R 比较四个具有公差间隔的数字向量，并报告常用值

我有四个长度不等的大向量。下面我提供了一个与我的原始数据集类似的玩具数据集：

a <- c(1021.923, 3491.31, 102.3, 12019.11, 879.2, 583.1)
b <- c(21,32,523,123.1,123.4545,12345,95.434, 879.25, 1021.9,11,12,662)
c <- c(52,21,1021.9288,12019.12, 879.1)
d <- c(432.432,23466.3,45435,3456,123,6688,1021.95)

我知道这对于两个向量是可能的，但是对于4个向量我怎么做呢

相关的

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这是一个data.table解决方案
它可以扩展到n个向量，所以请尝试按您喜欢的方式馈送它。。当多个值在所有向量中都有“命中”时，它的性能也很好
样本数据

a <- c(1021.923, 3491.31, 102.3, 12019.11, 879.2, 583.1)
b <- c(21,32,523,123.1,123.4545,12345,95.434, 879.25, 1021.9,11,12,662)
c <- c(52,21,1021.9288,12019.12, 879.1)
d <- c(432.432,23466.3,45435,3456,123,6688,1021.95)

---

编写一个函数来处理两个向量，将其称为

my_compare

，然后

Reduce（my_compare，list（a，b，c，d））

尽管存在潜在的问题，例如，如果

a

有

100

，

b

有

100.4

，

c

有

99.6

，这取决于您希望如何处理。在不同的订单上运行或制作

my_compare

accept和return等同物列表都可以。

a <- c(1021.923, 3491.31, 102.3, 12019.11, 879.2, 583.1)
b <- c(21,32,523,123.1,123.4545,12345,95.434, 879.25, 1021.9,11,12,662)
c <- c(52,21,1021.9288,12019.12, 879.1)
d <- c(432.432,23466.3,45435,3456,123,6688,1021.95)

library(data.table)

#create list with vectors
l <- list( a,b,c,d )
names(l) <- letters[1:4]
#create data.table to work with
DT <- rbindlist( lapply(l, function(x) {data.table( value = x)} ), idcol = "group")
#add margins to each value
DT[, `:=`( id = 1:.N, start = value - 0.5, end = value + 0.5 ) ]
#set keys for joining
setkey(DT, start, end)
#perform overlap-join
result <- foverlaps(DT,DT)

#cast, to check how the 'hits' each id has in each group (a,b,c,d)
answer <- dcast( result, 
             group + value ~ i.group, 
             fun.aggregate = function(x){ x * 1 }, 
             value.var = "i.value", 
             fill = NA )

#get your final answer
#set columns to look at (i.e. the names from the earlier created list)
cols = names(l)
#keep the rows without NA (use rowSums, because TRUE = 1, FALSE = 0 )
#so if rowSums == 0, then columns in the vactor 'cols' do not contain a 'NA'
answer[ rowSums( is.na( answer[ , ..cols ] ) ) == 0, ]

#    group    value        a      b        c       d
# 1:     a 1021.923 1021.923 1021.9 1021.929 1021.95
# 2:     b 1021.900 1021.923 1021.9 1021.929 1021.95
# 3:     c 1021.929 1021.923 1021.9 1021.929 1021.95
# 4:     d 1021.950 1021.923 1021.9 1021.929 1021.95