def fill(self, arr, vle_min=-1.0, vle_max=1.0):
"""Fills numpy array with random numbers.
Parameters:
arr: numpy array.
vle_min: minimum value in random distribution.
vle_max: maximum value in random distribution.
"""
arr = ravel(arr)
arr[:] = (my_random.rand(arr.size) * (vle_max - vle_min) + vle_min)[:]
def fill(self, arr, vle_min=-1.0, vle_max=1.0):
"""Fills numpy array with random numbers.
Parameters:
arr: numpy array.
vle_min: minimum value in random distribution.
vle_max: maximum value in random distribution.
"""
arr = ravel(arr)
arr[:] = (my_random.rand(arr.size) * (vle_max - vle_min) +
vle_min)[:]
def fill_normal_real(self, arr, mean, stddev, clip_to_sigma=5.0):
"""
#Fills real-valued numpy array with random normal distribution.
#Parameters:
# arr: numpy array.
# mean:
# stddev:
# min_val, max_val (optional): clipping values of output data.
"""
arr = ravel(arr)
arr[:] = my_random.normal(loc=mean, scale=stddev, size=arr.size)[:]
numpy.clip(arr, mean - clip_to_sigma * stddev,
mean + clip_to_sigma * stddev, out=arr)
def fill_normal_real(self, arr, mean, stddev, clip_to_sigma=5.0):
"""
#Fills real-valued numpy array with random normal distribution.
#Parameters:
# arr: numpy array.
# mean:
# stddev:
# min_val, max_val (optional): clipping values of output data.
"""
arr = ravel(arr)
arr[:] = my_random.normal(loc=mean, scale=stddev, size=arr.size)[:]
numpy.clip(arr,
mean - clip_to_sigma * stddev,
mean + clip_to_sigma * stddev,
out=arr)
def plain(self):
return ravel(self.mem)
def plain(self):
return ravel(self.mem)