munsell/0000755000176200001440000000000013307646022011734 5ustar liggesusersmunsell/inst/0000755000176200001440000000000013307601203012701 5ustar liggesusersmunsell/inst/raw/0000755000176200001440000000000012111711677013503 5ustar liggesusersmunsell/inst/raw/getmunsellmap.R0000644000176200001440000000435312325545303016506 0ustar liggesusers### explore the mapping getmunsellmap <- function(){ require(colorspace) col.map <- read.table("real.dat", header = TRUE) # correct sequence # 1. convert xyY to XYZ # 2. convert to XYZ to use correct reference white (C to D65) # 3. convert XYZ (D65) to sRGB # 1. convert to XYZ # http://www.brucelindbloom.com/Eqn_xyY_to_XYZ.html # Y needs to be scaled down by 100 col.map <- within(col.map, { Y <- Y/100 X <- x * Y / y Z <- ((1 - x - y) * Y) / y }) # 2. convert to XYZ to use correct reference white (C to D65) # http://www.brucelindbloom.com/Eqn_ChromAdapt.html # using Bradford method Bradford.C.D65 <- matrix(c(0.990448, -0.012371, -0.003564, -0.007168, 1.015594, 0.006770, -0.011615, -0.002928, 0.918157), ncol=3, byrow=TRUE) col.map[ , c("X", "Y", "Z")] <- as.matrix(col.map[, c("X", "Y", "Z")]) %*% Bradford.C.D65 # 3. Use colorspace methods to convert XYZ to hex (sRGB) col.map$hex <- hex(XYZ(100 * as.matrix(col.map[, c("X", "Y", "Z")]))) cols <- c("R", "YR", "Y", "GY", "G", "BG", "B", "PB", "P", "RP") ints <- seq(2.5, 10, 2.5) col.map$h <- factor(col.map$h, levels = paste(rep(ints, 10), rep(cols, each = 4), sep = "")) # from here: http://wiki.laptop.org/go/Munsell grey.map <- read.table("greys.dat", header = TRUE) grey.map$hex <- hex(sRGB(as.matrix(1/255 * grey.map[, c("r", "b", "g")]))) munsell.map <- rbind(grey.map[, c("h", "C", "V", "hex")], col.map[, c("h", "C", "V", "hex")]) names(munsell.map) <- c("hue", "chroma", "value", "hex") munsell.map$name <- paste(munsell.map$hue, " ", munsell.map$value, "/", munsell.map$chroma, sep = "") munsell.map$name[is.na(munsell.map$hex)] <- NA not.miss <- subset(munsell.map, !is.na(hex)) not.miss <- cbind(not.miss, as(hex2RGB(not.miss$hex), "LUV")@coords) munsell.map <- merge(munsell.map, not.miss, all.x = TRUE) munsell.map[munsell.map$name == "N 0/0" & !is.na(munsell.map$name), c("L", "U", "V")] <- c(0, 0, 0) more.greys <- expand.grid(hue = unique(col.map$h), chroma = 0, value = 0:10) munsell.map <- rbind(munsell.map, merge(more.greys, munsell.map[munsell.map$hue == "N", c("chroma", "value", "hex", "name", "L", "U", "V")])) save(munsell.map, file = "../../R/sysdata.rda") }munsell/inst/raw/greys.dat0000644000176200001440000000030012023721262015310 0ustar liggesusersh C V r g b N 0 10 255 255 255 N 0 9 232 232 232 N 0 8 203 203 203 N 0 7 179 179 179 N 0 6 150 150 150 N 0 5 124 124 124 N 0 4 97 97 97 N 0 3 70 70 70 N 0 2 48 48 48 N 0 1 28 28 28 N 0 0 0 0 0munsell/inst/raw/real.dat0000644000176200001440000026522212023721262015122 0ustar liggesusers h V C x y Y 10RP 1 2 0.3629 0.2710 1.210 10RP 1 4 0.3920 0.2423 1.210 10RP 1 6 0.4151 0.2169 1.210 10RP 1 8 0.4357 0.1921 1.210 10RP 1 10 0.4521 0.1710 1.210 10RP 1 12 0.4668 0.1514 1.210 2.5R 1 2 0.3768 0.2816 1.210 2.5R 1 4 0.4166 0.2569 1.210 2.5R 1 6 0.4515 0.2329 1.210 2.5R 1 8 0.4812 0.2103 1.210 2.5R 1 10 0.5058 0.1900 1.210 5R 1 2 0.3908 0.2929 1.210 5R 1 4 0.4420 0.2728 1.210 5R 1 6 0.4885 0.2515 1.210 5R 1 8 0.5282 0.2297 1.210 5R 1 10 0.5604 0.2100 1.210 7.5R 1 2 0.4020 0.3034 1.210 7.5R 1 4 0.4660 0.2888 1.210 7.5R 1 6 0.5235 0.2698 1.210 7.5R 1 8 0.5722 0.2487 1.210 7.5R 1 10 0.6111 0.2290 1.210 10R 1 2 0.4128 0.3154 1.210 10R 1 4 0.4933 0.3068 1.210 10R 1 6 0.5584 0.2921 1.210 10R 1 8 0.6178 0.2713 1.210 10R 1 10 0.6661 0.2499 1.210 2.5YR 1 2 0.4258 0.3344 1.210 2.5YR 1 4 0.5311 0.3371 1.210 2.5YR 1 6 0.6048 0.3270 1.210 2.5YR 1 8 0.6721 0.3058 1.210 5YR 1 2 0.4377 0.3580 1.210 5YR 1 4 0.5660 0.3795 1.210 7.5YR 1 2 0.4430 0.3775 1.210 10YR 1 2 0.4446 0.3982 1.210 2.5Y 1 2 0.4362 0.4177 1.210 5Y 1 2 0.4230 0.4265 1.210 7.5Y 1 2 0.4042 0.4287 1.210 10Y 1 2 0.3802 0.4212 1.210 2.5GY 1 2 0.3540 0.4088 1.210 5GY 1 2 0.3359 0.3982 1.210 5GY 1 4 0.3765 0.5942 1.210 7.5GY 1 2 0.3154 0.3840 1.210 7.5GY 1 4 0.3133 0.5380 1.210 10GY 1 2 0.3006 0.3720 1.210 10GY 1 4 0.2722 0.4903 1.210 10GY 1 6 0.2232 0.6392 1.210 2.5G 1 2 0.2910 0.3634 1.210 2.5G 1 4 0.2454 0.4489 1.210 2.5G 1 6 0.1711 0.5619 1.210 2.5G 1 8 0.0620 0.6896 1.210 5G 1 2 0.2833 0.3564 1.210 5G 1 4 0.2290 0.4218 1.210 5G 1 6 0.1468 0.4996 1.210 7.5G 1 2 0.2758 0.3484 1.210 7.5G 1 4 0.2159 0.3967 1.210 7.5G 1 6 0.1344 0.4505 1.210 10G 1 2 0.2689 0.3407 1.210 10G 1 4 0.2040 0.3724 1.210 10G 1 6 0.1249 0.4019 1.210 2.5BG 1 2 0.2600 0.3289 1.210 2.5BG 1 4 0.1883 0.3406 1.210 2.5BG 1 6 0.1169 0.3452 1.210 2.5BG 1 8 0.0476 0.3458 1.210 5BG 1 2 0.2500 0.3141 1.210 5BG 1 4 0.1753 0.3021 1.210 5BG 1 6 0.1093 0.2860 1.210 7.5BG 1 2 0.2430 0.3023 1.210 7.5BG 1 4 0.1702 0.2768 1.210 7.5BG 1 6 0.1059 0.2485 1.210 10BG 1 2 0.2362 0.2882 1.210 10BG 1 4 0.1658 0.2496 1.210 10BG 1 6 0.1074 0.2129 1.210 2.5B 1 2 0.2322 0.2781 1.210 2.5B 1 4 0.1649 0.2324 1.210 2.5B 1 6 0.1118 0.1908 1.210 5B 1 2 0.2291 0.2677 1.210 5B 1 4 0.1667 0.2168 1.210 5B 1 6 0.1212 0.1745 1.210 7.5B 1 2 0.2291 0.2579 1.210 7.5B 1 4 0.1716 0.2048 1.210 7.5B 1 6 0.1303 0.1639 1.210 7.5B 1 8 0.0968 0.1280 1.210 10B 1 2 0.2309 0.2491 1.210 10B 1 4 0.1783 0.1974 1.210 10B 1 6 0.1392 0.1563 1.210 10B 1 8 0.1077 0.1218 1.210 2.5PB 1 2 0.2360 0.2420 1.210 2.5PB 1 4 0.1895 0.1911 1.210 2.5PB 1 6 0.1539 0.1491 1.210 2.5PB 1 8 0.1273 0.1157 1.210 5PB 1 2 0.2427 0.2368 1.210 5PB 1 4 0.2012 0.1867 1.210 5PB 1 6 0.1678 0.1447 1.210 5PB 1 8 0.1447 0.1124 1.210 5PB 1 10 0.1285 0.0870 1.210 7.5PB 1 2 0.2547 0.2310 1.210 7.5PB 1 4 0.2232 0.1821 1.210 7.5PB 1 6 0.2000 0.1422 1.210 7.5PB 1 8 0.1872 0.1141 1.210 7.5PB 1 10 0.1804 0.0950 1.210 7.5PB 1 12 0.1763 0.0804 1.210 7.5PB 1 14 0.1738 0.0688 1.210 7.5PB 1 16 0.1720 0.0583 1.210 7.5PB 1 18 0.1709 0.0518 1.210 7.5PB 1 20 0.1701 0.0454 1.210 7.5PB 1 22 0.1696 0.0402 1.210 7.5PB 1 24 0.1691 0.0352 1.210 7.5PB 1 26 0.1689 0.0309 1.210 7.5PB 1 28 0.1686 0.0270 1.210 7.5PB 1 30 0.1684 0.0234 1.210 7.5PB 1 32 0.1682 0.0202 1.210 7.5PB 1 34 0.1682 0.0180 1.210 7.5PB 1 36 0.1681 0.0160 1.210 7.5PB 1 38 0.1680 0.0140 1.210 10PB 1 2 0.2677 0.2280 1.210 10PB 1 4 0.2459 0.1828 1.210 10PB 1 6 0.2290 0.1470 1.210 10PB 1 8 0.2190 0.1228 1.210 10PB 1 10 0.2120 0.1029 1.210 10PB 1 12 0.2070 0.0869 1.210 10PB 1 14 0.2038 0.0745 1.210 10PB 1 16 0.2008 0.0638 1.210 10PB 1 18 0.1991 0.0564 1.210 10PB 1 20 0.1976 0.0493 1.210 10PB 1 22 0.1965 0.0436 1.210 10PB 1 24 0.1952 0.0380 1.210 10PB 1 26 0.1942 0.0326 1.210 10PB 1 28 0.1936 0.0281 1.210 10PB 1 30 0.1928 0.0240 1.210 2.5P 1 2 0.2808 0.2296 1.210 2.5P 1 4 0.2668 0.1874 1.210 2.5P 1 6 0.2570 0.1559 1.210 2.5P 1 8 0.2496 0.1303 1.210 2.5P 1 10 0.2441 0.1112 1.210 2.5P 1 12 0.2394 0.0940 1.210 2.5P 1 14 0.2361 0.0810 1.210 2.5P 1 16 0.2331 0.0696 1.210 2.5P 1 18 0.2312 0.0618 1.210 2.5P 1 20 0.2295 0.0542 1.210 2.5P 1 22 0.2279 0.0473 1.210 2.5P 1 24 0.2266 0.0418 1.210 2.5P 1 26 0.2251 0.0355 1.210 5P 1 2 0.2936 0.2330 1.210 5P 1 4 0.2854 0.1927 1.210 5P 1 6 0.2794 0.1628 1.210 5P 1 8 0.2742 0.1375 1.210 5P 1 10 0.2701 0.1178 1.210 5P 1 12 0.2670 0.1006 1.210 5P 1 14 0.2645 0.0863 1.210 5P 1 16 0.2625 0.0746 1.210 5P 1 18 0.2612 0.0667 1.210 5P 1 20 0.2601 0.0586 1.210 5P 1 22 0.2590 0.0509 1.210 7.5P 1 2 0.3030 0.2361 1.210 7.5P 1 4 0.2991 0.1974 1.210 7.5P 1 6 0.2960 0.1682 1.210 7.5P 1 8 0.2932 0.1429 1.210 7.5P 1 10 0.2905 0.1229 1.210 7.5P 1 12 0.2884 0.1059 1.210 7.5P 1 14 0.2868 0.0903 1.210 7.5P 1 16 0.2852 0.0790 1.210 7.5P 1 18 0.2841 0.0706 1.210 7.5P 1 20 0.2831 0.0625 1.210 10P 1 2 0.3132 0.2404 1.210 10P 1 4 0.3132 0.2032 1.210 10P 1 6 0.3126 0.1737 1.210 10P 1 8 0.3114 0.1481 1.210 10P 1 10 0.3102 0.1282 1.210 10P 1 12 0.3094 0.1110 1.210 10P 1 14 0.3084 0.0952 1.210 10P 1 16 0.3078 0.0839 1.210 10P 1 18 0.3069 0.0748 1.210 2.5RP 1 2 0.3240 0.2459 1.210 2.5RP 1 4 0.3290 0.2095 1.210 2.5RP 1 6 0.3321 0.1811 1.210 2.5RP 1 8 0.3342 0.1551 1.210 2.5RP 1 10 0.3354 0.1351 1.210 2.5RP 1 12 0.3361 0.1181 1.210 2.5RP 1 14 0.3368 0.1020 1.210 2.5RP 1 16 0.3368 0.0902 1.210 5RP 1 2 0.3378 0.2542 1.210 5RP 1 4 0.3503 0.2196 1.210 5RP 1 6 0.3588 0.1920 1.210 5RP 1 8 0.3660 0.1662 1.210 5RP 1 10 0.3727 0.1458 1.210 5RP 1 12 0.3772 0.1283 1.210 5RP 1 14 0.3811 0.1138 1.210 7.5RP 1 2 0.3498 0.2617 1.210 7.5RP 1 4 0.3705 0.2300 1.210 7.5RP 1 6 0.3865 0.2036 1.210 7.5RP 1 8 0.4005 0.1793 1.210 7.5RP 1 10 0.4132 0.1580 1.210 7.5RP 1 12 0.4240 0.1400 1.210 10RP 2 2 0.3532 0.2957 3.126 10RP 2 4 0.3850 0.2778 3.126 10RP 2 6 0.4139 0.2608 3.126 10RP 2 8 0.4428 0.2419 3.126 10RP 2 10 0.4678 0.2237 3.126 10RP 2 12 0.4911 0.2060 3.126 10RP 2 14 0.5129 0.1888 3.126 2.5R 2 2 0.3614 0.3033 3.126 2.5R 2 4 0.4021 0.2900 3.126 2.5R 2 6 0.4390 0.2760 3.126 2.5R 2 8 0.4776 0.2593 3.126 2.5R 2 10 0.5122 0.2428 3.126 2.5R 2 12 0.5438 0.2254 3.126 2.5R 2 14 0.5734 0.2083 3.126 5R 2 2 0.3692 0.3111 3.126 5R 2 4 0.4184 0.3032 3.126 5R 2 6 0.4642 0.2934 3.126 5R 2 8 0.5143 0.2800 3.126 5R 2 10 0.5557 0.2633 3.126 5R 2 12 0.5930 0.2465 3.126 5R 2 14 0.6302 0.2287 3.126 7.5R 2 2 0.3751 0.3181 3.126 7.5R 2 4 0.4335 0.3169 3.126 7.5R 2 6 0.4875 0.3123 3.126 7.5R 2 8 0.5433 0.3027 3.126 7.5R 2 10 0.5952 0.2874 3.126 7.5R 2 12 0.6392 0.2704 3.126 7.5R 2 14 0.6791 0.2520 3.126 10R 2 2 0.3811 0.3274 3.126 10R 2 4 0.4481 0.3330 3.126 10R 2 6 0.5095 0.3331 3.126 10R 2 8 0.5713 0.3259 3.126 10R 2 10 0.6247 0.3120 3.126 10R 2 12 0.6732 0.2937 3.126 10R 2 14 0.7165 0.2734 3.126 2.5YR 2 2 0.3852 0.3365 3.126 2.5YR 2 4 0.4598 0.3508 3.126 2.5YR 2 6 0.5280 0.3581 3.126 2.5YR 2 8 0.5995 0.3590 3.126 5YR 2 2 0.3880 0.3476 3.126 5YR 2 4 0.4674 0.3738 3.126 5YR 2 6 0.5426 0.3925 3.126 7.5YR 2 2 0.3889 0.3590 3.126 7.5YR 2 4 0.4690 0.3964 3.126 7.5YR 2 6 0.5475 0.4271 3.126 10YR 2 2 0.3872 0.3688 3.126 10YR 2 4 0.4676 0.4168 3.126 2.5Y 2 2 0.3825 0.3785 3.126 2.5Y 2 4 0.4627 0.4392 3.126 5Y 2 2 0.3757 0.3839 3.126 5Y 2 4 0.4543 0.4573 3.126 7.5Y 2 2 0.3660 0.3858 3.126 7.5Y 2 4 0.4401 0.4723 3.126 10Y 2 2 0.3556 0.3848 3.126 10Y 2 4 0.4188 0.4789 3.126 2.5GY 2 2 0.3421 0.3803 3.126 2.5GY 2 4 0.3881 0.4752 3.126 5GY 2 2 0.3309 0.3743 3.126 5GY 2 4 0.3582 0.4650 3.126 5GY 2 6 0.3839 0.5748 3.126 7.5GY 2 2 0.3165 0.3650 3.126 7.5GY 2 4 0.3248 0.4457 3.126 7.5GY 2 6 0.3260 0.5379 3.126 7.5GY 2 8 0.3160 0.6509 3.126 10GY 2 2 0.3069 0.3580 3.126 10GY 2 4 0.2986 0.4240 3.126 10GY 2 6 0.2852 0.4972 3.126 10GY 2 8 0.2628 0.5837 3.126 10GY 2 10 0.2307 0.6814 3.126 10GY 2 12 0.1907 0.7798 3.126 2.5G 2 2 0.2978 0.3507 3.126 2.5G 2 4 0.2763 0.3998 3.126 2.5G 2 6 0.2493 0.4522 3.126 2.5G 2 8 0.2192 0.5042 3.126 2.5G 2 10 0.1773 0.5698 3.126 2.5G 2 12 0.1307 0.6308 3.126 2.5G 2 14 0.0820 0.6860 3.126 2.5G 2 16 0.0329 0.7358 3.126 5G 2 2 0.2918 0.3450 3.126 5G 2 4 0.2640 0.3845 3.126 5G 2 6 0.2318 0.4231 3.126 5G 2 8 0.1979 0.4583 3.126 5G 2 10 0.1560 0.4981 3.126 5G 2 12 0.1120 0.5358 3.126 5G 2 14 0.0688 0.5691 3.126 5G 2 16 0.0277 0.5986 3.126 7.5G 2 2 0.2869 0.3400 3.126 7.5G 2 4 0.2540 0.3705 3.126 7.5G 2 6 0.2200 0.3983 3.126 7.5G 2 8 0.1842 0.4244 3.126 7.5G 2 10 0.1442 0.4505 3.126 7.5G 2 12 0.1022 0.4759 3.126 7.5G 2 14 0.0629 0.4973 3.126 7.5G 2 16 0.0276 0.5153 3.126 10G 2 2 0.2820 0.3341 3.126 10G 2 4 0.2442 0.3559 3.126 10G 2 6 0.2092 0.3739 3.126 10G 2 8 0.1705 0.3911 3.126 10G 2 10 0.1321 0.4059 3.126 10G 2 12 0.0934 0.4183 3.126 10G 2 14 0.0599 0.4270 3.126 10G 2 16 0.0285 0.4327 3.126 2.5BG 2 2 0.2765 0.3271 3.126 2.5BG 2 4 0.2343 0.3378 3.126 2.5BG 2 6 0.1971 0.3452 3.126 2.5BG 2 8 0.1557 0.3517 3.126 2.5BG 2 10 0.1190 0.3551 3.126 2.5BG 2 12 0.0851 0.3576 3.126 2.5BG 2 14 0.0555 0.3588 3.126 5BG 2 2 0.2697 0.3175 3.126 5BG 2 4 0.2234 0.3150 3.126 5BG 2 6 0.1843 0.3110 3.126 5BG 2 8 0.1405 0.3037 3.126 5BG 2 10 0.1050 0.2956 3.126 5BG 2 12 0.0769 0.2880 3.126 7.5BG 2 2 0.2651 0.3098 3.126 7.5BG 2 4 0.2162 0.2981 3.126 7.5BG 2 6 0.1747 0.2853 3.126 7.5BG 2 8 0.1325 0.2710 3.126 7.5BG 2 10 0.0991 0.2582 3.126 7.5BG 2 12 0.0724 0.2478 3.126 10BG 2 2 0.2606 0.3010 3.126 10BG 2 4 0.2096 0.2790 3.126 10BG 2 6 0.1669 0.2570 3.126 10BG 2 8 0.1258 0.2331 3.126 10BG 2 10 0.0929 0.2133 3.126 2.5B 2 2 0.2578 0.2940 3.126 2.5B 2 4 0.2060 0.2649 3.126 2.5B 2 6 0.1621 0.2358 3.126 2.5B 2 8 0.1230 0.2076 3.126 2.5B 2 10 0.0911 0.1828 3.126 5B 2 2 0.2559 0.2874 3.126 5B 2 4 0.2048 0.2518 3.126 5B 2 6 0.1617 0.2162 3.126 5B 2 8 0.1245 0.1827 3.126 5B 2 10 0.0965 0.1558 3.126 7.5B 2 2 0.2545 0.2799 3.126 7.5B 2 4 0.2063 0.2400 3.126 7.5B 2 6 0.1658 0.2026 3.126 7.5B 2 8 0.1313 0.1692 3.126 7.5B 2 10 0.1051 0.1422 3.126 10B 2 2 0.2558 0.2725 3.126 10B 2 4 0.2102 0.2313 3.126 10B 2 6 0.1716 0.1937 3.126 10B 2 8 0.1396 0.1603 3.126 10B 2 10 0.1157 0.1346 3.126 2.5PB 2 2 0.2592 0.2675 3.126 2.5PB 2 4 0.2175 0.2245 3.126 2.5PB 2 6 0.1825 0.1857 3.126 2.5PB 2 8 0.1540 0.1530 3.126 2.5PB 2 10 0.1332 0.1278 3.126 2.5PB 2 12 0.1166 0.1076 3.126 5PB 2 2 0.2638 0.2624 3.126 5PB 2 4 0.2263 0.2192 3.126 5PB 2 6 0.1942 0.1811 3.126 5PB 2 8 0.1685 0.1491 3.126 5PB 2 10 0.1500 0.1240 3.126 5PB 2 12 0.1363 0.1048 3.126 5PB 2 14 0.1253 0.0873 3.126 7.5PB 2 2 0.2712 0.2582 3.126 7.5PB 2 4 0.2420 0.2148 3.126 7.5PB 2 6 0.2189 0.1790 3.126 7.5PB 2 8 0.2005 0.1495 3.126 7.5PB 2 10 0.1882 0.1258 3.126 7.5PB 2 12 0.1813 0.1094 3.126 7.5PB 2 14 0.1762 0.0955 3.126 7.5PB 2 16 0.1728 0.0839 3.126 7.5PB 2 18 0.1701 0.0742 3.126 7.5PB 2 20 0.1685 0.0666 3.126 7.5PB 2 22 0.1670 0.0594 3.126 7.5PB 2 24 0.1660 0.0538 3.126 7.5PB 2 26 0.1653 0.0492 3.126 7.5PB 2 28 0.1647 0.0451 3.126 7.5PB 2 30 0.1640 0.0409 3.126 7.5PB 2 32 0.1635 0.0373 3.126 7.5PB 2 34 0.1630 0.0340 3.126 7.5PB 2 36 0.1628 0.0310 3.126 7.5PB 2 38 0.1623 0.0280 3.126 10PB 2 2 0.2803 0.2567 3.126 10PB 2 4 0.2600 0.2162 3.126 10PB 2 6 0.2440 0.1840 3.126 10PB 2 8 0.2294 0.1551 3.126 10PB 2 10 0.2200 0.1330 3.126 10PB 2 12 0.2139 0.1170 3.126 10PB 2 14 0.2087 0.1026 3.126 10PB 2 16 0.2052 0.0910 3.126 10PB 2 18 0.2021 0.0808 3.126 10PB 2 20 0.1998 0.0718 3.126 10PB 2 22 0.1978 0.0643 3.126 10PB 2 24 0.1962 0.0578 3.126 10PB 2 26 0.1949 0.0520 3.126 10PB 2 28 0.1937 0.0471 3.126 10PB 2 30 0.1925 0.0420 3.126 10PB 2 32 0.1918 0.0379 3.126 10PB 2 34 0.1911 0.0344 3.126 2.5P 2 2 0.2892 0.2583 3.126 2.5P 2 4 0.2758 0.2208 3.126 2.5P 2 6 0.2661 0.1921 3.126 2.5P 2 8 0.2570 0.1635 3.126 2.5P 2 10 0.2501 0.1422 3.126 2.5P 2 12 0.2449 0.1245 3.126 2.5P 2 14 0.2406 0.1100 3.126 2.5P 2 16 0.2372 0.0980 3.126 2.5P 2 18 0.2345 0.0873 3.126 2.5P 2 20 0.2320 0.0779 3.126 2.5P 2 22 0.2298 0.0696 3.126 2.5P 2 24 0.2277 0.0621 3.126 2.5P 2 26 0.2260 0.0555 3.126 2.5P 2 28 0.2245 0.0491 3.126 2.5P 2 30 0.2231 0.0432 3.126 5P 2 2 0.2984 0.2612 3.126 5P 2 4 0.2908 0.2261 3.126 5P 2 6 0.2850 0.1992 3.126 5P 2 8 0.2791 0.1707 3.126 5P 2 10 0.2748 0.1500 3.126 5P 2 12 0.2709 0.1320 3.126 5P 2 14 0.2676 0.1163 3.126 5P 2 16 0.2652 0.1045 3.126 5P 2 18 0.2632 0.0935 3.126 5P 2 20 0.2612 0.0838 3.126 5P 2 22 0.2597 0.0750 3.126 5P 2 24 0.2582 0.0669 3.126 5P 2 26 0.2569 0.0594 3.126 5P 2 28 0.2559 0.0525 3.126 7.5P 2 2 0.3071 0.2647 3.126 7.5P 2 4 0.3048 0.2321 3.126 7.5P 2 6 0.3025 0.2058 3.126 7.5P 2 8 0.3000 0.1781 3.126 7.5P 2 10 0.2979 0.1569 3.126 7.5P 2 12 0.2956 0.1392 3.126 7.5P 2 14 0.2938 0.1235 3.126 7.5P 2 16 0.2922 0.1106 3.126 7.5P 2 18 0.2912 0.0995 3.126 7.5P 2 20 0.2902 0.0901 3.126 7.5P 2 22 0.2890 0.0799 3.126 7.5P 2 24 0.2882 0.0719 3.126 10P 2 2 0.3161 0.2691 3.126 10P 2 4 0.3189 0.2390 3.126 10P 2 6 0.3207 0.2132 3.126 10P 2 8 0.3219 0.1862 3.126 10P 2 10 0.3230 0.1659 3.126 10P 2 12 0.3233 0.1477 3.126 10P 2 14 0.3235 0.1317 3.126 10P 2 16 0.3235 0.1181 3.126 10P 2 18 0.3233 0.1063 3.126 10P 2 20 0.3231 0.0962 3.126 10P 2 22 0.3230 0.0861 3.126 2.5RP 2 2 0.3279 0.2754 3.126 2.5RP 2 4 0.3382 0.2496 3.126 2.5RP 2 6 0.3470 0.2259 3.126 2.5RP 2 8 0.3555 0.2003 3.126 2.5RP 2 10 0.3617 0.1800 3.126 2.5RP 2 12 0.3668 0.1618 3.126 2.5RP 2 14 0.3711 0.1449 3.126 2.5RP 2 16 0.3748 0.1310 3.126 2.5RP 2 18 0.3778 0.1188 3.126 2.5RP 2 20 0.3802 0.1080 3.126 5RP 2 2 0.3383 0.2829 3.126 5RP 2 4 0.3558 0.2597 3.126 5RP 2 6 0.3708 0.2380 3.126 5RP 2 8 0.3858 0.2140 3.126 5RP 2 10 0.3971 0.1939 3.126 5RP 2 12 0.4080 0.1764 3.126 5RP 2 14 0.4180 0.1598 3.126 5RP 2 16 0.4269 0.1454 3.126 5RP 2 18 0.4338 0.1340 3.126 7.5RP 2 2 0.3459 0.2892 3.126 7.5RP 2 4 0.3702 0.2683 3.126 7.5RP 2 6 0.3918 0.2490 3.126 7.5RP 2 8 0.4137 0.2276 3.126 7.5RP 2 10 0.4321 0.2082 3.126 7.5RP 2 12 0.4481 0.1903 3.126 7.5RP 2 14 0.4624 0.1737 3.126 7.5RP 2 16 0.4744 0.1595 3.126 10RP 3 2 0.3526 0.3068 6.555 10RP 3 4 0.3889 0.2969 6.555 10RP 3 6 0.4218 0.2864 6.555 10RP 3 8 0.4552 0.2741 6.555 10RP 3 10 0.4851 0.2618 6.555 10RP 3 12 0.5139 0.2489 6.555 10RP 3 14 0.5380 0.2369 6.555 10RP 3 16 0.5628 0.2241 6.555 2.5R 3 2 0.3591 0.3130 6.555 2.5R 3 4 0.4021 0.3076 6.555 2.5R 3 6 0.4409 0.3009 6.555 2.5R 3 8 0.4821 0.2918 6.555 2.5R 3 10 0.5191 0.2811 6.555 2.5R 3 12 0.5536 0.2691 6.555 2.5R 3 14 0.5828 0.2579 6.555 2.5R 3 16 0.6116 0.2456 6.555 5R 3 2 0.3645 0.3190 6.555 5R 3 4 0.4148 0.3190 6.555 5R 3 6 0.4592 0.3168 6.555 5R 3 8 0.5064 0.3114 6.555 5R 3 10 0.5500 0.3024 6.555 5R 3 12 0.5884 0.2904 6.555 5R 3 14 0.6204 0.2789 6.555 5R 3 16 0.6520 0.2660 6.555 7.5R 3 2 0.3690 0.3248 6.555 7.5R 3 4 0.4240 0.3302 6.555 7.5R 3 6 0.4738 0.3316 6.555 7.5R 3 8 0.5251 0.3297 6.555 7.5R 3 10 0.5730 0.3240 6.555 7.5R 3 12 0.6158 0.3129 6.555 7.5R 3 14 0.6492 0.3012 6.555 7.5R 3 16 0.6817 0.2872 6.555 10R 3 2 0.3728 0.3314 6.555 10R 3 4 0.4308 0.3412 6.555 10R 3 6 0.4854 0.3467 6.555 10R 3 8 0.5393 0.3477 6.555 10R 3 10 0.5871 0.3440 6.555 10R 3 12 0.6322 0.3361 6.555 10R 3 14 0.6703 0.3249 6.555 2.5YR 3 2 0.3757 0.3391 6.555 2.5YR 3 4 0.4360 0.3563 6.555 2.5YR 3 6 0.4954 0.3692 6.555 2.5YR 3 8 0.5475 0.3771 6.555 2.5YR 3 10 0.5941 0.3818 6.555 5YR 3 2 0.3771 0.3476 6.555 5YR 3 4 0.4376 0.3715 6.555 5YR 3 6 0.4966 0.3908 6.555 5YR 3 8 0.5456 0.4040 6.555 7.5YR 3 2 0.3771 0.3549 6.555 7.5YR 3 4 0.4378 0.3865 6.555 7.5YR 3 6 0.4930 0.4116 6.555 7.5YR 3 8 0.5390 0.4306 6.555 10YR 3 2 0.3747 0.3630 6.555 10YR 3 4 0.4341 0.4018 6.555 10YR 3 6 0.4872 0.4326 6.555 10YR 3 8 0.5305 0.4559 6.555 2.5Y 3 2 0.3703 0.3700 6.555 2.5Y 3 4 0.4277 0.4166 6.555 2.5Y 3 6 0.4784 0.4531 6.555 5Y 3 2 0.3646 0.3748 6.555 5Y 3 4 0.4191 0.4283 6.555 5Y 3 6 0.4670 0.4711 6.555 7.5Y 3 2 0.3589 0.3778 6.555 7.5Y 3 4 0.4086 0.4379 6.555 7.5Y 3 6 0.4526 0.4889 6.555 10Y 3 2 0.3513 0.3789 6.555 10Y 3 4 0.3961 0.4452 6.555 10Y 3 6 0.4345 0.5026 6.555 2.5GY 3 2 0.3412 0.3768 6.555 2.5GY 3 4 0.3772 0.4484 6.555 2.5GY 3 6 0.4069 0.5110 6.555 5GY 3 2 0.3319 0.3729 6.555 5GY 3 4 0.3554 0.4429 6.555 5GY 3 6 0.3750 0.5109 6.555 5GY 3 8 0.3924 0.5832 6.555 7.5GY 3 2 0.3180 0.3644 6.555 7.5GY 3 4 0.3270 0.4288 6.555 7.5GY 3 6 0.3333 0.4967 6.555 7.5GY 3 8 0.3341 0.5700 6.555 7.5GY 3 10 0.3266 0.6448 6.555 10GY 3 2 0.3088 0.3578 6.555 10GY 3 4 0.3053 0.4123 6.555 10GY 3 6 0.2992 0.4717 6.555 10GY 3 8 0.2887 0.5361 6.555 10GY 3 10 0.2724 0.6026 6.555 10GY 3 12 0.2531 0.6700 6.555 10GY 3 14 0.2283 0.7423 6.555 2.5G 3 2 0.2999 0.3500 6.555 2.5G 3 4 0.2836 0.3915 6.555 2.5G 3 6 0.2642 0.4342 6.555 2.5G 3 8 0.2435 0.4752 6.555 2.5G 3 10 0.2170 0.5211 6.555 2.5G 3 12 0.1902 0.5642 6.555 2.5G 3 14 0.1626 0.6052 6.555 2.5G 3 16 0.1341 0.6420 6.555 2.5G 3 18 0.1049 0.6766 6.555 2.5G 3 20 0.0720 0.7127 6.555 2.5G 3 22 0.0390 0.7468 6.555 5G 3 2 0.2935 0.3439 6.555 5G 3 4 0.2711 0.3780 6.555 5G 3 6 0.2471 0.4100 6.555 5G 3 8 0.2228 0.4380 6.555 5G 3 10 0.1935 0.4682 6.555 5G 3 12 0.1660 0.4948 6.555 5G 3 14 0.1382 0.5197 6.555 5G 3 16 0.1120 0.5414 6.555 5G 3 18 0.0882 0.5605 6.555 5G 3 20 0.0620 0.5802 6.555 5G 3 22 0.0340 0.6011 6.555 7.5G 3 2 0.2890 0.3391 6.555 7.5G 3 4 0.2618 0.3667 6.555 7.5G 3 6 0.2346 0.3901 6.555 7.5G 3 8 0.2088 0.4101 6.555 7.5G 3 10 0.1800 0.4310 6.555 7.5G 3 12 0.1516 0.4505 6.555 7.5G 3 14 0.1262 0.4667 6.555 7.5G 3 16 0.1023 0.4818 6.555 7.5G 3 18 0.0798 0.4954 6.555 7.5G 3 20 0.0568 0.5082 6.555 7.5G 3 22 0.0332 0.5206 6.555 10G 3 2 0.2844 0.3337 6.555 10G 3 4 0.2525 0.3537 6.555 10G 3 6 0.2240 0.3699 6.555 10G 3 8 0.1970 0.3841 6.555 10G 3 10 0.1688 0.3974 6.555 10G 3 12 0.1411 0.4095 6.555 10G 3 14 0.1161 0.4192 6.555 10G 3 16 0.0925 0.4275 6.555 10G 3 18 0.0718 0.4340 6.555 10G 3 20 0.0528 0.4393 6.555 10G 3 22 0.0333 0.4444 6.555 2.5BG 3 2 0.2799 0.3271 6.555 2.5BG 3 4 0.2437 0.3386 6.555 2.5BG 3 6 0.2132 0.3468 6.555 2.5BG 3 8 0.1845 0.3531 6.555 2.5BG 3 10 0.1552 0.3580 6.555 2.5BG 3 12 0.1288 0.3620 6.555 2.5BG 3 14 0.1051 0.3648 6.555 2.5BG 3 16 0.0843 0.3667 6.555 2.5BG 3 18 0.0648 0.3682 6.555 2.5BG 3 20 0.0482 0.3695 6.555 5BG 3 2 0.2742 0.3192 6.555 5BG 3 4 0.2343 0.3200 6.555 5BG 3 6 0.2020 0.3188 6.555 5BG 3 8 0.1703 0.3159 6.555 5BG 3 10 0.1410 0.3118 6.555 5BG 3 12 0.1158 0.3071 6.555 5BG 3 14 0.0940 0.3027 6.555 5BG 3 16 0.0735 0.2979 6.555 5BG 3 18 0.0580 0.2940 6.555 7.5BG 3 2 0.2699 0.3120 6.555 7.5BG 3 4 0.2272 0.3041 6.555 7.5BG 3 6 0.1928 0.2958 6.555 7.5BG 3 8 0.1620 0.2872 6.555 7.5BG 3 10 0.1326 0.2784 6.555 7.5BG 3 12 0.1086 0.2706 6.555 7.5BG 3 14 0.0874 0.2627 6.555 7.5BG 3 16 0.0691 0.2559 6.555 10BG 3 2 0.2660 0.3050 6.555 10BG 3 4 0.2221 0.2886 6.555 10BG 3 6 0.1861 0.2722 6.555 10BG 3 8 0.1551 0.2571 6.555 10BG 3 10 0.1250 0.2411 6.555 10BG 3 12 0.1018 0.2281 6.555 10BG 3 14 0.0798 0.2151 6.555 2.5B 3 2 0.2636 0.2983 6.555 2.5B 3 4 0.2183 0.2748 6.555 2.5B 3 6 0.1826 0.2536 6.555 2.5B 3 8 0.1511 0.2331 6.555 2.5B 3 10 0.1220 0.2132 6.555 2.5B 3 12 0.0989 0.1963 6.555 5B 3 2 0.2617 0.2921 6.555 5B 3 4 0.2176 0.2632 6.555 5B 3 6 0.1835 0.2375 6.555 5B 3 8 0.1527 0.2119 6.555 5B 3 10 0.1259 0.1879 6.555 5B 3 12 0.1042 0.1681 6.555 7.5B 3 2 0.2616 0.2857 6.555 7.5B 3 4 0.2200 0.2536 6.555 7.5B 3 6 0.1875 0.2258 6.555 7.5B 3 8 0.1583 0.1987 6.555 7.5B 3 10 0.1343 0.1756 6.555 7.5B 3 12 0.1131 0.1542 6.555 10B 3 2 0.2631 0.2801 6.555 10B 3 4 0.2246 0.2467 6.555 10B 3 6 0.1933 0.2173 6.555 10B 3 8 0.1658 0.1905 6.555 10B 3 10 0.1432 0.1675 6.555 10B 3 12 0.1228 0.1460 6.555 10B 3 14 0.1065 0.1285 6.555 2.5PB 3 2 0.2663 0.2756 6.555 2.5PB 3 4 0.2312 0.2405 6.555 2.5PB 3 6 0.2022 0.2101 6.555 2.5PB 3 8 0.1780 0.1833 6.555 2.5PB 3 10 0.1576 0.1600 6.555 2.5PB 3 12 0.1398 0.1395 6.555 2.5PB 3 14 0.1251 0.1218 6.555 5PB 3 2 0.2708 0.2719 6.555 5PB 3 4 0.2393 0.2361 6.555 5PB 3 6 0.2122 0.2052 6.555 5PB 3 8 0.1908 0.1799 6.555 5PB 3 10 0.1718 0.1562 6.555 5PB 3 12 0.1557 0.1356 6.555 5PB 3 14 0.1431 0.1184 6.555 5PB 3 16 0.1318 0.1024 6.555 5PB 3 18 0.1228 0.0895 6.555 7.5PB 3 2 0.2777 0.2687 6.555 7.5PB 3 4 0.2520 0.2319 6.555 7.5PB 3 6 0.2311 0.2010 6.555 7.5PB 3 8 0.2149 0.1761 6.555 7.5PB 3 10 0.2005 0.1536 6.555 7.5PB 3 12 0.1903 0.1353 6.555 7.5PB 3 14 0.1824 0.1188 6.555 7.5PB 3 16 0.1765 0.1048 6.555 7.5PB 3 18 0.1730 0.0948 6.555 7.5PB 3 20 0.1702 0.0867 6.555 7.5PB 3 22 0.1677 0.0782 6.555 7.5PB 3 24 0.1658 0.0711 6.555 7.5PB 3 26 0.1642 0.0655 6.555 7.5PB 3 28 0.1632 0.0609 6.555 7.5PB 3 30 0.1621 0.0556 6.555 7.5PB 3 32 0.1612 0.0511 6.555 7.5PB 3 34 0.1608 0.0480 6.555 10PB 3 2 0.2847 0.2670 6.555 10PB 3 4 0.2660 0.2319 6.555 10PB 3 6 0.2511 0.2031 6.555 10PB 3 8 0.2387 0.1786 6.555 10PB 3 10 0.2278 0.1565 6.555 10PB 3 12 0.2206 0.1407 6.555 10PB 3 14 0.2142 0.1250 6.555 10PB 3 16 0.2092 0.1118 6.555 10PB 3 18 0.2060 0.1020 6.555 10PB 3 20 0.2030 0.0930 6.555 10PB 3 22 0.2004 0.0847 6.555 10PB 3 24 0.1982 0.0772 6.555 10PB 3 26 0.1963 0.0708 6.555 10PB 3 28 0.1950 0.0650 6.555 10PB 3 30 0.1938 0.0599 6.555 10PB 3 32 0.1926 0.0542 6.555 10PB 3 34 0.1918 0.0503 6.555 2.5P 3 2 0.2922 0.2680 6.555 2.5P 3 4 0.2792 0.2342 6.555 2.5P 3 6 0.2691 0.2072 6.555 2.5P 3 8 0.2615 0.1845 6.555 2.5P 3 10 0.2548 0.1638 6.555 2.5P 3 12 0.2498 0.1480 6.555 2.5P 3 14 0.2449 0.1325 6.555 2.5P 3 16 0.2410 0.1198 6.555 2.5P 3 18 0.2380 0.1094 6.555 2.5P 3 20 0.2354 0.1003 6.555 2.5P 3 22 0.2329 0.0911 6.555 2.5P 3 24 0.2305 0.0832 6.555 2.5P 3 26 0.2286 0.0765 6.555 2.5P 3 28 0.2268 0.0698 6.555 2.5P 3 30 0.2252 0.0638 6.555 2.5P 3 32 0.2242 0.0587 6.555 2.5P 3 34 0.2230 0.0543 6.555 5P 3 2 0.2997 0.2700 6.555 5P 3 4 0.2928 0.2386 6.555 5P 3 6 0.2870 0.2135 6.555 5P 3 8 0.2819 0.1910 6.555 5P 3 10 0.2772 0.1707 6.555 5P 3 12 0.2739 0.1539 6.555 5P 3 14 0.2707 0.1397 6.555 5P 3 16 0.2680 0.1272 6.555 5P 3 18 0.2657 0.1163 6.555 5P 3 20 0.2639 0.1074 6.555 5P 3 22 0.2620 0.0978 6.555 5P 3 24 0.2602 0.0891 6.555 5P 3 26 0.2590 0.0822 6.555 5P 3 28 0.2579 0.0750 6.555 5P 3 30 0.2568 0.0690 6.555 5P 3 32 0.2557 0.0630 6.555 7.5P 3 2 0.3088 0.2740 6.555 7.5P 3 4 0.3072 0.2448 6.555 7.5P 3 6 0.3057 0.2208 6.555 7.5P 3 8 0.3037 0.1981 6.555 7.5P 3 10 0.3020 0.1794 6.555 7.5P 3 12 0.3003 0.1618 6.555 7.5P 3 14 0.2992 0.1475 6.555 7.5P 3 16 0.2981 0.1356 6.555 7.5P 3 18 0.2969 0.1239 6.555 7.5P 3 20 0.2961 0.1151 6.555 7.5P 3 22 0.2953 0.1057 6.555 7.5P 3 24 0.2944 0.0967 6.555 7.5P 3 26 0.2938 0.0892 6.555 7.5P 3 28 0.2930 0.0812 6.555 7.5P 3 30 0.2922 0.0750 6.555 10P 3 2 0.3170 0.2790 6.555 10P 3 4 0.3214 0.2517 6.555 10P 3 6 0.3243 0.2293 6.555 10P 3 8 0.3269 0.2075 6.555 10P 3 10 0.3286 0.1889 6.555 10P 3 12 0.3301 0.1715 6.555 10P 3 14 0.3309 0.1572 6.555 10P 3 16 0.3320 0.1456 6.555 10P 3 18 0.3329 0.1332 6.555 10P 3 20 0.3332 0.1240 6.555 10P 3 22 0.3340 0.1146 6.555 10P 3 24 0.3341 0.1055 6.555 10P 3 26 0.3343 0.0978 6.555 2.5RP 3 2 0.3272 0.2861 6.555 2.5RP 3 4 0.3400 0.2624 6.555 2.5RP 3 6 0.3501 0.2425 6.555 2.5RP 3 8 0.3598 0.2233 6.555 2.5RP 3 10 0.3681 0.2054 6.555 2.5RP 3 12 0.3754 0.1898 6.555 2.5RP 3 14 0.3818 0.1758 6.555 2.5RP 3 16 0.3876 0.1629 6.555 2.5RP 3 18 0.3929 0.1506 6.555 2.5RP 3 20 0.3969 0.1413 6.555 2.5RP 3 22 0.4018 0.1304 6.555 5RP 3 2 0.3370 0.2940 6.555 5RP 3 4 0.3586 0.2742 6.555 5RP 3 6 0.3765 0.2569 6.555 5RP 3 8 0.3930 0.2395 6.555 5RP 3 10 0.4073 0.2235 6.555 5RP 3 12 0.4199 0.2089 6.555 5RP 3 14 0.4313 0.1944 6.555 5RP 3 16 0.4418 0.1809 6.555 5RP 3 18 0.4503 0.1695 6.555 5RP 3 20 0.4577 0.1593 6.555 7.5RP 3 2 0.3450 0.3001 6.555 7.5RP 3 4 0.3739 0.2851 6.555 7.5RP 3 6 0.3990 0.2708 6.555 7.5RP 3 8 0.4234 0.2556 6.555 7.5RP 3 10 0.4445 0.2419 6.555 7.5RP 3 12 0.4654 0.2273 6.555 7.5RP 3 14 0.4831 0.2140 6.555 7.5RP 3 16 0.4991 0.2011 6.555 7.5RP 3 18 0.5130 0.1893 6.555 10RP 4 2 0.3417 0.3106 12.000 10RP 4 4 0.3715 0.3042 12.000 10RP 4 6 0.3999 0.2972 12.000 10RP 4 8 0.4282 0.2890 12.000 10RP 4 10 0.4528 0.2811 12.000 10RP 4 12 0.4789 0.2717 12.000 10RP 4 14 0.5020 0.2623 12.000 10RP 4 16 0.5234 0.2530 12.000 10RP 4 18 0.5466 0.2424 12.000 10RP 4 20 0.5674 0.2319 12.000 2.5R 4 2 0.3461 0.3150 12.000 2.5R 4 4 0.3806 0.3125 12.000 2.5R 4 6 0.4141 0.3085 12.000 2.5R 4 8 0.4472 0.3031 12.000 2.5R 4 10 0.4774 0.2969 12.000 2.5R 4 12 0.5072 0.2897 12.000 2.5R 4 14 0.5369 0.2810 12.000 2.5R 4 16 0.5620 0.2724 12.000 5R 4 2 0.3508 0.3200 12.000 5R 4 4 0.3916 0.3223 12.000 5R 4 6 0.4299 0.3226 12.000 5R 4 8 0.4690 0.3209 12.000 5R 4 10 0.5043 0.3176 12.000 5R 4 12 0.5385 0.3129 12.000 5R 4 14 0.5734 0.3057 12.000 5R 4 16 0.6039 0.2978 12.000 5R 4 18 0.6329 0.2881 12.000 7.5R 4 2 0.3538 0.3236 12.000 7.5R 4 4 0.3990 0.3300 12.000 7.5R 4 6 0.4415 0.3340 12.000 7.5R 4 8 0.4850 0.3359 12.000 7.5R 4 10 0.5235 0.3351 12.000 7.5R 4 12 0.5603 0.3321 12.000 7.5R 4 14 0.5959 0.3269 12.000 7.5R 4 16 0.6260 0.3192 12.000 7.5R 4 18 0.6538 0.3100 12.000 7.5R 4 20 0.6806 0.2988 12.000 10R 4 2 0.3582 0.3294 12.000 10R 4 4 0.4078 0.3412 12.000 10R 4 6 0.4535 0.3500 12.000 10R 4 8 0.4995 0.3557 12.000 10R 4 10 0.5418 0.3580 12.000 10R 4 12 0.5801 0.3588 12.000 10R 4 14 0.6154 0.3568 12.000 10R 4 16 0.6409 0.3533 12.000 2.5YR 4 2 0.3624 0.3367 12.000 2.5YR 4 4 0.4141 0.3539 12.000 2.5YR 4 6 0.4612 0.3674 12.000 2.5YR 4 8 0.5071 0.3777 12.000 2.5YR 4 10 0.5475 0.3856 12.000 2.5YR 4 12 0.5809 0.3910 12.000 5YR 4 2 0.3651 0.3442 12.000 5YR 4 4 0.4187 0.3679 12.000 5YR 4 6 0.4651 0.3859 12.000 5YR 4 8 0.5070 0.3994 12.000 5YR 4 10 0.5432 0.4097 12.000 5YR 4 12 0.5729 0.4169 12.000 7.5YR 4 2 0.3662 0.3504 12.000 7.5YR 4 4 0.4208 0.3809 12.000 7.5YR 4 6 0.4655 0.4029 12.000 7.5YR 4 8 0.5038 0.4204 12.000 7.5YR 4 10 0.5356 0.4342 12.000 10YR 4 2 0.3660 0.3590 12.000 10YR 4 4 0.4189 0.3948 12.000 10YR 4 6 0.4618 0.4213 12.000 10YR 4 8 0.4965 0.4414 12.000 10YR 4 10 0.5250 0.4573 12.000 2.5Y 4 2 0.3633 0.3654 12.000 2.5Y 4 4 0.4138 0.4076 12.000 2.5Y 4 6 0.4542 0.4391 12.000 2.5Y 4 8 0.4865 0.4625 12.000 2.5Y 4 10 0.5120 0.4800 12.000 5Y 4 2 0.3590 0.3701 12.000 5Y 4 4 0.4069 0.4188 12.000 5Y 4 6 0.4451 0.4550 12.000 5Y 4 8 0.4745 0.4810 12.000 7.5Y 4 2 0.3542 0.3727 12.000 7.5Y 4 4 0.3982 0.4272 12.000 7.5Y 4 6 0.4331 0.4688 12.000 7.5Y 4 8 0.4595 0.4990 12.000 10Y 4 2 0.3436 0.3732 12.000 10Y 4 4 0.3871 0.4321 12.000 10Y 4 6 0.4190 0.4795 12.000 10Y 4 8 0.4430 0.5153 12.000 2.5GY 4 2 0.3382 0.3706 12.000 2.5GY 4 4 0.3708 0.4329 12.000 2.5GY 4 6 0.3968 0.4857 12.000 2.5GY 4 8 0.4174 0.5300 12.000 5GY 4 2 0.3312 0.3678 12.000 5GY 4 4 0.3538 0.4284 12.000 5GY 4 6 0.3718 0.4852 12.000 5GY 4 8 0.3868 0.5384 12.000 5GY 4 10 0.3983 0.5850 12.000 7.5GY 4 2 0.3185 0.3604 12.000 7.5GY 4 4 0.3281 0.4157 12.000 7.5GY 4 6 0.3355 0.4739 12.000 7.5GY 4 8 0.3400 0.5348 12.000 7.5GY 4 10 0.3395 0.5913 12.000 7.5GY 4 12 0.3348 0.6468 12.000 10GY 4 2 0.3109 0.3550 12.000 10GY 4 4 0.3100 0.4018 12.000 10GY 4 6 0.3069 0.4550 12.000 10GY 4 8 0.3008 0.5095 12.000 10GY 4 10 0.2908 0.5672 12.000 10GY 4 12 0.2758 0.6282 12.000 10GY 4 14 0.2590 0.6858 12.000 10GY 4 16 0.2422 0.7360 12.000 2.5G 4 2 0.3012 0.3470 12.000 2.5G 4 4 0.2891 0.3821 12.000 2.5G 4 6 0.2735 0.4215 12.000 2.5G 4 8 0.2561 0.4597 12.000 2.5G 4 10 0.2355 0.5006 12.000 2.5G 4 12 0.2128 0.5425 12.000 2.5G 4 14 0.1909 0.5779 12.000 2.5G 4 16 0.1682 0.6111 12.000 2.5G 4 18 0.1446 0.6431 12.000 2.5G 4 20 0.1230 0.6706 12.000 2.5G 4 22 0.1009 0.6975 12.000 2.5G 4 24 0.0760 0.7250 12.000 2.5G 4 26 0.0528 0.7502 12.000 5G 4 2 0.2959 0.3417 12.000 5G 4 4 0.2781 0.3704 12.000 5G 4 6 0.2581 0.3992 12.000 5G 4 8 0.2359 0.4266 12.000 5G 4 10 0.2115 0.4532 12.000 5G 4 12 0.1843 0.4807 12.000 5G 4 14 0.1627 0.5015 12.000 5G 4 16 0.1402 0.5214 12.000 5G 4 18 0.1188 0.5400 12.000 5G 4 20 0.1018 0.5543 12.000 5G 4 22 0.0841 0.5684 12.000 5G 4 24 0.0614 0.5857 12.000 5G 4 26 0.0407 0.6010 12.000 7.5G 4 2 0.2919 0.3371 12.000 7.5G 4 4 0.2702 0.3602 12.000 7.5G 4 6 0.2467 0.3822 12.000 7.5G 4 8 0.2232 0.4022 12.000 7.5G 4 10 0.1989 0.4219 12.000 7.5G 4 12 0.1706 0.4419 12.000 7.5G 4 14 0.1500 0.4562 12.000 7.5G 4 16 0.1293 0.4703 12.000 7.5G 4 18 0.1086 0.4842 12.000 7.5G 4 20 0.0928 0.4942 12.000 7.5G 4 22 0.0770 0.5040 12.000 7.5G 4 24 0.0581 0.5151 12.000 7.5G 4 26 0.0392 0.5258 12.000 10G 4 2 0.2880 0.3327 12.000 10G 4 4 0.2628 0.3498 12.000 10G 4 6 0.2374 0.3655 12.000 10G 4 8 0.2124 0.3799 12.000 10G 4 10 0.1876 0.3933 12.000 10G 4 12 0.1602 0.4070 12.000 10G 4 14 0.1398 0.4168 12.000 10G 4 16 0.1212 0.4245 12.000 10G 4 18 0.1006 0.4330 12.000 10G 4 20 0.0850 0.4388 12.000 10G 4 22 0.0702 0.4440 12.000 10G 4 24 0.0553 0.4492 12.000 10G 4 26 0.0400 0.4545 12.000 2.5BG 4 2 0.2840 0.3270 12.000 2.5BG 4 4 0.2552 0.3375 12.000 2.5BG 4 6 0.2278 0.3463 12.000 2.5BG 4 8 0.2006 0.3540 12.000 2.5BG 4 10 0.1738 0.3600 12.000 2.5BG 4 12 0.1492 0.3649 12.000 2.5BG 4 14 0.1283 0.3688 12.000 2.5BG 4 16 0.1102 0.3720 12.000 2.5BG 4 18 0.0915 0.3754 12.000 2.5BG 4 20 0.0768 0.3773 12.000 2.5BG 4 22 0.0636 0.3788 12.000 2.5BG 4 24 0.0510 0.3800 12.000 5BG 4 2 0.2799 0.3208 12.000 5BG 4 4 0.2480 0.3232 12.000 5BG 4 6 0.2182 0.3240 12.000 5BG 4 8 0.1890 0.3234 12.000 5BG 4 10 0.1618 0.3219 12.000 5BG 4 12 0.1379 0.3198 12.000 5BG 4 14 0.1170 0.3170 12.000 5BG 4 16 0.0992 0.3141 12.000 5BG 4 18 0.0828 0.3108 12.000 5BG 4 20 0.0675 0.3075 12.000 7.5BG 4 2 0.2764 0.3148 12.000 7.5BG 4 4 0.2429 0.3108 12.000 7.5BG 4 6 0.2113 0.3052 12.000 7.5BG 4 8 0.1815 0.2985 12.000 7.5BG 4 10 0.1540 0.2910 12.000 7.5BG 4 12 0.1298 0.2840 12.000 7.5BG 4 14 0.1092 0.2774 12.000 7.5BG 4 16 0.0922 0.2718 12.000 7.5BG 4 18 0.0768 0.2667 12.000 10BG 4 2 0.2740 0.3091 12.000 10BG 4 4 0.2384 0.2984 12.000 10BG 4 6 0.2065 0.2863 12.000 10BG 4 8 0.1760 0.2730 12.000 10BG 4 10 0.1480 0.2600 12.000 10BG 4 12 0.1248 0.2484 12.000 10BG 4 14 0.1033 0.2376 12.000 10BG 4 16 0.0888 0.2298 12.000 2.5B 4 2 0.2727 0.3038 12.000 2.5B 4 4 0.2360 0.2872 12.000 2.5B 4 6 0.2048 0.2708 12.000 2.5B 4 8 0.1737 0.2524 12.000 2.5B 4 10 0.1463 0.2354 12.000 2.5B 4 12 0.1247 0.2209 12.000 2.5B 4 14 0.1027 0.2057 12.000 2.5B 4 16 0.0900 0.1973 12.000 5B 4 2 0.2723 0.2992 12.000 5B 4 4 0.2363 0.2782 12.000 5B 4 6 0.2060 0.2572 12.000 5B 4 8 0.1759 0.2345 12.000 5B 4 10 0.1512 0.2148 12.000 5B 4 12 0.1299 0.1963 12.000 5B 4 14 0.1098 0.1785 12.000 7.5B 4 2 0.2733 0.2947 12.000 7.5B 4 4 0.2388 0.2704 12.000 7.5B 4 6 0.2102 0.2470 12.000 7.5B 4 8 0.1821 0.2232 12.000 7.5B 4 10 0.1601 0.2028 12.000 7.5B 4 12 0.1393 0.1837 12.000 7.5B 4 14 0.1204 0.1655 12.000 10B 4 2 0.2753 0.2910 12.000 10B 4 4 0.2429 0.2648 12.000 10B 4 6 0.2157 0.2407 12.000 10B 4 8 0.1893 0.2160 12.000 10B 4 10 0.1681 0.1954 12.000 10B 4 12 0.1487 0.1760 12.000 10B 4 14 0.1310 0.1580 12.000 10B 4 16 0.1155 0.1416 12.000 2.5PB 4 2 0.2782 0.2876 12.000 2.5PB 4 4 0.2487 0.2597 12.000 2.5PB 4 6 0.2235 0.2343 12.000 2.5PB 4 8 0.1995 0.2094 12.000 2.5PB 4 10 0.1805 0.1888 12.000 2.5PB 4 12 0.1634 0.1698 12.000 2.5PB 4 14 0.1473 0.1513 12.000 2.5PB 4 16 0.1336 0.1349 12.000 2.5PB 4 18 0.1218 0.1208 12.000 5PB 4 2 0.2816 0.2842 12.000 5PB 4 4 0.2562 0.2560 12.000 5PB 4 6 0.2325 0.2300 12.000 5PB 4 8 0.2103 0.2050 12.000 5PB 4 10 0.1925 0.1843 12.000 5PB 4 12 0.1773 0.1659 12.000 5PB 4 14 0.1627 0.1479 12.000 5PB 4 16 0.1504 0.1317 12.000 5PB 4 18 0.1392 0.1167 12.000 5PB 4 20 0.1288 0.1027 12.000 7.5PB 4 2 0.2861 0.2819 12.000 7.5PB 4 4 0.2657 0.2528 12.000 7.5PB 4 6 0.2471 0.2266 12.000 7.5PB 4 8 0.2304 0.2023 12.000 7.5PB 4 10 0.2158 0.1811 12.000 7.5PB 4 12 0.2037 0.1629 12.000 7.5PB 4 14 0.1941 0.1468 12.000 7.5PB 4 16 0.1861 0.1316 12.000 7.5PB 4 18 0.1798 0.1185 12.000 7.5PB 4 20 0.1742 0.1058 12.000 7.5PB 4 22 0.1713 0.0980 12.000 7.5PB 4 24 0.1684 0.0899 12.000 7.5PB 4 26 0.1659 0.0825 12.000 10PB 4 2 0.2911 0.2804 12.000 10PB 4 4 0.2759 0.2522 12.000 10PB 4 6 0.2618 0.2263 12.000 10PB 4 8 0.2497 0.2038 12.000 10PB 4 10 0.2388 0.1837 12.000 10PB 4 12 0.2298 0.1659 12.000 10PB 4 14 0.2220 0.1503 12.000 10PB 4 16 0.2170 0.1373 12.000 10PB 4 18 0.2120 0.1256 12.000 10PB 4 20 0.2075 0.1140 12.000 10PB 4 22 0.2048 0.1064 12.000 10PB 4 24 0.2020 0.0985 12.000 10PB 4 26 0.1994 0.0904 12.000 10PB 4 28 0.1971 0.0840 12.000 10PB 4 30 0.1952 0.0778 12.000 2.5P 4 2 0.2962 0.2807 12.000 2.5P 4 4 0.2855 0.2531 12.000 2.5P 4 6 0.2763 0.2300 12.000 2.5P 4 8 0.2685 0.2089 12.000 2.5P 4 10 0.2619 0.1903 12.000 2.5P 4 12 0.2559 0.1730 12.000 2.5P 4 14 0.2509 0.1585 12.000 2.5P 4 16 0.2467 0.1452 12.000 2.5P 4 18 0.2430 0.1332 12.000 2.5P 4 20 0.2394 0.1221 12.000 2.5P 4 22 0.2371 0.1143 12.000 2.5P 4 24 0.2348 0.1062 12.000 2.5P 4 26 0.2322 0.0978 12.000 2.5P 4 28 0.2302 0.0909 12.000 2.5P 4 30 0.2285 0.0847 12.000 2.5P 4 32 0.2265 0.0774 12.000 5P 4 2 0.3022 0.2825 12.000 5P 4 4 0.2958 0.2565 12.000 5P 4 6 0.2903 0.2347 12.000 5P 4 8 0.2855 0.2150 12.000 5P 4 10 0.2814 0.1967 12.000 5P 4 12 0.2778 0.1808 12.000 5P 4 14 0.2747 0.1660 12.000 5P 4 16 0.2718 0.1520 12.000 5P 4 18 0.2693 0.1408 12.000 5P 4 20 0.2670 0.1300 12.000 5P 4 22 0.2652 0.1218 12.000 5P 4 24 0.2635 0.1132 12.000 5P 4 26 0.2618 0.1052 12.000 5P 4 28 0.2600 0.0971 12.000 5P 4 30 0.2588 0.0907 12.000 5P 4 32 0.2574 0.0833 12.000 7.5P 4 2 0.3093 0.2859 12.000 7.5P 4 4 0.3084 0.2622 12.000 7.5P 4 6 0.3076 0.2416 12.000 7.5P 4 8 0.3066 0.2228 12.000 7.5P 4 10 0.3056 0.2060 12.000 7.5P 4 12 0.3045 0.1905 12.000 7.5P 4 14 0.3035 0.1755 12.000 7.5P 4 16 0.3028 0.1621 12.000 7.5P 4 18 0.3016 0.1500 12.000 7.5P 4 20 0.3010 0.1396 12.000 7.5P 4 22 0.3001 0.1306 12.000 7.5P 4 24 0.2993 0.1225 12.000 7.5P 4 26 0.2986 0.1135 12.000 7.5P 4 28 0.2979 0.1062 12.000 7.5P 4 30 0.2969 0.0979 12.000 7.5P 4 32 0.2962 0.0906 12.000 10P 4 2 0.3162 0.2902 12.000 10P 4 4 0.3210 0.2686 12.000 10P 4 6 0.3248 0.2493 12.000 10P 4 8 0.3280 0.2318 12.000 10P 4 10 0.3306 0.2162 12.000 10P 4 12 0.3331 0.2014 12.000 10P 4 14 0.3351 0.1875 12.000 10P 4 16 0.3370 0.1756 12.000 10P 4 18 0.3386 0.1626 12.000 10P 4 20 0.3400 0.1500 12.000 10P 4 22 0.3411 0.1424 12.000 10P 4 24 0.3421 0.1337 12.000 10P 4 26 0.3428 0.1248 12.000 10P 4 28 0.3432 0.1172 12.000 10P 4 30 0.3440 0.1080 12.000 2.5RP 4 2 0.3231 0.2951 12.000 2.5RP 4 4 0.3340 0.2770 12.000 2.5RP 4 6 0.3442 0.2595 12.000 2.5RP 4 8 0.3533 0.2438 12.000 2.5RP 4 10 0.3608 0.2301 12.000 2.5RP 4 12 0.3683 0.2162 12.000 2.5RP 4 14 0.3748 0.2039 12.000 2.5RP 4 16 0.3807 0.1923 12.000 2.5RP 4 18 0.3865 0.1802 12.000 2.5RP 4 20 0.3926 0.1679 12.000 2.5RP 4 22 0.3967 0.1593 12.000 2.5RP 4 24 0.4011 0.1504 12.000 2.5RP 4 26 0.4048 0.1428 12.000 5RP 4 2 0.3310 0.3010 12.000 5RP 4 4 0.3491 0.2872 12.000 5RP 4 6 0.3671 0.2733 12.000 5RP 4 8 0.3833 0.2600 12.000 5RP 4 10 0.3960 0.2489 12.000 5RP 4 12 0.4104 0.2361 12.000 5RP 4 14 0.4225 0.2249 12.000 5RP 4 16 0.4339 0.2139 12.000 5RP 4 18 0.4455 0.2023 12.000 5RP 4 20 0.4571 0.1906 12.000 5RP 4 22 0.4656 0.1821 12.000 7.5RP 4 2 0.3371 0.3061 12.000 7.5RP 4 4 0.3612 0.2963 12.000 7.5RP 4 6 0.3850 0.2859 12.000 7.5RP 4 8 0.4072 0.2750 12.000 7.5RP 4 10 0.4259 0.2651 12.000 7.5RP 4 12 0.4450 0.2541 12.000 7.5RP 4 14 0.4629 0.2437 12.000 7.5RP 4 16 0.4799 0.2329 12.000 7.5RP 4 18 0.4965 0.2217 12.000 7.5RP 4 20 0.5130 0.2101 12.000 10RP 5 2 0.3332 0.3131 19.770 10RP 5 4 0.3594 0.3090 19.770 10RP 5 6 0.3851 0.3039 19.770 10RP 5 8 0.4105 0.2980 19.770 10RP 5 10 0.4332 0.2918 19.770 10RP 5 12 0.4579 0.2841 19.770 10RP 5 14 0.4767 0.2776 19.770 10RP 5 16 0.4986 0.2695 19.770 10RP 5 18 0.5185 0.2620 19.770 10RP 5 20 0.5396 0.2535 19.770 2.5R 5 2 0.3360 0.3158 19.770 2.5R 5 4 0.3660 0.3148 19.770 2.5R 5 6 0.3960 0.3130 19.770 2.5R 5 8 0.4252 0.3101 19.770 2.5R 5 10 0.4533 0.3058 19.770 2.5R 5 12 0.4820 0.3002 19.770 2.5R 5 14 0.5047 0.2950 19.770 2.5R 5 16 0.5300 0.2880 19.770 2.5R 5 18 0.5540 0.2804 19.770 2.5R 5 20 0.5784 0.2719 19.770 5R 5 2 0.3392 0.3192 19.770 5R 5 4 0.3740 0.3220 19.770 5R 5 6 0.4078 0.3238 19.770 5R 5 8 0.4413 0.3240 19.770 5R 5 10 0.4747 0.3227 19.770 5R 5 12 0.5071 0.3194 19.770 5R 5 14 0.5341 0.3158 19.770 5R 5 16 0.5637 0.3102 19.770 5R 5 18 0.5918 0.3038 19.770 5R 5 20 0.6142 0.2970 19.770 7.5R 5 2 0.3425 0.3229 19.770 7.5R 5 4 0.3806 0.3294 19.770 7.5R 5 6 0.4180 0.3348 19.770 7.5R 5 8 0.4563 0.3387 19.770 7.5R 5 10 0.4927 0.3399 19.770 7.5R 5 12 0.5280 0.3389 19.770 7.5R 5 14 0.5590 0.3370 19.770 7.5R 5 16 0.5901 0.3331 19.770 7.5R 5 18 0.6161 0.3277 19.770 7.5R 5 20 0.6388 0.3216 19.770 10R 5 2 0.3465 0.3278 19.770 10R 5 4 0.3879 0.3398 19.770 10R 5 6 0.4299 0.3499 19.770 10R 5 8 0.4713 0.3575 19.770 10R 5 10 0.5113 0.3630 19.770 10R 5 12 0.5481 0.3660 19.770 10R 5 14 0.5771 0.3664 19.770 10R 5 16 0.6037 0.3657 19.770 10R 5 18 0.6297 0.3642 19.770 2.5YR 5 2 0.3506 0.3337 19.770 2.5YR 5 4 0.3925 0.3494 19.770 2.5YR 5 6 0.4365 0.3640 19.770 2.5YR 5 8 0.4795 0.3758 19.770 2.5YR 5 10 0.5175 0.3844 19.770 2.5YR 5 12 0.5482 0.3909 19.770 2.5YR 5 14 0.5731 0.3953 19.770 2.5YR 5 16 0.5933 0.3989 19.770 5YR 5 2 0.3530 0.3395 19.770 5YR 5 4 0.3968 0.3614 19.770 5YR 5 6 0.4420 0.3808 19.770 5YR 5 8 0.4830 0.3960 19.770 5YR 5 10 0.5161 0.4064 19.770 5YR 5 12 0.5422 0.4141 19.770 5YR 5 14 0.5642 0.4201 19.770 7.5YR 5 2 0.3540 0.3445 19.770 7.5YR 5 4 0.3991 0.3714 19.770 7.5YR 5 6 0.4440 0.3954 19.770 7.5YR 5 8 0.4820 0.4141 19.770 7.5YR 5 10 0.5108 0.4276 19.770 7.5YR 5 12 0.5335 0.4378 19.770 7.5YR 5 14 0.5506 0.4450 19.770 10YR 5 2 0.3546 0.3514 19.770 10YR 5 4 0.3995 0.3840 19.770 10YR 5 6 0.4428 0.4128 19.770 10YR 5 8 0.4770 0.4338 19.770 10YR 5 10 0.5025 0.4489 19.770 10YR 5 12 0.5211 0.4600 19.770 2.5Y 5 2 0.3534 0.3570 19.770 2.5Y 5 4 0.3968 0.3954 19.770 2.5Y 5 6 0.4380 0.4292 19.770 2.5Y 5 8 0.4685 0.4524 19.770 2.5Y 5 10 0.4905 0.4683 19.770 2.5Y 5 12 0.5082 0.4812 19.770 5Y 5 2 0.3500 0.3620 19.770 5Y 5 4 0.3915 0.4057 19.770 5Y 5 6 0.4302 0.4435 19.770 5Y 5 8 0.4579 0.4692 19.770 5Y 5 10 0.4777 0.4876 19.770 5Y 5 12 0.4932 0.5019 19.770 7.5Y 5 2 0.3470 0.3640 19.770 7.5Y 5 4 0.3850 0.4120 19.770 7.5Y 5 6 0.4199 0.4551 19.770 7.5Y 5 8 0.4450 0.4850 19.770 7.5Y 5 10 0.4632 0.5057 19.770 7.5Y 5 12 0.4767 0.5208 19.770 10Y 5 2 0.3422 0.3648 19.770 10Y 5 4 0.3762 0.4158 19.770 10Y 5 6 0.4072 0.4621 19.770 10Y 5 8 0.4307 0.4967 19.770 10Y 5 10 0.4468 0.5209 19.770 10Y 5 12 0.4590 0.5390 19.770 2.5GY 5 2 0.3352 0.3636 19.770 2.5GY 5 4 0.3621 0.4143 19.770 2.5GY 5 6 0.3879 0.4646 19.770 2.5GY 5 8 0.4088 0.5068 19.770 2.5GY 5 10 0.4224 0.5369 19.770 2.5GY 5 12 0.4333 0.5602 19.770 5GY 5 2 0.3289 0.3612 19.770 5GY 5 4 0.3482 0.4097 19.770 5GY 5 6 0.3663 0.4614 19.770 5GY 5 8 0.3815 0.5093 19.770 5GY 5 10 0.3928 0.5485 19.770 5GY 5 12 0.4011 0.5802 19.770 7.5GY 5 2 0.3188 0.3560 19.770 7.5GY 5 4 0.3274 0.3994 19.770 7.5GY 5 6 0.3354 0.4483 19.770 7.5GY 5 8 0.3412 0.4976 19.770 7.5GY 5 10 0.3451 0.5490 19.770 7.5GY 5 12 0.3450 0.5949 19.770 7.5GY 5 14 0.3429 0.6335 19.770 10GY 5 2 0.3110 0.3508 19.770 10GY 5 4 0.3111 0.3881 19.770 10GY 5 6 0.3108 0.4301 19.770 10GY 5 8 0.3080 0.4759 19.770 10GY 5 10 0.3028 0.5237 19.770 10GY 5 12 0.2940 0.5751 19.770 10GY 5 14 0.2838 0.6208 19.770 10GY 5 16 0.2702 0.6700 19.770 10GY 5 18 0.2549 0.7179 19.770 2.5G 5 2 0.3030 0.3445 19.770 2.5G 5 4 0.2943 0.3735 19.770 2.5G 5 6 0.2841 0.4045 19.770 2.5G 5 8 0.2710 0.4380 19.770 2.5G 5 10 0.2565 0.4705 19.770 2.5G 5 12 0.2385 0.5071 19.770 2.5G 5 14 0.2211 0.5411 19.770 2.5G 5 16 0.2005 0.5759 19.770 2.5G 5 18 0.1782 0.6095 19.770 2.5G 5 20 0.1579 0.6392 19.770 2.5G 5 22 0.1377 0.6674 19.770 2.5G 5 24 0.1188 0.6918 19.770 2.5G 5 26 0.0992 0.7155 19.770 2.5G 5 28 0.0794 0.7385 19.770 5G 5 2 0.2978 0.3392 19.770 5G 5 4 0.2841 0.3628 19.770 5G 5 6 0.2690 0.3860 19.770 5G 5 8 0.2511 0.4107 19.770 5G 5 10 0.2329 0.4331 19.770 5G 5 12 0.2104 0.4578 19.770 5G 5 14 0.1912 0.4773 19.770 5G 5 16 0.1695 0.4981 19.770 5G 5 18 0.1489 0.5171 19.770 5G 5 20 0.1318 0.5321 19.770 5G 5 22 0.1144 0.5463 19.770 5G 5 24 0.0953 0.5628 19.770 5G 5 26 0.0784 0.5761 19.770 5G 5 28 0.0609 0.5898 19.770 7.5G 5 2 0.2945 0.3355 19.770 7.5G 5 4 0.2775 0.3545 19.770 7.5G 5 6 0.2598 0.3724 19.770 7.5G 5 8 0.2395 0.3915 19.770 7.5G 5 10 0.2200 0.4082 19.770 7.5G 5 12 0.1964 0.4271 19.770 7.5G 5 14 0.1776 0.4415 19.770 7.5G 5 16 0.1571 0.4561 19.770 7.5G 5 18 0.1372 0.4705 19.770 7.5G 5 20 0.1212 0.4817 19.770 7.5G 5 22 0.1050 0.4927 19.770 7.5G 5 24 0.0878 0.5039 19.770 7.5G 5 26 0.0730 0.5131 19.770 7.5G 5 28 0.0585 0.5224 19.770 10G 5 2 0.2910 0.3310 19.770 10G 5 4 0.2711 0.3455 19.770 10G 5 6 0.2519 0.3587 19.770 10G 5 8 0.2297 0.3730 19.770 10G 5 10 0.2095 0.3853 19.770 10G 5 12 0.1852 0.3992 19.770 10G 5 14 0.1671 0.4089 19.770 10G 5 16 0.1469 0.4192 19.770 10G 5 18 0.1275 0.4288 19.770 10G 5 20 0.1120 0.4360 19.770 10G 5 22 0.0958 0.4428 19.770 10G 5 24 0.0811 0.4491 19.770 10G 5 26 0.0690 0.4542 19.770 10G 5 28 0.0572 0.4590 19.770 2.5BG 5 2 0.2880 0.3270 19.770 2.5BG 5 4 0.2659 0.3369 19.770 2.5BG 5 6 0.2448 0.3452 19.770 2.5BG 5 8 0.2205 0.3537 19.770 2.5BG 5 10 0.1980 0.3606 19.770 2.5BG 5 12 0.1735 0.3668 19.770 2.5BG 5 14 0.1559 0.3708 19.770 2.5BG 5 16 0.1348 0.3750 19.770 2.5BG 5 18 0.1165 0.3785 19.770 2.5BG 5 20 0.1005 0.3814 19.770 2.5BG 5 22 0.0861 0.3832 19.770 2.5BG 5 24 0.0738 0.3851 19.770 5BG 5 2 0.2841 0.3210 19.770 5BG 5 4 0.2591 0.3246 19.770 5BG 5 6 0.2360 0.3270 19.770 5BG 5 8 0.2100 0.3280 19.770 5BG 5 10 0.1850 0.3280 19.770 5BG 5 12 0.1614 0.3280 19.770 5BG 5 14 0.1448 0.3275 19.770 5BG 5 16 0.1243 0.3261 19.770 5BG 5 18 0.1046 0.3244 19.770 5BG 5 20 0.0904 0.3231 19.770 5BG 5 22 0.0781 0.3211 19.770 7.5BG 5 2 0.2812 0.3161 19.770 7.5BG 5 4 0.2550 0.3150 19.770 7.5BG 5 6 0.2292 0.3125 19.770 7.5BG 5 8 0.2030 0.3082 19.770 7.5BG 5 10 0.1776 0.3032 19.770 7.5BG 5 12 0.1537 0.2976 19.770 7.5BG 5 14 0.1364 0.2932 19.770 7.5BG 5 16 0.1167 0.2880 19.770 7.5BG 5 18 0.0982 0.2828 19.770 10BG 5 2 0.2796 0.3111 19.770 10BG 5 4 0.2512 0.3040 19.770 10BG 5 6 0.2234 0.2952 19.770 10BG 5 8 0.1970 0.2860 19.770 10BG 5 10 0.1716 0.2760 19.770 10BG 5 12 0.1485 0.2662 19.770 10BG 5 14 0.1308 0.2582 19.770 10BG 5 16 0.1108 0.2489 19.770 2.5B 5 2 0.2791 0.3071 19.770 2.5B 5 4 0.2492 0.2954 19.770 2.5B 5 6 0.2210 0.2823 19.770 2.5B 5 8 0.1947 0.2687 19.770 2.5B 5 10 0.1697 0.2549 19.770 2.5B 5 12 0.1461 0.2406 19.770 2.5B 5 14 0.1283 0.2292 19.770 2.5B 5 16 0.1090 0.2166 19.770 5B 5 2 0.2794 0.3032 19.770 5B 5 4 0.2493 0.2879 19.770 5B 5 6 0.2215 0.2701 19.770 5B 5 8 0.1958 0.2519 19.770 5B 5 10 0.1729 0.2347 19.770 5B 5 12 0.1505 0.2172 19.770 5B 5 14 0.1320 0.2021 19.770 5B 5 16 0.1132 0.1863 19.770 7.5B 5 2 0.2803 0.3000 19.770 7.5B 5 4 0.2511 0.2808 19.770 7.5B 5 6 0.2248 0.2612 19.770 7.5B 5 8 0.2007 0.2417 19.770 7.5B 5 10 0.1792 0.2230 19.770 7.5B 5 12 0.1584 0.2042 19.770 7.5B 5 14 0.1404 0.1878 19.770 7.5B 5 16 0.1230 0.1711 19.770 10B 5 2 0.2821 0.2966 19.770 10B 5 4 0.2547 0.2757 19.770 10B 5 6 0.2299 0.2548 19.770 10B 5 8 0.2067 0.2344 19.770 10B 5 10 0.1860 0.2149 19.770 10B 5 12 0.1666 0.1964 19.770 10B 5 14 0.1492 0.1797 19.770 10B 5 16 0.1326 0.1632 19.770 10B 5 18 0.1203 0.1505 19.770 2.5PB 5 2 0.2847 0.2942 19.770 2.5PB 5 4 0.2600 0.2720 19.770 2.5PB 5 6 0.2365 0.2488 19.770 2.5PB 5 8 0.2157 0.2278 19.770 2.5PB 5 10 0.1968 0.2078 19.770 2.5PB 5 12 0.1793 0.1894 19.770 2.5PB 5 14 0.1642 0.1728 19.770 2.5PB 5 16 0.1495 0.1559 19.770 2.5PB 5 18 0.1363 0.1410 19.770 5PB 5 2 0.2882 0.2923 19.770 5PB 5 4 0.2662 0.2687 19.770 5PB 5 6 0.2447 0.2449 19.770 5PB 5 8 0.2255 0.2239 19.770 5PB 5 10 0.2080 0.2041 19.770 5PB 5 12 0.1918 0.1858 19.770 5PB 5 14 0.1773 0.1689 19.770 5PB 5 16 0.1638 0.1521 19.770 5PB 5 18 0.1518 0.1365 19.770 7.5PB 5 2 0.2918 0.2908 19.770 7.5PB 5 4 0.2739 0.2666 19.770 7.5PB 5 6 0.2563 0.2417 19.770 7.5PB 5 8 0.2417 0.2204 19.770 7.5PB 5 10 0.2285 0.2020 19.770 7.5PB 5 12 0.2157 0.1830 19.770 7.5PB 5 14 0.2042 0.1661 19.770 7.5PB 5 16 0.1945 0.1511 19.770 7.5PB 5 18 0.1862 0.1365 19.770 7.5PB 5 20 0.1794 0.1239 19.770 10PB 5 2 0.2959 0.2905 19.770 10PB 5 4 0.2821 0.2659 19.770 10PB 5 6 0.2686 0.2412 19.770 10PB 5 8 0.2572 0.2211 19.770 10PB 5 10 0.2478 0.2030 19.770 10PB 5 12 0.2384 0.1857 19.770 10PB 5 14 0.2299 0.1698 19.770 10PB 5 16 0.2224 0.1555 19.770 10PB 5 18 0.2174 0.1444 19.770 10PB 5 20 0.2121 0.1329 19.770 10PB 5 22 0.2082 0.1225 19.770 2.5P 5 2 0.3000 0.2912 19.770 2.5P 5 4 0.2898 0.2667 19.770 2.5P 5 6 0.2806 0.2444 19.770 2.5P 5 8 0.2728 0.2240 19.770 2.5P 5 10 0.2665 0.2075 19.770 2.5P 5 12 0.2608 0.1913 19.770 2.5P 5 14 0.2560 0.1774 19.770 2.5P 5 16 0.2515 0.1644 19.770 2.5P 5 18 0.2476 0.1532 19.770 2.5P 5 20 0.2438 0.1419 19.770 2.5P 5 22 0.2402 0.1315 19.770 2.5P 5 24 0.2372 0.1223 19.770 2.5P 5 26 0.2348 0.1140 19.770 5P 5 2 0.3045 0.2928 19.770 5P 5 4 0.2986 0.2699 19.770 5P 5 6 0.2932 0.2487 19.770 5P 5 8 0.2885 0.2296 19.770 5P 5 10 0.2845 0.2137 19.770 5P 5 12 0.2806 0.1977 19.770 5P 5 14 0.2775 0.1847 19.770 5P 5 16 0.2744 0.1718 19.770 5P 5 18 0.2718 0.1604 19.770 5P 5 20 0.2694 0.1499 19.770 5P 5 22 0.2673 0.1398 19.770 5P 5 24 0.2652 0.1304 19.770 5P 5 26 0.2635 0.1224 19.770 5P 5 28 0.2618 0.1135 19.770 7.5P 5 2 0.3103 0.2959 19.770 7.5P 5 4 0.3100 0.2750 19.770 7.5P 5 6 0.3093 0.2555 19.770 7.5P 5 8 0.3087 0.2375 19.770 7.5P 5 10 0.3080 0.2230 19.770 7.5P 5 12 0.3071 0.2080 19.770 7.5P 5 14 0.3068 0.1951 19.770 7.5P 5 16 0.3060 0.1830 19.770 7.5P 5 18 0.3052 0.1711 19.770 7.5P 5 20 0.3042 0.1606 19.770 7.5P 5 22 0.3038 0.1500 19.770 7.5P 5 24 0.3030 0.1423 19.770 7.5P 5 26 0.3022 0.1331 19.770 7.5P 5 28 0.3018 0.1253 19.770 7.5P 5 30 0.3010 0.1170 19.770 10P 5 2 0.3148 0.2986 19.770 10P 5 4 0.3198 0.2807 19.770 10P 5 6 0.3243 0.2630 19.770 10P 5 8 0.3280 0.2464 19.770 10P 5 10 0.3308 0.2328 19.770 10P 5 12 0.3335 0.2187 19.770 10P 5 14 0.3360 0.2066 19.770 10P 5 16 0.3382 0.1951 19.770 10P 5 18 0.3401 0.1840 19.770 10P 5 20 0.3422 0.1735 19.770 10P 5 22 0.3437 0.1644 19.770 10P 5 24 0.3450 0.1555 19.770 10P 5 26 0.3468 0.1460 19.770 10P 5 28 0.3478 0.1388 19.770 10P 5 30 0.3490 0.1308 19.770 2.5RP 5 2 0.3199 0.3019 19.770 2.5RP 5 4 0.3298 0.2869 19.770 2.5RP 5 6 0.3396 0.2718 19.770 2.5RP 5 8 0.3490 0.2570 19.770 2.5RP 5 10 0.3560 0.2452 19.770 2.5RP 5 12 0.3635 0.2325 19.770 2.5RP 5 14 0.3703 0.2211 19.770 2.5RP 5 16 0.3763 0.2108 19.770 2.5RP 5 18 0.3821 0.2007 19.770 2.5RP 5 20 0.3873 0.1909 19.770 2.5RP 5 22 0.3924 0.1814 19.770 2.5RP 5 24 0.3965 0.1738 19.770 2.5RP 5 26 0.4011 0.1652 19.770 5RP 5 2 0.3256 0.3065 19.770 5RP 5 4 0.3421 0.2954 19.770 5RP 5 6 0.3585 0.2842 19.770 5RP 5 8 0.3748 0.2729 19.770 5RP 5 10 0.3880 0.2630 19.770 5RP 5 12 0.4022 0.2523 19.770 5RP 5 14 0.4142 0.2428 19.770 5RP 5 16 0.4261 0.2331 19.770 5RP 5 18 0.4372 0.2242 19.770 5RP 5 20 0.4484 0.2150 19.770 5RP 5 22 0.4581 0.2068 19.770 5RP 5 24 0.4683 0.1978 19.770 7.5RP 5 2 0.3296 0.3098 19.770 7.5RP 5 4 0.3515 0.3024 19.770 7.5RP 5 6 0.3726 0.2941 19.770 7.5RP 5 8 0.3932 0.2852 19.770 7.5RP 5 10 0.4108 0.2773 19.770 7.5RP 5 12 0.4303 0.2675 19.770 7.5RP 5 14 0.4454 0.2596 19.770 7.5RP 5 16 0.4617 0.2506 19.770 7.5RP 5 18 0.4761 0.2421 19.770 7.5RP 5 20 0.4915 0.2330 19.770 7.5RP 5 22 0.5045 0.2248 19.770 10RP 6 2 0.3292 0.3141 30.050 10RP 6 4 0.3508 0.3112 30.050 10RP 6 6 0.3740 0.3074 30.050 10RP 6 8 0.3930 0.3038 30.050 10RP 6 10 0.4150 0.2989 30.050 10RP 6 12 0.4360 0.2936 30.050 10RP 6 14 0.4552 0.2881 30.050 10RP 6 16 0.4781 0.2812 30.050 10RP 6 18 0.4961 0.2751 30.050 2.5R 6 2 0.3318 0.3166 30.050 2.5R 6 4 0.3566 0.3163 30.050 2.5R 6 6 0.3832 0.3158 30.050 2.5R 6 8 0.4065 0.3144 30.050 2.5R 6 10 0.4320 0.3118 30.050 2.5R 6 12 0.4568 0.3082 30.050 2.5R 6 14 0.4790 0.3041 30.050 2.5R 6 16 0.5041 0.2983 30.050 2.5R 6 18 0.5262 0.2928 30.050 5R 6 2 0.3343 0.3190 30.050 5R 6 4 0.3628 0.3221 30.050 5R 6 6 0.3921 0.3244 30.050 5R 6 8 0.4187 0.3251 30.050 5R 6 10 0.4480 0.3250 30.050 5R 6 12 0.4760 0.3234 30.050 5R 6 14 0.5020 0.3212 30.050 5R 6 16 0.5297 0.3179 30.050 5R 6 18 0.5552 0.3138 30.050 7.5R 6 2 0.3381 0.3228 30.050 7.5R 6 4 0.3692 0.3291 30.050 7.5R 6 6 0.4000 0.3340 30.050 7.5R 6 8 0.4318 0.3383 30.050 7.5R 6 10 0.4655 0.3412 30.050 7.5R 6 12 0.4961 0.3428 30.050 7.5R 6 14 0.5265 0.3431 30.050 7.5R 6 16 0.5560 0.3420 30.050 7.5R 6 18 0.5829 0.3396 30.050 10R 6 2 0.3417 0.3268 30.050 10R 6 4 0.3768 0.3381 30.050 10R 6 6 0.4103 0.3473 30.050 10R 6 8 0.4449 0.3550 30.050 10R 6 10 0.4812 0.3619 30.050 10R 6 12 0.5150 0.3667 30.050 10R 6 14 0.5468 0.3697 30.050 10R 6 16 0.5741 0.3713 30.050 10R 6 18 0.6009 0.3720 30.050 2.5YR 6 2 0.3453 0.3321 30.050 2.5YR 6 4 0.3806 0.3467 30.050 2.5YR 6 6 0.4180 0.3600 30.050 2.5YR 6 8 0.4533 0.3708 30.050 2.5YR 6 10 0.4891 0.3806 30.050 2.5YR 6 12 0.5215 0.3887 30.050 2.5YR 6 14 0.5488 0.3947 30.050 2.5YR 6 16 0.5698 0.3990 30.050 2.5YR 6 18 0.5879 0.4021 30.050 5YR 6 2 0.3474 0.3373 30.050 5YR 6 4 0.3840 0.3564 30.050 5YR 6 6 0.4229 0.3750 30.050 5YR 6 8 0.4592 0.3900 30.050 5YR 6 10 0.4921 0.4022 30.050 5YR 6 12 0.5199 0.4119 30.050 5YR 6 14 0.5423 0.4188 30.050 5YR 6 16 0.5597 0.4239 30.050 5YR 6 18 0.5715 0.4270 30.050 7.5YR 6 2 0.3487 0.3421 30.050 7.5YR 6 4 0.3860 0.3652 30.050 7.5YR 6 6 0.4242 0.3876 30.050 7.5YR 6 8 0.4596 0.4064 30.050 7.5YR 6 10 0.4904 0.4220 30.050 7.5YR 6 12 0.5145 0.4331 30.050 7.5YR 6 14 0.5320 0.4412 30.050 7.5YR 6 16 0.5468 0.4478 30.050 10YR 6 2 0.3491 0.3483 30.050 10YR 6 4 0.3861 0.3767 30.050 10YR 6 6 0.4240 0.4030 30.050 10YR 6 8 0.4570 0.4249 30.050 10YR 6 10 0.4843 0.4416 30.050 10YR 6 12 0.5050 0.4536 30.050 10YR 6 14 0.5200 0.4623 30.050 2.5Y 6 2 0.3480 0.3540 30.050 2.5Y 6 4 0.3840 0.3867 30.050 2.5Y 6 6 0.4203 0.4176 30.050 2.5Y 6 8 0.4517 0.4421 30.050 2.5Y 6 10 0.4760 0.4607 30.050 2.5Y 6 12 0.4928 0.4730 30.050 2.5Y 6 14 0.5061 0.4829 30.050 5Y 6 2 0.3457 0.3580 30.050 5Y 6 4 0.3794 0.3955 30.050 5Y 6 6 0.4140 0.4305 30.050 5Y 6 8 0.4426 0.4588 30.050 5Y 6 10 0.4639 0.4790 30.050 5Y 6 12 0.4780 0.4920 30.050 5Y 6 14 0.4905 0.5038 30.050 7.5Y 6 2 0.3431 0.3601 30.050 7.5Y 6 4 0.3745 0.4004 30.050 7.5Y 6 6 0.4060 0.4400 30.050 7.5Y 6 8 0.4321 0.4719 30.050 7.5Y 6 10 0.4512 0.4943 30.050 7.5Y 6 12 0.4638 0.5087 30.050 7.5Y 6 14 0.4754 0.5220 30.050 10Y 6 2 0.3398 0.3611 30.050 10Y 6 4 0.3679 0.4033 30.050 10Y 6 6 0.3960 0.4452 30.050 10Y 6 8 0.4201 0.4812 30.050 10Y 6 10 0.4372 0.5068 30.050 10Y 6 12 0.4488 0.5237 30.050 10Y 6 14 0.4593 0.5392 30.050 2.5GY 6 2 0.3342 0.3607 30.050 2.5GY 6 4 0.3572 0.4038 30.050 2.5GY 6 6 0.3799 0.4470 30.050 2.5GY 6 8 0.4006 0.4885 30.050 2.5GY 6 10 0.4159 0.5190 30.050 2.5GY 6 12 0.4269 0.5414 30.050 2.5GY 6 14 0.4354 0.5594 30.050 5GY 6 2 0.3288 0.3592 30.050 5GY 6 4 0.3461 0.4008 30.050 5GY 6 6 0.3622 0.4438 30.050 5GY 6 8 0.3772 0.4880 30.050 5GY 6 10 0.3891 0.5264 30.050 5GY 6 12 0.3980 0.5564 30.050 5GY 6 14 0.4042 0.5788 30.050 7.5GY 6 2 0.3193 0.3550 30.050 7.5GY 6 4 0.3275 0.3922 30.050 7.5GY 6 6 0.3351 0.4321 30.050 7.5GY 6 8 0.3418 0.4768 30.050 7.5GY 6 10 0.3463 0.5196 30.050 7.5GY 6 12 0.3488 0.5596 30.050 7.5GY 6 14 0.3498 0.5985 30.050 7.5GY 6 16 0.3498 0.6282 30.050 10GY 6 2 0.3112 0.3496 30.050 10GY 6 4 0.3124 0.3822 30.050 10GY 6 6 0.3128 0.4175 30.050 10GY 6 8 0.3116 0.4563 30.050 10GY 6 10 0.3086 0.4949 30.050 10GY 6 12 0.3037 0.5358 30.050 10GY 6 14 0.2962 0.5802 30.050 10GY 6 16 0.2872 0.6199 30.050 10GY 6 18 0.2763 0.6616 30.050 10GY 6 20 0.2648 0.7004 30.050 2.5G 6 2 0.3039 0.3437 30.050 2.5G 6 4 0.2967 0.3695 30.050 2.5G 6 6 0.2892 0.3963 30.050 2.5G 6 8 0.2799 0.4239 30.050 2.5G 6 10 0.2690 0.4530 30.050 2.5G 6 12 0.2574 0.4814 30.050 2.5G 6 14 0.2426 0.5133 30.050 2.5G 6 16 0.2278 0.5430 30.050 2.5G 6 18 0.2102 0.5737 30.050 2.5G 6 20 0.1922 0.6035 30.050 2.5G 6 22 0.1739 0.6318 30.050 2.5G 6 24 0.1536 0.6605 30.050 2.5G 6 26 0.1340 0.6871 30.050 2.5G 6 28 0.1145 0.7122 30.050 5G 6 2 0.2988 0.3382 30.050 5G 6 4 0.2868 0.3595 30.050 5G 6 6 0.2748 0.3795 30.050 5G 6 8 0.2612 0.3990 30.050 5G 6 10 0.2466 0.4181 30.050 5G 6 12 0.2293 0.4390 30.050 5G 6 14 0.2130 0.4571 30.050 5G 6 16 0.1960 0.4751 30.050 5G 6 18 0.1785 0.4924 30.050 5G 6 20 0.1609 0.5091 30.050 5G 6 22 0.1432 0.5252 30.050 5G 6 24 0.1252 0.5408 30.050 5G 6 26 0.1079 0.5560 30.050 5G 6 28 0.0908 0.5695 30.050 7.5G 6 2 0.2958 0.3344 30.050 7.5G 6 4 0.2807 0.3522 30.050 7.5G 6 6 0.2662 0.3672 30.050 7.5G 6 8 0.2510 0.3829 30.050 7.5G 6 10 0.2350 0.3979 30.050 7.5G 6 12 0.2171 0.4138 30.050 7.5G 6 14 0.2001 0.4278 30.050 7.5G 6 16 0.1832 0.4414 30.050 7.5G 6 18 0.1654 0.4551 30.050 7.5G 6 20 0.1485 0.4677 30.050 7.5G 6 22 0.1325 0.4795 30.050 7.5G 6 24 0.1159 0.4910 30.050 7.5G 6 26 0.1010 0.5018 30.050 7.5G 6 28 0.0858 0.5127 30.050 10G 6 2 0.2929 0.3303 30.050 10G 6 4 0.2749 0.3443 30.050 10G 6 6 0.2591 0.3558 30.050 10G 6 8 0.2420 0.3679 30.050 10G 6 10 0.2247 0.3796 30.050 10G 6 12 0.2060 0.3914 30.050 10G 6 14 0.1895 0.4015 30.050 10G 6 16 0.1722 0.4113 30.050 10G 6 18 0.1551 0.4208 30.050 10G 6 20 0.1382 0.4299 30.050 10G 6 22 0.1230 0.4378 30.050 10G 6 24 0.1070 0.4458 30.050 10G 6 26 0.0941 0.4520 30.050 2.5BG 6 2 0.2902 0.3268 30.050 2.5BG 6 4 0.2702 0.3369 30.050 2.5BG 6 6 0.2526 0.3448 30.050 2.5BG 6 8 0.2332 0.3522 30.050 2.5BG 6 10 0.2148 0.3584 30.050 2.5BG 6 12 0.1954 0.3645 30.050 2.5BG 6 14 0.1779 0.3699 30.050 2.5BG 6 16 0.1600 0.3748 30.050 2.5BG 6 18 0.1428 0.3790 30.050 2.5BG 6 20 0.1269 0.3829 30.050 2.5BG 6 22 0.1120 0.3860 30.050 5BG 6 2 0.2872 0.3219 30.050 5BG 6 4 0.2648 0.3262 30.050 5BG 6 6 0.2441 0.3290 30.050 5BG 6 8 0.2236 0.3311 30.050 5BG 6 10 0.2037 0.3329 30.050 5BG 6 12 0.1844 0.3337 30.050 5BG 6 14 0.1662 0.3343 30.050 5BG 6 16 0.1491 0.3345 30.050 5BG 6 18 0.1325 0.3345 30.050 5BG 6 20 0.1168 0.3344 30.050 7.5BG 6 2 0.2849 0.3172 30.050 7.5BG 6 4 0.2604 0.3169 30.050 7.5BG 6 6 0.2384 0.3155 30.050 7.5BG 6 8 0.2171 0.3138 30.050 7.5BG 6 10 0.1961 0.3110 30.050 7.5BG 6 12 0.1762 0.3081 30.050 7.5BG 6 14 0.1585 0.3052 30.050 7.5BG 6 16 0.1408 0.3017 30.050 7.5BG 6 18 0.1248 0.2981 30.050 10BG 6 2 0.2837 0.3132 30.050 10BG 6 4 0.2578 0.3078 30.050 10BG 6 6 0.2335 0.3015 30.050 10BG 6 8 0.2116 0.2950 30.050 10BG 6 10 0.1909 0.2881 30.050 10BG 6 12 0.1698 0.2802 30.050 10BG 6 14 0.1518 0.2729 30.050 10BG 6 16 0.1337 0.2651 30.050 10BG 6 18 0.1181 0.2581 30.050 2.5B 6 2 0.2835 0.3097 30.050 2.5B 6 4 0.2571 0.3008 30.050 2.5B 6 6 0.2312 0.2899 30.050 2.5B 6 8 0.2080 0.2789 30.050 2.5B 6 10 0.1879 0.2682 30.050 2.5B 6 12 0.1660 0.2561 30.050 2.5B 6 14 0.1480 0.2459 30.050 2.5B 6 16 0.1294 0.2348 30.050 5B 6 2 0.2842 0.3063 30.050 5B 6 4 0.2579 0.2938 30.050 5B 6 6 0.2320 0.2789 30.050 5B 6 8 0.2088 0.2635 30.050 5B 6 10 0.1883 0.2487 30.050 5B 6 12 0.1685 0.2339 30.050 5B 6 14 0.1496 0.2193 30.050 5B 6 16 0.1310 0.2048 30.050 7.5B 6 2 0.2854 0.3037 30.050 7.5B 6 4 0.2602 0.2881 30.050 7.5B 6 6 0.2352 0.2708 30.050 7.5B 6 8 0.2132 0.2537 30.050 7.5B 6 10 0.1934 0.2374 30.050 7.5B 6 12 0.1734 0.2203 30.050 7.5B 6 14 0.1556 0.2043 30.050 7.5B 6 16 0.1376 0.1879 30.050 10B 6 2 0.2871 0.3012 30.050 10B 6 4 0.2637 0.2840 30.050 10B 6 6 0.2399 0.2650 30.050 10B 6 8 0.2189 0.2468 30.050 10B 6 10 0.2000 0.2298 30.050 10B 6 12 0.1803 0.2114 30.050 10B 6 14 0.1629 0.1947 30.050 10B 6 16 0.1454 0.1778 30.050 2.5PB 6 2 0.2897 0.2991 30.050 2.5PB 6 4 0.2684 0.2804 30.050 2.5PB 6 6 0.2465 0.2599 30.050 2.5PB 6 8 0.2274 0.2406 30.050 2.5PB 6 10 0.2095 0.2225 30.050 2.5PB 6 12 0.1913 0.2038 30.050 2.5PB 6 14 0.1754 0.1868 30.050 5PB 6 2 0.2923 0.2978 30.050 5PB 6 4 0.2734 0.2778 30.050 5PB 6 6 0.2533 0.2558 30.050 5PB 6 8 0.2360 0.2365 30.050 5PB 6 10 0.2197 0.2188 30.050 5PB 6 12 0.2026 0.1999 30.050 5PB 6 14 0.1873 0.1822 30.050 7.5PB 6 2 0.2955 0.2963 30.050 7.5PB 6 4 0.2798 0.2752 30.050 7.5PB 6 6 0.2638 0.2531 30.050 7.5PB 6 8 0.2505 0.2347 30.050 7.5PB 6 10 0.2378 0.2168 30.050 7.5PB 6 12 0.2241 0.1975 30.050 7.5PB 6 14 0.2119 0.1799 30.050 10PB 6 2 0.2988 0.2961 30.050 10PB 6 4 0.2863 0.2747 30.050 10PB 6 6 0.2740 0.2533 30.050 10PB 6 8 0.2637 0.2352 30.050 10PB 6 10 0.2540 0.2176 30.050 10PB 6 12 0.2440 0.1998 30.050 10PB 6 14 0.2352 0.1839 30.050 10PB 6 16 0.2265 0.1671 30.050 2.5P 6 2 0.3016 0.2960 30.050 2.5P 6 4 0.2932 0.2759 30.050 2.5P 6 6 0.2842 0.2550 30.050 2.5P 6 8 0.2770 0.2372 30.050 2.5P 6 10 0.2703 0.2204 30.050 2.5P 6 12 0.2647 0.2052 30.050 2.5P 6 14 0.2593 0.1909 30.050 2.5P 6 16 0.2548 0.1768 30.050 2.5P 6 18 0.2504 0.1658 30.050 5P 6 2 0.3050 0.2967 30.050 5P 6 4 0.3001 0.2778 30.050 5P 6 6 0.2950 0.2585 30.050 5P 6 8 0.2905 0.2421 30.050 5P 6 10 0.2862 0.2260 30.050 5P 6 12 0.2829 0.2121 30.050 5P 6 14 0.2794 0.1979 30.050 5P 6 16 0.2761 0.1852 30.050 5P 6 18 0.2731 0.1738 30.050 5P 6 20 0.2702 0.1621 30.050 7.5P 6 2 0.3107 0.2993 30.050 7.5P 6 4 0.3107 0.2831 30.050 7.5P 6 6 0.3101 0.2650 30.050 7.5P 6 8 0.3099 0.2502 30.050 7.5P 6 10 0.3092 0.2350 30.050 7.5P 6 12 0.3090 0.2222 30.050 7.5P 6 14 0.3084 0.2095 30.050 7.5P 6 16 0.3080 0.1976 30.050 7.5P 6 18 0.3075 0.1870 30.050 7.5P 6 20 0.3069 0.1745 30.050 7.5P 6 22 0.3062 0.1638 30.050 7.5P 6 24 0.3058 0.1547 30.050 10P 6 2 0.3146 0.3018 30.050 10P 6 4 0.3181 0.2871 30.050 10P 6 6 0.3226 0.2716 30.050 10P 6 8 0.3259 0.2584 30.050 10P 6 10 0.3293 0.2450 30.050 10P 6 12 0.3321 0.2329 30.050 10P 6 14 0.3349 0.2203 30.050 10P 6 16 0.3370 0.2095 30.050 10P 6 18 0.3388 0.1995 30.050 10P 6 20 0.3409 0.1882 30.050 10P 6 22 0.3426 0.1785 30.050 10P 6 24 0.3441 0.1698 30.050 10P 6 26 0.3457 0.1604 30.050 2.5RP 6 2 0.3188 0.3048 30.050 2.5RP 6 4 0.3272 0.2929 30.050 2.5RP 6 6 0.3362 0.2799 30.050 2.5RP 6 8 0.3437 0.2688 30.050 2.5RP 6 10 0.3509 0.2578 30.050 2.5RP 6 12 0.3582 0.2462 30.050 2.5RP 6 14 0.3652 0.2355 30.050 2.5RP 6 16 0.3718 0.2251 30.050 2.5RP 6 18 0.3773 0.2158 30.050 2.5RP 6 20 0.3833 0.2056 30.050 2.5RP 6 22 0.3877 0.1978 30.050 2.5RP 6 24 0.3927 0.1892 30.050 5RP 6 2 0.3232 0.3085 30.050 5RP 6 4 0.3371 0.3001 30.050 5RP 6 6 0.3520 0.2904 30.050 5RP 6 8 0.3648 0.2820 30.050 5RP 6 10 0.3769 0.2738 30.050 5RP 6 12 0.3900 0.2646 30.050 5RP 6 14 0.4023 0.2552 30.050 5RP 6 16 0.4136 0.2467 30.050 5RP 6 18 0.4245 0.2382 30.050 5RP 6 20 0.4368 0.2283 30.050 5RP 6 22 0.4449 0.2219 30.050 7.5RP 6 2 0.3261 0.3113 30.050 7.5RP 6 4 0.3439 0.3056 30.050 7.5RP 6 6 0.3635 0.2987 30.050 7.5RP 6 8 0.3791 0.2929 30.050 7.5RP 6 10 0.3960 0.2860 30.050 7.5RP 6 12 0.4125 0.2784 30.050 7.5RP 6 14 0.4285 0.2705 30.050 7.5RP 6 16 0.4448 0.2622 30.050 7.5RP 6 18 0.4581 0.2549 30.050 7.5RP 6 20 0.4735 0.2464 30.050 10RP 7 2 0.3258 0.3148 43.060 10RP 7 4 0.3446 0.3125 43.060 10RP 7 6 0.3648 0.3098 43.060 10RP 7 8 0.3851 0.3067 43.060 10RP 7 10 0.4040 0.3030 43.060 10RP 7 12 0.4260 0.2980 43.060 10RP 7 14 0.4456 0.2931 43.060 10RP 7 16 0.4648 0.2878 43.060 2.5R 7 2 0.3284 0.3170 43.060 2.5R 7 4 0.3499 0.3171 43.060 2.5R 7 6 0.3728 0.3170 43.060 2.5R 7 8 0.3961 0.3160 43.060 2.5R 7 10 0.4183 0.3144 43.060 2.5R 7 12 0.4435 0.3119 43.060 2.5R 7 14 0.4660 0.3082 43.060 2.5R 7 16 0.4885 0.3039 43.060 5R 7 2 0.3306 0.3190 43.060 5R 7 4 0.3552 0.3222 43.060 5R 7 6 0.3805 0.3244 43.060 5R 7 8 0.4067 0.3256 43.060 5R 7 10 0.4320 0.3260 43.060 5R 7 12 0.4595 0.3252 43.060 5R 7 14 0.4848 0.3238 43.060 7.5R 7 2 0.3335 0.3220 43.060 7.5R 7 4 0.3611 0.3282 43.060 7.5R 7 6 0.3888 0.3336 43.060 7.5R 7 8 0.4196 0.3382 43.060 7.5R 7 10 0.4470 0.3413 43.060 7.5R 7 12 0.4777 0.3435 43.060 7.5R 7 14 0.5059 0.3450 43.060 7.5R 7 16 0.5341 0.3452 43.060 10R 7 2 0.3360 0.3253 43.060 10R 7 4 0.3671 0.3360 43.060 10R 7 6 0.3984 0.3452 43.060 10R 7 8 0.4308 0.3533 43.060 10R 7 10 0.4600 0.3596 43.060 10R 7 12 0.4930 0.3659 43.060 10R 7 14 0.5234 0.3700 43.060 10R 7 16 0.5519 0.3729 43.060 2.5YR 7 2 0.3392 0.3298 43.060 2.5YR 7 4 0.3715 0.3439 43.060 2.5YR 7 6 0.4053 0.3570 43.060 2.5YR 7 8 0.4371 0.3679 43.060 2.5YR 7 10 0.4671 0.3768 43.060 2.5YR 7 12 0.5001 0.3861 43.060 2.5YR 7 14 0.5297 0.3938 43.060 2.5YR 7 16 0.5522 0.3989 43.060 2.5YR 7 18 0.5695 0.4024 43.060 2.5YR 7 20 0.5824 0.4046 43.060 5YR 7 2 0.3421 0.3349 43.060 5YR 7 4 0.3750 0.3530 43.060 5YR 7 6 0.4091 0.3701 43.060 5YR 7 8 0.4402 0.3842 43.060 5YR 7 10 0.4711 0.3972 43.060 5YR 7 12 0.5007 0.4081 43.060 5YR 7 14 0.5252 0.4168 43.060 5YR 7 16 0.5437 0.4228 43.060 5YR 7 18 0.5564 0.4267 43.060 5YR 7 20 0.5657 0.4298 43.060 7.5YR 7 2 0.3437 0.3397 43.060 7.5YR 7 4 0.3772 0.3613 43.060 7.5YR 7 6 0.4107 0.3820 43.060 7.5YR 7 8 0.4415 0.3996 43.060 7.5YR 7 10 0.4704 0.4151 43.060 7.5YR 7 12 0.4970 0.4282 43.060 7.5YR 7 14 0.5174 0.4381 43.060 7.5YR 7 16 0.5319 0.4449 43.060 7.5YR 7 18 0.5417 0.4492 43.060 10YR 7 2 0.3443 0.3454 43.060 10YR 7 4 0.3778 0.3719 43.060 10YR 7 6 0.4102 0.3960 43.060 10YR 7 8 0.4399 0.4164 43.060 10YR 7 10 0.4667 0.4335 43.060 10YR 7 12 0.4900 0.4480 43.060 10YR 7 14 0.5074 0.4581 43.060 10YR 7 16 0.5188 0.4650 43.060 10YR 7 18 0.5276 0.4700 43.060 2.5Y 7 2 0.3436 0.3507 43.060 2.5Y 7 4 0.3761 0.3800 43.060 2.5Y 7 6 0.4073 0.4073 43.060 2.5Y 7 8 0.4353 0.4312 43.060 2.5Y 7 10 0.4606 0.4516 43.060 2.5Y 7 12 0.4806 0.4666 43.060 2.5Y 7 14 0.4950 0.4773 43.060 2.5Y 7 16 0.5049 0.4843 43.060 5Y 7 2 0.3419 0.3540 43.060 5Y 7 4 0.3718 0.3885 43.060 5Y 7 6 0.4009 0.4198 43.060 5Y 7 8 0.4271 0.4462 43.060 5Y 7 10 0.4509 0.4696 43.060 5Y 7 12 0.4677 0.4857 43.060 5Y 7 14 0.4791 0.4965 43.060 5Y 7 16 0.4875 0.5047 43.060 7.5Y 7 2 0.3396 0.3558 43.060 7.5Y 7 4 0.3677 0.3925 43.060 7.5Y 7 6 0.3943 0.4264 43.060 7.5Y 7 8 0.4184 0.4568 43.060 7.5Y 7 10 0.4400 0.4830 43.060 7.5Y 7 12 0.4547 0.5005 43.060 7.5Y 7 14 0.4652 0.5128 43.060 7.5Y 7 16 0.4728 0.5215 43.060 10Y 7 2 0.3369 0.3569 43.060 10Y 7 4 0.3624 0.3951 43.060 10Y 7 6 0.3864 0.4305 43.060 10Y 7 8 0.4090 0.4641 43.060 10Y 7 10 0.4289 0.4937 43.060 10Y 7 12 0.4420 0.5131 43.060 10Y 7 14 0.4516 0.5277 43.060 10Y 7 16 0.4582 0.5375 43.060 2.5GY 7 2 0.3328 0.3569 43.060 2.5GY 7 4 0.3534 0.3953 43.060 2.5GY 7 6 0.3728 0.4316 43.060 2.5GY 7 8 0.3919 0.4684 43.060 2.5GY 7 10 0.4091 0.5030 43.060 2.5GY 7 12 0.4213 0.5270 43.060 2.5GY 7 14 0.4309 0.5459 43.060 2.5GY 7 16 0.4366 0.5578 43.060 5GY 7 2 0.3284 0.3559 43.060 5GY 7 4 0.3437 0.3929 43.060 5GY 7 6 0.3581 0.4291 43.060 5GY 7 8 0.3722 0.4669 43.060 5GY 7 10 0.3852 0.5051 43.060 5GY 7 12 0.3949 0.5367 43.060 5GY 7 14 0.4027 0.5615 43.060 5GY 7 16 0.4076 0.5783 43.060 7.5GY 7 2 0.3190 0.3516 43.060 7.5GY 7 4 0.3267 0.3848 43.060 7.5GY 7 6 0.3341 0.4191 43.060 7.5GY 7 8 0.3406 0.4558 43.060 7.5GY 7 10 0.3461 0.4950 43.060 7.5GY 7 12 0.3502 0.5328 43.060 7.5GY 7 14 0.3532 0.5700 43.060 7.5GY 7 16 0.3549 0.6000 43.060 7.5GY 7 18 0.3555 0.6242 43.060 10GY 7 2 0.3117 0.3469 43.060 10GY 7 4 0.3133 0.3764 43.060 10GY 7 6 0.3142 0.4058 43.060 10GY 7 8 0.3140 0.4387 43.060 10GY 7 10 0.3123 0.4732 43.060 10GY 7 12 0.3092 0.5095 43.060 10GY 7 14 0.3047 0.5458 43.060 10GY 7 16 0.2981 0.5835 43.060 10GY 7 18 0.2905 0.6186 43.060 10GY 7 20 0.2816 0.6563 43.060 10GY 7 22 0.2728 0.6893 43.060 2.5G 7 2 0.3047 0.3413 43.060 2.5G 7 4 0.2992 0.3644 43.060 2.5G 7 6 0.2933 0.3873 43.060 2.5G 7 8 0.2861 0.4129 43.060 2.5G 7 10 0.2775 0.4395 43.060 2.5G 7 12 0.2672 0.4667 43.060 2.5G 7 14 0.2568 0.4931 43.060 2.5G 7 16 0.2448 0.5203 43.060 2.5G 7 18 0.2328 0.5467 43.060 2.5G 7 20 0.2181 0.5744 43.060 2.5G 7 22 0.2029 0.6017 43.060 2.5G 7 24 0.1875 0.6265 43.060 2.5G 7 26 0.1689 0.6549 43.060 5G 7 2 0.3001 0.3366 43.060 5G 7 4 0.2902 0.3548 43.060 5G 7 6 0.2801 0.3721 43.060 5G 7 8 0.2687 0.3901 43.060 5G 7 10 0.2554 0.4087 43.060 5G 7 12 0.2416 0.4267 43.060 5G 7 14 0.2262 0.4450 43.060 5G 7 16 0.2111 0.4616 43.060 5G 7 18 0.1967 0.4771 43.060 5G 7 20 0.1805 0.4933 43.060 5G 7 22 0.1659 0.5074 43.060 5G 7 24 0.1521 0.5200 43.060 5G 7 26 0.1397 0.5312 43.060 7.5G 7 2 0.2972 0.3333 43.060 7.5G 7 4 0.2850 0.3482 43.060 7.5G 7 6 0.2728 0.3622 43.060 7.5G 7 8 0.2595 0.3764 43.060 7.5G 7 10 0.2445 0.3914 43.060 7.5G 7 12 0.2295 0.4058 43.060 7.5G 7 14 0.2139 0.4199 43.060 7.5G 7 16 0.1982 0.4330 43.060 7.5G 7 18 0.1841 0.4448 43.060 7.5G 7 20 0.1688 0.4570 43.060 7.5G 7 22 0.1539 0.4683 43.060 7.5G 7 24 0.1415 0.4778 43.060 7.5G 7 26 0.1303 0.4858 43.060 10G 7 2 0.2945 0.3297 43.060 10G 7 4 0.2803 0.3415 43.060 10G 7 6 0.2662 0.3526 43.060 10G 7 8 0.2513 0.3635 43.060 10G 7 10 0.2352 0.3748 43.060 10G 7 12 0.2195 0.3854 43.060 10G 7 14 0.2033 0.3956 43.060 10G 7 16 0.1881 0.4049 43.060 10G 7 18 0.1734 0.4135 43.060 10G 7 20 0.1589 0.4220 43.060 10G 7 22 0.1434 0.4306 43.060 10G 7 24 0.1310 0.4377 43.060 2.5BG 7 2 0.2927 0.3269 43.060 2.5BG 7 4 0.2764 0.3354 43.060 2.5BG 7 6 0.2608 0.3430 43.060 2.5BG 7 8 0.2439 0.3508 43.060 2.5BG 7 10 0.2264 0.3576 43.060 2.5BG 7 12 0.2102 0.3636 43.060 2.5BG 7 14 0.1932 0.3694 43.060 2.5BG 7 16 0.1788 0.3739 43.060 2.5BG 7 18 0.1626 0.3788 43.060 2.5BG 7 20 0.1490 0.3827 43.060 2.5BG 7 22 0.1334 0.3870 43.060 5BG 7 2 0.2898 0.3225 43.060 5BG 7 4 0.2712 0.3269 43.060 5BG 7 6 0.2543 0.3302 43.060 5BG 7 8 0.2354 0.3335 43.060 5BG 7 10 0.2163 0.3361 43.060 5BG 7 12 0.1997 0.3379 43.060 5BG 7 14 0.1838 0.3390 43.060 5BG 7 16 0.1675 0.3401 43.060 5BG 7 18 0.1515 0.3410 43.060 5BG 7 20 0.1380 0.3412 43.060 7.5BG 7 2 0.2878 0.3182 43.060 7.5BG 7 4 0.2671 0.3189 43.060 7.5BG 7 6 0.2490 0.3186 43.060 7.5BG 7 8 0.2292 0.3178 43.060 7.5BG 7 10 0.2094 0.3165 43.060 7.5BG 7 12 0.1914 0.3148 43.060 7.5BG 7 14 0.1751 0.3129 43.060 7.5BG 7 16 0.1584 0.3101 43.060 7.5BG 7 18 0.1427 0.3076 43.060 10BG 7 2 0.2869 0.3143 43.060 10BG 7 4 0.2642 0.3109 43.060 10BG 7 6 0.2448 0.3069 43.060 10BG 7 8 0.2235 0.3014 43.060 10BG 7 10 0.2035 0.2956 43.060 10BG 7 12 0.1841 0.2892 43.060 10BG 7 14 0.1671 0.2832 43.060 10BG 7 16 0.1489 0.2768 43.060 2.5B 7 2 0.2867 0.3110 43.060 2.5B 7 4 0.2629 0.3038 43.060 2.5B 7 6 0.2418 0.2960 43.060 2.5B 7 8 0.2208 0.2871 43.060 2.5B 7 10 0.1994 0.2775 43.060 2.5B 7 12 0.1797 0.2672 43.060 2.5B 7 14 0.1624 0.2581 43.060 5B 7 2 0.2875 0.3078 43.060 5B 7 4 0.2633 0.2972 43.060 5B 7 6 0.2410 0.2854 43.060 5B 7 8 0.2204 0.2729 43.060 5B 7 10 0.1986 0.2579 43.060 5B 7 12 0.1778 0.2430 43.060 5B 7 14 0.1615 0.2307 43.060 7.5B 7 2 0.2888 0.3058 43.060 7.5B 7 4 0.2651 0.2927 43.060 7.5B 7 6 0.2436 0.2787 43.060 7.5B 7 8 0.2225 0.2631 43.060 7.5B 7 10 0.2016 0.2466 43.060 7.5B 7 12 0.1818 0.2303 43.060 10B 7 2 0.2908 0.3039 43.060 10B 7 4 0.2685 0.2886 43.060 10B 7 6 0.2478 0.2728 43.060 10B 7 8 0.2277 0.2559 43.060 10B 7 10 0.2078 0.2382 43.060 10B 7 12 0.1883 0.2203 43.060 2.5PB 7 2 0.2932 0.3025 43.060 2.5PB 7 4 0.2729 0.2848 43.060 2.5PB 7 6 0.2538 0.2677 43.060 2.5PB 7 8 0.2352 0.2498 43.060 2.5PB 7 10 0.2162 0.2309 43.060 5PB 7 2 0.2952 0.3011 43.060 5PB 7 4 0.2773 0.2828 43.060 5PB 7 6 0.2596 0.2643 43.060 5PB 7 8 0.2427 0.2458 43.060 5PB 7 10 0.2254 0.2267 43.060 7.5PB 7 2 0.2982 0.3003 43.060 7.5PB 7 4 0.2833 0.2809 43.060 7.5PB 7 6 0.2687 0.2612 43.060 7.5PB 7 8 0.2546 0.2418 43.060 7.5PB 7 10 0.2410 0.2224 43.060 10PB 7 2 0.3005 0.3000 43.060 10PB 7 4 0.2886 0.2801 43.060 10PB 7 6 0.2776 0.2612 43.060 10PB 7 8 0.2670 0.2425 43.060 10PB 7 10 0.2563 0.2240 43.060 10PB 7 12 0.2465 0.2058 43.060 2.5P 7 2 0.3031 0.3000 43.060 2.5P 7 4 0.2950 0.2810 43.060 2.5P 7 6 0.2873 0.2633 43.060 2.5P 7 8 0.2799 0.2459 43.060 2.5P 7 10 0.2729 0.2289 43.060 2.5P 7 12 0.2664 0.2127 43.060 5P 7 2 0.3059 0.3010 43.060 5P 7 4 0.3009 0.2831 43.060 5P 7 6 0.2961 0.2663 43.060 5P 7 8 0.2918 0.2504 43.060 5P 7 10 0.2872 0.2343 43.060 5P 7 12 0.2833 0.2197 43.060 5P 7 14 0.2801 0.2068 43.060 7.5P 7 2 0.3109 0.3037 43.060 7.5P 7 4 0.3111 0.2880 43.060 7.5P 7 6 0.3111 0.2730 43.060 7.5P 7 8 0.3109 0.2584 43.060 7.5P 7 10 0.3108 0.2442 43.060 7.5P 7 12 0.3104 0.2320 43.060 7.5P 7 14 0.3101 0.2192 43.060 7.5P 7 16 0.3099 0.2074 43.060 7.5P 7 18 0.3093 0.1962 43.060 10P 7 2 0.3138 0.3054 43.060 10P 7 4 0.3181 0.2920 43.060 10P 7 6 0.3221 0.2786 43.060 10P 7 8 0.3256 0.2654 43.060 10P 7 10 0.3288 0.2531 43.060 10P 7 12 0.3314 0.2423 43.060 10P 7 14 0.3341 0.2308 43.060 10P 7 16 0.3368 0.2192 43.060 10P 7 18 0.3391 0.2088 43.060 10P 7 20 0.3410 0.1988 43.060 10P 7 22 0.3430 0.1883 43.060 2.5RP 7 2 0.3170 0.3076 43.060 2.5RP 7 4 0.3254 0.2971 43.060 2.5RP 7 6 0.3338 0.2854 43.060 2.5RP 7 8 0.3417 0.2745 43.060 2.5RP 7 10 0.3487 0.2648 43.060 2.5RP 7 12 0.3555 0.2545 43.060 2.5RP 7 14 0.3620 0.2448 43.060 2.5RP 7 16 0.3688 0.2342 43.060 2.5RP 7 18 0.3751 0.2241 43.060 2.5RP 7 20 0.3811 0.2143 43.060 5RP 7 2 0.3206 0.3104 43.060 5RP 7 4 0.3332 0.3032 43.060 5RP 7 6 0.3470 0.2949 43.060 5RP 7 8 0.3603 0.2869 43.060 5RP 7 10 0.3713 0.2798 43.060 5RP 7 12 0.3841 0.2710 43.060 5RP 7 14 0.3958 0.2628 43.060 5RP 7 16 0.4076 0.2540 43.060 5RP 7 18 0.4186 0.2459 43.060 7.5RP 7 2 0.3232 0.3125 43.060 7.5RP 7 4 0.3389 0.3079 43.060 7.5RP 7 6 0.3562 0.3022 43.060 7.5RP 7 8 0.3722 0.2963 43.060 7.5RP 7 10 0.3871 0.2906 43.060 7.5RP 7 12 0.4040 0.2834 43.060 7.5RP 7 14 0.4195 0.2762 43.060 7.5RP 7 16 0.4346 0.2689 43.060 10RP 8 2 0.3218 0.3152 59.100 10RP 8 4 0.3412 0.3135 59.100 10RP 8 6 0.3600 0.3112 59.100 10RP 8 8 0.3800 0.3082 59.100 10RP 8 10 0.3983 0.3049 59.100 2.5R 8 2 0.3236 0.3169 59.100 2.5R 8 4 0.3460 0.3177 59.100 2.5R 8 6 0.3671 0.3175 59.100 2.5R 8 8 0.3900 0.3171 59.100 2.5R 8 10 0.4125 0.3160 59.100 5R 8 2 0.3254 0.3186 59.100 5R 8 4 0.3510 0.3224 59.100 5R 8 6 0.3743 0.3248 59.100 5R 8 8 0.4001 0.3263 59.100 5R 8 10 0.4249 0.3270 59.100 7.5R 8 2 0.3277 0.3211 59.100 7.5R 8 4 0.3564 0.3279 59.100 7.5R 8 6 0.3830 0.3335 59.100 7.5R 8 8 0.4118 0.3385 59.100 7.5R 8 10 0.4388 0.3419 59.100 10R 8 2 0.3301 0.3237 59.100 10R 8 4 0.3621 0.3349 59.100 10R 8 6 0.3910 0.3442 59.100 10R 8 8 0.4212 0.3526 59.100 10R 8 10 0.4490 0.3589 59.100 2.5YR 8 2 0.3334 0.3276 59.100 2.5YR 8 4 0.3667 0.3429 59.100 2.5YR 8 6 0.3960 0.3547 59.100 2.5YR 8 8 0.4275 0.3662 59.100 2.5YR 8 10 0.4552 0.3761 59.100 2.5YR 8 12 0.4852 0.3847 59.100 5YR 8 2 0.3373 0.3330 59.100 5YR 8 4 0.3690 0.3510 59.100 5YR 8 6 0.3988 0.3663 59.100 5YR 8 8 0.4310 0.3820 59.100 5YR 8 10 0.4576 0.3938 59.100 5YR 8 12 0.4849 0.4050 59.100 5YR 8 14 0.5088 0.4145 59.100 7.5YR 8 2 0.3395 0.3379 59.100 7.5YR 8 4 0.3699 0.3586 59.100 7.5YR 8 6 0.4000 0.3770 59.100 7.5YR 8 8 0.4306 0.3952 59.100 7.5YR 8 10 0.4568 0.4100 59.100 7.5YR 8 12 0.4816 0.4232 59.100 7.5YR 8 14 0.5025 0.4338 59.100 7.5YR 8 16 0.5195 0.4424 59.100 7.5YR 8 18 0.5316 0.4480 59.100 7.5YR 8 20 0.5391 0.4518 59.100 10YR 8 2 0.3407 0.3434 59.100 10YR 8 4 0.3701 0.3674 59.100 10YR 8 6 0.3994 0.3896 59.100 10YR 8 8 0.4280 0.4102 59.100 10YR 8 10 0.4527 0.4268 59.100 10YR 8 12 0.4753 0.4414 59.100 10YR 8 14 0.4940 0.4530 59.100 10YR 8 16 0.5079 0.4613 59.100 10YR 8 18 0.5179 0.4670 59.100 10YR 8 20 0.5245 0.4709 59.100 2.5Y 8 2 0.3406 0.3484 59.100 2.5Y 8 4 0.3684 0.3751 59.100 2.5Y 8 6 0.3969 0.4009 59.100 2.5Y 8 8 0.4231 0.4231 59.100 2.5Y 8 10 0.4469 0.4423 59.100 2.5Y 8 12 0.4678 0.4589 59.100 2.5Y 8 14 0.4842 0.4712 59.100 2.5Y 8 16 0.4957 0.4800 59.100 2.5Y 8 18 0.5033 0.4855 59.100 2.5Y 8 20 0.5091 0.4900 59.100 5Y 8 2 0.3394 0.3518 59.100 5Y 8 4 0.3650 0.3826 59.100 5Y 8 6 0.3913 0.4117 59.100 5Y 8 8 0.4158 0.4378 59.100 5Y 8 10 0.4376 0.4601 59.100 5Y 8 12 0.4562 0.4788 59.100 5Y 8 14 0.4699 0.4920 59.100 5Y 8 16 0.4791 0.5012 59.100 5Y 8 18 0.4847 0.5069 59.100 7.5Y 8 2 0.3379 0.3540 59.100 7.5Y 8 4 0.3622 0.3861 59.100 7.5Y 8 6 0.3862 0.4175 59.100 7.5Y 8 8 0.4088 0.4466 59.100 7.5Y 8 10 0.4283 0.4712 59.100 7.5Y 8 12 0.4455 0.4917 59.100 7.5Y 8 14 0.4574 0.5062 59.100 7.5Y 8 16 0.4658 0.5158 59.100 7.5Y 8 18 0.4709 0.5220 59.100 10Y 8 2 0.3359 0.3552 59.100 10Y 8 4 0.3581 0.3883 59.100 10Y 8 6 0.3803 0.4216 59.100 10Y 8 8 0.4008 0.4520 59.100 10Y 8 10 0.4190 0.4791 59.100 10Y 8 12 0.4341 0.5020 59.100 10Y 8 14 0.4450 0.5181 59.100 10Y 8 16 0.4525 0.5295 59.100 10Y 8 18 0.4570 0.5366 59.100 2.5GY 8 2 0.3327 0.3555 59.100 2.5GY 8 4 0.3504 0.3887 59.100 2.5GY 8 6 0.3690 0.4230 59.100 2.5GY 8 8 0.3858 0.4550 59.100 2.5GY 8 10 0.4021 0.4869 59.100 2.5GY 8 12 0.4154 0.5133 59.100 2.5GY 8 14 0.4261 0.5344 59.100 2.5GY 8 16 0.4327 0.5475 59.100 2.5GY 8 18 0.4371 0.5557 59.100 5GY 8 2 0.3284 0.3542 59.100 5GY 8 4 0.3433 0.3872 59.100 5GY 8 6 0.3573 0.4214 59.100 5GY 8 8 0.3696 0.4542 59.100 5GY 8 10 0.3816 0.4879 59.100 5GY 8 12 0.3924 0.5199 59.100 5GY 8 14 0.4011 0.5468 59.100 5GY 8 16 0.4061 0.5641 59.100 5GY 8 18 0.4104 0.5785 59.100 5GY 8 20 0.4127 0.5855 59.100 7.5GY 8 2 0.3194 0.3502 59.100 7.5GY 8 4 0.3266 0.3809 59.100 7.5GY 8 6 0.3339 0.4129 59.100 7.5GY 8 8 0.3408 0.4452 59.100 7.5GY 8 10 0.3463 0.4791 59.100 7.5GY 8 12 0.3511 0.5144 59.100 7.5GY 8 14 0.3546 0.5490 59.100 7.5GY 8 16 0.3569 0.5798 59.100 7.5GY 8 18 0.3585 0.6063 59.100 7.5GY 8 20 0.3592 0.6235 59.100 10GY 8 2 0.3121 0.3459 59.100 10GY 8 4 0.3140 0.3727 59.100 10GY 8 6 0.3150 0.4014 59.100 10GY 8 8 0.3149 0.4284 59.100 10GY 8 10 0.3140 0.4601 59.100 10GY 8 12 0.3124 0.4926 59.100 10GY 8 14 0.3091 0.5247 59.100 10GY 8 16 0.3043 0.5578 59.100 10GY 8 18 0.2987 0.5919 59.100 10GY 8 20 0.2918 0.6255 59.100 10GY 8 22 0.2846 0.6564 59.100 10GY 8 24 0.2781 0.6840 59.100 2.5G 8 2 0.3053 0.3404 59.100 2.5G 8 4 0.3009 0.3614 59.100 2.5G 8 6 0.2952 0.3851 59.100 2.5G 8 8 0.2896 0.4065 59.100 2.5G 8 10 0.2829 0.4301 59.100 2.5G 8 12 0.2743 0.4554 59.100 2.5G 8 14 0.2661 0.4780 59.100 2.5G 8 16 0.2563 0.5045 59.100 2.5G 8 18 0.2451 0.5309 59.100 2.5G 8 20 0.2339 0.5561 59.100 2.5G 8 22 0.2221 0.5799 59.100 2.5G 8 24 0.2091 0.6033 59.100 5G 8 2 0.3009 0.3359 59.100 5G 8 4 0.2924 0.3523 59.100 5G 8 6 0.2822 0.3702 59.100 5G 8 8 0.2723 0.3865 59.100 5G 8 10 0.2613 0.4026 59.100 5G 8 12 0.2489 0.4191 59.100 5G 8 14 0.2368 0.4348 59.100 5G 8 16 0.2240 0.4500 59.100 5G 8 18 0.2103 0.4652 59.100 5G 8 20 0.1956 0.4806 59.100 5G 8 22 0.1821 0.4940 59.100 7.5G 8 2 0.2981 0.3326 59.100 7.5G 8 4 0.2874 0.3464 59.100 7.5G 8 6 0.2754 0.3608 59.100 7.5G 8 8 0.2639 0.3733 59.100 7.5G 8 10 0.2515 0.3867 59.100 7.5G 8 12 0.2380 0.4002 59.100 7.5G 8 14 0.2254 0.4125 59.100 7.5G 8 16 0.2120 0.4252 59.100 7.5G 8 18 0.1980 0.4372 59.100 7.5G 8 20 0.1845 0.4492 59.100 10G 8 2 0.2957 0.3293 59.100 10G 8 4 0.2828 0.3403 59.100 10G 8 6 0.2693 0.3512 59.100 10G 8 8 0.2564 0.3611 59.100 10G 8 10 0.2430 0.3710 59.100 10G 8 12 0.2282 0.3811 59.100 10G 8 14 0.2148 0.3903 59.100 10G 8 16 0.2012 0.3992 59.100 10G 8 18 0.1866 0.4086 59.100 10G 8 20 0.1734 0.4164 59.100 2.5BG 8 2 0.2940 0.3268 59.100 2.5BG 8 4 0.2791 0.3351 59.100 2.5BG 8 6 0.2647 0.3429 59.100 2.5BG 8 8 0.2500 0.3500 59.100 2.5BG 8 10 0.2352 0.3566 59.100 2.5BG 8 12 0.2196 0.3630 59.100 2.5BG 8 14 0.2057 0.3681 59.100 2.5BG 8 16 0.1915 0.3732 59.100 2.5BG 8 18 0.1759 0.3782 59.100 5BG 8 2 0.2919 0.3228 59.100 5BG 8 4 0.2752 0.3278 59.100 5BG 8 6 0.2588 0.3318 59.100 5BG 8 8 0.2419 0.3352 59.100 5BG 8 10 0.2264 0.3383 59.100 5BG 8 12 0.2101 0.3412 59.100 5BG 8 14 0.1958 0.3432 59.100 5BG 8 16 0.1814 0.3450 59.100 7.5BG 8 2 0.2900 0.3183 59.100 7.5BG 8 4 0.2718 0.3200 59.100 7.5BG 8 6 0.2525 0.3198 59.100 7.5BG 8 8 0.2352 0.3198 59.100 7.5BG 8 10 0.2184 0.3196 59.100 7.5BG 8 12 0.2010 0.3188 59.100 7.5BG 8 14 0.1868 0.3179 59.100 7.5BG 8 16 0.1721 0.3168 59.100 10BG 8 2 0.2894 0.3152 59.100 10BG 8 4 0.2686 0.3130 59.100 10BG 8 6 0.2489 0.3099 59.100 10BG 8 8 0.2302 0.3063 59.100 10BG 8 10 0.2120 0.3025 59.100 10BG 8 12 0.1937 0.2978 59.100 10BG 8 14 0.1788 0.2936 59.100 2.5B 8 2 0.2897 0.3124 59.100 2.5B 8 4 0.2668 0.3067 59.100 2.5B 8 6 0.2462 0.3000 59.100 2.5B 8 8 0.2264 0.2923 59.100 2.5B 8 10 0.2066 0.2839 59.100 2.5B 8 12 0.1877 0.2752 59.100 5B 8 2 0.2908 0.3096 59.100 5B 8 4 0.2671 0.2998 59.100 5B 8 6 0.2457 0.2888 59.100 5B 8 8 0.2237 0.2761 59.100 7.5B 8 2 0.2922 0.3077 59.100 7.5B 8 4 0.2688 0.2956 59.100 7.5B 8 6 0.2472 0.2821 59.100 7.5B 8 8 0.2252 0.2668 59.100 10B 8 2 0.2935 0.3062 59.100 10B 8 4 0.2718 0.2911 59.100 10B 8 6 0.2512 0.2760 59.100 10B 8 8 0.2294 0.2587 59.100 2.5PB 8 2 0.2957 0.3047 59.100 2.5PB 8 4 0.2758 0.2879 59.100 2.5PB 8 6 0.2562 0.2709 59.100 5PB 8 2 0.2974 0.3039 59.100 5PB 8 4 0.2798 0.2861 59.100 5PB 8 6 0.2614 0.2670 59.100 7.5PB 8 2 0.3003 0.3034 59.100 7.5PB 8 4 0.2856 0.2846 59.100 7.5PB 8 6 0.2702 0.2648 59.100 10PB 8 2 0.3027 0.3035 59.100 10PB 8 4 0.2911 0.2848 59.100 10PB 8 6 0.2792 0.2649 59.100 10PB 8 8 0.2677 0.2443 59.100 2.5P 8 2 0.3048 0.3040 59.100 2.5P 8 4 0.2962 0.2850 59.100 2.5P 8 6 0.2881 0.2671 59.100 2.5P 8 8 0.2800 0.2488 59.100 5P 8 2 0.3065 0.3047 59.100 5P 8 4 0.3012 0.2868 59.100 5P 8 6 0.2963 0.2704 59.100 5P 8 8 0.2914 0.2534 59.100 5P 8 10 0.2870 0.2380 59.100 7.5P 8 2 0.3107 0.3070 59.100 7.5P 8 4 0.3114 0.2915 59.100 7.5P 8 6 0.3114 0.2785 59.100 7.5P 8 8 0.3116 0.2626 59.100 7.5P 8 10 0.3116 0.2497 59.100 7.5P 8 12 0.3117 0.2370 59.100 10P 8 2 0.3131 0.3084 59.100 10P 8 4 0.3175 0.2955 59.100 10P 8 6 0.3213 0.2829 59.100 10P 8 8 0.3250 0.2700 59.100 10P 8 10 0.3282 0.2582 59.100 10P 8 12 0.3312 0.2470 59.100 10P 8 14 0.3342 0.2349 59.100 2.5RP 8 2 0.3154 0.3100 59.100 2.5RP 8 4 0.3239 0.3000 59.100 2.5RP 8 6 0.3327 0.2898 59.100 2.5RP 8 8 0.3406 0.2793 59.100 2.5RP 8 10 0.3479 0.2699 59.100 2.5RP 8 12 0.3552 0.2594 59.100 2.5RP 8 14 0.3621 0.2496 59.100 5RP 8 2 0.3180 0.3120 59.100 5RP 8 4 0.3308 0.3052 59.100 5RP 8 6 0.3440 0.2978 59.100 5RP 8 8 0.3570 0.2900 59.100 5RP 8 10 0.3685 0.2828 59.100 5RP 8 12 0.3818 0.2742 59.100 7.5RP 8 2 0.3200 0.3136 59.100 7.5RP 8 4 0.3360 0.3092 59.100 7.5RP 8 6 0.3521 0.3042 59.100 7.5RP 8 8 0.3682 0.2983 59.100 7.5RP 8 10 0.3830 0.2930 59.100 7.5RP 8 12 0.4002 0.2859 59.100 10RP 9 2 0.3205 0.3155 78.660 10RP 9 4 0.3400 0.3140 78.660 10RP 9 6 0.3590 0.3118 78.660 2.5R 9 2 0.3210 0.3168 78.660 2.5R 9 4 0.3445 0.3179 78.660 2.5R 9 6 0.3665 0.3183 78.660 5R 9 2 0.3240 0.3188 78.660 5R 9 4 0.3495 0.3226 78.660 5R 9 6 0.3734 0.3256 78.660 7.5R 9 2 0.3263 0.3210 78.660 7.5R 9 4 0.3551 0.3283 78.660 7.5R 9 6 0.3812 0.3348 78.660 10R 9 2 0.3284 0.3233 78.660 10R 9 4 0.3600 0.3348 78.660 10R 9 6 0.3880 0.3439 78.660 2.5YR 9 2 0.3320 0.3273 78.660 2.5YR 9 4 0.3641 0.3422 78.660 2.5YR 9 6 0.3927 0.3550 78.660 5YR 9 2 0.3353 0.3325 78.660 5YR 9 4 0.3668 0.3509 78.660 5YR 9 6 0.3948 0.3659 78.660 7.5YR 9 2 0.3380 0.3377 78.660 7.5YR 9 4 0.3679 0.3585 78.660 7.5YR 9 6 0.3950 0.3763 78.660 7.5YR 9 8 0.4220 0.3930 78.660 10YR 9 2 0.3392 0.3430 78.660 10YR 9 4 0.3677 0.3668 78.660 10YR 9 6 0.3941 0.3877 78.660 10YR 9 8 0.4199 0.4069 78.660 2.5Y 9 2 0.3390 0.3472 78.660 2.5Y 9 4 0.3655 0.3738 78.660 2.5Y 9 6 0.3910 0.3972 78.660 2.5Y 9 8 0.4154 0.4186 78.660 2.5Y 9 10 0.4370 0.4369 78.660 2.5Y 9 12 0.4569 0.4527 78.660 5Y 9 2 0.3378 0.3504 78.660 5Y 9 4 0.3621 0.3799 78.660 5Y 9 6 0.3858 0.4071 78.660 5Y 9 8 0.4080 0.4319 78.660 5Y 9 10 0.4275 0.4529 78.660 5Y 9 12 0.4455 0.4719 78.660 5Y 9 14 0.4602 0.4869 78.660 5Y 9 16 0.4711 0.4977 78.660 5Y 9 18 0.4782 0.5049 78.660 5Y 9 20 0.4830 0.5092 78.660 7.5Y 9 2 0.3365 0.3527 78.660 7.5Y 9 4 0.3591 0.3832 78.660 7.5Y 9 6 0.3811 0.4123 78.660 7.5Y 9 8 0.4019 0.4392 78.660 7.5Y 9 10 0.4201 0.4622 78.660 7.5Y 9 12 0.4369 0.4829 78.660 7.5Y 9 14 0.4503 0.4993 78.660 7.5Y 9 16 0.4595 0.5104 78.660 7.5Y 9 18 0.4663 0.5188 78.660 10Y 9 2 0.3349 0.3537 78.660 10Y 9 4 0.3558 0.3852 78.660 10Y 9 6 0.3761 0.4155 78.660 10Y 9 8 0.3957 0.4450 78.660 10Y 9 10 0.4120 0.4694 78.660 10Y 9 12 0.4271 0.4920 78.660 10Y 9 14 0.4393 0.5101 78.660 10Y 9 16 0.4477 0.5225 78.660 10Y 9 18 0.4540 0.5320 78.660 2.5GY 9 2 0.3321 0.3539 78.660 2.5GY 9 4 0.3499 0.3866 78.660 2.5GY 9 6 0.3670 0.4178 78.660 2.5GY 9 8 0.3834 0.4490 78.660 2.5GY 9 10 0.3973 0.4761 78.660 2.5GY 9 12 0.4108 0.5028 78.660 2.5GY 9 14 0.4212 0.5237 78.660 2.5GY 9 16 0.4288 0.5383 78.660 2.5GY 9 18 0.4354 0.5508 78.660 5GY 9 2 0.3284 0.3534 78.660 5GY 9 4 0.3437 0.3861 78.660 5GY 9 6 0.3572 0.4179 78.660 5GY 9 8 0.3698 0.4497 78.660 5GY 9 10 0.3810 0.4791 78.660 5GY 9 12 0.3911 0.5082 78.660 5GY 9 14 0.3993 0.5329 78.660 5GY 9 16 0.4058 0.5541 78.660 5GY 9 18 0.4108 0.5699 78.660 7.5GY 9 2 0.3198 0.3500 78.660 7.5GY 9 4 0.3274 0.3793 78.660 7.5GY 9 6 0.3351 0.4111 78.660 7.5GY 9 8 0.3414 0.4415 78.660 7.5GY 9 10 0.3471 0.4735 78.660 7.5GY 9 12 0.3518 0.5042 78.660 7.5GY 9 14 0.3551 0.5339 78.660 7.5GY 9 16 0.3581 0.5654 78.660 7.5GY 9 18 0.3602 0.5920 78.660 10GY 9 2 0.3124 0.3454 78.660 10GY 9 4 0.3144 0.3711 78.660 10GY 9 6 0.3153 0.4008 78.660 10GY 9 8 0.3157 0.4259 78.660 10GY 9 10 0.3155 0.4558 78.660 10GY 9 12 0.3139 0.4829 78.660 10GY 9 14 0.3115 0.5129 78.660 10GY 9 16 0.3079 0.5440 78.660 10GY 9 18 0.3032 0.5748 78.660 2.5G 9 2 0.3058 0.3400 78.660 2.5G 9 4 0.3018 0.3606 78.660 2.5G 9 6 0.2966 0.3846 78.660 2.5G 9 8 0.2912 0.4054 78.660 2.5G 9 10 0.2851 0.4275 78.660 2.5G 9 12 0.2786 0.4491 78.660 2.5G 9 14 0.2711 0.4726 78.660 2.5G 9 16 0.2630 0.4966 78.660 5G 9 2 0.3017 0.3357 78.660 5G 9 4 0.2933 0.3519 78.660 5G 9 6 0.2832 0.3697 78.660 5G 9 8 0.2735 0.3854 78.660 5G 9 10 0.2639 0.4001 78.660 5G 9 12 0.2528 0.4160 78.660 7.5G 9 2 0.2987 0.3323 78.660 7.5G 9 4 0.2882 0.3461 78.660 7.5G 9 6 0.2763 0.3607 78.660 7.5G 9 8 0.2652 0.3738 78.660 7.5G 9 10 0.2545 0.3855 78.660 7.5G 9 12 0.2419 0.3985 78.660 10G 9 2 0.2965 0.3293 78.660 10G 9 4 0.2840 0.3402 78.660 10G 9 6 0.2703 0.3513 78.660 10G 9 8 0.2574 0.3618 78.660 10G 9 10 0.2457 0.3702 78.660 10G 9 12 0.2325 0.3796 78.660 2.5BG 9 2 0.2947 0.3267 78.660 2.5BG 9 4 0.2805 0.3349 78.660 2.5BG 9 6 0.2652 0.3433 78.660 2.5BG 9 8 0.2509 0.3507 78.660 2.5BG 9 10 0.2382 0.3568 78.660 5BG 9 2 0.2930 0.3232 78.660 5BG 9 4 0.2768 0.3287 78.660 5BG 9 6 0.2599 0.3338 78.660 5BG 9 8 0.2437 0.3378 78.660 5BG 9 10 0.2301 0.3405 78.660 7.5BG 9 2 0.2911 0.3188 78.660 7.5BG 9 4 0.2728 0.3208 78.660 7.5BG 9 6 0.2543 0.3220 78.660 7.5BG 9 8 0.2361 0.3225 78.660 7.5BG 9 10 0.2215 0.3226 78.660 10BG 9 2 0.2907 0.3159 78.660 10BG 9 4 0.2700 0.3140 78.660 10BG 9 6 0.2501 0.3118 78.660 2.5B 9 2 0.2909 0.3125 78.660 2.5B 9 4 0.2680 0.3073 78.660 5B 9 2 0.2919 0.3102 78.660 5B 9 4 0.2675 0.3005 78.660 7.5B 9 2 0.2937 0.3087 78.660 7.5B 9 4 0.2688 0.2961 78.660 10B 9 2 0.2949 0.3076 78.660 10B 9 4 0.2712 0.2924 78.660 2.5PB 9 2 0.2975 0.3063 78.660 5PB 9 2 0.2991 0.3057 78.660 7.5PB 9 2 0.3015 0.3052 78.660 10PB 9 2 0.3038 0.3054 78.660 10PB 9 4 0.2910 0.2850 78.660 2.5P 9 2 0.3050 0.3051 78.660 2.5P 9 4 0.2963 0.2865 78.660 5P 9 2 0.3067 0.3060 78.660 5P 9 4 0.3003 0.2870 78.660 7.5P 9 2 0.3107 0.3081 78.660 7.5P 9 4 0.3117 0.2928 78.660 7.5P 9 6 0.3120 0.2788 78.660 10P 9 2 0.3128 0.3094 78.660 10P 9 4 0.3176 0.2966 78.660 10P 9 6 0.3218 0.2845 78.660 2.5RP 9 2 0.3149 0.3108 78.660 2.5RP 9 4 0.3234 0.3010 78.660 2.5RP 9 6 0.3322 0.2910 78.660 5RP 9 2 0.3172 0.3126 78.660 5RP 9 4 0.3301 0.3060 78.660 5RP 9 6 0.3431 0.2988 78.660 7.5RP 9 2 0.3190 0.3141 78.660 7.5RP 9 4 0.3350 0.3099 78.660 7.5RP 9 6 0.3512 0.3052 78.660 munsell/tests/0000755000176200001440000000000012657216233013102 5ustar liggesusersmunsell/tests/testthat.R0000644000176200001440000000007012657216233015062 0ustar liggesuserslibrary(testthat) library(munsell) test_check("munsell")munsell/tests/testthat/0000755000176200001440000000000013307646022014736 5ustar liggesusersmunsell/tests/testthat/test-alter.R0000644000176200001440000000463513306551227017156 0ustar liggesusers context("Lightening/darkening colours") test_that("Lightening a light colour gives white", { expect_equal(lighter("5PB 9/4"), "N 10/0") expect_equal(lighter("N 9/0"), "N 10/0") expect_equal(lighter("N 10/0 "), "N 10/0") expect_equal(lighter(c("N 9/0 ", "N 10/0 ")), c("N 10/0", "N 10/0")) }) test_that("Darkening a dark colour gives black", { expect_equal(darker("N 0/0"), "N 0/0") expect_equal(darker("5PB 1/4"), "N 0/0") }) test_that("Negative darkening lightens", { expect_equal(lighter("5PB 2/4", -1), darker("5PB 2/4", 1)) }) context("Saturate/desaturate colours") test_that("Saturation edge cases", { expect_equal(desaturate("5PB 2/2"), "N 2/0") expect_equal(saturate("5PB 2/32"), "5PB 2/34") }) test_that("Saturation/desaturate opposites", { expect_equal(desaturate("5PB 2/4"), saturate("5PB 2/4", -1)) expect_equal(desaturate(saturate("5PB 2/10")), "5PB 2/10") }) context("Complement colours") test_that("Complement",{ expect_equal(complement("2.5R 2/2"), "2.5BG 2/2") expect_equal(complement("10G 2/2"), "10RP 2/2") expect_warning(complement("N 10/0"), "grey") }) context("Hues") test_that("hue edges",{ expect_equal(pbgyr("2.5R 2/2"), "10RP 2/2") expect_equal(rygbp("10RP 2/2"), "2.5R 2/2") expect_warning(rygbp("N 10/0"), "[Gg]rey") }) context("Handling NAs") test_that(" NA handler", { expect_equivalent(na_handle(na.exclude(NA), numeric(0)), as.numeric(NA)) # vector vector expect_equal(na_handle(na.exclude(c(NA, 1:2)), 3:4), c(NA, 3, 4)) # vector dataframe expect_equivalent(na_handle(na.exclude(c(NA, 1:2)), data.frame(x = 1:2, y = 4:5)), data.frame(x = c(NA, 1:2), y = c(NA, 4:5))) # dataframe vector expect_equivalent(na_handle(na.exclude(data.frame(x = c(NA, 1:2), y = c(NA, 4:5))), 1:2), c(NA, 1:2)) # dataframe dataframe expect_equivalent(na_handle(na.exclude(data.frame(x = c(NA, 1:2), y = c(NA, 4:5))), data.frame(x = 1:2, y = 4:5)), data.frame(x = c(NA, 1:2), y = c(NA, 4:5))) }) test_that("single NA", { expect_error(lighter(NA), "zero") expect_error(saturate(NA),"zero") expect_error(rygbp(NA), "zero") expect_error(complement(NA), "zero") }) test_that("NA with colour", { expect_equal(lighter(c(NA, "10RP 2/2")), c(NA, lighter("10RP 2/2"))) expect_equal(saturate(c(NA, "10RP 2/2")), c(NA, saturate("10RP 2/2"))) expect_equal(rygbp(c(NA, "10RP 2/2")), c(NA, rygbp("10RP 2/2"))) expect_equal(complement(c(NA, "10RP 2/2")), c(NA, complement("10RP 2/2"))) }) munsell/tests/testthat/test-convert.R0000644000176200001440000000175113307367774017540 0ustar liggesuserscontext("Testing missing value conversion") test_that("NAs handled in convert", { expect_error(mnsl2hvc(c(NA)), "zero") expect_equal(hvc2mnsl(mnsl2hvc(c(NA, "10RP 2/2"))), c(NA, "10RP 2/2")) }) test_that("NAs handled in checks", { expect_equal(check_mnsl(NA), as.character(NA)) expect_equal(in_gamut(NA), as.logical(NA)) #wtf expect_equal(check_mnsl(c(NA, "10RP 2/2")), c(NA, "10RP 2/2")) }) context("Out of gamut colors") test_that("Fix gets passed along to `in_gamut()`", { expect_equal(mnsl("5PB 5/10", fix = TRUE), mnsl("5PB 5/10")) expect_equal(mnsl("5PB 5/14", fix = TRUE), mnsl("5PB 5/12")) }) test_that("Converting out of gamut colors generate warnings", { expect_warning(mnsl("5PB 5/14"), "fix") expect_warning(mnsl(rygbp("2.5G 8/12")), "fix") }) test_that("Altering out of gamut colors don't generate warnings", { expect_equal(lighter("5R 6/12"), "5R 7/12") expect_equal(rygbp("2.5G 8/12"), "5G 8/12") expect_equal(complement("2.5RP 8/12"), "2.5G 8/12") })munsell/NAMESPACE0000644000176200001440000000106012657230023013145 0ustar liggesusers# Generated by roxygen2: do not edit by hand export(check_mnsl) export(chroma_slice) export(complement) export(complement_slice) export(darker) export(desaturate) export(fix_mnsl) export(hue_slice) export(hvc2mnsl) export(in_gamut) export(lighter) export(mnsl) export(mnsl2hex) export(mnsl2hvc) export(mnsl_hues) export(pbgyr) export(plot_closest) export(plot_hex) export(plot_mnsl) export(rgb2mnsl) export(rygbp) export(saturate) export(seq_mnsl) export(text_colour) export(value_slice) import(colorspace) importFrom(methods,as) importFrom(stats,na.exclude) munsell/NEWS.md0000644000176200001440000000375113307545012013035 0ustar liggesusersVersion 0.5.0 ============================================================================== * Passing `...` to `complement()` deprecated * Fix bug where fix = TRUE couldn't be passed to mnsl(), issue (#10). Thanks to @bryanhanson * Fix to work with ggplot2 2.2.1.9000 * move README images to folder that CRAN can find Version 0.4.3 ============================================================================== * many fixes to remove R CMD check notes/warnings fixes issue (#5) * fix bug that gave incorrect greys * add functions rygbp and pbgyr to change the hue of a colour * add function mnsl2hvc to pull apart a munsell string * reimplement altering functions to make use of mnsl2hvc and hvc2mnsl * fix plot_mnsl to show multiple swatches of identical colour * lighter, darker, saturate and desaturate take an additional argument 'steps' to specify how many steps to take. Version 0.4.2 ============================================================================== * hues with zero chroma are now defined but are named using the corresponding grey (i.e. 5B 0/4 is equivalent to N 0/4) (fixes issue #3) * fixed slice_complement to display correct colours (issue #2). Version 0.4.1 ============================================================================== * fixed plot_hex to preserve order of colours (fix courtesy of https://github.com/sebastian-c) Version 0.4 ============================================================================== * fixed plotting functions to work with new themeing system in ggplot2 0.9.2 Version 0.3 ============================================================================== * put lookup code data in the right place to avoid namespace problems. Version 0.2 ============================================================================== * added a NAMESPACE and removed package dependencies - colorspace is now imported, and ggplot2 is only a suggestion - you don't need it if you're using munsell only for colour choice, not for visualising the space. munsell/R/0000755000176200001440000000000013307543466012145 5ustar liggesusersmunsell/R/check.r0000644000176200001440000001164613307543436013412 0ustar liggesusers#' Checks for valid Munsell colours #' #' Checks user supplied munsell specification for validity. #' I.e. colour is of form "h v/c" and h, v and c take valid values. #' @param col a character vector representing Munsell colours. #' @param fix passed on to \code{\link{fix_mnsl}}. Use \code{fix = TRUE} to #' fix "bad" colours #' @return a character vector containing the input colours. If any colours #' were outside the gamut they will be represented by NA. #' @export #' @examples #' check_mnsl(c("5R 5/8","2.5R 9/28")) #' @keywords internal #' @importFrom methods as #' @importFrom stats na.exclude check_mnsl <- function(col){ col_na <- na.exclude(col) col <- toupper(as.vector(col_na)) # check format right.format <- grep("^[N]|([0-9]?.?[0-9][A-Z]{1,2})[ ][0-9]?.?[0-9]/[0-9]?.?[0-9]{1,2}$", col) if (length(right.format) != length((col))) { if (length(right.format) == 0) {bad.cols <- paste(col, collapse = ", ")} else {bad.cols <- paste(col[-right.format], collapse = ", ")} stop("some of your colours are not correctly formatted:", bad.cols) } #check hues hues <- gsub("[0-9 /.]", "", col) act.hues <- c("N", "R", "YR", "Y", "GY", "G", "BG", "B", "PB", "P", "RP") good.hue <- hues %in% act.hues if (!all(good.hue)){ bad.hue <- paste(hues[!good.hue], "in", col[!good.hue], collapse = "; ") act.hue.str <- paste(act.hues, collapse = ", ") stop("you have specified invalid hue names: ", bad.hue, "\n hues should be one of ", act.hue.str) } col.split <- lapply(strsplit(col, "/"), function(x) unlist(strsplit(x, " "))) col.split <- lapply(col.split, gsub, pattern = "[A-Z]", replacement = "") step <- as.numeric(sapply(col.split, "[", 1)) values <- as.numeric(sapply(col.split, "[", 2)) chromas <- as.numeric(sapply(col.split, "[", 3)) act.steps <- c(seq(2.5, 10, by = 2.5), NA) good.step <- step %in% act.steps if(!all(good.step)){ bad.step <- paste(step[!good.step], "in", col[!good.step], collapse = "; ") act.step.str <- paste(act.steps, collapse = ", ") stop("you have specified invalid hue steps: ", bad.step, "\n hues steps should be one of ", act.step.str) } good.value <- values == round(values) & values <= 10 & values >= 0 if(!all(good.value)) { bad.value <- paste(values[!good.value], "in", col[!good.value], collapse = "; ") stop("some colours have values that are not integers between 0 and 10: ", bad.value) } good.chroma <- (chromas %% 2) == 0 if(!all(good.chroma)) { bad.chroma <- paste(chromas[!good.chroma], "in", col[!good.chroma], collapse = "; ") stop("some colours have chromas that are not multiples of two: ", bad.chroma) } na_handle(col_na, col) } #' Checks if a Munsell colour is defined in RGB space #' #' Not all possible correctly formatted Munsell colours result in a colour #' representable in RGB space. This function checks if the colour is #' representable. #' @param col a character vector representing Munsell colours. #' @param fix passed on to \code{\link{fix_mnsl}}. Use \code{fix = TRUE} to #' fix "bad" colours #' @return a character vector containing the input colours. If any colours #' were outside the gamut they will be represented by NA. #' @export #' @importFrom stats na.exclude #' @examples #' in_gamut(c("5R 5/8","2.5R 9/28")) #' @keywords internal in_gamut <- function(col, fix = FALSE){ col <- na.exclude(col) positions <- match(col, munsell.map$name) hex <- munsell.map[positions, "hex"] if(any(is.na(hex))){ bad.colours <- paste(col[is.na(hex)], collapse = ", ") if(!fix){ warning("some specified colours are undefined. You could try fix = TRUE") col[is.na(hex)] <- NA } else{ col[is.na(hex)] <- fix_mnsl(col[is.na(hex)]) } } na_handle(col, as.vector(col)) } #' Fix an undefined Munsell colour #' #' Takes correctly specified but undefined colours and outputs something #' sensible. Normally this happens when the chroma is too high. So, here #' sensible means the colour with the same hue and value and maximum defined #' chroma. #' @param col a character vector representing Munsell colours. #' @return a character vector containing the fixed colours. #' @export #' @examples #' fix_mnsl(c("5R 5/8","2.5R 9/28")) #' @keywords internal fix_mnsl <- function(col){ col.split <- lapply(strsplit(col, "/"), function(x) unlist(strsplit(x, " "))) max.chroma <- function(colour.args){ hue.value <- munsell.map[munsell.map$hue == colour.args[1] & munsell.map$value == colour.args[2] & !is.na(munsell.map$hex),] hue.value[which.max(hue.value$chroma), "name"] } unlist(lapply(col.split, max.chroma)) } #' Munsell hues #' #' Returns a character vector of the Munsell hues in hue order starting at 2.5R and excluding grey ("N"). #' @return a character vector containing the hue values. #' @export #' @examples #' mnsl_hues() mnsl_hues <- function(){ as.character(unique(munsell.map$hue)[-1]) }munsell/R/plot.r0000644000176200001440000003116313307362626013307 0ustar liggesusers#' Default munsell plot theme #' #' Removes unnecessary clutter in plots #' @keywords internal #' @param bg.col takes colour to use as background colour theme_munsell <- function(bg.col = "white") { ggplot2::theme( panel.grid.major = ggplot2::element_line(colour = NA), panel.grid.minor = ggplot2::element_line(colour = NA), panel.background = ggplot2::element_rect(fill = bg.col), plot.background = ggplot2::element_blank(), axis.line = ggplot2::element_line(colour = NA), axis.ticks = ggplot2::element_blank(), axis.text = ggplot2::element_blank(), axis.title = ggplot2::element_blank(), legend.background = ggplot2::element_blank(), legend.key = ggplot2::element_blank(), legend.text = ggplot2::element_text(), legend.title = ggplot2::element_text()) } #' Plot hex colours #' #' Quick way to look at a set of hex colours. #' @param hex.colour character vector specifying colours in hex form #' @param back.col specification of background colour of display #' @return A ggplot object #' @export #' @examples #' plot_hex("#000000") #' plot_hex(c("#000000","#FFFFFF")) plot_hex <- function(hex.colour, back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } if(length(hex.colour) == 1) { add.ops <- list(ggplot2::geom_text(ggplot2::aes(label = names))) } else add.ops <- list(ggplot2::facet_wrap(~ names)) df <- data.frame(colour = hex.colour, names = factor(hex.colour, levels=hex.colour), x = 0, y = 0) ggplot2::ggplot(data = df, ggplot2::aes(x = x, y = y)) + ggplot2::geom_tile(ggplot2::aes(fill = colour)) + ggplot2::scale_fill_identity() + add.ops + ggplot2::scale_x_continuous(expand = c(0, 0)) + ggplot2::scale_y_continuous(expand = c(0, 0)) + ggplot2::coord_fixed(ratio = 1) + theme_munsell(back.col) } #' Plot a munsell colour #' #' Takes munsell text specifications and plots colour squares of them. #' @param cols character vector specifying colours in Munsell form #' @param back.col specification of background colour of display #' @param ... passed to \code{\link{check_mnsl}}. Add fix = TRUE to fix "bad" colours() #' @return A ggplot object #' @export #' @examples #' plot_mnsl("5R 5/6") #' plot_mnsl("5R 5/6", back.col = "grey40") #' p <- plot_mnsl(c("5R 6/6", "5Y 6/6", "5G 6/6", "5B 6/6", "5P 6/6"), #' back.col = "grey40") #' p #' # returned object is a ggplot object so we can alter the layout #' summary(p) #' p + ggplot2::facet_wrap(~ num, nrow = 1) plot_mnsl <- function(cols, back.col = "white", ...){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } add.ops <- NULL if(length(cols) > 1) { add.ops <- list(ggplot2::facet_wrap(~ num)) } cols <- check_mnsl(cols) cols <- in_gamut(cols, ...) df <- data.frame(num = 1:length(cols), names = factor(cols, levels = c(unique(cols))), hex = mnsl2hex(cols), x = 0 , y = 0, stringsAsFactors = FALSE) df$labels <- factor(df$names, levels = c(unique(cols), "NA")) df$labels[is.na(df$labels)] <- "NA" ggplot2::ggplot(data = df, ggplot2::aes(x = x, y = y)) + ggplot2::geom_tile(ggplot2::aes(fill = hex)) + add.ops + ggplot2::geom_text(ggplot2::aes(label = labels, colour = text_colour(as.character(names)))) + ggplot2::scale_x_continuous(expand = c(0, 0))+ ggplot2::scale_y_continuous(expand = c(0, 0))+ ggplot2::coord_fixed() + theme_munsell(back.col) + ggplot2::scale_fill_identity() + ggplot2::scale_colour_identity() + ggplot2::theme(strip.background = ggplot2::element_blank(), strip.text = ggplot2::element_blank()) } #' Plot all colours with the same hue #' #' Plots slices of the Munsell colour system where hue is constant. #' @param hue.name character vector of the desired hues. Or "all" for all hues. #' @param back.col colour for the background #' @return ggplot object #' @export #' @examples #' hue_slice("5R") #' hue_slice(c("5R", "5P")) #' \dontrun{hue_slice("all")} hue_slice <- function(hue.name = "all", back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } if (any(hue.name == "all")) { return( ggplot2::ggplot(ggplot2::aes(x = factor(chroma), y = factor(value)), data = munsell.map) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col) + ggplot2::facet_wrap(~ hue) + ggplot2::scale_x_discrete("Chroma", expand = c(0, 0)) + ggplot2::coord_fixed(ratio = 1) + ggplot2::scale_y_discrete("Value", expand = c(0, 0)) + theme_munsell(back.col) + ggplot2::scale_fill_identity() ) } else { if (!all(hue.name %in% munsell.map$hue)) stop("invalid hue names") ggplot2::ggplot(ggplot2::aes(x = factor(chroma), y = factor(value)), data = subset(munsell.map, hue %in% hue.name)) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col, size = 1) + ggplot2::geom_text(ggplot2::aes(label = name, colour = text_colour(name)), angle = 45, size = 2) + ggplot2::scale_colour_identity() + ggplot2::scale_x_discrete("Chroma") + ggplot2::scale_y_discrete("Value", expand = c(0.125, 0)) + theme_munsell(back.col) + ggplot2::scale_fill_identity() + ggplot2::facet_wrap(~ hue) } } #' Plot all colours with the same value #' #' Plots slices of the Munsell colour system where value is constant. #' @param value.name integer vector of the desired values. #' @param back.col colour for the background #' @return ggplot object #' @export #' @examples #' value_slice(2) #' value_slice(c(2, 4)) #' # all values #' \dontrun{value_slice(1:10)} value_slice <- function(value.name = 1:10, back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } if (!all(value.name %in% munsell.map$value)) stop("invalid Value") ggplot2::ggplot(ggplot2::aes(x = hue, y = factor(chroma)), data = subset(munsell.map, value %in% value.name & hue != "N" & !is.na(hex))) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col) + ggplot2::coord_polar() + ggplot2::scale_x_discrete("Hue") + ggplot2::scale_y_discrete("Chroma") + ggplot2::facet_wrap(~ value) + theme_munsell(back.col) + ggplot2::scale_fill_identity() } #' Plot all colours with the same chroma #' #' Plots slices of the Munsell colour system where chroma is constant. #' @param chroma.name integer vector of the desired values. #' @param back.col colour for the background #' @return ggplot object #' @export #' @examples #' chroma_slice(2) #' chroma_slice(18) #' # Maybe want to delete text and add axis instead #' p <- chroma_slice(18) #' p$layers[[2]] <- NULL # remove text layer #' p + ggplot2::theme(axis.text = ggplot2::element_text(), #' axis.text.x = ggplot2::element_text(angle = 90, hjust = 1)) #' # all values #' \dontrun{chroma_slice(seq(0, 38, by = 2))} chroma_slice <- function(chroma.name = seq(0, 26, by = 2), back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } if (!all(chroma.name %in% munsell.map$chroma)) stop("invalid Chroma") ggplot2::ggplot(ggplot2::aes(x = hue, y = value), data = subset(munsell.map, chroma %in% chroma.name & hue != "N")) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col) + ggplot2::geom_text(ggplot2::aes(label = name, colour = text_colour(name)), angle = 45, size = 2) + ggplot2::scale_colour_identity() + ggplot2::scale_x_discrete("Hue") + ggplot2::scale_y_continuous("Value") + ggplot2::coord_fixed(ratio = 1/4) + ggplot2::facet_wrap(~ chroma) + theme_munsell(back.col) + ggplot2::scale_fill_identity() } #' A vertical slice through the Munsell space #' #' Plot a hue and its complement at all values and chromas #' @param hue.name character string of the desired hue. #' @param back.col colour for the background #' @return ggplot object #' @export #' @examples #' complement_slice("5PB") #' complement_slice("5R") #' complement_slice("10G") complement_slice <- function(hue.name, back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } if (length(hue.name) > 1) stop("complement_slice currently only takes one hue") if (!hue.name %in% munsell.map$hue) stop("invalid hue name") comp.hue <- mnsl2hvc(complement(hvc2mnsl(hue.name, 2, 2)))$hue munsell.sub <- subset(munsell.map, hue == hue.name | hue == comp.hue) munsell.sub <- within(munsell.sub, { chroma <- ifelse(hue == comp.hue, -1, 1) * chroma hue <- factor(hue, levels = c(comp.hue, "N", hue.name)) }) ggplot2::ggplot(ggplot2::aes(x = chroma, y = value), data = munsell.sub) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col, size = 1) + ggplot2::geom_text(ggplot2::aes(label = name, colour = text_colour(name)), angle = 45, size = 2) + ggplot2::scale_fill_identity() + ggplot2::scale_colour_identity() + ggplot2::scale_x_continuous("Chroma") + ggplot2::scale_y_continuous("Value") + ggplot2::facet_grid(. ~ hue, scales = "free_x") + theme_munsell(back.col) } # # slice <- function(hue = NULL, chroma = NULL, value = NULL) { # if (!requireNamespace("ggplot2", quietly = TRUE)) { # stop("ggplot2 needed for this function to work. Please install it.", # call. = FALSE) # } # spec <- as.list(match.call())[-1] # cols <- merge(munsell:::munsell.map, expand.grid(spec)) # vars <- names(spec) # varying <- c("hue", "chroma", "value")[!(c("hue", "chroma", "value") %in% vars)] # if (length(vars) == 1){ # print(ggplot(cols, aes_string(varying[1], varying[2])) + # geom_tile(aes(fill = hex), size = 1) + # geom_text(aes(label = name, colour = text_colour(name)), # angle = 45, size = 2) + # scale_fill_identity() + # scale_colour_identity() + # coord_fixed() + # theme_munsell()) # } else if (length(vars) == 2){ # print(ggplot(cols, aes_string(varying[1], 1)) + # geom_tile(aes(fill = hex), size = 1) + # geom_text(aes(label = name, colour = text_colour(name)), # angle = 45, size = 2) + # scale_fill_identity() + # scale_colour_identity() + # coord_fixed() + # theme_munsell()) # } # cols[order(cols$hue, cols$chroma, cols$value), "name"] # } #' Plot closest Munsell colour to an sRGB colour #' #' Take an sRGB colour and plots it along with the closest Munsell colour (using \code{\link{rgb2mnsl}} to find it) #' @param R a numeric vector of red values or a 3 column matrix with the #' proportions R, G, B in the columns. #' @param G numeric vector of green values #' @param B numeric vector of blue values #' @param back.col colour for the background #' @seealso \code{\link{rgb2mnsl}} #' @return ggplot object #' @export #' @examples #' plot_closest(0.1, 0.1, 0.3) #' plot_closest(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) plot_closest <- function(R, G = NULL, B = NULL, back.col = "white"){ if (!requireNamespace("ggplot2", quietly = TRUE)) { stop("ggplot2 needed for this function to work. Please install it.", call. = FALSE) } closest <- rgb2mnsl(R, G, B) ncolours <- length(closest) rgbnames <- apply(round(sRGB(R, G, B)@coords, 2), 1, paste, collapse = ", ") little.df <- data.frame(type = rep(c("actual", "closest"), each = ncolours), hex = c(hex(sRGB(R,G,B)), mnsl2hex(closest)), name = c(rgbnames, closest), x = rep(c(0, 0), each = ncolours), y = rep(1:ncolours, 2), text.colour = rep(text_colour(closest), 2)) ggplot2::ggplot(data = little.df, ggplot2::aes(x = x, y = y)) + ggplot2::geom_tile(ggplot2::aes(fill = hex), colour = back.col, size = 2) + ggplot2::geom_text(ggplot2::aes(label = name, colour = text.colour), size = 2) + ggplot2::scale_colour_identity() + ggplot2::coord_fixed(ratio = 1) + theme_munsell(back.col) + ggplot2::scale_fill_identity()+ ggplot2::facet_wrap(~ type) } #' Get text colour #' #' Get the appropriate text colour for writing on a munsell colour. #' @param a character vector of munsell colours #' @return a vector of "black" or "white" #' @export #' @keywords internal text_colour <- function(cols){ values <- mnsl2hvc(cols)[, "value"] ifelse(values >4, "black", "white") }munsell/R/alter.r0000644000176200001440000001636713307543466013454 0ustar liggesusers#' Make a munsell colour lighter #' #' Increases the value of the Munsell colour. #' @param col character vector of Munsell colours #' @param steps number of steps to take in increasing value #' @return character vector of Munsell colours #' @export #' @importFrom stats na.exclude #' @examples #' lighter("5PB 2/4") #' cols <- c("5PB 2/4", "5Y 6/8") #' p <- plot_mnsl(c(cols, lighter(cols), lighter(cols, 2))) #' p + ggplot2::facet_wrap(~ names, ncol = 2) #' # lighter and darker are usually reversible #' lighter(darker("5PB 2/4")) #' # unless you try to pass though white or black #' lighter(darker("5PB 1/4")) lighter <- function(col, steps = 1){ col <- na.exclude(col) col_hvc <- mnsl2hvc(as.vector(col)) col_hvc[, "value"] <- col_hvc[, "value"] + steps # check edge cases whites <- col_hvc[, "value"] >= 10 blacks <- col_hvc[, "value"] <= 0 if (any(whites | blacks)){ col_hvc[whites, "hue"] <- "N" col_hvc[whites, "value"] <- 10 col_hvc[whites, "chroma"] <- 0 col_hvc[blacks, "hue"] <- "N" col_hvc[blacks, "value"] <- 0 col_hvc[blacks, "chroma"] <- 0 } na_handle(col, hvc2mnsl(col_hvc)) } na_handle <- function(naobj, res){ nas <- attr(naobj, "na.action") if(is.null(nas)) return(res) if (is.vector(res) & is.vector(as.vector(naobj))){ keep <- rep(NA, length(naobj) + length(nas)) stopifnot(length(naobj) == length(res)) keep[-nas] <- 1:length(res) result <- res[keep] } else if(is.data.frame(res) & is.vector(as.vector(naobj))){ keep <- rep(NA, length(naobj) + length(nas)) stopifnot(length(naobj) == nrow(res)) keep[-nas] <- 1:nrow(res) result <- res[keep, ] } else if(is.vector(res) & is.data.frame(naobj)){ keep <- rep(NA, nrow(naobj) + length(nas)) stopifnot(nrow(naobj) == length(res)) keep[-nas] <- 1:length(res) result <- res[keep] } else if (is.data.frame(res) & is.data.frame(naobj)){ keep <- rep(NA, nrow(naobj) + length(nas)) stopifnot(nrow(naobj) == nrow(res)) keep[-nas] <- 1:nrow(res) result <- res[keep, ] } result } #' Make a munsell colour darker #' #' Decreases the value of the Munsell colour by 1. #' @param col character vector of Munsell colours #' @param steps number of steps to take in decreasing value #' @return character vector of Munsell colours #' @export #' @examples #' darker("5PB 3/4") #' cols <- c("5PB 3/4", "5Y 7/8") #' p <- plot_mnsl(c(cols, darker(cols), darker(cols, 2))) #' p + ggplot2::facet_wrap(~ names, ncol = 2) darker <- function(col, steps = 1){ lighter(col, steps = -steps) } #' Make a munsell colour more saturated #' #' Increases the chroma of the Munsell colour by step steps (multiples of 2). #' @param col character vector of Munsell colours #' @param steps number of steps to take in increasing chroma #' @return character vector of Munsell colours #' @export #' @importFrom stats na.exclude #' @examples #' saturate("5PB 2/4") #' cols <- c("5PB 2/2", "5Y 7/6") #' p <- plot_mnsl(c(cols, saturate(cols), saturate(cols, 2))) #' p + ggplot2::facet_wrap(~ names, ncol = 2) saturate <- function(col, steps = 1){ col <- na.exclude(col) col_hvc <- mnsl2hvc(as.vector(col)) col_hvc[, "chroma"] <- col_hvc[, "chroma"] + 2*steps greys <- col_hvc[, "chroma"] <= 0 if (any(greys)){ col_hvc[greys, "hue"] <- "N" col_hvc[greys, "chroma"] <- 0 } na_handle(col, hvc2mnsl(col_hvc)) } #' Make a munsell colour less saturated #' #' Decreases the chroma of the Munsell colour by one step steps (multiples of 2). #' @param col character vector of Munsell colours #' @param steps number of steps to take in decreasing chroma #' @return character vector of Munsell colours #' @export #' @examples #' desaturate("5PB 2/4") #' cols <- c("5PB 2/6", "5Y 7/8") #' p <- plot_mnsl(c(cols, desaturate(cols), desaturate(cols, 2))) #' p + ggplot2::facet_wrap(~ names, ncol = 2) desaturate <- function(col, steps = 1){ saturate(col, steps = -steps) } #' Find the complement of a munsell colour #' #' Finds the munsell colour with the same chroma and value but on the opposite #' side of the hue circle. The complement is not defined #' for greys (hue == "N"), and the function returns the grey untransformed. #' @param col character vector of Munsell colours #' @param ... deprecated #' @return character vector of Munsell colours #' @export #' @importFrom stats na.exclude #' @examples #' complement("5PB 2/4") #' cols <- c("5PB 2/4", "5Y 7/8") #' plot_mnsl(c(cols, complement(cols))) complement <- function(col, ...){ if(!missing(...)) warning("Passing `...` to `complement()` is deprecated", call. = FALSE) col <- na.exclude(col) col_hvc <- mnsl2hvc(as.vector(col)) greys <- col_hvc[, "hue"] == "N" inds <- match(col_hvc$hue, mnsl_hues()) col_hvc[, "hue"] <- mnsl_hues()[((inds + 20 -1) %% 40) + 1] if (any(greys)){ warning("Complement not defined for greys") col_hvc[greys, "hue"] <- "N" } na_handle(col, hvc2mnsl(col_hvc)) } #' Generate a sequence of Munsell colours #' #' Generates a sequence of Munsell colours. The sequence is generated by #' finding the closest munsell colours to a equidistant sequence of colours in #' LUV space. #' @param from character string of first Munsell colour #' @param to character string of last Munsell colour #' @param n number of colours in sequence #' @param fix Should colours outside of the gamut be fixed? #' Passed on to \code{\link{fix_mnsl}} #' @return character vector of Munsell colours #' @export #' @importFrom methods as #' @examples #' seq_mnsl("5R 2/4", "5R 5/16", 4) #' plot_mnsl(seq_mnsl("5R 2/4", "5R 5/16", 4)) #' plot_mnsl(seq_mnsl("5R 5/6", #' complement("5R 5/6"), 5)) seq_mnsl <- function(from, to, n, fix = FALSE){ cols <- in_gamut(c(from, to), fix = fix) if(any(is.na(cols))) stop("Colors must be in gamut") in.LUV <- munsell.map[match(cols, munsell.map$name), c("L", "U", "V")] LUV.seq <- matrix(c(seq(in.LUV$L[1], in.LUV$L[2], length = n), seq(in.LUV$U[1], in.LUV$U[2], length = n), seq(in.LUV$V[1], in.LUV$V[2], length = n)), ncol = 3) rgb2mnsl(as(LUV(LUV.seq), "sRGB")@coords) } #' Change the hue of a munsell colour #' #' Moves the hue of a munsell colour in the direction red->yellow->green->blue->purple->red #' @param col character vector of Munsell colours #' @param steps number of hue steps to take #' @return character vector of Munsell colours #' @export #' @importFrom stats na.exclude #' @examples #' my_red <- "10R 4/8" #' rygbp(my_red) #' plot_mnsl(c(my_red, rygbp(my_red, 2), rygbp(my_red, 4))) rygbp <- function(col, steps = 1){ col <- na.exclude(col) col_hvc <- mnsl2hvc(as.vector(col)) greys <- col_hvc[, "hue"] == "N" inds <- match(col_hvc$hue, mnsl_hues()) col_hvc[, "hue"] <- mnsl_hues()[((inds + steps -1) %% 40) + 1] if (any(greys)){ warning("Greys returned untransformed") col_hvc[greys, "hue"] <- "N" } na_handle(col, hvc2mnsl(col_hvc)) } #' Change the hue of a munsell colour #' #' Moves the hue of a munsell colour in the direction purple->blue->green->yellow->red->purple #' @param col character vector of Munsell colours #' @param steps number of hue steps to take #' @return character vector of Munsell colours #' @export #' @examples #' my_red <- "2.5R 4/8" #' pbgyr(my_red) #' plot_mnsl(c(my_red, pbgyr(my_red, 2), pbgyr(my_red, 4))) pbgyr <- function(col, steps = 1){ rygbp(col, steps = -steps) } munsell/R/sysdata.rda0000644000176200001440000015126412325541703014305 0ustar liggesusers]\G;[Qnow{{g %݉݅ݝ 7; *:̲;{3;&V2VhgggoO~MgKc.*35oߢmf|neg6;:},H>ҥvC|(GG_~d?9G#;>SȞzG/=rɑ+#w#O9O'GãQ(z-KESpM=-G~xzzQ"Ԯۮe?;>TBe*fOT%VڥPBe'T%Q:+P&5r.ۥPBuw&,QJ*RUBo_3L%%ɕˤJ>_eQڥPB?E&rGY7T9qgy|',e|w<'ڥPB?E-2-ARtJ2U~~TdإPB-|RtJ>*] N)T[*RQڥPBm<;mBouuqI#ug_w,6Pl`(4] N)T=gERaKOHK)Tq7Hu:)e'R%OӃ=K)ߕzP>z~]K)T}U}Ӌ?n`BS zGoуʹ] N)TկOJRtJ2U(n9KJRtJ.7 !?????????????w6%1ɹ&;kϮ}`KIl}YXLAԳg#C229s|ᅭ=sWx@PٺW=G3{y?Ѷs̿~֎?wJ}yjs/?{,OR3?J?WbwJ?dLÿ9~9zs [;%%mg3gO>[zg?;Yz>6߿7.վO1qԱ:6>??!};1~MɾԾ' Ï~?P?H?2mU'6KjT4/ʪ%V9CĪX4!_bK$V)1Zؠ(#M[0#&Vyc9.g*^6D,<(#g VeT[E,UVhK<0剴NY^ctUzFXzC0Sx}A?FžSW8FX[Wz4^[ԨMI>XʈcOJ3E* Dy_M*-DR jN "gia8C7i$I%zOZz('݈Q>EDѤed#F}b붯Jbx%1 %G#%c"HVTE *$ZSHI,mhX!%0"%TY=$PЊ RzM5R56$IV(>#%jhE$)yLZVRm% %S,(CRIcCD&5R*i%Zƀᑁex \'2idJ"bn4Fj"?Hi &= nR2ֺ؊F#0+F++++Ef˽5LfHW,jgbj"o_urW]T02q*•#]`# шt5"]1RF FPt`+8DHiMYVV1[hHIM) kaDi9I*1WDbڄh(LvhL;(F EYB&,4mLZ;X C%&R'Wm4^[, /sCh`'"mWmU[0(@BeܐxmGbO-,&2`WmiY$K m<ф/wEe8-& , U1*b=Fg^1j&>i`)D᢬h0yѦ9kdR$E^d"H-h1k!f@88A E0CiQ h# qRZ a"lE 6FfA% H3jL&ƌIf irG!`1F:b: H܌k0!=}|ъJa1Ehyd :ZOM"§8Tx\%kڄ= TDZ;ϫ2b.)#rLc6"_sB%B 8FL&-;?mxX5:F[KZP( >%a/) 6~2"-F6LmŔ/laoU0"}%B2VKKYHƋ?Ftc1pg{`d/*g/_NH`Y-KLFc_+r. 9rHEc6</Z\wD&H Fkb56GY=XUαk8cz2&ISHαf?ʪ/i[Q15ySAz4D}DI4wGrMڪW&O>c؅=6Yb A#0cZ{ܪ^&|0g&֚0a*\nLk籗4^Ark$zm7>yE6-[ 6WWV'gqU^Z3ɐYWlaSTjVSy SrZO Z<"ǖ*LjSV!<-zJ\J ٰ8M?#?<Pw Rkdji,Ro&$ACEd>^bSȽ#M"eDa)_taXc<ڳ%@xFjYl6L_rIh!iOZA0`}2a jQ $ŀ$"$)sl"H$ F&`(bRFzeEiaGmD 0CKyAӢڈ/7"I{ZV=k0e`xS2Z2$)&=idT($KFl slZS%#9"" p`Fޤ.;u 9|0k{@c9&.aF,xWc_ZFLߩ=I bT^ UPMɥP4H;0Kapj΀oвOAmphXDQVHUoaP&Zz_$'W!v D>7ZڀMi(*ƦXNPto'؀)ɔ:D5f|M*,Ġh'q(1&zXmD &1'҅d).iWN(A&ibԸ!P%$4%K& [Ei(S O㛪1Ka?0gi\&iݠk)=p'ufA9lYˠgS4LaD SmA$t"mK'ZA/aԬF.=&/h~%q"V'S }*e4*.FV 8c4.=sBdHLvkMhy5q4"60E. F5L"f0f8ƈ0ⴘzaFoDX0& pj7(| @k0f4ŗCps0 Em֢?!Fj|Je|i2?jϛƿBe!dPXOſMiF`gr VrNR fh19 o4}IIh5`dmT x"nXda"'Ee~-<$LX>h^匬 ɚ7VKzZ-L,yT8"M3xIB1i%ŢP6Vs.3A(ZRFLcb' / j9R!#'G*V` Y4 ̣S#cyƀYm^ͱXLתUm^`4.FQG/^E`sFgiN#"xL@N(EV4cIUZl+MQ8A%0*:*aQz*a ^1boIJ,qj<5 G3jlF:~co,zh—FfOS w Y(kj-#IiEF5YxUD=・9w{ˀOX:U̸1b8~rT<0P+2-GݤQ؀zQ'#hԪ(&z C?UO%@ Jc9Zǯ8~'NZ/bjl5 &6Rz aXZ!,`SC0z=65$j 65d4U&!41bMXl #h ,яcdSc^#fi#ɬEnVmr+3xEfELHٱԅk&w$ڈ"4|FyC˱xRPc r~ c+wJ^<,ljW2Y"V\k"I)uHōl C`Cdw2*Te$_IGqdx/Z1L-5:[ca0?C1A?Xتc-6/C6PᱩI7& [XgDl K4hE[ FT!v6 /K (PZl+F1a9^7]8`1=6A%gLa&ZOs?r8=OBh5 K鍼f,3jTGp"bkXָP&LSU(ZkVg-¾š( ai=̜ j14qd Wo2X&!ޑrZKѥ *0GTqcjR aBk9 k*ED̉Dg҃"VLiIFbP`"xldd_[ f?iyXPcF ?"6qH]_5NKaJGaQpњ?"0Id}'oAj lFCYtm&X9&²QcZa=!UAMQ 6z e5<͇'(a &=%bsb5h*|R#Fŗ( 0XbYI!V~e8lVE3 3cb`񫏓DZ!ō)0 >#"8KE*k%PXM<_BF2>`MG-3qJh1eO*'&LF>/8:i:{R,Zb8Z#ۯdO(H&q/a3Fs`s^2YYJ#22o|??G!Li,4ȽhxІ Yi#s |WaU-x|G.-b){Lj!~Y͐S82b`"_h= 4GEH-Z%̘T N4oeK3#hj Iπ!b7݋\E=Ɩx>j z —eY^MJ`-5F{&Fw mBu13ZH>45*{-6*jQTEɶvB2UfjycE)  /hL ( O$[ ^321Y}Πl L̪4)FMp2ioxP˄K9 &Hװda0ꑮa446,6"`EcPˌڈoMǿvboXOeUȟ1h㮒E3fR0֢^?Ʊ E&kb=0ci@fE#`LV Kf1ꔈD0ClP<. ~@QK9i">f(1/6TT2[ZMlUmZMl'ZM٪F/ZM*RjV9Cjj5eZ6_j5UA/ZM٪AZMlKVSjgdgi"*KEW(+4^a W8mbEZXHO2a JVD!,Q:OԵD]]& ~h& ~hԠ%` >X%` >l-Hy>O )dڤBI )dZBA (dڣ⻚B5 (dB- (~) (dZB! ~(Jn(嚡RRJ>( J.(嚠L(mi] p8pC# G04ah8pC# G04ah8# G04ah8p ͏G7.O h&I>hfTY*KReI,I%"MЧ 4A&}o~tXKa :,Af[<>ODIơڱDJF’o艔|"RQDJ>HG)("%E䣈|"RQD >HG)("UIz,A%=~j"RQD< o%^/ˏ7|F z4 B&n )d B&f )d" B&^ p)d B&V P)d"&POq!RDH! 7&}=L2RG$(+0dqdqdqdqdqdqdqdqdqdqdqdqdqdqdqdqdqߕ:,A%tlBG@G@Ul8DOh.sؾg<%O~Fɓ}*'򪖤Kr.-KrwQ|&.p(r +`s珶xy[-^V22JmɖSZ-nPG "AQD1(#bKR.Jh*傩3{2TR)J-$pXOR(Q}fO $c4M2F$c4M2FY|$,K|$,ɇ&IKg IO zd~,B ~+~J2]V4Y!cE2X޾RU/a9Vs[#l5Gj՜ [#l5Gja9Vsl%$ "&Id6#l4Gh'm4Gdadm Z D޽|&)H>$I $gpZU^^N>-Or>-O' HrR+'I%WEmU=Zv%7!z7!z7o'8OD~h&I~h&I&eI,I%$џO|$xOyN-L)W2\ŔrSK)W.\rRjyB&)zkRCJ)NrQuG)\o?5FyyT=IH‘# G4(iP8ҠpA w0G#iG8Ҏp?kG8ҎpH;‘vi;B4͓Md]HtdebG"NuD#MЧ 4A&u=XKYNh'w船++++~$}Oi>MЧ ɖoXKc z?-wvr T)d2IB&O 4)dIB&GJB&C )dIB&; (~Jn2QdF!/ɋB&-|a94MA|4MA|$'.wȽ D] rᅣ=vyݿ_Z&S‚<%,S‚<%,S‚<%,S¸<}~7%,S‚<%,S‚<%,S‚<%,|}mA)aANmv5;IHrD3D ! $g@$9Cpiv'Oh}JB""vD3D !&2f,I%$UʒTWbX%`I>X'I>x'I>NdL +{)+] mu:ZΨ/ANYQSVIwB@[Q(VHP`(VX+ ['xxx~o5TRfjT([Y=VLkK|fQD!,Q:OԵD]Z D ~h& ~ E` >X%` >Xy>O ` Inp_N1Br!,G1Br!,GkS!Mb#!f=BYb#!vq !>B|P!xs'xs' !fEBY͝ 2S0O!C< 2SȰN!C: 2S|8+ÚRjJ9)倦$컔(9%JNS(9%eR]5m ȔrSAL)0-nC-C, h7n,L dwZsGxoqGxoqGxoqGxoqGxoqGxoq%xo'' >x' >b\t8yH#7t޸D ?ǛK O)9@;s hMIbJܩKh%fɶas6O͓m'd =i/NrĒ-'ܐ7FQ|Y_yWyW9yW38V~cA٠lr6h9 Z+g`lr6X9 Ay9}^Ny9}A_L!}F} t(EС:?%OD?Yx D~[{<O\Hv?E[2<ﴓ,8KYԊB6a8r};!O <'8OВ'mp,Kd&Ih1d&Ih1d%cIX1d%cI~ A. d'I6x d e sd1 cu:/`$R(RV)+ mE[lYZgZgZO.ZH.%rR!J)(rpRʡI)&rPR!I)$r0RʡH)"e }X9}VNgY9}VNNeirQQF)eذ'@%=) @IOIdICt(ė.MK&c"!d{H'yqpGzqpGzq$0F$c4M2F$c4ɘw?,KÒ$?,KÒXrG# d'I6x|3*g3ՙd-&PVt(+:[ZZM.XH7x/7 ?Qu3D%Q牺<ɴ8& ~h;kdK|,K|`\& Q­՝Lw2F-P9ӯ0D4+D~|ά=ݎ- >A)rz |2DN)Ra%ۜa!"*L!D])!ՀX·I*[2dcsG<.ϲ|ˮ#U@D%'huOQwEfU/ρnYQ"޹sͱ{\pm9 = ^C/Kh'=ZI{QMۙeŭ >g`5]>Dɧz#b>7yb;aڢDX/:+߆- >;Ӵf~ˎᡷڀy{lC#AmG=u*!>_ezJm>mzwӜZ |T }XI0|f|J;?CCK /+_ܩ\t AlRc<w+Ky]"vSUq7Z@}}.O3_GsƛW@wl[>nH{Ҡ:׺2/Ԇ:B=N~qTb⠓{8h[[ 26>^VAq_N*A?դ_JCfdgͮ_8i\deݮ`^yԌھ~G?yc>n!xScgϵdyWxm=]OR$S۲z7:>u77׹C[ ϥ^A6g5=]莺Y%<*!丵+qj?(g7P ?{hjLm@CUߪ^.s܉R5$)=rts*= }V1z߀,m *# mZUbyë_|U>p$K˱H4t}˔B݊۾~$3aP`^jVE)N3>E #m53z\D;xigo9@=0\{ʈ^9V.pݤQJDn~y yf* tswHWyKNt>lbK&@\/p6bK!"J|l ?%e J_ݩQ&qw y >_Qo|Ы;~Y¶t"w^/}|ش9|qtՐ?IrͥBV h,Hk04=?{Wglyk{\'֓.uI0Ws>ٶ1I1oukK7_sÍKm^V3g?ܼ4a1б=AvyWlLCxX``ޑT=zwz_"9qf<gzt'6:5φinL#'p~h5d Y7J?0lܩrNQ†: 9K9E8ԹJ"1|\ix|u*B]7(eKӸYW[+Lݚ5[FXvɝG˳8 v"d3/񙾨t0a½ovBv`=.qK>L9YgӞnޔcqywԽHZ(v bl׈SuρȬaoDz҇^҇~MU0D;<^๤Sn;.^87 S6 ~HZzWvZ+#/'Qjl؅,/Qm ;n*xjgnѣ%՗W VPCq3WCBLCs! rU{T7xuA;^o~R{Rt]sk=.30#}8t|Gy<3m+n -i Tl \/@Dcjzȧ뀞dmVHOɀhWi|,0dg:v !7 x^E4{z Iĩ1Sz<,2L*d?6\:Xl;N,آR%Y Mb wf= z v"x>+1;7E2~@7lk؀vnîBL{1! ̚`DiS'];Ź<@Oݶ!5q[teAqӭ!vc'AtybEGmȵSaG{5\Yo7ߑ}`+ԟᨇDT'D]Tw,W6}gӡrasco;ŪʔZtM5Uro{ָre? Wjqf͛ߤ @~g"WYǃ[59w!a |Sfx__wHqٕkTٽtw.E0 13=vuG|x\C] 2V@kT3jy+G8vQkޕ=" ?^;2|@z}[% pXXa8OFs-ҧΜ3™yp&[%y>MAqntkeQ7h浯ƙhצ rNz50m??Y:j!1=nѣjzVXȠ7هsWAglrm7Dn%{@o.-ooWtaf,ٿ^nԹzcf@ ;}ɹ B]>=ʐ y#‘/LCX=}p|{[ Q#9ܼ[0-i=:Oևwco4zM[6nVVtMzN84>*a؃+_W5 t_uV~<  N G~mǟGr6(?@/o׊F"EFžz_F8~ʝF= pcX&pu7 Xmm拏+zѥ˓6.r`!OwDi+OEfOq렁~!k(jQRq+Y5}b; Nj[]ʽp:s_DmU5]'CZ{JRގ~hȞvKL@q[_f&͚\Dqˑ;H~ws{k9=o`Yak T)kK"E@h^Go7WGxAD}uڰNq6E{k&>Xl1;i?q ),;8\px=鸏?'=χDl̏+ֹ# uq6r<n6[fC-|r6gaOṽ㳻ꌐd9Ѐ6 !>'{Bdͧ4phu?E [.(u^{aQ\nACAIgoGwu =>~,"+5FǤ5kxD4w{B )}Lp,=ѾLw;ҹEoAUnwˢٽOm;\@~}-E\׋9#WQtj=蔫C!ݪ8umזxeH0_NmJ?YgC@v8Fώ#[waM>ōg3Hz#|7 fT&Sd'sÆy[?cr8/j}#ުACM'izW~Q))[{'@OSɧBr8QT`rep2|-Y=zy_UfOܵpBus-rwH=AwfUܗ8k֑ iX|{P,z~GmP>N|ϩۉ`э|ҷ[!ExhʑkF LhLr~~z,f&^dߛ#o$_=$GV[{ZG8zdQӢF푭7<{<Mȫ6j$DqgͰǹ~j>/ Xn0 yWe(g~@raH7$7̹,I ;jG7;|$i~` Ӟ(ֱ7f`7wӁw^{53?@ O״g]t,t ')tNFԤؓdzNAD{?WA~I]V_s]>EPv:̇^A).Bz/o 88v$o26iy>Rk|_Q@9Uh%d|~:WվylUlrWMz UɨLtWJpdQkVՍC~Ú#h 6LJMhgd(DT:mhB-`ծDپ=R0=„1uPt)9_7pQu*ɗG\ K+vDu}e̓:xt @{أv(~8ڤ9?'^xL@~Z.z!ѹ=?#Ǟp]}y>hNw 1C49n܊-HrnlFpYqЎҧUU;}ܲi/+r Ń՚ R+Q\94(<`앒SSW/77!w_j}q|~:cH{%!׆-Ӳmhb,?{;d7ӭ5=n{/BLf%Go^gVz}/DqV ~_e! b#krU&VgIӞ.ܱ/u2+?obU՞Mj"ZOhs_7A+.=~񙋠֘ A2u{V:қckL~Κ2@A`MdۣzXZ9#nؽū̃ _I/77S81$$N{fɧ8sCOI֝zgk#4Sd?w}܅лM^^cs_7qt @ŕF8:{;B>bF{6:P!&a- ;Ax8]xtsˎ qhU<Q?^k0˟_K{}6%I>ʼn+܍-W7#h,.٥+]ypɘ$ EW%{ӄz|ރqdnm:K2! xû mYQi/Uq 0 DR;8˒wcލtө{=D8_،UM`>}g$τ܏C>:BDtV@w~掓#{U0ϗ\`>1gƸVwA~e _hIwr/e'!p–cФyk~'/?x:BH *)?.6*˕:6tqwvAvjQlF~8ʊ?n/?:{c-ܣN}Z? Nǂ@# GA:_D^+p1mө#w>Z݀vWA7c&!(R<'=?9B]sm JYuΞG޳7]! %~R$7dr;ϲicܘFel=wx , +>2gI|4_8 zFݢ~⠨ǽ'Dx9b޹L&H'v̑"w :BvA5A7kw F|u 4~kGhzCH/^_wZC2=p4~KߪSn5B̅pGJ&(>rU sO<5k7,}|US\=Х틕JL]sM#kyu~4>{N?E>}GW|tØv ޵{3o(?VSr}gkӂ? 9$^y>e@'~/b{o*駞/QY/cx ;ڔ]bJ_ze/gcO:QIŕɞ?o0̍e; no]ykrېh^VRmce_A[/mW*}s/8u4>>a/04~'>̌E9km ^iZo^zAumP\lYnm^$Wq7@x0ݝ?TZsEPH}D szǂӋCn|ȿz]`YW@.^M{BzmԨvX:{zv.wȽ|3q@l3(5!eZjV@ r7]Ȉho]?7c0\2Lh`dEk1Dp^//!|]vձ6ߧ*c} 6ԚAqJ옮x6ҿ*!pi+zg2md1\m3SN=.lh{"uzݦȳ >znG~ρgg#f~;+zL ՗--D,zqe >"]}̾ NzXsSd?VlBSD 8d-5̃{iiܵkd̴ڣӋwgMY"O1k!+<tS/|)Ɨۼr݄oqqIgOćn|ĻwCC J$ z;;ٛGKHm=(KX޸C{3k+U:"Vln4C9صIݗάa5WZ@j>b[v>GWi[As ..\pzN9B6+YG }@ܽ x8sbY51+/nмmz0*d:ѳ;ѳua-zLv7s/{gSk3h|d·ت+yI U0x1kN#ut'S \Wn\"9L]"`9!x괋nWC~FIE~B)(_oܥ@W{0rcK/s 5Z{T t6WwGGEk}l_(0W-o7;Hsla _wgs[޽ĎS&PS#kź߅Eץ-^BՍo}_D=E@a_rR̓ytH!-Vd܃>8; W0ƅZk0Ophs"/~MXfvUh>`.~Ǟ(~0^,t[LqAw~Ԩb6T>(-ȅpZesV@z-ܙʙs}NsҺaAiρ`^W}l*{:. HiuJ@mg9g49C#)k]L+#S4i1> wSf幊5vumUz ’L˒ .'C5VÑ8}5v@7ֳ a+5;#^/ďQc: 3SK]r:еwނ=j`^*~>G 8JbϙYi?S]wk!uBŬc[=a[N(r&oLo}YdKГ~5־8م*6~Pݦȿ;֡R[[=Ð_ ھn@X[иWS >x]Nxyz@O[[}_k\M܆y_ˇ-E׵oQdoܜ;zDd^+l[z$҇T8g$kLms$׉N?psG9.n}{Γ\zh_Iml|h=g)Lgךwut=;>nNAd5HM EvpMY/k94d1xvT6;>i\\2ȽddZB JqR^\V|zIoR̪HB{1 pxs &cݢT G' Tr bNWM!GyCz0)MVW\|]8z}ԘgA7ڌ|A(oWV>qg]6JNN~I1˸] 4G@,lz ޫ#+)"ʜ_ܹrxbΓE_f[isL^VAx7sX&=8*a>PF`i>y WCvw* 3ʔx].K^\{HC8]NGN(.Y1ΣI'Z"|"},k?On߾VqAխʡ!Xzm]\ ůu( ;C]_QO[Enۥ (Lˑ_zGw#]g[$kUd{o::,1KAWU!=:t%0D!Og $6v41lj`(.ps!'g[qQ߯+ nʬ:ޣsoӟ\zaݩh ?y)7,;,ҁnKE'qʰzs.}? Ì\uki_@eFE^GzB=e*?;Ř"wstSӏ\f޲E^&h: })~?u N {}vIˀG#Zc*ʵ|yîa_80/u;'e..Ch7 |P|Æ4ݑ_go]iy]3\Xop;!̴o.^Eqצ:CқGArhs(^޹O5…ms6X2+>_^aa]ד\,>Ad-;V7"kƉ?g> |ڄ9Bz<>lOYU{lv?mjke~寕 )V&CZZwjke¾寕 ŧV&쳟ZZ}ʄ:Tو<6k{Gr~c8F]WbK}QB)O[ykűU(zomZq,[x81ݱi4vwQ x(uf힆Pbryw~][sM?mDoaoy+'[z;@G/n5:~l۰=Ci/ hnN/-nx߅U x~Þ%g> Win=LG j/U]+1~Q;qY`E4RAi'6ך kj Np{Py S(Կymao$mqx6cdgvw_Ǎ9J@x9gJ^8:T\rAPIM-8+U_ވs^ U[שn]Ү+^=w]_qx]6'(,Pm(\jfz}]s ]{K\O{9CaOvG߁GOG}@WmV:eQRz߃zʶ}oGr Nm!`qScRACϥq`K/'|fLcf*Z=_}+%@~HCnBZۮLdBpFCզ[#9!|o@ c!*L!6=$BWf~]M 뫽YPPmí}^Q۱֭ם~Zޥ^׈l#GU%ә_t{ZqC~w_t|^]  Vχ3CVi}~|}FnK phtۆP݅sTu#4ezZ0`D;K@9s\m:0`부&M'k/ݓS#/Q*Z'[8lQBYsCK? "0 D,w5xT DT~jIW_n> j]k*oY_Qqz%XhwU{[a :8x;,9](q'x@b˝P,;fuߦPǒޓ2Wz66 +R{Gft--djU}\ n굳 )0uQJdᇭeOx ¬A9;A&}F|2N?e{qP~fuF)@5&;T~wsm d3ۖO['?h0">ۿRi&V0'D>smo+ *vԇP-KR~Ǎ-}?ibq?\.یZrOS}B*wY'd=J,c (1jc¡_lכ=@1Sk}'Ӫ|@-అ]ŮaRvr?:It.En=ؒwuR bA`lX6Ԋ}Lv|%_ θx m6dc>>+xwo(ѳrB M LW5OX?pmV~| $p)=S#s4 ᕲ[Wvo"6i߫Y)>]=L S-]?C-ZA ub75ZP=uy8y٫=/y8<^@o4ot.`th r=h`ֺw<٠b#B9KQ6([A{\3{ *`Tpvlev ![51-⠷>EC,AͧL@J|vٶz=EGBhڲZ)+lWMEvziU#l3v[zmno#N--=>Ҭ uNc¤mY|סɜSiދG+hF>8P[\ z\ ~u S`}k!4VLԦ1@j=@7x: ZlH0zgܘd! (]fnorZυcݿ ۽g݌rcUj2.0}ٛf/YܢgTF ?~ekRoڃ[Nx㕾T:ۻ!C[;m0ǶY1>h O z鍠v1wYpol;`g@-( l2=ýU,S4`n[Y$)F"֍t|w8W.=nc-rRiE`X=ppijW@lSb`C0ګ[f%-{ZK;.&Jٸz_W} 7I(nG$Ե8Aݦat-qΊ{9_̀_!] ~'ڇ~}cs}mARx5vM?!~Queێ I v~oo*Oacyޚo@ns؍!ϩ[K fWAިwԇVc@f1,M \>ԯ$xu4̲%gm9y\(;|;`xiR,b4NznXn\@^!pTpz}*s-3 |q'u6vŸq^'] }쮝8l >vfLW{ ⦉)M iE ׽* .=c 8=(~dkg!Gv9֬||9fz?sȯu)m w\=,׭2o7;A*&"EkgAXkf|TCˑ>ݯnkWT-sXku[Huqw:riBqw%MƗQn#_c'*-w(:μQ܈bG> sہW> i6WG|o{s\ ^ZxqOݿwθæ▿4LTML/[JW1v =4]Rڊˎ`Ž3jr̵ܝ= fW6uqDK0Xe[Uag}[^vSs͸*>tҗc3+IvYe$5Tٸ{ )z?=nOZ&K/N|.4>!){? "bI }ʫI{T)mОN}(>@#q)ͮ&.`ֱsKyڿ4&Zʳ`CR[RngCRE)[w=/84Ew sY$ޭ5Ws`/KK.R糊i#BkZ%x$cg+Fz%YV=ϸQlͻ%kl=$*sKms ij-rmhgJA挱yAN$вnRؾro=zjgYRC[m^;癔߯S&RGÃKHbR[BʥKE13{ ½a%iTsyHX9{"K>C>^TTlϨׯߘ4ՖTe/u(\f_>Jb׍%Vy>#7I/i6+OD;cj?rsg̼3iP_^FFZ} cfKCgooF%xksb%׶ ?`ی%C_#JR_h+M.Msnt3G rt 븥L>9r6;@ZI[Vr}i 5jO:M>}J{ZCwѬgkb.<3gT|j_בJjzГj ]8rW\Pرilsnғ-r=gAf$faVHܶYvHRWOhnH~&I*oAnÒE5V u+WALPϘJ $r7&,ZU .R~YpHqFPD2^XU4.3ݴOKCEc{ߟ6ɰ^*S>RْoWl?\ ^qoTaFGN}a_~JP ∔XDRu1K% LRr}mبRQih$wǑ?ܔCwiR@ٝ o-7~$v_^Z$r9UQ2x^;$Js8DKC܇@*]CPddNqMRoJJCL~ )4VsK-RbюR]K_PG9a2$|Sڦgԣ춭J>H*9]XO}ѤToWgn:?b%* ݣW2M.l'̷1ԡ8WJl(XswMXm}z+yܷ&sfS$ GV-( l=2G^Uk^J98!j9g`ӒVU^?<_>ٶK^~CNe|vʻFۗH/W%~H*Xf$}9H+,Ov)>R@rZcU8)Zߒ&4-. >b9?$rgn/ͷNn&U*]*兟?rbelTś,Rb!1Rn~t;W*r]QS%ōyg|mTӋT^}SRpEo%ڵ&.Wf*3xMR7 5K=&?(,z;=ouAa ^ M37d|&cYRWO]ޯ\؃FKy\d^6XV*;2K[ԟ!yݟ3kR\qwL|Uܙ}\^9ѧTr~ϣY:Ua:8WHt.ȧ2|'RH'/W:7KodSZK}9Ӓp2z$1kq%qijjK7LX&nC~Tf#}ӬR~Krۥ ϟ_&]'4Hߴv!?I>y:mVox&-_[!XS %]'t{HZY^ ƓNݸJ|" ޜ},)wRӗJ'/"=tH5JD+w*l\V۬|fO$A33,;<<[b/|$xҾVwx)8%.wg%FH| ,_aCzi Je2RH_ {\ F{Iɓ̭G2z-wb(V9E*Mks}?rmm3PR =Ar[-$y4lq䬒Y]nTWF\,y94*Nrܵ'jWZ̗ K̀&ڿW}XfkWv?^Gm%Ň^A*}K+jW^,49NrM]24t/sO#U=Jټjz!U#TȆlEk O$׽#N_ܢ煇 $7̓%v./[۲ =)1_,PzAG[Kt_Nk;K lJו!͛Rsǵ^ nr*͐^_j+H~}'>~zyc%nsSOd7J2,RsKʱ)V ¾doWķl_rwi_)>̓[B)"Z4fI/#ABw_I޶䔪E_]G>#G1m/Oqr-hL$[7.409O)on/PRϦ-6J6j'TsCWn3>o.mȾqm@1kN[<_L=J>㨍/½$6'KyzIlDucŗwj&D s\]UFLj)鲾ѕv M/3BҶ+| hovn{zy_}n%gLW%HOtk<82JrXYkErnlhf)m/FG{QmEml:||E6zUa*)ۀhvIE)H- mI.w Ms)Nr͟Q6Jn\ㇼ{f[GK\$ZMZAKT"xnRkv[)$89V6pTIO9MIyPuOK*wqe2GI7t4Fnu,1aCl/̧'I\̀ u,d({} %] $_\Fsڶʸ#U}{qX'uXS%Ǵ |m9q ;ѵ,urM HVo~ndt%}˝kŽ[;NR>QGr I;fs)s勖Ğ{\rqHkg窍$dWgʢeY9Q(3Y%kKyv8{+G:}Y)'/ jY^* T/Ž9׿ðْӥBu<ݕ. {&@ȈO@xM0ɽk}=.١zcls^>j'=jRE%Ur{D܂쒧/AS oz.]๧JYFotuD-/{8h.yuW*~z-D|2|:2 o0M95F,;f[ kowT]^doʓβkR͛>B|ؤT1v%59|Iʓ{ْgOw 3$Ux}֤[;n/y(3>Ob_G_r;(C[1{TMLn? |\?gu3>~1"rg)wz>xwՁ kOCⶅ>?i*y3n!ڮoVfY7{w?xWW> +^Xlx^Ůg[}^/}Qjqf/ְ2i#k`GI>]4{ͣGL |yuܧ,5^]~fs=}} omvz0'gnaZEHG_g+?йk _-K?A~Uہˡk-+\.[Zi(R-K@׫PPDiA)] k#pS[P <8 _| p=_Y+zߕ 굝%JaPЍkT:bFgQ5O{^6Ni(NPT>TPi9~,]j4E7ȣM^8_굜?a{=jPV3YvOz&#~>U5{ӑU)'ܱm͕m@n;Õ܇{5:?ܜh}-7 Y럮pmqs뷺jXlͫ j3 󫢯lޞ+n͍)QGx&?|]4uO-E[|=(FoA׆_򫕃 <ޤQ yD7 9ٛC_[n':t[픽sQoud m]pw%11FqyŞ02+/㹺/S%4{X[GBbgWi>SqjyR9a.l70#h~1aS=h`PkyZ*> 85`7_3pόYؓV&yIV n[4ෲ[tH^a"pkm}>Ky]=ҽ\;>8}ޱ9ӬN1꽹O¢:nGy^?=ug 9`2%Iy炙̾Ϳ]Zxy(](oK[{8CsϸuWl$]GӦs5NBQ7V9r,ܗT>=BP-(yUR8&x4hUkwK4jgrG=g>JTT\grI7=b?wn T†JWǃBmej~ռ7ӿ*t@U|ٳb׃Cn*fyx` j^Q]z;xhn?9hӝzuX o:wq ~g:^?/^ܵO۝WAb@^o_*u˥/ PrO&yA3EN"R3c)~~ .yM`Tkx,`- 0Ll2!o{-c<=S\U̳p۫BPv-7PzdÁ9(L ǮDх|㠌.hW QP_JRʝ(\^|cvm7fy!BU3θdæx!n/Fl|7c_1nCќ;#y .;kg2 ^H{bV$|Vt4w㫑C&61MڜrQǭ .+&6}.x,ꣶPrZwǮՇIח+oV6 |]{(YeKöo<q+wt#w2MnPc-Nr pk풱{w-]|@/٧8$GKgmNxyEJVPQF"]Н/K:֑f+W@i=.}r]rOOKM%~EXZ <յ\ ,.pn0ϒV6Yܱ`*}Q׷K fUz@c$9^-%wʎe F :0(fiaI/-U*8X?+& m3|}!zǎ87(zYi3_x_x&퇈joll6z.g΀7n<ӀOW7NdC [ wVmȬjԡv٠p?o\ <wd:0uܴm)c|PB{J砙[jo#F~My1'6jºƙB@ssni4L۾1[jzsNKz԰nOPPjn&R9/?JM;^ +w CϾ{OC3V'4W@l12ek0JSuVos}`zXa4g,BU_JW!y sUۻ=.4ԄُV ]8Z8iyPcĖBڽw@Rٗ&Oc_f_~)["S I+Dj8}t.? zg@Ϗs̷@tک٪V/7̓άA}g?JcFA~tGX}=tn7 Vmᔇ?x(L=`(ǯDã دΨAjtp|0ksFAXỮ1@X u/mVDGqbOAš-Z_En{T~WQ&^_}##m>/[ 1]}n 04JrNwN/»]Kz>a(`.:hδr(K+PfѰ[i4`YS%(ɶ,!$ǧG2q}O®̣NAsIoBx*!b͇܇ Z`*Qh^*=s *]XFwt-NumT}~7V׻4nY6 ߧ(r7gfuxCig\‡ndϢSsUBS'_ |tU0i5m7Pn+wc^c8ڦ[߃vsl@u#3>aE1{s Ƹ{UX D?߫g?w x[Цyzl(wuݴ PնaFՃrEE~Omҿ/ 2'@X!OB6(^x\+ۡ|6Tm%.v nXgQ;l|]!'8'=U6^|n ;Xo {8pb?qiGAڎ(e[9 9f0 9ADPlQ( f3(*b ,PL`΀H |Wg띹S9jS5tt"%`}]X[Gx`, (-~ 8%,ONScY 73V]\t𢕛-dv7oV zu CAm`$|>gnHLҗۣ+6 e`ӘAg!<>%£r`wcfX,m Lx"5o/L=H9tCn}O}' x~,l__F^M 5Fj'iZ;@is,HƿL^ Ngd`A7@j9|Uxwt1hzވ5QHv Ts] f՗cۅD@~IQM鳨VKZVamO)0^s"Mk"ѽgʼJ.z6y1[A9<..} V~$DmңnG4`a#Ƞ~U@)-; +]{`h 6J6;~(9SP f<^j0Qϝw9nw)S .Y L.sk5փ}MC`Ǘ `.$LR'Qi[-08#z,_d[yH|/wi>9F)iPXK GzY.:5f^U`?3vn;n"({n~!խvǀ 6k7&PQ}g3tTǂP6mPx"6hW 7Sn0st}N[kZT睚`t=0)s:r!2̾kWu/ov`\8U,[Ux@;2Y2>X-K`o,wI(h_V/PX[}lru};NI%8 sYN;ysq N:gn)s5Ѩr#5~u*ڡ8!I?\Ak)4gо` rm@$Qt0Y&H"^:wT̕ <0/j]4v_O m1UTPum.@lS |ʏ4hڀBuޢ=rp޶~Ja2 gӝQ-U@+rg_#QmJQ nж}f;rN\0ֈmWD@ ۇ3C@mzCn_< J?(cg-`f9s,̱K23X\ҶIOa@JpK^2I ]ATMش-ٹuiL({/ z3}N%%G,&cSp͹ˑ\#/g4Bwr~,I 8q^Hd; ΗLcE͚la{@p~p02x<}~漼hF/~O&({$EﭣuQTsזk9˔FwCm{%`T;z2L.g4}`Cʁtaua }*yH!572s_.X/Y|P0(kO?[F3sSnyrC(8Xh.4s_{p%CҜN:[ ցJMR7r*p(qn=Di)KNt|S5h,0fdԶe:zdg[Ao0t6`#+wze`x S, 7f f{),a[@3}SrآM@ᵏ{q$A]zQK/rdCпL" Zd~b>Ppn%E.;:r,g3Cfej0ֵ5h&W T͝sgq{5~G\B\hւ|Ȃ; ׁ|DF_] ߨFX\f|^XE`Q%`K=GB 2itLAT^\Eo*/p3tׁ;QI<5>|nx%9( V{4 M悻_~t^y-276gL沁BIk>>PQfr4< ]jHS2}|tE֢z>(m,caj*{`7oK2LD$nq27 `i~(H&7_3oO#˔3@fػlVYvl.R,)`$H8^><.r^E[`۸Cp\v|-̻b%.24M2p;ԿN/Ȇú{G,q.2s**i`b[+_Ne>4@XZVZ2wT@έ򝜀.ڶ^ wtXA.g /T wO\" twrU엁Yw|:zA|F;GGsq)AOr)8\ %OFȖKwځG[G +`&܃֯X3MOa캋JNQʻA&vp4;DC\(t8.CEUp;sWN ܸul 6~c \gK>qBSʴuC*kH@~ ㇵM);_np]8R6q˽% ߲c@_v*ME;ZAUpTvCb|% y?^-&uyRŸ0lTL~>ңޙ2P+08v`Z|:i 9pr S/dfdGf[t훹rKτF]op{mجީa+)&j5=pm8{KOùCl5mB`8˼gSR;@tA(֞Qj^GzL2VP#NBׄHO$Hwe-g2]ԼoħUu^e0hީt>@nK@ yM޻q~6m :Ow$aLCc`|<{?<3zOIz]Z X8l% aƅƜ4S7m ,O/?8lēBnyFd~ai|a_<-G`WoAٰ?᜜yxN6,3?RF*@덄&{A,0EqS!(uy+k5(i`' .m;CB~0z_[eʀcHwP&+_"v^+"E%N!/9٫N\aHkERo,qL-)yxㅼ_'Dn#ghdgK`ٟW I ,[.,TBX@OSQ|R>cumI_oG˽âdTv,ɴGoD)נ(pnM8pџ]/MJZnkEt˲i9[_!/N_B,ȴ/>GYfȒܛBCQ*eEJfCP ruczM(CpIEEL:ߐIkZs{|EPTe0կr_׷C9/W͋mC(ݘ{,»η5Dkʝ9!YLQ/7X.NsB}kQo8]},7$1'.V}NDqYm5tiu⢥g2lZnBoSTe2]JS%fH`#<__OL%_ΜǏzJ|Qvo ~FvBؓ48_^G _`N_Tw۸ e#V{D3 -|XU yqw<`xkFO$EiQ~jyK!G"شjNEG7K8bR& aDoԼ؞08O,pFۀ%/{&sU.W`Kj4]Ԍ #2SdTP@eQ{ ճ8$X:"ˎO ~G[͟ cG-jʮv4N;|:6MN^V!MMh%V%bZ$YRw$9+d=I>o:#b &]FBk=\3]L Z:]0F{4=5(Zӊ[_ً'-gi""\i{!?o-X*3B _se2a}u#:{&xg_Ïzr\TE |vYvI)EeЇ 4\y"֗vMa^hi@[_d; vT) dfx#fh\a >VC{sB>_┓:o]t'>]gM_.6.|b5M?bt"/Q%1C%f̉y$FIklO\^*T=jHUjeԽ35Tt ߧ!+B|q͝Ǒb3k!2m24v;8M꾷}ϺF ZhTWya?ObZcV%Z1ᤛ3ZZLAHI:O>"`zy'Ɗx~hB<3RDv)݈z _VOz^hepaO{GqEn%گqD>V=t^ㅋfFע[ᛥ$E8,͹~waFt:e2z>"FוFiqqdZg  _`V5{y.5WPu/!8}YJfnO޺E /H^؏SLr<0hCm ,2 ĠK_N7s[g1dD4~-2s}?.Q2tOkdQqUs e}TSd rA$o Â,QN*^ eΝyt7C>Yn",0WM(+ŢVhmfz0eYWGc]GǃԍRDڭ*jˑT.h_'ϰή[۴!yh>ԈeESL 6@=h0key?fWEoKոߣShQ3aܺҷzNbF.tz|,twQCIҝ5ߓݔ.5P{c(;`%Ur vC7G hj}!hq,% =o1^Gv 9V=sXQūcAVkcF#t}xz+Zпk7y2vɉĽ/֚aЉMLi'I;ނ_ W#tC2PzD.ZFhN挊J(MݧHp^jU K9flsO|QC-Xop8Sf,|tΗW玄vj4Mz/5sR-N1*s@ߣnZj'~9;7߰F櫂QzylE#̢ Yf{5&EG. )\ _ =*r\m]^brfo&6_=aФ]XIӲ{&4מ`'%џB}G΁jkKyzٓ PqC.Q hz%hI͕xAI%z^p+˂">5}kszQ:Dݎ^ *hΩ~kŗw.Ky)|^\=pȢ}|?gjG'= nHCX5G%-OBX 1ڶ(Jij(SQz}Žnu!%/E!/\ (y=3SbPZRkz|Il{x_Bx$8$]kB"5)!x%$'!fy`I""7޸w)/=:@FJ./ǂ6qʺh3Y60)R(Z Q=9@^}dۋBc5Aߖ|΍ `tzK;֗0fS /Yxٶѫ;c Mz5= 'h//JY=t[$>n4ӧdU߂ҭ's#/[7Wx\E\ *HJ2FLKyPgj5kG%SA~x\`CnT fj\c|tV\ߌ5v7fPm={{MT5*C vR SvTapԌRL8zɓ_hSG 4|a3 xDGuZ4`>|@}hko4^*Y'f?; @Uּ6esaAjHܩI{@RF뽷o&rvj/n|qn㱫}*hr⬋¸GT1\07}LwxIxq/951~N֡EW YʨEۭbej󂠐yM +aZ'SjWC"=ycL(BB.@Ik6m ӹjѐL'!s7iڡ^V_?5K XW?w M)w0.+Pٍ Uͻ -Ґ=H۹(]ݫ:JA6kzfEVxUH5&Ȯe㍷Pؽ=%U(A&jr|jCὁk{.oy|HXt4'ou^@객;)35:\nFM5E=MfcQh͸0F>1S:odühN U8N@g'i4L}^F-5xn# d[j uM{Ax"ubrwj5f|Pn~A}\YW{Qik~(8EaF;Jc&![L+nS /P#^\Lp`:Bv>SۻP}鸩$nu^ݔ,wEqiR'jO՛wxokS6% El]~!: ;k#|_|m!˄Ʊb~₅hEكb;$PdOz0(L*`y.N !y8P4Q?췅oFS]j-&b '6-ӹPGr?͙8ܾѓ9jLD2bGDHmOF~w^ȕ:vzS#J=Nk# )-0)Vt`׫펪e<|E87r}2w%O* OhHf B}"#qvԪ'xP,:|U: _V9Ve܊5J>oZ ԩg ^9uT2]"| 'F6ޣ.W풁5| ;N=ꬩBᙇg>:6vM(q,LXHnNm$2W,L|-=gNx^?8.yM>d7k9;_'7>o<? Ƴ9->_Bm# , },?#vulobbH#J3o޿=Ïr]/0m{E[B_o8%iEۯ005 0)munsell/R/munsell.r0000644000176200001440000000167112657214043014005 0ustar liggesusers#' Munsell colour system. #' #' @description #' This package makes it easy to access and manipulate the colours in the #' munsell colour system. The conversion from munsell specifications to sRGB based on the renotation data from \url{http://www.cis.rit.edu/mcsl/online/munsell.php} which is a digitization of Table 1 in Newhall, Nickerson & Judd (1943). The code for conversion can be found in the package directory in inst/raw/getmunsellmap.r #' @references S. M. Newhall, D. Nickerson, and D. B. Judd. Final report of the O.S.A. subcommittee on the spacing of the munsell colors. J. Opt. Soc. Am., 33(7):385-411, 07 1943. #' @references Munsell Renotation Data, RIT Munsell Color Science Laboratory. \url{http://www.cis.rit.edu/mcsl/online/munsell.php} #' @docType package #' @name munsell #' @aliases munsell package-munsell #' @import colorspace NULL globalVariables(c("hue", "value", "chroma", "name", "x", "y", "text.colour", "colour"))munsell/R/convert.r0000644000176200001440000001340713307367774014023 0ustar liggesusers#' Converts a Munsell colour to hex #' #' Take a character string representation of a Munsell colour and returns the #' hex specification of that colour #' #' Munsell colours are specified by hue, value and chroma. They #' take a form like "5PB 5/10" where the first characters represent the #' hue, followed by a space then the value and chroma separated by a "/". In #' this package value should be an integer in 0:10 and chroma an even number #' at most 24. Note that not all possible specifications result in #' representable colours. #' @param col a character string representing a Munsell colour. #' @param ... passed on to \code{\link{in_gamut}}. Use \code{fix = TRUE} to #' fix "bad" colours #' @return a character string specification of a hex colour #' @seealso \code{\link{check_mnsl}},\code{\link{in_gamut}}, \code{\link{hvc2mnsl}} #' @aliases mnsl2hex mnsl #' @export mnsl2hex mnsl #' @examples #' mnsl2hex("5PB 5/10") #' # use a munsell colour in a plot #' plot.new() #' rect(0, 0, 1 ,1 , col = mnsl("5R 5/10")) mnsl <- function(col, ...){ col <- check_mnsl(col) col <- in_gamut(col, ...) positions <- match(col, munsell.map$name) munsell.map[positions, "hex"] } mnsl2hex <- mnsl #' Converts a hue, chroma and value to a Munsell colour #' #' Takes separate specifications of hue, value and chroma and returns the #' text specification of that colour. #' #' Munsell colours are specified by hue, value and chroma. They #' take a form like "5PB 5/10" where the first characters represent the #' hue, followed by a space then the value and chroma separated by a "/". In #' this package value should be an integer in 0:10 and chroma an even number #' at most 24. Note that not all possible specifications result in #' representable colours. Regular recycling rules apply. #' @param hue a character vector of Munsell hues, or a 3 column data frame #' containing the hue value and chroma levels #' @param value a numeric vector of values #' @param chroma a numeric vector of chromas #' @param ... passed on to \code{\link{check_mnsl}}. Use \code{fix = TRUE} to #' fix "bad" colours #' @return a character string specification of a hex colour #' @seealso \code{\link{check_mnsl}}, \code{\link{mnsl2hex}} #' @export #' @importFrom stats na.exclude #' @examples #' hvc2mnsl("5PB", 5, 10) #' # All values of 5PB with chroma 10 #' hvc2mnsl("5PB", 1:9, 10) # note some are undefined #' plot_mnsl(hvc2mnsl("5PB", 1:9, 10)) hvc2mnsl <- function(hue, value = NULL, chroma = NULL, ...){ if(!(is.null(value) == is.null(chroma))) stop("specify both value and chroma") hcv <- hue if(!is.null(value)) { hcv <- cbind(hcv, value, chroma) } hcv <- na.exclude(hcv) selected <- paste(hcv[, 1], " ", hcv[, 2], "/", hcv[, 3], sep = "") selected <- check_mnsl(selected, ...) na_handle(hcv, selected) } #' Converts a Munsell colour to a hue, chroma and value triplet #' #' Takes a text specification of a Munsell colour and returns #' the hue, chroma and value triplet. #' #' Munsell colours are specified by hue, value and chroma. They #' take a form like "5PB 5/10" where the first characters represent the #' hue, followed by a space then the value and chroma separated by a "/". In #' this package value should be an integer in 0:10 and chroma an even number #' at most 24. Note that not all possible specifications result in #' representable colours. #' @param col a character vector of Munsell colours #' @param ... passed on to \code{\link{check_mnsl}}. Use \code{fix = TRUE} to #' fix "bad" colours #' @return a data frame with named columns hue, value and chroma containing the hue, #' value and chroma levels. #' @seealso \code{\link{check_mnsl}}, \code{\link{hvc2mnsl}} #' @importFrom stats na.exclude #' @export #' @examples #' mnsl2hvc("5PB 5/10") #' hvc2mnsl(mnsl2hvc("5PB 5/10")) mnsl2hvc <- function(col, ...){ col <- check_mnsl(col, ...) col <- na.exclude(col) if (length(col) == 0) stop("zero non-missing colours") col.split <- lapply(strsplit(col, "/"), function(x) unlist(strsplit(x, " "))) col_mat <- data.frame(do.call(rbind, col.split), stringsAsFactors = FALSE) colnames(col_mat) <- c("hue", "value", "chroma") col_mat[, "value"] <- as.numeric(col_mat[, "value"]) col_mat[, "chroma"] <- as.numeric(col_mat[, "chroma"]) na_handle(col, col_mat) } #' Converts an sRGB colour to Munsell #' #' Finds the closest Munsell colour (in LUV space) to the specified sRGB colour #' #' @param R a numeric vector of red values or a 3 column matrix with the #' proportions R, G, B in the columns. #' @param G numeric vector of green values #' @param B numeric vector of blue values #' @seealso \code{\link{plot_closest}} #' @export #' @importFrom methods as #' @examples #' rgb2mnsl(0.1, 0.1, 0.3) #' rgb2mnsl(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) #' plot_closest(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) rgb2mnsl <- function(R, G = NULL, B = NULL){ LUV.vals <- as(sRGB(R, G, B), "LUV")@coords # check for black if (any(LUV.vals[,"L"] == 0)){ LUV.vals[LUV.vals[,"L"] == 0, ] <- 0 } ncolors <- nrow(LUV.vals) dist.calc <- function(x, y) rowSums((rep(x, each = ncolors) - y) ^ 2) dists <- apply(munsell.map[, c("L", "U", "V")], 1, dist.calc, y = LUV.vals) if(is.null(dim(dists))) closest <- which.min(dists) else closest <- apply(dists, 1, which.min) munsell.map[closest, "name"] } RGB2mnsl <- function(rgb.cols){ LUV.vals <- as(rgb.cols, "LUV")@coords # check for black if (any(LUV.vals[,"L"] == 0)){ LUV.vals[LUV.vals[,"L"] == 0, ] <- 0 } ncolors <- nrow(LUV.vals) dist.calc <- function(x, y) rowSums((rep(x, each = ncolors) - y) ^ 2) dists <- apply(munsell.map[, c("L", "U", "V")], 1, dist.calc, y = LUV.vals) if(is.null(dim(dists))) closest <- which.min(dists) else closest <- apply(dists, 1, which.min) munsell.map[closest, "name"] } munsell/README.md0000644000176200001440000000634113307574343013225 0ustar liggesusers # munsell The `munsell` package provides easy access to, and manipulation of, the Munsell colours. The `munsell` package provides a mapping between Munsell’s original notation (e.g. “5R 5/10”) and hexadecimal sRGB strings suitable for use directly in R graphics. The package also provides utilities to explore slices through the Munsell colour tree, to transform Munsell colours and display colour palettes. Munsell devised his system of colour notation to match the three perceptual dimensions of colour: hue, value and chroma. His notation provides a naming scheme to colours that eases the choice of color according to a specific purpose. His century old advice is still relevant for the producers of statistical graphics and the munsell package aims to enable user to easily follow it. Functions in `munsell` fall into three basic use categories: specifying Munsell colours, altering Munsell colours and exploring the Munsell color space. The code below relies on the development version of `munsell`, get it with: ``` r devtools::install_github("cwickham/munsell") ``` ## Color specification Following Munsell, specifying colours is done with a specific string format: “H V/C” where H is a hue code (see `mnsl_hues()` for a list of those available, excluding “N”), V an integer in \([0, 10]\) specifying value, and C an even integer specifying chroma. The `mnsl` function takes the string and returns a hexadecimal RGB representation: ``` r library(munsell) mnsl("5R 5/10") #> [1] "#C65858" ``` Visually examining a colour can either be done by using `mnsl` with a base plotting call, or using `plot_mnsl` which plots colour swatches using `ggplot2`: ``` r plot.new() rect(0, 0, 1 ,1 , col = mnsl("5R 5/10")) plot_mnsl("5R 5/10") ``` ## Colour manipulation `munsell` provides convenience functions that alter a colour by taking steps in the hue, value and chroma dimensions: `rygbp`, `pbgyr`, `lighter`, `darker`, `saturate` and `desaturate`. ``` r my_blue <- "5PB 5/8" p <- plot_mnsl(c( lighter(my_blue, 2), my_blue, darker(my_blue, 2), desaturate(my_blue, 2), my_blue, saturate(my_blue, 2), rygbp(my_blue, 2), my_blue, pbgyr(my_blue, 2))) p ``` ![](man/figures/README-manipulate-blue-1.png) Each function optionally takes the number of steps to take in the dimension and consequently are easily used to create scales in a particular dimension. ``` r p <- plot_mnsl(sapply(0:6, darker, col = "5PB 7/4")) p + ggplot2::facet_wrap(~ num, nrow = 1) ``` ![](man/figures/README-palette-1.png) ## Colour space exploration Slices through the colour space of constant hue, chroma or value can be displayed using the functions: `hue_slice`, `chroma_slice` and `value_slice`. Additionally `complement_slice` displays a slice of constant hue, alongside a slice of its complement, the hue that is on the opposite side of the colour sphere to that specified. ``` r complement_slice("5R") ``` ![](man/figures/README-complement-slice-1.png) munsell/MD50000644000176200001440000000450213307646022012245 0ustar liggesusers8650a8395e9d6bba9893bc37ad82b170 *DESCRIPTION 87ef3467fce6d5a255c09d2c0f4e980b *LICENSE f2b196714119df71068365d96a78adca *NAMESPACE bd328b2da12ac6ec1070f9e86329c883 *NEWS.md 39682aa58a2762df2a063080bb8ef5c0 *R/alter.r c385fffc4bf275ee9d376f9f2fbdf28b *R/check.r 7de6cc3b3e130c8b9a72888ee516dd02 *R/convert.r 0c0d5c63bdba8c43db46acb682c79f98 *R/munsell.r 95f51be26cb0882c5d0893ae515e7b34 *R/plot.r a5f63509303f8527dcb119cbbf5c1dd2 *R/sysdata.rda 6f19335e6f50f01960c90e64912be628 *README.md 4c45c679a2b7365d48ee7f168b37ce77 *inst/raw/getmunsellmap.R 1a50e408003768c47b8ee59f96daf9f6 *inst/raw/greys.dat 17ec52f21d55878850b4323ab28122d3 *inst/raw/real.dat 831bfb993509eb617295f9a0694dd5fc *man/check_mnsl.Rd f9a1f6bde7f196d5f08304b5b7604ac6 *man/chroma_slice.Rd ba19b66d1dd174bab67c9c14c47bb5fa *man/complement.Rd 610936b742a5c4d61cb385149ef64b66 *man/complement_slice.Rd 87f0e1b0d0f11dc6c776ba117b67f85f *man/darker.Rd 424e73b71dfa4a940aed9d1bee29fc73 *man/desaturate.Rd 0437a4915ec1202d4edd135ae4a2165e *man/figures/README-complement-slice-1.png 1cc548d8918b7d403e2f0ac3e69a2bbb *man/figures/README-manipulate-blue-1.png a23b32894ced7dd72d8a2a2ebcede8e5 *man/figures/README-palette-1.png 9a6ed99bb177677d81baaadbf9ea5950 *man/fix_mnsl.Rd 1dd7a5f816d954db145b7f14db37baa2 *man/hue_slice.Rd 70cb94aa5417b8555c4c94d7420c1b36 *man/hvc2mnsl.Rd 1192d2674be2285240584d65913e6b7a *man/in_gamut.Rd 0bef84810db7c2b1bf5c062c15b9275e *man/lighter.Rd 8cb23596e29499d7a46a85fae3bd2ab3 *man/mnsl.Rd 67b3a4b4919649b96fd1c9a2a1223f1a *man/mnsl2hvc.Rd 4e377e35862355548766ab116d0b58bf *man/mnsl_hues.Rd 5db7f84a6c822b5a36d25edf4fd3ccc2 *man/munsell.Rd 068aba4d200c86bb9f20822733e3e1ec *man/pbgyr.Rd 62fb1c65c42d21f51ef304688931adb6 *man/plot_closest.Rd 69cfc81f0d782a312f057de0ac1920ab *man/plot_hex.Rd 98f6507750d267de352fc258c2f435fc *man/plot_mnsl.Rd e0cff544f5cda602d810d6caf4c72bd0 *man/rgb2mnsl.Rd 3945677558520ef8a61c57f2b782622a *man/rygbp.Rd 20a5a936ffee16502460012f6106537e *man/saturate.Rd cf1a20580d6252e60fa67663b6613acf *man/seq_mnsl.Rd 1bfd0faf3fbf5a56f3e26020cb0ef8fe *man/text_colour.Rd f5343f15032165fdd42fde7f5738e8d2 *man/theme_munsell.Rd 4078b6bc8d11d41bd4ffedfe70c7b329 *man/value_slice.Rd 793adaa149c94009bab8e335b413b9f8 *tests/testthat.R 0b91378a76c507aa56d6a981ba2a3b78 *tests/testthat/test-alter.R 0ecf15667ed8f2244de80f9cd8ee42d8 *tests/testthat/test-convert.R munsell/DESCRIPTION0000644000176200001440000000156413307646022013450 0ustar liggesusersPackage: munsell Type: Package Title: Utilities for Using Munsell Colours Version: 0.5.0 Author: Charlotte Wickham Maintainer: Charlotte Wickham Description: Provides easy access to, and manipulation of, the Munsell colours. Provides a mapping between Munsell's original notation (e.g. "5R 5/10") and hexadecimal strings suitable for use directly in R graphics. Also provides utilities to explore slices through the Munsell colour tree, to transform Munsell colours and display colour palettes. Suggests: ggplot2, testthat Imports: colorspace, methods License: MIT + file LICENSE URL: https://cran.r-project.org/package=munsell, https://github.com/cwickham/munsell/ RoxygenNote: 6.0.1 NeedsCompilation: no Packaged: 2018-06-11 23:15:15 UTC; wickhamc Repository: CRAN Date/Publication: 2018-06-12 04:29:06 UTC munsell/man/0000755000176200001440000000000013307367774012525 5ustar liggesusersmunsell/man/plot_mnsl.Rd0000644000176200001440000000147013304561121015000 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{plot_mnsl} \alias{plot_mnsl} \title{Plot a munsell colour} \usage{ plot_mnsl(cols, back.col = "white", ...) } \arguments{ \item{cols}{character vector specifying colours in Munsell form} \item{back.col}{specification of background colour of display} \item{...}{passed to \code{\link{check_mnsl}}. Add fix = TRUE to fix "bad" colours()} } \value{ A ggplot object } \description{ Takes munsell text specifications and plots colour squares of them. } \examples{ plot_mnsl("5R 5/6") plot_mnsl("5R 5/6", back.col = "grey40") p <- plot_mnsl(c("5R 6/6", "5Y 6/6", "5G 6/6", "5B 6/6", "5P 6/6"), back.col = "grey40") p # returned object is a ggplot object so we can alter the layout summary(p) p + ggplot2::facet_wrap(~ num, nrow = 1) } munsell/man/figures/0000755000176200001440000000000013307574343014161 5ustar liggesusersmunsell/man/figures/README-complement-slice-1.png0000644000176200001440000017173113307574343021232 0ustar liggesusersPNG  IHDR iCCPICC Profile8U]hU>sg#$Sl4t? % V46nI6"dΘ83OEP|1Ŀ (>/ % (>P苦;3ie|{g蹪X-2s=+WQ+]L6O w[C{_F qb Uvz?Zb1@/zcs>~if,ӈUSjF 1_Mjbuݠpamhmçϙ>a\+5%QKFkm}ۖ?ޚD\!~6,-7SثŜvķ5Z;[rmS5{yDyH}r9|-ăFAJjI.[/]mK 7KRDrYQO-Q||6 (0 MXd(@h2_f<:”_δ*d>e\c?~,7?& ك^2Iq2"y@g|UP`o@IDATx\H b+bwwv7W]u펵Ŏ@;Xt5f9y3:)$`aL 0&`L@+dҊ^r'`L 0&_&`L 0&EТ2&`L 06;`L 0&Z4U&`L 0&`L 0&|/`L d@ S 44`L d|Ȟ=G 6`L' ]# 0&)):| 0&`L h64l@;L 0&`LS`L 0&46&`L 0&)l|_cL 0&`F P`L 0&/J-Z4>qgϞ{{{,X{ `L d,pqqy*U$N?uTL2![lP]HL@ ]K%ǣlٲiH:u$۷o^Elٲ+Vİaä{#F k֬(]40n8o:tHk`L cwV\B =0ŋKuuuӧO ,@&ԑ~Dܹ1}sZlUJD_~}􁨢7ydԬYݺuKHVЯ_?4h@2.`L dnnnhѢtgٳ' ҮM4 gΜA޽T#J#s+`N Ma\uI$qԪU_dK [[[K&LXׅ0Ko "`L d_%SL2|#GI$0<Ѱ@۶mpB_;)A'N(rAi+Wj׮2$>/RU%$b_3L 0@@q :Tq_wQ ~~H"mH-vY&СU͏ſsQL D ~DEEI#Fc9E00vY̤M /PGo F['" `L XD 0 `wy;&`L 0&1&`L 0w .~`L 0&4=9&`L 0&./  w;&Yw* 0m#`dd.QO`L 0&(? `L 0&䖘`L 0&@'@"~@&`L 0& 6c-1&`L 0 O ?DL 0&`L@>lǒ[bL 0&`~`L 0&|%`L 0&2<622&`L 0 Kn 0&`L dxld!dL 0&``@>`L 0&C`L 0&#|,%&`L 0& ᇈ 0&`L G XrKL 0&`L ` ? `L 0&䖘`L 0&@'@"~@&`L 0& 6c-1&իWMmhqM 0&]]R&&OwbȑXnݻݓ'O ؜={?3õw 0& 6ȭ0&@`` bbb V GGG_՞&}S2v튱cb̘1߿?RRR4& v䬐 0&H,[ M6Ŝ9s sŮ]IKv {{{ODD*TzܹsZJpV`_E@E:u :::_՞&}HlٲSNEǎiR7/L 0СTKU;vV={6߿-[y5kĹ/Jb›;wn$ ͛9rH UhQb֭Xd,i0`L@FlbL |¿{ni_L={vT\ӄӳgO_>w؁I&In@i`L@HY`L=|ƍDWj=#!xb)}R `2`@& `LlذAKn?G2 0@ՄF^̙3M6 7/8~w`L{JY'`L@ T7oYuҡCd˖ C F$R$۶m+/ zVVV[ւ3&"1 f`i>E{^.]ȔI7c;>} SB ~pV`M ,, ]tI3>Zp… 1E& hqB&ɓuYkzz)/Y_\ĉ#FQF'`L@lÑ[aL 6FrFFppTCZN9&2f`*§=::bQ#@u>⟐)S &&F0~2&Y'`ZA@nZ*5kִL6-Z#GԖZ\j6n܈rA__%K;|O1&P*055Ņ  *.[ fff{.7oh-ӧ#<<\~$8;;KDP4 `L gRki-$wȟ?*"D Ծ}|`L NcdG 2&yJ.b+ٳC@dq/_$1&P"&@GG7&P`F`L 0&@$.@s\`L 0&"P+7`L 0&2&62S1&`L 0EVn 0&`L dL\,c ?@@ ԃhbD*V&35t<8e`3A$}!1xhr#22!!!CΜ9!gqqqPv ?TuYKDOˊg-L4>,L 0QFS $" 0tD'(>М*>5"e&˗`^_BeL@ v7V $'$e<1ѯԳzg9B7}Zt %WO̡#~ts 0&Z9iM%(թ:GDTaሏBe3v,<.\STh*g<$JF+t"]&`J`@i>P/Z'SB FMENJ<5[Ae\G_Yq"n;.^jT >n{z!^>y CR9A ;HLTaK.q_H?0c@ۙ`wlɘ0/SᏞU0a#axsܛۗ'a[^|5*ysJ֩S+7( i! Kӱ3_\ľNُ>FX^m.^~# aX)`L@ l(Adj$r|j=|B+Ԁm<> v#o6>/ z'N@&VSez#iƙq-:us'NG<`L _L@s=pmN(r6^.ۈPH#_P"MEI R 'B߃Ѱ_wS/]ETEe\m[CްΕK=MۤU9'BbŰyfZeʔAեq][%** 6mBݺub Ä paE[NNŀ_a-dwv={11>7P6Au0doR};|vABh" 5~Ǚӥ?ώF塽ڿu`ph\I}/Ru l_[.!TBDHJ/:ȑ#1x`<~~~~044TDߏh| UR vΜ9pwW6S\\>}+mÜ9'7n(h-[D   rGkVF_|y0N@~#GźU ǜe+p#m(PA 3&6y@ЄaLTٷ!S[Ut?Ů[M#ol_%*A`eg:ͯǗE1l*];X]9udm`׊(S2mXcş3V;i)v 4jHZo޼9\v6XZZ޽{D*T'1Δ">m]֫S'Qm{U H<{Lz '6af/]ּ0Kn@維Ӯ`L@I}X٭򶠗Yɢ(~L$@>Qm0UoMlՆ["2+6( գ ^KgRѡHHD`l]2rӾaÆfs̉3fH?"ݧxV9pDtٳgqGuMWo__2C{DHX;^=0WO)}G!aL jU77DP*B9˥Iy\SOJEn9A&4őp}*T/oP8_d[`=wQ8lZk{)U_!gz28t.>Y)LE޻wXO<#@d@߿?Ν̙3Cdup,6vl 2U u[ck }H~Lh0ڙP_\[qocne됷Tq0@{f2@dHd˛[u3A٤qX;ytv^B!|;gn8~>Ȟ2;Ӭ_LӋ/2 +BDU[#)>FD֠\r}GgDfw@ O>E !:t(L… nWQ8J\BT$b|=*]ߺg%3+qʞSFbYlhw  0Fc}7 |wնpX6{~SL'xxM&_G?(Ƚ_&F>)6[9돉=3͑_xm۶I~J "E@dF?a,C]lϿ.[SdH#Shxַ7Z7z6h[L 8( YzHr1-fU[} ^<ˑpgWX-U_F(Ԙg1x7=h!]Mr/r=tm.E< tyeK}>[C̔Z+8)>I1R;^ʓ O_@4ZV-@י5[__2KIJD@\+/΅. ]-@2q`TmXkTVDX^DE_oooT\cǎ\DK~|ocT_xv$*/fI&8wf͚%eBpʝwaҷ-P %S\!dlڵm7E4e})4mVP;7L 0 p 0)&|ۂ0ΊʻWm5zYL$*_>q3=;r kc%nVr1 }䢓p}qt$%c%xt"P_b׬knX>i:IߤUK(Msˋ¡SB?%J/}ֽL%j;5kĠA-6{7,߸YԨ!FO];z  `L@ 665C~7p4)vd3t̹s WR0\#}Wn[&I7Mz)+ަU-":u`x|2Daۘ)pz$ Tj\6}bR7g,سw.^~ w%LGҮ@]#`ҤIy} bCIU2޺_;G9PFuR* (fL dH!JH,< !k Rߧ`h#맆߄}`s#x^בjy Mpi`2iGHo:9a}h@Y{6.E"6 PG¡c0Ѣ8w&&&׶/["h P ~I 5+WC ]nܪIL |'.|NZ&(="t)# ۹ ȯ܈hRW.5)SSk$IyQDD>zuAjh?'2Qv*寸+:T}-wA*`+U~ طL+ﳩAFC1y޿`ZC]f?K \&G"hṳ 0eBydגYu7D&E ɲjWO:"P{_?Ϙ( `L@ ͣ}ϰM$Py3&%yI_&ul?KUM-ԣsaL 0&ȳ^&@Sd42L3>ڽM*˔)~Ev ,Ҁ$BW?퓙3vdIO+k\U)QLi&hzJ20⯜TqĬ 0 p%`rsL 0&`L # <:lL 0&`L@f|dncL Ǜʼ/% HrJ_g^ ) EEt*)ٌL`gUR7J)rRX!x换J(ժG:K,R%ar,U  Pn|4%UgYEOG'L KoS;L%:T:eϛt&#|,%&ó|BO?x+󱯾ii\>%l p 9yǾsc+2b)L^Μ9 82|_V8k0_}wϩ˭e렓II)966#`%HLH S]qL 0&1>~ `QzJt1"81DVƵ( aWMppE1C <$oBJjázyy)ȵ끳ڟ0܈vZ$5=t{OL~r'p\sg\'O}FDQ EqcZx!QX|8`@sǖ{elĈHҪI(ݥnߋZGHF׵ۈ pɤxjpzSr5 Ľ'0b} wɕxXdKt8~ r{oxŋc̙x7yuuuԩSl2DQ`$$b>nܻ-oxZ!VVhW68׮{i`@t[VF0&YЬh'nx2aWl&YBc? a''˖J8?y. }22.$ݶo#V-*g.Db|<*i;Jh7y h^C+5zl/mqr>}sS7O̙ey%TV FѣGqe:p4i'"##%ytn & #gQSu,~6;._K+@ٴB.24 eSgNFoCм\YrMx`@CCcoݤ.> yPx`d]UV0ΟAQQ<;|YLPןa[2ʦ]߷;3af o^"{A[SZL(^۶ąCGkr9|56os:?tlll3ϟG j'OHLagg!C`ʕj"¾xq8# >,X4AVReώI8h>Ҥ6_?ڷx oB]=%9rL |W@&oagS!?Ꮯe447(Ff{d28XZ>[7ӊ/m~رo r\Ŋ+lb,_tPBA4|>}ZZmnРߏh…q) . #v=`yx ƈ pc9~<4kKbgaRiߧE3=rn kNvA1zf?c2vJ+8!*BӲe͍2&سf& BzՑy}9aFVըHRu@i߮i}&jS8TQF_PT E,6c%$; ',ZiѲGWxP&}{ȪNndɒx%zׯ_cƌq*V(1QM!TfM899aXbd(QBxxy#o&6 hg湇7g"vX_tT+U iPe|6@1(9Ơ('OcU ޮr%l|eØV?JJJv>ZW{0XU(;q|R,W5[U(o Чp!˔m^)SlJmmJ3*V/Y TnЇDq/PLii/102D9u2$SGann5k`hӦ {ݥWW+A?E)VGuuQVԩ#ɓ'+ƆoWo߁+d(w?/l/ ")% 5cVOܼR (Vj׊~۸`r:Kهꗖ/~HNpL |16 |7I Y"9&I)173iJ9[#'5eر.Y 㬖0$͖Bċc \bBɔ b/Ôqʿ^;PFU>2.kӻ;0&7 ŝ ׯc([,DqPPѪpppAC߾}[2DDӂq#|NW`X^Hv׮R֮=VŀV-Qd <:vRt_` [zd D,0rm?h7 "~+ocld:H=}Z)XӚ pmQIbŤ`ĒyfZy"[[[-Z*===}=`H?&"W R\ZڵCۻjJ((\nE>= 9U21Vg,2U?zvQZUanlGԸay>`L@s c=Q/=vi$+7/o eOJJ)&dtdx]TpR  w%gsk)էX* T}VE7P]^}-(uttLKѢEaoo[K.i@;/Y$~~iEЯE[p,<{/K?|!)?>3JM޵sFZ5M//% &h8s/@c/rx8hLForwlֲ4wD$DǠ@EL)~\dr-ܕʦ#ZߍTL+3%+pi=`;"/u mzuƹz42&}M*gƍйsgIpyQD\rIĉ1m4 6LZM|#kt N]JdnL?W>B=*uiGQX񜌛5a0~nBRn`_LQQ&262ܐ19i_|X8[a+f!q(.J%)WLEVtovPJF 1M@0xH~{fFX:A6j"|\xp_kba.* / ܿnF-7AX$*IGNǏi/v+DeȩGiK<}-iiff&+ƍìY$#@t=jtО*}0+-d`戥ÇaFχ^͛)&"H|<< `K]w@4״hw/Gzc|x꒴/_]1AQG9!b:VJ>#FR_EsL dhld6g0tLë ;wgҪx7ri'2Sƴ.8(TTLN遣 #w9 ϮD1JiEGߺTwl+Uߠi- krkɫn-E١YfСi{;͓~S+"+%ZpUԯQs(?@ҥJ-ؘe+G1~Zi'@@hHn>/1mc2-rcaL@{ c=`bi{>? >;\ʬsWyTd[Y WHdyc? ݇$ן+•84֩+;%J)spq@#s ueo?iߺcvǘAQȦc ~<2.]*+ CPUέ[hBRnjO?!1)=7fU*Mcr=ԡڳݪ\}P/J+>n 08cOhUڐY놵 Rzo#D8"k-y3Ԉ>&6pm _Ѷh`*\\O ªZ0ǒ;ܓ#V=~"OT}~K~3\[JLOUtM^T}(Ðxszo4v`NU-"O(Uxu ۵U0&7@"onc_H>Yk˻~WMQm Z/̫2YSt%TH) +pπc굺'*&tP`@E_@"`;GjO*0;eЪ)-VakQDM>w`L{`{gDZ%`ּAf26K{ā?u  {aeOS`c^^,Z0e2Hk#}4<2gg*#B.w!IgqsE/\ K:zy`ۊ꫘V. ĮgWpQ4,WI[n)τ&\[VTԩSr6ɶ ^URf~[N~~9/6 o}>p9h[ot=M0A!=58vA<}Gzd\(YgojڞqU5On폝IGYnN&`@Fub=zjIG aT / (Gns٭a@IDAT\l\ظd-|ބ3%}Sg$ ).:M^O,٠6\}h0Pq}q!Ml2YyPP۷olٲݻ7.\%"4x`ԪUK2Ԃ&%%OD{ꑛ0 _W6&v^,SR]k3wWTXZ"k׮ptt֦b_-Z BÐ%VdfXgMͻ } d|}\ٲ">!AaYݏMcGOA๿?ѵz5suxJ0~ ֟ B<>] Q̇Sfܴ$cCH6XԠdSձXѤ12W.&@&;k Y!),4C+ff5+#7둾 (ƅG <+!t Qϯȑ&x.zڇЖaW$ , Bp}W.ʿh;_|ɗ("viZjx\ BwF[[[\|:tƍ%(7] w)%ecXqUB\ 0 2լREb?m6S! мJe}[Ζ 6j(^Ѡ?&ދ!3;ErW[%H YtF{4M[*CzgLZ51ytp(/|R Uv*#@k,L@ ɣ}h6YkYy9ZJdR}7J+ׯ֥KA~}ffMp4Br!*Uw \t AL+NNN(\0^zvQ-XGҥe43,_\2*VZӧab_JɞcǑ6KTX044_Pd/2J(0iBGocPX_|$dߕkiU,sB.2֭P攅~Ѯn>?)bJ9sʮ;6ߵћ aE0G'`ZASRO!6D=űDS:'eTNJE@5MfwiԨN>mbիHDLRdIsfTuСѣ+2MWeT?ʬB(b+T(Z iAҗ>RR&4XQ|KzGvۗ" ewҮB_IŤ_HyrrWIL{>dX%Cڨ`A%7$YY"ϯC kN `Y) %w׹%QpZg,DgꊨmA0?7Vo؇s/;Eb4{c%p&EҨÇUf͚*0kKe]/m1ׯ_G&g̙p˕Kҙ?"(8mǮ j؊%9Kup!Kݬ>"۹m@{ -ʴR%Լ7 # 2Rz?~=n$Ccl*[g=%= $Ŝ$N &FF)}1'N=ye"79(ܶN]Z)tqN21.Y C^y[%hB$%WGZ:bJm;@E|{{{T!!§]Ҹqc+Í0'ܬw=5jܹT\4)LJI @f.-[bہJ${^ĤUCJXEޗ%KQ:N$X} ygTFtvSb!dPr|g_1 &.wMsĸ%Ke@~:*VZ_@Ad]h[";vH]W);s;l e9E#}q[Vz-L`:E/_TL\4]ӫ3+; .beWz.'CsL@ q $f|EhRy!ba"cozܘp._ᑈ }GPY}ـ {qxB@-p|2C>GڵM3?k/6]ROǿ!׏rڍF>}A"͚5ke/_^ rUݫm'dodTH IGTj'\a#^ʴ6}ձ]K&߈y;wS״88I^Nس܀0hf,9yʹllvq2z!+UeX>zM)ŕ8:; k2;,L@ icL HIާ3Cz<,5E:JEЯ\ūPGgľ M Ro1CҀ~+?1?|ԨrT@FGi{wӑ-*fj[ɿ(eO5[4-֤!~W ]3,( Q.9r|i@ҿ_U2'KϏ֎yzj)".B #@RRde}_&&X8aӗ&I_MFFg pܺ%FX`븱R""B{Ҩf3t\cj&jyw4iEtߢﺟۣ=$k/?#/Sk*>fЮbZ5$BFOQyYmp3$/EE_B[+O.__Xn"[]=K8sɤХ !F.e }o|%ታc+u Cl/o(qsx)Z.rNNɏ݈&=¾}@_͒r܋{O'NȎtU\xQ14b;rQ}H~ߦIf*w^th(Dͦ3fG۷+G1$&V$߿O*V\~*ŃYL3-$<1_6ZRpa -!)֠,[ yN˗T_NiU})G/l_(!Xmp3dzy7늤H=  Jez|E&>gZbѰ+rV˒OVSo ׶&wܱv>iހ~ OO܃Z)y8U+uS}DP/V ӷJWUȯ[A $_p3"DTUR^Є~Xe+hmMu% 1xTM _>ݧ&MUJGc)RI Rʞ| ,?#[#ULO=“&>!ĎݨlnFpkm#h2&Dd H,%VAߕIc(G;Ql/t> i -[ѿt%Q 2T}.MNTGZ#MN@"-$J5/S~}Ch',Bٕ^Adu,Qs@ [sAGJK,L CÂw%L)\]d KjP:G)8G^"h ;(dB+atzRHi[ nً00m rܠv\*UZ6ǖ" yaܼySZWr/Q-aL.Had<6VYqy{ѲaCiI~JW ( 2QyS]0ϝK$WJχ^gP!3]2|/ zz Fd.X]2V" |h`@[GdԼq،K1 V#ϸ!th%QN147mZxf .d'T54]x;cx pl4YO]`5 ky3]틖B:{&`b̴1~W+WwSzgw|R^= V䡉ugy kTZS*]kr?[E)@kp.F;o~dl{Q+)I5k_,, ̎om3?ڈj4j`?gX!"_jU(I[}yޮllYʁS#VaF+JMFN"}dD*%eRʫț:]*MD?uȴ3qCu cjj@)VK7))5;ꝨlZ_}⟺h2X& TrrKm!CXRO&Q Pd 3JU@xҗ>QqTt Idesod>,<EFGƔ<ҧZԙTvQlN]K.6$r7պ"ХBo76!֙Ng6WY&`@F`L 0&>}&( hd X%"v7lLOZ U**X~XO[VMWvԴ/UUK?_jοԮ;Xou;5KO2:MR'k֥,6˭3 I`3@g]*W!8]8JQBbO=ܱbNE*[f7qrrgFS9͛lm988y=\qlO/Şc̊6̛(ʹ32B)$UP+(ޮ=լ%{>ǎMwYa`i)S%E~|}V&W3&`L 0&_ ?@*KrNćσp9nB<]{q 0 $E}] pvGtK ˟3wU^@ "Ի[ٶ[-uۺmh)t+;B!̗4w潼w=sU#P_U5dġ4sbraJ\X0qA Zwv[Kk4M$X8u wlڄrQw *X).F7 嘹oN,whZ%[vۡ2=ߵFxm߭d?VSQrQC``/SJg :4,:hfĤE%Xj5>[Y6(e0ҷ)- ߲ `qxyvp~8t)!\קB=ܱ>9EE>Ȭ ݧd*l}h޷K\< !_IA!R )ǰqA}C 둔Elk֭[,Caijb0d swuEMm-xtA w={`j[HGw vB"ߣ*?+Ww~3߽ߕŅ;&u8''MT_D:O6{{.jT3{tuuSXTA%8&U<3 BMuT9NΡ/E#p#mA9{@pfLc`ٶPWo 6v" ׭l+pٛX@xSRP_ǡ/a毈 p{#F`Q+[Q?gРA;w.٘y1Ď`v^јlC*X"O#]<[5)S O*{(d_1:xu}bǤD9d-~Go!sHK:NjQ2צʿ+ILB2ۙ `^{5q{'d>{ܖʿX~m z$A!0nz :8o$@EZܺwA8R/;qg(i@9=x":Sǎc'_"~x#7!ɜn:yAQ(c0TìJߜ8=|0|}}\VIAeГLC[6B0fVc&Nh e㎳_Q`î~ n㼇Y)r$W</~0i"3Z_^&wf`x5ɟVx*&{sɻ_t/;FI/gSy/l啖e+#k-rrџԛ8:_X UY.חj/l݊֬H^ǒ#G N6J\o}} a ;Lv/ ()i4 gYF:4@LSEu~=ё71 D1MծZ =t1a +*λ)F b ~\nTϐcz:te.4.wC2`\L?|N\eV:b^)'0/)U(!ʵIX&ܼ/4gVoHDtQ\]= ֬7lD]wD+Ф cG‰MW]f4n[FEAG=EGY Tŋ;E-[{VE UΝ;C$P[HGe `I98䉀OBHQa41 s`笡q$5 P ICq#%&7Ubjخ]BuT--u8d*ȳQƜIc6 a9<p#%'b*-xT{Qy <P=qW1waF[wOo&-&`/OyNRq(ڷQ^S$@/a cc^p#zLImD#щCѭxeh|kwlE%8s&*?/J?0E;1ϓmmwhFpw+ g½w4R~mh7!˚>Ju(0n#F_)@m׳N>c/1hOUV`D39v$C8O*\yU!ﺖ˗I`1i$!r쯜1Yl?x'33`ˠ(A d2.*?O$$"|L E''ȀWnE޳:4|(iza7)wħZ&w_b(9j$Cmءgh||罚}]˂C5XJh?ץ`uܬmQFӱnscSNaWwӯ:6ohl ]ve2<}>=;[Cstظ͠9ͬ {"f0lazs=|4ܺP~>}7Mz O6gIihK2E޹`#4(1S UA#oYyc/M Ž[y GijKWlrtany_G+x.KpaFoE2}3 WaXY'Ǎ?×?9 0H޿_rǦMTLwڅ9!uɵY3!IfuόM-7yApdD UcG#J<$}{э##؛&:^`XL$AM}8{Ha! $ qxlh<Ƅ$UyEWW0{ƾ{Lo4 ػOmQ]f<^}T5^Z"ff~NnnV~AD@ۦ/Z#?~qЁg8TgA>cN;2r4zpTѷGBQt-V"ז_F?d1w5ԧYb1ILb4oTLVT~o`@(&*Z8`On7gQ[.DYo˹קZyn8|2aM6!O~yy@!ϐs?Y6Me:oƪ$B 2>gٷkG`bWC2WJ`E8]߀.l|W_Jp6SPF.@ֲ$G(Gifhiߎ2*3>O5ҋ߀Rr߽\]P"-&40R,ﻇ1)\ RwŤۉLNME$]C T%="xav`ݏ &Εh8sV$2t{2z5%8 _R˷~hF@;yy@#8WvrנH[\ʀ*mߑCy"ߜ֎LַGE21 敥CNw}ѤLrQy?4q\Y$ ~@4U`TV[ztsCWmي~k?)9XJ}bZ^ċө?<"\䭎ՋX`ȄKiH &Io=_Qq7]0_t~oD;F4NP.lG{NQ⇨a6!O~y@@WwwEmQcޯ*L&VQêpUoMRYtaҟ E@T.RL+^*|?EiLO-Q}1QE?c;wqʶn؞̓@E}܏;DbʨB4[~~ktkLg4m ;/nى2@% 8u, '6|jwp4H?C,(ߘv&r y -iC8Wml-@XHmsnh ۥ/V#ᖭuu"r,/G#mX?[v6٫$<ΊNoگ:ڝ[^=0ReS$eT ":.J옔('(3:pvihJ?Z[TRلi)seU U5;-RB-!u<lko之xK5|8P\yUޣڳ[o)s0pu-a)ju I}>hR8j??!Џ4F@#h4=j:{5F@#h4:j_B۱%_Z㏾yRtoh1k}_z=&,4H@WK7C/֭[[TJ^.]j1QQQ1b/IlZk% ~*KL;pԛo1]}fzI(V iry ҷmSm–Rbqo|K?yl&/'_z]?5jdF/ kOO.%CO5fG/BO>qtr?gӁN&ڷF,!p$++R=ܧ/N pRM`qR¡[bs]~4/P;Ӄ*8|J5&-o se8o_˗>+?{%pjk򏝢,eE}p! @{MLpfS84d5)(e`)fW[66AY-l98O(V";O\ 458S[ωcPtUjw&''e2"fuuȥFcQ˩e*M#8?Hzg'pOEZ>LEգNOBBE~Rjp[1'%AeN[t^F )哏_ џh 6ksP̊5V%,k'䢺RϚt.FeA֟œ\4;:8;Sޱt>}6d_cNIYˉo$皴2KZ!'ei3{Cb&ٟ=B]C%6|%boG `%E&S*0s|g S\dv֗X,UW6hɸjXwk1pF,N oT%&.(*l;m dwv&FV3P.)'*̝k'G d-(^iav eb;>}mWSRױWdF 6Xۙ͟I < ܟ7ϛ]\H+722146mj̙Ok[z/ǣي-|y_Y 'ɚJgнbR'~n8i-H=*ctB==1dE4;~m:ُ <AL3y=T?9I8Q.q=yНmRg忐U|ب8 0ֶVTI```!xRR6{6{? 3`KHa"{RΓV }*+~KS%Og`ft4)1O`1DX061XzrH(VrmP0zB^MOesb^xdsk>ITMf#sPh$O$$TbKY!.g?A/g# i [C6֒CG<Թ9 -@v CaHyLntp"}s = ǩEsX_u2}{"nȈ8FxEEF!ݐ!bV0p$`?_ο4G3J`P9Aڵk[M0l\8IN]:udഓ%< Rdp5FXg>H39:|8Io'i~ |ns`P3 pu{kh*М=pm# |Ks-zec03<vbȢU&ZbddTWh'ij'IY{h +oMTW# X_UR(1z['Wr 3oǒk$ԖM'mkKD8D;d/r?V<_*6Pg4dϭ翪&է_nld@f.+,,48Zsr ѣC @IDATގk*֑#v#&9ׯq9Pe \)1ʊ N N5ue?l 'e؉Ϸl5MqU{>͓ tf]ιxonıF(*CN#T(x(}(څLW5џv?i)ҝ𴡤EL*SJ},nT- y{ &}!Q*(٬[S+IDW/%){%/g~LL /@ul(&ۿoI^bЖM'mk:Rb*Ot?#g}F,_\[QmQcQà0}xwD{3VǫdHB5V8CxYu6#3iBsId-~6|A4Js3 %)yMudí=+ݒ9I9%$Du{ٰAūxHJ_*/mނ+V*^1N҄Jт|-!j&^*Cƈ(3,#S:໌4U.^Tҹ{3V72ǫ ě:;}P@o®]{dA휃LV?#s +sq>"Hр _a"pWmP !?hTOD)|ej4‚ :P*G-8໺r93f3ݲN ̞^Ç?Լ_{RBCC!itJ͛I-[.]JXRR¨|s!dSE a!B)xXf~|o3-NRȾ|d3r_/G8ԉ4,63" ތU9^L>8L|}F*xPܢȡWwdr)aD ,Xq./)u-~6x<AVvpnorA*.bSHyh8T65"Nh~P|*9F{t5{,2GDt2*Fƿ!ƎF ļe`Li*ΊT-ݖMp 2Oނ*غ[h^^(>N _@ա.ͯ)dN fxx:9[Q'^ރl>> {/&_3x&iOsYA OZb<<1ڏR,\9nLzT5z0 ;dU%nl"oa|xrG'ts`'7Ej?-!R|a .4f \ Or߆;'aES'ÿdïFt 8s 7qpO({W_kOgENNRd)83ZVMʨ|2ҹHtcsTm2idIDZ\swV&9TWҮD U^@2\cϠUlLG>]BNlm)ywSCl̅}]ΒC QX`臋z 5͓I07* l~L$?wqTG}RnLI>0g!j?Rh0-ށƄߧ9$r*MMkx, 8We_LU=| Y@G@[GCٲɶڼx{¹Ww0GVil@Ƹ[`l Wd8G~"%2峊{*mwr4ߵ_q` Io{}&K`@a\ؙr?# f$Brr0h ذ""1^n؀&>ʙi~HQi_G2e)܋~eJ@?Iaζ[~ GzTu ?ՍrA;^l4ޝٙ(=6,]dXPa(PQtKO4)Imaƴ_ylndzl,6<~ D) ہȀ W/Os@&dRPsTfYeVd>I@[ ԧ$GƍU EڼABG9dL?G+3{<ͶQ-t GE\f}wŮ4dj)H@DF'9]79E\i1Ƙ;rq{6z1oi\ M"HxW,JC.~y^Q%?k[< ~foUdMpCŊ̟dĩ_|}⿃ C?L \#[›/Y#`nW/㒝{сy gBjok>lE^>ҶFYQ 5"h`X_ڌI {ZW/ ?u()2koa>"]죒t-Ty(4 ɕXFS')KU`r Ҏ!3|ɿlEM!)فK*KAPnp:Sg%^gu?G!$lT~~w/h2.ecQvS3sT29=v ~:09r mT3@{F*8Xʑ= <S)זM=\p֯_%BRe˷l(VE_|?R~*W7v ))TJn`>:*)| !8|\wʌ~g/ ihG$6V+8ҁTciUay|?GA> B#/_U,7Nx*;=q ,KNd2|{f 60 ߌÄNG$ eJDQjTIE.lu˂n?b 7^1 :섃Ues[z;dKe\&7S￿5<go*3Bd#B(it6 yp4 Sʪ(;xs6nEab gd%ǣ(5L6ƎF1'YzxS\&ȡ`DNVm6K0)@)՜)4H{ ϿhV8DؔM rX7c0" ?)& W6'߄.&R' >]"O~o 7|^lf|ߙB:?:XwXQcpmف3 L̯41~ NW<}njBʱ8S MՏMFoBɯ-yg˜Q~~k?QJ2ml1෾ܟhkD鹠$/_%ẃTYRt Ld⯥̚>fE6!;D_۟GFרR#PЁ7w~Pdž=k& n]QK6g=io# *?W?A-G/l+r +k=u:hwM_F/"'05 UZwjp,: 0=U1:'9Ew680HӢLUi—oM&1iGh 9MWR| e[T#9`õ,aZTwQpkp#dna;Tv?ѷ| PM%3KCO"vdK6TL&PK>s53,ϪOW:[ڱQy4F@#h4ezF@#h4sM:o4@3ҕn׃wKKpDR~nqIiiiJ=(s刏7Z2h-b%H_KY޽a4Dl,j>c "=_?UMER[Ç)pn&V~qz חi@Yn #euݵb~](87<) '-kdtpP75bю~N~~@`ÁX*n^#-N}<&M3޿?z-nfj1lvfxͰҟ[bǫ= __šzb_ 8kfɺ᪐>^K5|LN =x|lJxCyp@5 Fщd~Wթ\VNDz/sJ{eBff4 @#h uDwK\TYi,֦h4wQA#І Œ;QyYp=2m蝦hϟǘg_ݾ{( zQ z1XYxH]YYtG@'g+hKLODz[0yU..pb{lڵ;Cg&亇w$-=ݺ>LͶ…Ӛφ 'uLmˈR@c,WUecP$E]kggtj@E s FAF^.9C_۝mn9?u,]XVF#,(Q6Z%ݷ/a1cO W/K2wY #FB$n4gRee÷g4jk6y<}-C7)*6Y֖i,=zv-sPKAEtp׮5?F6yzbֈQ|]EMu6;766((*2.Rh@|pEs/ 7tNt= ?rXX\g@l){>}ar, ub5fR[ZP?3f׈9 pE0]s>&#U`G/OF ONư[nЛoTgyĝ{6N>e׻Ͼ֜O<=}{g_1nO+y\͝iNw?[+Yp8M.p @8Ͱ .L?:ڑF@# h\a.= ׮ヘLʋ.ZYw纹`_\9SK)kyIxWQmF!C`x71aN]Α_X~=‘W-aB}rEXw8}RN$1F(km֡g†lIGrBiN2/Xx>Bs3|sP|B۰h/>LI@ٹ_}n/ O7Գ$ Ǒb5ui; 5Lrc}exɪ1l=%3n* d~klQU]m_6 m'V;2rH`b!2III=z4.\[oHdi_\w/Ocf^y-[pkUUٴj+/Lj#kl[5 V7oaTuIvxD;,8ǎ!q.%ocǠ?g;?nG9_LoYT~<"#pQ$@(@nBֆ-{$GV7S!oq%{uesIuMtpn}U@ Tԭ;jXusr4~A *KNOCH80(/aѳKW|+1֓I<]@׏Xa˦S,M;_ v؁={ ]wnf@zpyS}: ;֘+^<'BfYN)YP}y!# ]'LDIN.}q2圠):9 bݧNF#ʫȍO0ok|{54ҭđ$[z>M :G +L/I@g'S6hu 6\ԗIҭ-tжޭFF [uƥAC{o_A&s *&+#׿ )(~O $ě^2Gizf +>e/_]#7Wd3٭.)| 8kMz7_F}qּҴtT=\Â1㷌$*'I}r IZ8 ƚ7E5o[.m%I@Y)7;*:8k (|>xհ=ȏ+b0v3OXeM5GۯnL>LvSO -+ӨDKm۶m\ ;wl\9Rn˖\*w}7u M%!āboƤ3 ~j[ @9^B{* ./oX(J\2!y>ckKQWNMH@ο~XNb8|ڱ[ǟW`0a42nDk.SXR;I(ܶ^cZķvrn"s96PYc:zzFQWtx7nV0mGK-ĉ ?`1K! g޼y8EJڏM']-O0 ٛWe>LZkV2 d3ʏ?O?G*qmCj ji:|yi,Y us=wsg@?Ӛּ;vbSзߛ>zl_paqŰvWS/OD{;{ T#RrRQWşDɁcepm!hoD2S&ͽh!R}: ܋6p 3i޻C}^sbYNj$}믣{hF:{ښlN"{? 3g"s|l?Qd-sLymֿ!d~Cxd-74'v>&bi=?*&"*,tP1v.[>ҘOjV-eKf]a_|¡/\c.@QÐb.=o?.Z8Eh:ʑE6%t߬ɽcGq_{[L?2˜ N=prOv#{dÅT&fꫯ>ńLK Z~ þ>CҦpmIa!{EL=r`JT.wd!:ԡIbT_Y'$#pG7ZfȖ1{G gHHs 2`C9z%=HÁ>R19?+3pUf&N)>N^1&*ٰ^!VwkDFp<=C7_c7`B% J(6sMGRj t~b㆛0۟]ʪ(qI@}ImƍFïL5%!^PFPy'bcwUO$ ݺGE1y["A!KIi6Ʉ_]38~GBU6{[ع`nb$}Ł_f݁yqtv@)8?bҤo8{17Vx%kZ;l칸g7HOxy(f3i~^y =!28~*pgkNI?'N@t}ݟ%՚֒ er$A0[&3'ͤH킿 ɷʦRt=R&d99׎|W(t&~nxmzM2ٱeóaU=Kx3˰8GO8* Nx9~m~Ґ{XO?sx%ҧWq8tEO!48ep eNTEcA#h7ROeSէYu)өSjߏPR w\7Ϙ軐4K@ /s]ᮇ[^veF\eSI|pѧOcXj2 E' |'ҳܛRVԇq- G߃<&`{|k*%`߲taSߙ}'b5C@.܋ $ yEA!N3.~/^V+.D{k5 O8vb-z&{(>mNsoy=@o./?57u$,~{7~hl5o F]s/}oxl8y8`vřwo2QًW^oJ2L}|gPp-V ?E*M!z{b*~GwH޲܁k?Dܣ#gfծ}Њot@kB}x[Ϸ=1|Dn-Va-Ifz¥3.Ŀ77;NYݸcBH+M;m$teCH e ή͛e6ş үne ᇏ=(6¦QTe/{΢Jp0Ob̜ePTKԿ,{$ t|G_zٻ>1󮁕vAiJ˰4#we/JHYqg|\\:ۧ߂𻯁Ɖ*[/:hN_FU!pi;q%Óxã\o*ϛl6IPq|xp$`ߑ%tkӆ ddd( 14R~\J? QaH߅<}OHr&F~-e^| G8tV*\HwH߶ݻR,Z.DyW!pxx,B}F*̫ҲQAERJkΎutpD@kAࣕˌkѺҟh`ÿTe?]CL8rjzI ۷[,_$?_z)vmdӘ,DD`%`wE՟r:A8J%KYUq1lїxgdXπ ;(ʏ46"k^6(vΎ=<|cڼH_^iӱl=ϣyv"hog2hU j&R|w1kht2ORVO;߰ ef(6juɓalCK5U`+Zw%%cXyo؏?C QWV,+*^D 9+XįvҺ @5o6m PDrz8џ(iho$@2_@[rwO!jI+aeoJKZ!:h7M_F!`gmO*~s?ܩך#~5C "gZdpk2ثƤ%OEł=-Ջ/s,av-ު-с &ς,e2;dvmۮkzˏ lNk l}}+nNk 9V;[ٲF@#h4@E4bwh4F@#h3h Pz@ TCڇ]#-*4 kNYbuuṳJ#Zɼk)ڏ]_cA2WNɴ_sZ)cKO5`Yʬ9úI[zsrj֬)'aρ_4:8ރFGq߫(ʋ'L+aŏ;fLA6Z3fC=d|>J.c׾q-ܚ͹90IB7 .m ycx海7-=[Y=nO%[lڑF@%]F@#h4FC@c7D_F@##0m3YF|Ԑ0r9/NZړF6uvDꎽv/5>#9@v~uNu pxBuP@r@0ͮ={Z F:<{Kn'4t|G5hnmR=EC` $ݵ= v6s/w}wΙ9+[r8z#wM KxAa 6 QJ@<Ʌe8r%K"o(Z$Td#K|]mAkX9( Wý/8@=@$ :vGSAC 0B@H:-mx%HcIqyQ<{U~G0HoY̦SݺuC~3gNʔ)<<߶ d4ӯJ(כ؉"m|8j n9 ݜPk'j.ѽõUrթ U"ȼeHY0Os D@XM R!dy䱱.E ĐtPL]ܬN(nᅰ0>qĮq1,)d*U_5[PZзo_,KDL1,!jVX2sV`JOU%˗_^]CJg;mݐ0V[zb$Ǹ.]q(XV*j)Vk$[ v)cj;'|x3jխO9jfz D)P{0d,mت]?@HԩHT/Q$ׯk7$äeKѼrt=6~ҥNV y(ZT:s@WK֬m[TV nBlF$ 0KF"1BlYPLIϹs닎;Z;Y:vq7F۫|o߼S?Wܕ)n0N f={GH(e(Z*,rqިalZ %+TkYwS_X سa#Xҵj"ܕQݻAihb!F_TC9X=~GͮS5h%BWl0-\5X'N]w1G1&O|MPF2˳˱))?\~cAd.޸ed%s/Nvb#qJvE%͛7Sq[j߾=1|Ԯ]'N4v^mu1d\QNAcnݺըuy_xx>*BȾJ=x`7ZvSFf=]0cP*[W4Dܺphک%Ͱi,dSqhQZ8>/3k2yxQ@&@ LO/GC BxɆ#RcuXc{`prLJ}DZIS}׭7n\4YܜĬv HAsN# |kmnț70aBԯ_eʔY `Μ9ZjLV})9q0TFmb,u={ WϞ3^/84Yb-L3TLxM&F^uʓ;wqh*CŽUU֟E==w,_ u&Sve6lBmFQΣG0hdĔ]`4MR`V2MÇ :G0bx}egH356zhrԩP.-*A`-e I (7)]P\_>gAɕ?~ΆeR o 86I x*"F0|M5d-]j^nH\ qm9$'cOƈ鞹_߾x>>,/]Ai?"njW͗P}g{$`n4M UkY(;z_3@|[pKiS9`⬙A`{.hW~`WOq/O;wK ?~p RnA&A\cNܪ`RUNe$.>)ڡC|RpXw%Od؉2PR˚/uP U0?v^  8I %TwKl6vuu;xĎ=kڤEr'R9Lu 1Է;wY?:rtSu-k5m* '6"AğAZrm+Wbl?7ܿuH1Tſݯ;:aJH!V]leJ"}غ=D>SVxX@߲P7D} *KG5$ЧxM@-2HռfyDt?{6&4ɒ#9wŰ[+-ZaU,~d;RI#]Ƚ[C斿dk.ṷZ[z5^@ܯFC\bkG*]5h]TELrt%/Y%iZtS+[.MS/$JGJO] ׫s w{vCK#NrC"E̺͸vT}t ls$JſX$s³];[=eX&ފ+nj? Vm܀)sgGp>q:A#qjԨ{i?9PF;Ln@fSfE EtA-Jy2???#)S2.; nk 6+ ,O"`$2KveHva5f.j1zE \}"`yH#Δ(ws^ _}e $>NZcl?Gj9up %)(|:99O>A4eʔ)h*~I%Ͱa @tart1e}WnЩouqjL%zIbM"FCb]1FtIe2}~ELqM!k"8c.H,~gwFɶ-`1](n:Ƿwt:;b|ró'Fw}$`x`? N\'ϟatBٳ#E$pSzUt>qpɓ#%S?|12|}}T*(#@Pє"_4fLG;)u:x5*umot;~<ƻ{`S,R$ſ} <,SjB7B{X0޽zZWLhm zŰ# .mVr(Y($@O'ςW$@ 1e2L#EgzxB7җ>.] ɸY J0pjrM!  6g)ٶg7H6 M ߷yH~ᆸe'dQs\v]:ċI%6tj5F RZD?rEwPq%7i%-Tw aJzy}c]#ԚPFU_KI|a.P>{)^A(Q>oe얒dYJV4e$@$@$@$@$@HHHH` VlH $m:kU]f-бX UroY*5 E=VZY+WFod׶ml1 ׯE\ﯤeʸ#w-!c[ Unju-Ѣ 5c\/~,oZObJalB9 >V*$_CySJZkUW7#ml. @X$8 Y]E éWOĕ,CS2KlHHB O$@@ِ)}z|͛#_SPyv,$@W׾64Erx-P߲_Ot8+{ T戀 #@@[L$`BxdΞ Ԇ@/-}KH'O[VAq[ D!]^h"ȟ??N&M ۤoɒ%V[Δ-+:SܩPIc:G_5^įX`͘x~d񴙨ڸq?*w%X2~ 2Ʌ;׮#RH/': 4잃صh?yb QTqɧ99vML->N6L@-8w8}THdHw3܁(w>}O%KPJܿ&L޽{ujʕ 4k Ϟ=: Pb2i$ܹsG wz-whijx+.7JTc%Ƀ3RLig-mn߾pRUd{X) W2 V`A qs9>H1GjUj!}:<HTnGC)>kWkz3܀>i7WCh=Ԟw_ c4  !@{( 0G dW;MXߛ?SlyPrQ̙\+UK L}5t'N.1cDĎ(6j0m[uK0T]?uRzhmڭ7?}ycQӟa?-FΕkkYGpnaZgg3"|C ϘHB DRQXB0f/RJc >cӇ",2M,M TOۮkۤ'4]P\TP]ʜcP>^}p%$H^1KJM:bH7>ÅG?a@=9yjܣ =!}RW+U+̛oMpj>$HT2D@題`%i\|%  0H _ym8xDMJ2s.mI$S*4Ae_(2d@T7W T/bXǖVzI2(}p8)SgtMt$I 7\ZW_|U|tۧNM $v R~WNAx#jz3u:cKi:6I ,1 Ȕ>q6H(@Y0W^=)VF 8qp3:wʖ-k*1bѣ@REǏqD1e nheO@V-Sqkߪ{Wxt.o(.>ESiѺB*.8~]\9w*URdLC׌8vp.T8}Щm 77#>A$`'åWԭ^zA0jxi\T>kbƍر#֬Yٳg㍤Zey94h/_ͨj̝;q4tްKme/ɼtdtKtxtvF_Ad{Zu(S%EKQ#ReʀuH/NFٳl؆o3^<~).6kHj6M$h|$>B$`ҋkG+r%-[p (]kS 3'OƂ 0yd*RmGBL ޹sqmoТJ;6Ya8w_/x>|_+WmR+ه.'/ցN9yOîp@3̎t9'q\XU:ŽQc ܹ| 'Hh:ͶI GHyNb"v,.o?GLF@|tMF%=ɵ?{T#)O mH)$PD1BUjϣbpܽyӨm:jzӇƅKPT. Nyp6X WɳX=v:RH-:Um GHZԭ^8u Ͼpt ⋿t* J (#X }؏< Ă<[RRz6}Je+/Xlĕ3a‰Q`8K бuR%KǑ^/؎},H û$@VL`)_ϛkB-U!K.E#u}[ZV[Xqb'U*)'SK*W'zsI{J!=h`OHL@-.{:ժ#⟿xb;f 3#XoſI/Mȩ DHŋXvڹ$@$@a 9 4)MRo\s6]v9𽎋رchV[I&$hd!M8vq |"T6I-2."G1]Dh^EU(QL zE.ǎe6KC r$@$@$@$@$`Զ矣'   1t pI\v KV:Ԝٲb 'N)0SbŊFTaֶUEk,,QKNoYJTh>Z0eZ($R(hئ1̇wa2 re>*"0/'[#6nތiIi6mJakΞTUR6[~\|*^L {qc7Kd|hm %@ |:  (S YYp}   HH_x{x rȘ6nbƈ/O X1O% $]P'K%` H6{Au!M cS Ż#VL,zdiRXRK*% n @  #Cr7SO7:.\8y$|9o@q T* Zޘ/;]NFΝŋ|yKX⠡S VlBP= @$pE2 E1:܀88K9{l1" ,Xl톅rȁqz!nX1cƴؐԜ$ZK`PΗ"%Cݻ},@ݖPj%*"iKaX )9c4&G(+eTB$HH (RW(=alʸ~Z6i:˗gOŊn:8;;Ce)_9 mhmڴ9s0qDXrxnӱ&,߼}eT]K+[Ԟo߽`dRhիn5\p!YY X?Ю H,K'Mm$@@1~x)\Yb/?͹o"ב'O~:uB*U4iPNIorUܹ &)RѧOUO려1M0!^z(o707dHܸrFA9Pg ) {[挘Mb/ 9"qx  E@ؚOH' ^ 4Κf]nbiҤ*UfM| .D=~֯=zk6\ ܹsF6&k5dՒeJ%؏gϞj3u:ڭ m;!ݧǣqX4m<2 :\xENFۯ^cN@:Wn"J؞رzlH 9L$ _/qāСfr#I8EU @T0j(.]6K;S yTZvrr; Z !sZx%._~-mƜ.s& 00=y* woVId/߰Tnyа&n_)Gta #@ S3 @PŽHD(#k_~N5-vo{˖-1Tvڡ{ƎO+!Ըqc۷oGp}8=zq:\NyZon} #ȁpHPy]q ;X8u&JUCNxq۵?}f?|  ʩH 1TL$fΌAS)R$jKx2<|?>K,a\ru*vmYIdZ2'OFӦM $`3v<}NȔL+/ja>rvg1lLp`NݸMn* 94B=5 NSRz.xdɰz"Q]ڲcǎFzG\l] wp8%|}C7篰?e{{ ]L2|]Gν̡mn^|)صn= @$@ N*D$Tpʼ|ӦNo/)'-vT.>&Qn&wŝD)#@eQAgX[+֨QӧZ+Q>*&"]tZ =GBx-g>.p9[.TM;w~(_Ư^Ip2#ܥjGwH l擣!%¯X7n2.?I ?v/ubKQF@nݾfo޼0 ~8^ '3.Dze0zGlJi(M3\uvΉ-=pY>HFLyȗnlB)tb- ($5}<=QXKϠa g\#\r 6s鳦v2KEhѠmO#c7oz @>yi©Wt_]b2]wVFm6"_Bpj RRcظԮ*W?K"ARa "/ Ȓ)zu >I̔;9gÇP~)*x^zP9߾}3gΠdR/'*1ԩSq=_wA̜9Ө}H ^q͔\{¥U{n^p);=;s&b@.zZ[WkɆIB?C Rr_$>Տ,WUWvg^z.ĸ3&N:ٳg#!W\Aرb4UQjUrqqS*8x⏯K`n U=UZ(?\ K4DzCzl~@ 7A|,7 hG]  5tm ]Ñ B2d!'J(uV8ڥ׽rwQ'2ƎU54~MJeQUn݊#F`޽ں?expl?*UĚ+O;wt]%׈58s7\}')oAhUys"sI@xquf$@ P>A >FoK+:$;*x=:/_c[&#`Vd `[vo߁=y8:~7oe[j5"]L1$ԼIp`ܺ~Өq*j[m>x S@,q\8~Zn6N$ (t{G$ԢnɊp]↳s# .5eP&&MX(Rm;w3q=!E,!Y]@ߌٲDa3539jq1}(K :HB9|= ' 6~cF#j{.MK-M4 }ߦ,xlĖ *%Evs; FW  @%wG:u-K^pYV`֬Y(\-cѸqccƌ1 SN!J(6ͅ' s`.lH@ѢE4iRڵ 9r0iҤ3P|y];[ [Jj_B-B% CbسgO0GC$@!DC<Ւ &777c+Aleި<=HH@?S 0I$a 2N:e ~J$@$]tPe$@$2(&`o$@$@@Z6L$@$@$@$@ 7' h#@@Z6L$@$@$@$@@"[ X7o˗Z;d"Z"*`)9QWRH k=HHHHI.@IHHHH cIHHHH h'    k&@g}'    `L`|HHHH k=HHHHI@0q    f4yw    &IHHHH cIHHHH h'    k&@g}'    `L`|HHHH k=HHHHI@0q    f4yw    &IHHHH cIHHHH h'    k&@g}'    `L`|HHHH k=HHHHI@0q    f4yw    &IHHHH cIHHHH fGIENDB`munsell/man/figures/README-palette-1.png0000644000176200001440000003224513307574342017423 0ustar liggesusersPNG  IHDR iCCPICC Profile8U]hU>sg#$Sl4t? % V46nI6"dΘ83OEP|1Ŀ (>/ % (>P苦;3ie|{g蹪X-2s=+WQ+]L6O w[C{_F qb Uvz?Zb1@/zcs>~if,ӈUSjF 1_Mjbuݠpamhmçϙ>a\+5%QKFkm}ۖ?ޚD\!~6,-7SثŜvķ5Z;[rmS5{yDyH}r9|-ăFAJjI.[/]mK 7KRDrYQO-Q||6 (0 MXd(@h2_f<:”_δ*d>e\c?~,7?& ك^2Iq2"y@g|UP`o0SIDATxxU#R%N@U* DbÂb6DQTA,AQAP{Wϙݐd]ٙyfs̹w/[P@@@ ,҄Yr   F@@@ ¨9U@@x   Fa؜*  @@#0jlN@@  @56  @@H SE@@  a$@Fͩ"  @{@@0 T@@ =  @ Qcs  @@@ ¨9U@@x   Fa؜*  @@#0jlN@@  @56  @@H SE@@  a$@Fͩ"  @{@@0 T@@ =  @ Qcs  @@@ ¨9U@@x   Fa؜*  @@#0jlN@@  @56  @@H SE@@ mr|>59թ ͙E:^^8R9zVV CSidMgEF z6ѝ=K;qfYxcN+־) YadIge`vU[;:V^f e&r m@@@1   9{D@@ hAg  ^ @@ #  xG@@&@4zv  @o@@@1   9{D@@ hAg  ^ @@ #  xG@@&@4zv  @o@@@1   9{D@@ hAg  ^ @@ #  xG@@&@4zv  @o@@@1   9{D@@ hAg  ^ @@ #  xG@@&@4zv  @o@@@1   9{D@@ hAg  ^ @@ #  xG@@&@4zv  @o@@@1   9{D@@ hAg  ^ mw;"z^ڍ%}bYb4i$cRxY)UE.2g1S'zd|J }x?(T)QYt)>r/J4{W㿖R+;"^:WN9~^:ˇ"sDv)T2f yS:O{ϗGY^~]QK= UKdgΣaDWV.Hid[K?Oh7Iԕˣ/k<;""NձNm%w?#㽏􉣼ə3]{` 'N;/dH.OM`FF.]:.m6ܺa,cӑy({XPiR fi-7]yIۺkDz<wlџ+v@G|G*h$ŭ׹s`Rw=X\SꥳLt-fϣo?^ ҤLz>z8t3 GҾMY|I()]l#}>Ԉ$'N<=eOUk׬*YdL?+Ԑ6Ubd`^Ϋ3o?4 vX66P~I"+=#ʰ/Nt͕3y ]frrN2 d͚n_J^?<ȢK.ضy-%?70Qs=_Yi/˪|κW_+״խk&y]|l$w{}y@Yl\}M+w%s\tu=ؽsv,'gHKJ}J1UKȸdeRt.{μ>j}eΌr-lyđYؾ(UZku6gَ%[3P+rf_)]I}w^+ɻy{ `wq'yM6m{;gÿTXVׯ-q7_!y'hxuM6cv?BlVϊRb93o4sg+o뭽~CS5 l尯|+[̛9VmR_ƌ.~PTw-W^I2>+|%t릵z8*prpch:Iپe}Y pD$^H?J=mVjP+8W +ZݦWV3{;7KfMTN +i5rϧW--%rpn٤DƱRc)Cw=dWb_lص]ukۦzoeƟpx`W~|;wKZx^.dՅKVDdK]`]rοkǎKv6.WMᆳ,dH^J(*Jڝ̉,mzu+CWZZw'Rs*aqNjG=f6`89̖N䯜hˏIk۹?=;夦,R}c>"B]I? wÃ;6IdҘOdݪNF5vorKb'8;)%clXݞPٷ{\:[K><74"/Rfc=mk뀧KQL#6ԶBԓbebS;˳kz혗rX'8;w޺~ԽޭǖRvsw{ſ˵m>T !TBrIrUh9t=I:7ɳh22w ^Z1VB|HNBno2fttU^5J_./St}uUcwy8<(]^uܹ j@L6[HڣfL,Y;Wvr|ƹoISg%ڳ_쟕 Jʍ 3..n2sv~l̂-|Srg>'ewګ ɖ-LT8$Ir&=~Wcx+49}#lZ\6`Axu?ҦӃ(Nj*zMZ_+eu gKrxigggUn5e*TsghοK?ٱeܺ鬗*w:Wd)UO{X՘aԻ LWIu~?vX]bl۴ܭwX};cG_T 85vp g"B4K۱οu6p:[/TJ +[p}~zV>A,9_*,*^Heͬ /3Kӆ5w83fuZ]_4vjo~rC_uۃ Vo,YY]ދ}@Q?Lue?vtS vD}*rڡ} 5Ektg'۳J:ɷ#EU+gYZӸ4ŐWmM W,p29ɮO[wXg Mx#θ]b<wG7uFu[;ɭx+Pf=oZUuMa'-y_#G剶yVy7Uoֵ3{<~%#F*A6ͫ·:`=t65xu\ċ<߽zuk蝞bNZҏ?r?x>$^JFW;=u^|1ٺm|:l5y%d"8kC.R}RY[66MbGH͝Y5lNjtԂ: KI̞D\}ٝ*5:N8.ÇB pXgъ߰?;ʮ)Atz>WsݛVq^:m=,|UVS_u+Hi @6]Y0p 'QEsñirs̮[_3w|#Լ+nTTuGl9J;r@eⷃ5έk%o~lzxٸ@^'\J7>r>9YRvvsԱ8MMgW;u*b|KdPG}dyvyÑt.ց,W,ԙ㍛ˤiqۄslϜ5 ~ҙ]A{Ŋ>[X٥:ku[t+Cܙf$>qP/yZEE6F폻{`_)A4P1ÇhN5(X$*g{(jt"g6逎bFvwu6zw-;WYhQY[Ŧҍ_,~㚅>cjJb3x*6#XGL`N깊Yo?5zs)JYvHҍy=yTgfC34_{t3XJw;:|ZtlWm֚ j:lY2_!moh>FT*#+Wot͛;l^ϙw^ݶ ቦL*~bzRp<1c'},uʫ?]{\-^6{PZU@ :7mӱc;I^eu5N(O64x[%9ɘQ/OyPiW=yMՀ`lA )Bh>u4=x}c}Ys/kwl}c+{,N}EFg! `sko HaMoggyt.^cx nW@Zb>t{y5{=^qȞ9|@lh;A%,=[zN/Xa8oۣ]tX޹9^W-tM)W*<9m ЮRwUr>ۼ:5(Ht\~Ȧto38~ YRϟv1ɪSnX9߹Zu>3z%~?X^'t2}l4K8`Oj39SUl:ң:F rJ!dUҡm3Ylkrֿ>KK驤[Lέ]\a^?wiӢΓԝ׿N9NȈQ;iIܧR=ERjڷVF}?Y[I3{tvdUaVKnA &LPg ҮUnT&t1SK Gzlk?ZQB[B`)3W厎msTWǁdae1~[ZdG8%j׺~5blx<l?*/=]~E[Q^~:ͅ"4(*+H.ePB^Xs;#+ ͎MbгŚyϊ]Mo&SDHamNatJ6M6sE6mҬuV>DZ:- y{^V4KC&*3Yj5K}LlٹI&~__+if6η&}2减JrFbc oCxZBNN!˗!{8WdmF7􋸒?@'Tb3nԢKˠL v-/ʐ!lМJΧҽ['yR+YKo$?`Wң.kmДGz+ ۗ}g=S/ I~t,+U)žʳO/|1u{_Ew;`=#6 E@xR⯯X:g_ME_/ܞ ݡɚӜS_S6-w闆?+vGlݏ/JkY}ǗZez =.Z'3υYo\S;@ׅvޜYCV}yH9t$0Q =qd͞+EZaDkmjtUy3~+O%|0LϿ{1ZuJil| tIhǎ-ǓF z6U/eĄ&ѿ\aWl@vp7ot^*e%y(kߔR,xs^ؔ޽Gl;>kbY%2u[uQ[}N N{sQw/^_@l_ k[%z(y]wWiVm g柋lmƼKkPF~g%w0gy0(TG~]TD@@&@ZE@@ )cS@@R@jk1@@M@@Hm8^@@R @<6E@@ x@@H@ @@&@ZE@@ )cS@@R@jk1@@M@@Hm8^@@R @<6E@@ x@@H@ @@&@ZE@@ )cS@@R@jk1@@M@@Hm8^@@R @<6E@@ x@@H@ @@&@ZE@@ )cS@@R@jk1@@M@@Hm8^@@R @<6E@@ x@@H@ @@&@ZE@@ )cS@@R@jk1@@M@@Hm8^@@R @<6E@@ x@@H@ @@&@ZE@@ imtɩNX kI!&8y:: @ڴ'Je@\Ia#PBK`8 u GKCsƁp@L IJt$׳2&֒d V"  @2Mɉ   _5@@iJN@@  @LSr"   oD @@BF dA@@#j   2!Ӕ  Q@@ D@@/@߈  @4%'  F@@@ dB)9@@ 7  !#@2Mɉ   _5@@iJN@@  @LSr"   oD @@BF dA@@#j   2!Ӕ  Q@@ D@@/@߈  @4%'  F@@@ dB)9@@ 7  !#@2Mɉ   _5@@iJN@@  @LSr"   oD @@BF dA@@#j   2!Ӕ  Q@@ D@@/@߈  @4%'  F@@@ dŀr~NIENDB`munsell/man/figures/README-manipulate-blue-1.png0000644000176200001440000004137613307574342021056 0ustar liggesusersPNG  IHDRǵ iCCPICC Profile8U]hU>sg#$Sl4t? % V46nI6"dΘ83OEP|1Ŀ (>/ % (>P苦;3ie|{g蹪X-2s=+WQ+]L6O w[C{_F qb Uvz?Zb1@/zcs>~if,ӈUSjF 1_Mjbuݠpamhmçϙ>a\+5%QKFkm}ۖ?ޚD\!~6,-7SثŜvķ5Z;[rmS5{yDyH}r9|-ăFAJjI.[/]mK 7KRDrYQO-Q||6 (0 MXd(@h2_f<:”_δ*d>e\c?~,7?& ك^2Iq2"y@g|UP`o>IDATxT,KoĚ`bD?h~1Ƙ`h-F`Iea) , {=ܝٝ;fd{O?w<\<9tc     njx @ 7%pSc  )˛/&;ۯcHp=O3Ns#ѵLJ?U(-jѭ # Vvx[nG. #@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<#@l„L  `<ޮ6:~; ٟQA-Ӌ)>m ;<<^]L3G\n]CEV?ǯEzC)%!>}v:mYo\n*<>yK`:rWI6DCZki['yxzҾUis'(iE>MuY TWQDs&]܇ioQ}u ">>{7thހX~#yds/'S_-Sk5ك(<~6ًM* dhW*H1Zo[uJn/n4tz4_pL=g>-5ʫ\2igSww7<[}iHb=et߯_|"hJ~>޴O=ZZ}/^4yPZ5Ν@ާN:{H PWM??򍞶[݅gгo跡Ut/\N RGEG~Ez5ә4,sJM4k*Ο>NH/MC^FwҨ3?,)?ucR((4utwX+ _v# ԡM$00blW@Ofj16ЮާqRī5v ?!e.W7}Ӧ\~"ǩV=LPƂͫƵyonAktOOz|X[)\Ϫ@"߽^|guhL3' dejCeS.%8ɵL> 70|P7MߚL b~ok}[-jC 'NUo`VU@H1-|i8:tP7q{?'dv߈Z8{ng/Ro}c E[d1먊(3[T'}y{؇`)<|?OٷI V;TomF'g-W!hHtz]QTSr2oոB`̰-O@n>Z~hZt8jimZj vI:!&s t*NT\^>8"nz_p_s{MjeQY@ M$+ڢr 勿]+3~+iϧן& \ /2KtX]v}cDƛGY>#))H>US)*>*aeνV?MGwG- týtE9X'P_y[ꕏ?~ *>Uc7œ'OD%j ?mu,X}v/:"Ɩ+ y_!aSnk@G7?O-0jyN`|zVSGwnG1!t_LIs 9>$}﫩g&\f+~og&Ϳ~"Uvљr->HqG-j*=qE%[[|RJn5ћ\* '?&שW}[M@qIS@Ihɜ?ӗ|&]'R|}I47XN2u5e1DXEm4dLO_#ĦSD齧KmwϹɬF\Z#>b`_]\.MVS&>u~ JHXDIciH Kz&vj/oӞw7NI^S}[+?CcU9 t`S4vwLj+#,ٟbT?- vmqT{ .N>𳻯]\{u!I!y_wh۾𽿑rA\T-[<6m2I6|G]LgW?UAZV0m?qma%g.%twca1ChB0O_[o9nwRMY$U%.o[\Mix9Ar|:u$D% FM]LG>("/_ |s9Yl[$^V~zSE"y>Ҕ}~BcRnuD51}CD'u5i^4(q*E?.n vHM߰bCY7XU% QtrzL}~ -3Xr3:%S+?bETdX_do/t`y|)=t:UtlKEuH6λoոB@}}{=7U廟{m]S<~y'[Η#z[)cX<xK+*GDo}9z[x[ 7? 8م/Wz6tW.l UڝEްUg//|gޯfjSCQIo~*ⷷN^}͔]7˛C3Ñ־)N4鿥RME<~6=1`bL6o1lkiUlqRt6?~:/ȓCurއwur+Hn/whTn+t3#D/Dj}kq Ú0=09Niڼ8'7B-;]l~kqnE&'q='cKy~v(  .MCA@~١$4K @g   .m>t@'JKy~v(  .MCA@~١$4K @g   .m>t@'JKy~v(  .MCA@~١$4K @g   .m>t@'JKy~v(  .MCA@~١$4K @g   .m>t@'JKy~v(  .MCA@~١$4K @g   .m>t@'JKy~v(  .MCA@~١$4K @g   .m>t@'JKyG7$ U-~$Q@\U-~$Q@\U-~$Q@\U-~$}1ogdG^ ʟ򱕛)+H7 G`v:#ѵ,̌7VXA@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾A@@@@ @@ ƶ/F uS4 O׻#2ǗgtȘdKFr/!g&hRhD,%$ O//-`g@ )#)&a)J}F(*6"7JO& aq#(82Z0S4#hMB޾*>-=HC~AZ7,̡3:ZXSLeoOo1ۈ0ewǩEW@$VqM-uZ7ySYkQ}<;I ߘ[})\$_[-hH~2"^۔:Γ_Xm,8l]MaR((;O'rvR\bJ&ZOC%d/BDey7pڗ2]]ϴ":>F.:9 W˘6Z%mut: MPY@'Cӿ8PUa*>"z&f:u&-}BcR/kߔ$/;McQ8KOnoe] wW@HF&GxgG`2ݫś_ھLiS Jvk~JTUYk(cUʓ> .a)bF/?MO(N_A ښ}/Q(d܍3]6vUjL,8ނ.= 2_ʖ1d,# /TD$^41SSY[6]@~ܠǖ OGd"Ydm|ORt+GB?28+~\&W UE֒U(Bɿ׽7-jC d70L* $Z @WG+װ<]kt.d╧&2ې|ւ-U摇?; '>S(nyU2ĢΦ*կ x,a:ylGk*ɓڗ &Ͼd(Ȥ,(-[[k+55ȏM$/ooJN{aKŅ'hҬާ̘AGo[% .o@:E?@>Ϟ0J}һP{Rӥ{)}rݺli0E TuD'\ KUH5%')up3bwGj1;ɮBsAy^w`4ڋUJU]/ Ճ{ɼN[ڗ'xs` NZ=WWA9r5xj#j?OK~R  `Hdzw^7/)?SuIeX$֠J1Sf_CQڵ-Kk(:ɠ,Mݫm@kbPg^ϠyOY*>vS(YO5˄6:Sj>G_{@ Ilg~cK}:in>9m:Q*:%:m$cݩE/yʗS3ջVfY4;ݳx7E\Ul|Bi~e-bkRߨj<:r*Dc"B}g DY#Ы[YaC.dibߺSL'jo+w7AMjW nW[t oݟ^Mqq O-o(WyݽRtKh:ʔ_6yEԷF'(j=Ghoaf$=U 4xG}[k?(8Qͻ];2^ʉZL5a0ےoЛ^Lq̝|\jȆ@@ &@@I@88 G88'!pC  hGG{  $ Nbt@Mhh@I n @M8! p4=p'1 &p4q NB$@7@@ &@@I@88 G88'!pC  hGG{  $ Nbt@Mhh@I n @M8! p4=p'1 &p4q NB$@7@@ &@@I@88 G88'!pC  hGG{  $ Nbt@Mhh@I n @M8! p4=p'1 &p4q NB$@7@@ &@@Ix_L?&gFF%03b 2`<9   $!͊A 3B0$!͊A 3B0$!͊A 3B0$zeH<ܡ;Vn"t$+^0E`aF pNc  `lc]]4Hc۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ @m_@t @t @M`lbt  K  `lc]]4Hc۾Mq„H)젢#TZq#RZdPy Ǵ@1Qi?Fw`*oC7M[[t~#f{ #ΕjcdL’@d7# s>5K /?ش)ғZ>O/_ O1o_)0P + s NVE5SۇG6"LY}f{:qyZl+/3+ OHuj=B'2#/ijLA+ ]mTѳ^T\j):F>$y=\O4r'>WKNB:ݏ~EM͵4lT|I&sR=?_zrm꾻ZiׁwhHZ2>O*d9y&bG|m͔{r+uuw+Ȃ1*u+k2Qc4>}56U{ JKߢܼtݢ@,pds?rOo_-Gk5ك(<~6wNfq T|rE$::ښ\gͶA I6}Sޒ,#M Ur{qæ({ߧi7dʎo To}m1MVɶ۷yDn O` Z% [2JTr!p$ }Wk;_8_R:Uorr_~"N'O}áP+-7'U?0v1hȹgn]_Ypd:BSՓ.wȄ%*ym ?I޼7^S/|,ޡ,t񾑸h.F%&zAV2'j+= r-j@tU“9Um~yV0N-gwz^WJ#/Y̓_0U՜ӢZZΨRe^{E d6ϣUPXI!14)jjn6|ݯ)?D֗R|U4W1G\NH'yuB_=Yi^?+R{KA'jsU|P䩻DM2MΔ,]?!~ea6OU;r`ؔ?S'7a#Lzy}'ֽCTѺH>!b7I=G^~g}%uM]V ?v/%._{OC&> < ݳeQw[ oW=4TQN/Rgd@Nj$r1"<WXlS=Oj}7]tMJ˿Gͥ=PIc餣jtgۮWO-[ Haadiy3T5/\tڈe1 ~uqd6Y/d&>ud@,D@wbK}9~8͸iE?J 38V+}Iut Z?] ]6̓i :y1gWٺZڤ@͋k.?F_yyrj>{FMVmzZ R7'%kl!كp *,+9iZ>L!( .V[|fy"Y(xrSFro@ywX<$o#2㪒>4y 2E @Xo@N'z>Os&EMANߏ@mi?4%i߃_na*;jbzϏ_D'u5i^4(q*Dž]5TQdQozߊ|LAxqJeꔎUsՁSd2Q PU~ v zN M`j<%cD“<Ϣ Ibd ro=OV?J5|Rx\ 1 -ނT] \GoR]|vƙG6`sߊk_?Q)6p',HEEв/ F%|Fkk)1AYc+@>NZTөjU}t. +O-՟<};}/m}G)_%9j-̙M/NIDRo,ϡ!}Z=u?#o>+B֪wdז{ QmC={SsbXo_ V9~>yGuM1q$/+Uutx+wv͔]_ ysW||tÑ־)N4d"halH9y.X>>R(A2`swO;U#]|Vl@2co] 3R;t3nKjnW}-^'|! 襜Ho-d/ )_ӑ/ZnKotro>Wy#dq/W6r5kT n@FA@5*7 p#c  `ā1DF` @@ @"X#Fq   n`d @X8p702 @QACk ֨ @܀ !5kT n@FA@5*7 p#c  `ā1DF` @@ @"X#Fq   n`d @X8p702 @QACk ֨ @܀ !5kT n@FA@5*7 p#c  `ā1DF` @@ @"X#Fq   n`d @X8p702 @QACk ֨ @܀ !5kT n@FA@n  `lX۾A@@@@ @@ ƶ/F  h &0}1:%E06с..$ kjIENDB`munsell/man/mnsl.Rd0000644000176200001440000000215513307367774013770 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/convert.r \name{mnsl} \alias{mnsl} \alias{mnsl2hex} \title{Converts a Munsell colour to hex} \usage{ mnsl(col, ...) } \arguments{ \item{col}{a character string representing a Munsell colour.} \item{...}{passed on to \code{\link{in_gamut}}. Use \code{fix = TRUE} to fix "bad" colours} } \value{ a character string specification of a hex colour } \description{ Take a character string representation of a Munsell colour and returns the hex specification of that colour } \details{ Munsell colours are specified by hue, value and chroma. They take a form like "5PB 5/10" where the first characters represent the hue, followed by a space then the value and chroma separated by a "/". In this package value should be an integer in 0:10 and chroma an even number at most 24. Note that not all possible specifications result in representable colours. } \examples{ mnsl2hex("5PB 5/10") # use a munsell colour in a plot plot.new() rect(0, 0, 1 ,1 , col = mnsl("5R 5/10")) } \seealso{ \code{\link{check_mnsl}},\code{\link{in_gamut}}, \code{\link{hvc2mnsl}} } munsell/man/rygbp.Rd0000644000176200001440000000104413304561121014111 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{rygbp} \alias{rygbp} \title{Change the hue of a munsell colour} \usage{ rygbp(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of hue steps to take} } \value{ character vector of Munsell colours } \description{ Moves the hue of a munsell colour in the direction red->yellow->green->blue->purple->red } \examples{ my_red <- "10R 4/8" rygbp(my_red) plot_mnsl(c(my_red, rygbp(my_red, 2), rygbp(my_red, 4))) } munsell/man/rgb2mnsl.Rd0000644000176200001440000000126713304561121014523 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/convert.r \name{rgb2mnsl} \alias{rgb2mnsl} \title{Converts an sRGB colour to Munsell} \usage{ rgb2mnsl(R, G = NULL, B = NULL) } \arguments{ \item{R}{a numeric vector of red values or a 3 column matrix with the proportions R, G, B in the columns.} \item{G}{numeric vector of green values} \item{B}{numeric vector of blue values} } \description{ Finds the closest Munsell colour (in LUV space) to the specified sRGB colour } \examples{ rgb2mnsl(0.1, 0.1, 0.3) rgb2mnsl(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) plot_closest(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) } \seealso{ \code{\link{plot_closest}} } munsell/man/chroma_slice.Rd0000644000176200001440000000145113304561121015420 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{chroma_slice} \alias{chroma_slice} \title{Plot all colours with the same chroma} \usage{ chroma_slice(chroma.name = seq(0, 26, by = 2), back.col = "white") } \arguments{ \item{chroma.name}{integer vector of the desired values.} \item{back.col}{colour for the background} } \value{ ggplot object } \description{ Plots slices of the Munsell colour system where chroma is constant. } \examples{ chroma_slice(2) chroma_slice(18) # Maybe want to delete text and add axis instead p <- chroma_slice(18) p$layers[[2]] <- NULL # remove text layer p + ggplot2::theme(axis.text = ggplot2::element_text(), axis.text.x = ggplot2::element_text(angle = 90, hjust = 1)) # all values \dontrun{chroma_slice(seq(0, 38, by = 2))} } munsell/man/value_slice.Rd0000644000176200001440000000103713304561121015263 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{value_slice} \alias{value_slice} \title{Plot all colours with the same value} \usage{ value_slice(value.name = 1:10, back.col = "white") } \arguments{ \item{value.name}{integer vector of the desired values.} \item{back.col}{colour for the background} } \value{ ggplot object } \description{ Plots slices of the Munsell colour system where value is constant. } \examples{ value_slice(2) value_slice(c(2, 4)) # all values \dontrun{value_slice(1:10)} } munsell/man/hvc2mnsl.Rd0000644000176200001440000000252513307362601014534 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/convert.r \name{hvc2mnsl} \alias{hvc2mnsl} \title{Converts a hue, chroma and value to a Munsell colour} \usage{ hvc2mnsl(hue, value = NULL, chroma = NULL, ...) } \arguments{ \item{hue}{a character vector of Munsell hues, or a 3 column data frame containing the hue value and chroma levels} \item{value}{a numeric vector of values} \item{chroma}{a numeric vector of chromas} \item{...}{passed on to \code{\link{check_mnsl}}. Use \code{fix = TRUE} to fix "bad" colours} } \value{ a character string specification of a hex colour } \description{ Takes separate specifications of hue, value and chroma and returns the text specification of that colour. } \details{ Munsell colours are specified by hue, value and chroma. They take a form like "5PB 5/10" where the first characters represent the hue, followed by a space then the value and chroma separated by a "/". In this package value should be an integer in 0:10 and chroma an even number at most 24. Note that not all possible specifications result in representable colours. Regular recycling rules apply. } \examples{ hvc2mnsl("5PB", 5, 10) # All values of 5PB with chroma 10 hvc2mnsl("5PB", 1:9, 10) # note some are undefined plot_mnsl(hvc2mnsl("5PB", 1:9, 10)) } \seealso{ \code{\link{check_mnsl}}, \code{\link{mnsl2hex}} } munsell/man/text_colour.Rd0000644000176200001440000000057113304561121015341 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{text_colour} \alias{text_colour} \title{Get text colour} \usage{ text_colour(cols) } \arguments{ \item{a}{character vector of munsell colours} } \value{ a vector of "black" or "white" } \description{ Get the appropriate text colour for writing on a munsell colour. } \keyword{internal} munsell/man/plot_closest.Rd0000644000176200001440000000142213304561121015500 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{plot_closest} \alias{plot_closest} \title{Plot closest Munsell colour to an sRGB colour} \usage{ plot_closest(R, G = NULL, B = NULL, back.col = "white") } \arguments{ \item{R}{a numeric vector of red values or a 3 column matrix with the proportions R, G, B in the columns.} \item{G}{numeric vector of green values} \item{B}{numeric vector of blue values} \item{back.col}{colour for the background} } \value{ ggplot object } \description{ Take an sRGB colour and plots it along with the closest Munsell colour (using \code{\link{rgb2mnsl}} to find it) } \examples{ plot_closest(0.1, 0.1, 0.3) plot_closest(matrix(c(.1, .2, .4, .5, .6, .8), ncol = 3)) } \seealso{ \code{\link{rgb2mnsl}} } munsell/man/hue_slice.Rd0000644000176200001440000000103713304561121014730 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{hue_slice} \alias{hue_slice} \title{Plot all colours with the same hue} \usage{ hue_slice(hue.name = "all", back.col = "white") } \arguments{ \item{hue.name}{character vector of the desired hues. Or "all" for all hues.} \item{back.col}{colour for the background} } \value{ ggplot object } \description{ Plots slices of the Munsell colour system where hue is constant. } \examples{ hue_slice("5R") hue_slice(c("5R", "5P")) \dontrun{hue_slice("all")} } munsell/man/in_gamut.Rd0000644000176200001440000000135513307362633014610 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/check.r \name{in_gamut} \alias{in_gamut} \title{Checks if a Munsell colour is defined in RGB space} \usage{ in_gamut(col, fix = FALSE) } \arguments{ \item{col}{a character vector representing Munsell colours.} \item{fix}{passed on to \code{\link{fix_mnsl}}. Use \code{fix = TRUE} to fix "bad" colours} } \value{ a character vector containing the input colours. If any colours were outside the gamut they will be represented by NA. } \description{ Not all possible correctly formatted Munsell colours result in a colour representable in RGB space. This function checks if the colour is representable. } \examples{ in_gamut(c("5R 5/8","2.5R 9/28")) } \keyword{internal} munsell/man/saturate.Rd0000644000176200001440000000116013304561121014615 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{saturate} \alias{saturate} \title{Make a munsell colour more saturated} \usage{ saturate(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of steps to take in increasing chroma} } \value{ character vector of Munsell colours } \description{ Increases the chroma of the Munsell colour by step steps (multiples of 2). } \examples{ saturate("5PB 2/4") cols <- c("5PB 2/2", "5Y 7/6") p <- plot_mnsl(c(cols, saturate(cols), saturate(cols, 2))) p + ggplot2::facet_wrap(~ names, ncol = 2) } munsell/man/pbgyr.Rd0000644000176200001440000000105013304561121014106 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{pbgyr} \alias{pbgyr} \title{Change the hue of a munsell colour} \usage{ pbgyr(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of hue steps to take} } \value{ character vector of Munsell colours } \description{ Moves the hue of a munsell colour in the direction purple->blue->green->yellow->red->purple } \examples{ my_red <- "2.5R 4/8" pbgyr(my_red) plot_mnsl(c(my_red, pbgyr(my_red, 2), pbgyr(my_red, 4))) } munsell/man/complement.Rd0000644000176200001440000000122113307537513015141 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{complement} \alias{complement} \title{Find the complement of a munsell colour} \usage{ complement(col, ...) } \arguments{ \item{col}{character vector of Munsell colours} \item{...}{deprecated} } \value{ character vector of Munsell colours } \description{ Finds the munsell colour with the same chroma and value but on the opposite side of the hue circle. The complement is not defined for greys (hue == "N"), and the function returns the grey untransformed. } \examples{ complement("5PB 2/4") cols <- c("5PB 2/4", "5Y 7/8") plot_mnsl(c(cols, complement(cols))) } munsell/man/darker.Rd0000644000176200001440000000110013304561121014227 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{darker} \alias{darker} \title{Make a munsell colour darker} \usage{ darker(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of steps to take in decreasing value} } \value{ character vector of Munsell colours } \description{ Decreases the value of the Munsell colour by 1. } \examples{ darker("5PB 3/4") cols <- c("5PB 3/4", "5Y 7/8") p <- plot_mnsl(c(cols, darker(cols), darker(cols, 2))) p + ggplot2::facet_wrap(~ names, ncol = 2) } munsell/man/theme_munsell.Rd0000644000176200001440000000053313304561121015631 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{theme_munsell} \alias{theme_munsell} \title{Default munsell plot theme} \usage{ theme_munsell(bg.col = "white") } \arguments{ \item{bg.col}{takes colour to use as background colour} } \description{ Removes unnecessary clutter in plots } \keyword{internal} munsell/man/mnsl_hues.Rd0000644000176200001440000000055413304561121014770 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/check.r \name{mnsl_hues} \alias{mnsl_hues} \title{Munsell hues} \usage{ mnsl_hues() } \value{ a character vector containing the hue values. } \description{ Returns a character vector of the Munsell hues in hue order starting at 2.5R and excluding grey ("N"). } \examples{ mnsl_hues() } munsell/man/munsell.Rd0000644000176200001440000000163713304561121014455 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/munsell.r \docType{package} \name{munsell} \alias{munsell} \alias{package-munsell} \alias{munsell-package} \title{Munsell colour system.} \description{ This package makes it easy to access and manipulate the colours in the munsell colour system. The conversion from munsell specifications to sRGB based on the renotation data from \url{http://www.cis.rit.edu/mcsl/online/munsell.php} which is a digitization of Table 1 in Newhall, Nickerson & Judd (1943). The code for conversion can be found in the package directory in inst/raw/getmunsellmap.r } \references{ S. M. Newhall, D. Nickerson, and D. B. Judd. Final report of the O.S.A. subcommittee on the spacing of the munsell colors. J. Opt. Soc. Am., 33(7):385-411, 07 1943. Munsell Renotation Data, RIT Munsell Color Science Laboratory. \url{http://www.cis.rit.edu/mcsl/online/munsell.php} } munsell/man/complement_slice.Rd0000644000176200001440000000102613304561121016310 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{complement_slice} \alias{complement_slice} \title{A vertical slice through the Munsell space} \usage{ complement_slice(hue.name, back.col = "white") } \arguments{ \item{hue.name}{character string of the desired hue.} \item{back.col}{colour for the background} } \value{ ggplot object } \description{ Plot a hue and its complement at all values and chromas } \examples{ complement_slice("5PB") complement_slice("5R") complement_slice("10G") } munsell/man/desaturate.Rd0000644000176200001440000000120013304561121015121 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{desaturate} \alias{desaturate} \title{Make a munsell colour less saturated} \usage{ desaturate(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of steps to take in decreasing chroma} } \value{ character vector of Munsell colours } \description{ Decreases the chroma of the Munsell colour by one step steps (multiples of 2). } \examples{ desaturate("5PB 2/4") cols <- c("5PB 2/6", "5Y 7/8") p <- plot_mnsl(c(cols, desaturate(cols), desaturate(cols, 2))) p + ggplot2::facet_wrap(~ names, ncol = 2) } munsell/man/seq_mnsl.Rd0000644000176200001440000000151113304561121014606 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{seq_mnsl} \alias{seq_mnsl} \title{Generate a sequence of Munsell colours} \usage{ seq_mnsl(from, to, n, fix = FALSE) } \arguments{ \item{from}{character string of first Munsell colour} \item{to}{character string of last Munsell colour} \item{n}{number of colours in sequence} \item{fix}{Should colours outside of the gamut be fixed? Passed on to \code{\link{fix_mnsl}}} } \value{ character vector of Munsell colours } \description{ Generates a sequence of Munsell colours. The sequence is generated by finding the closest munsell colours to a equidistant sequence of colours in #' LUV space. } \examples{ seq_mnsl("5R 2/4", "5R 5/16", 4) plot_mnsl(seq_mnsl("5R 2/4", "5R 5/16", 4)) plot_mnsl(seq_mnsl("5R 5/6", complement("5R 5/6"), 5)) } munsell/man/check_mnsl.Rd0000644000176200001440000000127113307362631015106 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/check.r \name{check_mnsl} \alias{check_mnsl} \title{Checks for valid Munsell colours} \usage{ check_mnsl(col) } \arguments{ \item{col}{a character vector representing Munsell colours.} \item{fix}{passed on to \code{\link{fix_mnsl}}. Use \code{fix = TRUE} to fix "bad" colours} } \value{ a character vector containing the input colours. If any colours were outside the gamut they will be represented by NA. } \description{ Checks user supplied munsell specification for validity. I.e. colour is of form "h v/c" and h, v and c take valid values. } \examples{ check_mnsl(c("5R 5/8","2.5R 9/28")) } \keyword{internal} munsell/man/lighter.Rd0000644000176200001440000000132313304561121014424 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/alter.r \name{lighter} \alias{lighter} \title{Make a munsell colour lighter} \usage{ lighter(col, steps = 1) } \arguments{ \item{col}{character vector of Munsell colours} \item{steps}{number of steps to take in increasing value} } \value{ character vector of Munsell colours } \description{ Increases the value of the Munsell colour. } \examples{ lighter("5PB 2/4") cols <- c("5PB 2/4", "5Y 6/8") p <- plot_mnsl(c(cols, lighter(cols), lighter(cols, 2))) p + ggplot2::facet_wrap(~ names, ncol = 2) # lighter and darker are usually reversible lighter(darker("5PB 2/4")) # unless you try to pass though white or black lighter(darker("5PB 1/4")) } munsell/man/mnsl2hvc.Rd0000644000176200001440000000212013304561121014516 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/convert.r \name{mnsl2hvc} \alias{mnsl2hvc} \title{Converts a Munsell colour to a hue, chroma and value triplet} \usage{ mnsl2hvc(col, ...) } \arguments{ \item{col}{a character vector of Munsell colours} \item{...}{passed on to \code{\link{check_mnsl}}. Use \code{fix = TRUE} to fix "bad" colours} } \value{ a data frame with named columns hue, value and chroma containing the hue, value and chroma levels. } \description{ Takes a text specification of a Munsell colour and returns the hue, chroma and value triplet. } \details{ Munsell colours are specified by hue, value and chroma. They take a form like "5PB 5/10" where the first characters represent the hue, followed by a space then the value and chroma separated by a "/". In this package value should be an integer in 0:10 and chroma an even number at most 24. Note that not all possible specifications result in representable colours. } \examples{ mnsl2hvc("5PB 5/10") hvc2mnsl(mnsl2hvc("5PB 5/10")) } \seealso{ \code{\link{check_mnsl}}, \code{\link{hvc2mnsl}} } munsell/man/fix_mnsl.Rd0000644000176200001440000000116013304561121014604 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/check.r \name{fix_mnsl} \alias{fix_mnsl} \title{Fix an undefined Munsell colour} \usage{ fix_mnsl(col) } \arguments{ \item{col}{a character vector representing Munsell colours.} } \value{ a character vector containing the fixed colours. } \description{ Takes correctly specified but undefined colours and outputs something sensible. Normally this happens when the chroma is too high. So, here sensible means the colour with the same hue and value and maximum defined chroma. } \examples{ fix_mnsl(c("5R 5/8","2.5R 9/28")) } \keyword{internal} munsell/man/plot_hex.Rd0000644000176200001440000000075213304561121014615 0ustar liggesusers% Generated by roxygen2: do not edit by hand % Please edit documentation in R/plot.r \name{plot_hex} \alias{plot_hex} \title{Plot hex colours} \usage{ plot_hex(hex.colour, back.col = "white") } \arguments{ \item{hex.colour}{character vector specifying colours in hex form} \item{back.col}{specification of background colour of display} } \value{ A ggplot object } \description{ Quick way to look at a set of hex colours. } \examples{ plot_hex("#000000") plot_hex(c("#000000","#FFFFFF")) } munsell/LICENSE0000644000176200001440000000005612657221733012747 0ustar liggesusersYEAR: 2016 COPYRIGHT HOLDER: Charlotte Wickham