) animation } #' Catch attempt to use the old API #' #' @export #' @keywords internal gganimate <- function(...) { stop( 'It appears that you are trying to use the old API, which has been deprecated.\n', 'Please update your code to the new API or install the old version of gganimate\n', 'from https://github.com/thomasp85/gganimate/releases/tag/v0.1.1', call. = FALSE ) } #' @rdname gganimate #' @export gg_animate <- gganimate #' @importFrom utils modifyList prepare_args <- function(nframes, fps, duration, detail, renderer, device, ref_frame, start_pause, end_pause, rewind, ...) { args <- list() chunk_args <- if (is_knitting()) get_knitr_options(knitr::opts_chunk$get(), unlist = FALSE) else list(dev_args = list()) args$nframes <- nframes %?% chunk_args$nframes %||% getOption('gganimate.nframes', 100) args$fps <- fps %?% chunk_args$fps %||% getOption('gganimate.fps', 10) duration <- duration %?% chunk_args$duration %||% getOption('gganimate.duration', NULL) if (!is.null(duration)) { if ( !missing(fps) || is.null(args$nframes) || (!is.null(getOption('gganimate.fps')) && is.null(getOption('gganimate.nframes'))) ) args$nframes <- duration * args$fps else args$fps <- args$nframes / duration } if (is.null(args$nframes) || is.null(args$fps)) { stop("At least 2 of 'nframes', 'fps', and 'duration' must be given", call. = FALSE) } args$detail <- detail %?% chunk_args$detail %||% getOption('gganimate.detail', 1) args$renderer <- renderer %?% chunk_args$renderer %||% getOption('gganimate.renderer', def_ren$renderer) args$device <- tolower(device %?% chunk_args$device %||% getOption('gganimate.device', 'png')) if (args$device == 'svglite' && !requireNamespace('svglite', quietly = TRUE)) { stop('The svglite package is required to use this device', call. = FALSE) } if (args$device == 'ragg_png' && !requireNamespace('ragg', quietly = TRUE)) { stop('The ragg package is required to use this device', call. = FALSE) } args$ref_frame <- ref_frame %?% chunk_args$ref_frame %||% getOption('gganimate.ref_frame', 1) args$start_pause <- start_pause %?% chunk_args$start_pause %||% getOption('gganimate.start_pause', 0) args$end_pause <- end_pause %?% chunk_args$end_pause %||% getOption('gganimate.end_pause', 0) args$rewind <- rewind %?% chunk_args$rewind %||% getOption('gganimate.rewind', FALSE) dev_args <- list(...) args$dev_args <- if (length(dev_args) > 0) { modifyList(getOption('gganimate.dev_args', list()), dev_args) } else { modifyList(getOption('gganimate.dev_args', list()), chunk_args$dev_args) } args } # Build plot for a specific number of frames prerender <- function(plot, nframes) { plot <- set_nframes(plot, nframes) ggplot_build(plot) } # Draw each frame as an image based on a specified device # Returns a data.frame of frame metadata with image location in frame_source # column draw_frames <- function(plot, frames, device, ref_frame, ...) { stream <- device == 'current' dims <- tryCatch( plot_dims(plot, ref_frame), error = function(e) { warning('Cannot get dimensions of plot table. Plot region might not be fixed', call. = FALSE) list(widths = NULL, heights = NULL) } ) dir <- tempfile(pattern = '') dir.create(dir, showWarnings = FALSE) files <- file.path(dir, sprintf('gganim_plot%04d', seq_along(frames))) files <- switch( tolower(device), ragg_png = , png = paste0(files, '.png'), jpg = , jpeg = paste0(files, '.jpg'), tif = , tiff = paste0(files, '.tif'), bmp = paste0(files, '.bmp'), svglite = , svg = paste0(files, '.svg'), current = files, stop('Unsupported device', call. = FALSE) ) device <- switch( device, ragg_png = ragg::agg_png, png = png, jpg = , jpeg = jpeg, tif = , tiff = tiff, bmp = bmp, svg = svg, svglite = svglite::svglite ) pb <- progress_bar$new( 'Rendering [:bar] at :fps fps ~ eta: :eta', total = length(frames) ) start <- Sys.time() pb$tick(0) for (i in seq_along(frames)) { if (!stream) device(files[i], ...) tryCatch( plot$scene$plot_frame(plot, frames[i], widths = dims$widths, heights = dims$heights), error = function(e) { warning(conditionMessage(e), call. = FALSE) } ) rate <- i/as.double(Sys.time() - start, units = 'secs') if (is.nan(rate)) rate <- 0 rate <- format(rate, digits = 2) pb$tick(tokens = list(fps = rate)) if (!stream) dev.off() } frame_vars <- plot$scene$frame_vars[frames, , drop = FALSE] if (!stream) frame_vars$frame_source <- files frame_vars } # Get dimensions of plot based on a reference frame plot_dims <- function(plot, ref_frame) { tmpf <- tempfile() png(tmpf) on.exit({ dev.off() unlink(tmpf) }) frame <- plot$scene$get_frame(plot, ref_frame) frame <- ggplot_gtable(frame) widths_rel <- frame$widths widths <- convertWidth(widths_rel, 'mm') heights_rel <- frame$heights heights <- convertHeight(heights_rel, 'mm') if (is.list(widths)) { # New unit spec null_widths <- vapply(unclass(widths), `[[`, numeric(1), 1L) == 0 null_heights <- vapply(unclass(heights), `[[`, numeric(1), 1L) == 0 } else { null_widths <- as.numeric(widths) == 0 null_heights <- as.numeric(heights) == 0 } widths[null_widths] <- widths_rel[null_widths] heights[null_heights] <- heights_rel[null_heights] list(widths = widths, heights = heights) } is_knitting <- function() isTRUE(getOption("knitr.in.progress")) gganimate/R/tween_before_stat.R0000644000176200001440000000040313405665100016226 0ustar liggesusers#' Define if layers should be tweened before stats are calculated #' #' @param x a Layer, Geom, or Stat #' @keywords internal #' @export tween_before_stat <- function(x) UseMethod('tween_before_stat') #' @export tween_before_stat.default <- function(x) FALSE gganimate/R/transmute-exit.R0000644000176200001440000000256513405665100015533 0ustar liggesusers#' @rdname enter_exit #' @export exit_manual <- function(default = NULL, ..., name = 'manual') { create_factory('exit', default, ..., name = name) } #' @rdname enter_exit #' @export exit_disappear <- function(early = FALSE, ...) { transmute_appear('exit', early = !early, ..., name = 'disappear') } #' @rdname enter_exit #' @export exit_fade <- function(..., alpha = 0) { transmute_fade('exit', ..., alpha = alpha, name = 'fade') } #' @rdname enter_exit #' @export exit_shrink <- function(..., size = 0) { transmute_grow('exit', ..., size = size, name = 'shrink') } #' @rdname enter_exit #' @export exit_recolour <- function(..., colour = 'white', fill = colour) { transmute_recolour('exit', ..., colour = colour, fill = fill, name = 'recolour') } #' @rdname enter_exit #' @export exit_recolor <- function(..., color = 'white', fill = color) { exit_recolour(..., colour = color, fill = fill) } #' @rdname enter_exit #' @export exit_fly <- function(..., x_loc = NA, y_loc = NA) { transmute_fly('exit', ..., x_loc = x_loc, y_loc = y_loc, name = 'fly') } #' @rdname enter_exit #' @export exit_drift <- function(..., x_mod = 0, y_mod = 0) { transmute_drift('exit', ..., x_mod = x_mod, y_mod = y_mod, name = 'drift') } # RESET ------------------------------------------------------------------- #' @rdname enter_exit #' @export exit_reset <- function() { create_resetter('exit') } gganimate/R/view-zoom.R0000644000176200001440000001244713413127333014476 0ustar liggesusers#' @include view-step.R NULL #' Pan and zoom smoothly between different states #' #' This view is in many ways equivalent to [view_step()] and #' [view_step_manual()] but instead of simply tweening the bounding box of each #' view it implement the smooth zoom and pan technique developed by Reach & #' North (2018). It gradually zooms out and then in during the pan to allow a #' smooth transition of the view. As with [view_step()] the standard version #' will look at the data present in the calculated frames and set the ranges #' based on that, while the `_manual` version will allow you to define your own #' ranges to zoom between. #' #' @references Reach, A., North, C. (2018) *Smooth, Efficient, and Interruptible Zooming and Panning*. IEEE Transactions on Visualization and Computer Graphics DOI:10.1109/TVCG.2018.2800013 #' #' @param pan_zoom The tradeoff between pan- and zoom-induced movement. Negative #' values will value zoom over pan and positive values will value pan over zoom #' @inheritParams view_step #' #' @family views #' #' @importFrom ggplot2 ggproto #' @export #' #' @examples #' anim <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + #' view_zoom(pause_length = 1, step_length = 2, nsteps = 3) #' #' # Use pan_zoom to change the relationship between pan- and zoom movement #' # Mainly zooming #' anim1 <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + #' view_zoom(pause_length = 1, step_length = 2, nsteps = 3, pan_zoom = -3) #' #' # Mainly panning #' anim2 <- ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) + #' geom_point() + #' transition_states(Species, transition_length = 2, state_length = 1) + #' shadow_mark(past = TRUE, future = TRUE, colour = 'grey') + #' view_zoom(pause_length = 1, step_length = 2, nsteps = 3, pan_zoom = -3) #' view_zoom <- function(pause_length = 1, step_length = 1, nsteps = NULL, look_ahead = 0, delay = 0, include = FALSE, pan_zoom = 0, ease = 'sine-in-out', wrap = TRUE, pause_first = TRUE, fixed_x = FALSE, fixed_y = FALSE, exclude_layer = NULL, aspect_ratio = 1) { ggproto(NULL, ViewZoom, fixed_lim = list(x = fixed_x, y = fixed_y), exclude_layer = exclude_layer, aspect_ratio = aspect_ratio, params = list( pause_length = pause_length, step_length = step_length, nsteps = nsteps, look_ahead = look_ahead, delay = delay, include = include, pan_zoom = exp(pan_zoom), ease = ease, wrap = wrap, pause_first = pause_first ) ) } transition_window <- function(windows, next_window, n, params) { if (is.null(windows$.frame)) { windows$.id <- seq_len(nrow(windows)) windows$.phase <- 'raw' windows$.frame <- seq_len(nrow(windows)) } else { attr(windows, 'nframes') <- NULL } if (nrow(windows) == 1) n <- n - 1 start <- windows[nrow(windows), , drop = FALSE] w0 <- start$xmax - start$xmin w1 <- next_window$xmax - next_window$xmin x0 <- start$xmin + w0/2 x1 <- next_window$xmin + w1/2 x_traj <- trajectory(x0, x1, w0, w1, n + 1, params$pan_zoom, params$ease) h0 <- start$ymax - start$ymin h1 <- next_window$ymax - next_window$ymin y0 <- start$ymin + h0/2 y1 <- next_window$ymin + h1/2 y_traj <- trajectory(y0, y1, h0, h1, n + 1, params$pan_zoom, params$ease) new_windows <- data.frame( xmin = as.vector(x_traj$u - x_traj$v/2), xmax = as.vector(x_traj$u + x_traj$v/2), ymin = as.vector(y_traj$u - y_traj$v/2), ymax = as.vector(y_traj$u + y_traj$v/2), .frame = seq_len(n + 1) - 1 + if (is.null(start$.frame)) 0 else start$.frame ) missing_cols <- setdiff(names(start), names(new_windows)) new_windows[missing_cols] <- start[1, missing_cols, drop = FALSE] rbind( windows, new_windows[-1, match(names(start), names(new_windows))] ) } #' @rdname gganimate-ggproto #' @format NULL #' @usage NULL #' @export #' @importFrom ggplot2 ggproto #' @importFrom tweenr tween_numeric ViewZoom <- ggproto('ViewZoom', ViewStep, window_transition = transition_window ) trajectory <- function(u0, u1, v0, v1, n, tradeoff, ease) { v0 <- v0 * tradeoff v1 <- v1 * tradeoff s <- tween_numeric(c(0, 1), n, ease)[[1]] if (all(u0 == u1)) { u <- matrix(u0, ncol = length(u0), nrow = n, byrow = TRUE) k <- sign(v1 - v0) S <- abs(log(v1/v0)) s <- s * S v <- v0 * exp(s * k) } else { lu <- sqrt(sum((u1 - u0)^2)) r0 <- ri(v1, v0, 0, lu) r1 <- ri(v1, v0, 1, lu) S <- r1 - r0 s <- s * S cosh_s_r0 <- cosh(s + r0) v <- v0 * cosh(r0) / cosh_s_r0 u_part1 <- v0 * (sinh(s) / cosh_s_r0) u_part2 <- (u1 - u0) / lu u_part12 <- vapply(u_part2, `*`, u_part1, u_part1) u <- matrix(u0, ncol = length(u0))[rep(1, length(u_part1))] + u_part12 } list(u = u, v = v/tradeoff) } ri <- function(v1, v0, i, lu) { top <- v1^2 - v0^2 + (-1)^i * lu^2 bottom <- -2 * (if (i == 0) v0 else v1) * lu asinh(top/bottom) } gganimate/NEWS.md0000644000176200001440000000305313741667505013323 0ustar liggesusers# gganimate 1.0.7 * Support ragg png device to ensure that it works with knitr's ragg support # gganimate 1.0.6 # gganimate 1.0.5 * No longer needs the png package for gifski rendering * Give startup message if no renderer backend are detected. # gganimate 1.0.4 * Fix a bug in `ffmpeg_renderer()` where the `fps` argument were being ignored. * Make sure `ggraph` objects registers the graph context after they are promoted to `gganim` objects. * Better fallback strategy for lack of gifski. # gganimate 1.0.3 * Fix a conditional in the plot building step to make it work with the ggplot2 3.1.1 hotfix. # gganimate 1.0.2 * Fix registration of S3 methods for suggested packages. # gganimate 1.0.1 * Fix bug in transitions when the group aesthetic was late evalued (#262) * Better fade support for `geom_smooth()`. Both ribbon and line will now fade. * Fix bug in transitions when group aesthetic was a string that could be interpreted as a double (#266) * Fix bug in `shadow_mark()` where future shadows were drawn above the main frame data. * Better error messages when a layer type is not supported by the transition * Fix bug where transitions didn't work with difftime/hms for specifying durations when transition variable was a POSIX or date class. * Fix bug where using a view would modify the plot coordinate system in-place, resulting in modifications to the original plot object. * `view_follow` now works with transformed scales. # gganimate 1.0.0 * First CRAN release, featuring a complete rewrite... 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[*ggplot2*](https://ggplot2.tidyverse.org) package, that adds support for declaring animations using an API familiar to users of *ggplot2*. > The following introduction assumes familiarity with *ggplot2* to the extend that constructing static plots and reading standard *ggplot2* code feels natural. If you are new to both *ggplot2* and *gganimate* you'll benefit from exploring the trove of *ggplot2* documentation, tutorials, and courses available online first (see the [*ggplot2* webpage](https://ggplot2.tidyverse.org/#learning-ggplot2) for some pointers). ## Your First Animation We'll jump right into our first animation. Don't worry too much about understanding the code, as we'll dissect it later. ```{r} library(gganimate) # We'll start with a static plot p <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point() plot(p) ``` You go from a static plot made with *ggplot2* to an animated one, simply by adding on functions from *gganimate*. ```{r} anim <- p + transition_states(Species, transition_length = 2, state_length = 1) anim ``` > â— `transition_states()` splits up plot data by a discrete variable and animates between the different states. As can be seen, very few additions to the plot results in a quite complex animation. So what did we do to get this animation? We added a type of *transition*. Transitions are functions that interpret the plot data in order to somehow distribute it over a number of frames. `transition_states()` specifically splits the data into subsets based on a variable in the data (here `Species`), and calculates intermediary data states that ensures a smooth transition between the states (something referred to as *tweening*). *gganimate* provides a range of different transitions, but for the rest of the examples we'll be sticking to `transition_states()` and see how we can modify the output. ## Easing When `transition_states()` calculates intermediary data for the tweening, it needs to decide how the change from one value to another should progress. This is a concept called *easing*. The default easing is *linear*, but others can be used, potentially only targeting specific aesthetics. Setting easing is done with the `ease_aes()` function. The first argument sets the default easing and subsequent named arguments sets it for specific aesthetics. ```{r} anim + ease_aes('cubic-in-out') # Slow start and end for a smoother look ``` > â— `ease_aes()` defines the velocity with which aesthetics change during an animation. ```{r} anim + ease_aes(y = 'bounce-out') # Sets special ease for y aesthetic ``` ## Labeling It can be quite hard to understand an animation without any indication as to what each time point relates to. *gganimate* solves this by providing a set of variables for each frame, which can be inserted into plot labels using [*glue*](https://glue.tidyverse.org) syntax. ```{r} anim + ggtitle('Now showing {closest_state}', subtitle = 'Frame {frame} of {nframes}') ``` > â— Use *glue* syntax to insert frame variables in plot labels and titles. Different transitions provide different frame variables. `closest_state` only makes sense for `transition_states()` and is thus only available when that transition is used. ## Object Permanence In the animation above, it appears as if data in a single measurement changes gradually as the flower being measured on somehow morphs between three different iris species. This is probably not how Fisher conducted the experiment and got those numbers. In general, when you make an animation, *graphic elements should only transition between instances of the same underlying phenomenon*. This sounds complicated but it is more or less the same principle that governs makes sense to draw a line between two observations. You wouldn't connect observations from different iris species, but repeated observations on the same plant would be fine to connect. Same thing with animations. Just to make this very clear (it is an important concept). The line plot equivalent of our animation above is: ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_line(aes(group = rep(1:50, 3)), colour = 'grey') + geom_point() ``` Ugh... So, how do we fix this and tell *gganimate* to not morph observations from different species into each others? The key is the *group aesthetic*. You may be familiar with this aesthetic from plotting lines and polygons, but in *gganimate* it takes a more central place. Data that have the same group aesthetic are interpreted as being linked across states. The semantics of the group aesthetic in *ggplot2* is such that if it is undefined it will get calculated based on the interaction of all discrete aesthetics (sans `label`). If none exists, such as in our iris animation, all data will get the same group, and will thus be matched by *gganimate*. So, there are two ways to fix our plot: 1. Add some aesthetics that distinguish the different species ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species)) + transition_states(Species, transition_length = 2, state_length = 1) ``` 2. Set the group directly ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(group = seq_along(Species))) + transition_states(Species, transition_length = 2, state_length = 1) ``` > â— The group aesthetic defines how the data in a layer is matched across the animation. In general *2)* is preferred as it makes the intend explicit. It also makes it possible to match data with different discrete aesthetics such as keeping our (now obviously faulty) transition while having different colour for the different species) ```{r} ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species, group = 1L)) + transition_states(Species, transition_length = 2, state_length = 1) ``` ## Enter and Exit While we may have made our animation more correct by separating the data from the different species, we have also made it quite a bit more boring. Now it simply appears as three static plots shown one at a time, which is hardly an attention grabber. If only there were a way to animate the appearance and disappearance of data... Enter the `enter` and `exit` functions. These functions are responsible for modifying the state of appearing (entering) and disappearing (exiting) data, so that the animation can tween from and to the new state. Let's spice up our animation a bit: ```{r} anim <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species), size = 2) + transition_states(Species, transition_length = 2, state_length = 1) anim + enter_fade() + exit_shrink() ``` > â— `enter` and `exit` functions are used to modify the aesthetics of appearing and disappearing data so that their entrance or exit may be animated. *gganimate* comes with a range of different functions, and using the `enter_manual()` and `exit_manual()` functions you can create your own. Enter and exit functions are composable though, so you can often come pretty far by combining preexisting ones ```{r} anim + enter_fade() + enter_drift(x_mod = -1) + exit_shrink() + exit_drift(x_mod = 5) ``` ## Rendering In the examples above the animations has simply appeared when we printed the animation object, just like we would expect from *ggplot2*. As a lot of things are happening automatically, and you might want to take control, this section will give a brief overview of the rendering. *gganimate*'s model for an animation is dimensionless in the same way as *ggplot2* describe plots independent of the final width and height of the plot. This means that the final number of frames and its frame-rate are only ever given when you ask *gganimate* to render the animation. When you print an animation object the `animate()` function is called on the animation with default arguments, some of which are: - **nframes** sets the number of frames (defaults to `100`) - **fps** sets the number of frames (defaults to `10`) - **dev** sets the device used to render each frame (defaults to `'png'`) - **renderer** sets the function used to combine each frame into an animate (defaults to `gifski_renderer()`) There are other arguments as well (e.g. `...` will be passed on to the device so you can set width, height, dpi, etc), but these are the most important. If you don't like the defaults you can either call `animate()` directly with values of your choosing, or modify the defaults by setting new with `options(gganimate. = )`. A topic that requires some additional words are the renderers. The default will use [gifski](https://github.com/r-rust/gifski) to combine the frames into a gif. gifs are great because they are virtually supported everywhere, and gifski is both a very fast, and very high quality converter. Still, you may have reasons to want a different output. *gganimate* is quite agnostic to how you want to combine the frames and, while it comes with a set of predefined renderers, any function that takes a vector of paths to image files along with a frame-rate, will do. The return value of your renderer is what is ultimately returned by the `animate()` function. Below are a couple of examples of different `animate()` calls: ```{r, eval=requireNamespace('av', quietly = TRUE)} # Video output animate( anim + enter_fade() + exit_fly(y_loc = 1), renderer = av_renderer() ) ``` ```{r, out.width=NULL} # Different size and resolution animate( anim + ease_aes(x = 'bounce-out') + enter_fly(x_loc = -1) + exit_fade(), width = 400, height = 600, res = 35 ) ``` If you need to save the animation for later use you can use the `anim_save()` function. It works much like `ggsave()` from *ggplot2* and automatically grabs the last rendered animation if you do not specify one directly. ## Want more? This guide is far from exhaustive, but have hopefully given you a broad understanding of how *gganimate* works. There are still more to explore as we have only scratched the surface of transitions, let alone mentioned views and shadows. But for now this is left to you. There is a fantastic joy in discovery and with the things you have now learned you are ready to go digging on your own. gganimate/inst/doc/gganimate.html0000644000176200001440000717753313741667704016620 0ustar liggesusers Getting Started

Getting Started

gganimate is an extension of the grammar of graphics, as implemented by the ggplot2 package, that adds support for declaring animations using an API familiar to users of ggplot2.

The following introduction assumes familiarity with ggplot2 to the extend that constructing static plots and reading standard ggplot2 code feels natural. If you are new to both ggplot2 and gganimate you’ll benefit from exploring the trove of ggplot2 documentation, tutorials, and courses available online first (see the ggplot2 webpage for some pointers).

Your First Animation

We’ll jump right into our first animation. Don’t worry too much about understanding the code, as we’ll dissect it later.

library(gganimate)
#> Loading required package: ggplot2

# We'll start with a static plot
p <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_point()

plot(p)

You go from a static plot made with ggplot2 to an animated one, simply by adding on functions from gganimate.

anim <- p + 
  transition_states(Species,
                    transition_length = 2,
                    state_length = 1)

anim

â— transition_states() splits up plot data by a discrete variable and animates between the different states.

As can be seen, very few additions to the plot results in a quite complex animation. So what did we do to get this animation? We added a type of transition. Transitions are functions that interpret the plot data in order to somehow distribute it over a number of frames. transition_states() specifically splits the data into subsets based on a variable in the data (here Species), and calculates intermediary data states that ensures a smooth transition between the states (something referred to as tweening). gganimate provides a range of different transitions, but for the rest of the examples we’ll be sticking to transition_states() and see how we can modify the output.

Easing

When transition_states() calculates intermediary data for the tweening, it needs to decide how the change from one value to another should progress. This is a concept called easing. The default easing is linear, but others can be used, potentially only targeting specific aesthetics. Setting easing is done with the ease_aes() function. The first argument sets the default easing and subsequent named arguments sets it for specific aesthetics.

anim + 
  ease_aes('cubic-in-out') # Slow start and end for a smoother look

â— ease_aes() defines the velocity with which aesthetics change during an animation.

anim + 
  ease_aes(y = 'bounce-out') # Sets special ease for y aesthetic

Labeling

It can be quite hard to understand an animation without any indication as to what each time point relates to. gganimate solves this by providing a set of variables for each frame, which can be inserted into plot labels using glue syntax.

anim + 
  ggtitle('Now showing {closest_state}',
          subtitle = 'Frame {frame} of {nframes}')

â— Use glue syntax to insert frame variables in plot labels and titles.

Different transitions provide different frame variables. closest_state only makes sense for transition_states() and is thus only available when that transition is used.

Object Permanence

In the animation above, it appears as if data in a single measurement changes gradually as the flower being measured on somehow morphs between three different iris species. This is probably not how Fisher conducted the experiment and got those numbers. In general, when you make an animation, graphic elements should only transition between instances of the same underlying phenomenon. This sounds complicated but it is more or less the same principle that governs makes sense to draw a line between two observations. You wouldn’t connect observations from different iris species, but repeated observations on the same plant would be fine to connect. Same thing with animations.

Just to make this very clear (it is an important concept). The line plot equivalent of our animation above is:

ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_line(aes(group = rep(1:50, 3)), colour = 'grey') + 
  geom_point()

Ugh…

So, how do we fix this and tell gganimate to not morph observations from different species into each others? The key is the group aesthetic. You may be familiar with this aesthetic from plotting lines and polygons, but in gganimate it takes a more central place. Data that have the same group aesthetic are interpreted as being linked across states. The semantics of the group aesthetic in ggplot2 is such that if it is undefined it will get calculated based on the interaction of all discrete aesthetics (sans label). If none exists, such as in our iris animation, all data will get the same group, and will thus be matched by gganimate. So, there are two ways to fix our plot:

  1. Add some aesthetics that distinguish the different species
ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_point(aes(colour = Species)) + 
  transition_states(Species,
                    transition_length = 2,
                    state_length = 1)

  1. Set the group directly
ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_point(aes(group = seq_along(Species))) + 
  transition_states(Species,
                    transition_length = 2,
                    state_length = 1)

â— The group aesthetic defines how the data in a layer is matched across the animation.

In general 2) is preferred as it makes the intend explicit. It also makes it possible to match data with different discrete aesthetics such as keeping our (now obviously faulty) transition while having different colour for the different species)

ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_point(aes(colour = Species, group = 1L)) + 
  transition_states(Species,
                    transition_length = 2,
                    state_length = 1)

Enter and Exit

While we may have made our animation more correct by separating the data from the different species, we have also made it quite a bit more boring. Now it simply appears as three static plots shown one at a time, which is hardly an attention grabber. If only there were a way to animate the appearance and disappearance of data…

Enter the enter and exit functions. These functions are responsible for modifying the state of appearing (entering) and disappearing (exiting) data, so that the animation can tween from and to the new state. Let’s spice up our animation a bit:

anim <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + 
  geom_point(aes(colour = Species), size = 2) + 
  transition_states(Species,
                    transition_length = 2,
                    state_length = 1)

anim + 
  enter_fade() + 
  exit_shrink()

â— enter and exit functions are used to modify the aesthetics of appearing and disappearing data so that their entrance or exit may be animated.

gganimate comes with a range of different functions, and using the enter_manual() and exit_manual() functions you can create your own. Enter and exit functions are composable though, so you can often come pretty far by combining preexisting ones

anim + 
  enter_fade() + enter_drift(x_mod = -1) + 
  exit_shrink() + exit_drift(x_mod = 5)

Rendering

In the examples above the animations has simply appeared when we printed the animation object, just like we would expect from ggplot2. As a lot of things are happening automatically, and you might want to take control, this section will give a brief overview of the rendering.

gganimate’s model for an animation is dimensionless in the same way as ggplot2 describe plots independent of the final width and height of the plot. This means that the final number of frames and its frame-rate are only ever given when you ask gganimate to render the animation. When you print an animation object the animate() function is called on the animation with default arguments, some of which are:

  • nframes sets the number of frames (defaults to 100)
  • fps sets the number of frames (defaults to 10)
  • dev sets the device used to render each frame (defaults to 'png')
  • renderer sets the function used to combine each frame into an animate (defaults to gifski_renderer())

There are other arguments as well (e.g. ... will be passed on to the device so you can set width, height, dpi, etc), but these are the most important. If you don’t like the defaults you can either call animate() directly with values of your choosing, or modify the defaults by setting new with options(gganimate.<argument> = <value>).

A topic that requires some additional words are the renderers. The default will use gifski to combine the frames into a gif. gifs are great because they are virtually supported everywhere, and gifski is both a very fast, and very high quality converter. Still, you may have reasons to want a different output. gganimate is quite agnostic to how you want to combine the frames and, while it comes with a set of predefined renderers, any function that takes a vector of paths to image files along with a frame-rate, will do. The return value of your renderer is what is ultimately returned by the animate() function.

Below are a couple of examples of different animate() calls:

# Video output
animate(
  anim + enter_fade() + exit_fly(y_loc = 1),
  renderer = av_renderer()
)
# Different size and resolution
animate(
  anim + ease_aes(x = 'bounce-out') + enter_fly(x_loc = -1) + exit_fade(),
  width = 400, height = 600, res = 35
)

If you need to save the animation for later use you can use the anim_save() function. It works much like ggsave() from ggplot2 and automatically grabs the last rendered animation if you do not specify one directly.

Want more?

This guide is far from exhaustive, but have hopefully given you a broad understanding of how gganimate works. There are still more to explore as we have only scratched the surface of transitions, let alone mentioned views and shadows. But for now this is left to you. There is a fantastic joy in discovery and with the things you have now learned you are ready to go digging on your own.

gganimate/inst/doc/gganimate.R0000644000176200001440000000614013741667703016026 0ustar liggesusers## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", gganimate = list( nframes = 50 ), out.width = '100%' ) ## ----------------------------------------------------------------------------- library(gganimate) # We'll start with a static plot p <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point() plot(p) ## ----------------------------------------------------------------------------- anim <- p + transition_states(Species, transition_length = 2, state_length = 1) anim ## ----------------------------------------------------------------------------- anim + ease_aes('cubic-in-out') # Slow start and end for a smoother look ## ----------------------------------------------------------------------------- anim + ease_aes(y = 'bounce-out') # Sets special ease for y aesthetic ## ----------------------------------------------------------------------------- anim + ggtitle('Now showing {closest_state}', subtitle = 'Frame {frame} of {nframes}') ## ----------------------------------------------------------------------------- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_line(aes(group = rep(1:50, 3)), colour = 'grey') + geom_point() ## ----------------------------------------------------------------------------- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species)) + transition_states(Species, transition_length = 2, state_length = 1) ## ----------------------------------------------------------------------------- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(group = seq_along(Species))) + transition_states(Species, transition_length = 2, state_length = 1) ## ----------------------------------------------------------------------------- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species, group = 1L)) + transition_states(Species, transition_length = 2, state_length = 1) ## ----------------------------------------------------------------------------- anim <- ggplot(iris, aes(x = Petal.Width, y = Petal.Length)) + geom_point(aes(colour = Species), size = 2) + transition_states(Species, transition_length = 2, state_length = 1) anim + enter_fade() + exit_shrink() ## ----------------------------------------------------------------------------- anim + enter_fade() + enter_drift(x_mod = -1) + exit_shrink() + exit_drift(x_mod = 5) ## ---- eval=requireNamespace('av', quietly = TRUE)----------------------------- # Video output animate( anim + enter_fade() + exit_fly(y_loc = 1), renderer = av_renderer() ) ## ---- out.width=NULL---------------------------------------------------------- # Different size and resolution animate( anim + ease_aes(x = 'bounce-out') + enter_fly(x_loc = -1) + exit_fade(), width = 400, height = 600, res = 35 )