+
+
+def plot_throughput_speedup_analysis(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_throughput_speedup_analysis
+ specified in the specification file.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the plot {0} ...".
+ format(plot.get("title", "")))
+
+ # Transform the data
+ data = input_data.filter_data(plot)
+ if data is None:
+ logging.error("No data.")
+ return
+
+ throughput = dict()
+ for job in data:
+ for build in job:
+ for test in build:
+ if throughput.get(test["parent"], None) is None:
+ throughput[test["parent"]] = {"1": list(),
+ "2": list(),
+ "4": list()}
+ try:
+ if "1T1C" in test["tags"]:
+ throughput[test["parent"]]["1"].\
+ append(test["throughput"]["value"])
+ elif "2T2C" in test["tags"]:
+ throughput[test["parent"]]["2"]. \
+ append(test["throughput"]["value"])
+ elif "4T4C" in test["tags"]:
+ throughput[test["parent"]]["4"]. \
+ append(test["throughput"]["value"])
+ except (KeyError, TypeError):
+ pass
+
+ for test_name, test_vals in throughput.items():
+ for key, test_val in test_vals.items():
+ if test_val:
+ throughput[test_name][key] = sum(test_val) / len(test_val)
+
+ print(throughput)
+
+ names = ['1 core', '2 cores', '4 cores']
+ x_vals = list()
+ y_vals_1 = list()
+ y_vals_2 = list()
+ y_vals_4 = list()
+
+ for test_name, test_vals in throughput.items():
+ if test_vals["1"]:
+ x_vals.append("-".join(test_name.split('-')[:-1]))
+ y_vals_1.append(1)
+ if test_vals["2"]:
+ y_vals_2.append(
+ round(float(test_vals["2"]) / float(test_vals["1"]), 2))
+ else:
+ y_vals_2.append(None)
+ if test_vals["4"]:
+ y_vals_4.append(
+ round(float(test_vals["4"]) / float(test_vals["1"]), 2))
+ else:
+ y_vals_4.append(None)
+
+ y_vals = [y_vals_1, y_vals_2, y_vals_4]
+
+ y_vals_zipped = zip(names, y_vals)
+ traces = list()
+ for val in y_vals_zipped:
+ traces.append(plgo.Bar(x=x_vals,
+ y=val[1],
+ name=val[0]))
+
+ try:
+ # Create plot
+ logging.info(" Writing file '{0}{1}'.".
+ format(plot["output-file"], plot["output-file-type"]))
+ plpl = plgo.Figure(data=traces, layout=plot["layout"])
+
+ # Export Plot
+ ploff.plot(plpl,
+ show_link=False, auto_open=False,
+ filename='{0}{1}'.format(plot["output-file"],
+ plot["output-file-type"]))
+ except PlotlyError as err:
+ logging.error(" Finished with error: {}".
+ format(str(err).replace("\n", " ")))
+ return
+
+ logging.info(" Done.")
Code Review / csit.git / commitdiff