type t = [ `Generator | `Object ] Obj.tval of_pyobject : Py.Object.t -> tval to_pyobject : [> tag ] Obj.t -> Py.Object.tval create : Py.Object.t -> tGenerator(bit_generator)
Container for the BitGenerators.
``Generator`` exposes a number of methods for generating random numbers drawn from a variety of probability distributions. In addition to the distribution-specific arguments, each method takes a keyword argument `size` that defaults to ``None``. If `size` is ``None``, then a single value is generated and returned. If `size` is an integer, then a 1-D array filled with generated values is returned. If `size` is a tuple, then an array with that shape is filled and returned.
The function :func:`numpy.random.default_rng` will instantiate a `Generator` with numpy's default `BitGenerator`.
**No Compatibility Guarantee**
``Generator`` does not provide a version compatibility guarantee. In particular, as better algorithms evolve the bit stream may change.
Parameters ---------- bit_generator : BitGenerator BitGenerator to use as the core generator.
Notes ----- The Python stdlib module `random` contains pseudo-random number generator with a number of methods that are similar to the ones available in ``Generator``. It uses Mersenne Twister, and this bit generator can be accessed using ``MT19937``. ``Generator``, besides being NumPy-aware, has the advantage that it provides a much larger number of probability distributions to choose from.
Examples -------- >>> from numpy.random import Generator, PCG64 >>> rg = Generator(PCG64()) >>> rg.standard_normal() -0.203 # random
See Also -------- default_rng : Recommended constructor for `Generator`.
val to_string : t -> stringPrint the object to a human-readable representation.
val show : t -> stringPrint the object to a human-readable representation.
val pp : Stdlib.Format.formatter -> t -> unitPretty-print the object to a formatter.