CSIT-1041: Trending dashboard

[csit.git] / resources / tools / presentation / generator_tables.py

diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 6c30187..a5a8824 100644 (file)
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -18,7 +18,6 @@
 import logging
 import csv
 import prettytable
-import numpy as np
 import pandas as pd
 
 from string import replace
@@ -441,7 +440,7 @@ def table_performance_comparison(table, input_data):
                                                table["output-file-ext"])
                  ]
     for file_name in tbl_names:
-        logging.info("      Writing file: '{}'".format(file_name))
+        logging.info("      Writing file: '{0}'".format(file_name))
         with open(file_name, "w") as file_handler:
             file_handler.write(header_str)
             for test in tbl_lst:
@@ -462,7 +461,7 @@ def table_performance_comparison(table, input_data):
 
     for i, txt_name in enumerate(tbl_names_txt):
         txt_table = None
-        logging.info("      Writing file: '{}'".format(txt_name))
+        logging.info("      Writing file: '{0}'".format(txt_name))
         with open(tbl_names[i], 'rb') as csv_file:
             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
             for row in csv_content:
@@ -484,7 +483,7 @@ def table_performance_comparison(table, input_data):
 
     output_file = "{0}-ndr-1t1c-top{1}".format(table["output-file"],
                                                table["output-file-ext"])
-    logging.info("      Writing file: '{}'".format(output_file))
+    logging.info("      Writing file: '{0}'".format(output_file))
     with open(output_file, "w") as out_file:
         out_file.write(header_str)
         for i, line in enumerate(lines[1:]):
@@ -494,7 +493,7 @@ def table_performance_comparison(table, input_data):
 
     output_file = "{0}-ndr-1t1c-bottom{1}".format(table["output-file"],
                                                   table["output-file-ext"])
-    logging.info("      Writing file: '{}'".format(output_file))
+    logging.info("      Writing file: '{0}'".format(output_file))
     with open(output_file, "w") as out_file:
         out_file.write(header_str)
         for i, line in enumerate(lines[-1:0:-1]):
@@ -511,7 +510,7 @@ def table_performance_comparison(table, input_data):
 
     output_file = "{0}-pdr-1t1c-top{1}".format(table["output-file"],
                                                table["output-file-ext"])
-    logging.info("      Writing file: '{}'".format(output_file))
+    logging.info("      Writing file: '{0}'".format(output_file))
     with open(output_file, "w") as out_file:
         out_file.write(header_str)
         for i, line in enumerate(lines[1:]):
@@ -521,7 +520,7 @@ def table_performance_comparison(table, input_data):
 
     output_file = "{0}-pdr-1t1c-bottom{1}".format(table["output-file"],
                                                   table["output-file-ext"])
-    logging.info("      Writing file: '{}'".format(output_file))
+    logging.info("      Writing file: '{0}'".format(output_file))
     with open(output_file, "w") as out_file:
         out_file.write(header_str)
         for i, line in enumerate(lines[-1:0:-1]):
@@ -549,9 +548,9 @@ def table_performance_trending_dashboard(table, input_data):
     # Prepare the header of the tables
     header = ["Test case",
               "Thput trend [Mpps]",
-              "Change [Mpps]",
+              "Anomaly [Mpps]",
               "Change [%]",
-              "Anomaly"]
+              "Classification"]
     header_str = ",".join(header) + "\n"
 
     # Prepare data to the table:
@@ -567,8 +566,8 @@ def table_performance_trending_dashboard(table, input_data):
                                           "data": list()}
                 try:
                     tbl_dict[tst_name]["data"]. \
-                        append(tst_data["throughput"]["value"])
-                except TypeError:
+                        append(tst_data["result"]["throughput"])
+                except (TypeError, KeyError):
                     pass  # No data in output.xml for this test
 
     tbl_lst = list()
@@ -580,45 +579,56 @@ def table_performance_trending_dashboard(table, input_data):
             # Test name:
             name = tbl_dict[tst_name]["name"]
             # Throughput trend:
-            trend = list(pd_data.rolling(window=win_size).median())[-2]
+            trend = list(pd_data.rolling(window=win_size, min_periods=2).
+                         median())[-2]
             # Anomaly:
             t_data, _ = find_outliers(pd_data)
             last = list(t_data)[-1]
             t_stdev = list(t_data.rolling(window=win_size, min_periods=2).
                          std())[-2]
             if isnan(last):
-                anomaly = "outlier"
+                classification = "outlier"
+                last = list(pd_data)[-1]
             elif last < (trend - 3 * t_stdev):
-                anomaly = "regression"
+                classification = "regression"
             elif last > (trend + 3 * t_stdev):
-                anomaly = "progression"
+                classification = "progression"
             else:
-                anomaly = "normal"
-            # Change:
-            change = round(float(last - trend) / 1000000, 2)
-            # Relative change:
-            rel_change = int(relative_change(float(trend), float(last)))
-
-            tbl_lst.append([name,
-                            round(float(last) / 1000000, 2),
-                            change,
-                            rel_change,
-                            anomaly])
+                classification = "normal"
+
+            if not isnan(last) and not isnan(trend) and trend != 0:
+                # Change:
+                change = round(float(last - trend) / 1000000, 2)
+                # Relative change:
+                rel_change = int(relative_change(float(trend), float(last)))
+
+                tbl_lst.append([name,
+                                round(float(trend) / 1000000, 2),
+                                last,
+                                rel_change,
+                                classification])
 
     # Sort the table according to the relative change
-    tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
+    # tbl_lst.sort(key=lambda rel: rel[-2], reverse=True)
+
+    # Sort the table according to the classification
+    tbl_sorted = list()
+    for classification in ("regression", "outlier", "progression", "normal"):
+        tbl_tmp = [item for item in tbl_lst if item[4] == classification]
+        tbl_tmp.sort(key=lambda rel: rel[0])
+        tbl_sorted.extend(tbl_tmp)
 
-    file_name = "{}.{}".format(table["output-file"], table["output-file-ext"])
+    file_name = "{0}.{1}".format(table["output-file"], table["output-file-ext"])
 
-    logging.info("      Writing file: '{}'".format(file_name))
+    logging.info("      Writing file: '{0}'".format(file_name))
     with open(file_name, "w") as file_handler:
         file_handler.write(header_str)
-        for test in tbl_lst:
+        for test in tbl_sorted:
             file_handler.write(",".join([str(item) for item in test]) + '\n')
 
-    txt_file_name = "{}.txt".format(table["output-file"])
+    txt_file_name = "{0}.txt".format(table["output-file"])
     txt_table = None
-    logging.info("      Writing file: '{}'".format(txt_file_name))
+    logging.info("      Writing file: '{0}'".format(txt_file_name))
     with open(file_name, 'rb') as csv_file:
         csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
         for row in csv_content: