CDAT 8.0 installation notes

[ Back to all versions ]

UV-CDAT is now the “Community Data Analysis Tools” (CDAT)

Follow the instructions about the conda-based versions of UV-CDAT initialization for actually using an installed version of 8.0

What's New?

8.0 announcement and features summary (all versions)

Full Change log

Installation with Miniconda3

Installing Miniconda3

We have installed a new version of Miniconda3 (steps below adapted from the installing miniconda instructions)

Get the Python 3.7 Linux 64-bit (bash installer) (unless there is a more recent version?)

Find some temporary space on Linux or Windows

Linux:cd /home/scratch01/jypeter

WSL: cd /mnt/h/Scratch/jypeter/ (assuming that there is a H:\Scratch\jypeter directory)

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh (67 Mo, 15 Feb 2019)

Execute the installer

bash Miniconda3-latest-Linux-x86_64.sh

Accept the license

Specify an explicit installation path outside of the home directory, with enough disk space (more than 3G if you are going to install UV-CDAT and some extra packages), preferably on a disk that is not backed up:

Linux LSCE: /home/share/unix_files/cdat/miniconda3

Linux ciclad: /data/jypmce/cdat/miniconda3

WSL: installing to a directory that is not in /home/ does not work (e.g. /mnt/h/CDAT/miniconda3,assuming there is a H:\CDAT\ directory, does not work)
Need to accept the installation in the default location: /home/jypeter/miniconda3

Resulting miniconda3 directory size is 302M

>du -sh miniconda3
302M miniconda3
>cd miniconda3
/home/share/unix_files/cdat/miniconda3
>du -sh *
6.3M bin
2.0M compiler_compat
524K conda-meta
4.0K envs
28K etc
5.2M include
146M lib
8.0K LICENSE.txt
142M pkgs
928K share
92K ssl
12K x86_64-conda_cos6-linux-gnu

Accept the automatic update of the PATH variable in .bashrc (note: the installer automatically creates a backup of .bashrc). This will some extra lines at the end of .bashrc used by the old-style conda initialization (we will later switch to the new-style). The added lines should look like:

# added by Miniconda3 installer
export PATH=“/home/share/unix_files/cdat/miniconda3/bin:$PATH”

# added by Miniconda4.xxx installer
[some really fancy bash shell commands]

Remove the installer: rm Miniconda3-latest-Linux-x86_64.sh

Open a new terminal (if you use bash) or open a new terminal and type bash

check if the python from the conda distribution has been correctly installed

> bash
$ which python
/home/share/unix_files/cdat/miniconda3/bin/python
$ which conda
/home/share/unix_files/cdat/miniconda3/bin/conda

Update and clean the new installation

$ conda update --all
$ du -sh /home/share/unix_files/cdat/miniconda3
515M /home/share/unix_files/cdat/miniconda3
$ conda clean --all
$ du -sh /home/share/unix_files/cdat/miniconda3
270M /home/share/unix_files/cdat/miniconda3
$ conda list
# packages in environment at /home/share/unix_files/cdat/miniconda3:
#
# Name Version Build Channel
[...]
python 3.7.1 h0371630_3
readline 7.0 h7b6447c_5
requests 2.20.0 py37_0
[...]

Post-Miniconda3 installation

The idea is to remove the miniconda3 initialization lines that were automatically added at the end of .bashrc and put them (and other useful commands) in a special initialization file, that can be sourced only when we actually want to use conda and CDAT (in order to avoid potentiel side effects)

New style initialization

Note: this is the new conda activate some_version style

See the ~jypeter/.conda3_jyp.sh file below, and how to use it, in a bash shell. In a tcsh shell, see the ~jypeter/.conda3_jyp.csh further down. In both shell cases, if you are installing your own version of python, you need to use your own location of the initialization files in the source lines, and you can use another file name than conda3_jyp

$ which python
/usr/bin/python
$ cat ~jypeter/.conda3_jyp.sh
# Conda initialization by JYP, NEW style
#
# Use this for working with conda and CDAT centrally managed by JYP
#
# Execute this file in a BASH shell with
# source path/this_file
# Then get the list of available python distributions with
# conda env list
# Then activate a specific distribution with
# conda activate version_name
#
# More details in:
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:python:starting#conda-based_versions_of_uv-cdat
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:uvcdat:conda_notes
#
# Jean-Yves Peterschmitt - LSCE - 11/2018
source /home/share/unix_files/cdat/miniconda3/etc/profile.d/conda.sh
# Use the alias below to easily determine where your python
# interpreter is located
alias wp="which python"
# Where are ALL the python interpreters in the search path
alias wpa="which -a python"
# The end
$ source ~jypeter/.conda3_jyp.sh
$ conda activate
(base) $ which python
/home/share/unix_files/cdat/miniconda3/bin/python

tcsh shell usage example

>which python
/usr/bin/python
>cat ~jypeter/.conda3_jyp.csh
# Conda initialization by JYP, NEW style
#
# Use this for working with conda and CDAT centrally managed by JYP
#
# Execute this file in a TCSH shell with
# source path/this_file
# Then get the list of available python distributions with
# conda env list
# Then activate a specific distribution with
# conda activate version_name
#
# More details in:
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:python:starting#conda-based_versions_of_uv-cdat
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:uvcdat:conda_notes
#
# Jean-Yves Peterschmitt - LSCE - 11/2018
source /home/share/unix_files/cdat/miniconda3/etc/profile.d/conda.csh
# Use the alias below to easily determine where your python
# interpreter is located
alias wp "which python"
# The end
>source ~jypeter/.conda3_jyp.csh
>conda activate
(base) >which python
/home/share/unix_files/cdat/miniconda3/bin/python

You probably don't want to type the source line each time you need to use your conda based python, so you can add a source ~jypeter/.conda3_jyp.sh line in your ~/.bashrc file, and source ~jypeter/.conda3_jyp.csh line in your ~/.cshrc file. Then, when you need a specific python environment, just type conda activate name_of_the_specific_environment

Old style initialization

The old style notes below are just for reference sake and you can skip them

Note: this is the old source activate some_version style

See the ~jypeter/.conda3old_jyp.sh file below, and how to use it, in a bash shell

bash-4.2$ which python
/usr/bin/python
$ cat .conda3old_jyp.sh
# Conda initialization by JYP, OLD style
#
# Use this for working with conda and CDAT centrally managed by JYP
#
# Execute this file in a BASH shell with
# source path/this_file
# Then get the list of available python distributions with
# conda env list
# Then activate a specific distribution with
# source activate version_name
#
# More details in:
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:python:starting#conda-based_versions_of_uv-cdat
# https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:uvcdat:conda_notes
#
# Jean-Yves Peterschmitt - LSCE - 11/2018
export PATH="/home/share/unix_files/cdat/miniconda3/bin:$PATH"
# Use the alias below to easily determine where your python
# interpreter is located
alias wp="which python"
# Where are ALL the python interpreters in the search path
alias wpa="which -a python"
# The end
$ source ~jypeter/.conda3old_jyp.sh
$ wp
/home/share/unix_files/cdat/miniconda3/bin/python

Installing CDAT 8.0

Python 2.7 version

$ conda create -n cdat-8.0_py2 -c cdat/label/v80 -c conda-forge -c cdat python=2.7 cdat
# Generate the list of installed packages
$ conda list -n cdat-8.0_py2 > /home/scratch01/jypeter/cdat-8.0_py2_list_181108.txt

List of installed packages: cdat-8.0_py2_list_181108.txt

Disk space after 8.0 installation

$ du -sh /home/share/unix_files/cdat/miniconda3
4.3G /home/share/unix_files/cdat/miniconda3
$ du -sh /home/share/unix_files/cdat/miniconda3/*
15M /home/share/unix_files/cdat/miniconda3/bin
2.4M /home/share/unix_files/cdat/miniconda3/compiler_compat
4.0K /home/share/unix_files/cdat/miniconda3/conda-bld
3.7M /home/share/unix_files/cdat/miniconda3/conda-meta
2.8G /home/share/unix_files/cdat/miniconda3/envs
28K /home/share/unix_files/cdat/miniconda3/etc
4.9M /home/share/unix_files/cdat/miniconda3/include
156M /home/share/unix_files/cdat/miniconda3/lib
8.0K /home/share/unix_files/cdat/miniconda3/LICENSE.txt
1.4G /home/share/unix_files/cdat/miniconda3/pkgs
1.3M /home/share/unix_files/cdat/miniconda3/share
24K /home/share/unix_files/cdat/miniconda3/ssl
12K /home/share/unix_files/cdat/miniconda3/x86_64-conda_cos6-linux-gnu
$ du -sh /home/share/unix_files/cdat/miniconda3/envs/*
2.8G /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2

Python 3.6 version

$ conda create -n cdat-8.0_py3 -c cdat/label/v80 -c conda-forge -c cdat python=3.6 cdat

Installing CDAT nightly

Notes:

This page is about CDAT 8.0, but we have added a short nightly section here as a convenient shortcut. This should probably be moved to a stand-alone nightly page later

Official nightly page

Python 2.7 version

$ conda create -n cdat-nightly_py2 -c cdat/label/nightly -c conda-forge -c cdat python=2.7 cdat

Not tested! Can this be updated with conda update -n cdat-nightly_py2 -c cdat/label/nightly -c conda-forge -c cdat –all ???

Python 3.6 version

$ conda create -n cdat-nightly_py3 -c cdat/label/nightly -c conda-forge -c cdat python=3.6 cdat

Cloning cdat to add specific packages for LSCE

This section is about the creation of the cdatm17 environment Notes about actually using the cdatm17 conda-based python

Note: using hard links, cloning a full environment only adds an extra 582M of disk space

$ du -sh /home/share/unix_files/cdat/miniconda3/envs/*
2.8G /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
$ conda create -n cdatm17_py2 --clone cdat-8.0_py2
Source: /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
Destination: /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2
Packages: 226
Files: 3
[...]
$ du -sh /home/share/unix_files/cdat/miniconda3/envs/*
2.8G /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
582M /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2

Getting ready for a moving default CDAT

We create a cdatm symbolic link in the envs directory, that has a stable name but can be moved to point to the latest default CDAT. In that case, most users can just activate this cdatm version and always get the latest stable version

$ cd /home/share/unix_files/cdat/miniconda3/envs
$ conda env list
base * /home/share/unix_files/cdat/miniconda3
cdat-8.0_py2 /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
cdatm17_py2 /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2
$ ln -s cdatm17_py2 cdatm
$ conda env list
base * /home/share/unix_files/cdat/miniconda3
cdat-8.0_py2 /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
cdatm /home/share/unix_files/cdat/miniconda3/envs/cdatm
cdatm17_py2 /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2
$ source activate cdatm
(cdatm) bash-4.2$ conda env list
base /home/share/unix_files/cdat/miniconda3
cdat-8.0_py2 /home/share/unix_files/cdat/miniconda3/envs/cdat-8.0_py2
cdatm * /home/share/unix_files/cdat/miniconda3/envs/cdatm
cdatm17_py2 /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2

Customizing UV-CDAT for LSCE

Downloading cdms2/vcs test data

You should download the test data (174M of data…) and use it in the example scripts that you want to distribute, and scripts you write for reporting the errors you find (if any…)

$ source activate cdatm17_py2
(cdatm17_py2) $ python -c 'import vcs; vcs.download_sample_data_files(); print "\nFinished downloading sample data to", vcs.sample_data'
[...]
Finished downloading sample data to /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2/share/uvcdat/sample_data
(cdatm17_py2) $ du -sh /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2/share/uvcdat/sample_data
174M /home/share/unix_files/cdat/miniconda3/envs/cdatm17_py2/share/uvcdat/sample_data

Packages that have no dependency problems

After cloning, we are ready to install some extra packages that may be requested by LSCE users

# Keep a trace of what will be installed
bash-4.1$ conda install --dry-run -n cdatm15 -c conda-forge -c uvcdat -c pcmdi pillow pandas statsmodels seaborn scikit-image seawater gsw netcdf4 pyferret basemap-data-hires pcmdi_metrics xlsxwriter cmor shapely cartopy rpy2 > /home/scratch01/jypeter/lsce-extra_01_install_170808.txt
# Install...
bash-4.1$ conda install -n cdatm15 -c conda-forge -c uvcdat -c pcmdi pillow pandas statsmodels seaborn scikit-image seawater gsw netcdf4 pyferret basemap-data-hires pcmdi_metrics xlsxwriter cmor shapely cartopy rpy2
[...]
# Check the disk space after installation
bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2
11G	/home/share/unix_files/cdat/miniconda2
bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/*
0	/home/share/unix_files/cdat/miniconda2/envs/cdatm
2.8G	/home/share/unix_files/cdat/miniconda2/envs/cdatm14
3.7G	/home/share/unix_files/cdat/miniconda2/envs/cdatm15
574M	/home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.10
2.0G	/home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
# Check the disk space again after cleaning
bash-4.1$ conda clean --all
bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2
9.9G	/home/share/unix_files/cdat/miniconda2

List of installed packages: lsce-extra_01_install_170808.txt

Disk space used after adding the extra packages, in in the new directory hierarchy (cdat/miniconda2b, on the obelix servers)

bash-4.2$ du -sh /home/share/unix_files/cdat/miniconda2b
6.4G	/home/share/unix_files/cdat/miniconda2b
bash-4.2$ du -sh /home/share/unix_files/cdat/miniconda2b/envs/*
0	/home/share/unix_files/cdat/miniconda2b/envs/cdatm
3.8G	/home/share/unix_files/cdat/miniconda2b/envs/cdatm15
630M	/home/share/unix_files/cdat/miniconda2b/envs/uvcdat-2.10
# Check the disk space again after cleaning
bash-4.2$ conda clean --all
bash-4.2$ du -sh /home/share/unix_files/cdat/miniconda2b
5.4G	/home/share/unix_files/cdat/miniconda2b

Packages installed with pip

dreqPy: CMIP6 Data Request Python API

pip install dreqPy

Update with: pip install --upgrade dreqPy

Get version number with:

$ drq -v
dreqPy version 01.00.06 [Version 01.00.06]

dtw: DTW (Dynamic Time Warping) python module

pip install dtw

Requested by Sentia Goursaud

The following packages have no dependency problems and were installed (or updated) later

ESMPy: ESMF Python Regridding Interface

We used the following to get a more up-to-date version of esmpy than the one bundled with 2.10

bash-4.1$ conda list | grep -i esm
esmf 7.0.0 6 conda-forge
esmpy 7.0.0 py27_1 conda-forge
bash-4.1$ conda install -n cdatm15 -c nesii/channel/dev-esmf -c conda-forge esmpy=7.1.0.dev32
[...]
bash-4.1$ conda list | grep -i esm
esmf 7.1.0.dev32 1 nesii/channel/dev-esmf
esmpy 7.1.0.dev32 py27_1 nesii/channel/dev-esmf

cmocean: beautiful colormaps for oceanography

conda install -n cdatm15 -c conda-forge cmocean

iris: A Python library for Meteorology and Climatology

conda install -n cdatm15 -c conda-forge -c scitools iris

OSGeo/GDAL: Geospatial Data Abstraction Library. GDAL is a translator library for raster and vector geospatial data formats

conda install -c conda-forge gdal

Python GDAL/OGR Cookbook

spanlib: Spectral Analysis Library

conda install -n cdatm15 -c stefraynaud -c conda-forge spanlib

Test: python -c 'from spanlib.analyzer import Analyzer'

wrf-python: A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model

conda install -n cdatm15 -c conda-forge wrf-python

glances: a cross-platform monitoring tool (similar to top)

conda install -n cdatm15 -c conda-forge glances

glances@github

windspharm: spherical harmonic wind analysis in Python

conda install -n cdatm15 -c conda-forge windspharm

windspharm@github

TODO

Add here packages that would be useful but have some problems that prevent their installation

vacumm: Validation, Analysis, Comparison - Utilities written in Python to validate and analyze Multi-Model outputs, and compare them to observations

As of August 08 2017, installing vacumm in 2.10 requires downgrading to 2.10 (see github issue)!

Problem solved with vacumm 3.4.1-1 on August 31st! Installation was OK with
conda install -n cdatm15 -c conda-forge -c vacumm vacumm

Install PySPLIT for Sentia
PySPLIT A package for generating HYSPLIT air parcel trajectories trajectories, performing moisture uptake analyses, expediting HYSPLIT cluster analysis, and for visualizing trajectories, clusters, and along-trajectory meteorological data
Works with HYSPLiT

conda install -n cdatm15 -c conda-forge fiona geopandas

pip install pysplit

Other packages

There is no warranty that the packages listed below will work correctly, because it was required to bypass the compatibility checks in order to install them…

NO such packages now!

Updating some packages

Some packages change more often than others, and can be easily updated the following way:

CMOR

Update with: conda update -n cdatm15 -c conda-forge -c pcmdi -c uvcdat cmor

Get version number with: python -c 'from cmor import *; print CMOR_VERSION_MAJOR, CMOR_VERSION_MINOR, CMOR_VERSION_PATCH'

dreqPy

Update with: pip install --upgrade dreqPy

Get version number with: drq -v

Cleaning up things

Some packages may have files that can only be read by the person who installed CDAT and the LSCE extensions (eg pcmdi-metrics in 2.8.0 and cdp in 2.10)

We check if some of the installed files are missing read access for the group or other, and we manually change the permissions

(cdatm15) bash-4.2$ find cdatm15 \! -perm /g+r,o+r -ls
50333969 4 -rw------- 2 jypeter lsce 234 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp-1.0.3-py2.7.egg-info/PKG-INFO
50333971 4 -rw------- 2 jypeter lsce 291 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp-1.0.3-py2.7.egg-info/SOURCES.txt
50333962 4 -rw------- 2 jypeter lsce 4 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp-1.0.3-py2.7.egg-info/top_level.txt
50333961 4 -rw------- 2 jypeter lsce 1 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp-1.0.3-py2.7.egg-info/dependency_links.txt
50333960 4 -rw------- 2 jypeter lsce 1 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp-1.0.3-py2.7.egg-info/not-zip-safe
50333987 8 -rw------- 2 jypeter lsce 5149 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_viewer.pyc
50333986 8 -rw------- 2 jypeter lsce 4208 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_metric.py
50333966 4 -rw------- 2 jypeter lsce 150 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/__init__.pyc
50333968 4 -rw------- 2 jypeter lsce 201 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_provenance.py
50333988 8 -rw------- 2 jypeter lsce 5365 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_metric.pyc
50333982 4 -rw------- 2 jypeter lsce 1821 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_parser.py
50333981 4 -rw------- 2 jypeter lsce 1773 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_parameter.py
50333973 4 -rw------- 2 jypeter lsce 670 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_output.py
50333980 4 -rw------- 2 jypeter lsce 1642 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_output.pyc
50333979 4 -rw------- 2 jypeter lsce 1474 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/_cache.pyc
50333967 4 -rw------- 2 jypeter lsce 187 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_tool.py
50333989 0 -rw------- 2 jypeter lsce 0 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/__init__.py
50333985 4 -rw------- 2 jypeter lsce 3843 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_viewer.py
50333984 4 -rw------- 2 jypeter lsce 2436 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_parameter.pyc
50333970 4 -rw------- 2 jypeter lsce 288 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_io.py
50333974 4 -rw------- 2 jypeter lsce 692 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_tool.pyc
50333978 4 -rw------- 2 jypeter lsce 878 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_io.pyc
50333976 4 -rw------- 2 jypeter lsce 734 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/_cache.py
50333983 4 -rw------- 2 jypeter lsce 2269 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_parser.pyc
50333975 4 -rw------- 2 jypeter lsce 724 Apr 4 20:35 cdatm15/lib/python2.7/site-packages/cdp/cdp_provenance.pyc
(cdatm15) bash-4.2$ chmod -R a+r cdatm15/lib/python2.7/site-packages/cdp*
(cdatm15) bash-4.2$ find cdatm15 \! -perm /g+r,o+r -ls

Extra packages list

pillow: the friendly PIL (Python Imaging Library) fork

pandas: Python Data Analysis Library

statsmodels: a Python module that allows users to explore data, estimate statistical models, and perform statistical tests

seaborn: statistical data visualization

scikit-image: image processing in Python

seawater: Python re-write of the CSIRO seawater toolbox

gsw: Python implementation of the Thermodynamic Equation Of Seawater

vacumm: Validation, Analysis, Comparison - Utilities written in Python to validate and analyze Multi-Model outputs, and compare them to observations

netcdf4: a Python interface to the netCDF C library

pyferret: Ferret encapsulated in

basemap-data-hires: high resolution data for basemap

PCMDI metrics package (PMP): objectively compare results from climate models with observations using well-established statistical tests

XlsxWriter: a Python module for creating Excel XLSX files

Note: this is a dependency of dreqPy

dreqPy: CMIP6 Data Request Python API

CMOR: CMOR (Climate Model Output Rewriter) is used to produce CF-compliant netCDF files

dtw: DTW (Dynamic Time Warping) python module

shapely: a Python wrapper for GEOS for algebraic manipulation of geometry (manipulation and analysis of geometric objects in the Cartesian plane)

cartopy: a library providing cartographic tools for python

rpy2: providing simple and robust access to R from within Python

cmocean: beautiful colormaps for oceanography

iris: A Python library for Meteorology and Climatology

OSGeo/GDAL: Geospatial Data Abstraction Library. GDAL is a translator library for raster and vector geospatial data formats

spanlib: Spectral Analysis Library

wrf-python: A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model

glances: a cross-platform monitoring tool (similar to top)

windspharm: spherical harmonic wind analysis in Python

Removed packages

NO removed packages!

Environments summary

After following the steps above, we get the following environments. Use the conda info --envs or the conda env list command to get the up-to-date list of available environments

Environment name	Server	conda list
uvcdat-2.10	LSCE	package list
cdatm15	LSCE	package list

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