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.