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examples/images_contours_and_fields
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Comparison of a contour plot of irregularly spaced data interpolated
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on a regular grid versus a tricontour plot for an unstructured triangular grid.
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- Since :meth: `~.axes.Axes.contour` and :meth: `~.axes.Axes.contourf` expect the
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- data to live on a regular grid, plotting a contour plot of irregularly spaced
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- data requires different methods. The two options are:
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+ Since `~.axes.Axes.contour` and `~.axes.Axes.contourf` expect the data to live
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+ on a regular grid, plotting a contour plot of irregularly spaced data requires
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+ different methods. The two options are:
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- * Interpolate the data to a regular grid first. This can be done with on-borad
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+ * Interpolate the data to a regular grid first. This can be done with on-board
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means, e.g. via `~.tri.LinearTriInterpolator` or using external functionality
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- e.g. via `scipy.interpolate.griddata`. Then plot the
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- interpolated data with the usual :meth:`~.axes.Axes.contour`.
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- * Directly use :meth:`~.axes.Axes.tricontour` or
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- :meth:`~.axes.Axes.tricontourf` which will perform a triangulation
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- internally.
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+ e.g. via `scipy.interpolate.griddata`. Then plot the interpolated data with
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+ the usual `~.axes.Axes.contour`.
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+ * Directly use `~.axes.Axes.tricontour` or `~.axes.Axes.tricontourf` which will
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+ perform a triangulation internally.
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This example shows both methods in action.
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"""
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