From a6dc6a8a66ff5bd527d04dee8dce6d70236eeed4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Trygve=20Magnus=20R=C3=A6der?= Date: Wed, 22 Jan 2025 11:19:46 +0100 Subject: [PATCH] Backport PR #29478: DOC: Added blurb for colorizer objects in what's new for 3.10 --- doc/users/prev_whats_new/whats_new_3.10.0.rst | 56 +++++++++++++++++++ 1 file changed, 56 insertions(+) diff --git a/doc/users/prev_whats_new/whats_new_3.10.0.rst b/doc/users/prev_whats_new/whats_new_3.10.0.rst index 2a6e55f7c3cb..78d4d3c30662 100644 --- a/doc/users/prev_whats_new/whats_new_3.10.0.rst +++ b/doc/users/prev_whats_new/whats_new_3.10.0.rst @@ -292,6 +292,62 @@ the ``set_data`` method, enabling e.g. resampling fig.savefig("after.png") +``matplotlib.colorizer.Colorizer`` as container for ``norm`` and ``cmap`` +------------------------------------------------------------------------- + + `matplotlib.colorizer.Colorizer` encapsulates the data-to-color pipeline. It makes reuse of colormapping easier, e.g. across multiple images. Plotting methods that support *norm* and *cmap* keyword arguments now also accept a *colorizer* keyword argument. + +In the following example the norm and cmap are changed on multiple plots simultaneously: + + +.. plot:: + :include-source: true + :alt: Example use of a matplotlib.colorizer.Colorizer object + + import matplotlib.pyplot as plt + import matplotlib as mpl + import numpy as np + + x = np.linspace(-2, 2, 50)[np.newaxis, :] + y = np.linspace(-2, 2, 50)[:, np.newaxis] + im_0 = 1 * np.exp( - (x**2 + y**2 - x * y)) + im_1 = 2 * np.exp( - (x**2 + y**2 + x * y)) + + colorizer = mpl.colorizer.Colorizer() + fig, axes = plt.subplots(1, 2, figsize=(6, 2)) + cim_0 = axes[0].imshow(im_0, colorizer=colorizer) + fig.colorbar(cim_0) + cim_1 = axes[1].imshow(im_1, colorizer=colorizer) + fig.colorbar(cim_1) + + colorizer.vmin = 0.5 + colorizer.vmax = 2 + colorizer.cmap = 'RdBu' + +All plotting methods that use a data-to-color pipeline now create a colorizer object if one is not provided. This can be re-used by subsequent artists such that they will share a single data-to-color pipeline: + +.. plot:: + :include-source: true + :alt: Example of how artists that share a ``colorizer`` have coupled colormaps + + import matplotlib.pyplot as plt + import matplotlib as mpl + import numpy as np + + x = np.linspace(-2, 2, 50)[np.newaxis, :] + y = np.linspace(-2, 2, 50)[:, np.newaxis] + im_0 = 1 * np.exp( - (x**2 + y**2 - x * y)) + im_1 = 2 * np.exp( - (x**2 + y**2 + x * y)) + + fig, axes = plt.subplots(1, 2, figsize=(6, 2)) + + cim_0 = axes[0].imshow(im_0, cmap='RdBu', vmin=0.5, vmax=2) + fig.colorbar(cim_0) + cim_1 = axes[1].imshow(im_1, colorizer=cim_0.colorizer) + fig.colorbar(cim_1) + + cim_1.cmap = 'rainbow' + 3D plotting improvements ========================