C-Dash: Hover info and y-axis in trending and iterative graphs

[csit.git] / csit.infra.dash / app / cdash / report / graphs.py

diff --git a/csit.infra.dash/app/cdash/report/graphs.py b/csit.infra.dash/app/cdash/report/graphs.py
index 0e27836..2d1f4b1 100644 (file)
--- a/csit.infra.dash/app/cdash/report/graphs.py
+++ b/csit.infra.dash/app/cdash/report/graphs.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2022 Cisco and/or its affiliates.
+# Copyright (c) 2023 Cisco and/or its affiliates.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at:
@@ -11,10 +11,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""
+"""Implementation of graphs for iterative data.
 """
 
-import re
 import plotly.graph_objects as go
 import pandas as pd
 
@@ -24,36 +23,6 @@ from ..utils.constants import Constants as C
 from ..utils.utils import get_color
 
 
-def get_short_version(version: str, dut_type: str="vpp") -> str:
-    """Returns the short version of DUT without build number.
-
-    :param version: Original version string.
-    :param dut_type: DUT type.
-    :type version: str
-    :type dut_type: str
-    :returns: Short verion string.
-    :rtype: str
-    """
-
-    if dut_type in ("trex", "dpdk"):
-        return version
-
-    s_version = str()
-    groups = re.search(
-        pattern=re.compile(r"^(\d{2}).(\d{2})-(rc0|rc1|rc2|release$)"),
-        string=version
-    )
-    if groups:
-        try:
-            s_version = \
-                f"{groups.group(1)}.{groups.group(2)}.{groups.group(3)}".\
-                    replace("release", "rls")
-        except IndexError:
-            pass
-
-    return s_version
-
-
 def select_iterative_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame:
     """Select the data for graphs and tables from the provided data frame.
 
@@ -77,26 +46,20 @@ def select_iterative_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame:
     else:
         return None
 
-    core = str() if itm["dut"] == "trex" else f"{itm['core']}"
-    ttype = "ndrpdr" if itm["testtype"] in ("ndr", "pdr") else itm["testtype"]
-    dut_v100 = "none" if itm["dut"] == "trex" else itm["dut"]
-    dut_v101 = itm["dut"]
-
+    if itm["testtype"] in ("ndr", "pdr"):
+        test_type = "ndrpdr"
+    elif itm["testtype"] == "mrr":
+        test_type = "mrr"
+    elif itm["area"] == "hoststack":
+        test_type = "hoststack"
     df = data.loc[(
         (data["release"] == itm["rls"]) &
-        (
-            (
-                (data["version"] == "1.0.0") &
-                (data["dut_type"].str.lower() == dut_v100)
-            ) |
-            (
-                (data["version"] == "1.0.1") &
-                (data["dut_type"].str.lower() == dut_v101)
-            )
-        ) &
-        (data["test_type"] == ttype) &
+        (data["test_type"] == test_type) &
         (data["passed"] == True)
     )]
+
+    core = str() if itm["dut"] == "trex" else f"{itm['core']}"
+    ttype = "ndrpdr" if itm["testtype"] in ("ndr", "pdr") else itm["testtype"]
     regex_test = \
         f"^.*[.|-]{nic}.*{itm['framesize']}-{core}-{drv}{itm['test']}-{ttype}$"
     df = df[
@@ -135,28 +98,40 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
     lat_traces = list()
     y_lat_max = 0
     x_lat = list()
+    y_units = set()
     show_latency = False
     show_tput = False
     for idx, itm in enumerate(sel):
+
         itm_data = select_iterative_data(data, itm)
         if itm_data.empty:
             continue
+
         phy = itm["phy"].split("-")
         topo_arch = f"{phy[0]}-{phy[1]}" if len(phy) == 4 else str()
         norm_factor = (C.NORM_FREQUENCY / C.FREQUENCY[topo_arch]) \
             if normalize else 1.0
+
+        if itm["area"] == "hoststack":
+            ttype = f"hoststack-{itm['testtype']}"
+        else:
+            ttype = itm["testtype"]
+
+        y_units.update(itm_data[C.UNIT[ttype]].unique().tolist())
+
         if itm["testtype"] == "mrr":
-            y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list()[0]
+            y_data_raw = itm_data[C.VALUE_ITER[ttype]].to_list()[0]
             y_data = [(y * norm_factor) for y in y_data_raw]
             if len(y_data) > 0:
                 y_tput_max = \
                     max(y_data) if max(y_data) > y_tput_max else y_tput_max
         else:
-            y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list()
+            y_data_raw = itm_data[C.VALUE_ITER[ttype]].to_list()
             y_data = [(y * norm_factor) for y in y_data_raw]
             if y_data:
                 y_tput_max = \
                     max(y_data) if max(y_data) > y_tput_max else y_tput_max
+
         nr_of_samples = len(y_data)
         tput_kwargs = dict(
             y=y_data,
@@ -174,7 +149,7 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
         tput_traces.append(go.Box(**tput_kwargs))
         show_tput = True
 
-        if itm["testtype"] == "pdr":
+        if ttype == "pdr":
             y_lat_row = itm_data[C.VALUE_ITER["pdr-lat"]].to_list()
             y_lat = [(y / norm_factor) for y in y_lat_row]
             if y_lat:
@@ -203,8 +178,9 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
         pl_tput = deepcopy(layout["plot-throughput"])
         pl_tput["xaxis"]["tickvals"] = [i for i in range(len(sel))]
         pl_tput["xaxis"]["ticktext"] = [str(i + 1) for i in range(len(sel))]
+        pl_tput["yaxis"]["title"] = f"Throughput [{'|'.join(sorted(y_units))}]"
         if y_tput_max:
-            pl_tput["yaxis"]["range"] = [0, (int(y_tput_max / 1e6) + 1) * 1e6]
+            pl_tput["yaxis"]["range"] = [0, (int(y_tput_max / 1e6) + 2) * 1e6]
         fig_tput = go.Figure(data=tput_traces, layout=pl_tput)
 
     if show_latency: