def core_model_test(base_dir, mapping_table, taxa_level, output_dir):
""" Tests the core model
Inputs:
base_dir: base common directory of all mapping files
mapping_table: dictionary with the mapping table information
output_dir: output directory
"""
profiles = get_profiles_list(base_dir, mapping_table, taxa_level)
# Bootstrap profiles to get the results
profile, mean, stdev, ci = bootstrap_profiles(normalize_profiles(profiles))
# Write the bootstrapped profile
profile_fp = join(output_dir, 'core_model_profile.txt')
write_profile(profile, profile_fp)
# Write the test result
output_fp = join(output_dir, 'core_model_result.txt')
outf = open(output_fp, 'w')
outf.write("Results for the core model test:\n")
outf.write("Microbiome model: ")
if profile['not_shared'] < 0.5:
outf.write("Substantial core.\n")
elif profile['not_shared'] < 1.0:
outf.write("Minimal core.\n")
else:
outf.write('No core\n')
outf.write("\nStatistical results (amount shared):\n")
outf.write("Mean: %f %%\n" % (mean * 100))
outf.write("Standard deviation: %f %%\n" % (stdev * 100))
outf.write("Confidence interval for the mean: [%f %%, %f %%]\n"
% ((ci[0] * 100), (ci[1] * 100)))
def test_bootstrap_profiles(self):
randfunc = lambda : 1
obs_prof, obs_mean, obs_stdev, obs_ci = \
bootstrap_profiles(self.profiles_list, randfunc = randfunc)
exp_prof = {'taxa1': (0.10),'taxa2': (0.22),
'taxa3': (0.15),'taxa4': (0.25)}
def core_model_test(base_dir, mapping_table, taxa_level, output_dir):
""" Tests the core model
Inputs:
base_dir: base common directory of all mapping files
mapping_table: dictionary with the mapping table information
output_dir: output directory
"""
profiles = get_profiles_list(base_dir, mapping_table, taxa_level)
# Bootstrap profiles to get the results
profile, mean, stdev, ci = bootstrap_profiles(normalize_profiles(profiles))
# Write the bootstrapped profile
profile_fp = join(output_dir, 'core_model_profile.txt')
write_profile(profile, profile_fp)
# Write the test result
output_fp = join(output_dir, 'core_model_result.txt')
outf = open(output_fp, 'w')
outf.write("Results for the core model test:\n")
outf.write("Microbiome model: ")
if profile['not_shared'] < 0.5:
outf.write("Substantial core.\n")
elif profile['not_shared'] < 1.0:
outf.write("Minimal core.\n")
else:
outf.write('No core\n')
outf.write("\nStatistical results (amount shared):\n")
outf.write("Mean: %f %%\n" % (mean * 100))
outf.write("Standard deviation: %f %%\n" % (stdev * 100))
outf.write("Confidence interval for the mean: [%f %%, %f %%]\n" %
((ci[0] * 100), (ci[1] * 100)))
def test_bootstrap_profiles(self):
randfunc = lambda: 1
obs_prof, obs_mean, obs_stdev, obs_ci = \
bootstrap_profiles(self.profiles_list, randfunc = randfunc)
exp_prof = {
'taxa1': (0.10),
'taxa2': (0.22),
'taxa3': (0.15),
'taxa4': (0.25)
}
