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other:uvcdat:cdat_conda:cdat_8_2_1 [2023/08/09 08:56] jypeter [Extra packages list] Added link for xESMF |
other:uvcdat:cdat_conda:cdat_8_2_1 [2024/03/07 16:49] jypeter [Extra packages list] |
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* [[https://cmor.llnl.gov/|CMOR]]: CMOR (//Climate Model Output Rewriter//) is used to produce CF-compliant netCDF files | * [[https://cmor.llnl.gov/|CMOR]]: CMOR (//Climate Model Output Rewriter//) is used to produce CF-compliant netCDF files | ||
* ''conda install -n cdatm19_py3 -c conda-forge cmor'' | * ''conda install -n cdatm19_py3 -c conda-forge cmor'' | ||
- | * Get version number with: ''python -c 'from cmor import *; print( (CMOR_VERSION_MAJOR, CMOR_VERSION_MINOR, CMOR_VERSION_PATCH) )' '' | ||
- | * <wrap hi>Warning!</wrap> [[https://github.com/PCMDI/cmor/issues/449|CMOR currently requires Python 2.7]] | ||
* [[http://scitools.org.uk/cartopy/|cartopy]]: a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses | * [[http://scitools.org.uk/cartopy/|cartopy]]: a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses | ||
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</WRAP> | </WRAP> | ||
+ | * [[https://github.com/AutoViML/AutoViz|AutoViz]]: the One-Line Automatic Data Visualization Library. Automatically Visualize any dataset, any size with a single line of code | ||
* [[https://matplotlib.org/basemap/|basemap]]: a library for plotting 2D data on maps in Python | * [[https://matplotlib.org/basemap/|basemap]]: a library for plotting 2D data on maps in Python | ||
* [[missing|basemap-data]] and [[https://github.com/conda-forge/basemap-data-hires-feedstock|basemap-data-hires]]: (high resolution) data for ''basemap'' | * [[missing|basemap-data]] and [[https://github.com/conda-forge/basemap-data-hires-feedstock|basemap-data-hires]]: (high resolution) data for ''basemap'' | ||
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* [[https://dash.plotly.com/|dash]] and [[https://github.com/plotly/jupyter-dash|jupyter-dash]]: the original low-code framework for rapidly building data apps in Python, R, Julia, and F# | * [[https://dash.plotly.com/|dash]] and [[https://github.com/plotly/jupyter-dash|jupyter-dash]]: the original low-code framework for rapidly building data apps in Python, R, Julia, and F# | ||
* see also ''plotly'' | * see also ''plotly'' | ||
+ | * [[https://github.com/man-group/dtale|D-Tale]] brings you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. | ||
+ | * Install with: ''conda install dtale -c conda-forge'' | ||
* [[https://dynamictimewarping.github.io/|python-dtw]]: implementation of Dynamic Time Warping-type (DTW) | * [[https://dynamictimewarping.github.io/|python-dtw]]: implementation of Dynamic Time Warping-type (DTW) | ||
* Note: older installations provided [[https://github.com/pierre-rouanet/dtw|dtw]]: DTW (Dynamic Time Warping) python module | * Note: older installations provided [[https://github.com/pierre-rouanet/dtw|dtw]]: DTW (Dynamic Time Warping) python module | ||
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* need to install ''eccodes'' and ''python-eccodes'' ([[https://github.com/ecmwf/eccodes-python/issues/56|details]]) | * need to install ''eccodes'' and ''python-eccodes'' ([[https://github.com/ecmwf/eccodes-python/issues/56|details]]) | ||
* see also ''cfgrib'' and ''pygrib'' | * see also ''cfgrib'' and ''pygrib'' | ||
+ | * [[https://eigen.tuxfamily.org/|eigen]]: a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms | ||
* [[https://ajdawson.github.io/eofs/|eofs]]: a Python package for EOF analysis of spatial-temporal data | * [[https://ajdawson.github.io/eofs/|eofs]]: a Python package for EOF analysis of spatial-temporal data | ||
* [[https://docs.esmvaltool.org/en/latest/|ESMValTool]]: Earth System Model Evaluation Tool | * [[https://docs.esmvaltool.org/en/latest/|ESMValTool]]: Earth System Model Evaluation Tool | ||
- | * not installed yet (March 2022) because it required download of 302 Mb extra packages and a downgrade of gdal | + | * should install ''esmvaltool-python'' in order to reduce the size/number of dependencies, after checking that it does not require downgrading important packages |
* [[https://flox.readthedocs.io/|flox]]: fast & furious //GroupBy// reductions for dask.array | * [[https://flox.readthedocs.io/|flox]]: fast & furious //GroupBy// reductions for dask.array | ||
* See also | * See also | ||
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* OSGeo/[[http://www.gdal.org/|gdal]]: Geospatial Data Abstraction Library. GDAL is a translator library for raster and vector geospatial data formats | * OSGeo/[[http://www.gdal.org/|gdal]]: Geospatial Data Abstraction Library. GDAL is a translator library for raster and vector geospatial data formats | ||
* [[https://pcjericks.github.io/py-gdalogr-cookbook/|Python GDAL/OGR Cookbook]] | * [[https://pcjericks.github.io/py-gdalogr-cookbook/|Python GDAL/OGR Cookbook]] | ||
+ | * [[https://geopy.readthedocs.io/|GeoPy]]: a Python client for several popular geocoding web services | ||
+ | * ''GeoPy'' makes it easy for Python developers to locate the coordinates of addresses, cities, countries, and landmarks across the globe using third-party geocoders and other data sources. | ||
+ | * [[https://github.com/piskvorky/gensim?tab=readme-ov-file|gensim]]: a Python library for topic modelling, document indexing and similarity retrieval with large corpora | ||
+ | * See also //scikit-learn// | ||
* [[https://github.com/TEOS-10/GSW-python|gsw]]: Python implementation of the Thermodynamic Equation Of Seawater | * [[https://github.com/TEOS-10/GSW-python|gsw]]: Python implementation of the Thermodynamic Equation Of Seawater | ||
* see also //seawater// | * see also //seawater// | ||
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* [[https://requests.readthedocs.io/|requests]]: is an elegant and simple HTTP library for Python, built for human beings | * [[https://requests.readthedocs.io/|requests]]: is an elegant and simple HTTP library for Python, built for human beings | ||
* See also ''pooch'' | * See also ''pooch'' | ||
+ | * [[https://rasterio.readthedocs.io/|rasterio]]: access to geospatial raster data | ||
+ | * [[https://corteva.github.io/rioxarray/|rioxarray]]: ''rasterio'' xarray extension | ||
* [[https://rpy2.github.io/|rpy2]]: an interface to R running embedded in a Python process | * [[https://rpy2.github.io/|rpy2]]: an interface to R running embedded in a Python process | ||
* [[http://scikit-image.org/|scikit-image]]: a collection of algorithms for image processing in Python | * [[http://scikit-image.org/|scikit-image]]: a collection of algorithms for image processing in Python | ||
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* see also ''gsw'' | * see also ''gsw'' | ||
* [[https://www.statsmodels.org/|statsmodels]]: a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. | * [[https://www.statsmodels.org/|statsmodels]]: a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. | ||
+ | * [[https://streamlit.io/|streamlit]]: Streamlit turns data scripts into shareable web apps in minutes | ||
* [[https://github.com/SatAgro/suntime|suntime]]: simple sunset and sunrise time calculation python library | * [[https://github.com/SatAgro/suntime|suntime]]: simple sunset and sunrise time calculation python library | ||
* **Warning**: not available in conda, use ''pip install suntime'' | * **Warning**: not available in conda, use ''pip install suntime'' | ||
+ | * [[https://github.com/fbdesignpro/sweetviz|Sweetviz]] is pandas based Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. | ||
* [[https://www.tensorflow.org/|tensorflow-mkl]]: an end-to-end open source machine learning platform | * [[https://www.tensorflow.org/|tensorflow-mkl]]: an end-to-end open source machine learning platform | ||
* [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version | * [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version | ||
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* [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] | * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] | ||
* [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! | * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! | ||
- | * See also: ''flox'', ''xcdat'', ... | + | * See also: ''flox'', ''xcdat'', ''rioxarray'', ... |
* [[https://xcdat.readthedocs.io/|xcdat]]: Xarray extended with Climate Data Analysis Tools | * [[https://xcdat.readthedocs.io/|xcdat]]: Xarray extended with Climate Data Analysis Tools | ||
* [[https://xclim.readthedocs.io/|xclim]]: an operational Python library for climate services, providing numerous climate-related indicator tools with an extensible framework for constructing custom climate indicators, statistical downscaling and bias adjustment of climate model simulations, as well as climate model ensemble analysis tools. | * [[https://xclim.readthedocs.io/|xclim]]: an operational Python library for climate services, providing numerous climate-related indicator tools with an extensible framework for constructing custom climate indicators, statistical downscaling and bias adjustment of climate model simulations, as well as climate model ensemble analysis tools. | ||
* [[https://xesmf.readthedocs.io/|xESMF]]: Universal Regridder for Geospatial Data | * [[https://xesmf.readthedocs.io/|xESMF]]: Universal Regridder for Geospatial Data | ||
* [[https://xgrads.readthedocs.io/|xgrads]]: parse and read binary dataset described by a ''.ctl'' file commonly used by [[http://cola.gmu.edu/grads/|GrADS]] or [[http://www.opengrads.org/|openGrADS]] | * [[https://xgrads.readthedocs.io/|xgrads]]: parse and read binary dataset described by a ''.ctl'' file commonly used by [[http://cola.gmu.edu/grads/|GrADS]] or [[http://www.opengrads.org/|openGrADS]] | ||
- | * Install with: ''pip install xgrads'' | ||
* [[https://xlrd.readthedocs.io/|xlrd]]: a library for reading data and formatting information from Excel files in the historical .xls format | * [[https://xlrd.readthedocs.io/|xlrd]]: a library for reading data and formatting information from Excel files in the historical .xls format | ||
* [[https://xoa.readthedocs.io/en/latest/|xoa]]: xarray-based ocean analysis library | * [[https://xoa.readthedocs.io/en/latest/|xoa]]: xarray-based ocean analysis library | ||
* ''xoa'' is the successor of [[http://www.ifremer.fr/vacumm/|vacumm]] (vacumm does **not** support Python3) | * ''xoa'' is the successor of [[http://www.ifremer.fr/vacumm/|vacumm]] (vacumm does **not** support Python3) | ||
* [[https://xskillscore.readthedocs.io/|xskillscore]]: metrics for verifying forecasts | * [[https://xskillscore.readthedocs.io/|xskillscore]]: metrics for verifying forecasts | ||
+ | * [[https://docs.profiling.ydata.ai/|ydata-profiling]]: a leading package for data profiling, that automates and standardizes the generation of detailed reports, complete with statistics and visualizations. | ||
==== Removed packages ==== | ==== Removed packages ==== |