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--- other:uvcdat:cdat_conda:cdat_8_2_1 [2022/02/10 15:14]
jypeter [Extra packages list] Added intake and intake-esm
+++ other:uvcdat:cdat_conda:cdat_8_2_1 [2024/03/07 16:39]
jypeter [Extra packages list] Added eigen
@@ Line 259: / Line 259: @@
 dreqPy version 01.00.29 [Version 01.00.29]</code>
-  * [[https://github.com/PBrockmann/ipython_ferretmagic|ipython_ferretmagic]]: IPython notebook extension for ferret
+  * ''ipython_ferretmagic'': more details in the [[#extra_packages_list|Extra packages list section]]
-    * ''conda activate cdatm19_py3''\\ ''pip install ferretmagic''
 === Packages with no dependency problems and were added (or updated) later ===
@@ Line 267: / Line 266: @@
   * [[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''
-    * 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
@@ Line 282: / Line 279: @@
 //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
@@ Line 322: / Line 316: @@
   * [[http://unidata.github.io/netcdf4-python/|netcdf4]]: a Python interface to the netCDF C library
-  * [[https://github.com/PBrockmann/ipython_ferretmagic|ipython_ferretmagic]]: IPython notebook extension for ferret
   * [[https://github.com/PCMDI/pcmdi_metrics|PCMDI metrics package]] (PMP): objectively compare results from climate models with observations using well-established statistical tests
   * [[https://xlsxwriter.readthedocs.io/|XlsxWriter]]: a Python module for creating Excel XLSX files
@@ Line 338: / Line 331: @@
 </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
     * [[missing|basemap-data]] and [[https://github.com/conda-forge/basemap-data-hires-feedstock|basemap-data-hires]]: (high resolution) data for ''basemap''
@@ Line 346: / Line 339: @@
     * ''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]]
+  * [[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
     * 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://cf-xarray.readthedocs.io/|cf_xarray]]: provides an accessor (''DataArray.cf'' or ''Dataset.cf'') that allows you to interpret //Climate and Forecast// metadata convention attributes present on ''xarray'' objects
+    * Used with ''xarray''
   * [[https://clustergram.readthedocs.io/|clustergram]]: visualization and diagnostics for cluster analysis
   * [[https://www.fabiocrameri.ch/colourmaps/|cmcrameri]]: Crameri's Scientific colour maps ''[color]''
     * the colormaps are also available in [[https://jiffyclub.github.io/palettable/scientific/|palettable.scientific]]
   * [[http://matplotlib.org/cmocean/|cmocean]]: beautiful colormaps for oceanography ''[color]''
+  * [[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''
+  * [[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)
     * Note: older installations provided [[https://github.com/pierre-rouanet/dtw|dtw]]: DTW (Dynamic Time Warping) python module
@@ Line 357: / Line 361: @@
     * need to install ''eccodes'' and ''python-eccodes'' ([[https://github.com/ecmwf/eccodes-python/issues/56|details]])
     * 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://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
+  * [[https://flox.readthedocs.io/|flox]]: fast & furious //GroupBy// reductions for dask.array
+    * See also
+      * [[https://xarray.dev/blog/flox|flox: Faster GroupBy reductions with Xarray]]
+      * [[https://flox.readthedocs.io/en/latest/implementation.html|Parallel Algorithms]]
   * [[http://ferret.pmel.noaa.gov/Ferret/documentation/pyferret|pyferret]] and ''ferret_datasets'': Ferret encapsulated in Python
+    * [[https://github.com/PBrockmann/ipython_ferretmagic|ipython_ferretmagic]]: IPython notebook extension for ferret
+      * Install with: ''pip install ferretmagic''
   * 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://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
     * 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
+    * Supports the [[http://cfconventions.org/|CF]], [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID]] and [[http://sgrid.github.io/sgrid/|SGRID]] conventions
+  * [[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-esm.readthedocs.io/|intake-esm]]: data cataloging utility built on top of intake, pandas, and xarray
+  * [[https://ipyleaflet.readthedocs.io/en/latest/|ipyleaflet]]: interactive maps in the Jupyter notebook
+  * [[https://ipywidgets.readthedocs.io/|ipywidgets]]: ipywidgets, also known as jupyter-widgets or simply widgets, are interactive HTML widgets for Jupyter notebooks and the IPython kernel
   * [[https://scitools-iris.readthedocs.io/en/stable/|iris]]: a powerful, format-agnostic, community-driven Python package for analysing and visualising Earth science data
     * see also ''cartopy''
     * install sample data with ''conda install -c conda-forge iris-sample-data''
   * [[https://joblib.readthedocs.io/en/latest/|joblib]]: running Python functions as pipeline jobs
+  * [[https://jupyterlab.readthedocs.io/|jupyterlab]]: the next-generation web-based user interface for Project Jupyter
+  * [[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://unidata.github.io/MetPy/latest/|MetPy]]: a collection of tools in Python for reading, visualizing, and performing calculations with weather data
+  * [[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)
+    * 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://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://jiffyclub.github.io/palettable/|Palettable]]: Color palettes for Python ''[color]''
   * [[http://pandas.pydata.org/|pandas]]: Python Data Analysis Library
@@ Line 374: / Line 405: @@
   * [[https://peakutils.readthedocs.io/|PeakUtils]]: utilities related to the detection of peaks on 1D data
   * [[https://python-pillow.org/|pillow]]: the friendly PIL (//Python Imaging Library//) fork
+  * [[https://plotly.com/python/|plotly]]: Plotly's Python graphing library (sometimes referred to as //plotly.py//) makes interactive, publication-quality graphs
+    * see also ''python-kaleido'' and ''dash''
+  * [[https://www.fatiando.org/pooch/|pooch]]: a friend to fetch your data files (makes it easy to download a file, without messing with ''requests'' and ''urllib'')
   * [[https://proplot.readthedocs.io/en/latest/|proplot]]: a lightweight **matplotlib wrapper** for making beautiful, publication-quality graphics
+  * [[https://psyplot.github.io/|psyplot]]: Interactive Data Visualization from Python and GUIs
   * [[https://github.com/jswhit/pygrib|pygrib]]: high-level interface to the ECWMF ECCODES C library for reading GRIB files
     * see also ''eccodes'' and ''cfgrib''
+  * [[https://pyleoclim-util.readthedocs.io/|pyleoclim]]: a Python package designed for the analysis of paleoclimate data
+    * **Wait** till it can be installed with ''conda'' ([[https://github.com/LinkedEarth/Pyleoclim_util/discussions/205|Why I'm not installing Pyleoclim yet]])
+  * [[https://requests.readthedocs.io/|requests]]: is an elegant and simple HTTP library for Python, built for human beings
+    * 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
   * [[http://scikit-image.org/|scikit-image]]: a collection of algorithms for image processing in Python
@@ Line 382: / Line 423: @@
   * [[https://seaborn.pydata.org/|seaborn]]: statistical data visualization
   * [[http://pythonhosted.org/seawater/|seawater]]: Python re-write of the CSIRO seawater toolbox
-    * 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://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
+    * **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://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version
-  * [[https://xcdat.readthedocs.io/|xcdat]]: Xarray Extended with Climate Data Analysis Tools
+  * [[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/|UGRID Conventions]]
+  * [[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'', ''rioxarray'', ...
+  * [[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://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://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
     * ''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://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 ====

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