def generate(self, ary, size=None):
"""Generate quasi random number in ary.
:param ary: Numpy array or cuda device array.
:param size: Number of samples;
Default to array size. Must be multiple of ndim.
"""
self._require_array(ary)
size = size or ary.size
dary, conv = cuda._auto_device(ary, stream=self.stream)
self._gen.generate(dary, size)
if conv:
dary.copy_to_host(ary, stream=self.stream)
def poisson(self, ary, lmbd, size=None):
'''Generate floating point random number sampled
from a poisson distribution and fill into ary.
:param ary: Numpy array or cuda device array.
:param lmbda: Lambda for the distribution.
:param size: Number of samples. Default to array size.
'''
self._require_array(ary)
size = size or ary.size
dary, conv = cuda._auto_device(ary, stream=self.stream)
self._gen.generate_poisson(dary, lmbd, size)
if conv:
dary.copy_to_host(ary, stream=self.stream)
def lognormal(self, ary, mean, sigma, size=None):
'''Generate floating point random number sampled
from a log-normal distribution and fill into ary.
:param ary: Numpy array or cuda device array.
:param mean: Center of the distribution.
:param sigma: Standard deviation of the distribution.
:param size: Number of samples. Default to array size.
'''
self._require_array(ary)
size = size or ary.size
dary, conv = cuda._auto_device(ary, stream=self.stream)
self._gen.generate_log_normal(dary, size, mean, sigma)
if conv:
dary.copy_to_host(ary, stream=self.stream)
def to_device(ary):
dary, _ = cuda._auto_device(ary)
return dary
def to_device(ary):
dary, _ = cuda._auto_device(ary)
return dary
def _readonly(*arys):
ds = []
for a in arys:
dmem, _ = cuda._auto_device(a)
ds.append(dmem)
yield ds