diff options
Diffstat (limited to 'resources/tools/dash/app/pal/trending/graphs.py')
| -rw-r--r-- | resources/tools/dash/app/pal/trending/graphs.py | 167 |
1 files changed, 133 insertions, 34 deletions
diff --git a/resources/tools/dash/app/pal/trending/graphs.py b/resources/tools/dash/app/pal/trending/graphs.py index b71c3271a0..0760d9cc80 100644 --- a/resources/tools/dash/app/pal/trending/graphs.py +++ b/resources/tools/dash/app/pal/trending/graphs.py @@ -14,11 +14,13 @@ """ """ - import plotly.graph_objects as go import pandas as pd import re +import hdrh.histogram +import hdrh.codec + from datetime import datetime from numpy import isnan @@ -26,29 +28,10 @@ from ..jumpavg import classify _COLORS = ( - u"#1A1110", - u"#DA2647", - u"#214FC6", - u"#01786F", - u"#BD8260", - u"#FFD12A", - u"#A6E7FF", - u"#738276", - u"#C95A49", - u"#FC5A8D", - u"#CEC8EF", - u"#391285", - u"#6F2DA8", - u"#FF878D", - u"#45A27D", - u"#FFD0B9", - u"#FD5240", - u"#DB91EF", - u"#44D7A8", - u"#4F86F7", - u"#84DE02", - u"#FFCFF1", - u"#614051" + u"#1A1110", u"#DA2647", u"#214FC6", u"#01786F", u"#BD8260", u"#FFD12A", + u"#A6E7FF", u"#738276", u"#C95A49", u"#FC5A8D", u"#CEC8EF", u"#391285", + u"#6F2DA8", u"#FF878D", u"#45A27D", u"#FFD0B9", u"#FD5240", u"#DB91EF", + u"#44D7A8", u"#4F86F7", u"#84DE02", u"#FFCFF1", u"#614051" ) _ANOMALY_COLOR = { u"regression": 0.0, @@ -85,6 +68,44 @@ _UNIT = { "pdr": "result_pdr_lower_rate_unit", "pdr-lat": "result_latency_forward_pdr_50_unit" } +_LAT_HDRH = ( # Do not change the order + "result_latency_forward_pdr_0_hdrh", + "result_latency_reverse_pdr_0_hdrh", + "result_latency_forward_pdr_10_hdrh", + "result_latency_reverse_pdr_10_hdrh", + "result_latency_forward_pdr_50_hdrh", + "result_latency_reverse_pdr_50_hdrh", + "result_latency_forward_pdr_90_hdrh", + "result_latency_reverse_pdr_90_hdrh", +) +# This value depends on latency stream rate (9001 pps) and duration (5s). +# Keep it slightly higher to ensure rounding errors to not remove tick mark. +PERCENTILE_MAX = 99.999501 + +_GRAPH_LAT_HDRH_DESC = { + u"result_latency_forward_pdr_0_hdrh": u"No-load.", + u"result_latency_reverse_pdr_0_hdrh": u"No-load.", + u"result_latency_forward_pdr_10_hdrh": u"Low-load, 10% PDR.", + u"result_latency_reverse_pdr_10_hdrh": u"Low-load, 10% PDR.", + u"result_latency_forward_pdr_50_hdrh": u"Mid-load, 50% PDR.", + u"result_latency_reverse_pdr_50_hdrh": u"Mid-load, 50% PDR.", + u"result_latency_forward_pdr_90_hdrh": u"High-load, 90% PDR.", + u"result_latency_reverse_pdr_90_hdrh": u"High-load, 90% PDR." +} + + +def _get_hdrh_latencies(row: pd.Series, name: str) -> dict: + """ + """ + + latencies = {"name": name} + for key in _LAT_HDRH: + try: + latencies[key] = row[key] + except KeyError: + return None + + return latencies def _classify_anomalies(data): @@ -137,8 +158,8 @@ def _classify_anomalies(data): return classification, avgs, stdevs -def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, - end: datetime): +def graph_trending_tput(data: pd.DataFrame, sel:dict, layout: dict, + start: datetime, end: datetime) -> tuple: """ """ @@ -146,7 +167,7 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, return None, None def _generate_traces(ttype: str, name: str, df: pd.DataFrame, - start: datetime, end: datetime, color: str): + start: datetime, end: datetime, color: str) -> list: df = df.dropna(subset=[_VALUE[ttype], ]) if df.empty: @@ -159,6 +180,7 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, ) hover = list() + customdata = list() for _, row in df.iterrows(): hover_itm = ( f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>" @@ -178,6 +200,8 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, "<prop>", "latency" if ttype == "pdr-lat" else "average" ).replace("<stdev>", stdev) hover.append(hover_itm) + if ttype == "pdr-lat": + customdata.append(_get_hdrh_latencies(row, name)) hover_trend = list() for avg, stdev in zip(trend_avg, trend_stdev): @@ -207,6 +231,7 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, hoverinfo=u"text+name", showlegend=True, legendgroup=name, + customdata=customdata ), go.Scatter( # Trend line x=x_axis, @@ -259,9 +284,9 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, u"len": 0.8, u"title": u"Circles Marking Data Classification", u"titleside": u"right", - u"titlefont": { - u"size": 14 - }, + # u"titlefont": { + # u"size": 14 + # }, u"tickmode": u"array", u"tickvals": [0.167, 0.500, 0.833], u"ticktext": _TICK_TEXT_LAT \ @@ -319,8 +344,7 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, if traces: if not fig_tput: fig_tput = go.Figure() - for trace in traces: - fig_tput.add_trace(trace) + fig_tput.add_traces(traces) if itm["testtype"] == "pdr": traces = _generate_traces( @@ -329,8 +353,7 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, if traces: if not fig_lat: fig_lat = go.Figure() - for trace in traces: - fig_lat.add_trace(trace) + fig_lat.add_traces(traces) if fig_tput: fig_tput.update_layout(layout.get("plot-trending-tput", dict())) @@ -338,3 +361,79 @@ def trending_tput(data: pd.DataFrame, sel:dict, layout: dict, start: datetime, fig_lat.update_layout(layout.get("plot-trending-lat", dict())) return fig_tput, fig_lat + + +def graph_hdrh_latency(data: dict, layout: dict) -> go.Figure: + """ + """ + + fig = None + + try: + name = data.pop("name") + except (KeyError, AttributeError): + return 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) as err: + 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, PERCENTILE_MAX) + xaxis.append(previous_x) + yaxis.append(item.value_iterated_to) + hovertext.append( + f"<b>{_GRAPH_LAT_HDRH_DESC[lat_name]}</b><br>" + f"Direction: {(u'W-E', u'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>{_GRAPH_LAT_HDRH_DESC[lat_name]}</b><br>" + f"Direction: {(u'W-E', u'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=_GRAPH_LAT_HDRH_DESC[lat_name], + mode=u"lines", + legendgroup=_GRAPH_LAT_HDRH_DESC[lat_name], + showlegend=bool(idx % 2), + line=dict( + color=_COLORS[int(idx/2)], + dash=u"solid", + width=1 if idx % 2 else 2 + ), + hovertext=hovertext, + hoverinfo=u"text" + ) + ) + if traces: + fig = go.Figure() + fig.add_traces(traces) + layout_hdrh = layout.get("plot-hdrh-latency", None) + if lat_hdrh: + layout_hdrh["title"]["text"] = f"<b>{name}</b>" + fig.update_layout(layout_hdrh) + + return fig |