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More docs cleanup
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docs/2dplots.py

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# name: python3
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# ---
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _pandas: https://pandas.pydata.org
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#
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# .. _xarray: http://xarray.pydata.org/en/stable/
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# `~proplot.axes.PlotAxes.contour`, `~proplot.axes.PlotAxes.pcolor`,
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# and `~proplot.axes.PlotAxes.quiver`.
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_2dstd:
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#
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# Standardized arguments
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axs[2].contourf(x, y, data)
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axs[3].contourf(xedges, yedges, data)
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_2dintegration:
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#
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# Pandas and xarray integration
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ax.contourf(df, cmap='YlOrRd', colorbar='r', lw=0.7, ec='k')
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ax.format(xtickminor=False, yreverse=True)
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_apply_cmap:
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#
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# Colormaps and normalizers
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fig.format(suptitle='On-the-fly colormap normalizers')
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pplt.rc.reset()
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_discrete:
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#
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# Distinct colormap levels
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)
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ax.format(title=f'extend={extend!r}')
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_norm:
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#
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# Special colormap normalizers
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ax.format(title=f'{mode.title()}-skewed + {fair} scaling')
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i += 1
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_labels:
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#
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# Contour and gridbox labels
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)
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ax.format(title='Line contours with labels')
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# %% [raw]
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _ug_heatmap:
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#
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# Heatmap plots

docs/cycles.py

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# Color cycles
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# ============
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#
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# ProPlot defines **discrete colormaps** or **color cycles** as color palettes
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# ProPlot defines **color cycles** or **discrete colormaps** as color palettes
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# comprising sets of *distinct colors*. Unlike :ref:`continuous colormaps <ug_cmaps>`,
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# interpolation between these colors may not make sense. Generally, color cycles are
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# used with line plots, bar plots, and other distinct plot elements. Occasionally,

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