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