resources/tools/dash/app/pal/report/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 import re
  18 import plotly.graph_objects as go
  19 import pandas as pd
  20
  21 from copy import deepcopy
  22
  23 from ..utils.constants import Constants as C
  24
  25
  26 def _get_color(idx: int) -> str:
  27     """
  28     """
  29     return C.PLOT_COLORS[idx % len(C.PLOT_COLORS)]
  30
  31
  32 def get_short_version(version: str, dut_type: str="vpp") -> str:
  33     """
  34     """
  35
  36     if dut_type in ("trex", "dpdk"):
  37         return version
  38
  39     s_version = str()
  40     groups = re.search(
  41         pattern=re.compile(r"^(\d{2}).(\d{2})-(rc0|rc1|rc2|release$)"),
  42         string=version
  43     )
  44     if groups:
  45         try:
  46             s_version = \
  47                 f"{groups.group(1)}.{groups.group(2)}.{groups.group(3)}".\
  48                     replace("release", "rls")
  49         except IndexError:
  50             pass
  51
  52     return s_version
  53
  54
  55 def select_iterative_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame:
  56     """
  57     """
  58
  59     phy = itm["phy"].split("-")
  60     if len(phy) == 4:
  61         topo, arch, nic, drv = phy
  62         if drv == "dpdk":
  63             drv = ""
  64         else:
  65             drv += "-"
  66             drv = drv.replace("_", "-")
  67     else:
  68         return None
  69
  70     core = str() if itm["dut"] == "trex" else f"{itm['core']}"
  71     ttype = "ndrpdr" if itm["testtype"] in ("ndr", "pdr") else itm["testtype"]
  72     dut_v100 = "none" if itm["dut"] == "trex" else itm["dut"]
  73     dut_v101 = itm["dut"]
  74
  75     df = data.loc[(
  76         (data["release"] == itm["rls"]) &
  77         (
  78             (
  79                 (data["version"] == "1.0.0") &
  80                 (data["dut_type"].str.lower() == dut_v100)
  81             ) |
  82             (
  83                 (data["version"] == "1.0.1") &
  84                 (data["dut_type"].str.lower() == dut_v101)
  85             )
  86         ) &
  87         (data["test_type"] == ttype) &
  88         (data["passed"] == True)
  89     )]
  90     regex_test = \
  91         f"^.*[.|-]{nic}.*{itm['framesize']}-{core}-{drv}{itm['test']}-{ttype}$"
  92     df = df[
  93         (df.job.str.endswith(f"{topo}-{arch}")) &
  94         (df.dut_version.str.contains(itm["dutver"].replace(".r", "-r").\
  95             replace("rls", "release"))) &
  96         (df.test_id.str.contains(regex_test, regex=True))
  97     ]
  98
  99     return df
 100
 101
 102 def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
 103         normalize: bool) -> tuple:
 104     """
 105     """
 106
 107     fig_tput = None
 108     fig_lat = None
 109
 110     tput_traces = list()
 111     y_tput_max = 0
 112     lat_traces = list()
 113     y_lat_max = 0
 114     x_lat = list()
 115     show_latency = False
 116     show_tput = False
 117     for idx, itm in enumerate(sel):
 118         itm_data = select_iterative_data(data, itm)
 119         if itm_data.empty:
 120             continue
 121         phy = itm["phy"].split("-")
 122         topo_arch = f"{phy[0]}-{phy[1]}" if len(phy) == 4 else str()
 123         norm_factor = (C.NORM_FREQUENCY / C.FREQUENCY[topo_arch]) \
 124             if normalize else 1.0
 125         if itm["testtype"] == "mrr":
 126             y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list()[0]
 127             y_data = [(y * norm_factor) for y in y_data_raw]
 128             if len(y_data) > 0:
 129                 y_tput_max = \
 130                     max(y_data) if max(y_data) > y_tput_max else y_tput_max
 131         else:
 132             y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list()
 133             y_data = [(y * norm_factor) for y in y_data_raw]
 134             if y_data:
 135                 y_tput_max = \
 136                     max(y_data) if max(y_data) > y_tput_max else y_tput_max
 137         nr_of_samples = len(y_data)
 138         tput_kwargs = dict(
 139             y=y_data,
 140             name=(
 141                 f"{idx + 1}. "
 142                 f"({nr_of_samples:02d} "
 143                 f"run{'s' if nr_of_samples > 1 else ''}) "
 144                 f"{itm['id']}"
 145             ),
 146             hoverinfo=u"y+name",
 147             boxpoints="all",
 148             jitter=0.3,
 149             marker=dict(color=_get_color(idx))
 150         )
 151         tput_traces.append(go.Box(**tput_kwargs))
 152         show_tput = True
 153
 154         if itm["testtype"] == "pdr":
 155             y_lat_row = itm_data[C.VALUE_ITER["pdr-lat"]].to_list()
 156             y_lat = [(y / norm_factor) for y in y_lat_row]
 157             if y_lat:
 158                 y_lat_max = max(y_lat) if max(y_lat) > y_lat_max else y_lat_max
 159             nr_of_samples = len(y_lat)
 160             lat_kwargs = dict(
 161                 y=y_lat,
 162                 name=(
 163                     f"{idx + 1}. "
 164                     f"({nr_of_samples:02d} "
 165                     f"run{u's' if nr_of_samples > 1 else u''}) "
 166                     f"{itm['id']}"
 167                 ),
 168                 hoverinfo="all",
 169                 boxpoints="all",
 170                 jitter=0.3,
 171                 marker=dict(color=_get_color(idx))
 172             )
 173             x_lat.append(idx + 1)
 174             lat_traces.append(go.Box(**lat_kwargs))
 175             show_latency = True
 176         else:
 177             lat_traces.append(go.Box())
 178
 179     if show_tput:
 180         pl_tput = deepcopy(layout["plot-throughput"])
 181         pl_tput["xaxis"]["tickvals"] = [i for i in range(len(sel))]
 182         pl_tput["xaxis"]["ticktext"] = [str(i + 1) for i in range(len(sel))]
 183         if y_tput_max:
 184             pl_tput["yaxis"]["range"] = [0, (int(y_tput_max / 1e6) + 1) * 1e6]
 185         fig_tput = go.Figure(data=tput_traces, layout=pl_tput)
 186
 187     if show_latency:
 188         pl_lat = deepcopy(layout["plot-latency"])
 189         pl_lat["xaxis"]["tickvals"] = [i for i in range(len(x_lat))]
 190         pl_lat["xaxis"]["ticktext"] = x_lat
 191         if y_lat_max:
 192             pl_lat["yaxis"]["range"] = [0, (int(y_lat_max / 10) + 1) * 10]
 193         fig_lat = go.Figure(data=lat_traces, layout=pl_lat)
 194
 195     return fig_tput, fig_lat
 196
 197
 198 def table_comparison(data: pd.DataFrame, sel:dict,
 199         normalize: bool) -> pd.DataFrame:
 200     """
 201     """
 202     table = pd.DataFrame(
 203         {
 204             "Test Case": [
 205                 "64b-2t1c-avf-eth-l2xcbase-eth-2memif-1dcr",
 206                 "64b-2t1c-avf-eth-l2xcbase-eth-2vhostvr1024-1vm-vppl2xc",
 207                 "64b-2t1c-avf-ethip4udp-ip4base-iacl50sl-10kflows",
 208                 "78b-2t1c-avf-ethip6-ip6scale2m-rnd "],
 209             "2106.0-8": [
 210                 "14.45 +- 0.08",
 211                 "9.63 +- 0.05",
 212                 "9.7 +- 0.02",
 213                 "8.95 +- 0.06"],
 214             "2110.0-8": [
 215                 "14.45 +- 0.08",
 216                 "9.63 +- 0.05",
 217                 "9.7 +- 0.02",
 218                 "8.95 +- 0.06"],
 219             "2110.0-9": [
 220                 "14.45 +- 0.08",
 221                 "9.63 +- 0.05",
 222                 "9.7 +- 0.02",
 223                 "8.95 +- 0.06"],
 224             "2202.0-9": [
 225                 "14.45 +- 0.08",
 226                 "9.63 +- 0.05",
 227                 "9.7 +- 0.02",
 228                 "8.95 +- 0.06"],
 229             "2110.0-9 vs 2110.0-8": [
 230                 "-0.23 +-  0.62",
 231                 "-1.37 +-   1.3",
 232                 "+0.08 +-   0.2",
 233                 "-2.16 +-  0.83"],
 234             "2202.0-9 vs 2110.0-9": [
 235                 "+6.95 +-  0.72",
 236                 "+5.35 +-  1.26",
 237                 "+4.48 +-  1.48",
 238                 "+4.09 +-  0.95"]
 239         }
 240     )
 241
 242     return pd.DataFrame()  #table