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other:python:matplotlib_by_jyp [2021/05/11 17:12] – [Useful matplotlib reference pages] added tick formatters jypeterother:python:matplotlib_by_jyp [2023/10/26 10:39] (current) – [Useful matplotlib reference pages] jypeter
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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://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.1620745962.txt.gz · Last modified: 2021/05/11 17:12 by jypeter

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