The nem package

This package is there to use the NEM algorithm.

Submodules

ppanggolin.nem.partition module

ppanggolin.nem.partition.checkPangenomeFormerPartition(pangenome, force)

checks pangenome status and .h5 files for former partitions, delete them if allowed or raise an error

ppanggolin.nem.partition.evaluate_nb_partitions(organisms, sm_degree, free_dispersion, chunk_size, Krange, ICL_margin, draw_ICL, cpu, tmpdir, seed, outputdir)

ppanggolin.nem.partition.launch(args)

main code when launch partition from the command line.

ppanggolin.nem.partition.nemSamples(pack)

ppanggolin.nem.partition.nemSingle(args)

ppanggolin.nem.partition.partition(pangenome, tmpdir, outputdir=None, force=False, beta=2.5, sm_degree=10, free_dispersion=False, chunk_size=500, K=- 1, Krange=None, ICL_margin=0.05, draw_ICL=False, cpu=1, seed=42, keep_tmp_files=False)

ppanggolin.nem.partition.partitionSubparser(subparser)

ppanggolin.nem.partition.partition_nem(index, tmpdir, beta, sm_degree, free_dispersion, K, seed, init, keep_tmp_files)

ppanggolin.nem.partition.run_partitioning(nem_dir_path, nb_org, beta, free_dispersion, K=3, seed=42, init='param_file', keep_files=False, itermax=100, just_log_likelihood=False)

ppanggolin.nem.partition.write_nem_input_files(tmpdir, organisms, sm_degree)

ppanggolin.nem.rarefaction module

ppanggolin.nem.rarefaction.drawCurve(output, maxSampling, data)

ppanggolin.nem.rarefaction.launch(args)

main code when launch partition from the command line.

ppanggolin.nem.rarefaction.launch_raref_nem(args)

ppanggolin.nem.rarefaction.makeRarefactionCurve(pangenome, output, tmpdir, beta=2.5, depth=30, minSampling=1, maxSampling=100, sm_degree=10, free_dispersion=False, chunk_size=500, K=- 1, cpu=1, seed=42, kestimate=False, krange=[3, - 1], soft_core=0.95)

ppanggolin.nem.rarefaction.raref_nem(index, tmpdir, beta, sm_degree, free_dispersion, chunk_size, K, krange, seed)

ppanggolin.nem.rarefaction.rarefactionSubparser(subparser)