Functions for correlation matrix, copula indicator and plotting #216
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| # dingo : a python library for metabolic networks sampling and analysis | |
| # dingo is part of GeomScale project | |
| # Copyright (c) 2021-2022 Vissarion Fisikopoulos | |
| # Licensed under GNU LGPL.3, see LICENCE file | |
| name: dingo-ubuntu | |
| on: [push, pull_request] | |
| jobs: | |
| build: | |
| runs-on: ubuntu-latest | |
| strategy: | |
| matrix: | |
| #python-version: [2.7, 3.5, 3.6, 3.7, 3.8] | |
| python-version: [3.8] | |
| steps: | |
| - uses: actions/checkout@v2 | |
| - name: Set up Python ${{ matrix.python-version }} | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Load submodules | |
| run: | | |
| git submodule update --init; | |
| - name: Download and unzip the boost library | |
| run: | | |
| wget -O boost_1_76_0.tar.bz2 https://boostorg.jfrog.io/artifactory/main/release/1.76.0/source/boost_1_76_0.tar.bz2; | |
| tar xjf boost_1_76_0.tar.bz2; | |
| rm boost_1_76_0.tar.bz2; | |
| - name: Download and unzip the lp-solve library | |
| run: | | |
| wget https://sourceforge.net/projects/lpsolve/files/lpsolve/5.5.2.11/lp_solve_5.5.2.11_source.tar.gz | |
| tar xzvf lp_solve_5.5.2.11_source.tar.gz | |
| rm lp_solve_5.5.2.11_source.tar.gz | |
| - name: Install dependencies | |
| run: | | |
| sudo apt-get install libsuitesparse-dev; | |
| curl -sSL https://install.python-poetry.org | python3 - --version 1.3.2; | |
| poetry --version | |
| poetry show -v | |
| source $(poetry env info --path)/bin/activate | |
| poetry install; | |
| pip3 install numpy scipy; | |
| - name: Run tests | |
| run: | | |
| poetry run python3 tests/fba.py; | |
| poetry run python3 tests/full_dimensional.py; | |
| poetry run python3 tests/max_ball.py; | |
| poetry run python3 tests/scaling.py; | |
| poetry run python3 tests/sampling.py; | |
| poetry run python3 tests/sampling_no_multiphase.py; | |
| # currently we do not test with gurobi | |
| # python3 tests/fast_implementation_test.py; | |
| #run all tests | |
| #python -m unittest discover test | |
| #TODO: use pytest |