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other:python:matplotlib_by_jyp [2021/02/26 11:56]
jypeter More link updates
other:python:matplotlib_by_jyp [2023/10/26 08:39] (current)
jypeter [Useful matplotlib reference pages]
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 ====== Working with matplotlib (JYP version) ====== ====== Working with matplotlib (JYP version) ======
 +
 +<note tip>​Note:​ [[https://​matplotlib.org/​cheatsheets/​|Matplotlib cheatsheets]] ([[https://​github.com/​matplotlib/​cheatsheets#​cheatsheets-for-matplotlib-users|pdf version]])</​note>​
  
 **Summary**:​ there are lots of python libraries that you can use for plotting, but Matplotlib has become a //de facto// standard **Summary**:​ there are lots of python libraries that you can use for plotting, but Matplotlib has become a //de facto// standard
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         * if you need several display windows at the same time, create several figures!\\ <​code>​win_1 = plt.figure()         * if you need several display windows at the same time, create several figures!\\ <​code>​win_1 = plt.figure()
 win_2 = plt.figure()</​code>​ 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         * 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           * 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)             * 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)             * ''​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:​         * 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**()''​           * ''​my_plot = my_page.add_subplot(1,​ 1, 1)''​ or ''​my_plot = my_page.subplot**s**()''​
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     * The ''​plot''​ function will be faster for scatterplots where markers don't vary in size or color     * The ''​plot''​ function will be faster for scatterplots where markers don't vary in size or color
     * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.axes.Axes.contourf.html|contour(...) and contourf(...)]]:​ draw contour lines and filled contours     * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.axes.Axes.contourf.html|contour(...) and contourf(...)]]:​ draw contour lines and filled contours
-  * **X and Y axes parameters** (see also [[https://​matplotlib.org/​examples/​showcase/​anatomy.html|Anatomy of a figure]]):+  * **X and Y axes parameters** (see also [[https://​matplotlib.org/​stable/​gallery/​showcase/​anatomy.html|Anatomy of a figure]]):
     * **Axis range**: ''​my_plot.set_xlim(x_leftmost_value,​ x_rightmost_value)''​     * **Axis range**: ''​my_plot.set_xlim(x_leftmost_value,​ x_rightmost_value)''​
       * Use the leftmost and rightmost values to specify the orientation of the axis (i.e the rightmost value can be smaller than the leftmost)       * Use the leftmost and rightmost values to specify the orientation of the axis (i.e the rightmost value can be smaller than the leftmost)
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         * [[https://​stackoverflow.com/​questions/​35479508/​cartopy-set-xlabel-set-ylabel-not-ticklabels|Trick source]]         * [[https://​stackoverflow.com/​questions/​35479508/​cartopy-set-xlabel-set-ylabel-not-ticklabels|Trick source]]
         * Trick needs to be used with ''​cartopy 0.17.0''​\\ Remember to update/​remove this information in the future         * Trick needs to be used with ''​cartopy 0.17.0''​\\ Remember to update/​remove this information in the future
-    * Major (and minor) **tick marks location**: ''​my_plot.set_xticks(x_ticks_values,​ minor=False)''​+    * Major (and minor) **tick marks location**: ''​my_plot.set_xticks(x_ticks_values,​ minor=False)'' ​([[https://​matplotlib.org/​stable/​api/​_as_gen/​matplotlib.axes.Axes.set_xticks.html|set_xticks]])
       * Use an empty list if you don't want tick marks: ''​my_plot.set_xticks([])''​       * Use an empty list if you don't want tick marks: ''​my_plot.set_xticks([])''​
-    * **Tick labels** ​(if you don't want the default values): ''​my_plot.set_xticklabels(x_ticks_labels, minor=False,​ fontsize=ticklabels_fontsize)''​ +    * **Tick labels**: ''​my_plot.set_xticklabels(x_tick_labels, minor=False,​ fontsize=ticklabels_fontsize)'' ​([[https://​matplotlib.org/​stable/​api/​_as_gen/​matplotlib.axes.Axes.set_xticklabels.html|set_xticklabels]]) 
-      * ''​x_ticks_labels''​ is a list of strings that has the same length as ''​x_ticks_values''​. Use an empty string in the positions where you don't want a label+      * If you do not specify labels, the //default labels// will just be the values specifying the ticks' ​location 
 +      * ''​x_tick_labels''​ is a list of strings that has the same length as ''​x_ticks_values''​.\\ Use an empty string in the positions where you don't want a label 
 +      * The default numerical labels may be too long, due to numerical approximations. You can try to explicitly round the values, or generate correct label strings from the values\\ <​code>>>>​ x_tick_values = np.arange(0,​ 1, 0.2) 
 +>>>​ x_tick_values.tolist() 
 +[0.0, 0.2, 0.4, 0.6000000000000001,​ 0.8] 
 +>>>​ x_tick_values.round(decimals=1).tolist() 
 +[0.0, 0.2, 0.4, 0.6, 0.8] 
 +>>>​ x_tick_labels = [ '​%.1f'​ % (t_val,) for t_val in x_tick_values ] 
 +>>>​ x_tick_labels 
 +['​0.0',​ '​0.2',​ '​0.4',​ '​0.6',​ '​0.8'​] 
 +>>>​ x_tick_labels[0] = '​START'​ 
 +>>>​ x_tick_labels[-1] = '​END'​ 
 +>>>​ x_tick_labels 
 +['​START',​ '​0.2',​ '​0.4',​ '​0.6',​ '​END'​] 
 +</​code>​  
 +      * You can also use fancy [[https://​matplotlib.org/​stable/​gallery/​ticks_and_spines/​tick-formatters.html|tick formatters]]
       * Many more options for ticks, labels, orientation,​ ...       * Many more options for ticks, labels, orientation,​ ...
     * **Grid lines**:     * **Grid lines**:
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       * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.plot.html|plot(...)]]:​ //fmt// (see documentation) or ''​marker''​ and ''​markerfacecolor''/''​mfc''​ (and ''​markerfacecoloralt''/''​mfcalt''​ for dual color markers), ''​markersize'',​ ''​markeredgewidth''/''​mew'',​ ''​markeredgecolor''​ (use ''​markeredgecolor='​none'''​ if you don't want to plot the edge of the markers), ''​fillstyle''​ (''​full'',​ ''​None'',​ [[https://​matplotlib.org/​stable/​gallery/​lines_bars_and_markers/​marker_reference.htm|other]])       * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.plot.html|plot(...)]]:​ //fmt// (see documentation) or ''​marker''​ and ''​markerfacecolor''/''​mfc''​ (and ''​markerfacecoloralt''/''​mfcalt''​ for dual color markers), ''​markersize'',​ ''​markeredgewidth''/''​mew'',​ ''​markeredgecolor''​ (use ''​markeredgecolor='​none'''​ if you don't want to plot the edge of the markers), ''​fillstyle''​ (''​full'',​ ''​None'',​ [[https://​matplotlib.org/​stable/​gallery/​lines_bars_and_markers/​marker_reference.htm|other]])
       * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.scatter.html|scatter(...)]]:​ ''​marker''​ (marker type), ''​c''​ (color), ''​s''​ (size), ''​linewidths''​ (linewidth of the marker edges), ''​edgecolors''​       * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.scatter.html|scatter(...)]]:​ ''​marker''​ (marker type), ''​c''​ (color), ''​s''​ (size), ''​linewidths''​ (linewidth of the marker edges), ''​edgecolors''​
-  * [[https://​matplotlib.org/​api/​colors_api.html|colors]] and colormaps+  * [[https://​matplotlib.org/stable/​api/​colors_api.html|colors]] and colormaps
     * [[https://​matplotlib.org/​stable/​gallery/​color/​color_demo.html|color demo]]     * [[https://​matplotlib.org/​stable/​gallery/​color/​color_demo.html|color demo]]
-    * [[https://​matplotlib.org/​examples/​color/​named_colors.html|named colors]]+    * [[https://​matplotlib.org/​stable/​gallery/​color/​named_colors.html#​sphx-glr-gallery-color-named-colors-py|named colors]] 
 +    * [[https://​www.w3schools.com/​colors/​colors_picker.asp|HTML color picker]] and different ways of choosing colors
     * Reverting the colors: add ''​_r''​ at the end of the colormap name     * Reverting the colors: add ''​_r''​ at the end of the colormap name
     * Number of colors in the //my_cmap// colormap (usually 256): ''​my_cmap.N''​     * Number of colors in the //my_cmap// colormap (usually 256): ''​my_cmap.N''​
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       * ''​my_cmap.set_over(color='​k'​)'':​ color to be used for //high out-of-range values// **if** ''​extend''​ is specified and is //'​both'//​ or  //'​max'//​. Default color is ''​my_cmap(my_cmap.N - 1)''​       * ''​my_cmap.set_over(color='​k'​)'':​ color to be used for //high out-of-range values// **if** ''​extend''​ is specified and is //'​both'//​ or  //'​max'//​. Default color is ''​my_cmap(my_cmap.N - 1)''​
       * ''​my_cmap.set_under(color='​k'​)'':​ color to be used for //low out-of-range values// **if** ''​extend''​ is specified and is //'​both'//​ or  //'​min'//​. Default color is ''​my_cmap(0)''​       * ''​my_cmap.set_under(color='​k'​)'':​ color to be used for //low out-of-range values// **if** ''​extend''​ is specified and is //'​both'//​ or  //'​min'//​. Default color is ''​my_cmap(0)''​
-  * [[https://​matplotlib.org/​api/_as_gen/matplotlib.figure.Figure.html#​matplotlib.figure.Figure.colorbar|colorbar]]+  * [[https://​matplotlib.org/​stable/api/figure_api.html#​matplotlib.figure.Figure.colorbar|colorbar]] ​(see also the [[https://​matplotlib.org/​stable/​api/​colorbar_api.html|colorbar api]])
     * [[https://​matplotlib.org/​stable/​gallery/​subplots_axes_and_figures/​colorbar_placement.html|Placing colorbars demo]]     * [[https://​matplotlib.org/​stable/​gallery/​subplots_axes_and_figures/​colorbar_placement.html|Placing colorbars demo]]
     * [[https://​matplotlib.org/​stable/​gallery/​images_contours_and_fields/​contourf_demo.html|contourf + colorbar demo]]     * [[https://​matplotlib.org/​stable/​gallery/​images_contours_and_fields/​contourf_demo.html|contourf + colorbar demo]]
 +    * Changing the font size of a colorbar (i.e. //changing [[https://​matplotlib.org/​stable/​api/​axes_api.html#​ticks-and-tick-labels|ticks and tick labels]]//​):​
 +      * This can be done by manipulating the properties of the //Axes// where the colorbar is plotted\\ e.g. change the tick labels font size with\\ ''​cb.ax.tick_params(labelsize='​xx-large'​)''​ (where ''​cb''​ is a //​colorbar//​ object)
   * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.text.html|text(...)]] and [[https://​matplotlib.org/​tutorials/​text/​annotations.html|annotations]]   * [[https://​matplotlib.org/​api/​_as_gen/​matplotlib.pyplot.text.html|text(...)]] and [[https://​matplotlib.org/​tutorials/​text/​annotations.html|annotations]]
     * Some titles:     * Some titles:
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 [[https://​stackoverflow.com/​questions/​9797520/​masking-part-of-a-contourf-plot-in-matplotlib|trick source]] [[https://​stackoverflow.com/​questions/​9797520/​masking-part-of-a-contourf-plot-in-matplotlib|trick source]]
  
 +===== Unsorted matplotlib stuff =====
 +
 +Some useful notes and links that cannot be placed (yet) in a section of the main page
 +
 +==== Plotting arcs (segments of ellipses) ====
 +
 +  * [[https://​matplotlib.org/​stable/​api/​_as_gen/​matplotlib.patches.Arc.html|Offical patches.Arc documentation]]
 +  * A nice [[https://​stackoverflow.com/​questions/​54849976/​can-someone-explain-the-different-parameters-in-matplotlib-patches-arc|ellipses and arcs tutorial]] on stackoverflow
 +
 +==== Using hatches with contourf ====
 +
 +  * [[https://​matplotlib.org/​stable/​gallery/​shapes_and_collections/​hatch_style_reference.html|Hatch style reference]]
 +  * [[https://​matplotlib.org/​stable/​gallery/​shapes_and_collections/​hatch_demo.html|Hatch demo]]
 +  * [[https://​matplotlib.org/​stable/​gallery/​images_contours_and_fields/​contourf_hatching.html|Contourf hatching]]
 +  * //​Collections//​ trick for [[https://​fantashit.com/​hatching-color-in-contourf-function/​|changing the colors of hatches]]
  
 /* standard page footer */ /* standard page footer */
other/python/matplotlib_by_jyp.1614340610.txt.gz · Last modified: 2021/02/26 11:56 by jypeter