diff options
Diffstat (limited to 'csit.infra.dash/app/cdash/trending/graphs.py')
| -rw-r--r-- | csit.infra.dash/app/cdash/trending/graphs.py | 75 |
1 files changed, 73 insertions, 2 deletions
diff --git a/csit.infra.dash/app/cdash/trending/graphs.py b/csit.infra.dash/app/cdash/trending/graphs.py index 1a507dfeea..b55b18a444 100644 --- a/csit.infra.dash/app/cdash/trending/graphs.py +++ b/csit.infra.dash/app/cdash/trending/graphs.py @@ -18,6 +18,8 @@ import logging 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 @@ -73,7 +75,8 @@ def graph_trending( data: pd.DataFrame, sel: dict, layout: dict, - normalize: bool=False + 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). @@ -83,10 +86,12 @@ def graph_trending( :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) """ @@ -279,7 +284,7 @@ def graph_trending( marker={ "size": 5, "color": color, - "symbol": "circle", + "symbol": "circle" }, text=hover, hoverinfo="text", @@ -369,6 +374,56 @@ def graph_trending( 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: + 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 + )) + return traces + + fig_tput = None fig_lat = None fig_band = None @@ -401,6 +456,14 @@ def graph_trending( 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 C.TESTS_WITH_BANDWIDTH: @@ -414,6 +477,14 @@ def graph_trending( 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 C.TESTS_WITH_LATENCY: |