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plot_trials.py
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#!/usr/bin/env python3
import sys
import matplotlib.pyplot as plt
basename = sys.argv[1]
lnames = ["inelastic", "elastic_5", "elastic_10", "elastic_25", "elastic_50", "elastic_75", "elastic_100"]
pname = basename + "inelastic_vs_"
tnames = ["Total Runtime", "Average Runtime", "Total Wait Time", "Average Wait Time", "Average Turnaround Time", "System Utilization"]
def write_output(data, fname):
outfile = open(fname, "w+")
outfile.write("Elasticity,Trial 0,Trial 1,Trial 2,Trial 3,Trial 4,Average,Min,Max\n")
for i in range(0, len(lnames)):
outfile.write(lnames[i] + ",")
min_val = data[i][0]
max_val = data[i][0]
total = 0.0
for j in range(0, len(data[i])):
val = data[i][j]
total += val
if val < min_val:
min_val = val
elif val > max_val:
max_val = val
outfile.write("%f," % val)
outfile.write("%f,%f,%f\n" % (total/len(data[i]), min_val, max_val))
def plot_bar(data, title, y_label):
fig, ax = plt.subplots(1, 1, figsize=(16,9))
yvals = []
err_min = []
err_max = []
# Append inelastic data point
yvals.append(data[0][0])
err_min.append(0.0)
err_max.append(0.0)
for i in range(1, len(data)):
min_val = data[i][0]
min_idx = 0
max_val = data[i][0]
max_idx = 0
total = 0.0
for j in range(0, len(data[i])):
val = data[i][j]
if val < min_val:
min_val = val
min_idx = j
elif val > max_val:
max_val = val
max_idx = j
total += val
total -= min_val + max_val
yvals.append(total / float(len(data[i])-2))
e_min = max_val
e_max = min_val
for j in range(0, len(data[i])):
val = data[i][j]
if j != min_idx and j != max_idx:
if val < e_min:
e_min = val
if val > e_max:
e_max = val
tmp = yvals[-1] - e_min
if abs(tmp) < 0.01:
tmp = 0.0
err_min.append(tmp)
tmp = e_max - yvals[-1]
if abs(tmp) < 0.01:
tmp = 0.0
err_max.append(tmp)
if err_min[-1] < 0 or err_max[-1] < 0:
print(data[i])
print(yvals)
print(e_min)
print(err_min)
print(e_max)
print(err_max)
y_error = [err_min, err_max]
ax.grid(axis='y')
ax.bar(lnames, yvals, color = 'b')
ax.errorbar(lnames, yvals, yerr=y_error, fmt=".", color="r", markersize=0, capsize=5)
plt.xlabel("Elasticity")
plt.ylabel(y_label)
plt.title(title)
name = "%s%s.png" % (basename, title.replace(' ', '_').lower())
plt.savefig(name, dpi=250)
ofile = open("%s%s.csv" % (basename, title.replace(' ', '_').lower()), "w+")
ofile.write("err_min,")
for val in err_min:
ofile.write(str(val) + ",")
ofile.write("\n")
ofile.write("err_max,")
for val in err_max:
ofile.write(str(val) + ",")
ofile.write("\n")
ofile.write("lnames,")
for val in lnames:
ofile.write(str(val) + ",")
ofile.write("\n")
ofile.write("yvals,")
for val in yvals:
ofile.write(str(val) + ",")
ofile.write("\n")
tot_run_data = []
avg_run_data = []
tot_wait_data = []
avg_wait_data = []
util_data = []
avg_tt_data = []
for i in range(0, len(lnames)):
tot_run = []
avg_run = []
tot_wait = []
avg_wait = []
util = []
avg_tt = []
j = 0
while j < 5:
if lnames[i] == "inelastic":
fname = basename + "inelastic_stats.txt"
else:
fname = basename + str(j) + "_" + lnames[i] + "_stats.txt"
with open(fname) as f:
flag = ""
for line in f:
if "Run Time" in line:
flag = "Run"
if "Wait Time" in line:
flag = "Wait"
if "Elastic Time" in line:
flag = "Elastic"
if flag == "Run" and "Total" in line:
line = line.split()
tot_run.append(float(line[1]))
elif flag == "Run" and "Average" in line:
line = line.split()
avg_run.append(float(line[1]))
elif flag == "Wait" and "Total" in line:
line = line.split()
tot_wait.append(float(line[1]))
elif flag == "Wait" and "Average" in line:
line = line.split()
avg_wait.append(float(line[1]))
elif flag == "Elastic" and "Average Utilization" in line:
line = line.split()
util.append(float(line[2].replace('%', '')))
avg_tt.append(avg_wait[-1] + avg_run[-1])
if lnames[i] == "inelastic":
break
j += 1
tot_run_data.append(tot_run)
avg_run_data.append(avg_run)
tot_wait_data.append(tot_wait)
avg_wait_data.append(avg_wait)
util_data.append(util)
avg_tt_data.append(avg_tt)
plot_bar(avg_run_data, "Average Runtime by Elasticity", "Average Runtime (s)")
plot_bar(avg_wait_data, "Average Wait Time by Elasticity", "Average Wait Time (s)")
plot_bar(avg_tt_data, "Average Turnaround Time by Elasticity", "Average Turnaround Time (s)")
plot_bar(util_data, "Average Machine Utilization by Elasticity", "Average Machine Utilization Percentage")