def unprepare(data, shape):
"""
Inverses the manipulations in prepare().
:param data: numpy.ndarray
:param shape: The original shape of collapsed dimensions returned as
a second item of the tuple from prepare().
:return numpy.ndarray
"""
return reshape(transpose(data), (data.shape[1], ) + shape)
def unprepare(data, shape):
"""
Inverses the manipulations in prepare().
:param data: numpy.ndarray
:param shape: The original shape of collapsed dimensions returned as
a second item of the tuple from prepare().
:return numpy.ndarray
"""
return reshape(transpose(data), (data.shape[1],) + shape)
def prepare(data):
"""
Manipulates with the array's shape, collapsing all the dimensions but
the first and transposing the resulting 2D matrix.
:param data: numpy.ndarray
:return tuple (the reshaped and transposed data,
the original shape of collapsed dimensions)
"""
shape = data.shape[1:]
old_data = data
new_data = transpose(
reshape(data, (data.shape[0], data.size // data.shape[0])))
assert_addr(old_data, new_data)
return new_data, shape
def prepare(data):
"""
Manipulates with the array's shape, collapsing all the dimensions but
the first and transposing the resulting 2D matrix.
:param data: numpy.ndarray
:return tuple (the reshaped and transposed data,
the original shape of collapsed dimensions)
"""
shape = data.shape[1:]
old_data = data
new_data = transpose(reshape(data, (data.shape[0],
data.size // data.shape[0])))
assert_addr(old_data, new_data)
return new_data, shape
def matrix(self):
return reshape(self.mem, (self.shape[0], self.sample_size))
def matrix(self):
return reshape(self.mem, (self.shape[0], self.sample_size))
