other:python:matplotlib_by_jyp
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other:python:matplotlib_by_jyp [2020/03/31 10:49] jypeter [Misc Matplotlib tricks] Improved |
other:python:matplotlib_by_jyp [2020/12/14 14:55] jypeter [Useful matplotlib reference pages] Added details to the titles |
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| - 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]] | ||
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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 | + | * **X and Y axes parameters** (see also [[https://matplotlib.org/examples/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) | ||
| - | * Axis label: ''my_plot.set_xlabel(x_label_string, fontsize=axis_label_fontsize)'' | + | * **Axis label**: ''my_plot.set_xlabel(x_label_string, fontsize=axis_label_fontsize)'' |
| - | * Use the extra labelpad parameter to move the label closer (negative value) to the axis or farther (positive value): e.g. ''my_plot.set_xlabel('A closer label', labelpad=-20'' | + | * Use the extra labelpad parameter to move the label closer (negative value) to the axis or farther (positive value): e.g. ''my_plot.set_xlabel('A closer label', labelpad=-20'') |
| - | * Major (and minor) tick marks location: ''my_plot.set_xticks(x_ticks_values, minor=False)'' | + | * <wrap hi>cartopy dirty trick</wrap>: you have to use ''my_plot.set_xticks([])'', otherwise the X axis label will not be printed |
| + | * [[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 | ||
| + | * Major (and minor) **tick marks location**: ''my_plot.set_xticks(x_ticks_values, minor=False)'' | ||
| * 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** (if you don't want the default values): ''my_plot.set_xticklabels(x_ticks_labels, minor=False, fontsize=ticklabels_fontsize)'' |
| * ''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 | * ''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 | ||
| * Many more options for ticks, labels, orientation, ... | * Many more options for ticks, labels, orientation, ... | ||
| + | * **Grid lines**: | ||
| + | * Their position is determined by the values used for ''set_xticks'' and ''set_yticks'' | ||
| + | * Activate all (horizontal **and** vertical) grid lines with: ''my_plot.grid(True, linestyle="%%--%%", linewidth=0.5, color='.25',zorder=some_value)''\\ You can adjust the ''zorder'' value to determine if the grid lines should be above or below other parts of the plot! | ||
| + | * Plot only the horizontal **or** vertical lines with:\\ ''ax.yaxis.grid(True)''\\ or ''ax.xaxis.grid(True)'' | ||
| + | * Note: <wrap hi>special case of //cartopy// plots</wrap>: the location of the gridlines, and the properties of the associated labels are determined by ''myplot.gridlines''! See [[https://scitools.org.uk/cartopy/docs/latest/matplotlib/gridliner.html|Cartopy map gridlines and tick labels]] | ||
| * [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html|line]] parameters | * [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html|line]] parameters | ||
| * ''linestyle'': ''solid'', ''None'', [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linestyle|other]] ([[https://matplotlib.org/examples/lines_bars_and_markers/line_styles_reference.html|default styles example]], [[https://matplotlib.org/examples/lines_bars_and_markers/linestyles.html|custom styles example]]) | * ''linestyle'': ''solid'', ''None'', [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linestyle|other]] ([[https://matplotlib.org/examples/lines_bars_and_markers/line_styles_reference.html|default styles example]], [[https://matplotlib.org/examples/lines_bars_and_markers/linestyles.html|custom styles example]]) | ||
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| * [[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: | ||
| - | * [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.suptitle|Figure title]]: ''my_figure.suptitle('Figure title', x=xloc_in_normalized_coordinates, y=yloc_in_normalized_coordinates, ...)'' | + | * **Title at the top of the page**: [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.suptitle|Figure title]]: ''my_figure.suptitle('Figure title', x=xloc_in_normalized_coordinates, y=yloc_in_normalized_coordinates, ...)'' |
| - | * [[https://matplotlib.org/api/axes_api.html#axis-labels-title-and-legend|Axis Labels, title, and legend]]: ''my_plot.set_title('Plot title', ...)'' | + | * **Title above each plot**:[[https://matplotlib.org/api/axes_api.html#axis-labels-title-and-legend|Axis Labels, title, and legend]]: ''my_plot.set_title('Plot title', ...)'' |
| + | * [[https://matplotlib.org/gallery/text_labels_and_annotations/titles_demo.html#sphx-glr-gallery-text-labels-and-annotations-titles-demo-py|Title and labels positions demo]] | ||
| * ''fontsize'': size in points, or (better!) string specifying a relative size (''xx-small'', ''x-small'', ''small'', ''medium'', ''large'', ''x-large'', ''xx-large'') | * ''fontsize'': size in points, or (better!) string specifying a relative size (''xx-small'', ''x-small'', ''small'', ''medium'', ''large'', ''x-large'', ''xx-large'') | ||
| * [[https://matplotlib.org/api/text_api.html#matplotlib.text.Text|all the text properties]] | * [[https://matplotlib.org/api/text_api.html#matplotlib.text.Text|all the text properties]] | ||
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| ===== Misc Matplotlib tricks ===== | ===== Misc Matplotlib tricks ===== | ||
| + | |||
| + | ==== Creating a plot offline ==== | ||
| + | |||
| + | 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 ==== | ==== Specifying the background color of a plot ==== | ||
other/python/matplotlib_by_jyp.txt · Last modified: 2023/10/26 08:39 by jypeter
