Files
dima/instruments/readers/acsm_flag_reader.py

102 lines
3.7 KiB
Python

import sys
import os
try:
thisFilePath = os.path.abspath(__file__)
except NameError:
print("Error: __file__ is not available. Ensure the script is being run from a file.")
print("[Notice] Path to DIMA package may not be resolved properly.")
thisFilePath = os.getcwd() # Use current directory or specify a default
dimaPath = os.path.normpath(os.path.join(thisFilePath, "..",'..','..')) # Move up to project root
if dimaPath not in sys.path: # Avoid duplicate entries
sys.path.insert(0,dimaPath)
import pandas as pd
import collections
import json
import h5py
import argparse
import logging
import utils.g5505_utils as utils
def read_jsonflag_as_dict(path_to_file):
file_dict = {}
path_tail, path_head = os.path.split(path_to_file)
file_dict['name'] = path_head
# TODO: review this header dictionary, it may not be the best way to represent header data
file_dict['attributes_dict'] = {}
file_dict['datasets'] = []
try:
with open(path_to_file, 'r') as stream:
flag = json.load(stream)#, Loader=json.FullLoader)
except (FileNotFoundError, json.JSONDecodeError) as exc:
print(exc)
dataset = {}
dataset['name'] = 'data_table'#_numerical_variables'
dataset['data'] = utils.convert_attrdict_to_np_structured_array(flag) #df_numerical_attrs.to_numpy()
dataset['shape'] = dataset['data'].shape
dataset['dtype'] = type(dataset['data'])
file_dict['datasets'].append(dataset)
return file_dict
if __name__ == "__main__":
from src.hdf5_ops import save_file_dict_to_hdf5
from utils.g5505_utils import created_at
# Set up argument parsing
parser = argparse.ArgumentParser(description="Data ingestion process to HDF5 files.")
parser.add_argument('dst_file_path', type=str, help="Path to the target HDF5 file.")
parser.add_argument('src_file_path', type=str, help="Relative path to source file to be saved to target HDF5 file.")
parser.add_argument('dst_group_name', type=str, help="Group name '/instFolder/[category]/fileName' in the target HDF5 file.")
args = parser.parse_args()
hdf5_file_path = args.dst_file_path
src_file_path = args.src_file_path
dst_group_name = args.dst_group_name
default_mode = 'r+'
try:
# Read source file and return an internal dictionary representation
idr_dict = read_jsonflag_as_dict(src_file_path)
if not os.path.exists(hdf5_file_path):
default_mode = 'w'
print(f'Opening HDF5 file: {hdf5_file_path} in mode {default_mode}')
with h5py.File(hdf5_file_path, mode=default_mode, track_order=True) as hdf5_file_obj:
try:
# Create group if it does not exist
if dst_group_name not in hdf5_file_obj:
hdf5_file_obj.create_group(dst_group_name)
hdf5_file_obj[dst_group_name].attrs['creation_date'] = created_at().encode('utf-8')
print(f'Created new group: {dst_group_name}')
else:
print(f'Group {dst_group_name} already exists. Proceeding with data transfer...')
except Exception as inst:
logging.error('Failed to create group %s in HDF5: %s', dst_group_name, inst)
# Save dictionary to HDF5
save_file_dict_to_hdf5(hdf5_file_obj, dst_group_name, idr_dict)
print(f'Completed saving file dict with keys: {idr_dict.keys()}')
except Exception as e:
logging.error('File reader failed to process %s: %s', src_file_path, e)
print(f'File reader failed to process {src_file_path}. See logs for details.')