-# Copyright (c) 2023 Cisco and/or its affiliates.
+# Copyright (c) 2024 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:
import plotly.graph_objects as go
import pandas as pd
+from numpy import nan
+
from ..utils.constants import Constants as C
from ..utils.utils import get_color, get_hdrh_latencies
from ..utils.anomalies import classify_anomalies
test_type = "ndrpdr"
elif itm["testtype"] == "mrr":
test_type = "mrr"
+ elif itm["testtype"] == "soak":
+ test_type = "soak"
elif itm["area"] == "hoststack":
test_type = "hoststack"
df = data.loc[(
data: pd.DataFrame,
sel: dict,
layout: dict,
- normalize: bool
+ normalize: bool=False,
+ trials: bool=False
) -> tuple:
"""Generate the trending graph(s) - MRR, NDR, PDR and for PDR also Latences
(result_latency_forward_pdr_50_avg).
:param layout: Layout of plot.ly graph.
:param normalize: If True, the data is normalized to CPU frquency
Constants.NORM_FREQUENCY.
+ :param trials: If True, MRR trials are displayed in the trending graph.
:type data: pandas.DataFrame
:type sel: dict
:type layout: dict
:type normalize: bool
+ :type: trials: bool
:returns: Trending graph(s)
:rtype: tuple(plotly.graph_objects.Figure, plotly.graph_objects.Figure)
"""
customdata_samples = list()
name_lst = name.split("-")
for _, row in df.iterrows():
- h_tput, h_band, h_lat = str(), str(), str()
+ h_tput, h_band, h_lat, h_tput_trials, h_band_trials = \
+ str(), str(), str(), str(), str()
if ttype in ("mrr", "mrr-bandwidth"):
h_tput = (
f"tput avg [{row['result_receive_rate_rate_unit']}]: "
f"{row['result_receive_rate_bandwidth_stdev']* nf:,.0f}"
"<br>"
)
+ if trials:
+ h_tput_trials = (
+ f"tput trials "
+ f"[{row['result_receive_rate_rate_unit']}]: "
+ )
+ for itm in row["result_receive_rate_rate_values"]:
+ h_tput_trials += f"{itm * nf:,.0f}; "
+ h_tput_trials = h_tput_trials[:-2] + "<br>"
+ if pd.notna(row["result_receive_rate_bandwidth_avg"]):
+ h_band_trials = (
+ f"bandwidth trials "
+ f"[{row['result_receive_rate_bandwidth_unit']}]: "
+ )
+ for itm in row["result_receive_rate_bandwidth_values"]:
+ h_band_trials += f"{itm * nf:,.0f}; "
+ h_band_trials = h_band_trials[:-2] + "<br>"
+
elif ttype in ("ndr", "ndr-bandwidth"):
h_tput = (
f"tput [{row['result_ndr_lower_rate_unit']}]: "
f"bandwidth [{row['result_bandwidth_unit']}]: "
f"{row['result_bandwidth_value'] * nf:,.0f}<br>"
)
+ elif ttype in ("soak", "soak-bandwidth"):
+ h_tput = (
+ f"tput [{row['result_critical_rate_lower_rate_unit']}]: "
+ f"{row['result_critical_rate_lower_rate_value'] * nf:,.0f}"
+ "<br>"
+ )
+ if pd.notna(row["result_critical_rate_lower_bandwidth_value"]):
+ bv = row['result_critical_rate_lower_bandwidth_value']
+ h_band = (
+ "bandwidth "
+ f"[{row['result_critical_rate_lower_bandwidth_unit']}]:"
+ f" {bv * nf:,.0f}"
+ "<br>"
+ )
+ try:
+ hosts = f"<br>hosts: {', '.join(row['hosts'])}"
+ except (KeyError, TypeError):
+ hosts = str()
hover_itm = (
f"dut: {name_lst[0]}<br>"
f"infra: {'-'.join(name_lst[1:5])}<br>"
f"test: {'-'.join(name_lst[5:])}<br>"
f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
- f"{h_tput}{h_band}{h_lat}"
+ f"{h_tput}{h_tput_trials}{h_band}{h_band_trials}{h_lat}"
f"{row['dut_type']}-ref: {row['dut_version']}<br>"
- f"csit-ref: {row['job']}/{row['build']}<br>"
- f"hosts: {', '.join(row['hosts'])}"
+ f"csit-ref: {row['job']}/{row['build']}"
+ f"{hosts}"
)
hover.append(hover_itm)
if ttype == "latency":
hover_trend = list()
for avg, stdev, (_, row) in zip(trend_avg, trend_stdev, df.iterrows()):
+ try:
+ hosts = f"<br>hosts: {', '.join(row['hosts'])}"
+ except (KeyError, TypeError):
+ hosts = str()
hover_itm = (
f"dut: {name_lst[0]}<br>"
f"infra: {'-'.join(name_lst[1:5])}<br>"
f"trend [{row[C.UNIT[ttype]]}]: {avg:,.0f}<br>"
f"stdev [{row[C.UNIT[ttype]]}]: {stdev:,.0f}<br>"
f"{row['dut_type']}-ref: {row['dut_version']}<br>"
- f"csit-ref: {row['job']}/{row['build']}<br>"
- f"hosts: {', '.join(row['hosts'])}"
+ f"csit-ref: {row['job']}/{row['build']}"
+ f"{hosts}"
)
if ttype == "latency":
hover_itm = hover_itm.replace("[pps]", "[us]")
marker={
"size": 5,
"color": color,
- "symbol": "circle",
+ "symbol": "circle"
},
text=hover,
hoverinfo="text",
return traces, units
+ def _add_mrr_trials_traces(
+ ttype: str,
+ name: str,
+ df: pd.DataFrame,
+ color: str,
+ nf: float
+ ) -> list:
+ """Add the traces with mrr trials.
+
+ :param ttype: Test type (mrr, mrr-bandwidth).
+ :param name: The test name to be displayed in hover.
+ :param df: Data frame with test data.
+ :param color: The color of the trace.
+ :param nf: The factor used for normalization of the results to
+ CPU frequency set to Constants.NORM_FREQUENCY.
+ :type ttype: str
+ :type name: str
+ :type df: pandas.DataFrame
+ :type color: str
+ :type nf: float
+ :returns: list of Traces
+ :rtype: list
+ """
+ traces = list()
+ x_axis = df["start_time"].tolist()
+ y_data = df[C.VALUE[ttype].replace("avg", "values")].tolist()
+
+ for idx_trial in range(10):
+ y_axis = list()
+ for idx_run in range(len(x_axis)):
+ try:
+ y_axis.append(y_data[idx_run][idx_trial] * nf)
+ except (IndexError, TypeError, ValueError):
+ y_axis.append(nan)
+ traces.append(go.Scatter(
+ x=x_axis,
+ y=y_axis,
+ name=name,
+ mode="markers",
+ marker={
+ "size": 2,
+ "color": color,
+ "symbol": "circle"
+ },
+ showlegend=True,
+ legendgroup=name,
+ hoverinfo="skip"
+ ))
+ return traces
+
+
fig_tput = None
fig_lat = None
fig_band = None
if traces:
if not fig_tput:
fig_tput = go.Figure()
+ if trials and "mrr" in ttype:
+ traces.extend(_add_mrr_trials_traces(
+ ttype,
+ itm["id"],
+ df,
+ get_color(idx),
+ norm_factor
+ ))
fig_tput.add_traces(traces)
- if ttype in ("ndr", "pdr", "mrr", "hoststack-cps", "hoststack-rps"):
+ if ttype in C.TESTS_WITH_BANDWIDTH:
traces, _ = _generate_trending_traces(
f"{ttype}-bandwidth",
itm["id"],
if traces:
if not fig_band:
fig_band = go.Figure()
+ if trials and "mrr" in ttype:
+ traces.extend(_add_mrr_trials_traces(
+ f"{ttype}-bandwidth",
+ itm["id"],
+ df,
+ get_color(idx),
+ norm_factor
+ ))
fig_band.add_traces(traces)
- if ttype in ("pdr", "hoststack-cps", "hoststack-rps"):
+ if ttype in C.TESTS_WITH_LATENCY:
traces, _ = _generate_trending_traces(
"latency" if ttype == "pdr" else "hoststack-latency",
itm["id"],
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