如何在照片上绘制二维密度图

问题描述

我有一个二维密度图，需要将其叠加到照片上。我可以用rtiff包读入图片：

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（请参见下面的可再现数据）；密度图的代码是这样的：

library(ggplot2)
ggplot(eet2,aes(x=X,y= Y)) +
  geom_point() + stat_density2d()

我可以轻松地分别生成两个图，但是不知道如何将密度图叠加到照片上，从而使密度图按比例缩小以适合图片。任何帮助深表感谢！

可复制的数据：

eet2 <- dput(eet1[1:1000,2:3])
structure(list(X = c(0,177.378,27.289,852.719,852.813,71.068,144.875,140.385,21.598,170.325,136.746,21.038,146.279,141.86,11.822,146.078,137.681,21.182,148.867,132.886,20.444,146.129,80.251,6.688,141.08,149.789,23.044,74.097,141.182,21.72,83.075,81.192,6.766,849.784,153.96,23.686,78.374,142.782,21.967,72.929,142.922,11.91,83.639,143.912,22.14,134.809,142.826,21.973,132.7,85.876,7.156,138.935,80.951,12.454,144.385,141.716,21.802,76.768,74.406,6.2,134.444,155.341,23.899,189.336,224.517,34.541,207.46,216.122,18.01,204.552,208.524,32.081,207.513,203.162,31.256,197.578,204.362,17.03,195.223,956.396,147.138,201.969,224.989,34.614,214.064,140.374,11.698,140.235,958.501,147.462,141.898,143.337,22.052,955.901,954.965,79.58,131.323,223.214,34.341,952.203,143.102,22.016,935.525,918.238,76.52,123.337,127.93,19.682,915.755,128.336,19.744,913.158,120.076,10.006,911.196,124.387,19.136,911.631,911.389,140.214,910.433,119.375,9.948,115.898,910.073,140.011,915.461,965.025,148.465,1125.565,1074.389,165.291,1061.611,1051.23,161.728,1044.3,269.733,22.478,245.869,206.934,234.525,245.609,250.874,251.576,260.164,262.974,263.161,269.25,262.693,261.818,265.634,266.479,266.592,266.39,262.751,262.508,265.093,262.666,262.343,1059.856,1075.848,1077.98,1068.255,1065.442,1065.255,1071.821,1072.292,1072.355,1073.788,1072.572,1072.41,1074.295,1074.487,1074.499,1078.434,1080.074,1080.293,1081.104,1080.014,1079.869,1080.261,1080.181,1080.175,1078.568,1079.422,1079.536,1078.84,1077.459,1077.275,1077.805,1076.787,1076.719,1077.199,1076.045,1075.891,1077.362,1076.663,1076.569,1077.942,1078.842,1078.902,1078.713,1080.023,1080.198,1080.764,1081.553,1081.659,1081.946,1082.445,1082.479,1083.987,1084.113,1084.13,1084.741,1085.809,1085.952,1085.031,1084.708,1084.686,1085.901,1085.266,1085.181,1085.513,1085.159,1085.112,1088.024,1088.29,1088.308,1088.889,1088.327,1088.252,1069.543,1065.069,1064.472,1067.409,1068.075,1068.119,1068.377,1070.019,1070.238,1072.384,1071.454,1071.33,1072.31,1069.704,1069.53,1068.856,1073.986,1074.67,1075.824,1077.42,1077.633,1080.095,1082.62,1082.788,1087.112,1090.026,1090.414,1094.654,1098.678,1099.215,1103.801,1097.674,1097.266,1110.129,1105.4,1104.769,1115.638,1115.922,1115.96,1115.612,1115.278,1115.256,1114.682,1112.96,1112.73,1063.573,948.249,932.873,844.512,834.23,833.545,865.203,867.402,867.695,838.499,864.3,867.74,837.215,864.187,865.985,760.653,862.073,861.199,860.757,860.699,861.681,71.807,851.287,855.415,855.965,859.554,864.523,865.185,868.109,873.22,873.561,845.881,882.877,887.81,893.391,899.782,900.634,908.492,56.781,319.09,696.905,704.008,58.667,677.276,673.676,673.195,673.45,671.209,671.06,672.474,674.07,674.283,674.896,656.33,653.855,678.654,681.884,682.099,684.933,715.507,719.584,735.659,1290.244,1364.188,1362.632,1366.322,1366.568,1371.973,1364.1,1363.051,1361.383,812.325,739.117,734.716,1322.199,1361.365,730.422,731.132,731.227,729.084,724.164,723.507,726.199,725.939,725.922,725.437,1278.917,1352.714,726.791,1281.431,1355.383,1366.558,764.435,724.294,725.46,724.544,724.422,724.178,1288.932,1364.232,723.902,680.495,677.601,724.172,722.856,722.681,735.236,743.706,744.835,554.779,735.387,747.427,724.914,720.25,719.628,721.122,742.971,745.884,742.171,737.947,737.665,729.207,808.032,818.542,905.216,106.496,1169.534,1195.852,99.654,1236.396,1190.473,183.15,1143.686,1132.754,1132.025,1123.856,1103.6,1100.9,1083.716,1079.191,1078.588,1083.785,1070.395,1069.503,1066.885,1065.121,1064.885,1064.401,1065.285,1065.403,1075.009,1076.036,1076.105,1086.308,1075.821,1074.423,1073.282,126.268,1092.281,1019.684,1087.663,286.389,33.693,1117.064,1114.254,171.424,1111.518,1110.347,92.529,1077.293,1107.754,170.424,1107.136,1076.571,165.626,1067.475,1110.71,92.559,274.852,280.654,43.177,280.278,271.773,270.639,1060.434,88.369,1054.964,1047.876,1046.931,1052.977,1064.93,1066.524,1061.181,1069.339,1069.883,275.888,970.662,1063.299,268.308,974.232,1068.355,1044.757,1065.286,1066.655,1076.68,1085.54,1086.721,1088.216,1083.409,1082.768,1087.272,1087.283,1086.689,1087.19,1087.257,1089.988,1087.837,1087.55,272.953,1040.007,1091.144,1076.712,1089.387,1091.077,1103.104,-360.56,-555.715,1072.081,1073.131,1073.201,1073.04,1089.257,1091.419,1072.888,1073.111,1073.141,1104.182,1075.399,1073.48,1103.711,1076.133,1072.456,1104.247,1105.181,1105.305,1072.744,1104.02,1106.105,1074.673,1102.759,1106.503,1076.082,1104.401,1108.177,1078.025,1109.772,1111.888,288.949,292.278,292.722,1112.981,1123.139,1124.493,1127.996,1134.943,1135.406,1136.071,1141.749,1142.506,1148.754,1150.764,1151.032,1156.093,1154.597,1154.497,1150.481,1124.218,1120.716,1108.646,1095.181,1093.385,1113.175,1089.783,1088.224,1719.795,-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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= 31537:32536,class = "data.frame")

解决方法

这应该为您提供一种获取所需图像的方法。但是，我没有您的原始TIFF，因此这里的对齐方式不正确，因为我必须在问题中使用png的剪切粘贴版本。

无论如何，我将使用的方法是：

1. 将图像转换为栅格
2. 将栅格转换为grid::rasterGrob
3. 使用annotation_custom
将rasterGrob绘制为ggplot中的第一层
4. 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。

作为示例，如果我们假设max(eet2$Y)是图像的顶部边缘，而min(eet2$Y)是图像的底部边缘，并且还假设min(eet2$X)是图像的顶部边缘和{{1 }}的右边缘（正如您所建议的那样，您可以在注释中使用这种情况），我们可以将图片与以下数据结合起来：

max(eet2$X)

如果对齐方式不正确，则我们需要数据中不存在的额外校准信息（即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,y= Y)) + annotation_custom(picgrob) + geom_point() + stat_density2d() + coord_equal(xlim = range(eet2$X),ylim = range(eet2$Y)) 应的值代表图像的顶部和底部，以及什么？值eet2$Y代表左右边缘。