Merge pull request #14666 from bingyao/docs_update_link

tacaswell · web-flow · commit 73d711952191 · 2019-07-01T23:27:16.000-04:00
DOC: Update IPython's doc link in Image tutorial
diff --git a/tutorials/introductory/images.py b/tutorials/introductory/images.py
@@ -12,16 +12,17 @@
 
 First, let's start IPython.  It is a most excellent enhancement to the
 standard Python prompt, and it ties in especially well with
-Matplotlib.  Start IPython either at a shell, or the IPython Notebook now.
+Matplotlib.  Start IPython either directly at a shell, or with the Jupyter
+Notebook (where IPython as a running kernel).
 
 With IPython started, we now need to connect to a GUI event loop.  This
 tells IPython where (and how) to display plots.  To connect to a GUI
 loop, execute the **%matplotlib** magic at your IPython prompt.  There's more
 detail on exactly what this does at `IPython's documentation on GUI
 event loops
-<http://ipython.org/ipython-doc/2/interactive/reference.html#gui-event-loop-support>`_.
+<https://ipython.readthedocs.io/en/stable/interactive/reference.html#gui-event-loop-support>`_.
 
-If you're using IPython Notebook, the same commands are available, but
+If you're using Jupyter Notebook, the same commands are available, but
 people commonly use a specific argument to the %matplotlib magic:
 
 .. sourcecode:: ipython
@@ -157,7 +158,7 @@
 #
 # .. note::
 #
-#    However, remember that in the IPython notebook with the inline backend,
+#    However, remember that in the Jupyter Notebook with the inline backend,
 #    you can't make changes to plots that have already been rendered.  If you
 #    create imgplot here in one cell, you cannot call set_cmap() on it in a later
 #    cell and expect the earlier plot to change.  Make sure that you enter these
@@ -208,7 +209,7 @@
 # imshow.  You could also do this by calling the
 # :meth:`~matplotlib.image.Image.set_clim` method of the image plot
 # object, but make sure that you do so in the same cell as your plot
-# command when working with the IPython Notebook - it will not change
+# command when working with the Jupyter Notebook - it will not change
 # plots from earlier cells.
 #
 # You can specify the clim in the call to ``plot``.
