X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fdash%2Fapp%2Fpal%2Freport%2Fgraphs.py;h=c5d8f8f2d730a54cf5608fc6091d330adff283b6;hp=76aa8b77930c5287f23bfc388fb3d0e861aa75e7;hb=ae1fe880286d7b0414664bce2b2c7c91c3f543f3;hpb=739e01de7a65045dc42e6c16406a6d054da72f7b diff --git a/resources/tools/dash/app/pal/report/graphs.py b/resources/tools/dash/app/pal/report/graphs.py index 76aa8b7793..c5d8f8f2d7 100644 --- a/resources/tools/dash/app/pal/report/graphs.py +++ b/resources/tools/dash/app/pal/report/graphs.py @@ -20,75 +20,13 @@ import pandas as pd from copy import deepcopy -import hdrh.histogram -import hdrh.codec - - -_NORM_FREQUENCY = 2.0 # [GHz] -_FREQURENCY = { # [GHz] - "2n-aws": 1.000, - "2n-dnv": 2.000, - "2n-clx": 2.300, - "2n-icx": 2.600, - "2n-skx": 2.500, - "2n-tx2": 2.500, - "2n-zn2": 2.900, - "3n-alt": 3.000, - "3n-aws": 1.000, - "3n-dnv": 2.000, - "3n-icx": 2.600, - "3n-skx": 2.500, - "3n-tsh": 2.200 -} - -_VALUE = { - "mrr": "result_receive_rate_rate_values", - "ndr": "result_ndr_lower_rate_value", - "pdr": "result_pdr_lower_rate_value", - "pdr-lat": "result_latency_forward_pdr_50_avg" -} -_UNIT = { - "mrr": "result_receive_rate_rate_unit", - "ndr": "result_ndr_lower_rate_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 = { - "result_latency_forward_pdr_0_hdrh": "No-load.", - "result_latency_reverse_pdr_0_hdrh": "No-load.", - "result_latency_forward_pdr_10_hdrh": "Low-load, 10% PDR.", - "result_latency_reverse_pdr_10_hdrh": "Low-load, 10% PDR.", - "result_latency_forward_pdr_50_hdrh": "Mid-load, 50% PDR.", - "result_latency_reverse_pdr_50_hdrh": "Mid-load, 50% PDR.", - "result_latency_forward_pdr_90_hdrh": "High-load, 90% PDR.", - "result_latency_reverse_pdr_90_hdrh": "High-load, 90% PDR." -} +from ..utils.constants import Constants as C def _get_color(idx: int) -> str: """ """ - _COLORS = ( - "#1A1110", "#DA2647", "#214FC6", "#01786F", "#BD8260", "#FFD12A", - "#A6E7FF", "#738276", "#C95A49", "#FC5A8D", "#CEC8EF", "#391285", - "#6F2DA8", "#FF878D", "#45A27D", "#FFD0B9", "#FD5240", "#DB91EF", - "#44D7A8", "#4F86F7", "#84DE02", "#FFCFF1", "#614051" - ) - return _COLORS[idx % len(_COLORS)] + return C.PLOT_COLORS[idx % len(C.PLOT_COLORS)] def get_short_version(version: str, dut_type: str="vpp") -> str: @@ -182,16 +120,16 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict, continue phy = itm["phy"].split("-") topo_arch = f"{phy[0]}-{phy[1]}" if len(phy) == 4 else str() - norm_factor = (_NORM_FREQUENCY / _FREQURENCY[topo_arch]) \ + norm_factor = (C.NORM_FREQUENCY / C.FREQUENCY[topo_arch]) \ if normalize else 1.0 if itm["testtype"] == "mrr": - y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list()[0] + y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list()[0] y_data = [(y * norm_factor) for y in y_data_raw] if len(y_data) > 0: y_tput_max = \ max(y_data) if max(y_data) > y_tput_max else y_tput_max else: - y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list() + y_data_raw = itm_data[C.VALUE_ITER[itm["testtype"]]].to_list() y_data = [(y * norm_factor) for y in y_data_raw] if y_data: y_tput_max = \ @@ -214,7 +152,7 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict, show_tput = True if itm["testtype"] == "pdr": - y_lat_row = itm_data[_VALUE["pdr-lat"]].to_list() + y_lat_row = itm_data[C.VALUE_ITER["pdr-lat"]].to_list() y_lat = [(y / norm_factor) for y in y_lat_row] if y_lat: y_lat_max = max(y_lat) if max(y_lat) > y_lat_max else y_lat_max @@ -302,73 +240,3 @@ def table_comparison(data: pd.DataFrame, sel:dict, ) return pd.DataFrame() #table - - -def graph_hdrh_latency(data: dict, layout: dict) -> go.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) 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"{_GRAPH_LAT_HDRH_DESC[lat_name]}
" - f"Direction: {('W-E', 'E-W')[idx % 2]}
" - f"Percentile: {prev_perc:.5f}-{percentile:.5f}%
" - 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"{_GRAPH_LAT_HDRH_DESC[lat_name]}
" - f"Direction: {('W-E', 'E-W')[idx % 2]}
" - f"Percentile: {prev_perc:.5f}-{percentile:.5f}%
" - 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="lines", - legendgroup=_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