Updates based on code review

Author: trygvrad

galleries/examples/images_contours_and_fields/multi_image.py

@@ -20,7 +20,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-import matplotlib as mpl
+import matplotlib.colorizer as mcolorizer
+import matplotlib.colors as mcolors
 
 np.random.seed(19680801)
 
@@ -32,9 +33,9 @@
 fig, axs = plt.subplots(2, 2)
 fig.suptitle('Multiple images')
 
-# create a single norm and colorizer to be shared across all images
-norm = mpl.colors.Normalize(vmin=np.min(datasets), vmax=np.max(datasets))
-colorizer = mpl.colorizer.Colorizer(norm=norm)
+# create a colorizer with a predefined norm to be shared across all images
+norm = mcolors.Normalize(vmin=np.min(datasets), vmax=np.max(datasets))
+colorizer = mcolorizer.Colorizer(norm=norm)
 
 images = []
 for ax, data in zip(axs.flat, datasets):
@@ -61,4 +62,3 @@
 #    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`
 #    - `matplotlib.colorizer.Colorizer`
 #    - `matplotlib.colors.Normalize`
-#    - `matplotlib.cbook.CallbackRegistry.connect`

galleries/users_explain/colors/colorbar_only.py

@@ -8,11 +8,11 @@
 This tutorial shows how to build and customize standalone colorbars, i.e.
 without an attached plot.
 
-A `~.Figure.colorbar` needs a "mappable" (`matplotlib.colorizer.ColorizingArtist`)
-object (typically, an image) which contains a colorizer
-(`matplotlib.colorizer.Colorizer`) that holds the data-to-color pipeline (norm and
-colormap).  In order to create a colorbar without an attached image, one can instead
+A `~.Figure.colorbar` requires a `matplotlib.colorizer.ColorizingArtist` which
+contains a `matplotlib.colorizer.Colorizer` that holds the data-to-color pipeline
+(norm and colormap). To create a colorbar without an attached plot one can
 use a `.ColorizingArtist` with no associated data.
+
 """
 
 import matplotlib.pyplot as plt