How to replace some elements of a matrix using numpy in python ?

Daidalos October 31, 2019


Examples of how to replace some elements of a matrix using numpy in python:

Replace some elements of a 1D matrix

Let's try to replace the elements of a matrix called M strictly lower than 5 by the value -1:

  >>> import numpy as np
  >>> M = np.arange(10)
  >>> M
  array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
  >>> M[M > 5 ] = -1
  >>> M
  array([ 0,  1,  2,  3,  4,  5, -1, -1, -1, -1])

Replace some elements of a 2D matrix

Another example using a 2D matrix

>>> A = np.arange(16)
>>> A
array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15])
>>> A = A.reshape(4,4)
>>> A
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])
>>> A[A<=5]=0
>>> A
array([[ 0,  0,  0,  0],
       [ 0,  0,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])
>>> A[A>1]=1
>>> A
array([[0, 0, 0, 0],
       [0, 0, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1]])

Using multiple conditions

Exemple using multiple conditions: try to replace the elements > 3 and < 7 using the following syntax M[(M > 2) & (M < 7)] = -1, illustration:

  >>> import numpy as np
   >>> M = np.arange(10)
   >>> M
   array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
   >>> M[(M > 2) & (M < 7)] = -1
   >>> M
   array([ 0,  1,  2, -1, -1, -1, -1,  7,  8,  9])

Using the numpy function where

Another solution is to use the numpy function where

>>> A = np.array((1,7,3,8,4,9,1))
>>> np.where(A>4,1,A)
array([1, 1, 3, 1, 4, 1, 1])

References

Links Site
Replace all elements of Python NumPy Array that are greater than some value stackoverflow
Replace “zero-columns” with values from a numpy array stackoverflow
numpy.place numpy doc
Numpy where function multiple conditions stackoverflow
Replace NaN's in NumPy array with closest non-NaN value stackoverflow
numpy.put numpy doc
numpy.nan_to_num numpy doc
How to: Replace values in an array kite.com

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