other:python:jyp_steps
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other:python:jyp_steps [2018/02/26 13:19] jypeter [Matplotlib] Added a ref to zorder |
other:python:jyp_steps [2018/09/04 12:43] jypeter [Matplotlib] added note about colors |
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| - [[https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html|Numpy for Matlab users]] | - [[https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html|Numpy for Matlab users]] | ||
| - [[http://mathesaurus.sourceforge.net/matlab-numpy.html|NumPy for MATLAB users]] (nice, but does not seem to be maintained any more) | - [[http://mathesaurus.sourceforge.net/matlab-numpy.html|NumPy for MATLAB users]] (nice, but does not seem to be maintained any more) | ||
| - | - read the [[https://docs.scipy.org/doc/numpy-dev/user/quickstart.html|Quickstart tutorial]] | + | - read the really nice [[https://docs.scipy.org/doc/numpy/user/quickstart.html|numpy Quickstart tutorial]] |
| - have a quick look at the full documentation to know where things are | - have a quick look at the full documentation to know where things are | ||
| - Numpy User Guide | - Numpy User Guide | ||
| Line 120: | Line 120: | ||
| [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
| </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 ===== | ||
| Line 129: | Line 148: | ||
| ==== cdms2 ==== | ==== cdms2 ==== | ||
| - | Summary: cdms2 can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. Unfortunately, cdms2 is only available in the [[other:python:starting#uv-cdat|UV-CDAT distribution]], and distributions where somebody has installed some version of //cdat-lite//. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data. | + | Summary: cdms2 can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. cdms2 is available in the [[other:python:starting#uv-cdat|UV-CDAT distribution]], and can theoretically be installed independently of UV-CDAT (e.g. it will be installed when you install [[https://cmor.llnl.gov/mydoc_cmor3_conda/|CMOR in conda)]]. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data. |
| How to get started: | How to get started: | ||
| Line 135: | Line 154: | ||
| - the tutorial is in French (soooorry!) | - the tutorial is in French (soooorry!) | ||
| - you have to replace //cdms// with **cdms2**, and //MV// with **MV2** (sooorry about that, the tutorial was written when CDAT was based on //Numeric// instead of //numpy// to handle array data) | - you have to replace //cdms// with **cdms2**, and //MV// with **MV2** (sooorry about that, the tutorial was written when CDAT was based on //Numeric// instead of //numpy// to handle array data) | ||
| - | - read the [[http://uv-cdat.llnl.gov/documentation/cdms/cdms.html|official cdms documentation]] | + | - read the [[http://cdms.readthedocs.io/en/docstanya/index.html|official cdms documentation]] (link may change) |
| - | - ask questions and get answers on the [[http://uvcdat.askbot.com/questions/|UV-CDAT askbot]] | + | |
| Line 145: | Line 163: | ||
| Where: [[http://unidata.github.io/netcdf4-python/]] | Where: [[http://unidata.github.io/netcdf4-python/]] | ||
| + | ===== CDAT-related resources ===== | ||
| + | |||
| + | Some links, in case they can't be found easily on the [[https://uv-cdat.llnl.gov|UV-CDAT]] web site... | ||
| + | |||
| + | * [[https://uv-cdat.llnl.gov/tutorials.html|Tutorials in ipython notebooks]] | ||
| + | * [[http://cdat-vcs.readthedocs.io/en/latest/|VCS: Visualization Control System]] | ||
| + | * [[https://github.com/CDAT/vcs/issues/238|Colormaps in vcs examples]] | ||
| + | * [[https://github.com/CDAT/cdat-site/blob/master/eztemplate.md|EzTemplate Documentation]] | ||
| ===== Matplotlib ===== | ===== Matplotlib ===== | ||
| Line 160: | Line 186: | ||
| - 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]] | ||
| - 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 [[|Gallery]] 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 | ||
| - 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 | - 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 | ||
| - 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...) | ||
| Line 168: | Line 199: | ||
| ===== 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://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| | ||
| Python Seaborn Tutorial For Beginners]] | Python Seaborn Tutorial For Beginners]] | ||
| - | * [[http://colorbrewer2.org|ColorBrewer 2.0]] is a tool that can help you understand, and experiment with //sequential//, //diverging// and //qualitative// colormaps | + | * Working with colors |
| + | * [[https://matplotlib.org/users/colormaps.html|Choosing colormaps]] | ||
| + | * [[https://matplotlib.org/cmocean/|Beautiful colormaps for oceanography: cmocean]] | ||
| + | * [[http://colorbrewer2.org|ColorBrewer 2.0]] is a tool that can help you understand, and experiment with //sequential//, //diverging// and //qualitative// colormaps | ||
| Line 207: | Line 242: | ||
| Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/cartopy|cartopy help]] | Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/cartopy|cartopy help]] | ||
| + | ===== Maps and projections resources ===== | ||
| + | |||
| + | ==== About projections ==== | ||
| + | |||
| + | * [[https://egsc.usgs.gov/isb//pubs/MapProjections/projections.html|Map projections from USGS poster]] | ||
| + | * [[https://pubs.usgs.gov/pp/1395/report.pdf|Map projections - A working manual (USGS)]] | ||
| + | |||
| + | ==== Libraries ==== | ||
| + | |||
| + | * Projections in vcs | ||
| + | * [[http://matplotlib.org/basemap/users/mapsetup.html|Projections in basemap]] | ||
| + | * [[https://scitools.org.uk/cartopy/docs/latest/crs/projections.html|Projections in cartopy]] | ||
| + | |||
| + | |||
| + | ===== 3D resources ===== | ||
| + | |||
| + | * [[https://ipyvolume.readthedocs.io/en/latest/|Ipyvolume]] | ||
| + | * [[https://zulko.wordpress.com/2012/09/29/animate-your-3d-plots-with-pythons-matplotlib/|Animate your 3D plots with Python’s Matplotlib]] | ||
| + | * [[https://stackoverflow.com/questions/26796997/how-to-get-vertical-z-axis-in-3d-surface-plot-of-matplotlib|How to get vertical Z axis in 3D surface plot of Matplotlib?]] | ||
| + | |||
| + | ===== Data file formats ===== | ||
| + | |||
| + | We list here some resources about non-NetCDF data formats that can be useful | ||
| + | |||
| + | ==== json files ==== | ||
| + | |||
| + | More and more applications use //json files// as configuration files or as a mean to use text files to exchange data (through serialization/deserialization ). | ||
| + | |||
| + | //json// files look basically like a **list of (nested) python dictionaries** that would have been dumped to a text file | ||
| + | |||
| + | * [[https://docs.python.org/2/library/json.html|json module]] documentation | ||
| + | * [[https://realpython.com/python-json/|Working With JSON Data in Python]] tutorial | ||
| + | * example script: ''/home/users/jypeter/CDAT/Progs/Devel/beaugendre/nc2json.py'' | ||
| + | * A compact (not easy to read...) //json// file can be pretty-printed with\\ ''cat file.json | python -m json.tool | less'' | ||
| + | |||
| + | ==== LiPD files ==== | ||
| + | |||
| + | Resources for //Linked PaleoData//: | ||
| + | * [[http://linked.earth/projects/lipd/|LiPD]] | ||
| + | * [[https://doi.org/10.5194/cp-12-1093-2016|Technical note: The Linked Paleo Data framework – | ||
| + | a common tongue for paleoclimatology]] @ GMD | ||
| + | * [[https://github.com/nickmckay/LiPD-utilities|LiPD-utilities]] @ github | ||
| + | |||
| + | ==== BagIt files ==== | ||
| + | |||
| + | //BagIt//, a set of hierarchical file layout conventions for storage and transfer of arbitrary digital content. | ||
| + | |||
| + | * [[https://tools.ietf.org/html/draft-kunze-bagit-16|The BagIt File Packaging Format]] | ||
| + | * [[https://github.com/LibraryOfCongress/bagger|Bagger]] (BagIt GUI) | ||
| + | * [[https://github.com/LibraryOfCongress/bagit-python|bagit-python]] | ||
| ===== Pandas ===== | ===== Pandas ===== | ||
| Line 229: | Line 314: | ||
| * 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]] | ||
| + | * A possibly more [[http://iysik.com/PQR2.7/PQR2.7.html|up-date-version]] | ||
| + | |||
| + | * Python 3 [[https://perso.limsi.fr/pointal/python:abrege|Quick reference]] and [[https://perso.limsi.fr/pointal/python:memento|Cheat sheet]] | ||
| ===== Some good coding tips ===== | ===== Some good coding tips ===== | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
