2D Normalization & Colormapping for ScalerMappables #8738
Add bivariate example
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| """ | ||
| =========== | ||
| Bivariate Demo | ||
| =========== | ||
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| Plotting bivariate data. | ||
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| imshow, pcolor, pcolormesh, pcolorfast allows you to plot bivariate data | ||
| using a bivaraite colormap. | ||
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| In this example we use imshow to plot air temperature with surface pressure | ||
| alongwith a color square. | ||
| """ | ||
| import matplotlib.colors as colors | ||
| from matplotlib.cbook import get_sample_data | ||
| import matplotlib.pyplot as plt | ||
| import numpy as np | ||
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| ############################################################################### | ||
| # Bivariate plotting demo | ||
| # ----------------------- | ||
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| air_temp = np.load(get_sample_data('air_temperature.npy')) | ||
| surf_pres = np.load(get_sample_data('surface_pressure.npy')) | ||
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| fig, ax = plt.subplots() | ||
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| bivariate = [air_temp, surf_pres] | ||
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| cax = ax.imshow(bivariate, norm=colors.BivariateNorm(), | ||
| cmap=colors.BivariateColormap()) | ||
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| # if input data is bivariate then colorbar automatically draws colorsquare | ||
| # instead of colorbar | ||
| cbar = fig.colorbar(cax, xlabel='air_temp', ylabel='surf_pres') | ||
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| plt.show() |
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How big are these data files? I have a slight preference for 'generated' data for examples (to keep the repository size small).
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84.2 kB each.
Couldn't come up with generated data so used these.
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That isn't too bad, suspect that is smaller than the test images.
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One argument in favour of this can be that the user seeing the example might relate to use case of bivariate plotting better with a real world example than with some mathematical function.