X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=b7fd420aa263e9462344fce33b2070a12c065a53;hp=5580cbdf1ca0abbf603c6f8d4f66da0e7f17354a;hb=482bb432e9607bce6cb92d41bf9e299c0e2fc288;hpb=0f06aa38489e4242ee2b51bc23f79682a8f658f9

diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index 5580cbdf1c..b7fd420aa2 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -19,6 +19,7 @@ import logging
 import pandas as pd
 import plotly.offline as ploff
 import plotly.graph_objs as plgo
+
 from plotly.exceptions import PlotlyError
 
 from utils import mean
@@ -45,7 +46,7 @@ def generate_plots(spec, data):
 
 
 def plot_performance_box(plot, input_data):
-    """Generate the plot(s) with algorithm: table_detailed_test_results
+    """Generate the plot(s) with algorithm: plot_performance_box
     specified in the specification file.
 
     :param plot: Plot to generate.
@@ -261,13 +262,16 @@ def plot_throughput_speedup_analysis(plot, input_data):
                 except (KeyError, TypeError):
                     pass
 
+    if not throughput:
+        logging.warning("No data for the plot '{}'".
+                        format(plot.get("title", "")))
+        return
+
     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()
@@ -276,7 +280,7 @@ def plot_throughput_speedup_analysis(plot, input_data):
 
     for test_name, test_vals in throughput.items():
         if test_vals["1"]:
-            x_vals.append("-".join(test_name.split('-')[:-1]))
+            x_vals.append("-".join(test_name.split('-')[1:-1]))
             y_vals_1.append(1)
             if test_vals["2"]:
                 y_vals_2.append(
@@ -315,3 +319,73 @@ def plot_throughput_speedup_analysis(plot, input_data):
         return
 
     logging.info("  Done.")
+
+
+def plot_http_server_performance_box(plot, input_data):
+    """Generate the plot(s) with algorithm: plot_http_server_performance_box
+    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
+
+    # Prepare the data for the plot
+    y_vals = dict()
+    for job in data:
+        for build in job:
+            for test in build:
+                if y_vals.get(test["name"], None) is None:
+                    y_vals[test["name"]] = list()
+                try:
+                    y_vals[test["name"]].append(test["result"]["value"])
+                except (KeyError, TypeError):
+                    y_vals[test["name"]].append(None)
+
+    # Add None to the lists with missing data
+    max_len = 0
+    for val in y_vals.values():
+        if len(val) > max_len:
+            max_len = len(val)
+    for key, val in y_vals.items():
+        if len(val) < max_len:
+            val.extend([None for _ in range(max_len - len(val))])
+
+    # Add plot traces
+    traces = list()
+    df = pd.DataFrame(y_vals)
+    df.head()
+    for i, col in enumerate(df.columns):
+        name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
+                                 replace('-rps', ''))
+        traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
+                               y=df[col],
+                               name=name,
+                               **plot["traces"]))
+    try:
+        # Create plot
+        plpl = plgo.Figure(data=traces, layout=plot["layout"])
+
+        # Export Plot
+        logging.info("    Writing file '{0}{1}'.".
+                     format(plot["output-file"], plot["output-file-type"]))
+        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.")