我是初学R用户（不完全确定它是否是最适合此用途的语言），并且很难找到我认为可能相对容易的解决方案。
编辑 - 我的数据的前60帧如下所示：
structure(list(Filename = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("BJB1NRL.mat", "DJG1NRL.mat",
"DMA1NRL.mat", "DWS1NRL.mat", "EJC1NRL.mat", "FMB1NRL.mat", "GPC1NRL.mat",
"GZZ1NRL.mat", "JMC1NRL.mat", "JTH1NRL.mat", "KAN1NRL.mat", "MAS1NRL.mat",
"MFM1NRL.mat", "MJU1NRL.mat", "OVK1NRL.mat", "PCA1NRL.mat", "RHG1NRL.mat",
"RHM1NRL.mat", "RJS1NRL.mat", "SIS1NRL.mat", "SXV1NRL.mat", "TXN1NRL.mat"
), class = "factor"), Label = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "V", class = "factor"),
seg_Start = c(231.537, 231.537, 231.537, 231.537, 231.537,
231.537, 231.537, 231.537, 231.537, 231.537, 231.537, 231.537,
231.537, 231.537, 231.537, 231.537, 231.537, 231.537, 231.537,
231.537, 231.537, 231.537, 554.141, 554.141, 554.141, 554.141,
554.141, 554.141, 554.141, 554.141, 554.141, 554.141, 554.141,
554.141, 554.141, 554.141, 554.141, 554.141, 554.141, 554.141,
554.141, 554.141, 554.141, 554.141, 554.141, 554.141, 554.141,
554.141, 554.141, 554.141, 554.141, 554.141, 554.141, 554.141,
554.141, 554.141, 554.141, 1081.457, 1081.457, 1081.457),
seg_End = c(444.039, 444.039, 444.039, 444.039, 444.039,
444.039, 444.039, 444.039, 444.039, 444.039, 444.039, 444.039,
444.039, 444.039, 444.039, 444.039, 444.039, 444.039, 444.039,
444.039, 444.039, 444.039, 887.246, 887.246, 887.246, 887.246,
887.246, 887.246, 887.246, 887.246, 887.246, 887.246, 887.246,
887.246, 887.246, 887.246, 887.246, 887.246, 887.246, 887.246,
887.246, 887.246, 887.246, 887.246, 887.246, 887.246, 887.246,
887.246, 887.246, 887.246, 887.246, 887.246, 887.246, 887.246,
887.246, 887.246, 887.246, 1269.05, 1269.05, 1269.05), t_ms = c(230L,
240L, 250L, 260L, 270L, 280L, 290L, 300L, 310L, 320L, 330L,
340L, 350L, 360L, 370L, 380L, 390L, 400L, 410L, 420L, 430L,
440L, 550L, 560L, 570L, 580L, 590L, 600L, 610L, 620L, 630L,
640L, 650L, 660L, 670L, 680L, 690L, 700L, 710L, 720L, 730L,
740L, 750L, 760L, 770L, 780L, 790L, 800L, 810L, 820L, 830L,
840L, 850L, 860L, 870L, 880L, 890L, 1080L, 1090L, 1100L),
CPP = c(0, 0, 19.553, 16.063, 18.09, 21.547, 21.37, 21.616,
18.125, 20.936, 20.134, 23.642, 23.319, 24.674, 22.299, 22.587,
27.477, 25.924, 20.166, 20.195, 16.807, 18.189, 16.843, 16.07,
20.384, 26.11, 26.536, 28.891, 26.769, 27.622, 28.303, 24.373,
22.043, 23.579, 26.797, 26.384, 29.34, 31.437, 31.531, 24.404,
22.396, 26.416, 28.531, 26.735, 28.796, 28.494, 27.177, 27.325,
26.273, 29.066, 24.344, 21.124, 28.363, 24.193, 19.815, 11.897,
14.125, 0, 0, 22.398)), .Names = c("Filename", "Label", "seg_Start",
"seg_End", "t_ms", "CPP"), row.names = c(NA, 60L), class = "data.frame")
我必须做的是直接手动做，但我正在努力创建一个脚本来为我做。 对于每个时间段（即231-444，然后是1081-1269等），我需要看到最终列（CPP）中的值达到阈值（例如28）所需的毫秒数。 也就是说，我需要计算从段开始的行数（t_ms = seg_Start），直到最后一行中的值达到此阈值，因为每行是10ms。 如果值永远不会达到阈值，那么应该给出值0。
到目前为止，我的代码主要是我尝试将数据集拆分以进行分析。它可能效率低下，而且更加令人担忧，不正确。
编辑 - 澄清 - 我需要分析CPP＆＃39;每个＆＃34;段的值＆＃34;另外，对于每个不同的文件名＆＃39;。一段是't_ms＆＃39;中的值。介于＆＃39; seg_Start＆＃39;和＆＃39; seg_End＆＃39;。
例如，对于第一个文件名的第一个段，我的答案是“＃28; 280ms＆＃39; - 每行10毫秒。 CPP在第一个seg_start-seg_End之间的时间段中第一次达到28，在第28行（值= 28.891）。 10 x 28 = 280ms。
最终编辑删除了无关的数据集。左侧部分仅与问题相关。
答案 0 :(得分：0)
我编辑了您的数据以包含两个不同的文件名，如下所示。
df$Filename[15:17] <- "DMA1NRL.mat"
time.2.threshold是一个带有三个参数的函数：df - data，threshold - CPP threshold，time_factor - 以ms为单位的数字。
在函数内部，有三个循环。第一个循环负责文件名的数据。第二个循环处理seg_Start中的值，第三个最内层循环处理通过第二个循环获得的数据帧，并对CPP列的数据帧进行排序，并找到达到CPP阈值及以上的最小行值（行索引）
time_2_threshold是time_factor * rows_CPP_to_threshold
最后，time.2.threshold函数返回一个数据框，其中包含整个数据框的文件名，seg_Start，seg_End，rows_CPP_to_threshold，total_rows和time_2_threshold值。
我仍在努力了解您的期望，因为您的问题尚不明显，但步骤编码正确。人们可能会建议这个代码的一些惯用的R版本可能会提高性能，但我不是在这里做，因为目前还不清楚你的期望是什么。希望这有帮助！
time.2.threshold <- function(df = df, threshold = 25, time_factor = 10){
df_threshold <- data.frame(filename = character(),
seg_Start = numeric(),
seg_End = numeric(),
rows_CPP_to_threshold = numeric(),
total_rows = numeric(),
time_2_threshold = numeric(),
stringsAsFactors = FALSE)
for(df_file in unique(df$Filename)){
df_filename <- df[which(df$Filename == df_file), ]
for (i in unique(df$seg_Start)){
start_df <- df_filename[which(df_filename$seg_Start == i), ]
seg_End_unique <- unique(start_df$seg_End)
if(length(seg_End_unique) > 0 ){
for(j in seg_End_unique){
df1 <- start_df[which(start_df$seg_End == j), ]
#df1 <- df1[with(df1, order(CPP)),]
df1_CPP_index = which(df1$CPP >= threshold)
if( length(df1_CPP_index) > 0 && !is.na(df1_CPP_index) && !is.nan(df1_CPP_index) ){
rows_CPP_to_threshold <- min(df1_CPP_index)
}else{
rows_CPP_to_threshold <- NA
}
total_rows = nrow(df1)
df2 <- data.frame(filename = df_file,
seg_Start = i,
seg_End = j,
rows_CPP_to_threshold = rows_CPP_to_threshold,
total_rows = total_rows,
time_2_threshold = time_factor*rows_CPP_to_threshold,
stringsAsFactors = FALSE)
df_threshold <- rbind(df_threshold, df2 )
}
}else
next
}
}
return(df_threshold)
}
df_threshold <- time.2.threshold(df = df, threshold = 15, time_factor = 10)
输出
df_threshold <- time.2.threshold(df = df, threshold = 15, time_factor = 10)
print(df_threshold)
filename seg_Start seg_End rows_CPP_to_threshold total_rows time_2_threshold
1 BJB1NRL.mat 231.537 444.039 3 19 30
2 BJB1NRL.mat 554.141 887.246 1 35 10
3 BJB1NRL.mat 1081.457 1269.050 3 3 30
4 DMA1NRL.mat 231.537 444.039 1 3 10
在评论出CPP列的排序后：
df_threshold <- time.2.threshold(df = df, threshold = 25, time_factor = 10)
print(df_threshold)
filename seg_Start seg_End rows_CPP_to_threshold total_rows time_2_threshold
1 BJB1NRL.mat 231.537 444.039 15 19 150
2 BJB1NRL.mat 554.141 887.246 4 35 40
3 BJB1NRL.mat 1081.457 1269.050 NA 3 NA
4 DMA1NRL.mat 231.537 444.039 3 3 30