更改颜色数据点 plotLearnerPrediction(MLR 包)
change color data points plotLearnerPrediction (MLR package)
我用 MLR 包的 plotLearnerPrediction 函数制作了一些不错的图。我能够对返回的 ggplot 进行一些调整(请参阅下面的代码)。但我不确定如何进行最后的调整。也就是说,我想根据标签(示例图中的组)更改数据点的颜色。
My last plot (with black data points)
Another produced plot (overlapping data points)
这是我的代码的最后一个版本(通常是 for 循环的一部分):
plot <- plotLearnerPrediction(learner = learner_name, task = tasks[[i]], cv = 0,
pointsize = 1.5, gridsize = 500) +
ggtitle(trimws(sprintf("Predictions %s %s", meta$name[i], meta$nr[i])),
subtitle = sprintf("DR = %s, ML = %s, CV = LOO, ACC = %.2f", meta$type[i],
toupper(strsplit(learner_name, "classif.")[[1]][2]), acc[[i]])) +
xlab(sprintf("%s 1", lab)) +
ylab(sprintf("%s 2", lab)) +
scale_fill_manual(values = colors) +
theme(plot.title = element_text(size = 18, face = "bold"),
plot.subtitle = element_text(size = 12, face = "bold", colour = "grey40"),
axis.text.x = element_text(vjust = 0.5, hjust = 1),
axis.text = element_text(size = 14, face = "bold"),
axis.title.x = element_text(vjust = 0.5),
axis.title = element_text(size = 16, face = "bold"),
#panel.grid.minor = element_line(colour = "grey80"),
axis.line.x = element_line(color = "black", size = 1),
axis.line.y = element_line(color = "black", size = 1),
panel.grid.major = element_line(colour = "grey80"),
panel.background = element_rect(fill = "white"),
legend.justification = "top",
legend.margin = margin(l = 0),
legend.title = element_blank(),
legend.text = element_text(size = 14))
以下是plotLearnerPrediction函数的部分源代码。我想否决 geom_point(colour = "black")。简单地向我的代码添加 geom_point(colour = "pink") 不会为数据点着色,而是为整个图着色。有没有一种解决方案可以用颜色矢量否决该代码?可能还需要更改 aes() 以根据组更改颜色。
else if (taskdim == 2L) {
p = ggplot(mapping = aes_string(x = x1n, y = x2n))
p = p + geom_tile(data = grid, mapping = aes_string(fill = target))
p = p + scale_fill_gradient2(low = bg.cols[1L], mid = bg.cols[2L],
high = bg.cols[3L], space = "Lab")
p = p + geom_point(data = data, mapping = aes_string(x = x1n,
y = x2n, colour = target), size = pointsize)
p = p + geom_point(data = data, mapping = aes_string(x = x1n,
y = x2n), size = pointsize, colour = "black",
shape = 1)
p = p + scale_colour_gradient2(low = bg.cols[1L],
mid = bg.cols[2L], high = bg.cols[3L], space = "Lab")
p = p + guides(colour = FALSE)
}
plotLearnerPrediction()
函数 returns ggplot
绘图对象,它允许进行某种程度的自定义,而无需修改源代码。在您的特定情况下,您可以使用 scale_fill_manual()
设置自定义填充颜色:
library(mlr)
g = plotLearnerPrediction(makeLearner("classif.randomForest"), iris.task)
g + scale_fill_manual(values = c("yellow", "orange", "red"))
你总是可以破解 gg 对象。以下适用于 ggplot2 2.2.1 并向所有 geom_point 层添加手动 alpha 值。
library(mlr)
library(ggplot2)
g = plotLearnerPrediction(makeLearner("classif.qda"), iris.task)
ids.geom.point = which(sapply(g$layers, function(z) class(z$geom)[[1]]) == "GeomPoint")
for(i in ids.geom.point) {
g$layers[[i]]$aes_params$alpha = 0.1
}
g
我用 MLR 包的 plotLearnerPrediction 函数制作了一些不错的图。我能够对返回的 ggplot 进行一些调整(请参阅下面的代码)。但我不确定如何进行最后的调整。也就是说,我想根据标签(示例图中的组)更改数据点的颜色。
My last plot (with black data points)
Another produced plot (overlapping data points)
这是我的代码的最后一个版本(通常是 for 循环的一部分):
plot <- plotLearnerPrediction(learner = learner_name, task = tasks[[i]], cv = 0,
pointsize = 1.5, gridsize = 500) +
ggtitle(trimws(sprintf("Predictions %s %s", meta$name[i], meta$nr[i])),
subtitle = sprintf("DR = %s, ML = %s, CV = LOO, ACC = %.2f", meta$type[i],
toupper(strsplit(learner_name, "classif.")[[1]][2]), acc[[i]])) +
xlab(sprintf("%s 1", lab)) +
ylab(sprintf("%s 2", lab)) +
scale_fill_manual(values = colors) +
theme(plot.title = element_text(size = 18, face = "bold"),
plot.subtitle = element_text(size = 12, face = "bold", colour = "grey40"),
axis.text.x = element_text(vjust = 0.5, hjust = 1),
axis.text = element_text(size = 14, face = "bold"),
axis.title.x = element_text(vjust = 0.5),
axis.title = element_text(size = 16, face = "bold"),
#panel.grid.minor = element_line(colour = "grey80"),
axis.line.x = element_line(color = "black", size = 1),
axis.line.y = element_line(color = "black", size = 1),
panel.grid.major = element_line(colour = "grey80"),
panel.background = element_rect(fill = "white"),
legend.justification = "top",
legend.margin = margin(l = 0),
legend.title = element_blank(),
legend.text = element_text(size = 14))
以下是plotLearnerPrediction函数的部分源代码。我想否决 geom_point(colour = "black")。简单地向我的代码添加 geom_point(colour = "pink") 不会为数据点着色,而是为整个图着色。有没有一种解决方案可以用颜色矢量否决该代码?可能还需要更改 aes() 以根据组更改颜色。
else if (taskdim == 2L) {
p = ggplot(mapping = aes_string(x = x1n, y = x2n))
p = p + geom_tile(data = grid, mapping = aes_string(fill = target))
p = p + scale_fill_gradient2(low = bg.cols[1L], mid = bg.cols[2L],
high = bg.cols[3L], space = "Lab")
p = p + geom_point(data = data, mapping = aes_string(x = x1n,
y = x2n, colour = target), size = pointsize)
p = p + geom_point(data = data, mapping = aes_string(x = x1n,
y = x2n), size = pointsize, colour = "black",
shape = 1)
p = p + scale_colour_gradient2(low = bg.cols[1L],
mid = bg.cols[2L], high = bg.cols[3L], space = "Lab")
p = p + guides(colour = FALSE)
}
plotLearnerPrediction()
函数 returns ggplot
绘图对象,它允许进行某种程度的自定义,而无需修改源代码。在您的特定情况下,您可以使用 scale_fill_manual()
设置自定义填充颜色:
library(mlr)
g = plotLearnerPrediction(makeLearner("classif.randomForest"), iris.task)
g + scale_fill_manual(values = c("yellow", "orange", "red"))
你总是可以破解 gg 对象。以下适用于 ggplot2 2.2.1 并向所有 geom_point 层添加手动 alpha 值。
library(mlr)
library(ggplot2)
g = plotLearnerPrediction(makeLearner("classif.qda"), iris.task)
ids.geom.point = which(sapply(g$layers, function(z) class(z$geom)[[1]]) == "GeomPoint")
for(i in ids.geom.point) {
g$layers[[i]]$aes_params$alpha = 0.1
}
g