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Follow the instructions about the conda-based versions of UV-CDAT initialization for actually using an installed version of 2.10
DIsk space used before 2.10 installation (after running conda clean –all
)
> du -sh /home/share/unix_files/cdat/miniconda2 6.5G /home/share/unix_files/cdat/miniconda2 > du -sh /home/share/unix_files/cdat/miniconda2/* 4.4M /home/share/unix_files/cdat/miniconda2/bin 4.0K /home/share/unix_files/cdat/miniconda2/conda-bld 272K /home/share/unix_files/cdat/miniconda2/conda-meta 6.4G /home/share/unix_files/cdat/miniconda2/envs 20K /home/share/unix_files/cdat/miniconda2/etc 3.8M /home/share/unix_files/cdat/miniconda2/include 99M /home/share/unix_files/cdat/miniconda2/lib 4.0K /home/share/unix_files/cdat/miniconda2/LICENSE.txt 76K /home/share/unix_files/cdat/miniconda2/pkgs 376K /home/share/unix_files/cdat/miniconda2/share 364K /home/share/unix_files/cdat/miniconda2/ssl >du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.8G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 1.7G /home/share/unix_files/cdat/miniconda2/envs/keras 2.0G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
Actual installation
bash-4.1$ conda create -n uvcdat-2.10 -c conda-forge -c uvcdat uvcdat=2.10 # Generate the list of installed packages conda list -n uvcdat-2.10 > /home/scratch01/jypeter/uvcdat-2.10_list_170721.txt
List of installed packages: uvcdat-2.10_list_170721.txt
Disk space after 2.10 installation
bash-4.1$ conda env list # conda environments: # cdatm14 /home/share/unix_files/cdat/miniconda2/envs/cdatm14 keras /home/share/unix_files/cdat/miniconda2/envs/keras uvcdat-2.10 /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.10 uvcdat-2.8.0 /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0 root * /home/share/unix_files/cdat/miniconda2 > du -sh /home/share/unix_files/cdat/miniconda2 11G /home/share/unix_files/cdat/miniconda2 > du -sh /home/share/unix_files/cdat/miniconda2/* 4.4M /home/share/unix_files/cdat/miniconda2/bin 4.0K /home/share/unix_files/cdat/miniconda2/conda-bld 272K /home/share/unix_files/cdat/miniconda2/conda-meta 9.2G /home/share/unix_files/cdat/miniconda2/envs 20K /home/share/unix_files/cdat/miniconda2/etc 3.8M /home/share/unix_files/cdat/miniconda2/include 99M /home/share/unix_files/cdat/miniconda2/lib 4.0K /home/share/unix_files/cdat/miniconda2/LICENSE.txt 1.4G /home/share/unix_files/cdat/miniconda2/pkgs 376K /home/share/unix_files/cdat/miniconda2/share 364K /home/share/unix_files/cdat/miniconda2/ssl > du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.8G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 1.7G /home/share/unix_files/cdat/miniconda2/envs/keras 2.8G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.10 2.0G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
Disk space after removing the keras environment that we don't need any more
jypeter@asterix2 - ...cdat - 67 >du -sh /home/share/unix_files/cdat/miniconda2 9.0G /home/share/unix_files/cdat/miniconda2 jypeter@asterix2 - ...cdat - 68 >du -sh /home/share/unix_files/cdat/miniconda2/* 4.4M /home/share/unix_files/cdat/miniconda2/bin 4.0K /home/share/unix_files/cdat/miniconda2/conda-bld 272K /home/share/unix_files/cdat/miniconda2/conda-meta 7.5G /home/share/unix_files/cdat/miniconda2/envs 20K /home/share/unix_files/cdat/miniconda2/etc 3.8M /home/share/unix_files/cdat/miniconda2/include 99M /home/share/unix_files/cdat/miniconda2/lib 4.0K /home/share/unix_files/cdat/miniconda2/LICENSE.txt 1.4G /home/share/unix_files/cdat/miniconda2/pkgs 376K /home/share/unix_files/cdat/miniconda2/share 364K /home/share/unix_files/cdat/miniconda2/ssl jypeter@asterix2 - ...cdat - 69 >du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.8G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 2.8G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.10 2.0G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
This section is about the creation of the cdatm14 environment
Notes about actually using the cdatm14 conda-based python
Note: using hard links, cloning a full environment only adds an extra 100M of disk space
bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2 2.7G /home/share/unix_files/cdat/miniconda2 bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.0G /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0 bash-4.1$ conda create -n cdatm14 --clone uvcdat-2.8.0 [...] bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2 2.8G /home/share/unix_files/cdat/miniconda2 bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.0G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 82M /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
You should download the test 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…)
(cdatm14) bash-4.1$ 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/miniconda2/envs/cdatm14/share/uvcdat/sample_data (cdatm14) bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/cdatm14/share/uvcdat/sample_data 174M /home/share/unix_files/cdat/miniconda2/envs/cdatm14/share/uvcdat/sample_data
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 cdatm14 -c conda-forge -c uvcdat -c vacumm pillow pandas statsmodels seaborn scikit-image seawater gsw netcdf4 pyferret vacumm > /home/scratch01/jypeter/lsce-extra_01_install_160223.txt # Install... bash-4.1$ conda install -n cdatm14 -c conda-forge -c uvcdat -c vacumm pillow pandas statsmodels seaborn scikit-image seawater gsw netcdf4 pyferret vacumm # Check the disk space after installation bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2 3.6G /home/share/unix_files/cdat/miniconda2 bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.4G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 82M /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 2.9G /home/share/unix_files/cdat/miniconda2 bash-4.1$ du -sh /home/share/unix_files/cdat/miniconda2/envs/* 2.4G /home/share/unix_files/cdat/miniconda2/envs/cdatm14 82M /home/share/unix_files/cdat/miniconda2/envs/uvcdat-2.8.0
Lists of installed packages: lsce-extra_01_install_160223.txt
The following packages have no dependency problems and were installed later
basemap
conda install -n cdatm14 -c conda-forge basemap-data-hires
conda install -n cdatm14 -c conda-forge -c pcmdi pcmdi_metrics
conda install -n cdatm14 xlsxwriter
dreqPy
pip install dreqPy
pip install --upgrade dreqPy
$ drq -v dreqPy version 01.00.06 [Version 01.00.06]
conda install -n cdatm14 -c conda-forge -c pcmdi -c uvcdat cmor
cmor-3.2.3
pip install dtw
Add here packages that would be useful but have some problems that prevent their installation
conda install -n cdatm14 -c conda-forge esmpy
7.0.0
did not report errors, but esmpy seemed to have libraries based importation problems and has been removedconda -n cdatm14 remove esmpy
shapely
request a downgrade of geos
when installed from conda-forge (see github issue) but it will work when installed from the default repoconda install -n cdatm14 shapely
cartopy
(below) requests the same downgrade of geos
…cartopy
(uvcdat-2.8.0) bash-4.1$ conda install -n cdatm14 -c conda-forge -c uvcdat libxslt lxml owslib pyepsg [...] The following NEW packages will be INSTALLED: libxslt: 1.1.29-3 conda-forge lxml: 3.7.2-py27_1 conda-forge owslib: 0.14.0-py27_0 conda-forge pyepsg: 0.3.1-py27_0 conda-forge [...] (uvcdat-2.8.0) bash-4.1$ conda install -n cdatm14 -c conda-forge cartopy [...] The following NEW packages will be INSTALLED: cartopy: 0.15.0-np111py27_0 conda-forge The following packages will be DOWNGRADED due to dependency conflicts: geos: 3.6.0-0 conda-forge --> 3.5.1-1 conda-forge matplotlib: 2.0.0-np111py27_2 conda-forge --> 1.5.3-np111py27_7 conda-forge Proceed ([y]/n)? n (uvcdat-2.8.0) bash-4.1$ conda install --force -n cdatm14 -c conda-forge cartopy [...] The following NEW packages will be INSTALLED: cartopy: 0.15.0-np111py27_0 conda-forge Proceed ([y]/n)? y
rpy2
will trigger the installation of R
!R
already installed at LSCEconda install --force -n cdatm14 -c conda-forge -c uvcdat rpy2
basemap
conda install -n cdatm14 -c daler wget=3.2
in order to get version 3.2, the same as the one on Pypi
After following the steps above, we get the following environments. Use the conda info –envs
command to get the up-to-date list of available environments
Environment name | Server | conda list |
---|---|---|
uvcdat-2.8.0 | LSCE ciclad | package list |
cdatm14 | LSCE ciclad | package list |
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