main file

src/datawave/main.py

@@ -1,91 +1,51 @@
-import argparse
-import pandas as pd
+import get_data
 import json
-import matplotlib.pyplot as plt
+import argparse
 import os
 
+def read_json(file_path):
+    with open(file_path, 'r') as f:
+        field_name_dict = json.load(f)
+    return dict(field_name_dict)
 
-# def load_data(file_path):
-#     # Assuming the input data file is a CSV for simplicity
-#     return pd.read_csv(file_path)
-#
-#
-# def perform_analysis(data, analysis_config, output_prefix):
-#     # Example: Perform some analysis on the data based on the config
-#     result = data.describe()  # Simple analysis: describe data
-#
-#     # Save results to CSV
-#     result_csv = f"{output_prefix}_derived_file.csv"
-#     result.to_csv(result_csv)
-#     return result_csv
-#
-#
-# def create_plots(data, output_prefix):
-#     # Example: Create and save plots
-#     sample_plot = f"{output_prefix}_sample_plot.png"
-#     analysis_plot = f"{output_prefix}_analysis_plot.png"
-#
-#     plt.figure()
-#     data.plot()
-#     plt.title('Sample Plot')
-#     plt.savefig(sample_plot)
-#
-#     plt.figure()
-#     data.hist()
-#     plt.title('Analysis Plot')
-#     plt.savefig(analysis_plot)
-#
-#     return sample_plot, analysis_plot
-#
-#
-# def main():
-#     parser = argparse.ArgumentParser(description='Data retrieval and analysis.')
-#     parser.add_argument('-i', '--input', action='append', required=True, help='Input files.')
-#     args = parser.parse_args()
-#
-#     # Input files
-#     data_file = None
-#     python_file = None
-#     json_file = None
-#
-#     for file_path in args.input:
-#         if file_path.endswith('.csv'):
-#             data_file = file_path
-#         elif file_path.endswith('.py'):
-#             python_file = file_path
-#         elif file_path.endswith('.json'):
-#             json_file = file_path
-#
-#     if not data_file or not python_file or not json_file:
-#         raise ValueError("Missing required input files.")
-#
-#     # Load JSON configuration
-#     with open(json_file, 'r') as f:
-#         config = json.load(f)
-#
-#     # Create an output directory
-#     output_dir = 'output'
-#     os.makedirs(output_dir, exist_ok=True)
-#
-#     # Set the output file prefix
-#     output_prefix = os.path.join(output_dir, os.path.splitext(os.path.basename(data_file))[0])
-#
-#     # Load and process data
-#     data = load_data(data_file)
-#
-#     # Perform analysis
-#     derived_file = perform_analysis(data, config, output_prefix)
-#
-#     # Create and save plots
-#     sample_plot, analysis_plot = create_plots(data, output_prefix)
-#
-#     # Return paths of the created files
-#     print(f"Derived file: {derived_file}")
-#     print(f"Sample plot: {sample_plot}")
-#     print(f"Analysis plot: {analysis_plot}")
-#
+
+parser = argparse.ArgumentParser(description='Data retrieval and analysis.')
+
+# Separate flags for each type of input
+parser.add_argument('--data-file', '-d', required=True, help='File name to the data file (e.g., .mat, .nwb, .txt).')
+parser.add_argument('--python-file', '-p', required=True, help='File name to the Python file for custom processing.')
+parser.add_argument('--json-file', '-j', required=True, help='File name to the JSON configuration file.')
+parser.add_argument('--filepath', '-f', required=True, help='Path for additional use.')
+
+args = parser.parse_args()
+
+# Input files
+data_file = args.data_file
+python_file = args.python_file
+json_file = args.json_file
+f_path = args.filepath
+
+supported_ext = ["mat", "nwb", "csv", "txt", "adicht", "rhd"]
+
+# Extract the file extension
+data_file_ext = os.path.splitext(data_file)[1].lower()
+
+# Ensure data file has a supported extension
+if data_file_ext not in supported_ext:
+    raise ValueError(f"Unsupported data file extension: {data_file_ext}")
+
+field_name_dict = read_json(os.path.join(json_file, f_path))
+get_final_df = get_data.run(data_file_ext, data_file, field_name_dict, f_path)
+
+# # Create an output directory
+# output_dir = 'output'
+# os.makedirs(output_dir, exist_ok=True)
 #
-# if __name__ == '__main__':
-#     main()
+# # Set the output file prefix
+# output_prefix = os.path.join(output_dir, os.path.splitext(os.path.basename(data_file))[0])
+
+# Save the DataFrame to a CSV file
+csv_file_path = f"derived_file.csv"
+get_final_df.to_csv(csv_file_path, index=False)
 
-print("hello world")
+print("files saved successfully")