# MXML env
export MXML_ROOT=$HOME/lib/mxml
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$MXML_ROOT/lib
# ADIOS env
export ADIOS_ROOT=$HOME/lib/adios-master
export PATH=$PATH:$ADIOS_ROOT/bin
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jupyter nbconvert "somenotebook.ipynb" --to="notebook" --nbformat=3 |
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# Modules ##################################################################### | |
# | |
if [ -f /etc/profile.modules ] | |
then | |
. /etc/profile.modules | |
module purge | |
# export MODULES_NO_OUTPUT=1 | |
# Core Dependencies |
Overview: http://matplotlib.org/faq/usage_faq.html#usage
Multiple, manual Axes: https://python4mpia.github.io/plotting/advanced.html
Another intro article http://pbpython.com/effective-matplotlib.html
(specific read/write library, no extras) https://github.com/blink1073/tifffile/blob/master/tifffile/tifffile.py
from tifffile import imsave
import numpy as np
# create data
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echo "int main() {}"|/opt/XXX/bin/g++ -xc++ - -v | |
ref: https://www.mail-archive.com/cmake@cmake.org/msg50008.html |
Besides best intentions, pre-installed and not correctly (cross-)compiled modules are painful when living on the cutting-dev-edge. Let's start from scratch! :)
The following intro is necessary for a cluster environment where every binary needs to be cross-compiled and $HOME is not mounted on the compute nodes. Furthermore, cross-dependencies and ABI incompatibilities force you to build the full software stack with the same compiler.
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/* Generate the output | |
* | |
* Debian: apt-get install libgraph-easy-perl | |
* Command: | |
* graph-easy --input=libraryDependencies.dot --boxart > libraryDependencies.md | |
* graph-easy --input=libraryDependencies.dot --as_ascii > libraryDependencies.txt | |
* graph-easy --input=libraryDependencies.dot --svg > libraryDependencies.svg | |
* graph-easy --input=libraryDependencies.dot --png | |
*/ |