how to modify a numpy matrix element-wise-CodePudding

I am currently trying to iterate over a matrix and modifying the elements inside it following some logic. I tried using the standard procedure for iterating matrices, but this only outputs the element at the current index, without updating the matrix itself.

This is what i have tried:

for row in initial_matrix:
    for element in row:
        if np.random.rand() > 0.5: element = 0
        print(element)

print(initial_matrix)

This, however, does not update initial matrix, I also tried:

for row in range(len(initial_matrix)):
    for element in range(row):
        if np.random.rand() > 0.5: initial_matrix[row, element] = 0
        print(element)

print(initial_matrix)

This is somehow working, but only in the lower diagonal of the matrix, while the upper remains unchanged. Here is the output:

0
0
1
0
1
2
0
1
2
3
[[1. 1. 1. 1. 1.]
 [0. 1. 1. 1. 1.]
 [1. 1. 1. 1. 1.]
 [0. 0. 1. 1. 1.]
 [0. 1. 1. 0. 1.]]

CodePudding user response：

Here's a minimalist modification (UPDATED to use np.array throughout) to your code which will do what I believe you are asking:

import numpy as np
initial_matrix = np.array([
[1,1,1,1,1],
[1,1,1,1,1],
[1,1,1,1,1],
[1,1,1,1,1],
[1,1,1,1,1]])
for row in range(len(initial_matrix)):
    for element in range(len(initial_matrix[row])):
        if np.random.rand() > 0.5:
            initial_matrix[row, element] = 0
print(initial_matrix)

Output:

[[0 1 1 1 0]
 [1 1 1 0 0]
 [0 0 0 0 0]
 [0 1 1 0 0]
 [1 0 0 1 0]]

Here, I have assumed that you start with a matrix containing 1 in every position and that you want to change this to 0 where your random() criterion is met.

As you can see, an adjustment to the inner loop logic of your original code was helpful in getting this to work.

CodePudding user response：

import numpy as np 
initial_matrix = np.ones([10,5])
print(initial_matrix)

for row in initial_matrix:
    for element in row:
        if np.random.rand() > 0.5: 
            element = 0
# Nothing will change
print(initial_matrix)

Basically you're not changing the values for the initial matrix with this approach

  [[1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]
     [1. 1. 1. 1. 1.]]

to better understand this let's take a simple example

initial_list=[1,1,1,1]

for i in initial_list:
    i=0

print(initial_list)

this will output the initial list as it is without any modifications because you're modifying the variable i and not the contents of the list itself, if you want to modify the list you can do something like this instead :

initial_list=[1,1,1,1]

for i in range(len(initial_list)):
    initial_list[i]=0

print(initial_list)

Now let's apply the same thing to your problem

    #Iterate through the rows and columns and change the initial matrix
    for i in range(initial_matrix.shape[0]):
        for j in range(initial_matrix.shape[1]):
            if np.random.rand() > 0.5: 
                initial_matrix[i,j] = 0
    print(initial_matrix)
[[0. 0. 0. 0. 0.]
 [0. 1. 1. 1. 0.]
 [0. 1. 0. 0. 1.]
 [0. 1. 0. 1. 1.]
 [1. 0. 1. 0. 1.]
 [0. 1. 1. 0. 0.]
 [0. 1. 0. 0. 1.]
 [1. 0. 0. 1. 0.]
 [1. 0. 0. 0. 0.]
 [0. 1. 0. 0. 0.]]

CodePudding user response：

import numpy as np
a = np.random.rand(3,4)
print(a)
b = np.random.rand(3,4) 
print(b)
a[ b > 0.5]=0
print(a)

a = a > 0.5
print(a.astype(int))

You can index into the array with boolean results like this. Output:

[[0.21577153 0.4810459  0.88036672 0.93817657]
 [0.48424368 0.88673521 0.26706288 0.47468637]
 [0.02435961 0.75210616 0.18391152 0.80976478]]
[[0.27385928 0.84570069 0.55326907 0.57076882]
 [0.11333208 0.26364198 0.26381841 0.57497278]
 [0.29163378 0.08612894 0.37857834 0.59921316]]
[[0.21577153 0.         0.         0.        ]
 [0.48424368 0.88673521 0.26706288 0.        ]
 [0.02435961 0.75210616 0.18391152 0.        ]]
[[0 0 0 0]
 [0 1 0 0]
 [0 1 0 0]]

If you want to output boolean array in terms of integers you can use astype() function.