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author | 2022-05-17 14:30:37 +0200 | |
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committer | 2022-05-19 11:58:43 +0000 | |
commit | 3343fe81729eb4005319ca15b1e6881630d38c5b (patch) | |
tree | fd172c3ba1146d5ddffb3ced53e4bed0e7ad2a1c /resources/tools/dash/app/pal/report/graphs.py | |
parent | 099b961a0aa234f870ff60e36492e324bb2abe11 (diff) |
feat(uti): Add iterative data
Change-Id: Iaa7253b377f019235289f6bbf48eafd850a2dfc8
Signed-off-by: Tibor Frank <tifrank@cisco.com>
Diffstat (limited to 'resources/tools/dash/app/pal/report/graphs.py')
-rw-r--r-- | resources/tools/dash/app/pal/report/graphs.py | 224 |
1 files changed, 224 insertions, 0 deletions
diff --git a/resources/tools/dash/app/pal/report/graphs.py b/resources/tools/dash/app/pal/report/graphs.py new file mode 100644 index 0000000000..751eb34006 --- /dev/null +++ b/resources/tools/dash/app/pal/report/graphs.py @@ -0,0 +1,224 @@ +# Copyright (c) 2022 Cisco and/or its affiliates. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at: +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" +""" + +import plotly.graph_objects as go +import pandas as pd + +import hdrh.histogram +import hdrh.codec + + +_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" +) +_VALUE = { + "mrr": "result_receive_rate_rate_avg", + "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 = { + 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 select_iterative_data(data: pd.DataFrame, itm:dict) -> pd.DataFrame: + """ + """ + + phy = itm["phy"].split("-") + if len(phy) == 4: + topo, arch, nic, drv = phy + if drv == "dpdk": + drv = "" + else: + drv += "-" + drv = drv.replace("_", "-") + else: + return None + + core = str() if itm["dut"] == "trex" else f"{itm['core']}" + ttype = "ndrpdr" if itm["testtype"] in ("ndr", "pdr") else itm["testtype"] + dut = "none" if itm["dut"] == "trex" else itm["dut"].upper() + + df = data.loc[( + (data["dut_type"] == dut) & + (data["test_type"] == ttype) & + (data["passed"] == True) + )] + df = df[df.job.str.endswith(f"{topo}-{arch}")] + df = df[df.test_id.str.contains( + f"^.*[.|-]{nic}.*{itm['framesize']}-{core}-{drv}{itm['test']}-{ttype}$", + regex=True + )].sort_values(by="start_time", ignore_index=True) + + return df + + +def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict) -> tuple: + """ + """ + + fig_tput = go.Figure() + fig_tsa = go.Figure() + + return fig_tput, fig_tsa + + +def table_comparison(data: pd.DataFrame, sel:dict) -> pd.DataFrame: + """ + """ + table = pd.DataFrame( + { + "Test Case": [ + "64b-2t1c-avf-eth-l2xcbase-eth-2memif-1dcr", + "64b-2t1c-avf-eth-l2xcbase-eth-2vhostvr1024-1vm-vppl2xc", + "64b-2t1c-avf-ethip4udp-ip4base-iacl50sl-10kflows", + "78b-2t1c-avf-ethip6-ip6scale2m-rnd "], + "2106.0-8": [ + "14.45 +- 0.08", + "9.63 +- 0.05", + "9.7 +- 0.02", + "8.95 +- 0.06"], + "2110.0-8": [ + "14.45 +- 0.08", + "9.63 +- 0.05", + "9.7 +- 0.02", + "8.95 +- 0.06"], + "2110.0-9": [ + "14.45 +- 0.08", + "9.63 +- 0.05", + "9.7 +- 0.02", + "8.95 +- 0.06"], + "2202.0-9": [ + "14.45 +- 0.08", + "9.63 +- 0.05", + "9.7 +- 0.02", + "8.95 +- 0.06"], + "2110.0-9 vs 2110.0-8": [ + "-0.23 +- 0.62", + "-1.37 +- 1.3", + "+0.08 +- 0.2", + "-2.16 +- 0.83"], + "2202.0-9 vs 2110.0-9": [ + "+6.95 +- 0.72", + "+5.35 +- 1.26", + "+4.48 +- 1.48", + "+4.09 +- 0.95"] + } +) + + return 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"<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: + fig.update_layout(layout_hdrh) + + return fig |