Homec4science
Diffusion Additive Manufacturing Work (temperature_mesh_coarsening) Browse

R11910/mechanical_model/time_optimization_plots.py
3e9a1d30b01ftemperature_mesh_coarse…

Last Change
Raw File

time_optimization_plots.py
View Options

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 13 10:54:28 2022
@author: ekinkubilay
"""
import matplotlib.pyplot as plt
import numpy as np
#class definition for all time measurement runs
class Trial_run():
def __init__(self, layer):
self.layer = layer
def set_mu_time(self, mutime):
self.mutime = mutime
def set_f_time(self, ftime):
self.ftime = ftime
def set_total_time(self, total_time):
self.total_time = total_time
def set_procs(self, fproc, muproc):
self.fproc = fproc
self.muproc = muproc
#create figure
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))
linestyle_dict = {'36':'-', '18':'--', '24':':', '72':'-.', '99': ':'}
label_dict = {'36':'36', '18':'18', '24':'24', '72':'36x2', '99': 'jed-48'}
linecolor_dict={10:plt.rcParams['axes.prop_cycle'].by_key()['color'][0],
30:plt.rcParams['axes.prop_cycle'].by_key()['color'][1],
50:plt.rcParams['axes.prop_cycle'].by_key()['color'][2],
70:plt.rcParams['axes.prop_cycle'].by_key()['color'][3],
90:plt.rcParams['axes.prop_cycle'].by_key()['color'][4],
130:plt.rcParams['axes.prop_cycle'].by_key()['color'][5],
170:plt.rcParams['axes.prop_cycle'].by_key()['color'][6],
210:plt.rcParams['axes.prop_cycle'].by_key()['color'][7],
250:plt.rcParams['axes.prop_cycle'].by_key()['color'][8],
270:plt.rcParams['axes.prop_cycle'].by_key()['color'][9],
280:plt.rcParams['axes.prop_cycle'].by_key()['color'][0],
290:plt.rcParams['axes.prop_cycle'].by_key()['color'][1],
300:plt.rcParams['axes.prop_cycle'].by_key()['color'][2],
310:plt.rcParams['axes.prop_cycle'].by_key()['color'][3],
320:plt.rcParams['axes.prop_cycle'].by_key()['color'][4],
330:plt.rcParams['axes.prop_cycle'].by_key()['color'][5]}
for n in ['18', '24', '36']:
#read time optimization output file
reader = open('results/time_optimization_'+n+'.log', 'r')
lines = reader.readlines()
reader.close()
#list for all runs
run = None
run_list = []
#read each line, full in the run list
for line in lines:
if line.split()!=[] and line.split()[0] != 'Process' and line.split()[0] != '***':
try:
int(line.split()[0])
if run != None:
run_list.append(run)
run = Trial_run(int(line.split()[0]))
except:
if 'MUSPECTRE' in line.split():
run.set_mu_time(float(line.split()[-1]))
if 'FENICS' in line.split():
run.set_f_time(float(line.split()[-1]))
if 'steps:' in line.split():
run.set_total_time(float(line.split()[-1]))
if 'tasks:' in line.split():
run.set_procs(int(line.split()[11]), int(line.split()[5]))
run_list.append(run)
#create dictionary with layers as keys, run_list as values
run_dict = {}
for run in run_list:
if run.layer in run_dict:
run_dict[run.layer].append(run)
else:
run_dict[run.layer] = []
run_dict[run.layer].append(run)
#order the dictionary by keys
run_dict = dict(sorted(run_dict.items()))
#plot each measurement
for k,v in run_dict.items():
ax1.plot([x.muproc for x in v], [x.total_time for x in v], linestyle=linestyle_dict[n], color=linecolor_dict[k], label='{}'.format(k))
#plot optimum process for each layer
opt_proc_no = [v[np.argmin([x.total_time for x in v])].muproc for v in run_dict.values()]
layer_no = [k for k in run_dict.keys()]
ax2.plot(layer_no, opt_proc_no, linestyle=linestyle_dict[n], label=label_dict[n], color='k')
handles, labels = ax1.get_legend_handles_labels()
by_label = dict(zip(labels, handles))
ax1.legend(by_label.values(), by_label.keys(), title='layer', loc='upper left', ncol=3)
#cost plot variables
ax1.grid(True)
ax1.set_ylabel('total time / 100 steps (s)')
ax1.set_xlabel('# of muspectre processes (-)')
ax1.set_title('Time cost vs. # of muspectre processors')
#optimum process plot variables
ax2.grid(True)
ax2.set_ylabel('Optimum muSpectre Processor number')
ax2.set_xlabel('# of Layers')
ax2.set_title('Optimum muSpectre Processor number vs. # of Layers')
ax2.legend(title='total processors', loc='upper left')
fig.savefig('results/optimization.png')
c4science · Help