other:uvcdat:cdat_conda:cdat_8_2_1
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other:uvcdat:cdat_conda:cdat_8_2_1 [2022/12/16 16:48] jypeter [Extra packages list] Added mpltern |
other:uvcdat:cdat_conda:cdat_8_2_1 [2023/02/01 10:06] jypeter [Extra packages list] Added cdsapi |
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| //Add here packages that would be useful and have not been installed yet, or have some problems that prevent their installation// | //Add here packages that would be useful and have not been installed yet, or have some problems that prevent their installation// | ||
| - | |||
| - | * [[http://scitools.org.uk/iris/index.html|iris]]: A Python library for Meteorology and Climatology | ||
| - | * ''conda install -n cdatxxx -c conda-forge iris'' | ||
| * [[http://wrf-python.readthedocs.io/en/latest/|wrf-python]]: A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model | * [[http://wrf-python.readthedocs.io/en/latest/|wrf-python]]: A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model | ||
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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]] | ||
| + | * [[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]] | ||
| + | * Example: [[https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=form|ERA5 hourly data on pressure levels from 1959 to present]] | ||
| * [[https://github.com/ecmwf/cfgrib|cfgrib]]: Python interface to map GRIB files to the Unidata's Common Data Model v4 following the CF Conventions | * [[https://github.com/ecmwf/cfgrib|cfgrib]]: Python interface to map GRIB files to the Unidata's Common Data Model v4 following the CF Conventions | ||
| * see also ''eccodes'' and ''pygrib'' | * see also ''eccodes'' and ''pygrib'' | ||
| + | * [[https://unidata.github.io/cftime/|cftime]]: Python library for decoding time units and variable values in a netCDF file conforming to the Climate and Forecasting (CF) netCDF conventions | ||
| + | * Used with ''xarray'' | ||
| * [[https://clustergram.readthedocs.io/|clustergram]]: visualization and diagnostics for cluster analysis | * [[https://clustergram.readthedocs.io/|clustergram]]: visualization and diagnostics for cluster analysis | ||
| * [[https://www.fabiocrameri.ch/colourmaps/|cmcrameri]]: Crameri's Scientific colour maps ''[color]'' | * [[https://www.fabiocrameri.ch/colourmaps/|cmcrameri]]: Crameri's Scientific colour maps ''[color]'' | ||
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| * [[https://github.com/plotly/Kaleido|python-kaleido]]: a cross-platform library for generating static images (e.g. png, svg, pdf, etc.) for web-based visualization libraries | * [[https://github.com/plotly/Kaleido|python-kaleido]]: a cross-platform library for generating static images (e.g. png, svg, pdf, etc.) for web-based visualization libraries | ||
| * [[https://mpltern.readthedocs.io/|mpltern]]: a Python plotting library based on Matplotlib specifically designed for ternary plots | * [[https://mpltern.readthedocs.io/|mpltern]]: a Python plotting library based on Matplotlib specifically designed for ternary plots | ||
| + | * [[https://nc-time-axis.readthedocs.io/en/stable/|nc-time-axis]]: a package that enables making plots in matplotlib with axes made up of ''cftime.datetime'' dates with any calendar type | ||
| * [[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]] | ||
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| * [[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]]: 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]] | ||
| + | * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! | ||
| * [[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://xoa.readthedocs.io/en/latest/|xoa]]: xarray-based ocean analysis library | * [[https://xoa.readthedocs.io/en/latest/|xoa]]: xarray-based ocean analysis library | ||
other/uvcdat/cdat_conda/cdat_8_2_1.txt · Last modified: 2024/07/02 10:44 by jypeter
