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other:python:jyp_steps [2019/05/29 08:55] jypeter [Matplotlib] details for subplots_adjust |
other:python:jyp_steps [2019/06/03 16:12] jypeter [Useful matplotlib reference pages] Added animations |
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Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/matplotlib|matplotlib help]] | Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/matplotlib|matplotlib help]] | ||
- | The documentation is good, but not always easy to use. <wrap hi>A good way to start with matplotlib</wrap> is to: | + | The matplotlib documentation is good, but not always easy to use. <wrap hi>A good way to start with matplotlib</wrap> is to quickly read the following, practice, and read this section again |
- | - Look at the [[https://matplotlib.org/gallery/index.html|matplotlib gallery]] to get an idea of all you can do with matplotlib. Later, when you need to plot something, go back to the gallery to find some examples that are close to what you need and click on them to view their source code | + | - Have a quick look at the [[https://matplotlib.org/gallery/index.html|matplotlib gallery]] to get an idea of all you can do with matplotlib. Later, when you need to plot something, go back to the gallery to find some examples that are close to what you need and click on them to view their source code |
+ | * some examples are more //pythonic// (ie object oriented) than others, some example mix different styles of coding, all this can be confusing. Try to [[http://matplotlib.org/faq/usage_faq.html#coding-styles|use an object oriented way of doing things]]! | ||
- Use the free hints provided by JY! | - Use the free hints provided by JY! | ||
- | - You need to know some matplotlib specific vocabulary: | + | - You will usually **initialize matplotlib** with: ''import matplotlib.pyplot as plt'' |
- | * a Matplotlib //Figure// is a graphical window in which you make your plots... | + | * in some cases you may also need: ''import matplotlib as mpl'' |
+ | * later, you may need other matplotlib related modules, for advanced usage | ||
+ | - You need to know some **matplotlib specific vocabulary**: | ||
+ | * a Matplotlib **//Figure//** (or //canvas//) is a graphical window in which you create your plots... | ||
+ | * example: ''my_page = plt.figure()'' | ||
+ | * if you need several display windows at the same time, create several figures | ||
* the [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|parts of a figure]] are often positioned in //normalized coordinates//: ''(0, 0)'' is the bottom left of the figure, and ''(1, 1)'' the top right | * the [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|parts of a figure]] are often positioned in //normalized coordinates//: ''(0, 0)'' is the bottom left of the figure, and ''(1, 1)'' the top right | ||
- | * You can't explicitly specify the orientation (//portrait// or //landscape//) of a plot. If you want a portrait plot, it's up to you to create a plot that will the higher than it is large. The idea is not to worry about this: create a plot and save it, and then adjust things if need be | + | * 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 |
- | * use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|fig.savefig(...)]] to save a figure | + | * If you 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 try to //fill// the figure |
- | * a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | + | * ''my_page = plt.figure()'': the ratio of the default figure is ''landscape'', because it is 33% larger than it is high. Creating a default figure will be OK most of the time! |
- | * a Matplotlib //Artist// or //Patch// is something (e.g a line, a group of markers, ...) plotted on the Figure/Axis | + | * ''my_page = plt.figure(figsize=(width, height))'': create a figure with a custom ratio (sizes are considered to be in inches) |
+ | * ''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 size details) | ||
+ | * a Matplotlib **//Axis//** is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|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)'': syntax is ''add_subplot(nrows, ncols, index)'' | ||
+ | * ''my_plot = my_page.subplot**s**()'' | ||
+ | * create **3 plots on 1 column** (each plot uses the full width of the figure): | ||
+ | * <code>top_plot = my_page.add_subplot(3, 1, 1) | ||
+ | middle_plot = my_page.add_subplot(3, 1, 2) | ||
+ | bottom_plot = my_page.add_subplot(3, 1, 3)</code> | ||
+ | * the following method is more efficient than add_subplot when there are lots of plots on a page<code>plot_array = my_page.subplots(3, 1) | ||
+ | top_plot = plot_array[0] | ||
+ | middle_plot = plot_array[1] | ||
+ | bottom_plot = plot_array[2]</code> | ||
+ | * creating a figure and axes with a single line: ''my_page, plot_array = **plt**.subplots(3, 1)'' | ||
+ | * a Matplotlib **//Artist//** or //Patch// is //something// (e.g a line, a group of markers, text, the legend...) plotted on the Figure/Axis | ||
+ | * **clearing** the //page// (or part of it): you probably won't need that | ||
+ | * ''my_page.clear()'' or ''my_page.clf()'' or ''plt.clf()'': clear the (current) figure | ||
+ | * ''my_plot.clear()'' or ''my_plot.cla()'': clear the (current) axis | ||
- some resources for having multiple plots on the same figure | - some resources for having multiple plots on the same figure | ||
* [[https://matplotlib.org/gallery/recipes/create_subplots.html#sphx-glr-gallery-recipes-create-subplots-py|Easily creating subplots]] | * [[https://matplotlib.org/gallery/recipes/create_subplots.html#sphx-glr-gallery-recipes-create-subplots-py|Easily creating subplots]] | ||
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* [[https://matplotlib.org/gallery/index.html#subplots-axes-and-figures|Subplots, axes and figures]] gallery | * [[https://matplotlib.org/gallery/index.html#subplots-axes-and-figures|Subplots, axes and figures]] gallery | ||
* [[https://matplotlib.org/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py|Customizing Figure Layouts Using GridSpec and Other Functions]], [[https://matplotlib.org/tutorials/intermediate/constrainedlayout_guide.html|constrained layout]] and [[https://matplotlib.org/tutorials/intermediate/tight_layout_guide.html|tight layout]] | * [[https://matplotlib.org/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py|Customizing Figure Layouts Using GridSpec and Other Functions]], [[https://matplotlib.org/tutorials/intermediate/constrainedlayout_guide.html|constrained layout]] and [[https://matplotlib.org/tutorials/intermediate/tight_layout_guide.html|tight layout]] | ||
- | - some examples are more //pythonic// (ie object oriented) than others, some example mix different styles of coding, all this can be confusing. Try to [[http://matplotlib.org/faq/usage_faq.html#coding-styles|use an object oriented way of doing things]]! | + | - use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|my_page.savefig(...)]] to save a figure |
- | - it may be hard to (remember how to) work with colors. Some examples from the [[https://matplotlib.org/gallery/index.html]] can help you! | + | * <wrap hi>savefig(...) must be called **before** plt.show()!</wrap> |
+ | * ''my_page.savefig('my_plot.pdf')'': save the figure to a pdf file | ||
+ | * ''my_page.savefig('my_plot.png', dpi=200, transparent=True, bbox_inches='tight')'': save the figure to a png file at a higher resolution than the default (default is 100 dots per inch), with a transparent background and no extra space around the figure | ||
+ | - **display** the figure and its plots, and **start interacting** (zooming, panning...) with them:\\ ''plt.show()'' | ||
+ | - it may be hard to (remember how to) **work with colors**. Some examples from the [[https://matplotlib.org/gallery/index.html]] can help you! | ||
* [[https://matplotlib.org/examples/pylab_examples/leftventricle_bulleye.html|leftventricle_bulleye.py]]: associating different types of colormaps to a plot and colorbar | * [[https://matplotlib.org/examples/pylab_examples/leftventricle_bulleye.html|leftventricle_bulleye.py]]: associating different types of colormaps to a plot and colorbar | ||
* [[https://matplotlib.org/examples/api/colorbar_only.html|colorbar_only.py]]: the different types of colorbars (or plotting only a colorbar) | * [[https://matplotlib.org/examples/api/colorbar_only.html|colorbar_only.py]]: the different types of colorbars (or plotting only a colorbar) | ||
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* [[https://matplotlib.org/examples/color/named_colors.html|named_colors.py]]: named colors | * [[https://matplotlib.org/examples/color/named_colors.html|named_colors.py]]: named colors | ||
* More details about the colors below, in the [[#graphics_related_resources|Resources section]] | * More details about the colors below, in the [[#graphics_related_resources|Resources section]] | ||
- | - sometimes the results of the python/matplolib commands are displayed immediately, sometimes not. It depends if you are in [[http://matplotlib.org/faq/usage_faq.html#what-is-interactive-mode|interactive or non-interactive]] mode | ||
- | - if your matplotlib is executed in a batch script, it will generate an error when trying to create (''show()'') a plot, because matplotlib expects to be able to display the figure on a screen by default. | ||
- | * Check how you can [[https://matplotlib.org/faq/howto_faq.html?highlight=web#generate-images-without-having-a-window-appear|generate images offline]] | ||
- | - the documentation may mention [[http://matplotlib.org/faq/usage_faq.html#what-is-a-backend|backends]]. What?? Basically, you use python commands to create a plot, and the backend is the //thing// that will render your plot on the screen or in a file (png, pdf, etc...) | ||
- if you don't see a part of what you have plotted, maybe it's hidden behind other elements! Use the [[https://matplotlib.org/examples/pylab_examples/zorder_demo.html|zorder parameter]] to explicitly specify the plotting order/layers | - if you don't see a part of what you have plotted, maybe it's hidden behind other elements! Use the [[https://matplotlib.org/examples/pylab_examples/zorder_demo.html|zorder parameter]] to explicitly specify the plotting order/layers | ||
* things should automatically work //as expected// if //zorder// is not explicitly specified | * things should automatically work //as expected// if //zorder// is not explicitly specified | ||
* Use the ''zorder=NN'' parameter when creating objects. ''NN'' is an integer where 0 is the lowest value (the farthest from the eye), and objects are plotted above objects with a lower //zorder// value | * Use the ''zorder=NN'' parameter when creating objects. ''NN'' is an integer where 0 is the lowest value (the farthest from the eye), and objects are plotted above objects with a lower //zorder// value | ||
* Use ''matplotlib_object.set_order(NN)'' to change the order after an object has been created | * Use ''matplotlib_object.set_order(NN)'' to change the order after an object has been created | ||
- | - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]] | + | - sometimes the results of the python/matplolib commands are displayed immediately, sometimes not. It depends if you are in [[http://matplotlib.org/faq/usage_faq.html#what-is-interactive-mode|interactive or non-interactive]] mode |
- | - Download the [[http://matplotlib.org/contents.html|pdf version of the manual]]. **Do not print** the 2800+ pages of the manual! Read the beginner's guide (Chapter //FIVE// of //Part II//) and have a super quick look at the table of contents of the whole document. | + | - if your matplotlib is executed in a batch script, it will generate an error when trying to create (''show()'') a plot, because matplotlib expects to be able to display the figure on a screen by default. |
+ | * Check how you can [[https://matplotlib.org/faq/howto_faq.html?highlight=web#generate-images-without-having-a-window-appear|generate images offline]] | ||
+ | - the documentation may mention [[http://matplotlib.org/faq/usage_faq.html#what-is-a-backend|backends]]. What?? Basically, you use python commands to create a plot, and the backend is the //thing// that will render your plot on the screen or in a file (png, pdf, etc...) | ||
+ | - Read the [[https://github.com/rougier/matplotlib-tutorial|Matplotlib tutorial by Nicolas Rougier]] | ||
+ | - Download the [[http://matplotlib.org/contents.html|pdf version of the manual]]. **Do not print** the 2300+ pages of the manual! Read the beginner's guide (Chapter //FIVE// of //Part II//) and have a super quick look at the table of contents of the whole document. | ||
- | ==== Useful reference pages ==== | + | ==== Useful matplotlib reference pages ==== |
* [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html|plot(...)]]: Plot y versus x as lines and/or markers | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html|plot(...)]]: Plot y versus x as lines and/or markers | ||
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* if the legend is outside of the plot, you have to **explicitly provide enough space for the legend on the page** | * if the legend is outside of the plot, you have to **explicitly provide enough space for the legend on the page** | ||
* e.g. with [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]], ''plt.subplots_adjust(right=0.75)'' will make all the plots use 75% on the left of the page, and leave 25% on the right for the legend | * e.g. with [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]], ''plt.subplots_adjust(right=0.75)'' will make all the plots use 75% on the left of the page, and leave 25% on the right for the legend | ||
+ | * The [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html|figure(...)]] and the associated methods | ||
+ | * The [[https://matplotlib.org/api/axes_api.html|axes]] and the associated methods | ||
+ | * [[https://matplotlib.org/tutorials/introductory/customizing.html#matplotlib-rcparams|matplotlib default settings]] can be queried and updated | ||
+ | * example: the default figure size (inches) is ''mpl.rcParams['figure.figsize']'' (''[6.4, 4.8]'') | ||
+ | * current settings' file: ''mpl.matplotlib_fname()'' | ||
+ | * [[https://matplotlib.org/api/animation_api.html|Animations]] ([[https://matplotlib.org/gallery/index.html#animation|demo]]) | ||
==== Misc Matplotlib tricks ==== | ==== Misc Matplotlib tricks ==== |