def __init__(self, incoming, data_shape, inv=False, **kwargs):
'''
Need to take input shape of the fft,
since it needs to precompute fft matrix
if nx != ny, we need to matrices
'''
super(FFT2Layer, self).__init__(incoming, **kwargs)
self.is_3d = len(data_shape) == 5
self.data_shape = data_shape
if self.is_3d:
n, _, nx, ny, nt = data_shape
else:
n, _, nx, ny = data_shape
# create matrix which performs fft
if inv:
fourier_mat_x = inverse_fourier_matrix(nx, nx)
fourier_mat_y = inverse_fourier_matrix(ny, ny) if nx != ny else fourier_mat_x
else:
fourier_mat_x = fourier_matrix(nx, nx)
fourier_mat_y = fourier_matrix(ny, ny) if nx != ny else fourier_mat_x
self.real_fft_x = np.real(fourier_mat_x).astype(theano.config.floatX)
self.complex_fft_x = np.imag(fourier_mat_x).astype(theano.config.floatX)
self.real_fft_y = np.real(fourier_mat_y).astype(theano.config.floatX)
self.complex_fft_y = np.imag(fourier_mat_y).astype(theano.config.floatX)
def __init__(self, incoming, data_shape, inv=False, **kwargs):
'''
Need to take input shape of the fft,
since it needs to precompute fft matrix
if nx != ny, we need to matrices
'''
super(FFT2Layer, self).__init__(incoming, **kwargs)
self.is_3d = len(data_shape) == 5
self.data_shape = data_shape
if self.is_3d:
n, _, nx, ny, nt = data_shape
else:
n, _, nx, ny = data_shape
# create matrix which performs fft
if inv:
fourier_mat_x = inverse_fourier_matrix(nx, nx)
fourier_mat_y = inverse_fourier_matrix(ny, ny) if nx != ny else fourier_mat_x
else:
fourier_mat_x = fourier_matrix(nx, nx)
fourier_mat_y = fourier_matrix(ny, ny) if nx != ny else fourier_mat_x
self.real_fft_x = np.real(fourier_mat_x).astype(theano.config.floatX)
self.complex_fft_x = np.imag(fourier_mat_x).astype(theano.config.floatX)
self.real_fft_y = np.real(fourier_mat_y).astype(theano.config.floatX)
self.complex_fft_y = np.imag(fourier_mat_y).astype(theano.config.floatX)
def __init__(self, incoming, data_shape, inv=False, **kwargs):
'''
Need to take input shape of the fft, since it needs to
precompute fft matrix
'''
super(FFTLayer, self).__init__(incoming, **kwargs)
self.data_shape = data_shape
n, _, nx, ny = data_shape
# create matrix which performs fft
if inv:
fourier_mat = inverse_fourier_matrix(nx, ny)
else:
fourier_mat = fourier_matrix(nx, ny)
self.real_fft = np.real(fourier_mat)
self.complex_fft = np.imag(fourier_mat)
def __init__(self, incoming, data_shape, inv=False, **kwargs):
'''
Need to take input shape of the fft, since it needs to
precompute fft matrix
'''
super(FFTLayer, self).__init__(incoming, **kwargs)
self.data_shape = data_shape
n, _, nx, ny = data_shape
# create matrix which performs fft
if inv:
fourier_mat = inverse_fourier_matrix(nx, ny)
else:
fourier_mat = fourier_matrix(nx, ny)
self.real_fft = np.real(fourier_mat)
self.complex_fft = np.imag(fourier_mat)