"""Convert simple commented-header .dat files (Ahmed Body, Faith Hill PIV/PSP/FISF formats) to flat CSV. Different from the NASA Tecplot zone parser (Extended_2D_Dataset/dat_to_csv.py). These .dat files are: - Header: any number of '#'-prefixed lines - The last '#' line contains the column names, possibly with units in brackets - Data: whitespace-separated floats, one row per measurement point Usage: python commented_dat_to_csv.py [ ...] """ import sys import os import re import glob import numpy as np import pandas as pd # Match e.g. "x[mm]" or "U[m/s]" -> capture name and unit _NAMED_UNIT_RE = re.compile(r'(\S+?)\[([^\]]+)\]') def _parse_columns_from_header_line(line): """Parse a header line like '# x[mm] y[mm] z[mm] U[m/s] ...' -> list of column names. Spatial coords gain a unit suffix ("x_mm", "y_in", "z_m") so downstream tooling can map experiment coords to the OF mesh scale unambiguously. Non-spatial columns retain their original names. """ s = line.lstrip('#').strip() out = [] for tok in s.split(): m = _NAMED_UNIT_RE.match(tok) if not m: out.append(tok) continue name, unit = m.group(1), m.group(2).strip() # only attach unit suffix to spatial coordinate columns if name.lower() in ('x', 'y', 'z') and unit in ('mm', 'm', 'in', 'cm'): out.append(f'{name}_{unit}') else: out.append(name) return out def read_commented_dat(path): """Read a commented-header .dat file -> pandas DataFrame. The last header line beginning with '#' is treated as the column-name line. All other '#' lines are skipped. Data rows are whitespace-separated floats. """ with open(path) as f: lines = f.readlines() last_header_idx = -1 for i, line in enumerate(lines): if line.lstrip().startswith('#'): last_header_idx = i else: if line.strip(): break if last_header_idx < 0: raise ValueError(f'{path}: no commented header found') columns = _parse_columns_from_header_line(lines[last_header_idx]) data = np.genfromtxt(path, comments='#') if data.ndim == 1: data = data.reshape(1, -1) if data.shape[1] != len(columns): # Some files have variables labeled with extra '*' or unusual chars; # fall back to generic col_N names if mismatch columns = [f'col_{i}' for i in range(data.shape[1])] return pd.DataFrame(data, columns=columns) def convert_path(path): if os.path.isdir(path): for dat in sorted(glob.glob(os.path.join(path, '*.dat'))): convert_path(dat) return if not path.lower().endswith('.dat'): return try: df = read_commented_dat(path) except Exception as exc: print(f' FAILED {path}: {exc}') return csv_path = path[:-4] + '.csv' df.to_csv(csv_path, index=False) print(f' {os.path.basename(path)} -> {os.path.basename(csv_path)}' f' ({len(df)} rows, {len(df.columns)} cols)') if __name__ == '__main__': if len(sys.argv) < 2: print(__doc__) sys.exit(1) for arg in sys.argv[1:]: print(f'\n[{arg}]') convert_path(arg)