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Update to account for yaml file attribute renamings.

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This commit is contained in:
florez_j
2025-02-05 18:15:43 +01:00
parent e2b5aa9d69
commit 2c2b154528
1 changed files with 168 additions and 166 deletions
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14
pipelines/steps/create_flags_for_diagnostic_vars.py
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@ -22,7 +22,7 @@ sys.path.append(dimaPath)
import dima.src.hdf5_ops as dataOps
def create_flags_for_diagnostic_vars(data_table, variable_limits):
def create_flags_for_diagnostic_vars(data_table, validity_thresholds_dict):
"""
Create indicator variables that check whether a particular diagnostic variable is within
pre-specified/acceptable limits, which are defined by `variable_limits`.
@ -47,15 +47,16 @@ def create_flags_for_diagnostic_vars(data_table, variable_limits):
# Loop through the column names in the data table
for diagnostic_variable in data_table.columns:
print(diagnostic_variable)
# Skip if the diagnostic variable is not in variable_limits
if diagnostic_variable not in variable_limits:
print(f'Diagnostic variable {diagnostic_variable} has not defined limits in {variable_limits}.')
if diagnostic_variable not in validity_thresholds_dict['validity_thresholds']['variables']:
print(f'Diagnostic variable {diagnostic_variable} has not defined limits in {validity_thresholds_dict}.')
continue
# Get lower and upper limits for diagnostic_variable from variable limits dict
lower_lim = variable_limits[diagnostic_variable]['lower_lim']['value']
upper_lim = variable_limits[diagnostic_variable]['upper_lim']['value']
variable_ranges = validity_thresholds_dict['validity_thresholds']['variables'][diagnostic_variable]
lower_lim = variable_ranges['lower_lim']
upper_lim = variable_ranges['upper_lim']
# Create an indicator variable for the current diagnostic variable
tmp = data_table[diagnostic_variable]
@ -136,6 +137,7 @@ if __name__ == '__main__':
print('Path to output file :', path_to_calibrated_file)
import dima.utils.g5505_utils as utils
import json
print(calibration_factors.keys())
calibrated_table = create_flags_for_diagnostic_vars(data_table, calibration_factors)
metadata['processing_date'] = utils.created_at()
calibrated_table.to_csv(path_to_calibrated_file, index=False)