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authorTibor Frank <tifrank@cisco.com>2023-04-11 12:56:56 +0200
committerTibor Frank <tifrank@cisco.com>2023-04-12 05:49:41 +0000
commit5edaac881f42de498d92efca3fbbfab8e2e47e71 (patch)
tree0c9678e2362b46f0c5060ae72835a91498ea9f21 /csit.infra.dash/app/cdash/trending/graphs.py
parent757fc06136fe9ea67b1a4f9b2aa43d70a50533b1 (diff)
C-Dash: Add latency hdrh for iterative data
Signed-off-by: Tibor Frank <tifrank@cisco.com> Change-Id: I4557c724d1d2b2eab355d03f0339c56660253360
Diffstat (limited to 'csit.infra.dash/app/cdash/trending/graphs.py')
-rw-r--r--csit.infra.dash/app/cdash/trending/graphs.py105
1 files changed, 2 insertions, 103 deletions
diff --git a/csit.infra.dash/app/cdash/trending/graphs.py b/csit.infra.dash/app/cdash/trending/graphs.py
index 10ad745e1e..fc26f8bd79 100644
--- a/csit.infra.dash/app/cdash/trending/graphs.py
+++ b/csit.infra.dash/app/cdash/trending/graphs.py
@@ -17,32 +17,8 @@
import plotly.graph_objects as go
import pandas as pd
-import hdrh.histogram
-import hdrh.codec
-
from ..utils.constants import Constants as C
-from ..utils.utils import classify_anomalies, get_color
-
-
-def _get_hdrh_latencies(row: pd.Series, name: str) -> dict:
- """Get the HDRH latencies from the test data.
-
- :param row: A row fron the data frame with test data.
- :param name: The test name to be displayed as the graph title.
- :type row: pandas.Series
- :type name: str
- :returns: Dictionary with HDRH latencies.
- :rtype: dict
- """
-
- latencies = {"name": name}
- for key in C.LAT_HDRH:
- try:
- latencies[key] = row[key]
- except KeyError:
- return None
-
- return latencies
+from ..utils.utils import classify_anomalies, get_color, get_hdrh_latencies
def select_trending_data(data: pd.DataFrame, itm: dict) -> pd.DataFrame:
@@ -189,7 +165,7 @@ def graph_trending(
).replace("<stdev>", stdev).replace("<additional-info>", add_info)
hover.append(hover_itm)
if ttype == "latency":
- customdata_samples.append(_get_hdrh_latencies(row, name))
+ customdata_samples.append(get_hdrh_latencies(row, name))
customdata.append({"name": name})
else:
customdata_samples.append(
@@ -367,83 +343,6 @@ def graph_trending(
return fig_tput, fig_lat
-def graph_hdrh_latency(data: dict, layout: dict) -> go.Figure:
- """Generate HDR Latency histogram graphs.
-
- :param data: HDRH data.
- :param layout: Layout of plot.ly graph.
- :type data: dict
- :type layout: dict
- :returns: HDR latency Histogram.
- :rtype: plotly.graph_objects.Figure
- """
-
- fig = None
-
- traces = list()
- for idx, (lat_name, lat_hdrh) in enumerate(data.items()):
- try:
- decoded = hdrh.histogram.HdrHistogram.decode(lat_hdrh)
- except (hdrh.codec.HdrLengthException, TypeError):
- continue
- previous_x = 0.0
- prev_perc = 0.0
- xaxis = list()
- yaxis = list()
- hovertext = list()
- for item in decoded.get_recorded_iterator():
- # The real value is "percentile".
- # For 100%, we cut that down to "x_perc" to avoid
- # infinity.
- percentile = item.percentile_level_iterated_to
- x_perc = min(percentile, C.PERCENTILE_MAX)
- xaxis.append(previous_x)
- yaxis.append(item.value_iterated_to)
- hovertext.append(
- f"<b>{C.GRAPH_LAT_HDRH_DESC[lat_name]}</b><br>"
- f"Direction: {('W-E', 'E-W')[idx % 2]}<br>"
- f"Percentile: {prev_perc:.5f}-{percentile:.5f}%<br>"
- f"Latency: {item.value_iterated_to}uSec"
- )
- next_x = 100.0 / (100.0 - x_perc)
- xaxis.append(next_x)
- yaxis.append(item.value_iterated_to)
- hovertext.append(
- f"<b>{C.GRAPH_LAT_HDRH_DESC[lat_name]}</b><br>"
- f"Direction: {('W-E', 'E-W')[idx % 2]}<br>"
- f"Percentile: {prev_perc:.5f}-{percentile:.5f}%<br>"
- f"Latency: {item.value_iterated_to}uSec"
- )
- previous_x = next_x
- prev_perc = percentile
-
- traces.append(
- go.Scatter(
- x=xaxis,
- y=yaxis,
- name=C.GRAPH_LAT_HDRH_DESC[lat_name],
- mode="lines",
- legendgroup=C.GRAPH_LAT_HDRH_DESC[lat_name],
- showlegend=bool(idx % 2),
- line=dict(
- color=get_color(int(idx/2)),
- dash="solid",
- width=1 if idx % 2 else 2
- ),
- hovertext=hovertext,
- hoverinfo="text"
- )
- )
- if traces:
- fig = go.Figure()
- fig.add_traces(traces)
- layout_hdrh = layout.get("plot-hdrh-latency", None)
- if lat_hdrh:
- fig.update_layout(layout_hdrh)
-
- return fig
-
-
def graph_tm_trending(data: pd.DataFrame, layout: dict) -> list:
"""Generates one trending graph per test, each graph includes all selected
metrics.