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--- other:python:matplotlib_by_jyp [2023/09/27 14:11] – [Working with matplotlib (JYP version)] Simplified pdf cheatsheets link jypeter
+++ other:python:matplotlib_by_jyp [2023/10/25 15:52] – [Starting (and more) with matplotlib] Slight update of the Axes documentation jypeter
@@ Line 34: / Line 34: @@
         * if you need several display windows at the same time, create several figures!\\ <code>win_1 = plt.figure()
 win_2 = plt.figure()</code>
-        * the [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|parts of a figure]] are usually positioned in //normalized coordinates//: ''(0, 0)'' is the bottom left of the figure, and ''(1, 1)'' is the top right
+        * the [[https://matplotlib.org/stable/gallery/showcase/anatomy.html|parts of a figure]] are usually positioned in //normalized coordinates//: ''(0, 0)'' is the bottom left of the figure, and ''(1, 1)'' is the top right
         * You don't really specify the **page orientation** (//portrait// or //landscape//) of a plot. If you want a portrait plot, it's up to you to create a plot that will look higher than it is large. The idea is not to worry about this and just check the final resulting plot: create a plot, save it, display the resulting png/pdf and then adjust the creation script
           * If you do have an idea of the layout of what you want to plot, it may be easier to explicitly specify the figure size/ratio at creation time, and then try to //fill// the normalized coordinates space of the figure
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             * The specified ''width'' and ''height'' are supposed to be in inches (1 inch = 2.54 cm)
             * ''my_page = plt.figure(figsize=(8.3, 11.7))'': create a figure that will theoretically fill an A4 size page in portrait mode (check [[https://www.papersizes.org/a-paper-sizes.htm|Dimensions Of A Series Paper Sizes]] if you need more details about standard paper sizes)
-      * a Matplotlib **//Axis//** is a **plot** inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]]
+      * a Matplotlib **//Axes//** (not to be confused with an //**axis**//) is a **(sub-)plot** inside a Figure... [[https://matplotlib.org/stable/api/axes_api.html|(much) More details]]
         * reserve space for **one plot** that will use most of the available area of the figure/page:
           * ''my_plot = my_page.add_subplot(1, 1, 1)'' or ''my_plot = my_page.subplot**s**()''