了解ggpmisc软件包R中的find_peaks函数的阈值参数忽略

问题描述

我无法理解要绘制突出峰的忽略阈值参数。但是，我希望对该参数有一定的了解。文档说“ 0.0到1.0之间的数字值表示大小阈值，低于该阈值将被忽略。”

我不明白这一点。

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CODE

plot(df)
peak_x_val <- x[ggpmisc:::find_peaks(y,ignore_threshold = 0.3)]
peaks <- y[ggpmisc:::find_peaks(y,ignore_threshold = 0.3)]
ggplot(data = data.frame(x,y),aes(x = x,y = y)) + geom_line() + stat_peaks(col = "red",ignore_threshold = 0.3) 

解决方法

寻找峰的算法最终来自于here定义的Fortran代码。 splus2R::peaks调用它，而ggpmisc:::find_peaks调用ggpmisc::stat_peaks，ignore_threshold使用该函数。峰值查找算法非常简单，可以有效地查找曲线的一阶导数为0且二阶导数为负的点。这将发现数据中的每一个小小的积极变化，以及您想称之为“峰值”的事物。我们可以通过将ggplot(df,aes(x,y)) + geom_line() + ggpmisc::stat_peaks(col = "red",ignore_threshold = 0) 参数设置为0来查看其原始输出：

ggpmisc:::find_peaks

但是，为了获得更多控制权，ignore_threshold函数采用ignore_threshold参数并将其乘以数据范围。如果您的任何一个峰值都低于此值，它将被消除。

例如，我们可以从您的数据中看到9个小峰均位于y = 0.125以下，约为y范围的1/10。因此，如果我们将0.1设置为threshold <- 0.1 ggplot(df,y)) + geom_line() + geom_hline(aes(yintercept = threshold * diff(range(y)) + min(y))) + ggpmisc::stat_peaks(col = "red",ignore_threshold = threshold) ，则应该只剩下三个峰。我们可以画一条水平线来显示所有峰被去除的水平：

threshold <- 0.8

ggplot(df,ignore_threshold = threshold) 

此外，我们可以看到，如果将阈值设置为0.8，则等于删除了y值低于1.0左右的任何峰，因此我们只应保留剩下的最高两个峰：

threshold <- 0.99

ggplot(df,ignore_threshold = threshold) 

最后，通过一些微调，我们可以找到使我们只剩下一个点的水平：

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