What’s New or Different¶

Differences from NumPy (1.17+)¶

• UserBitGenerator allows bit generators to be written in Python (slow, suitable for experiments and testing) or numba (fast, similar speed to compiled C). See the demonstration notebook for examples.

• PCG64 supports additional variants of PCG64, including the PCG4 2.0 variant (“cm-dxsm”).

• SFC64 supports optional Weyl sequence increments other than 1 which is the fixed increment in numpy.random.SFC64.

• random_entropy() provides access to the system source of randomness that is used in cryptographic applications (e.g., /dev/urandom on Unix).

• Support broadcasting when producing multivariate Gaussian values (multivariate_normal())

• Simulate from the complex normal distribution (complex_normal())

• Direct access to unsigned integers is provided by (uintegers())

• A wider range of bit generators:

  • Chaotic mappings

    • JSF (32 and 64-bit variants)

    • SFC64

  • Cryptographic Cipher-based:

    • AESCounter

    • ChaCha

    • HC128

    • Philox (limited version in NumPy)

    • SPECK128

    • ThreeFry

  • Hardware-based:

    • RDRAND

  • Mersenne Twisters

    • DSFMT

    • MT64

    • MT19937 (in NumPy)

    • SFMT

  • Permuted Congruential Generators

    • PCG32

    • PCG64 (limited version in NumPy)

    • LCG128Mix (limited version in NumPy)

  • Shift/rotate based:

    • LXM

    • Xoroshiro128

    • Xorshift1024

    • Xoshiro256

    • Xoshiro512

• For changes since the previous release, see the Change Log