r - 根据阈值对数据进行分箱？

Question

假设我有一个随时间上升和下降的响应变量。每次响应变量上升到阈值以上时，我们就有一个新的“试验”。也就是说，如果我添加一列 Threshold即 TRUE每当高于某个值时，连续的数据块位于 Threshold是 TRUE构成新的审判。

Time <- seq(1, 10, by = 0.5)
Response <- abs(sin(Time))
Threshold <- Response > 0.6
data <- data.frame(Time, Response, Threshold)

给定 Time , Response , 和 Threshold ，我怎么能去添加一个 Trial每组 TRUE 都有一个新值的因子阈值？像这样的东西:

   Time   Response Threshold Trial
1   1.0 0.84147098      TRUE A
2   1.5 0.99749499      TRUE A
3   2.0 0.90929743      TRUE A
4   2.5 0.59847214     FALSE NA
5   3.0 0.14112001     FALSE NA
6   3.5 0.35078323     FALSE NA
7   4.0 0.75680250      TRUE B
8   4.5 0.97753012      TRUE B
9   5.0 0.95892427      TRUE B
10  5.5 0.70554033      TRUE B
11  6.0 0.27941550     FALSE NA
12  6.5 0.21511999     FALSE NA
13  7.0 0.65698660      TRUE C
14  7.5 0.93799998      TRUE C
15  8.0 0.98935825      TRUE C
16  8.5 0.79848711      TRUE C
17  9.0 0.41211849     FALSE NA
18  9.5 0.07515112     FALSE NA
19 10.0 0.54402111     FALSE NA

Answer 1

data$Trial <- factor(
  ifelse(data$Threshold, cumsum(!data$Threshold), NA), labels = c("A", "B", "C")
)

##   Time   Response Threshold Trial
## 1   1.0 0.84147098      TRUE     A
## 2   1.5 0.99749499      TRUE     A
## 3   2.0 0.90929743      TRUE     A
## 4   2.5 0.59847214     FALSE  <NA>
## 5   3.0 0.14112001     FALSE  <NA>
## 6   3.5 0.35078323     FALSE  <NA>
## 7   4.0 0.75680250      TRUE     B
## 8   4.5 0.97753012      TRUE     B
## 9   5.0 0.95892427      TRUE     B
## 10  5.5 0.70554033      TRUE     B
## 11  6.0 0.27941550     FALSE  <NA>
## 12  6.5 0.21511999     FALSE  <NA>
## 13  7.0 0.65698660      TRUE     C
## 14  7.5 0.93799998      TRUE     C
## 15  8.0 0.98935825      TRUE     C
## 16  8.5 0.79848711      TRUE     C
## 17  9.0 0.41211849     FALSE  <NA>
## 18  9.5 0.07515112     FALSE  <NA>
## 19 10.0 0.54402111     FALSE  <NA>