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