1import re 2import pandas as pd 3from pathlib import Path 4 5# Regex to parse STDOUT of the navierstokes run 6logreg = re.compile( 7 r".*(?:^Degree of FEM Space: (\d+)).*(?:^Global FEM nodes: (\d{2,})).*(?:^dm_plex_box_faces: (\S+)).*(?:^Time taken for solution: (\d*\.?\d+)).*(?:^Relative Error: (\d*\.?\d+))", 8 re.DOTALL | re.MULTILINE, 9) 10 11 12def parseFile(file): 13 """Returns dictionary of parsed logfile contents. 14 15 Parameters 16 ---------- 17 file : Path-like object 18 Path to the file to be parsed. 19 20 Returns 21 ------- 22 dict 23 Values of "dofs", "time", "error", "degree", and "box_faces"' 24 """ 25 26 values = {} 27 with file.open() as filer: 28 filestring = filer.read() 29 match = logreg.match(filestring) 30 values["degree"] = match[1] 31 values["dofs"] = match[2] 32 box_faceStr = match[3] 33 values["time"] = match[4] 34 values["error"] = match[5] 35 36 # Splitting box_face argument str into individual entries 37 box_faceList = box_faceStr.split(",") 38 for i, box_face in enumerate(box_faceList): 39 values["box_face" + str(i)] = box_face 40 41 return values 42 43 44if __name__ == "__main__": 45 # Directory location of log files 46 runlogDir = Path("./") 47 48 results = pd.DataFrame() 49 for file in runlogDir.glob("*.log"): 50 values = parseFile(file) 51 results = results.append(values, ignore_index=True) 52 53 # Convert string values to numeric type 54 results = results.apply(lambda col: pd.to_numeric(col, errors="coerce")) 55