def test_get_simsam_rep_num(self):
"""Test getting number of necessary simsam reps."""
obs = get_simsam_rep_num(42, 13)
self.assertEqual(obs, 4)
obs = get_simsam_rep_num(50, 10)
self.assertEqual(obs, 5)
self.assertRaises(ValueError, get_simsam_rep_num, 42, 42)
def _build_simulated_data_commands(analysis_type, out_dir, even_otu_table_fp,
map_fp, tree_fp, workflow):
cmds = []
data_type_dir = join(out_dir, 'simulated')
create_dir(data_type_dir)
num_samps = get_num_samples_in_table(even_otu_table_fp)
for category in workflow['categories']:
category_dir = join(data_type_dir, category[0])
create_dir(category_dir)
for trial_num in range(workflow['num_sim_data_trials']):
trial_num_dir = join(category_dir, '%d' % trial_num)
create_dir(trial_num_dir)
for samp_size in workflow['sample_sizes']:
samp_size_dir = join(trial_num_dir, '%d' % samp_size)
create_dir(samp_size_dir)
# Lots of duplicate code between these two blocks...
# need to refactor and test.
if samp_size <= num_samps:
simsam_rep_num = 1
subset_otu_table_fp = join(samp_size_dir, basename(even_otu_table_fp))
subset_map_fp = join(samp_size_dir, basename(map_fp))
if not has_results(samp_size_dir, required_files=[basename(subset_otu_table_fp), basename(subset_map_fp)]):
run_command('choose_data_subset.py -t %s -i %s -m %s -c %s -n %d -o %s' % (analysis_type, even_otu_table_fp, map_fp, category[0], samp_size, samp_size_dir))
assert get_num_samples_in_table(subset_otu_table_fp) == samp_size
assert get_num_samples_in_map(subset_map_fp) == samp_size
for d in workflow['dissim']:
dissim_dir = join(samp_size_dir, repr(d))
create_dir(dissim_dir)
simsam_map_fp = join(dissim_dir, add_filename_suffix(subset_map_fp, '_n%d_d%r' % (simsam_rep_num, d)))
simsam_otu_table_fp = join(dissim_dir, add_filename_suffix(subset_otu_table_fp, '_n%d_d%r' % (simsam_rep_num, d)))
# Check for simulated table/map and various
# distance matrices / coordinates files.
required_simsam_files = [basename(simsam_map_fp), basename(simsam_otu_table_fp)]
has_simsam_files = has_results(dissim_dir, required_files=required_simsam_files)
has_metric_files = True
for metric in workflow['metrics']:
required_metric_files = ['dm.txt', 'map.txt', 'pc.txt']
if analysis_type == 'gradient':
required_metric_files.append('%s_dm.txt' % category[0])
metric_dir = join(dissim_dir, metric[0])
has_metric_files = has_results(metric_dir, required_metric_files)
if not has_metric_files:
break
if not (has_simsam_files and has_metric_files):
cmd = ['simsam.py -i %s -t %s -o %s -d %r -n %d -m %s' % (subset_otu_table_fp, tree_fp, dissim_dir, d, simsam_rep_num, subset_map_fp)]
for metric in workflow['metrics']:
metric_dir = join(dissim_dir, metric[0])
create_dir(metric_dir)
if analysis_type == 'gradient':
cmd.append('distance_matrix_from_mapping.py -i %s -c %s -o %s' % (simsam_map_fp, category[0], join(metric_dir, '%s_dm.txt' % category[0])))
cmd.append('beta_diversity.py -i %s -o %s -m %s -t %s' % (simsam_otu_table_fp, metric_dir, metric[0], tree_fp))
cmd.append('mv %s %s' % (join(metric_dir, '%s_%s.txt' % (metric[0], splitext(basename(simsam_otu_table_fp))[0])), join(metric_dir, 'dm.txt')))
cmd.append('cp %s %s' % (simsam_map_fp, join(metric_dir, 'map.txt')))
cmd.append('principal_coordinates.py -i %s -o %s' % (join(metric_dir, 'dm.txt'), join(metric_dir, 'pc.txt')))
cmds.append(' && '.join(cmd))
else:
# We need to simulate more samples than we originally have.
simsam_rep_num = get_simsam_rep_num(samp_size, num_samps)
for d in workflow['dissim']:
dissim_dir = join(samp_size_dir, repr(d))
create_dir(dissim_dir)
simsam_map_fp = join(dissim_dir, add_filename_suffix(map_fp, '_n%d_d%r' % (simsam_rep_num, d)))
simsam_otu_table_fp = join(dissim_dir, add_filename_suffix(even_otu_table_fp, '_n%d_d%r' % (simsam_rep_num, d)))
required_simsam_files = [basename(simsam_map_fp), basename(simsam_otu_table_fp)]
has_simsam_files = has_results(dissim_dir, required_files=required_simsam_files)
required_subset_files = [basename(simsam_map_fp), basename(simsam_otu_table_fp)]
has_subset_files = has_results(join(dissim_dir, 'subset'), required_files=required_subset_files)
has_metric_files = True
for metric in workflow['metrics']:
required_metric_files = ['dm.txt', 'map.txt', 'pc.txt']
if analysis_type == 'gradient':
required_metric_files.append('%s_dm.txt' % category[0])
metric_dir = join(dissim_dir, metric[0])
has_metric_files = has_results(metric_dir, required_metric_files)
if not has_metric_files:
break
if not (has_simsam_files and has_subset_files and has_metric_files):
cmd = ['simsam.py -i %s -t %s -o %s -d %r -n %d -m %s' % (even_otu_table_fp, tree_fp, dissim_dir, d, simsam_rep_num, map_fp)]
subset_dir = join(dissim_dir, 'subset')
cmd.append('choose_data_subset.py -t %s -i %s -m %s -c %s -n %d -o %s' % (analysis_type, simsam_otu_table_fp, simsam_map_fp, category[0], samp_size, subset_dir))
subset_otu_table_fp = join(subset_dir, basename(simsam_otu_table_fp))
subset_map_fp = join(subset_dir, basename(simsam_map_fp))
for metric in workflow['metrics']:
metric_dir = join(dissim_dir, metric[0])
create_dir(metric_dir)
if analysis_type == 'gradient':
cmd.append('distance_matrix_from_mapping.py -i %s -c %s -o %s' % (subset_map_fp, category[0], join(metric_dir, '%s_dm.txt' % category[0])))
cmd.append('beta_diversity.py -i %s -o %s -m %s -t %s' % (subset_otu_table_fp, metric_dir, metric[0], tree_fp))
cmd.append('mv %s %s' % (join(metric_dir, '%s_%s.txt' % (metric[0], splitext(basename(subset_otu_table_fp))[0])), join(metric_dir, 'dm.txt')))
cmd.append('cp %s %s' % (subset_map_fp, join(metric_dir, 'map.txt')))
cmd.append('principal_coordinates.py -i %s -o %s' % (join(metric_dir, 'dm.txt'), join(metric_dir, 'pc.txt')))
cmds.append(' && '.join(cmd))
return cmds
