forked from 170010011/fr
84 lines
2.2 KiB
Python
84 lines
2.2 KiB
Python
"""
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.. deprecated:: 1.20
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*This module is deprecated. Instead of importing functions from*
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``numpy.dual``, *the functions should be imported directly from NumPy
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or SciPy*.
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Aliases for functions which may be accelerated by SciPy.
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SciPy_ can be built to use accelerated or otherwise improved libraries
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for FFTs, linear algebra, and special functions. This module allows
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developers to transparently support these accelerated functions when
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SciPy is available but still support users who have only installed
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NumPy.
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.. _SciPy : https://www.scipy.org
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"""
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import warnings
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warnings.warn('The module numpy.dual is deprecated. Instead of using dual, '
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'use the functions directly from numpy or scipy.',
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category=DeprecationWarning,
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stacklevel=2)
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# This module should be used for functions both in numpy and scipy if
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# you want to use the numpy version if available but the scipy version
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# otherwise.
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# Usage --- from numpy.dual import fft, inv
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__all__ = ['fft', 'ifft', 'fftn', 'ifftn', 'fft2', 'ifft2',
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'norm', 'inv', 'svd', 'solve', 'det', 'eig', 'eigvals',
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'eigh', 'eigvalsh', 'lstsq', 'pinv', 'cholesky', 'i0']
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import numpy.linalg as linpkg
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import numpy.fft as fftpkg
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from numpy.lib import i0
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import sys
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fft = fftpkg.fft
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ifft = fftpkg.ifft
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fftn = fftpkg.fftn
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ifftn = fftpkg.ifftn
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fft2 = fftpkg.fft2
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ifft2 = fftpkg.ifft2
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norm = linpkg.norm
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inv = linpkg.inv
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svd = linpkg.svd
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solve = linpkg.solve
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det = linpkg.det
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eig = linpkg.eig
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eigvals = linpkg.eigvals
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eigh = linpkg.eigh
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eigvalsh = linpkg.eigvalsh
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lstsq = linpkg.lstsq
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pinv = linpkg.pinv
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cholesky = linpkg.cholesky
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_restore_dict = {}
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def register_func(name, func):
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if name not in __all__:
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raise ValueError("{} not a dual function.".format(name))
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f = sys._getframe(0).f_globals
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_restore_dict[name] = f[name]
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f[name] = func
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def restore_func(name):
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if name not in __all__:
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raise ValueError("{} not a dual function.".format(name))
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try:
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val = _restore_dict[name]
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except KeyError:
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return
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else:
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sys._getframe(0).f_globals[name] = val
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def restore_all():
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for name in _restore_dict.keys():
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restore_func(name)
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