def main():
here = os.path.dirname(os.path.realpath(__file__))
input_path_tecrdb = os.path.join(here, INPUT_PATH_TECRDB)
input_path_compounds = os.path.join(here, INPUT_PATH_COMPOUNDS)
input_path_microspecies = os.path.join(here, INPUT_PATH_MICROSPECIES)
tecrdb = pd.read_csv(input_path_tecrdb, index_col=0).loc[filter_tecrdb]
stoichiometry = get_stoichiometry(tecrdb)
cids = stoichiometry['compound_id'].unique()
rids = stoichiometry['reaction_id'].unique()
compounds = (
pd.read_csv(input_path_compounds, index_col=0)
.loc[lambda df: df['compound_id'].isin(cids)]
)
microspecies = (
pd.read_csv(input_path_microspecies, index_col=0)
.loc[lambda df: df['compound_id'].isin(cids)]
)
pkas, pkmgs = (
microspecies
.groupby(['compound_id', n])[[pk, "name"]].first()
.dropna()
.reset_index()
for n, pk in [('nh', 'pka'), ('nmg', 'pkmg')]
)
stan_codes = get_stan_codes(stoichiometry)
stan_input = get_stan_input(
tecrdb, stoichiometry, microspecies, compounds, pkas, pkmgs, stan_codes
)
pkas.to_csv(os.path.join(here, OUTPUT_PATH_PKAS))
compounds.to_csv(os.path.join(here, OUTPUT_PATH_COMPOUNDS))
tecrdb.to_csv(os.path.join(here, OUTPUT_PATH_TECRDB))
jsondump(os.path.join(here, OUTPUT_PATH_STAN_CODES), stan_codes)
jsondump(os.path.join(here, OUTPUT_PATH_JSON), stan_input)
rdump(os.path.join(here, OUTPUT_PATH_R), stan_input)
def test_roundtrip_metric(self):
dfile = os.path.join(DATAFILES_PATH, 'metric_diag.data.R')
data_dict_1 = rload(dfile)
self.assertEqual(data_dict_1['inv_metric'].shape, (3,))
dfile_tmp = os.path.join(DATAFILES_PATH, 'tmp.data.R')
rdump(dfile_tmp, data_dict_1)
data_dict_2 = rload(dfile_tmp)
self.assertTrue('inv_metric' in data_dict_2)
for i, x in enumerate(data_dict_2['inv_metric']):
self.assertEqual(x, data_dict_2['inv_metric'][i])
os.remove(dfile_tmp)
def write_rdump(self, dict: Dict) -> None:
rdump(self._data_file, dict)