other:python:jyp_steps
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other:python:jyp_steps [2018/08/07 14:26] jypeter Added a projections section |
other:python:jyp_steps [2019/05/29 16:04] jypeter [Matplotlib] Improved |
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| </code></note> | </code></note> | ||
| + | |||
| + | ==== Extra numpy information ==== | ||
| + | |||
| + | * More information about array indexing: | ||
| + | * Examples: | ||
| + | * {{ :other:python:indirect_indexing_2.py.txt |}}: Take a vertical slice in a 3D zyx array, along a varying y 'path' | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/basics.indexing.html|Indexing]] (//index arrays//, //boolean index arrays//, //np.newaxis//, //Ellipsis//, //variable numbers of indices//, ...) | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/quickstart.html#fancy-indexing-and-index-tricks|Fancy indexing]] and [[https://docs.scipy.org/doc/numpy/user/quickstart.html#the-ix-function|the ix_() function]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html|Indexing (in the numpy reference manual)]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.indexing.html#routines-indexing|Indexing routines]] | ||
| + | * More information about arrays: | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html#routines-array-creation|Array creation routines]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html|Array manipulation routines]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/maskedarray.html|Masked arrays]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.ma.html|Masked array operations]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/misc.html#ieee-754-floating-point-special-values|Dealing with special numerical values]] (//Nan//, //inf//) | ||
| + | * If you know that your data has missing values, it is cleaner and safer to handle them with [[https://docs.scipy.org/doc/numpy/reference/maskedarray.html|masked arrays]]! | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/misc.html#how-numpy-handles-numerical-exceptions|Handling numerical exceptions]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.err.html|Floating point error handling]] | ||
| ===== cdms2 and netCDF4 ===== | ===== cdms2 and netCDF4 ===== | ||
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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 [[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 | + | - 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 |
| - 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 will usually **initialize matplotlib** with: ''import matplotlib.pyplot as plt'' |
| - | - a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | + | * 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 | ||
| + | * 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 | ||
| + | * ''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=(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 | ||
| + | - 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/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 overall boundaries of the subplots on the figure, and the spacing between the subplots\\ ''plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=None)''\\ or ''my_page.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=None)'' | ||
| + | * [[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]] | ||
| + | - use [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html|my_page.savefig(...)]] to save a figure | ||
| + | * ''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, ...) with them:\\ ''plt.show()'' | ||
| - 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]]! | ||
| - | - sometimes the results of the python/matplolib commands are displayed directly, sometimes not. It depends if you are in [[http://matplotlib.org/faq/usage_faq.html#what-is-interactive-mode|interactive or non-interactive]] mode | + | - 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/api/colorbar_only.html|colorbar_only.py]]: the different types of colorbars (or plotting only a colorbar) | ||
| + | * [[https://matplotlib.org/examples/color/colormaps_reference.html|colormaps_reference.py]]: pre-defined colormaps | ||
| + | * [[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]] | ||
| + | - 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...) | - 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 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 ==== | ||
| + | |||
| + | * [[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 | ||
| + | * 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()'' | ||
| + | |||
| + | ==== 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) | ||
| + | * ''# 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]] | ||
| ===== Graphics related resources ===== | ===== Graphics related resources ===== | ||
| * [[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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| This is **a really nice and useful document** that is regularly updated and used for the [[https://www.euroscipy.org/|EuroScipy]] tutorials. You will learn more things about python, numpy and matplotlib, debugging and optimizing scripts, and also learn about using python for statistics, image processing, machine learning, washing dishes (this is just to check if you have read this page), etc... | This is **a really nice and useful document** that is regularly updated and used for the [[https://www.euroscipy.org/|EuroScipy]] tutorials. You will learn more things about python, numpy and matplotlib, debugging and optimizing scripts, and also learn about using python for statistics, image processing, machine learning, washing dishes (this is just to check if you have read this page), etc... | ||
| - | ===== Quick Reference ===== | + | ===== Quick Reference and cheat sheets ===== |
| * The nice and convenient Python 2.7 Quick Reference: [[http://rgruet.free.fr/PQR27/PQR2.7_printing_a4.pdf|pdf]] - [[http://rgruet.free.fr/PQR27/PQR2.7.html|html]] | * The nice and convenient Python 2.7 Quick Reference: [[http://rgruet.free.fr/PQR27/PQR2.7_printing_a4.pdf|pdf]] - [[http://rgruet.free.fr/PQR27/PQR2.7.html|html]] | ||
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| * Python 3 [[https://perso.limsi.fr/pointal/python:abrege|Quick reference]] and [[https://perso.limsi.fr/pointal/python:memento|Cheat sheet]] | * Python 3 [[https://perso.limsi.fr/pointal/python:abrege|Quick reference]] and [[https://perso.limsi.fr/pointal/python:memento|Cheat sheet]] | ||
| + | * [[https://www.cheatography.com/weidadeyue/cheat-sheets/jupyter-notebook/pdf_bw/|Jupyter Notebook Keyboard Shortcuts]] | ||
| + | |||
| + | ===== Misc tutorials ===== | ||
| + | |||
| + | * [[https://pyformat.info/|PyFormat]]: //With this site we try to show you the most common use-cases covered by the old and new style string formatting API with practical examples// | ||
| ===== Some good coding tips ===== | ===== Some good coding tips ===== | ||
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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
