I would like to generate a random number matrix within a specified range, say (0,1)
.
import numpy as np
A=np.random.random((3, 3))
print("A =",[A])
CodePudding user response:
numpy.random.uniform can receive low
, high
and size
parameters
Range 0-1 is the default
A = np.random.uniform(size=(3, 3))
print("A =", [A])
Output
A = [array([[0.76679099, 0.57459256, 0.07952816],
[0.02736909, 0.05905416, 0.09909474],
[0.08690106, 0.81983883, 0.18740471]])]
If you want another range specify it with parameters
A = np.random.uniform(0.2, 0.3, (3, 3))
print("A =", [A])
Output
A = [array([[0.20548205, 0.25373507, 0.28957419],
[0.20496673, 0.27004844, 0.28633947],
[0.22325187, 0.26327935, 0.24548129]])]
CodePudding user response:
you will be use it generate range [0, 1)
np.random.rand(d0, d1, ..., dn)
Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).
https://numpy.org/doc/stable/reference/random/generated/numpy.random.rand.html
CodePudding user response:
You can use Numpy's built-in rand method, which generates a matrix with random numbers with a uniform distribution over [0, 1).
A = np.random.rand(3, 3)