.. _sfmt19937_brng:

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.

.. code-block:: python
    :caption: 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)

.. code-block:: python
    :caption: 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.:

.. code-block:: python
    :caption: 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)