ENH: Add func norm #18653

jklymak · 2020-10-04T16:58:17Z

PR Summary

Derives a func norm from func scale. From the example:

###############################################################################
# FuncNorm: Arbitrary function normalization
# ------------------------------------------
#
# If the above norms do not provide the normalization you want, and you
# can express your normalization in terms of function, you can use
# `~.colors.FuncNorm`.  Note that this example is the same as
# `PowerNorm` with a power of 0.5:

def _forward(x):
    return np.sqrt(x)


def _inverse(x):
    return x**2

N = 100
X, Y = np.mgrid[0:3:complex(0, N), 0:2:complex(0, N)]
Z1 = (1 + np.sin(Y * 10.)) * X**2
fig, ax = plt.subplots()

norm = colors.FuncNorm((_forward, _inverse), vmin=0, vmax=20)
pcm = ax.pcolormesh(X, Y, Z1, norm=norm, cmap='PuBu_r', shading='auto')
ax.set_title('FuncNorm(x)')
fig.colorbar(pcm, shrink=0.6)
plt.show()

PR Checklist

Has pytest style unit tests (and pytest passes).
Is Flake 8 compliant (run flake8 on changed files to check).
New features are documented, with examples if plot related.
Documentation is sphinx and numpydoc compliant (the docs should build without error).
Conforms to Matplotlib style conventions (install flake8-docstrings and pydocstyle<4 and run flake8 --docstring-convention=all).
New features have an entry in doc/users/next_whats_new/ (follow instructions in README.rst there).
API changes documented in doc/api/next_api_changes/ (follow instructions in README.rst there).

lib/matplotlib/tests/test_colors.py

tutorials/colors/colormapnorms.py

timhoffm

Minor style comments.

lib/matplotlib/tests/test_colors.py

QuLogic · 2021-01-05T00:10:10Z

lib/matplotlib/tests/test_colors.py

+        return 10**x
+    norm = mcolors.FuncNorm((forward, inverse), vmin=0.1, vmax=10)
+    lognorm = mcolors.LogNorm(vmin=0.1, vmax=10)
+    assert_array_almost_equal(norm([0.2, 5, 10]), lognorm([0.2, 5, 10]))


Did you not want to assert the inverse here as well?

Yeah I wasn't going to but it does drop our test coverage, so added...

Interestingly the _make_norm_from_scale inverse doesn't work on a list of floats (i.e. [1, 2, 3]), but only on a numpy array (np.array([1, 2, 3])) whereas the forward works on a bare list. Not sure if that is a bug. @anntzer ?

Probably because inverse doesn't pass value through process_value like __call__ does. Something like:

diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py index e417b8178d..b37ec947fa 100644 --- a/lib/matplotlib/colors.py +++ b/lib/matplotlib/colors.py @@ -1449,12 +1449,14 @@ def _make_norm_from_scale(scale_cls, base_norm_cls=None, *, init=None): t_vmin, t_vmax = self._trf.transform([self.vmin, self.vmax]) if not np.isfinite([t_vmin, t_vmax]).all(): raise ValueError("Invalid vmin or vmax") + value, is_scalar = self.process_value(value) rescaled = value * (t_vmax - t_vmin) rescaled += t_vmin - return (self._trf - .inverted() - .transform(rescaled) - .reshape(np.shape(value))) + t_value = (self._trf + .inverted() + .transform(rescaled) + .reshape(np.shape(value))) + return t_value[0] if is_scalar else t_value Norm.__name__ = base_norm_cls.__name__ Norm.__qualname__ = base_norm_cls.__qualname__

Maybe it also needs the masking?

Looks right. But maybe orthogonal to this PR. I opened an issue in #19239 just to keep them separate...

Since that is now fixed, do you want to remove the np.array from the inverse check?

jklymak · 2021-01-12T23:05:58Z

@timhoffm I think I addressed your concern above? Thanks!

QuLogic

Feel free to merge after.

QuLogic · 2021-01-14T22:35:31Z

lib/matplotlib/tests/test_colors.py

+        return 10**x
+    norm = mcolors.FuncNorm((forward, inverse), vmin=0.1, vmax=10)
+    lognorm = mcolors.LogNorm(vmin=0.1, vmax=10)
+    assert_array_almost_equal(norm([0.2, 5, 10]), lognorm([0.2, 5, 10]))


Since that is now fixed, do you want to remove the np.array from the inverse check?

jklymak force-pushed the enh-add-func-norm branch 3 times, most recently from 989c966 to 15af903 Compare December 20, 2020 03:40

jklymak marked this pull request as ready for review December 20, 2020 03:42

jklymak added the topic: color/color & colormaps label Dec 20, 2020

jklymak added this to the v3.4.0 milestone Dec 20, 2020

jklymak force-pushed the enh-add-func-norm branch from 15af903 to 54be491 Compare December 20, 2020 06:13

jklymak added the status: needs review label Dec 20, 2020

QuLogic reviewed Dec 22, 2020

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jklymak force-pushed the enh-add-func-norm branch from 54be491 to b1c5a0c Compare December 29, 2020 18:10

timhoffm approved these changes Dec 29, 2020

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jklymak force-pushed the enh-add-func-norm branch from 7ab90e3 to 1c043b7 Compare December 30, 2020 02:42

QuLogic reviewed Jan 5, 2021

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jklymak mentioned this pull request Jan 5, 2021

_make_norm_from_scale needs to process values #19239

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ENH: Add func norm

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jklymak force-pushed the enh-add-func-norm branch from 1f91fcf to a3bfa93 Compare January 15, 2021 03:42

jklymak merged commit 6429e9d into matplotlib:master Jan 15, 2021

jklymak deleted the enh-add-func-norm branch January 15, 2021 05:03

QuLogic removed the status: needs merge label Jan 16, 2021

QuLogic mentioned this pull request Mar 18, 2021

DOC: Prepare What's new page for 3.4.0. #19713

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ENH: Add func norm #18653

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jklymak commented Oct 4, 2020 •

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