Improved support for style mapping constant values

[philippjfr]

Add support for style mapping constant values on an NdOverlay or in the dimensions of an element. This finally allows using style mapping to assign styles by NdOverlay value (addressing #3534) or by value dimension values, an example of that is the following:

df = pd.DataFrame({
    'Time': np.tile(np.arange(100), 9),
    'y': np.random.randn(900).cumsum(axis=0),
    'gridsize': np.repeat([0, 1, 2, 0, 1, 2, 0, 1, 2], 100),
    'turbulence': np.repeat([0, 0, 0, 1, 1, 1, 2, 2, 2], 100)})

df['label'] = ['Gridsize: %s, Turbulence: %s' % (r.gridsize, r.turbulence) for i, r in df.iterrows()]

curves = hv.Dataset(df, ['Time']).to(hv.Curve, 'Time', ['y', 'gridsize','turbulence'], 'label')
curves.overlay('label').opts(
    opts.Curve(color=dim('gridsize').categorize({0: 'red', 1: 'blue', 2: 'green'}),
               line_dash=dim('turbulence').categorize({0: 'solid', 1: 'dashed', 2: 'dotdash'})),
    opts.NdOverlay(width=900, legend_position='right'))

Here we mapped the gridsize dimension to color and the turbulence dimension to the line_dash style.

• Add tests
• Add matplotlib support

[jlstevens]

Looks good and makes sense!

[jbednar]

Nice!

[philippjfr]

Apparently this was already mostly working in matplotlib when mapping value dimensions:

and now also works for NdOverlay dimensions:

[philippjfr]

Ready to review and merge.

[jlstevens]

Looks good to me and this is definitely useful functionality. Merging.

[github-actions]

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