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- import numpy as np
- from . import pypocketfft as pfft
- from .helper import (_asfarray, _init_nd_shape_and_axes, _datacopied,
- _fix_shape, _fix_shape_1d, _normalization, _workers)
- import functools
- def _r2r(forward, transform, x, type=2, n=None, axis=-1, norm=None,
- overwrite_x=False, workers=None, orthogonalize=None):
- """Forward or backward 1-D DCT/DST
- Parameters
- ----------
- forward : bool
- Transform direction (determines type and normalisation)
- transform : {pypocketfft.dct, pypocketfft.dst}
- The transform to perform
- """
- tmp = _asfarray(x)
- overwrite_x = overwrite_x or _datacopied(tmp, x)
- norm = _normalization(norm, forward)
- workers = _workers(workers)
- if not forward:
- if type == 2:
- type = 3
- elif type == 3:
- type = 2
- if n is not None:
- tmp, copied = _fix_shape_1d(tmp, n, axis)
- overwrite_x = overwrite_x or copied
- elif tmp.shape[axis] < 1:
- raise ValueError("invalid number of data points ({0}) specified"
- .format(tmp.shape[axis]))
- out = (tmp if overwrite_x else None)
- # For complex input, transform real and imaginary components separably
- if np.iscomplexobj(x):
- out = np.empty_like(tmp) if out is None else out
- transform(tmp.real, type, (axis,), norm, out.real, workers)
- transform(tmp.imag, type, (axis,), norm, out.imag, workers)
- return out
- return transform(tmp, type, (axis,), norm, out, workers, orthogonalize)
- dct = functools.partial(_r2r, True, pfft.dct)
- dct.__name__ = 'dct'
- idct = functools.partial(_r2r, False, pfft.dct)
- idct.__name__ = 'idct'
- dst = functools.partial(_r2r, True, pfft.dst)
- dst.__name__ = 'dst'
- idst = functools.partial(_r2r, False, pfft.dst)
- idst.__name__ = 'idst'
- def _r2rn(forward, transform, x, type=2, s=None, axes=None, norm=None,
- overwrite_x=False, workers=None, orthogonalize=None):
- """Forward or backward nd DCT/DST
- Parameters
- ----------
- forward : bool
- Transform direction (determines type and normalisation)
- transform : {pypocketfft.dct, pypocketfft.dst}
- The transform to perform
- """
- tmp = _asfarray(x)
- shape, axes = _init_nd_shape_and_axes(tmp, s, axes)
- overwrite_x = overwrite_x or _datacopied(tmp, x)
- if len(axes) == 0:
- return x
- tmp, copied = _fix_shape(tmp, shape, axes)
- overwrite_x = overwrite_x or copied
- if not forward:
- if type == 2:
- type = 3
- elif type == 3:
- type = 2
- norm = _normalization(norm, forward)
- workers = _workers(workers)
- out = (tmp if overwrite_x else None)
- # For complex input, transform real and imaginary components separably
- if np.iscomplexobj(x):
- out = np.empty_like(tmp) if out is None else out
- transform(tmp.real, type, axes, norm, out.real, workers)
- transform(tmp.imag, type, axes, norm, out.imag, workers)
- return out
- return transform(tmp, type, axes, norm, out, workers, orthogonalize)
- dctn = functools.partial(_r2rn, True, pfft.dct)
- dctn.__name__ = 'dctn'
- idctn = functools.partial(_r2rn, False, pfft.dct)
- idctn.__name__ = 'idctn'
- dstn = functools.partial(_r2rn, True, pfft.dst)
- dstn.__name__ = 'dstn'
- idstn = functools.partial(_r2rn, False, pfft.dst)
- idstn.__name__ = 'idstn'
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