other:uvcdat:cdat_conda:cdat_8_2_1
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other:uvcdat:cdat_conda:cdat_8_2_1 [2024/01/08 13:58] jypeter [Extra packages list] Added GeoPy |
other:uvcdat:cdat_conda:cdat_8_2_1 [2024/07/02 10:44] (current) jypeter [Extra packages list] Added nco |
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| * ''python-cdo'' will install the ''cdo'' package (providing the ''cdo ''executable) as a dependency | * ''python-cdo'' will install the ''cdo'' package (providing the ''cdo ''executable) as a dependency | ||
| * see also [[https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo%7Brbpy%7D|Using CDO from python or ruby]] | * see also [[https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo%7Brbpy%7D|Using CDO from python or ruby]] | ||
| + | * See also ''nco'' | ||
| * [[https://cds.climate.copernicus.eu/api-how-to|cdsapi]]: The Climate Data Store (CDS) Application Program Interface (API) is a service providing programmatic access to CDS data | * [[https://cds.climate.copernicus.eu/api-how-to|cdsapi]]: The Climate Data Store (CDS) Application Program Interface (API) is a service providing programmatic access to CDS data | ||
| * CDS = Copernicus [[https://cds.climate.copernicus.eu/|Climate Data Store]] | * CDS = Copernicus [[https://cds.climate.copernicus.eu/|Climate Data Store]] | ||
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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://docs.dask.org/|dask]]: a Python library for parallel and distributed computing | ||
| + | * dask.[[https://distributed.dask.org/|distributed]]: lightweight library for distributed computing in Python | ||
| + | * See also: flox | ||
| * [[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. | * [[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'' | * Install with: ''conda install dtale -c conda-forge'' | ||
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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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| * [[https://geopy.readthedocs.io/|GeoPy]]: a Python client for several popular geocoding web services | * [[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. | * ''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// | ||
| * [[https://noaa-orr-erd.github.io/gridded/index.html|gridded]]: a single API for accessing / working with gridded model results on multiple grid types | * [[https://noaa-orr-erd.github.io/gridded/index.html|gridded]]: a single API for accessing / working with gridded model results on multiple grid types | ||
| * Supports the [[http://cfconventions.org/|CF]], [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID]] and [[http://sgrid.github.io/sgrid/|SGRID]] conventions | * Supports the [[http://cfconventions.org/|CF]], [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID]] and [[http://sgrid.github.io/sgrid/|SGRID]] conventions | ||
| + | * [[https://uber.github.io/h3-py/|h3-py]]: Uber’s H3 Hexagonal Hierarchical Geospatial Indexing System in Python | ||
| + | * Additional reading: [[https://towardsdatascience.com/uber-h3-for-data-analysis-with-python-1e54acdcc908|Uber H3 for Data Analysis with Python]] | ||
| * [[https://icclim.readthedocs.io/|icclim]]: icclim (Index Calculation for CLIMate) is a Python library to compute climate indices | * [[https://icclim.readthedocs.io/|icclim]]: icclim (Index Calculation for CLIMate) is a Python library to compute climate indices | ||
| * [[https://intake.readthedocs.io/|intake]]: a lightweight package for finding, investigating, loading and disseminating data | * [[https://intake.readthedocs.io/|intake]]: a lightweight package for finding, investigating, loading and disseminating data | ||
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| * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage) | * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage) | ||
| * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]] | * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]] | ||
| + | * [[https://nco.sourceforge.net/|nco]]: The NCO toolkit manipulates and analyzes data stored in netCDF-accessible formats | ||
| + | * Note: this only installs the [[https://nco.sourceforge.net/#Definition|nco executables]] (''ncks'', ''ncatted'', ...)! It is not really a Python package | ||
| + | * See also ''cdo'' | ||
| * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image** | * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image** | ||
| * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files | * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files | ||
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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'' | ||
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| * [[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 | ||
| - | * [[https://github.com/tqdm|tqdm]]: make your loops show a smart progress meter | + | * [[https://github.com/tqdm/tqdm|tqdm]]: make your loops show a smart progress meter |
| * [[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! | ||
other/uvcdat/cdat_conda/cdat_8_2_1.1704722306.txt.gz · Last modified: 2024/01/08 13:58 by jypeter
