Benchmarking speed and memory for fast calculation of Faith's PD
The installation of all packages needed for benchmarking requires
conda
.
conda create --yes -n faith-benchmark python=3.6 pip "numpy>=1.15" -c conda-forge
conda activate faith-benchmark
conda env update --file requirements.yml
# Make the subsets of the data
./01.01-make_data_array_all.sh
# Generate a file with commands used for benchmarking
./01.02-generate-commands-file.sh
# Benchmark Skbio Faith's PD
./01.03-par_timeout_skbio.sh
# Benchmark SFPhD
./01.04-par_timeout_sfphd.sh
# Aggregate the results
./01.05-process_results.sh
After the above steps have been completed, the benchmarking plot can be
recreated by running the 01.06-create-faiths-pd-benchmarking-figure.ipynb
notebook.
The benchmark/time_stacked_faith.py
script can be used with the large
table with the following command, if the path to table and tree are known.
python benchmark/time_stacked_faith.py <path to table> <path to tree>
The results of the power analysis can be recreated with the notebook:
02.01-power-analysis-figure.ipynb
The distributions of Faith's PD by Age group can recreated with the notebook:
03.01-plot-alpha-distributions.ipynb
The Empress visualization can be created with the notebook 03. 02-metagenomic-age-phylog-analysis.ipynb
. Note that a working installation
of Qiime2 with
Empress is need to reproduce the
visualization.