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feat: ✨ working on timefile

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Jake Pullen
2025-11-10 20:19:03 +00:00
parent 0259da7eaa
commit 88146c08b1
6 changed files with 218 additions and 46 deletions
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NIMROD_timeseries_cleaned.py
+89
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@@ -0,0 +1,89 @@
from __future__ import division, print_function
import numpy as np
import glob
# Configuration
asc_path = "asc_files/"
asc_wildcard_file = "*.asc"
asc_mult_source = asc_path + asc_wildcard_file
five_min_rainfall_spatial_timeseries_name = 'timeseries_data.txt'
things = [
# loc name, loc id, x loc, y loc, resolution
[1725 , 2175 , 608500 , 216500 , 1000 , -1 ], # 'BRICSC', 'TM0816'
[1725 , 2175 , 568500 , 342500 , 1000 , -1 ], # 'HEACSC', 'TF6842'
[1725.0, 2175.0, -404500.0, -624500.0, 1000.0, -1.0]# example
]
def read_ascii_header(ascii_raster_file):
"""Reads header information from an ASCII DEM"""
with open(ascii_raster_file) as f:
header_data = [float(f.__next__().split()[1]) for x in range(6)]
return header_data
def calculate_crop_coords(basin_header, radar_header):
"""Calculate crop coordinates based on header data"""
y0_radar = radar_header[3]
x0_radar = radar_header[2]
y0_basin = basin_header[3]
x0_basin = basin_header[2]
nrows_radar = radar_header[1]
nrows_basin = basin_header[1]
ncols_basin = basin_header[0]
cellres_radar = radar_header[4]
cellres_basin = basin_header[4]
xp = x0_basin - x0_radar
yp = y0_basin - y0_radar
xpp = ncols_basin * cellres_basin
ypp = nrows_basin * cellres_basin
start_col = np.floor( xp / cellres_radar )
end_col = np.ceil( (xpp + xp) / cellres_radar )
start_row = np.floor(nrows_radar - ( (yp + ypp)/cellres_radar ))
end_row = np.ceil(nrows_radar - (yp/cellres_radar))
print(start_col, start_row, end_col, end_row)
return int(start_col), int(start_row), int(end_col), int(end_row)
def extract_cropped_rain_data():
"""Extract cropped rain data and create rainfall timeseries"""
rainfile = []
#basin_header = read_ascii_header(basinsource)
basin_header = things[0] # just BRICSC for now
for f in glob.iglob(asc_mult_source):
print(f)
radar_header = read_ascii_header(f)
# print(radar_header)
start_col, start_row, end_col, end_row = calculate_crop_coords(basin_header, radar_header)
start_col = int(round(start_col))
start_row = int(round(start_row) )
end_col = int(round(end_col) )
end_row = int(round(end_row) )
cur_rawgrid = np.genfromtxt(f, skip_header=6, filling_values=0.0, loose=True, invalid_raise=False)
cur_croppedrain = cur_rawgrid[start_row:end_row, start_col:end_col]
print(cur_croppedrain)
# Flatten the cropped rain data into a 1D array
cur_rainrow = cur_croppedrain.flatten()
print(cur_rainrow)
rainfile.append(cur_rainrow)
rainfile_arr = np.vstack(rainfile)
np.savetxt(five_min_rainfall_spatial_timeseries_name, rainfile_arr, delimiter=' ', fmt='%1.1f')
if __name__ == '__main__':
extract_cropped_rain_data()
batch_nimrod.py
+16 -25
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@@ -4,6 +4,7 @@ from pathlib import Path
import re
import logging
import yaml
import time
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
@@ -14,11 +15,11 @@ BOUNDING_BOX_INFO = {
"WINTSC": (499000, 500000, 416000, 417000),
}
# TODO: The dat files im fairly sure are duplicated as it is the whole uk area, not area specific. need to change it
IN_TOP_FOLDER = "./dat_files"
OUT_TOP_FOLDER = "./asc_files"
CONFIG_FILE = "config.yaml"
def get_datetime(file_name: str) -> str:
"""
Extract datetime from a filename using regex pattern matching.
@@ -72,38 +73,24 @@ def process_nimrod_files() -> None:
This function reads all files from IN_TOP_FOLDER, applies the appropriate bounding
box for each area, and exports clipped raster data to OUT_TOP_FOLDER.
"""
# Load configuration
bounding_box_info = load_config()
# Read all file names in the folder
files_to_process = [f for f in os.listdir(Path(IN_TOP_FOLDER))]
# Use default if config is empty
if not bounding_box_info:
bounding_box_info = {
"BRISCS": (607000, 608000, 217000, 218000),
"WINTSC": (499000, 500000, 416000, 417000),
}
logging.info(f"Processing {len(files_to_process)} files...")
# read all file names in the folder
area_folders = os.listdir(IN_TOP_FOLDER)
os.makedirs(Path(OUT_TOP_FOLDER), exist_ok=True)
for area in area_folders:
bounding_box = bounding_box_info.get(area, (0, 0, 0, 0))
logging.info(f"Processing area: {area}, bounding box: {bounding_box}")
xmin, xmax, ymin, ymax = bounding_box
os.makedirs(Path(OUT_TOP_FOLDER, area), exist_ok=True)
for in_file in os.listdir(Path(IN_TOP_FOLDER, area)):
for in_file in os.listdir(Path(IN_TOP_FOLDER)):
timestamp = get_datetime(in_file)
out_file_name = f"{timestamp}_{area}.asc"
out_file_path = Path(OUT_TOP_FOLDER, area, out_file_name)
in_file_full = Path(IN_TOP_FOLDER, area, in_file)
out_file_name = f"{timestamp}.asc"
out_file_path = Path(OUT_TOP_FOLDER, out_file_name)
in_file_full = Path(IN_TOP_FOLDER, in_file)
try:
image = Nimrod(open(in_file_full, "rb"))
image.apply_bbox(xmin, xmax, ymin, ymax)
# image.query() # prints out file_details
with open(out_file_path, "w") as outfile:
image.extract_asc(outfile)
logging.info(f"Successfully processed: {in_file_full}")
#logging.info(f"Successfully processed: {in_file_full}")
except Nimrod.HeaderReadError as e:
logging.error(f"Failed to read file {in_file_full}, is it corrupt?")
@@ -115,7 +102,7 @@ def process_nimrod_files() -> None:
continue
except Nimrod.BboxRangeError as e:
logging.error(
f"Bounding Box out of range. Given bounding box: {bounding_box}"
"Bounding Box out of range. Given bounding box: {bounding_box}"
)
logging.error(e)
# Skips the whole area as bounding box will be out of bounds for all files
@@ -123,4 +110,8 @@ def process_nimrod_files() -> None:
if __name__ == "__main__":
start = time.time()
process_nimrod_files()
end = time.time()
elapsed_time = end - start
logging.info(f"Processing completed in {elapsed_time:.2f} seconds")
pyproject.toml
+1
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@@ -5,6 +5,7 @@ description = "Convert .dat nimrod files to .asc files"
readme = "README.md"
requires-python = ">=3.12"
dependencies = [
"numpy>=2.3.4",
"pyyaml>=6.0.3",
"ruff>=0.14.3",
]
rainfile_5min.txt
+13
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@@ -0,0 +1,13 @@
timeseries_data.txt
+13
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@@ -0,0 +1,13 @@
uv.lock
Generated
+65
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@@ -7,16 +7,81 @@ name = "met-office"
version = "1.0.0"
source = { virtual = "." }
dependencies = [
{ name = "numpy" },
{ name = "pyyaml" },
{ name = "ruff" },
]
[package.metadata]
requires-dist = [
{ name = "numpy", specifier = ">=2.3.4" },
{ name = "pyyaml", specifier = ">=6.0.3" },
{ name = "ruff", specifier = ">=0.14.3" },
]
[[package]]
name = "numpy"
version = "2.3.4"
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