feat: ✨ working on timefile

2025-11-10 20:19:03 +00:00
parent 0259da7eaa
commit 88146c08b1
6 changed files with 218 additions and 46 deletions
@@ -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()