X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fdash%2Fapp%2Fpal%2Freport%2Fgraphs.py;fp=resources%2Ftools%2Fdash%2Fapp%2Fpal%2Freport%2Fgraphs.py;h=751eb34006f4bb1ade0615073690b317e216bcd0;hp=0000000000000000000000000000000000000000;hb=3343fe81729eb4005319ca15b1e6881630d38c5b;hpb=099b961a0aa234f870ff60e36492e324bb2abe11

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