在R中优化Apply()While() [英] Optimize Apply() While() in R

问题描述

以下数据用于进行比较分析.我使用apply()和while()编写了代码，尽管它可以按预期工作，但在进一步优化它方面并未取得成功.在较大的数据集中，当前运行时间要超过几个小时.

The data below is being used to perform comparative analysis. I wrote the code using apply() and while(), and even though it works as expected, I haven't been successful in optimizing it further. Current run time is more than couple of hours in larger data set.

以下是一个小的示例数据集:

Following is small example data set:

数据_1

A B C D
2 1 3 2.5

数据_2

P Q R S
3 2 4 5.5

数据

 A   B   C   D
1.0 0.5 1.3 1.5
1.5 1.2 5.5 3.5
1.1 0.5 1.3 1.5
1.5 1.2 5.5 3.5
1.5 1.2 5.5 3.5
1.1 0.5 1.3 1.5
1.5 1.2 5.5 3.5
1.0 0.5 1.3 1.5

代码

# Row counter 
rowLine <<- 0

# Set current column to first one
columnLine <<- 1

# Preserve column header and dimensions for final data
finalData <- Data

# Find recursively
findThreshold <- function () {

  if ( columnLine <= ncol(Data) ){

    # Initialize row navigation to zero
    rowLine  <<- 1

    # Navigate through rows
    while (rowLine <= nrow(Data)){

      # If outside threshold
      if ( (Data[rowLine, columnLine] < data_1[columnLine]) |
           (Data[rowLine, columnLine] > data_2[columnLine])){

        finalData[rowLine, columnLine] <<- 1

      } else {

        finalData[rowLine, columnLine] <<- 0

      }

      # Increment row counter
      rowLine <<- rowLine + 1

    }
  }

  # Increment column counter
  columnLine <<- columnLine + 1

}

# Apply
apply(Data, 2, function(x) findThreshold())

我还理解，将<<-与loops一起使用并像apply()那样进行递归分析时，这是一个很大的缺点.

I also understand using <<- is a big no when it comes using it with loops and recursively analysis like apply().

谢谢，我建议如何进一步改善这种逻辑.

Please suggest how I can improve this logic further, thanks.

推荐答案

听起来像一个简单的Map练习:

Sounds like a simple Map exercise:

data.frame(Map(function(d,l,h) d < l | d > h, Data, data_1, data_2))
#     A     B    C     D
#1 TRUE  TRUE TRUE  TRUE
#2 TRUE FALSE TRUE FALSE
#3 TRUE  TRUE TRUE  TRUE
#4 TRUE FALSE TRUE FALSE
#5 TRUE FALSE TRUE FALSE
#6 TRUE  TRUE TRUE  TRUE
#7 TRUE FALSE TRUE FALSE
#8 TRUE  TRUE TRUE  TRUE

如果要使用0/1输出，只需将逻辑比较包装在as.integer中:

Just wrap the logical comparison in as.integer if you want a 0/1 output instead:

data.frame(Map(function(d,l,h) as.integer(d < l | d > h), Data, data_1, data_2))

如果数据是以matrix对象开头的，则可以使用sweep:

If your data are matrix objects to start with, you could use sweep:

sweep(Data, 2, data_1, FUN=`<`) | sweep(Data, 2, data_2, FUN=`>`)
#        A     B    C     D
#[1,] TRUE  TRUE TRUE  TRUE
#[2,] TRUE FALSE TRUE FALSE
#[3,] TRUE  TRUE TRUE  TRUE
#[4,] TRUE FALSE TRUE FALSE
#[5,] TRUE FALSE TRUE FALSE
#[6,] TRUE  TRUE TRUE  TRUE
#[7,] TRUE FALSE TRUE FALSE
#[8,] TRUE  TRUE TRUE  TRUE

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