102 lines
3.9 KiB
Python
102 lines
3.9 KiB
Python
import logging
|
|
import time
|
|
import os
|
|
import csv
|
|
import concurrent.futures
|
|
from pathlib import Path
|
|
|
|
from config import Config
|
|
from modules import BatchNimrod, GenerateTimeseries, CombineTimeseries
|
|
|
|
logging.basicConfig(
|
|
level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
|
|
)
|
|
|
|
if __name__ == "__main__":
|
|
os.makedirs(Path(Config.ASC_TOP_FOLDER), exist_ok=True)
|
|
os.makedirs(Path(Config.CSV_TOP_FOLDER), exist_ok=True)
|
|
os.makedirs(Path(Config.COMBINED_FOLDER), exist_ok=True)
|
|
|
|
locations = []
|
|
#load zone inputs here
|
|
for file in os.listdir(Path(Config.ZONE_FOLDER)):
|
|
with open(Path(Config.ZONE_FOLDER,file), 'r') as csvfile:
|
|
reader = csv.reader(csvfile)
|
|
header = next(reader) # Skip header row
|
|
for row in reader:
|
|
# Extract the relevant fields: Ossheet (location ID), Easting, Northing, Zone
|
|
zone_id = row[1] # Ossheet column
|
|
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])
|
|
|
|
batch = BatchNimrod(Config)
|
|
timeseries = GenerateTimeseries(Config)
|
|
combiner = CombineTimeseries(Config, locations)
|
|
|
|
start = time.time()
|
|
logging.info("Starting interleaved processing of DAT files and Timeseries generation")
|
|
|
|
# Initialize results structure
|
|
results = {loc[0]: {'dates': [], 'values': []} for loc in locations}
|
|
|
|
def process_pipeline(dat_file):
|
|
# 1. Process DAT to ASC
|
|
asc_file = batch._process_single_file(dat_file)
|
|
if not asc_file:
|
|
return None
|
|
|
|
# 2. Extract data from ASC
|
|
file_results = timeseries.process_asc_file(asc_file, locations)
|
|
return file_results
|
|
|
|
# Get list of DAT files
|
|
dat_files = [f for f in os.listdir(Path(Config.DAT_TOP_FOLDER)) if not f.startswith('.')]
|
|
total_files = len(dat_files)
|
|
|
|
logging.info(f"Processing {total_files} files concurrently...")
|
|
|
|
with concurrent.futures.ThreadPoolExecutor() as executor:
|
|
future_to_file = {
|
|
executor.submit(process_pipeline, dat_file): dat_file
|
|
for dat_file in dat_files
|
|
}
|
|
|
|
completed_count = 0
|
|
try:
|
|
for future in concurrent.futures.as_completed(future_to_file):
|
|
file_results = future.result()
|
|
if file_results:
|
|
for res in file_results:
|
|
zone_id = res['zone_id']
|
|
results[zone_id]['dates'].append(res['date'])
|
|
results[zone_id]['values'].append(res['value'])
|
|
|
|
completed_count += 1
|
|
if completed_count % 100 == 0:
|
|
elapsed_time = time.time() - start
|
|
files_per_minute = (completed_count / elapsed_time) * 60
|
|
remaining_files = total_files - completed_count
|
|
eta_minutes = remaining_files / (files_per_minute / 60) / 60
|
|
logging.info(f''''Processed {completed_count} out of {total_files} files.
|
|
Speed: {files_per_minute:.2f} files/min. ETA: {eta_minutes:.2f} minutes''')
|
|
except KeyboardInterrupt:
|
|
logging.warning("KeyboardInterrupt received. Cancelling pending tasks...")
|
|
executor.shutdown(wait=False, cancel_futures=True)
|
|
raise
|
|
|
|
elapsed_time = time.time() - start
|
|
logging.info(f"Interleaved processing completed in {elapsed_time:.2f} seconds")
|
|
|
|
logging.info("Writing CSV files...")
|
|
timeseries.write_results_to_csv(results, locations)
|
|
|
|
logging.info("combining CSVs into groups")
|
|
combiner.combine_csv_files()
|
|
logging.info("CSVs combined!")
|
|
end = time.time()
|
|
elapsed_time = end - start
|
|
|
|
logging.info(f"All Complete total time {elapsed_time:.2f} seconds")
|