docs: 📜 Made README clearer

README.MD

@@ -42,10 +42,13 @@ It is recommended to use UV for environment and package handling.
 
 ## Usage
 
-### Main Pipeline (main.py)
+1. Ensure all required packages are installed `uv sync`
-```bash
+1. Adjust the config.py file to match your needs.
-uv run main.py
+1. Ensure your .dat files are in the DAT_TOP_FOLDER (as per config location)
-```
+1. Ensure your zone csv files are in the ZONE_FOLDER (as per config location)
+1. RunMain Pipeline `uv run main.py
+1. find the output in the COMBINED_FOLDER (as per config location)
+
 
 The main pipeline will:
 1. Process DAT files to ASC format if needed
@@ -60,10 +63,15 @@ The `config.py` file defines folder paths:
 - CSV_TOP_FOLDER: "./csv_files"
 - COMBINED_FOLDER: "./combined_files"
 
+Example of how the zone csv files should look:
+```
+filler, zone_name, easting, northing, other_filler, last_filler, zone_number
+aa, TM0816, 608500, 216500, a, a, 1
+aa, TF6842, 568500, 342500, a, a, 1
+```
+
 ## Acknowledgments 
 
-[Richard Thomas - Original Nimrod dat to asc file conversion](https://github.com/richard-thomas/MetOffice_NIMROD)
+Thank you to the following projects for their inspiration and code:  
-[Declan Valters - building the timeseries from the asc files](https://github.com/dvalters/NIMROD-toolbox)
+* [Richard Thomas - Original Nimrod dat to asc file conversion](https://github.com/richard-thomas/MetOffice_NIMROD)  
-
+* [Declan Valters - building the timeseries from the asc files](https://github.com/dvalters/NIMROD-toolbox)
-# Met Office Radar Data
-

main.py

@@ -28,13 +28,8 @@ if __name__ == "__main__":
                 easting = int(row[2])  # Easting column
                 northing = int(row[3])  # Northing column
                 zone = int(row[6])  # ZoneID column
-
                 locations.append([zone_id, easting, northing, zone])
 
-    # # testing locations, can be removed.
-    # locations.append(["TM0816", 608500, 216500, 1])
-    # locations.append(["TF6842", 568500, 342500, 1])
-
     batch = BatchNimrod(Config)
     timeseries = GenerateTimeseries(Config)
     combiner = CombineTimeseries(Config, locations)