So, I have a given 2 dimensional matrix which is randomly generated:
a = np.random.randn(4,4)
which gives output:
array([[-0.11449491, -2.7777728 , -0.19784241, 1.8277976 ],
[-0.68511473, 0.40855461, 0.06003551, -0.8779363 ],
[-0.55650378, -0.16377137, 0.10348714, -0.53449633],
[ 0.48248298, -1.12199767, 0.3541335 , 0.48729845]])
I want to change all the negative values to 0 and all the positive values to 1. How can I do this without a for loop?
You can use np.where()
import numpy as np
a = np.random.randn(4,4)
a = np.where(a<0, 0, 1)
print(a)
[[1 1 0 1]
[1 0 1 0]
[1 1 0 0]
[0 1 1 0]]
(a<0).astype(int)
This is one possibly solution - converting the array to boolean array according to your condition and then converting it from boolean to integer.
array([[ 0.63694991, -0.02785534, 0.07505496, 1.04719295],
[-0.63054947, -0.26718763, 0.34228736, 0.16134474],
[ 1.02107383, -0.49594998, -0.11044738, 0.64459594],
[ 0.41280766, 0.668819 , -1.0636972 , -0.14684328]])
And the result -
(a<0).astype(int)
>>> array([[0, 1, 0, 0],
[1, 1, 0, 0],
[0, 1, 1, 0],
[0, 0, 1, 1]])
