other:python:matplotlib_by_jyp
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other:python:matplotlib_by_jyp [2020/02/11 11:00] jypeter [Starting (and more) with matplotlib] |
other:python:matplotlib_by_jyp [2020/03/31 14:26] jypeter [Starting (and more) with matplotlib] Improved offline plot creation |
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| mid_plot = my_page.add_subplot(3, 1, 2) | mid_plot = my_page.add_subplot(3, 1, 2) | ||
| bot_plot = my_page.add_subplot(3, 1, 3)</code> | bot_plot = my_page.add_subplot(3, 1, 3)</code> | ||
| - | * creating an //array of plots// with ''subplots'' is **more efficient** than ''add_subplot'' when there are lots of plots on a page<code>plot_array = my_page.subplots(3, 1) | + | * creating an //array of plots// with ''subplots'' 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] | top_plot = plot_array[0] | ||
| mid_plot = plot_array[1] | mid_plot = plot_array[1] | ||
| bot_plot = plot_array[2]</code> | bot_plot = plot_array[2]</code> | ||
| - | * it is **even more efficient** to create a //figure// and //axes// with a single line: | + | * it is **even more efficient** to create a //figure// **and** //axes// with a single line: |
| * one plot on one page: ''my_page, my_plot = **plt**.subplots()'' | * one plot on one page: ''my_page, my_plot = **plt**.subplots()'' | ||
| * three plots on one A4 portrait page:\\ <code> | * three plots on one A4 portrait page:\\ <code> | ||
| Line 59: | Line 59: | ||
| mid_plot = plot_array[1] | mid_plot = plot_array[1] | ||
| bot_plot = plot_array[2] | bot_plot = plot_array[2] | ||
| + | </code> | ||
| + | * if you need to specify the same additional //keyword// parameters (that will be passed //behind the scene// to the ''add_subplot'' function), you can use the ''subplot_kw'' parameter. For example, if all the plots will be created with cartopy, using the //Robinson// projection, the example above becomes:\\ <code> | ||
| + | my_page, plot_array = plt.subplots(nrows=3, ncols=1, | ||
| + | figsize=(8.3, 11.), # A4 portrait | ||
| + | subplot_kw=dict(projection=ccrs.Robinson())) | ||
| </code> | </code> | ||
| * use [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.add_axes|my_page.add_axes(...)]] to add an axis in an arbirary location of the page\\ ''my_page.add_axes([left, bottom, width, height])'' | * use [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.add_axes|my_page.add_axes(...)]] to add an axis in an arbirary location of the page\\ ''my_page.add_axes([left, bottom, width, height])'' | ||
| Line 99: | Line 104: | ||
| - you can use **transparency** to partially show what is behind some markers or other objects. Many //artists// accept the ''alpha'' parameter where ''0.0'' means that the object is completely transparent, and ''1.0'' means completely opaque\\ e.g. ''my_plot.scatter(..., alpha=0.7)'' | - you can use **transparency** to partially show what is behind some markers or other objects. Many //artists// accept the ''alpha'' parameter where ''0.0'' means that the object is completely transparent, and ''1.0'' means completely opaque\\ e.g. ''my_plot.scatter(..., alpha=0.7)'' | ||
| - 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 | - 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. | + | - 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 (with an X server running) by default.\\ Find out how to deal with this in [[other:python:matplotlib_by_jyp#creating_a_plot_offline|Creating a plot offline]]. |
| - | * 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...) | - 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]] | - Read the [[https://github.com/rougier/matplotlib-tutorial|Matplotlib tutorial by Nicolas Rougier]] | ||
| Line 182: | Line 186: | ||
| ===== Misc Matplotlib tricks ===== | ===== Misc Matplotlib tricks ===== | ||
| - | * Specifying the background color of a plot (e.g. when plotting a masked variable and you don't want the masked areas to be white) | + | ==== Creating a plot offline ==== |
| - | * ''# make the background dark gray (call this before the contourf)''\\ ''plt.gca().patch.set_color('.25')''\\ ''plt.contourf(d)''\\ ''plt.show()'' | + | |
| - | * [[https://stackoverflow.com/questions/9797520/masking-part-of-a-contourf-plot-in-matplotlib|trick source]] | + | You may need to create a plot offline when your network connection is not good enough, you don't have an X server running to display the plot (possibly because the script is running on a cluster), etc... This is easily done with the following code: |
| + | |||
| + | <code># offline_plot = False | ||
| + | offline_plot = True | ||
| + | |||
| + | import matplotlib as mpl | ||
| + | if offline_plot: | ||
| + | # Define the graphic back-end BEFORE importing pyplot | ||
| + | mpl.use('Agg') | ||
| + | |||
| + | # Import the rest of the matplotlib based modules | ||
| + | import matplotlib.pyplot as plt | ||
| + | |||
| + | [ ...your actual code... ] | ||
| + | |||
| + | # Done at last! Save the result | ||
| + | my_page.savefig(out_name, dpi=300, transparent=True, bbox_inches='tight') | ||
| + | |||
| + | if not offline_plot: | ||
| + | # Enter the interactive mode to display the plot | ||
| + | plt.show()</code> | ||
| + | |||
| + | Note: see also [[https://matplotlib.org/gallery/user_interfaces/canvasagg.html|CanvasAgg demo]] for a pure offline plot, and [[https://matplotlib.org/faq/howto_faq.html?highlight=web#howto-webapp|How to use Matplotlib in a web application server]]. But the code above is much easier! | ||
| + | |||
| + | ==== Specifying the background color of a plot ==== | ||
| + | |||
| + | e.g. You need to plot a masked variable, but you don't want the masked areas to be white | ||
| + | |||
| + | <code># make the background dark gray (call this before the contourf) | ||
| + | plt.gca().patch.set_color('.25') | ||
| + | plt.contourf(d) | ||
| + | plt.show()</code> | ||
| + | |||
| + | [[https://stackoverflow.com/questions/9797520/masking-part-of-a-contourf-plot-in-matplotlib|trick source]] | ||
other/python/matplotlib_by_jyp.txt · Last modified: 2023/10/26 08:39 by jypeter
