# Run seqenv #
cluster.otu_uparse.seqenv.threshold = 1.0
cluster.otu_uparse.seqenv.N = 5000
cluster.otu_uparse.seqenv.run()
# Run seqenv via SLURM #
cluster.run(steps=[{'otu_uparse.seqenv.run': {}}])
cluster.run_slurm(steps=[{'otu_uparse.seqenv.run': {}}], time="04:00:00")
# Check some matrix multiplications #
otu_vs_envo = cluster.otu_uparse.seqenv.base_dir + "centers_N1000_blast_F_ENVO_OTUs_labels.csv"
otu_vs_envo = pandas.io.parsers.read_csv(otu_vs_envo, sep=',', index_col=0, encoding='utf-8')
otu_vs_samples = cluster.otu_uparse.seqenv.base_dir + "abundances.csv"
otu_vs_samples = pandas.io.parsers.read_csv(otu_vs_samples, sep=',', index_col=0, encoding='utf-8')
otu_vs_samples = otu_vs_samples.loc[otu_vs_envo.index]
otu_vs_samples = otu_vs_samples.transpose()
result_us = otu_vs_samples.dot(otu_vs_envo)
result_them = cluster.otu_uparse.seqenv.base_dir + "centers_N1000_blast_F_ENVO_samples_labels.csv"
result_them = pandas.io.parsers.read_csv(result_them, sep=',', index_col=0, encoding='utf-8')
result_them.sum(axis=1)
cluster.otu_uparse.taxonomy_silva.otu_table
###############################################################################
# Print SRA information #
for s in cluster: s.sra.upload_to_sra()
from illumitag.helper.sra import MakeSpreadsheet
make_tsv = MakeSpreadsheet(cluster)
make_tsv.write_bio_tsv()
make_tsv.write_sra_tsv()
