SFMT19937 brng

The SIMD-oriented Mersenne Twister pseudo-random number generator can be initialized with either an integral seed, a list of integral seeds, or automatically.

Construction for SFMT19937 basic pseudo-random number generator with scalar seed

    import mkl_random
    rs = mkl_random.RandomState(1234, brng="SFMT19937")

    # Use random state instance to generate 1000 random numbers from
    # Exponential distribution
    esample = rs.exponential(2.3, size=1000)

Construction for SFMT19937 basic pseudo-random number generator with vector seed

    import mkl_random
    rs_vec = mkl_random.RandomState([1234, 567, 89, 0], brng="SFMT19937")

    # Use random state instance to generate 1000 random numbers from
    # Gamma distibution
    gsample = rs_vec.gamma(3, 1, size=1000)

When seed is not specified, the generator is initialized using system clock, e.g.:

Construction for SFMT19937 basic pseudo-random number generator with automatic seed

    import mkl_random
    rs_def = mkl_random.RandomState(brng="SFMT19937")

    # Use random state instance to generate 1000 random numbers
    # from discrete uniform distribution [1, 6]
    isample = rs_def.randint(1, 6 + 1, size=1000)