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Remove sucpp and depend on unifrac-binaries, instead (#139)
* Remove files that were moved to unifrac-binaries * Get ssu binaries from conda * Change compile to use the unifrac-binaries from conda * Remove sucpp, now in unnifrac-binaries repo * Minor edits to make flake8 happy and update github tests * Fix MacOs path * Fix typo * Add additional python test * Remoove sucpp lines * Update docs * Add one more python test
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‎.github/workflows/main.yml

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Original file line numberDiff line numberDiff line change
@@ -54,78 +54,57 @@ jobs:
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conda config --add channels bioconda
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if [[ "$(uname -s)" == "Linux" ]];
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then
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conda install --yes -c conda-forge -c bioconda gxx_linux-64=7.5.0
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conda install --yes -c conda-forge -c bioconda gxx_linux-64
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else
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conda install --yes -c conda-forge -c bioconda clangxx_osx-64=10.0.0
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conda install --yes -c conda-forge -c bioconda clangxx_osx-64
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fi
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conda install --yes -c conda-forge -c bioconda cython "hdf5>=1.8.17" biom-format numpy "h5py>=2.7.0" "scikit-bio>=0.5.1" flake8 nose
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conda install --yes -c conda-forge -c bioconda mkl-include lz4 hdf5-static
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conda install --yes -c conda-forge -c bioconda cython "hdf5>=1.8.17" biom-format numpy "h5py>=2.7.0" "scikit-bio>=0.5.1" unifrac-binaries flake8 nose
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echo "$(uname -s)"
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if [[ "$(uname -s)" == "Linux" ]];
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then
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which x86_64-conda-linux-gnu-gcc
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x86_64-conda-linux-gnu-gcc -v
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x86_64-conda-linux-gnu-g++ -v
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else
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conda install --yes liblapacke
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which clang
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clang -v
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fi
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which h5c++
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if [[ "$(uname -s)" == "Linux" ]];
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then
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./scripts/install_hpc_sdk.sh
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source setup_nv_h5.sh
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fi
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pushd sucpp
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make test
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make main
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make api
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make capi_test
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if [[ "$(uname -s)" == "Linux" ]];
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then
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rm -f ~/.R/Makevars
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conda install -c conda-forge r-base
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# the r-base package has a broken dependency
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ln -s $CONDA_PREFIX/lib/libreadline.so $CONDA_PREFIX/lib/libreadline.so.6
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R -e 'install.packages("Rcpp", repos="http://lib.stat.cmu.edu/R/CRAN/")'
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make rapi_test
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fi
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popd
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pip install -e .
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- name: Tests
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shell: bash -l {0}
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run: |
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conda activate unifrac
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pushd sucpp
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export UNIFRAC_GPU_INFO=Y
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./test_su
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./test_api
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./test_ska
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popd
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nosetests
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flake8 unifrac setup.py
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- name: Sanity checks
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shell: bash -l {0}
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run: |
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conda activate unifrac
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./sucpp/ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm -m unweighted
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set -e
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ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm -m unweighted
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python -c "import skbio; dm = skbio.DistanceMatrix.read('ci/test.dm')"
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pushd unifrac/tests
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python -c "import unifrac; unifrac.unweighted_to_file('data/crawford.biom','data/crawford.tre','../../ci/test.dm.h5')"
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python -c "import unifrac,skbio; dm_u=unifrac.unweighted('data/crawford.biom','data/crawford.tre'); dm = skbio.DistanceMatrix.read('../../ci/test.dm'); t=abs(dm_u.data-dm.data).max(); print(t); assert t < 0.1"
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popd
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python -c "import h5py,skbio; f_u=h5py.File('ci/test.dm.h5','r'); dm_u=skbio.stats.distance.DistanceMatrix(f_u['matrix'][:,:],f_u['order'][:])"
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python -c "import h5py,skbio; dm = skbio.DistanceMatrix.read('ci/test.dm'); f_u=h5py.File('ci/test.dm.h5','r'); dm_u=skbio.stats.distance.DistanceMatrix(f_u['matrix'][:,:],f_u['order'][:]); t=abs(dm_u.data-dm.data).max(); print(t); assert t < 0.1"
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if [[ "$(uname -s)" == "Linux" ]];
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then
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MD5=md5sum
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else
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MD5='md5 -r'
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fi
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./sucpp/ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.start0.stop3 -m unweighted --mode partial --start 0 --stop 3
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./sucpp/ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.start3.stop5 -m unweighted --mode partial --start 3 --stop 5
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./sucpp/ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.partial --mode merge-partial --partial-pattern "ci/test.dm.start*"
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ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.start0.stop3 -m unweighted --mode partial --start 0 --stop 3
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ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.start3.stop5 -m unweighted --mode partial --start 3 --stop 5
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ssu -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.dm.partial --mode merge-partial --partial-pattern "ci/test.dm.start*"
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exp=$($MD5 ci/test.dm | awk '{ print $1 }')
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obs=$($MD5 ci/test.dm.partial | awk '{ print $1 }')
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python -c "assert '${obs}' == '${exp}'"
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./sucpp/faithpd -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.faith.obs
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faithpd -i unifrac/tests/data/crawford.biom -t unifrac/tests/data/crawford.tre -o ci/test.faith.obs
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tail -n +2 ci/test.faith.obs > ci/test.faith.header-removed.obs
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exp1=$($MD5 unifrac/tests/data/test.faith.exp | awk '{ print $1 }')
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obs1=$($MD5 ci/test.faith.header-removed.obs | awk '{ print $1 }')

‎MANIFEST.in

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@@ -1,13 +1,5 @@
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graft unifrac
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include sucpp/*.biom
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include sucpp/*.tre
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include sucpp/*.hpp
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include sucpp/*.cpp
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include sucpp/*.sh
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include sucpp/Makefile
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global-exclude *.pyc
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global-exclude *.pyo
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global-exclude .git

‎README.md

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@@ -48,12 +48,6 @@ This library can also be installed via a combination of `conda-forge` and `bioco
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conda create --name unifrac -c conda-forge -c bioconda unifrac
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```
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Note: Only the CPU version of the binaries is currently available in conda.
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The GPU version must either be [locally compiled using freely-available NVIDIA HPC SDK](docs/compile_gpu.README.md)
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or obtained [from a github branch](https://github.com/sfiligoi/unifrac/blob/v0.20.2-docs/docs/install_gpu.README.md).
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Note: If you desire a fully optimized the binaries for your CPU, you can [compile them locally](docs/compile_cpu.README.md).
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## Install (pip)
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```
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## Install (native)
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To install, first the binary needs to be compiled. This assumes that the HDF5
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toolchain and libraries are available. More information about how to setup the
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stack can be found [here](https://support.hdfgroup.org/HDF5/Tutor/compile.html).
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To install, first the cython wrappers must be compiled. It also needs
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the libssu library to be present.
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Assuming `h5c++` is in your path, the following should work:
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Assuming the compiler is in your path, the following should work:
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pip install -e .
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**Note**: if you are using `conda` we recommend installing HDF5 using the
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`conda-forge` channel, for example:
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**Note**: if you are using `conda` we recommend installing the compiler and
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libssu using the `biooconda` channel, for example:
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conda install -c conda-forge hdf5
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conda install -c conda-forge -c bioconda gxx_linux-64 unifrac-binaries
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# Examples of use
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‎docs/compile_cpu.README.md

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‎docs/compile_gpu.README.md

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