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Add missing space, comma and hashes in docs
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examples/images_contours_and_fields/bivariate_demo.py

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@@ -28,13 +28,17 @@
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bivariate = [air_temp, surf_pres]
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# to distinguish bivariate data either BivariateNorm or BivariateColormap must
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###############################################################################
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# To distinguish bivariate data either BivariateNorm or BivariateColormap must
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# be passed in as argument
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cax = ax.imshow(bivariate, norm=colors.BivariateNorm(),
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cmap=colors.BivariateColormap())
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# if input data is bivariate then colorbar automatically draws colorsquare
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###############################################################################
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# If input data is bivariate then colorbar automatically draws colorsquare
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# instead of colorbar
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cbar = fig.colorbar(cax, xlabel='air_temp', ylabel='surf_pres')
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plt.show()

lib/matplotlib/axes/_axes.py

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@@ -5302,11 +5302,11 @@ def pcolor(self, *args, **kwargs):
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vectors, they will be expanded as needed into the appropriate 2-D
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arrays, making a rectangular grid.
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cmap : `~matplotlib.colors.Colormap` or
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cmap : `~matplotlib.colors.Colormap` or \
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`matplotlib.colors.BivariateColormap`, optional, default: None
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If `None`, default to rc settings.
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norm : `matplotlib.colors.Normalize` or
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norm : `matplotlib.colors.Normalize` or \
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`matplotlib.colors.BivariateNorm`, optional, default: None
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An instance is used to scale luminance data to (0, 1).
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If `None`, defaults to :func:`normalize`.
@@ -5575,7 +5575,7 @@ def pcolormesh(self, *args, **kwargs):
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*cmap*: [ *None* | Colormap ]
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A :class:`matplotlib.colors.Colormap` or
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:class:`matplotlib.colors.BivariateColormap`instance. If *None*,
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:class:`matplotlib.colors.BivariateColormap` instance. If *None*,
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use rc settings.
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*norm*: [ *None* | Normalize ]

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