R语言 托盘兼容性计算

Posted 2022-02-28 基督徒Isaac

# fun0----
fun0 <- function(df = data.frame(x = rep(1:3, each = 3),
                                 y = rep(1:3, times =3)),
                 k1 = 1, k2 = 1) 
  X = df[order(df[,1], df[,2]),]
  n = NROW(X)
  Y = c()
  
  for (i in 1:(n-1)) 
    Y[[i]] = X[i,]
    
    for (j in 1:(n-i)) 
      a = X[i+j,1] - X[i,1]
      b = X[i+j,2] - X[i,2]
      
      if (a <= k1 &
          b >=  0 &
          b <= k2) 
        Y[[i]] = rbind(Y[[i]], X[i+j,])
      
    
  
  return(Y)


# fun_index ----
fun_index <- function(df = data.frame(x = rep(1:3, each =  3),
                                      y = rep(1:3, times = 3)),
                      k1 = 1, k2 = 1) 
  X = df[order(df[,1], df[,2]),]
  n = NROW(X)
  index = c()
  
  # 1:n-1 × 1:(n-1) √
  for (i in 1:(n-1)) 
    index[[i]] = i
    
    for (j in 1:(n-i)) 
      a = X[i+j,1] - X[i,1]
      b = X[i+j,2] - X[i,2]
      
      if (a <= k1 &
          b >= 0  &
          b <= k2) 
        index[[i]] = rbind(index[[i]], i+j)
      
    
  
  return(index)


# fun1----
fun1 <- 
  function(df = data.frame(x = rep(1:3, each = 3),
                           y = rep(1:3, times =3)),
           k1 = 1, k2 = 1)
    
    X = df[order(df[,1], df[,2]),]
    n = NROW(X)
    Y = c()
    index = c()
    
    for (i in 1:(n-1)) 
      Y[[i]] = X[i,]
      index[[i]] = i
      
      for (j in 1:(n-i)) 
        a = X[i+j,1] - X[i,1]
        b = X[i+j,2] - X[i,2]
        
        if (a <= k1 &
            b >= 0  &
            b <= k2) 
          Y[[i]] = rbind(Y[[i]], X[i+j,])
          index[[i]] = rbind(index[[i]], i+j)
        
      
     
    out = list(Index = index, Ans = Y)
    return(out)
  

# fun2 ----
fun2 <- function(Ans = fun1()[[2]],
                 k = 0.1) 
  
  n = length(Ans)
  tuopan = c()
  
  for (i in 1:n) 
    tuopan = rbind(tuopan, 
                   data.frame(
                     x = max(guige_Y[[2]][[i]][,1]) + k,
                     y = max(guige_Y[[2]][[i]][,2]) + k)
    )
  
  tuopan_result = dplyr::distinct(tuopan)
  return(tuopan_result)


# debug ----
library(tidyverse)

fun_index()
fun0()
fun1()

Y <- fun1()
Index <- Y$Index
Ans <- Y$Ans

Ans[[1]] + 0.5 # 同时对行处理
Ans[[1]] + c(0.5, 10) # 第一行同时+0.5，第二行同时+10


Y[2] # length 1 指Ans或Index列表[]
Y[[2]] # length n-1 指列表里的列表[[]]，等同于Y$Ans，也等同于Y[2][[1]]，即：
# Y$Ans = Y[[2]] = Y[2][[1]]


Y[[2]][1] # 筛选列表里的列表 [[]]，里面的列表[]
Y[[2]][[1]] # 筛选列表里的列表 [[]]，里面的列表里的数据框[[]]
# Y[]是寻找列表的方法
# Y[[]][[]] 是寻找列表里你想要的结果的方法

Y[[2]][[1]][1] # 筛选数据框[[]]，抽出数据框的一部分
Y[[2]][[1]][[1]] # 抽出数据框里的列向量
Y[[2]][[1]][[1]][1] # 根据索引位置抽出列向量里的值



Y = fun1()
Ans <- Y$Ans
Ans %>% last() # 最后一个列表
Ans[[1]] %>% last() # 某个数据框的最后一列（不是行）
Ans[[1]] %>% tail(1) # 最后一行
Ans[[1]][Ans[[1]] %>% NROW(),] # 同上





# real ----
library(tidyverse)

guige <- readxl::read_excel("E:/guige.xlsx", sheet = "Sheet1")
guige_Y <- fun1(guige, k1 = 80, k2 = 80)
guige_tuopan <- fun2(guige_Y[[2]], k = 20)
guige_tuopan %>% View()

write.csv(guige_tuopan, "e:guige_tuopan.csv")
guige_Y[[2]][1:3]
guige_tuopan %>% head(3)