1# Copyright (c) 2017, Lawrence Livermore National Security, LLC. 2# Produced at the Lawrence Livermore National Laboratory. LLNL-CODE-734707. 3# All Rights reserved. See files LICENSE and NOTICE for details. 4# 5# This file is part of CEED, a collection of benchmarks, miniapps, software 6# libraries and APIs for efficient high-order finite element and spectral 7# element discretizations for exascale applications. For more information and 8# source code availability see http://github.com/ceed 9# 10# The CEED research is supported by the Exascale Computing Project 17-SC-20-SC, 11# a collaborative effort of two U.S. Department of Energy organizations (Office 12# of Science and the National Nuclear Security Administration) responsible for 13# the planning and preparation of a capable exascale ecosystem, including 14# software, applications, hardware, advanced system engineering and early 15# testbed platforms, in support of the nation's exascale computing imperative. 16 17import re 18import pandas as pd 19from pathlib import Path 20 21# Regex to parse STDOUT of the navierstokes run 22logreg = re.compile( 23 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+))", 24 re.DOTALL | re.MULTILINE, 25) 26 27 28def parseFile(file): 29 """Returns dictionary of parsed logfile contents. 30 31 Parameters 32 ---------- 33 file : Path-like object 34 Path to the file to be parsed. 35 36 Returns 37 ------- 38 dict 39 Values of "dofs", "time", "error", "degree", and "box_faces"' 40 """ 41 42 values = {} 43 with file.open() as filer: 44 filestring = filer.read() 45 match = logreg.match(filestring) 46 values["degree"] = match[1] 47 values["dofs"] = match[2] 48 box_faceStr = match[3] 49 values["time"] = match[4] 50 values["error"] = match[5] 51 52 # Splitting box_face argument str into individual entries 53 box_faceList = box_faceStr.split(",") 54 for i, box_face in enumerate(box_faceList): 55 values["box_face" + str(i)] = box_face 56 57 return values 58 59 60if __name__ == "__main__": 61 # Directory location of log files 62 runlogDir = Path("./") 63 64 results = pd.DataFrame() 65 for file in runlogDir.glob("*.log"): 66 values = parseFile(file) 67 results = results.append(values, ignore_index=True) 68 69 # Convert string values to numeric type 70 results = results.apply(lambda col: pd.to_numeric(col, errors="coerce")) 71