def __init__(self, csv_file_name):
cols = InOutSupport.read_csv_cols(file_name=csv_file_name,
n_cols=3,
if_ignore_first_row=True,
if_convert_float=True)
self._cohortIDs = cols[CalibrationColIndex.ID.value].astype(int)
self._weights = cols[CalibrationColIndex.W.value]
self._survivalProbs = cols[CalibrationColIndex.SURVIVAL_PROB.value]
self._multiCohorts = None
def __init__(self, csv_file_name):
# read the columns of the generated csv file containing the calibration results
cols = InOutSupport.read_csv_cols(file_name=csv_file_name,
n_cols=3,
if_ignore_first_row=True,
if_convert_float=True)
# store cohort IDs, likelihood weights, and mortality probabilities
self._cohortIDs = cols[CalibrationColIndex.ID.value].astype(int)
self._weights = cols[CalibrationColIndex.W.value]
self._mortalityProbs = cols[CalibrationColIndex.MORT_PROB.value]
self._multiCohorts = None
def __init__(self, csv_file_name):
""" extracts seeds, mortality probabilities and the associated likelihood from
the csv file where the calibration results are stored
:param cvs_file_name: name of the csv file where the calibrated results are stored
"""
# read the columns of the csv files containing the calibration results
cols = InOutSupport.read_csv_cols(file_name=csv_file_name, n_cols = 3,
if_ignore_first_row=True,
if_convert_float=True)
# store likelihood weights, cohort IDs and sampled mortality probabilities
self._cohortIDs = cols[CalibrationColIndex.ID.value].astype(int)
self._weights = cols[CalibrationColIndex.W.value]
self._mortality = cols[CalibrationColIndex.MORT_PROB.value]
self._multiCohorts = None
def __init__(self, cvs_file_name, drug_effectiveness_ratio=1):
""" extracts seeds, mortality probabilities and the associated likelihood from
the csv file where the calibration results are stored
:param cvs_file_name: name of the csv file where the calibrated results are stored
:param calibrated_model_with_drug: calibrated model simulated when drug is available
"""
# read the columns of the csv files containing the calibration results
cols = InOutSupport.read_csv_cols(file_name=cvs_file_name,
n_cols=3,
if_ignore_first_row=True,
if_convert_float=True)
# store likelihood weights, cohort IDs and sampled mortality probabilities
self._cohortIDs = cols[CalibrationColIndex.ID.value].astype(int)
self._weights = cols[CalibrationColIndex.W.value]
self._mortalityProbs = cols[
CalibrationColIndex.MORT_PROB.value] * drug_effectiveness_ratio
self._multiCohorts = None # multi-cohort
from scr import InOutFunctions as InOutSupport
# test reading by rows
rows = InOutSupport.read_csv_rows('myCSV',
if_del_first_row=True,
if_convert_float=True)
print('Testing reading by rows:')
for row in rows:
print(sum(row))
# test reading by columns
cols = InOutSupport.read_csv_cols('myCSV',
n_cols=3,
if_ignore_first_row=True,
if_convert_float=True)
print('Testing reading by columns:')
for j in range(0, 3):
print(sum(cols[j]))
