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#!/usr/bin/env python3
from matplotlib.patches import Rectangle
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
import argparse
import sys
import os
# Import ezbench from the utils/ folder
sys.path.append(os.path.abspath(sys.path[0]+'/../utils/'))
from ezbench import *
# constants
html_name="index.html"
report_folder="ezbench_report/"
def genFileNameReportImg(report_folder, data_raw_file):
return report_folder + data_raw_file + ".svg"
def genFileNameSparkline(report_folder, data_raw_file):
return report_folder + data_raw_file + ".spark.svg"
# parse the options
parser = argparse.ArgumentParser()
parser.add_argument("--frametime", help="Use frame times instead of FPS",
action="store_true")
parser.add_argument("log_folder")
args = parser.parse_args()
# Parse the report
commits, benchmarks = readPerformanceReport(args.log_folder, args.frametime)
# Generate the labels for the commits
commitsLabels = []
for commit in commits:
commitsLabels.append(commit.label)
# Create a folder for the results
os.chdir(args.log_folder)
if not os.path.isdir(report_folder):
try:
os.mkdir(report_folder)
except OSError:
print ("Error while creating the report folder")
# Generate the trend graph
print("Generating the trend graph")
f = plt.figure(figsize=(17,3))
plt.xlabel('Commits')
plt.ylabel('Perf. diff. with the first commit (%)')
plt.grid(True)
data = getResultsGeomDiffs(commits)
x_val = [x[0] for x in data]
y_val = [x[1] for x in data]
plt.plot(x_val, y_val, label="Geometric mean")
for i in range(len(benchmarks)):
data = getResultsBenchmarkDiffs(commits, benchmarks[i])
x_val = [x[0] for x in data]
y_val = [x[1] for x in data]
plt.plot(x_val, y_val, label=benchmarks[i].full_name)
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,
ncol=4, mode="expand", borderaxespad=0.)
plt.xticks(range(len(commitsLabels)), commitsLabels, size='small', rotation=70)
plt.savefig(report_folder + 'overview.svg', bbox_inches='tight')
plt.close()
def kde_scipy(x, x_grid, bandwidth=0.2, **kwargs):
kde = gaussian_kde(x, bw_method=bandwidth, **kwargs)
return kde.evaluate(x_grid)
# Generate the spark lines
print("Generating the sparklines",end="",flush=True)
for commit in commits:
for result in commit.results:
fig, ax = plt.subplots(1,1,figsize=(1.25,.3))
r_max = amax(result.data)
if r_max > 0:
plt.ylim(0, r_max)
plt.plot(result.data, linewidth=0.8)
# remove all the axes
plt.axis('off')
for k,v in ax.spines.items():
v.set_visible(False)
ax.set_xticks([])
ax.set_yticks([])
plt.savefig(genFileNameSparkline(report_folder, result.data_raw_file),
bbox_inches='tight', transparent=True)
plt.close()
print('.',end="",flush=True)
print(" DONE")
# Generate the large images
plt.rcParams.update({'font.size': 9})
print("Generating the runs' output image",end="",flush=True)
for c in range (0, len(commits)):
commit = commits[c]
for r in range (0, len(commit.results)):
result = commit.results[r]
img_src_name = genFileNameReportImg(report_folder, result.data_raw_file)
try:
f = plt.figure(figsize=(19.5, 4))
gs = gridspec.GridSpec(2, 2, width_ratios=[4, 1])
x = array(result.data)
ax1 = plt.subplot(gs[0])
plt.title("Time series across all the runs")
plt.xlabel('Run #')
if args.frametime:
plt.ylabel('Frametime (ms)')
else:
plt.ylabel('FPS')
YAvg = mean(x)
boxYMin = YAvg * 0.99
boxYMax = YAvg * 1.01
ax1.plot(x, label="cur.")
ax1.add_patch(Rectangle((0, boxYMin), len(x), boxYMax - boxYMin, alpha=.2, facecolor="green", label="2% box"))
if c > 0:
ax1.plot(commits[c - 1].results[r].data, label="prev.")
plt.legend()
ax2 = plt.subplot(gs[1])
if args.frametime:
plt.title("Frametime distribution (ms)")
plt.ylabel('Frametime (ms)')
else:
plt.title("FPS distribution")
plt.ylabel('FPS')
x_grid = linspace(amin(x) * 0.95, amax(x) * 1.05, 1000)
for bandwidth in [0.2]:
ax2.plot(x_grid, kde_scipy(x, x_grid, bandwidth=bandwidth),
label='bw={0}'.format(bandwidth), linewidth=1, alpha=1)
ax2.hist(x, 100, fc='gray', histtype='stepfilled', alpha=0.3, normed=True, label='histogram')
ax3 = plt.subplot(gs[2])
plt.title("Time series of the runs")
if args.frametime:
plt.xlabel('Frametime sample')
plt.ylabel('Frametime (ms)')
else:
plt.xlabel('FPS sample')
plt.ylabel('FPS')
for i in range(0, len(result.runs)):
ax3.plot(result.runs[i], label="{0}".format(i))
if len(result.runs) <= 40:
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=20, mode="expand", borderaxespad=0.)
plt.tight_layout()
plt.savefig(img_src_name, bbox_inches='tight')
except Exception as e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
print("Failed to generate {filename}: {error} at {fname}:{line}".format(filename=img_src_name,
error=str(e), fname=fname,
line=exc_tb.tb_lineno))
plt.close()
print('.',end="",flush=True)
print(" DONE")
# Generate the report
html_template="""
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<title>Performance report on the run named '{run_name}'</title>
<style>
body {{ font-size: 10pt}}
</style>
</head>
<body>
<h1>Performance report on the run named '{run_name}'</h1>
<h2>Trends</h2>
<center><img src="{report_folder}/overview.svg" alt="Trends"/></center>
<h2>Stats</h2>
<table border="1" style="">
<tr>
<th>Commit #</th>
<th>Commit SHA1</th>
<th>Geometric mean</th>
{tbl_hdr_benchmarks}
</tr>
{tbl_entries}
</table>
<h2>Commits</h2>
{commits}
</body>
</html>
"""
table_commit_template="""
<tr>
<td>{commitNum}</td>
<td><a href="#commit_{sha1}">{sha1}</a></td>
<td bgcolor="{geom_color}">{geom_mean:.2f} ({geom_diff:+.2f} %)</td>
{tbl_res_benchmarks}
</tr>
"""
table_entry_template="""
<td bgcolor="{color}">
<a href="#commit_{sha1}_bench_{bench_name}">
{value:.2f} ({diff:+.2f} %)
<img src="{sparkline_img}" alt="Test's time series and density of probability" />
<a/>
</td>"""
table_entry_no_results_template="""<td bgcolor="#FFFF00"><center>NO DATA</center>"""
commit_template="""
<h3 id="commit_{sha1}">{commit}</h3>
<p><a href="{patch}">Patch</a> <a href="{compile_log}">Compilation logs</a></p>
<table border="1" style="">
<tr>
<th>Commit #</th>
<th>Commit SHA1</th>
<th>Geometric mean</th>
{tbl_hdr_benchmarks}
</tr>
{commit_results}
</table>
{benchs}"""
bench_template="""
<h4 id="commit_{sha1}_bench_{bench_name}">{bench_name} (commit <a href="#commit_{sha1}">{commit}</a>)</h4>
<p><a href="{raw_data_file}">Original data</a></p>
<img src="{img_src}" alt="Test's time series and density of probability" />"""
def computeDiffAndColor(prev, new):
if prev > 0:
if args.frametime:
diff = (prev * 100.0 / new) - 100.0
else:
diff = (new * 100.0 / prev) - 100.0
else:
diff = 0
if diff < -1.5 or diff == float('inf'):
color = "#FF0000"
elif diff > 1.5:
color = "#00FF00"
else:
color = "#FFFFFF"
return diff, color
# Create the html file
print("Generating the HTML")
# generate the table's header
tbl_hdr_benchmarks = ""
for benchmark in benchmarks:
tbl_hdr_benchmarks += "<th>{benchmark}</th>\n".format(benchmark=benchmark.full_name)
# generate the reports for each commits
commits_txt = ""
tbl_entries_txt = ""
geom_prev = -1
i = 0
for commit in commits:
benchs_txt = ""
tbl_res_benchmarks = ""
for benchmark in benchmarks:
result = None
for r in commit.results:
if r.benchmark == benchmark:
result = r
break
if result != None:
value = array(result.data).mean()
diff, color = computeDiffAndColor(result.benchmark.prevValue, value)
result.benchmark.prevValue = value
img_src_name = genFileNameReportImg(report_folder, result.data_raw_file)
sparkline_img = genFileNameSparkline(report_folder, result.data_raw_file)
# Generate the html
benchs_txt += bench_template.format(sha1=commit.sha1,
commit=commit.full_name,
bench_name=result.benchmark.full_name,
img_src=img_src_name,
raw_data_file=result.data_raw_file)
tbl_res_benchmarks += table_entry_template.format(sha1=commit.sha1,
bench_name=result.benchmark.full_name,
sparkline_img=sparkline_img,
value=value,
diff=diff,
color=color)
else:
tbl_res_benchmarks += table_entry_no_results_template
# generate the html
diff, color = computeDiffAndColor(geom_prev, commit.geom_mean())
geom_prev = commit.geom_mean()
commit_results = table_commit_template.format(commitNum=i, sha1=commit.sha1,
geom_mean=commit.geom_mean(),
geom_diff=diff, geom_color=color,
tbl_res_benchmarks=tbl_res_benchmarks)
tbl_entries_txt += commit_results
commits_txt += commit_template.format(commit=commit.full_name,
sha1=commit.sha1,
benchs=benchs_txt,
compile_log=commit.compile_log,
tbl_hdr_benchmarks=tbl_hdr_benchmarks,
commit_results=commit_results,
patch=commit.patch)
i += 1
# Generate the final html file
html = html_template.format(run_name=args.log_folder,
commits=commits_txt,
tbl_entries=tbl_entries_txt,
tbl_hdr_benchmarks=tbl_hdr_benchmarks,
report_folder=report_folder);
with open(html_name, 'w') as f:
f.write(html)
print("Output HTML generated at: {0}/{1}".format(os.getcwd(), html_name))
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