def zf1d(s, size='auto'):
dim = s.udic['ndim'] - 1
if size == 'auto':
size = s.udic[dim]['size'] * 2
ret = ndarray_subclasser(zf_size)(s, size)
ret.udic[dim]['size'] = size
return ret
def fft_norm(s):
ret = ndarray_subclasser( p.fft_norm )(s)
_update_udic(ret)
return ret
def fft_positive(s):
ret = ndarray_subclasser( p.fft_positive )(s)
_update_udic(ret)
return ret
def fft_norm(s):
ret = ndarray_subclasser(p.fft_norm)(s)
_update_udic(ret)
return ret
def fft_positive(s):
ret = ndarray_subclasser(p.fft_positive)(s)
_update_udic(ret)
return ret
