resources/tools/dash/app/pal/trending/graphs.py

   1 # Copyright (c) 2022 Cisco and/or its affiliates.
   2 # Licensed under the Apache License, Version 2.0 (the "License");
   3 # you may not use this file except in compliance with the License.
   4 # You may obtain a copy of the License at:
   5 #
   6 #     http://www.apache.org/licenses/LICENSE-2.0
   7 #
   8 # Unless required by applicable law or agreed to in writing, software
   9 # distributed under the License is distributed on an "AS IS" BASIS,
  10 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  11 # See the License for the specific language governing permissions and
  12 # limitations under the License.
  13
  14 """
  15 """
  16
  17
  18 import plotly.graph_objects as go
  19 import pandas as pd
  20 import re
  21
  22 from datetime import datetime
  23
  24 from dash import no_update
  25
  26
  27 def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime,
  28     end: datetime):
  29     """
  30     """
  31
  32     if not sel:
  33         return no_update, no_update
  34
  35     def _generate_trace(ttype: str, name: str, df: pd.DataFrame,
  36         start: datetime, end: datetime):
  37
  38         value = {
  39             "mrr": "result_receive_rate_rate_avg",
  40             "ndr": "result_ndr_lower_rate_value",
  41             "pdr": "result_pdr_lower_rate_value"
  42         }
  43         unit = {
  44             "mrr": "result_receive_rate_rate_unit",
  45             "ndr": "result_ndr_lower_rate_unit",
  46             "pdr": "result_pdr_lower_rate_unit"
  47         }
  48
  49         x_axis = [
  50             d for d in df["start_time"] if d >= start and d <= end
  51         ]
  52         hover_txt = list()
  53         for _, row in df.iterrows():
  54             hover_itm = (
  55                 f"date: "
  56                 f"{row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
  57                 f"average [{row[unit[ttype]]}]: "
  58                 f"{row[value[ttype]]}<br>"
  59                 f"{row['dut_type']}-ref: {row['dut_version']}<br>"
  60                 f"csit-ref: {row['job']}/{row['build']}"
  61             )
  62             if ttype == "mrr":
  63                 stdev = (
  64                     f"stdev [{row['result_receive_rate_rate_unit']}]: "
  65                     f"{row['result_receive_rate_rate_stdev']}<br>"
  66                 )
  67             else:
  68                 stdev = ""
  69             hover_itm = hover_itm.replace("<stdev>", stdev)
  70             hover_txt.append(hover_itm)
  71
  72         return go.Scatter(
  73             x=x_axis,
  74             y=df[value[ttype]],
  75             name=name,
  76             mode="markers+lines",
  77             text=hover_txt,
  78             hoverinfo=u"text+name"
  79         )
  80
  81     # Generate graph:
  82     fig = go.Figure()
  83     for itm in sel:
  84         phy = itm["phy"].split("-")
  85         if len(phy) == 4:
  86             topo, arch, nic, drv = phy
  87             if drv in ("dpdk", "ixgbe"):
  88                 drv = ""
  89             else:
  90                 drv += "-"
  91         else:
  92             continue
  93         cadence = \
  94             "weekly" if (arch == "aws" or itm["testtype"] != "mrr") else "daily"
  95         sel_topo_arch = (
  96             f"csit-vpp-perf-"
  97             f"{itm['testtype'] if itm['testtype'] == 'mrr' else 'ndrpdr'}-"
  98             f"{cadence}-master-{topo}-{arch}"
  99         )
 100         df_sel = data.loc[(data["job"] == sel_topo_arch)]
 101         regex = (
 102             f"^.*{nic}.*\.{itm['framesize']}-{itm['core']}-{drv}{itm['test']}-"
 103             f"{'mrr' if itm['testtype'] == 'mrr' else 'ndrpdr'}$"
 104         )
 105         df = df_sel.loc[
 106             df_sel["test_id"].apply(
 107                 lambda x: True if re.search(regex, x) else False
 108             )
 109         ].sort_values(by="start_time", ignore_index=True)
 110         name = (
 111             f"{itm['phy']}-{itm['framesize']}-{itm['core']}-"
 112             f"{itm['test']}-{itm['testtype']}"
 113         )
 114         fig.add_trace(_generate_trace(itm['testtype'], name, df, start, end))
 115
 116     style={
 117         "vertical-align": "top",
 118         "display": "inline-block",
 119         "width": "80%",
 120         "padding": "5px"
 121     }
 122
 123     layout = layout.get("plot-trending", dict())
 124     fig.update_layout(layout)
 125
 126     return fig, style