Loading src/scripts/filter_constants.py +2 −3 Original line number Diff line number Diff line Loading @@ -28,7 +28,7 @@ import math import numpy as np import pdb #import pdb from sys import argv ## \cond Loading Loading @@ -64,7 +64,6 @@ def main(): if (len(split_input) == 1): scan_info = scan_single_file(config, split_input[0]) result = scan_info['exit_code'] #breakpoint() if (result == 0): write_output_file(config['output_files'], scan_info) # INFO section Loading Loading @@ -560,6 +559,7 @@ def scan_single_file(config, file_name): # end of while loop input_file.close() if (result['exit_code'] < 0): reason[-1] = 3 result['exit_code'] = 0 result['num_read_lines'] = num_read_lines result['num_orig_data'] = num_orig_data Loading Loading @@ -607,7 +607,6 @@ def match_multiple_files(config): info_arr = np.array(s['reason']) special_ieps.extend(x_arr[info_arr > 1]) # Make a regular grid #breakpoint() num_regular_points = int((x_max - x_min) / (config['step'] * wl_factor)) regular_x = np.linspace(x_min, x_max, num_regular_points) # Get a coarse global X vector Loading Loading
src/scripts/filter_constants.py +2 −3 Original line number Diff line number Diff line Loading @@ -28,7 +28,7 @@ import math import numpy as np import pdb #import pdb from sys import argv ## \cond Loading Loading @@ -64,7 +64,6 @@ def main(): if (len(split_input) == 1): scan_info = scan_single_file(config, split_input[0]) result = scan_info['exit_code'] #breakpoint() if (result == 0): write_output_file(config['output_files'], scan_info) # INFO section Loading Loading @@ -560,6 +559,7 @@ def scan_single_file(config, file_name): # end of while loop input_file.close() if (result['exit_code'] < 0): reason[-1] = 3 result['exit_code'] = 0 result['num_read_lines'] = num_read_lines result['num_orig_data'] = num_orig_data Loading Loading @@ -607,7 +607,6 @@ def match_multiple_files(config): info_arr = np.array(s['reason']) special_ieps.extend(x_arr[info_arr > 1]) # Make a regular grid #breakpoint() num_regular_points = int((x_max - x_min) / (config['step'] * wl_factor)) regular_x = np.linspace(x_min, x_max, num_regular_points) # Get a coarse global X vector Loading