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Remove/replace def load_parameters(flag_type) with steps.utils.load_project_yaml_files(.). This is to have a more centralized treatment of yaml files inside the data chain.

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florez_j
2025-03-10 11:38:51 +01:00
parent cf073126b9
commit ecdf3687ba
1 changed files with 5 additions and 33 deletions
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38
pipelines/steps/generate_flags.py
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@ -28,43 +28,13 @@ import dima.src.hdf5_ops as dataOps
import pipelines.steps.utils as stepUtils import pipelines.steps.utils as stepUtils
import dima.utils.g5505_utils as utils import dima.utils.g5505_utils as utils
import json import json
from pipelines.steps.utils import load_project_yaml_files
def compute_cpc_flags(): def compute_cpc_flags():
# TODO: ask rob where to find this information. # TODO: ask rob where to find this information.
return 0 return 0
def load_parameters(flag_type):
# Implicit input
if flag_type == 'diagnostics':
flag_type_file = os.path.normpath(os.path.join(projectPath,'pipelines/params/validity_thresholds.yaml'))
error_message = f"Error accessing validation thresholds at: {flag_type_file}"
elif flag_type == 'species':
flag_type_file = os.path.normpath(os.path.join(projectPath,'pipelines/params/calibration_params.yaml'))
error_message = f"Error accessing calibration parameters at: {flag_type_file}"
output_dict = {}
try:
with open(flag_type_file, 'r') as stream:
output_dict = yaml.load(stream, Loader=yaml.FullLoader)
except Exception as e:
print(error_message)
return {}
# Get name of the specifies to flag based on diagnostics and manual flags
#path_to_calib_params = os.path.normpath(os.path.join(projectPath,'pipelines/params/calibration_params.yaml'))
#if not os.path.exists(path_to_calib_params):
# raise FileNotFoundError(f'Calibration params file:{path_to_calib_params}')
#with open(path_to_calib_params,'r') as stream:
# calib_param_dict = yaml.safe_load(stream)
return output_dict
#def compute_diagnostic_variable_flags(data_table, validity_thresholds_dict): #def compute_diagnostic_variable_flags(data_table, validity_thresholds_dict):
def generate_diagnostic_flags(data_table, validity_thresholds_dict): def generate_diagnostic_flags(data_table, validity_thresholds_dict):
""" """
@ -390,11 +360,13 @@ if __name__ == '__main__':
# Compute diagnostic flags based on validity thresholds defined in configuration_file_dict # Compute diagnostic flags based on validity thresholds defined in configuration_file_dict
if flag_type == 'diagnostics': if flag_type == 'diagnostics':
validity_thresholds_dict = load_parameters(flag_type) #validity_thresholds_dict = load_parameters(flag_type)
validity_thresholds_dict = load_project_yaml_files(projectPath, "validity_thresholds.yaml")
flags_table = generate_diagnostic_flags(data_table, validity_thresholds_dict) flags_table = generate_diagnostic_flags(data_table, validity_thresholds_dict)
if flag_type == 'species': if flag_type == 'species':
calib_param_dict = load_parameters(flag_type) #calib_param_dict = load_parameters(flag_type)
calib_param_dict = load_project_yaml_files(projectPath, "calibration_params.yaml")
flags_table = generate_species_flags(data_table,calib_param_dict) flags_table = generate_species_flags(data_table,calib_param_dict)
metadata = {'actris_level' : 1, metadata = {'actris_level' : 1,