other:python:jyp_steps
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other:python:jyp_steps [2019/05/29 13:59] jypeter [Matplotlib] Improved |
other:python:jyp_steps [2019/06/03 16:12] jypeter [Useful matplotlib reference pages] Added animations |
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| 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 | 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 | ||
| - 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 | - 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 will usually **initialize matplotlib** with: ''import matplotlib.pyplot as plt'' | - You will usually **initialize matplotlib** with: ''import matplotlib.pyplot as plt'' | ||
| * in some cases you may also need: ''import matplotlib as mpl'' | * in some cases you may also need: ''import matplotlib as mpl'' | ||
| - | * you may need other matplotlib related modules, for advanced usage | + | * later, you may need other matplotlib related modules, for advanced usage |
| - You need to know some **matplotlib specific vocabulary**: | - You need to know some **matplotlib specific vocabulary**: | ||
| * a Matplotlib **//Figure//** (or //canvas//) is a graphical window in which you create your plots... | * a Matplotlib **//Figure//** (or //canvas//) is a graphical window in which you create your plots... | ||
| - | * example: ''my_figure = plt.figure()'' | + | * example: ''my_page = plt.figure()'' |
| * if you need several display windows at the same time, create several figures | * 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 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 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 | * 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 | ||
| - | * ''my_page = plt.figure()'': the ratio of the default figure is ''landscape'', because it is 33% larger than it is high | + | * ''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! |
| * ''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=(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) | * ''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]] | * 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 | * 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/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]] | ||
| - use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|my_page.savefig(...)]] to save a figure | - use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|my_page.savefig(...)]] to save a figure | ||
| + | * <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.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 | * ''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 | ||
| - | - 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]]! | + | - **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! | + | - 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 matplotlib reference pages ==== | ==== Useful matplotlib reference pages ==== | ||
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| * example: the default figure size (inches) is ''mpl.rcParams['figure.figsize']'' (''[6.4, 4.8]'') | * example: the default figure size (inches) is ''mpl.rcParams['figure.figsize']'' (''[6.4, 4.8]'') | ||
| * current settings' file: ''mpl.matplotlib_fname()'' | * 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 ==== | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
