def noncentral_chisquare(self, df, nonc, size=None, dtype=float):
"""Returns an array of samples drawn from the noncentral chi-square
distribution.
.. seealso::
:func:`cupy.random.noncentral_chisquare` for full documentation,
:meth:`numpy.random.RandomState.noncentral_chisquare`
"""
df, nonc = cupy.asarray(df), cupy.asarray(nonc)
if cupy.any(df <= 0):
raise ValueError("df <= 0")
if cupy.any(nonc < 0):
raise ValueError("nonc < 0")
if size is None:
size = cupy.broadcast(df, nonc).shape
y = cupy.empty(shape=size, dtype=dtype)
_kernels.noncentral_chisquare_kernel(df, nonc, self.rk_seed, y)
self.rk_seed += numpy.prod(size)
return y
def noncentral_chisquare(self, df, nonc, size=None, dtype=float):
"""Returns an array of samples drawn from the noncentral chi-square
distribution.
.. warning::
This function may synchronize the device.
.. seealso::
- :func:`cupy.random.noncentral_chisquare` for full documentation
- :meth:`numpy.random.RandomState.noncentral_chisquare`
"""
df, nonc = cupy.asarray(df), cupy.asarray(nonc)
if cupy.any(df <= 0): # synchronize!
raise ValueError('df <= 0')
if cupy.any(nonc < 0): # synchronize!
raise ValueError('nonc < 0')
if size is None:
size = cupy.broadcast(df, nonc).shape
y = cupy.empty(shape=size, dtype=dtype)
_kernels.noncentral_chisquare_kernel(df, nonc, self._rk_seed, y)
self._update_seed(y.size)
return y
