other:python:jyp_steps
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other:python:jyp_steps [2019/03/18 14:03] jypeter [Quick Reference and cheat sheets] |
other:python:jyp_steps [2019/05/28 16:24] jypeter [Matplotlib] Changed the URL of the Gallery |
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| The documentation is good, but not always easy to use. <wrap hi>A good way to start with matplotlib</wrap> is to: | The documentation is good, but not always easy to use. <wrap hi>A good way to start with matplotlib</wrap> is to: | ||
| - | - Look at the [[http://matplotlib.org/gallery.html|matplotlib gallery]] to get an idea of all you can do with matplotlib. Later, when you need to plot something, come back to the gallery to find some examples that are close to what you need and click on them to get the sources | + | - 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 |
| - Use the free hints provided by JY! | - Use the free hints provided by JY! | ||
| - | - a Matplotlib //Figure// is a graphical window in which you make your plots... | + | - You need to know some matplotlib specific vocabulary: |
| - | - a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | + | * a Matplotlib //Figure// is a graphical window in which you make your plots... |
| + | * 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 | ||
| + | * use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|fig.savefig(...)]] to save a figure | ||
| + | * a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | ||
| + | * a Matplotlib //Artist// or //Patch// is something (e.g a line, a group of markers, ...) plotted on the Figure/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]] | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.add_subplot|fig.add_subplot(...)]] | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.add_axes|fig.add_axes(...)]] | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplot.html|plt.subplot(...)]] | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots.html|plt.subplots(...)]] with an **s** at the end ([[https://matplotlib.org/gallery/subplots_axes_and_figures/subplots_demo.html|demo]]) | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]] can be used to change the boundaries | ||
| * [[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]] | ||
| - | * [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|parts of a 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]]! | - 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]]! | ||
| - | - it may be hard to (remember how to) work with colors. Some examples from the [[http://matplotlib.org/gallery.html|Gallery]] 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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| - 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...) | ||
| - 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 | ||
| + | * 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 | ||
| - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]] | - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]] | ||
| - 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. | - 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. | ||
| + | |||
| + | ==== Useful 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.scatter.html|scatter(...)]]: A scatter plot of y vs x with varying marker size and/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.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]]) | ||
| + | * [[https://matplotlib.org/api/markers_api.html|marker types]] | ||
| + | * ''fillstyle'': ''full'', ''None'', [[https://matplotlib.org/gallery/lines_bars_and_markers/marker_fillstyle_reference.html|other]] | ||
| + | * Other attributes: ''markersize'', ''markerfacecolor'' (and ''markerfacecoloralt'' for dual color markers), ''markeredgecolor'', ''markeredgewidth'' | ||
| + | * [[https://matplotlib.org/api/colors_api.html|colors]] | ||
| + | * [[https://matplotlib.org/gallery/color/color_demo.html|color demo]] | ||
| + | * [[https://matplotlib.org/examples/color/named_colors.html|named colors]] | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.text.html|text(...)]] and [[https://matplotlib.org/tutorials/text/annotations.html|annotations]] | ||
| + | * ''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/pyplot_api.html#matplotlib.pyplot.legend|legend(...)]] ([[https://matplotlib.org/examples/pylab_examples/legend_demo3.html|legend demo]], [[https://matplotlib.org/users/legend_guide.html|advanced legend guide]]) | ||
| + | * The legend will //show// the lines (or other objects) that were associated with a //label// with the ''label='' keyword when creating/updating a plot | ||
| + | * If there are some elements of a plot that you do not want to associate with a legend (e.g. there are several lines with the same color and markers, but you want to plot the legend only once), do not specify a ''label='' keyword for these elements, or add a ''_'' at the front of the label strings | ||
| + | * The legend is positioned somewhere (that can be specified) **inside** the plot. In order to place a legend **outside** the plot, use the ''bbox_to_anchor'' parameter | ||
| + | * the parameters of ''bbox_to_anchor'' are in normalized coordinates of the current (sub)plot: | ||
| + | * ''(0, 0)'' is the lower left corner of the plot, and ''(1, 1)'' the upper right corner | ||
| + | * ''legend(... bbox_to_anchor=(1.05, 1.), loc='upper left', ...)'' will put the upper left corner of the legend slightly right (''(1.05, 1.)'') of the upper right corner (''(1, 1)'') of the plot | ||
| + | * 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 | ||
| ==== Misc Matplotlib tricks ==== | ==== Misc Matplotlib tricks ==== | ||
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| * [[http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833|Ten Simple Rules for Better Figures]] | * [[http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833|Ten Simple Rules for Better Figures]] | ||
| + | * [[https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/|Top 50 matplotlib Visualizations]] | ||
| * [[http://seaborn.pydata.org/|Seaborn]] is a library for making attractive and informative statistical graphics in Python, built on top of matplotlib | * [[http://seaborn.pydata.org/|Seaborn]] is a library for making attractive and informative statistical graphics in Python, built on top of matplotlib | ||
| * See also: [[https://www.datacamp.com/community/tutorials/seaborn-python-tutorial| | * See also: [[https://www.datacamp.com/community/tutorials/seaborn-python-tutorial| | ||
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| * [[https://www.datacamp.com/community/tutorials/data-science-python-ide|Top 5 Python IDEs For Data Science]] | * [[https://www.datacamp.com/community/tutorials/data-science-python-ide|Top 5 Python IDEs For Data Science]] | ||
| * [[http://noeticforce.com/best-python-ide-for-programmers-windows-and-mac|Python IDE: The10 Best IDEs for Python Programmers]] | * [[http://noeticforce.com/best-python-ide-for-programmers-windows-and-mac|Python IDE: The10 Best IDEs for Python Programmers]] | ||
| + | * [[https://www.techbeamers.com/best-python-ide-python-programming/|Get the Best Python IDE]] | ||
| * [[https://wiki.python.org/moin/IntegratedDevelopmentEnvironments]] | * [[https://wiki.python.org/moin/IntegratedDevelopmentEnvironments]] | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
