150c0860bSLeila Ghaffari#!/usr/bin/env python3 250c0860bSLeila Ghaffari# Copyright (c) 2017-2018, Lawrence Livermore National Security, LLC. 350c0860bSLeila Ghaffari# Produced at the Lawrence Livermore National Laboratory. LLNL-CODE-734707. 450c0860bSLeila Ghaffari# All Rights reserved. See files LICENSE and NOTICE for details. 550c0860bSLeila Ghaffari# 650c0860bSLeila Ghaffari# This file is part of CEED, a collection of benchmarks, miniapps, software 750c0860bSLeila Ghaffari# libraries and APIs for efficient high-order finite element and spectral 850c0860bSLeila Ghaffari# element discretizations for exascale applications. For more information and 950c0860bSLeila Ghaffari# source code availability see http://github.com/ceed. 1050c0860bSLeila Ghaffari# 1150c0860bSLeila Ghaffari# The CEED research is supported by the Exascale Computing Project 17-SC-20-SC, 1250c0860bSLeila Ghaffari# a collaborative effort of two U.S. Department of Energy organizations (Office 1350c0860bSLeila Ghaffari# of Science and the National Nuclear Security Administration) responsible for 1450c0860bSLeila Ghaffari# the planning and preparation of a capable exascale ecosystem, including 1550c0860bSLeila Ghaffari# software, applications, hardware, advanced system engineering and early 1650c0860bSLeila Ghaffari# testbed platforms, in support of the nation's exascale computing imperative. 1750c0860bSLeila Ghaffari 1850c0860bSLeila Ghaffariimport numpy as np 1950c0860bSLeila Ghaffariimport pandas as pd 204b32fe0cSLeila Ghaffariimport argparse 2150c0860bSLeila Ghaffarifrom pylab import * 2250c0860bSLeila Ghaffarifrom matplotlib import use 2350c0860bSLeila Ghaffari 2450c0860bSLeila Ghaffari 2550c0860bSLeila Ghaffaridef plot(): 264b32fe0cSLeila Ghaffari # Define argparse for the input variables 274b32fe0cSLeila Ghaffari parser = argparse.ArgumentParser(description='Get input arguments') 284b32fe0cSLeila Ghaffari parser.add_argument('--conv_result_file', 294b32fe0cSLeila Ghaffari dest='conv_result_file', 304b32fe0cSLeila Ghaffari type=str, 314b32fe0cSLeila Ghaffari required=True, 324b32fe0cSLeila Ghaffari help='Path to the CSV file') 334b32fe0cSLeila Ghaffari args = parser.parse_args() 344b32fe0cSLeila Ghaffari conv_result_file = args.conv_result_file 354b32fe0cSLeila Ghaffari 3650c0860bSLeila Ghaffari # Load the data 374b32fe0cSLeila Ghaffari runs = pd.read_csv(conv_result_file) 3850c0860bSLeila Ghaffari colors = ['orange', 'red', 'navy', 'green', 'magenta', 3950c0860bSLeila Ghaffari 'gray', 'blue', 'purple', 'pink', 'black'] 4050c0860bSLeila Ghaffari res = 'mesh_res' 4150c0860bSLeila Ghaffari fig, ax = plt.subplots() 4250c0860bSLeila Ghaffari # Arbitrary coefficients 4350c0860bSLeila Ghaffari C = [2.2e-2, .24e0, .22e0, .7e0, 2.5e0, 4450c0860bSLeila Ghaffari 3e0, 3.5e0, 4e0, 4.5e0, 5e0] 4550c0860bSLeila Ghaffari i = 0 4650c0860bSLeila Ghaffari for group in runs.groupby('degree'): 4750c0860bSLeila Ghaffari data = group[1] 4850c0860bSLeila Ghaffari data = data.sort_values('rel_error') 4950c0860bSLeila Ghaffari p = data['degree'].values[0] 5050c0860bSLeila Ghaffari h = 1/data[res] 5150c0860bSLeila Ghaffari H = C[i] * h**p # H = C h^p 5250c0860bSLeila Ghaffari E = data['rel_error'] 5350c0860bSLeila Ghaffari log_h = np.log10(h) 5450c0860bSLeila Ghaffari log_H = np.log10(H) 55*1f814bfdSLeila Ghaffari ax.loglog(h, E, 'o', color=colors[i]) 5650c0860bSLeila Ghaffari m, b = np.polyfit(log_h, log_H, 1) 57*1f814bfdSLeila Ghaffari ax.loglog(h, 10**b * h**m, '--', color=colors[i], label='O(h^' + str(p) + ')') 5850c0860bSLeila Ghaffari i = i + 1 5950c0860bSLeila Ghaffari 6050c0860bSLeila Ghaffari ax.legend(loc='best') 6150c0860bSLeila Ghaffari ax.set_xlabel('h') 6250c0860bSLeila Ghaffari ax.set_ylabel('Relative Error') 6350c0860bSLeila Ghaffari ax.set_title('Convergence by h Refinement') 6450c0860bSLeila Ghaffari xlim(.03, .3) 6550c0860bSLeila Ghaffari fig.tight_layout() 6650c0860bSLeila Ghaffari plt.savefig('conv_plt_h.png', bbox_inches='tight') 6750c0860bSLeila Ghaffari 6850c0860bSLeila Ghaffari 6950c0860bSLeila Ghaffariif __name__ == "__main__": 7050c0860bSLeila Ghaffari plot() 71