Clarify Doc for Secondary axis, ad-hoc example (matplotlib#19249)

* Clarify Doc for Secondary axis, ad-hoc example

This clarifies that the mapping functions for secondary_axis need to be defined beyond the nominal plot range, which requires special care when doing ad-hoc mappings using interpolation functions.

Addresses matplotlib#19205

* Remove trailing spaces

* Apply suggestions from code review

Co-authored-by: Tim Hoffmann <[email protected]>

* Remove extra space from rst directive

Co-authored-by: Tim Hoffmann <[email protected]>

Author: dihm

examples/subplots_axes_and_figures/secondary_axis.py

@@ -42,7 +42,7 @@ def rad2deg(x):
 # Here is the case of converting from wavenumber to wavelength in a
 # log-log scale.
 #
-# .. note ::
+# .. note::
 #
 #   In this case, the xscale of the parent is logarithmic, so the child is
 #   made logarithmic as well.
@@ -79,6 +79,17 @@ def one_over(x):
 # the data, and is derived empirically.  In that case we can set the
 # forward and inverse transforms functions to be linear interpolations from the
 # one data set to the other.
+#
+# .. note::
+#
+#   In order to properly handle the data margins, the mapping functions
+#   (``forward`` and ``inverse`` in this example) need to be defined beyond the
+#   nominal plot limits.
+#
+#   In the specific case of the numpy linear interpolation, `numpy.interp`,
+#   this condition can be arbitrarily enforced by providing optional kwargs
+#   *left*, *right* such that values outside the data range are mapped
+#   well outside the plot limits.
 
 fig, ax = plt.subplots(constrained_layout=True)
 xdata = np.arange(1, 11, 0.4)