ggplot2：多个密度图与父直方图分布不匹配
[英]ggplot2: Multiple density plots not matching parent histogram distribution
问题描述
I am interested in creating a plot consisting of a histogram with two density plots overlayed. 
我有兴趣创建一个由直方图组成的图，其中两个密度图重叠。 These density plots consist of points from the parent histogram distribution. 这些密度图由父直方图分布中的点组成。 What I would like to see is like the plot seen in this question - see the answer that produced the red and green distributions. 我想看到的就像在这个问题中看到的情节 - 看到产生红色和绿色分布的答案。
Here is my data: 这是我的数据：
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I have attempted to mimic the plot in the answer above by creating new dataframes indicating membership in the child distributions. 我试图通过创建指示子分布中成员资格的新数据帧来模仿上面答案中的情节。 Assign the data above to the variable dat . 将上面的数据分配给变量dat 。
library(ggplot2)
g1 <- dat[dat$Filter == "Signal", ]
g2 <- dat[dat$Filter == "Background", ]
ggplot(dat, aes(x = Cutoff)) +
geom_histogram(aes(y = ..density..), fill = "grey60", bins = 100) +
stat_function(fun = dnorm,
args = list(mean = mean(g1$Cutoff),
sd = sd(g1$Cutoff)),
geom = "density",
fill = "chartreuse3",
alpha = 0.5) +
stat_function(fun = dnorm,
args = list(mean = mean(g2$Cutoff),
sd = sd(g2$Cutoff)),
geom = "density",
fill = "firebrick2",
alpha = 0.5) +
theme_bw()
However, the plot that I get from this looks like this: 但是，我从中得到的情节如下：
While the density plots follow the general shape of the histogram, the red peak appears a lot higher than the histogram. 虽然密度图遵循直方图的一般形状，但红色峰值显着高于直方图。 So, am I misunderstanding something fundamental on how density plots and histograms are different? 那么，我是否误解了密度图和直方图如何不同的基本内容？ Are they on different y-axis scales altogether? 它们是否完全在不同的y轴尺度上？ How can I change my scales so that the resulting plot looks closer to the example in the StackOverflow answer linked above? 如何更改我的比例，以便结果图看起来更接近上面链接的StackOverflow答案中的示例？ Note that in my actual dataset, which contains 5000 observations, the red peak looks even more pronounced, towering far over the limits of the histogram. 请注意，在我的实际数据集中，其中包含5000个观测值，红色峰值看起来更加明显，远远超出了直方图的极限。 Messing with the bins helps a little bit but not much. 与垃圾桶混淆有点但不多。
1 个解决方案
解决方案1
3 已采纳 2017-03-02 22:02:34
First, I think you are plotting perfect normal distributions based on the means and standard deviations of each subset, rather than the actual density-distributions. 首先，我认为您正在根据每个子集的均值和标准偏差绘制完美的正态分布，而不是实际的密度分布。 Second, you are plotting a density histogram based on 500 observations, but then two density curves based on 328 and 172 observations. 其次，您正在绘制基于500个观测值的密度直方图，然后绘制基于328和172个观测值的两个密度曲线。 Trying instead to add two separate geom_histogram and geom_density layers specifying each subset... 尝试添加两个单独的geom_histogram和geom_density图层来指定每个子集...
ggplot(dat, aes(x = Cutoff)) +
geom_histogram(data=dat[which(dat$Filter%in%"Signal"),], aes(y = ..density..), fill = "grey60", bins = 100) +
geom_histogram(data=dat[which(dat$Filter%in%"Background"),], aes(y = ..density..), fill = "grey60", bins = 100) +
geom_density(data=dat[which(dat$Filter%in%"Signal"),], aes(x=Cutoff, y=..density..), fill="chartreuse3", alpha=0.5) +
geom_density(data=dat[which(dat$Filter%in%"Background"),], aes(x=Cutoff, y=..density..), fill="firebrick2", alpha=0.5) +
theme_bw()
... will give you this plot: ......会给你这个情节：
Otherwise, if you do want to plot a single parent histogram but multiple subset densities, you should expect the peaks to not match. 否则，如果您确实要绘制单个父直方图但多个子集密度，则应该预期峰值不匹配。 Ie: 即：
ggplot(dat, aes(x = Cutoff)) +
geom_histogram(aes(y = ..density..), fill = "grey60", bins = 100) +
geom_density(data=dat[which(dat$Filter%in%"Signal"),], aes(x=Cutoff, y=..density..), fill="chartreuse3", alpha=0.5) +
geom_density(data=dat[which(dat$Filter%in%"Background"),], aes(x=Cutoff, y=..density..), fill="firebrick2", alpha=0.5) +
theme_bw()
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