diff options
Diffstat (limited to 'resources/tools/dash/app/pal/trending/graphs.py')
| -rw-r--r-- | resources/tools/dash/app/pal/trending/graphs.py | 67 |
1 files changed, 62 insertions, 5 deletions
diff --git a/resources/tools/dash/app/pal/trending/graphs.py b/resources/tools/dash/app/pal/trending/graphs.py index 4cd8285f72..06bea25466 100644 --- a/resources/tools/dash/app/pal/trending/graphs.py +++ b/resources/tools/dash/app/pal/trending/graphs.py @@ -27,7 +27,14 @@ 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} @@ -41,7 +48,15 @@ def _get_hdrh_latencies(row: pd.Series, name: str) -> dict: def select_trending_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame: - """ + """Select the data for graphs from the provided data frame. + + :param data: Data frame with data for graphs. + :param itm: Item (in this case job name) which data will be selected from + the input data frame. + :type data: pandas.DataFrame + :type itm: str + :returns: A data frame with selected data. + :rtype: pandas.DataFrame """ phy = itm["phy"].split("-") @@ -85,7 +100,25 @@ def select_trending_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame: def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame, start: datetime, end: datetime, 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) + :rtype: list """ df = df.dropna(subset=[C.VALUE[ttype], ]) @@ -242,7 +275,24 @@ def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame, def graph_trending(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, end: datetime, 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) """ if not sel: @@ -291,7 +341,14 @@ def graph_trending(data: pd.DataFrame, sel:dict, layout: dict, 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 |