Mean of Each Element of a List of Matrices

Element-wise mean over list of matrices

You can use:

Reduce("+", my.list) / length(my.list)

According to comments, you want both mean and sd implemented on a list of matrices, and the above ways will not work smoothly for sd. Try this instead :

apply(simplify2array(my.list), 1:2, mean)
apply(simplify2array(my.list), 1:2, sd)

Mean of each element of a list of matrices

Maybe what you want is:

> set.seed(1)
> a<-matrix(runif(4)) 
> b<-matrix(runif(4))
> c<-matrix(runif(4))
> mylist<-list(a,b,c)  # a list of 3 matrices 
> 
> apply(simplify2array(mylist), c(1,2), mean)
          [,1]
[1,] 0.3654349
[2,] 0.4441000
[3,] 0.5745011
[4,] 0.5818541

The vector c(1,2) for MARGIN in the apply call indicates that the function mean should be applied to rows and columns (both at once), see ?apply for further details.

Another alternative is using Reduce function

> Reduce("+", mylist)/ length(mylist)
          [,1]
[1,] 0.3654349
[2,] 0.4441000
[3,] 0.5745011
[4,] 0.5818541

Mean of each element of matrices in a list

try this:

import numpy as np
a= [[1,2,3],[3,4,5],[6,7,8]]
np.mean(a, axis=0)
# array([3.33333333, 4.33333333, 5.33333333])

How to average the same cells over many lists of matrices in R

Use as.matrix on the output if you want a matrix class object instead of a data.frame

Reduce('+', x)/length(x)

Finding the mean of multiple arrays in a list

If your data is not too large, you can just concatenate the arrays and then calculate the mean. However, this will create copies of the full dataset, which might need a lot of memory if your data is larger.

In that case, calculate mean and length of each dataset and then do the weighted average of those.

counts = [len(values) for values in cpw]
means = [values.mean() for values in cpw]
mean = np.average(means, weights=counts)

or with concatenation:

np.concatenate(cpw).mean()

element-wise averages of two (or more) nested lists of matrices

In base R, We could use:

A <-list(A_1, A_2)
lapply(Reduce(\(x, y)Map('+', x, y), A), '/', length(A))

$a
     [,1] [,2] [,3] [,4]
[1,]  5.5  7.5  9.5 11.5
[2,]  6.5  8.5 10.5 12.5

$b
     [,1] [,2] [,3] [,4]
[1,]  3.5  5.5  7.5  9.5
[2,]  4.5  6.5  8.5 10.5

This code is generic in that we can use to find the mean of several lists.
Note that A_1 and A_2 must have the same number of matrices, not necessarily 2. Can be 10 etc. Also note that each corresponding matrix has the same dimensions. Example below:

B_1 <- list(matrix(c(1,2,3,4), 2), matrix(c(1,3,4,2), 2),
            matrix(c(1:10), 5), matrix(c(1:20), 5))
B_2 <- lapply(B_1, '*', 2) # In this case, its B_1 * 2
B_3 <- lapply(B_2, '*', 3) #

Now you could use the code provide above:

B <-list(B_1, B_2, B_3)
lapply(Reduce(\(x, y)Map('+', x, y), B), '/', length(B))

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