-# Copyright (c) 2023 Cisco and/or its affiliates.
+# Copyright (c) 2024 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:
"""Plotly Dash HTML layout override.
"""
+
+import logging
import pandas as pd
import dash_bootstrap_components as dbc
from dash.exceptions import PreventUpdate
from dash.dash_table.Format import Format, Scheme
from ast import literal_eval
+from yaml import load, FullLoader, YAMLError
from ..utils.constants import Constants as C
from ..utils.control_panel import ControlPanel
from ..utils.trigger import Trigger
from ..utils.url_processing import url_decode
-from ..utils.utils import generate_options, gen_new_url
+from ..utils.utils import generate_options, gen_new_url, navbar_report, \
+ filter_table_data, show_tooltip
from .tables import comparison_table
"cmp-val-opt": list(),
"cmp-val-dis": True,
"cmp-val-val": str(),
- "normalize-val": list()
+ "normalize-val": list(),
+ "outliers-val": list()
}
# List of comparable parameters.
"infra": "Infrastructure",
"frmsize": "Frame Size",
"core": "Number of Cores",
- "ttype": "Test Type"
+ "ttype": "Measurement"
}
self,
app: Flask,
data_iterative: pd.DataFrame,
- html_layout_file: str
+ html_layout_file: str,
+ tooltip_file: str
) -> None:
"""Initialization:
- save the input parameters,
:param data_iterative: Iterative data to be used in comparison tables.
:param html_layout_file: Path and name of the file specifying the HTML
layout of the dash application.
+ :param tooltip_file: Path and name of the yaml file specifying the
+ tooltips.
:type app: Flask
:type data_iterative: pandas.DataFrame
:type html_layout_file: str
+ :type tooltip_file: str
"""
# Inputs
self._app = app
- self._html_layout_file = html_layout_file
self._data = data_iterative
+ self._html_layout_file = html_layout_file
+ self._tooltip_file = tooltip_file
# Get structure of tests:
tbs = dict()
tbs[dut][dver][infra]["ttype"].append("MRR")
elif row["test_type"] == "ndrpdr":
if "NDR" not in tbs[dut][dver][infra]["ttype"]:
- tbs[dut][dver][infra]["ttype"].extend(("NDR", "PDR", ))
+ tbs[dut][dver][infra]["ttype"].extend(
+ ("NDR", "PDR", "Latency")
+ )
elif row["test_type"] == "hoststack" and \
row["tg_type"] in ("iperf", "vpp"):
if "BPS" not in tbs[dut][dver][infra]["ttype"]:
f"Not possible to open the file {self._html_layout_file}\n{err}"
)
+ try:
+ with open(self._tooltip_file, "r") as file_read:
+ self._tooltips = load(file_read, Loader=FullLoader)
+ except IOError as err:
+ logging.warning(
+ f"Not possible to open the file {self._tooltip_file}\n{err}"
+ )
+ except YAMLError as err:
+ logging.warning(
+ f"An error occurred while parsing the specification file "
+ f"{self._tooltip_file}\n{err}"
+ )
+
# Callbacks:
if self._app is not None and hasattr(self, "callbacks"):
self.callbacks(self._app)
dbc.Row(
id="row-navbar",
class_name="g-0",
- children=[
- self._add_navbar()
- ]
+ children=[navbar_report((False, True, False, False)), ]
),
dbc.Row(
id="row-main",
children=[
dcc.Store(id="store-control-panel"),
dcc.Store(id="store-selected"),
+ dcc.Store(id="store-table-data"),
+ dcc.Store(id="store-filtered-table-data"),
dcc.Location(id="url", refresh=False),
self._add_ctrl_col(),
self._add_plotting_col()
]
+ ),
+ dbc.Offcanvas(
+ class_name="w-75",
+ id="offcanvas-documentation",
+ title="Documentation",
+ placement="end",
+ is_open=False,
+ children=html.Iframe(
+ src=C.URL_DOC_REL_NOTES,
+ width="100%",
+ height="100%"
+ )
)
]
)
]
)
- def _add_navbar(self):
- """Add nav element with navigation panel. It is placed on the top.
-
- :returns: Navigation bar.
- :rtype: dbc.NavbarSimple
- """
- return dbc.NavbarSimple(
- id="navbarsimple-main",
- children=[
- dbc.NavItem(
- dbc.NavLink(
- C.COMP_TITLE,
- disabled=True,
- external_link=True,
- href="#"
- )
- )
- ],
- brand=C.BRAND,
- brand_href="/",
- brand_external_link=True,
- class_name="p-2",
- fluid=True
- )
-
def _add_ctrl_col(self) -> dbc.Col:
"""Add column with controls. It is placed on the left side.
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("DUT"),
+ dbc.InputGroupText(
+ show_tooltip(self._tooltips, "help-dut", "DUT")
+ ),
dbc.Select(
id={"type": "ctrl-dd", "index": "dut"},
placeholder="Select a Device under Test...",
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("CSIT and DUT Version"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-csit-dut",
+ "CSIT and DUT Version"
+ )),
dbc.Select(
id={"type": "ctrl-dd", "index": "dutver"},
placeholder="Select a CSIT and DUT Version...")
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Infra"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-infra",
+ "Infra"
+ )),
dbc.Select(
id={"type": "ctrl-dd", "index": "infra"},
placeholder=\
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Frame Size"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-framesize",
+ "Frame Size"
+ )),
dbc.Checklist(
id={"type": "ctrl-cl", "index": "frmsize"},
inline=True,
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Number of Cores"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-cores",
+ "Number of Cores"
+ )),
dbc.Checklist(
id={"type": "ctrl-cl", "index": "core"},
inline=True,
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Test Type"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-measurement",
+ "Measurement"
+ )),
dbc.Checklist(
id={"type": "ctrl-cl", "index": "ttype"},
inline=True,
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Parameter"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-cmp-parameter",
+ "Parameter"
+ )),
dbc.Select(
id={"type": "ctrl-dd", "index": "cmpprm"},
placeholder="Select a Parameter..."
children=[
dbc.InputGroup(
[
- dbc.InputGroupText("Value"),
+ dbc.InputGroupText(show_tooltip(
+ self._tooltips,
+ "help-cmp-value",
+ "Value"
+ )),
dbc.Select(
id={"type": "ctrl-dd", "index": "cmpval"},
placeholder="Select a Value..."
)
]
- normalize = [
+ processing = [
dbc.Row(
class_name="g-0 p-1",
children=[
dbc.InputGroup(
- dbc.Checklist(
- id="normalize",
- options=[{
- "value": "normalize",
- "label": "Normalize to 2GHz CPU frequency"
- }],
- value=[],
- inline=True,
- class_name="ms-2"
- ),
+ children = [
+ dbc.Checklist(
+ id="normalize",
+ options=[{
+ "value": "normalize",
+ "label": "Normalize to 2GHz CPU frequency"
+ }],
+ value=[],
+ inline=True,
+ class_name="ms-2"
+ ),
+ dbc.Checklist(
+ id="outliers",
+ options=[{
+ "value": "outliers",
+ "label": "Remove Extreme Outliers"
+ }],
+ value=[],
+ inline=True,
+ class_name="ms-2"
+ )
+ ],
style={"align-items": "center"},
size="sm"
)
dbc.Card(
[
dbc.CardHeader(
- html.H5("Normalization")
+ html.H5("Data Manipulations")
),
dbc.CardBody(
- children=normalize,
+ children=processing,
class_name="g-0 p-0"
)
],
)
]
+ @staticmethod
def _get_plotting_area(
- self,
- selected: dict,
- url: str,
- normalize: bool
+ title: str,
+ table: pd.DataFrame,
+ url: str
) -> list:
"""Generate the plotting area with all its content.
- :param selected: Selected parameters of tests.
- :param normalize: If true, the values in tables are normalized.
+ :param title: The title of the comparison table.
+ :param table: Comparison table to be displayed.
:param url: URL to be displayed in the modal window.
- :type selected: dict
- :type normalize: bool
+ :type title: str
+ :type table: pandas.DataFrame
:type url: str
:returns: List of rows with elements to be displayed in the plotting
area.
:rtype: list
"""
- title, df = comparison_table(self._data, selected, normalize)
-
- if df.empty:
+ if table.empty:
return dbc.Row(
dbc.Col(
children=dbc.Alert(
)
cols = list()
- for idx, col in enumerate(df.columns):
+ for idx, col in enumerate(table.columns):
if idx == 0:
cols.append({
"name": ["", col],
children=[
dbc.Col(
children=dash_table.DataTable(
+ id={"type": "table", "index": "comparison"},
columns=cols,
- data=df.to_dict("records"),
+ data=table.to_dict("records"),
merge_duplicate_headers=True,
- editable=True,
- filter_action="native",
+ editable=False,
+ filter_action="custom",
+ filter_query="",
sort_action="native",
sort_mode="multi",
selected_columns=[],
),
dbc.Button(
id="plot-btn-download",
- children="Download Data",
+ children="Download Table",
+ class_name="me-1",
+ color="info",
+ style={
+ "text-transform": "none",
+ "padding": "0rem 1rem"
+ }
+ ),
+ dcc.Download(id="download-iterative-data"),
+ dbc.Button(
+ id="plot-btn-download-raw",
+ children="Download Raw Data",
class_name="me-1",
color="info",
style={
"padding": "0rem 1rem"
}
),
- dcc.Download(id="download-iterative-data")
+ dcc.Download(id="download-raw-data")
],
className=\
"d-grid gap-0 d-md-flex justify-content-md-end"
[
Output("store-control-panel", "data"),
Output("store-selected", "data"),
+ Output("store-table-data", "data"),
+ Output("store-filtered-table-data", "data"),
Output("plotting-area", "children"),
+ Output({"type": "table", "index": ALL}, "data"),
Output({"type": "ctrl-dd", "index": "dut"}, "value"),
Output({"type": "ctrl-dd", "index": "dutver"}, "options"),
Output({"type": "ctrl-dd", "index": "dutver"}, "disabled"),
Output({"type": "ctrl-dd", "index": "cmpval"}, "options"),
Output({"type": "ctrl-dd", "index": "cmpval"}, "disabled"),
Output({"type": "ctrl-dd", "index": "cmpval"}, "value"),
- Output("normalize", "value")
+ Output("normalize", "value"),
+ Output("outliers", "value")
],
[
State("store-control-panel", "data"),
- State("store-selected", "data")
+ State("store-selected", "data"),
+ State("store-table-data", "data"),
+ State("store-filtered-table-data", "data"),
+ State({"type": "table", "index": ALL}, "data")
],
[
Input("url", "href"),
Input("normalize", "value"),
+ Input("outliers", "value"),
+ Input({"type": "table", "index": ALL}, "filter_query"),
Input({"type": "ctrl-dd", "index": ALL}, "value"),
Input({"type": "ctrl-cl", "index": ALL}, "value"),
Input({"type": "ctrl-btn", "index": ALL}, "n_clicks")
def _update_application(
control_panel: dict,
selected: dict,
+ store_table_data: list,
+ filtered_data: list,
+ table_data: list,
href: str,
normalize: list,
+ outliers: bool,
+ table_filter: str,
*_
) -> tuple:
"""Update the application when the event is detected.
r_sel = selected["reference"]["selection"]
c_sel = selected["compare"]
normalize = literal_eval(url_params["norm"][0])
+ try: # Necessary for backward compatibility
+ outliers = literal_eval(url_params["outliers"][0])
+ except (KeyError, IndexError, AttributeError):
+ outliers = list()
process_url = bool(
(selected["reference"]["set"] == True) and
(c_sel["set"] == True)
)
- except (KeyError, IndexError):
+ except (KeyError, IndexError, AttributeError):
pass
if process_url:
ctrl_panel.set({
[r_sel["infra"]]["ttype"]
),
"ttype-val": r_sel["ttype"],
- "normalize-val": normalize
+ "normalize-val": normalize,
+ "outliers-val": outliers
})
opts = list()
for itm, label in CMP_PARAMS.items():
elif trigger.type == "normalize":
ctrl_panel.set({"normalize-val": normalize})
on_draw = True
+ elif trigger.type == "outliers":
+ ctrl_panel.set({"outliers-val": outliers})
+ on_draw = True
elif trigger.type == "ctrl-dd":
if trigger.idx == "dut":
try:
for itm in ctrl_panel.get(f"{value}-opt"):
set_val = ctrl_panel.get(f"{value}-val")
if isinstance(set_val, list):
+ if itm["value"] == "Latency":
+ continue
if itm["value"] not in set_val:
opts.append(itm)
else:
if all((ctrl_panel.get("core-val"),
ctrl_panel.get("frmsize-val"),
ctrl_panel.get("ttype-val"), )):
+ if "Latency" in ctrl_panel.get("ttype-val"):
+ ctrl_panel.set({"ttype-val": ["Latency", ]})
opts = list()
for itm, label in CMP_PARAMS.items():
+ if "Latency" in ctrl_panel.get("ttype-val") and \
+ itm == "ttype":
+ continue
if len(ctrl_panel.get(f"{itm}-opt")) > 1:
if isinstance(ctrl_panel.get(f"{itm}-val"), list):
if len(ctrl_panel.get(f"{itm}-opt")) == \
"cmp-val-dis": True,
"cmp-val-val": str()
})
+ elif trigger.type == "table" and trigger.idx == "comparison":
+ filtered_data = filter_table_data(
+ store_table_data,
+ table_filter[0]
+ )
+ table_data = [filtered_data, ]
if all((on_draw, selected["reference"]["set"],
selected["compare"]["set"], )):
- plotting_area = self._get_plotting_area(
+ title, table = comparison_table(
+ data=self._data,
selected=selected,
- normalize=bool(normalize),
+ normalize=normalize,
+ format="html",
+ remove_outliers=outliers
+ )
+ plotting_area = self._get_plotting_area(
+ title=title,
+ table=table,
url=gen_new_url(
parsed_url,
- params={"selected": selected, "norm": normalize}
+ params={
+ "selected": selected,
+ "norm": normalize,
+ "outliers": outliers
+ }
)
)
+ store_table_data = table.to_dict("records")
+ filtered_data = store_table_data
+ if table_data:
+ table_data = [store_table_data, ]
- ret_val = [ctrl_panel.panel, selected, plotting_area]
+ ret_val = [
+ ctrl_panel.panel,
+ selected,
+ store_table_data,
+ filtered_data,
+ plotting_area,
+ table_data
+ ]
ret_val.extend(ctrl_panel.values)
return ret_val
@app.callback(
Output("download-iterative-data", "data"),
- State("store-selected", "data"),
- State("normalize", "value"),
+ State("store-table-data", "data"),
+ State("store-filtered-table-data", "data"),
Input("plot-btn-download", "n_clicks"),
prevent_initial_call=True
)
- def _download_trending_data(selected: dict, normalize: list, _: int):
+ def _download_comparison_data(
+ table_data: list,
+ filtered_table_data: list,
+ _: int
+ ) -> dict:
"""Download the data.
- :param selected: List of tests selected by user stored in the
- browser.
- :param normalize: If set, the data is normalized to 2GHz CPU
- frequency.
- :type selected: list
- :type normalize: list
+ :param table_data: Original unfiltered table data.
+ :param filtered_table_data: Filtered table data.
+ :type table_data: list
+ :type filtered_table_data: list
:returns: dict of data frame content (base64 encoded) and meta data
used by the Download component.
:rtype: dict
"""
- if not selected:
+ if not table_data:
raise PreventUpdate
- _, table = comparison_table(self._data, selected, normalize, "csv")
+ if filtered_table_data:
+ table = pd.DataFrame.from_records(filtered_table_data)
+ else:
+ table = pd.DataFrame.from_records(table_data)
return dcc.send_data_frame(table.to_csv, C.COMP_DOWNLOAD_FILE_NAME)
+
+ @app.callback(
+ Output("download-raw-data", "data"),
+ State("store-selected", "data"),
+ Input("plot-btn-download-raw", "n_clicks"),
+ prevent_initial_call=True
+ )
+ def _download_raw_comparison_data(selected: dict, _: int) -> dict:
+ """Download the data.
+
+ :param selected: Selected tests.
+ :type selected: dict
+ :returns: dict of data frame content (base64 encoded) and meta data
+ used by the Download component.
+ :rtype: dict
+ """
+
+ if not selected:
+ raise PreventUpdate
+
+ _, table = comparison_table(
+ data=self._data,
+ selected=selected,
+ normalize=False,
+ remove_outliers=False,
+ raw_data=True
+ )
+
+ return dcc.send_data_frame(
+ table.dropna(how="all", axis=1).to_csv,
+ f"raw_{C.COMP_DOWNLOAD_FILE_NAME}"
+ )
+
+ @app.callback(
+ Output("offcanvas-documentation", "is_open"),
+ Input("btn-documentation", "n_clicks"),
+ State("offcanvas-documentation", "is_open")
+ )
+ def toggle_offcanvas_documentation(n_clicks, is_open):
+ if n_clicks:
+ return not is_open
+ return is_open
Code Review / csit.git / blobdiff