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DOC: better document how to handle omitted coefficients in multilevel DWT reconstructions #303

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merged 4 commits into from Dec 3, 2017
Merged

DOC: better document how to handle omitted coefficients in multilevel DWT reconstructions #303

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370ff88
MAINT: Raise a more informative error in the case that DWT detail coe…
grlee77 Mar 16, 2017
4e52cf4
DOC: update waverec* docstrings to indicate recommended way of
grlee77 Mar 16, 2017
3c804b1
DOC: fix typo in waverecn docstring
grlee77 Nov 28, 2017
e623c44
fix docstrings
grlee77 Nov 29, 2017
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12 changes: 8 additions & 4 deletions pywt/_multidim.py
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Expand Up @@ -192,12 +192,16 @@ def dwtn(data, wavelet, mode='symmetric', axes=None):


def _fix_coeffs(coeffs):
missing_keys = [k for k, v in coeffs.items() if
v is None]
missing_keys = [k for k, v in coeffs.items() if v is None]
if missing_keys:
raise ValueError(
"The following detail coefficients were set to None: "
"{}.".format(missing_keys))
"The following detail coefficients were set to None:\n"
"{0}\n"
"For multilevel transforms, rather than setting\n"
"\tcoeffs[key] = None\n"
"use\n"
"\tcoeffs[key] = np.zeros_like(coeffs[key])\n".format(
missing_keys))

invalid_keys = [k for k, v in coeffs.items() if
not set(k) <= set('ad')]
Expand Down
33 changes: 33 additions & 0 deletions pywt/_multilevel.py
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Expand Up @@ -122,6 +122,17 @@ def waverec(coeffs, wavelet, mode='symmetric', axis=-1):
Axis over which to compute the inverse DWT. If not given, the
last axis is used.

Notes
-----
It may sometimes be desired to run ``waverec`` with some sets of
coefficients omitted. This can best be done by setting the corresponding
arrays to zero arrays of matching shape and dtype. Explicitly removing
list entries or setting them to ``None`` is not supported.

Specifically, to ignore detail coefficients at level 2, one could do::

coeffs[-2] == np.zeros_like(coeffs[-2])

Examples
--------
>>> import pywt
Expand Down Expand Up @@ -251,6 +262,17 @@ def waverec2(coeffs, wavelet, mode='symmetric', axes=(-2, -1)):
-------
2D array of reconstructed data.

Notes
-----
It may sometimes be desired to run ``waverec2`` with some sets of
coefficients omitted. This can best be done by setting the corresponding
arrays to zero arrays of matching shape and dtype. Explicitly removing
list or tuple entries or setting them to ``None`` is not supported.

Specifically, to ignore all detail coefficients at level 2, one could do::

coeffs[-2] == tuple([np.zeros_like(v) for v in coeffs[-2]])

Examples
--------
>>> import pywt
Expand Down Expand Up @@ -436,6 +458,17 @@ def waverecn(coeffs, wavelet, mode='symmetric', axes=None):
-------
nD array of reconstructed data.

Notes
-----
It may sometimes be desired to run ``waverecn`` with some sets of
coefficients omitted. This can best be done by setting the corresponding
arrays to zero arrays of matching shape and dtype. Explicitly removing
list or dictionary entries or setting them to ``None`` is not supported.

Specifically, to ignore all detail coefficients at level 2, one could do::

coeffs[-2] = {k: np.zeros_like(v) for k, v in coeffs[-2].items()}

Examples
--------
>>> import numpy as np
Expand Down