diff options
Diffstat (limited to 'stats/gen_report.py')
| -rwxr-xr-x | stats/gen_report.py | 36 |
1 files changed, 30 insertions, 6 deletions
diff --git a/stats/gen_report.py b/stats/gen_report.py index 38a7c8d..77150c9 100755 --- a/stats/gen_report.py +++ b/stats/gen_report.py @@ -1,6 +1,8 @@ #!/usr/bin/python3 +import matplotlib.gridspec as gridspec import matplotlib.pyplot as plt +from scipy.stats import gaussian_kde from numpy import * import subprocess import argparse @@ -74,8 +76,6 @@ for commitLine in commitsLines: for benchFile in benchFiles: # Get the bench name bench_name = benchFile.replace("{sha1}_bench_".format(sha1=commit.sha1), "") - if bench_name.endswith(".png"): - continue # Find the right Benchmark or create one if none are found try: @@ -85,7 +85,7 @@ for commitLine in commitsLines: benchmarks.append(benchmark) # Create the result object - result = BenchResult(commit, benchmark, benchFile, report_folder + benchFile + ".png") + result = BenchResult(commit, benchmark, benchFile, report_folder + benchFile + ".svg") # Read the data with open(benchFile, 'rt') as f: @@ -159,12 +159,36 @@ for i in range(len(benchmarks)): plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=3, mode="expand", borderaxespad=0.) plt.savefig(report_folder + 'overview.svg', bbox_inches='tight') +plt.close() -# Generate the images (HACK, do that in python!) +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 large images for commit in commits: for result in commit.results: - subprocess.call(['../../stats/test_report.R', result.data_raw_file, result.img_src_name]) - + f = plt.figure(figsize=(19.5, 2)) + gs = gridspec.GridSpec(1, 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 #') + plt.ylabel('FPS') + ax1.plot(x) + + ax2 = plt.subplot(gs[1]) + plt.title("FPS distribution") + plt.xlabel('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') + + plt.tight_layout() + plt.savefig(result.img_src_name, bbox_inches='tight') + plt.close() # Generate the report html_template=""" |