Random numbers
NumPy provides a wide range of functions to generate random numbers in arrays. These functions are available in the numpy.random module.
The random numbers are generated using the same, excellent pseudo-random number generator called Mersenne Twister that is also used in the normal random module. Mersenne Twister has a period of 2^19937-1 and is generally regarded as a very good pseudo-random number generator (for non-cryptographic purposes).
Several functions for constructing random arrays are provided, including:
- random: uniform random numbers
- normal: normal distribution
- choice: random sample from given array
a = numpy.random.random((2,2))
print(a)
# output:
# [[ 0.02909142 0.90848 ]
# [ 0.9471314 0.31424393]]
b = numpy.random.choice(numpy.arange(4), 10)
print(b)
# output: [0 1 1 2 1 1 2 0 2 3]
What kind of random numbers do you need in your won work? Can you find them in NumPy?
Reach your personal and professional goals
Unlock access to hundreds of expert online courses and degrees from top universities and educators to gain accredited qualifications and professional CV-building certificates.
Join over 18 million learners to launch, switch or build upon your career, all at your own pace, across a wide range of topic areas.
