def r2cn(forward, x, shape=None, axes=None, norm=None, overwrite_x=False):
"""Return multi-dimensional discrete Fourier transform of real input"""
tmp = _asfarray(x)
if not np.isrealobj(tmp):
raise TypeError("x must be a real sequence")
shape, axes = _init_nd_shape_and_axes(tmp, shape, axes)
tmp, _ = _fix_shape(tmp, shape, axes)
norm = _normalization(norm, forward)
if len(axes) == 0:
raise ValueError("at least 1 axis must be transformed")
# Note: overwrite_x is not utilised
return pfft.r2c(tmp, axes, forward, norm, None, _default_workers)
def r2c(forward, x, n=None, axis=-1, norm=None, overwrite_x=False):
"""
Discrete Fourier transform of a real sequence.
"""
tmp = _asfarray(x)
norm = _normalization(norm, forward)
if not np.isrealobj(tmp):
raise TypeError("x must be a real sequence")
if n is not None:
tmp, _ = _fix_shape_1d(tmp, n, axis)
elif tmp.shape[axis] < 1:
raise ValueError("invalid number of data points ({0}) specified"
.format(tmp.shape[axis]))
# Note: overwrite_x is not utilised
return pfft.r2c(tmp, (axis,), forward, norm, None, _default_workers)