如何将二维密度图映射到照片上
How to map a two-dimensional density plot onto a photograph
我有一个二维密度图，我需要将其叠加到照片上。我可以用包读入图片 rtiff:
install.packages("rtiff")
library(rtiff)
x <- readTiff('F01_screenshot.tiff')
plot(x)
密度图的数据是一个非常大的数据框，称为 eet2（请参阅下面的可重现数据）；密度图的代码是这样的：
library(ggplot2)
ggplot(eet2, aes(x=X, y= Y)) +
geom_point() + stat_density2d()
我可以很容易地分别制作这两个图，但不知道如何将密度图叠加到照片上，密度图按比例缩小以适合图片.非常感谢任何帮助！
可重现数据:
eet2 <- dput(eet1[1:1000, 2:3])
structure(list(X = c(0, 177.378, 27.289, 0, 852.719, 0, 852.813,
71.068, 0, 144.875, 0, 140.385, 21.598, 0, 170.325, 0, 136.746,
21.038, 0, 146.279, 0, 141.86, 11.822, 0, 146.078, 0, 137.681,
21.182, 0, 148.867, 0, 132.886, 20.444, 0, 146.129, 0, 80.251,
6.688, 0, 141.08, 0, 149.789, 23.044, 0, 74.097, 0, 141.182,
21.72, 0, 83.075, 0, 81.192, 6.766, 0, 849.784, 0, 153.96, 23.686,
0, 78.374, 0, 142.782, 21.967, 0, 72.929, 0, 142.922, 11.91,
0, 83.639, 0, 143.912, 22.14, 0, 134.809, 0, 142.826, 21.973,
0, 132.7, 0, 85.876, 7.156, 0, 138.935, 0, 80.951, 12.454, 0,
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0, 155.341, 23.899, 0, 189.336, 0, 224.517, 34.541, 0, 207.46,
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163.4, 220.05, 210.838, 222.305, 223.069, -196.463, 176.753,
226.515, 217.024, 249.012, 253.277, 203.798, 226.753, 228.283,
241.225, 228.683, 227.011, 235.665, 243.606, 244.664, 212.621,
240.812, 242.692, 207.285, 207.473, 207.498, 194.745, 202.346,
203.359, 191.408, -221.759, -249.304, 186.022, 192.304, 193.141,
182.101, 191.751, 193.037, -260.225, 162.901, 191.109, -252.884,
141.317, 193.877, 186.754, 220.72, 225.249, 0, 0, 0, 0, 0, 0,
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352.419, 54.218, 0, 368.749, 0, 378.178, 31.515, 0, 378.548,
0, 339.912, 385.233, 406.951, 373.432, 368.963, 411.64, 362.786,
359.529, 358.897, 353.738, 353.051, 336.054, 340.344, 340.915,
335.944, 355.461, 356.762, 345.061, 372.321, 375.955, 376.513,
404.13, 407.812, 416.338, 426.28, 426.943, 432.67, 429.483, 429.058,
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261.561, 21.797, 0, 298.1, 0, 281.941, 43.375, 0, 314.226, 0,
304.413, 46.833, 0, 374.171, 0, 368.525, 30.71, 0, 359.118, 0,
367.905, 56.601, 0, 287.494, 0, 285.213, 43.879, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 304.619, 0)), row.names = 31537:32536, class = "data.frame")
这应该为您提供了一种获取所需图像的方法。但是，我没有你原来的 TIFF，因此这里的对齐方式不正确，因为我不得不在你的问题中使用 cut-and-pasted 版本的 png。
反正我会用的方法是：
- 将图像转换为光栅
- 将栅格转换为
grid::rasterGrob
- 使用
annotation_custom 将 rasterGrob 绘制为 ggplot 中的第一层
- 正常绘制其他图层。
这是一个例子：
library(ggplot2)
library(rtiff)
library(grid)
x <- readTiff('F01_screenshot.tiff')
pic <- as.raster(array(c(x@red, x@green, x@blue), c(x@size, 3)))
picgrob <- rasterGrob(pic)
ggplot(eet2, aes(x=X, y= Y)) +
annotation_custom(picgrob) +
geom_point() +
stat_density2d() +
coord_equal()
您可能需要缩放 Y 轴数据以使其与图片的纵横比匹配。
举个例子，如果我们假设 max(eet2$Y) 是图像的上边缘，min(eet2$Y) 是下边缘，还假设 min(eet2$X) 是左边缘 max(eet2$X) 右边缘（正如你在评论中所建议的那样），我们可以像这样将图片与数据结合起来：
pic_ratio <- dim(pic)[2]/dim(pic)[1]
data_ratio <- diff(range(eet2$X)) / diff(range(eet2$Y))
eet2$Y <- eet2$Y * data_ratio / pic_ratio
ggplot(eet2, aes(x=X, y= Y)) +
annotation_custom(picgrob) +
geom_point() +
stat_density2d() +
coord_equal(xlim = range(eet2$X), ylim = range(eet2$Y))
如果此对齐不正确，那么我们需要数据中不存在的额外校准信息（即 eet2$Y 的值应该 代表顶部和底部图像，eet2$X 的值代表左右边缘。
我有一个二维密度图，我需要将其叠加到照片上。我可以用包读入图片 rtiff:
install.packages("rtiff")
library(rtiff)
x <- readTiff('F01_screenshot.tiff')
plot(x)
密度图的数据是一个非常大的数据框，称为 eet2（请参阅下面的可重现数据）；密度图的代码是这样的：
library(ggplot2)
ggplot(eet2, aes(x=X, y= Y)) +
geom_point() + stat_density2d()
我可以很容易地分别制作这两个图，但不知道如何将密度图叠加到照片上，密度图按比例缩小以适合图片.非常感谢任何帮助！
可重现数据:
eet2 <- dput(eet1[1:1000, 2:3])
structure(list(X = c(0, 177.378, 27.289, 0, 852.719, 0, 852.813,
71.068, 0, 144.875, 0, 140.385, 21.598, 0, 170.325, 0, 136.746,
21.038, 0, 146.279, 0, 141.86, 11.822, 0, 146.078, 0, 137.681,
21.182, 0, 148.867, 0, 132.886, 20.444, 0, 146.129, 0, 80.251,
6.688, 0, 141.08, 0, 149.789, 23.044, 0, 74.097, 0, 141.182,
21.72, 0, 83.075, 0, 81.192, 6.766, 0, 849.784, 0, 153.96, 23.686,
0, 78.374, 0, 142.782, 21.967, 0, 72.929, 0, 142.922, 11.91,
0, 83.639, 0, 143.912, 22.14, 0, 134.809, 0, 142.826, 21.973,
0, 132.7, 0, 85.876, 7.156, 0, 138.935, 0, 80.951, 12.454, 0,
144.385, 0, 141.716, 21.802, 0, 76.768, 0, 74.406, 6.2, 0, 134.444,
0, 155.341, 23.899, 0, 189.336, 0, 224.517, 34.541, 0, 207.46,
0, 216.122, 18.01, 0, 204.552, 0, 208.524, 32.081, 0, 207.513,
0, 203.162, 31.256, 0, 197.578, 0, 204.362, 17.03, 0, 195.223,
0, 956.396, 147.138, 0, 201.969, 0, 224.989, 34.614, 0, 214.064,
0, 140.374, 11.698, 0, 140.235, 0, 958.501, 147.462, 0, 141.898,
0, 143.337, 22.052, 0, 955.901, 0, 954.965, 79.58, 0, 131.323,
0, 223.214, 34.341, 0, 952.203, 0, 143.102, 22.016, 0, 935.525,
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0, 128.336, 19.744, 0, 913.158, 0, 120.076, 10.006, 0, 911.196,
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261.818, 265.634, 266.479, 266.592, 266.39, 262.751, 262.508,
265.093, 262.666, 262.343, 1059.856, 1075.848, 1077.98, 1068.255,
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1103.801, 1097.674, 1097.266, 1110.129, 1105.4, 1104.769, 1115.638,
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71.807, 0, 851.287, 855.415, 855.965, 859.554, 864.523, 865.185,
868.109, 873.22, 873.561, 845.881, 882.877, 887.81, 893.391,
899.782, 900.634, 908.492, 56.781, 0, 0, 0, 0, 0, 0, 0, 319.09,
0, 0, 0, 0, 0, 0, 0, 0, 0, 696.905, 0, 704.008, 58.667, 0, 0,
0, 0, 677.276, 673.676, 673.195, 673.45, 671.209, 671.06, 672.474,
674.07, 674.283, 674.896, 656.33, 653.855, 678.654, 681.884,
682.099, 684.933, 715.507, 719.584, 735.659, 1290.244, 1364.188,
1362.632, 1366.322, 1366.568, 1371.973, 1364.1, 1363.051, 1361.383,
812.325, 739.117, 734.716, 1322.199, 1361.365, 730.422, 731.132,
731.227, 729.084, 724.164, 723.507, 726.199, 725.939, 725.922,
725.437, 1278.917, 1352.714, 726.791, 1281.431, 1355.383, 1366.558,
764.435, 724.294, 725.46, 724.544, 724.422, 724.178, 1288.932,
1364.232, 723.902, 680.495, 677.601, 724.172, 722.856, 722.681,
735.236, 743.706, 744.835, 554.779, 735.387, 747.427, 724.914,
720.25, 719.628, 721.122, 742.971, 745.884, 742.171, 737.947,
737.665, 729.207, 808.032, 818.542, 905.216, 106.496, 0, 1169.534,
0, 1195.852, 99.654, 0, 1236.396, 0, 0, 0, 0, 1190.473, 183.15,
0, 1143.686, 1132.754, 1132.025, 1123.856, 1103.6, 1100.9, 1083.716,
1079.191, 1078.588, 1083.785, 1070.395, 1069.503, 1066.885, 1065.121,
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0, 1019.684, 1087.663, 286.389, 33.693, 0, 1117.064, 0, 1114.254,
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270.639, 0, 1060.434, 88.369, 0, 1054.964, 1047.876, 1046.931,
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1087.272, 1087.283, 1087.283, 1086.689, 1087.19, 1087.257, 1089.988,
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1075.399, 1073.48, 1103.711, 1076.133, 1072.456, 1104.247, 1105.181,
1105.305, 1072.744, 1104.02, 1106.105, 1074.673, 1102.759, 1106.503,
1076.082, 1104.401, 1108.177, 1078.025, 1109.772, 1111.888, 288.949,
292.278, 292.722, 1112.981, 1123.139, 1124.493, 1127.996, 1134.943,
1135.406, 1136.071, 1141.749, 1142.506, 1148.754, 1150.764, 1151.032,
1156.093, 1154.597, 1154.497, 1150.481, 1124.218, 1120.716, 1108.646,
1095.181, 1093.385, 1113.175, 1089.783, 1088.224, 1719.795, -286.164,
-553.625, 1112.49, 1099.064, 1097.274, 1106.601, 1105.705, 1105.645,
1100.75, 1110.143, 1111.395, 1114.044, 1108.662, 1107.944, 1115.615,
1114.492, 1114.417, 296.606, 1011.559, 1106.886, 213.15, 735.037,
804.622, 643.816, 590.868, 587.338, 588.443, 591.022, 591.366,
595.437, 598.575, 598.994, -70.23, 562.977, 605.191, 608.988,
14.755, -64.476, -86.326, 490.189, 567.057, 573.015, 572.841,
572.83, 576.607, 578.243, 578.461, 579.714, 1343.595, 1445.446,
585.277, 588.153, 588.345, 588.809, 588.843, 588.848, 592.898,
591.447, 591.254, 592.538, 589.623, 589.429, 590.233, 587.901,
587.59, 589.276, 603.526, 605.426, 691.889, 810.649, 818.566,
889.948, 866.466, 863.335, 164.367, 164.895, 164.966, 158.056,
851.73, 897.975, 164.51, 806.786, 892.423, 894.069, 892.465,
892.251, 153.408, 842.909, 888.876, 151.935, 802.889, 889.683,
154.817, 146.446, 145.329, 888.428, 193.529, 147.202, 885.088,
224.817, 136.78, 147.255, 802.581, 889.958, 888.64, 889.975,
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872.007, 893.987, 895.452, 859.373, 892.292, 896.681, 859.84,
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847.791, 847.716, 847.847, 849.008, 849.163, 133.198, 806.744,
851.647, 146.291, 773.622, 857.267, 860.622, 834.937, 831.512,
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0, 659.733, 0, 603.775, 684.278, 696.548, 689.181, 688.198, 687.25,
682.216, 681.881, 711.089, 713.482, 713.802, 713.969, 715.124,
715.278, 711.369, 709.299, 709.162, 679.428, 675.016, 674.428,
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705.116, 0, 711.882, 109.52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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253.356, 255.099, 251.122, 262.086, 262.817, 258.677, 268.433,
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279.424, 280.077, 271.785, 281.741, 283.068, 276.083, 284.162,
285.239, 279.865, 291.741, 292.533, 291.52, 302.124, 303.538,
300.685, 313.141, 314.802, 313.594, 327.048, 327.945, 325.593,
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530.014, 516.432, 514.621, 494.618, 478.341, 477.256, 456.114,
458.922, 459.297, 456.514, 425.5, 421.365, 462.707, 472.408,
473.055, 467.768, 454.51, 452.742, 441.741, 201.307, 169.249,
167.631, 163.795, 163.539, 160.509, 161.775, 161.943, 161.298,
397.997, 429.557, 419.546, 177.979, 161.875, 418.022, 423.34,
424.049, 413.55, 419.645, 420.457, 407.472, 415.496, 416.031,
407.006, 148.509, 114.042, 409.442, 164.128, 131.419, 109.849,
407.293, 427.122, 418.844, 426.465, 427.481, 417.779, 161.317,
127.123, 409.12, 367.918, 365.171, 395.673, 396.298, 396.381,
388.306, 392.859, 393.466, 473.545, 400.213, 395.325, 366.771,
370.934, 371.489, 339.469, 387.501, 393.905, 386.022, 390.883,
391.207, 378.721, 394.352, 396.436, 384.581, 45.245, 0, 380.042,
0, 375.485, 31.29, 0, 335.187, 0, 0, 0, 0, 323.048, 49.7, 0,
359.169, 361.068, 361.195, 348.111, 362.176, 364.051, 383.932,
392.518, 393.663, 349.699, 392.668, 395.532, 391.36, 396.741,
397.458, 387.906, 391.383, 391.846, 371.849, 378.048, 378.461,
318.908, 357.694, 362.865, 342.973, 40.35, 0, 288.149, 0, 259.291,
276.577, -102.466, -12.055, 0, 241.977, 0, 234.288, 36.044, 0,
247.849, 0, 244.967, 20.414, 0, 290.17, 0, 258.996, 39.846, 0,
269.854, 0, 259.002, 39.847, 0, 297.18, 0, 266.569, 22.214, 0,
-87.029, 0, -89.617, -13.787, 0, -95.348, -79.043, -76.869, 0,
246.968, 20.581, 0, 272.257, 289.812, 292.152, 271.933, 287.652,
289.748, 276.443, 284.481, 285.017, -116.323, 230.711, 276.983,
-141.084, 229.411, 278.81, 314.961, 280.304, 277.994, 277.686,
282.62, 283.278, 287.306, 282.107, 281.414, 290.288, 291.936,
292.045, 288.296, 302.772, 304.702, 292.15, 302.242, 303.588,
-136.669, 270.271, 297.4, 274.154, 301.517, 305.165, 290.369,
-426.184, -521.724, 321.366, 329.046, 329.558, 321.7, 306.849,
304.869, 321.009, 327.981, 328.91, 290.339, 328.378, 330.914,
289.022, 325.172, 329.992, 288.447, 295.19, 296.089, 322.57,
298.091, 296.459, 321.394, 300.861, 298.123, 320.881, 300.679,
297.985, 319.966, 296.464, 294.897, -164.893, -160.079, -159.437,
278.924, 281.357, 281.682, 269.259, 274.752, 275.118, 267.165,
265.143, 264.873, 258.509, 264.614, 265.429, 256.744, 266.259,
266.893, 263.361, 301.473, 306.555, 262.416, 313.245, 320.022,
281.712, 320.535, 323.123, -194.846, -521.034, -564.526, 274.367,
278.267, 278.787, 264.133, 268.555, 268.85, 256.818, 266.194,
267.444, 260.084, 265.714, 266.464, 262.669, 272.063, 272.689,
-175.62, 225.568, 279.06, -159.431, 216.327, 266.428, 245.597,
254.043, 254.606, 244.851, 255.798, 257.258, 248.152, 256.508,
257.622, -319.948, 219.787, 255.769, 243.947, -235.689, -299.64,
-334.288, 164.071, 230.518, 224.188, 233.409, 234.024, 228.544,
236.363, 237.405, 235.462, -116.121, -162.999, 240.889, 251.796,
252.524, 246.8, 258.72, 260.309, 257.726, 267.828, 269.175, 265.087,
277.995, 278.856, 273.876, 287.09, 288.852, 280.858, 292.608,
294.174, 246.387, 213.675, 211.494, 201.469, 209.375, 210.429,
-217.38, -218.456, -218.6, -232.09, 196.612, 225.193, -248.699,
166.3, 221.633, 213.54, 219.095, 219.836, -261.438, 192.469,
222.729, -265.48, 164.234, 221.529, -254.99, -254.199, -254.094,
209.197, -218.172, -246.663, 207.52, -196.823, -250.735, -261.477,
163.4, 220.05, 210.838, 222.305, 223.069, -196.463, 176.753,
226.515, 217.024, 249.012, 253.277, 203.798, 226.753, 228.283,
241.225, 228.683, 227.011, 235.665, 243.606, 244.664, 212.621,
240.812, 242.692, 207.285, 207.473, 207.498, 194.745, 202.346,
203.359, 191.408, -221.759, -249.304, 186.022, 192.304, 193.141,
182.101, 191.751, 193.037, -260.225, 162.901, 191.109, -252.884,
141.317, 193.877, 186.754, 220.72, 225.249, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 304.742, 0, 316.744, 48.73, 0, 334.833, 0,
352.419, 54.218, 0, 368.749, 0, 378.178, 31.515, 0, 378.548,
0, 339.912, 385.233, 406.951, 373.432, 368.963, 411.64, 362.786,
359.529, 358.897, 353.738, 353.051, 336.054, 340.344, 340.915,
335.944, 355.461, 356.762, 345.061, 372.321, 375.955, 376.513,
404.13, 407.812, 416.338, 426.28, 426.943, 432.67, 429.483, 429.058,
426.368, 425.226, 425.074, 416.298, 411.677, 411.369, 0, 345.327,
53.127, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 183.69, 208.182, 0,
261.561, 21.797, 0, 298.1, 0, 281.941, 43.375, 0, 314.226, 0,
304.413, 46.833, 0, 374.171, 0, 368.525, 30.71, 0, 359.118, 0,
367.905, 56.601, 0, 287.494, 0, 285.213, 43.879, 0, 0, 0, 0,
0, 735.244, 113.115, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 304.619, 0)), row.names = 31537:32536, class = "data.frame")
这应该为您提供了一种获取所需图像的方法。但是，我没有你原来的 TIFF，因此这里的对齐方式不正确，因为我不得不在你的问题中使用 cut-and-pasted 版本的 png。
反正我会用的方法是：
- 将图像转换为光栅
- 将栅格转换为
grid::rasterGrob - 使用
annotation_custom 将 rasterGrob 绘制为 ggplot 中的第一层
- 正常绘制其他图层。
这是一个例子：
library(ggplot2)
library(rtiff)
library(grid)
x <- readTiff('F01_screenshot.tiff')
pic <- as.raster(array(c(x@red, x@green, x@blue), c(x@size, 3)))
picgrob <- rasterGrob(pic)
ggplot(eet2, aes(x=X, y= Y)) +
annotation_custom(picgrob) +
geom_point() +
stat_density2d() +
coord_equal()
您可能需要缩放 Y 轴数据以使其与图片的纵横比匹配。
举个例子，如果我们假设 max(eet2$Y) 是图像的上边缘，min(eet2$Y) 是下边缘，还假设 min(eet2$X) 是左边缘 max(eet2$X) 右边缘（正如你在评论中所建议的那样），我们可以像这样将图片与数据结合起来：
pic_ratio <- dim(pic)[2]/dim(pic)[1]
data_ratio <- diff(range(eet2$X)) / diff(range(eet2$Y))
eet2$Y <- eet2$Y * data_ratio / pic_ratio
ggplot(eet2, aes(x=X, y= Y)) +
annotation_custom(picgrob) +
geom_point() +
stat_density2d() +
coord_equal(xlim = range(eet2$X), ylim = range(eet2$Y))
如果此对齐不正确，那么我们需要数据中不存在的额外校准信息（即 eet2$Y 的值应该 代表顶部和底部图像，eet2$X 的值代表左右边缘。