def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame,
- start: datetime, end: datetime, color: str, norm_factor: float) -> list:
+ color: str, norm_factor: float) -> list:
"""Generate the trending traces for the trending graph.
:param ttype: Test type (MRR, NDR, PDR).
:param name: The test name to be displayed as the graph title.
:param df: Data frame with test data.
- :param start: The date (and time) when the selected data starts.
- :param end: The date (and time) when the selected data ends.
:param color: The color of the trace (samples and trend line).
:param norm_factor: 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 start: datetime.datetime
- :type end: datetime.datetime
:type color: str
:type norm_factor: float
:returns: Traces (samples, trending line, anomalies)
df = df.dropna(subset=[C.VALUE[ttype], ])
if df.empty:
return list()
- df = df.loc[((df["start_time"] >= start) & (df["start_time"] <= end))]
if df.empty:
return list()
def graph_trending(data: pd.DataFrame, sel:dict, layout: dict,
- start: datetime, end: datetime, normalize: bool) -> tuple:
+ normalize: bool) -> tuple:
"""Generate the trending graph(s) - MRR, NDR, PDR and for PDR also Latences
(result_latency_forward_pdr_50_avg).
:param data: Data frame with test results.
:param sel: Selected tests.
:param layout: Layout of plot.ly graph.
- :param start: The date (and time) when the selected data starts.
- :param end: The date (and time) when the selected data ends.
:param normalize: If True, the data is normalized to CPU frquency
Constants.NORM_FREQUENCY.
:type data: pandas.DataFrame
:type sel: dict
:type layout: dict
- :type start: datetime.datetime
- :type end: datetype.datetype
:type normalize: bool
:returns: Trending graph(s)
:rtype: tuple(plotly.graph_objects.Figure, plotly.graph_objects.Figure)
else:
norm_factor = 1.0
traces = _generate_trending_traces(
- itm["testtype"], name, df, start, end, get_color(idx), norm_factor
+ itm["testtype"], name, df, get_color(idx), norm_factor
)
if traces:
if not fig_tput:
if itm["testtype"] == "pdr":
traces = _generate_trending_traces(
- "pdr-lat", name, df, start, end, get_color(idx), norm_factor
+ "pdr-lat", name, df, get_color(idx), norm_factor
)
if traces:
if not fig_lat: