How to find min and max for each row of a matrix?

Question

Suppose that we have the following matrix m:

[1] "list of respective positions"
             [,1]      [,2]      [,3]      [,4]       [,5]
x:      2.4131066 3.8504796 3.7434050 -1.923839 2.41310661
y:      0.0260981 0.7128027 0.7128027  1.396096 0.01565761
obj-val 0.7937068 0.3105951 0.4038012  1.195259 0.83750443

How can I retrive the min and the max for each row? ( I need the couple (min, max) for each row of the matrix m.

I'm not wanting to use the rowmins() of the package Rfast.

Answer 1

We can use pmin and pmax after converting the matrix to data.frame

cbind(min = do.call(pmin, as.data.frame(my_mat)), 
             max = do.call(pmax, as.data.frame(my_mat)))
#           min       max
#[1,] -1.3169081 0.2660220
#[2,] -0.6051569 0.5982691
#[3,] -1.7096452 1.5362522
#[4,] -1.4290903 0.6099945
#[5,] -0.6485915 0.8474600

Or use rowMins/rowMaxs from matrixStats

library(matrixStats)
cbind(min = rowMins(my_mat), max = rowMaxs(my_mat))
#         min       max
#[1,] -1.3169081 0.2660220
#[2,] -0.6051569 0.5982691
#[3,] -1.7096452 1.5362522
#[4,] -1.4290903 0.6099945
#[5,] -0.6485915 0.8474600

Or more compactly rowRanges

rowRanges(my_mat)
#           [,1]      [,2]
#[1,] -1.3169081 0.2660220
#[2,] -0.6051569 0.5982691
#[3,] -1.7096452 1.5362522
#[4,] -1.4290903 0.6099945
#[5,] -0.6485915 0.8474600

---

Or using transmute

library(dplyr)
as.data.frame(my_mat) %>%
   transmute(min = pmin(!!! .), max = pmax(!!! .))
#        min       max
#1 -1.3169081 0.2660220
#2 -0.6051569 0.5982691
#3 -1.7096452 1.5362522
#4 -1.4290903 0.6099945
#5 -0.6485915 0.8474600

Or with rowwise/c_across

library(tidyr)
as.data.frame(my_mat) %>% 
    rowwise %>% 
    summarise(out = list(as.list(range(c_across(everything()))))) %>% 
    unnest_wider(c(out), names_repair = ~ c('min', 'max'))
# A tibble: 5 x 2
#     min   max
#   <dbl> <dbl>
#1 -1.32  0.266
#2 -0.605 0.598
#3 -1.71  1.54 
#4 -1.43  0.610
#5 -0.649 0.847

Benchmarks

set.seed(24)
my_mat1 <- matrix(rnorm(5 * 1e7), nrow = 1e7)

system.time(cbind(min = do.call(pmin, as.data.frame(my_mat1)), 
               max = do.call(pmax, as.data.frame(my_mat1))))
#   user  system elapsed 
#  0.804   0.209   1.009 

system.time(rowRanges(my_mat1))
#   user  system elapsed 
#   0.303   0.000   0.303 

system.time(apply(my_mat1, 1, range))
#   user  system elapsed 
# 30.373   0.455  31.037 



system.time(t(apply(my_mat1, 1, function(x) c(min = min(x), max = max(x)))))
#   user  system elapsed 
# 34.594   0.728  35.240 

data

set.seed(24)
my_mat <- matrix(rnorm(25), nrow = 5, dimnames = list(letters[1:5], NULL))

Answer 2

Using Allan Cameron's example matrix, you can apply the range function

my_mat <- matrix(rnorm(25), nrow = 5, dimnames = list(letters[1:5], NULL))
my_mat
#         [,1]       [,2]       [,3]       [,4]        [,5]
# a  1.7813097 -0.4946628  2.0344305  0.2620399  0.99000423
# b  1.0758692  0.4004411 -1.2957444  0.3443362 -0.71271404
# c  0.9705851 -0.1952594 -0.6168627 -0.3046352 -1.04132273
# d -0.5459703 -0.2538314 -1.6677170 -0.6585102 -0.06104492
# e -0.4463699 -0.3935345  0.6689235  0.5235429  0.40823566
apply(my_mat, 1, range)
#               a         b          c           d          e
# [1,] -0.4946628 -1.295744 -1.0413227 -1.66771703 -0.4463699
# [2,]  2.0344305  1.075869  0.9705851 -0.06104492  0.6689235

Answer 3

[1] "list of respective positions"
              [,1]       [,2]      [,3]      [,4]       [,5]
x:      3.69250663 3.75443457 4.4075606 3.7544346 4.16053631
y:      0.61196240 0.61196240 0.6899600 0.6899600 0.68996003
obj-val 0.05702941 0.08390476 0.1334916 0.2036376 0.07759858

MIN_t=apply(D, 1, min)   
MAX_t=apply(D, 1, max)   
New_domain_search=cbind(MIN_t,MAX_t)

output :

             MIN_t     MAX_t
x:      3.69250663 4.4075606
y:      0.61196240 0.6899600
obj-val 0.05702941 0.2036376

Answer 4

You can use apply:

my_mat <- matrix(rnorm(25), nrow = 5, dimnames = list(letters[1:5], NULL))

my_mat
#>         [,1]        [,2]       [,3]        [,4]        [,5]
#> a -1.7455936  0.79571392  0.1509219 -0.61944619 -0.65429261
#> b  0.5858837 -0.32462380  1.3739094 -0.08092246 -1.24418958
#> c  1.0757723 -0.23296522 -2.2174416  0.56720160 -0.02991945
#> d  1.8043565 -0.00370110 -1.4628807 -0.73418720  0.10333882
#> e -0.4153639 -0.07896341  1.0089698 -0.09542518  0.17067607

t(apply(my_mat, 1, function(x) c(min = min(x), max = max(x))))
#>          min       max
#> a -1.7455936 0.7957139
#> b -1.2441896 1.3739094
#> c -2.2174416 1.0757723
#> d -1.4628807 1.8043565
#> e -0.4153639 1.0089698

^{Created on 2020-06-21 by the reprex package (v0.3.0)}