+
+ @app.callback(
+ Output("offcanvas-details", "is_open"),
+ Output("offcanvas-details", "children"),
+ State("store-selected", "data"),
+ State("store-filtered-table-data", "data"),
+ State("normalize", "value"),
+ State("outliers", "value"),
+ Input({"type": "table", "index": ALL}, "active_cell"),
+ prevent_initial_call=True
+ )
+ def show_test_data(cp_sel, table, normalize, outliers, *_):
+ """Show offcanvas with graphs and tables based on selected test(s).
+ """
+
+ trigger = Trigger(callback_context.triggered)
+ if not all((trigger.value, cp_sel["reference"]["set"], \
+ cp_sel["compare"]["set"])):
+ raise PreventUpdate
+
+ try:
+ test_name = pd.DataFrame.from_records(table).\
+ iloc[[trigger.value["row"]]]["Test Name"].iloc[0]
+ dut = cp_sel["reference"]["selection"]["dut"]
+ rls, dutver = cp_sel["reference"]["selection"]["dutver"].\
+ split("-", 1)
+ phy = cp_sel["reference"]["selection"]["infra"]
+ framesize, core, test_id = test_name.split("-", 2)
+ test, ttype = test_id.rsplit("-", 1)
+ ttype = "pdr" if ttype == "latency" else ttype
+ l_phy = phy.split("-")
+ tb = "-".join(l_phy[:2])
+ nic = l_phy[2]
+ stype = "ndrpdr" if ttype in ("ndr", "pdr") else ttype
+ except(KeyError, IndexError, AttributeError, ValueError):
+ raise PreventUpdate
+
+ df = pd.DataFrame(self._data.loc[(
+ (self._data["dut_type"] == dut) &
+ (self._data["dut_version"] == dutver) &
+ (self._data["release"] == rls)
+ )])
+ df = df[df.job.str.endswith(tb)]
+ df = df[df.test_id.str.contains(
+ f"{nic}.*{test}-{stype}", regex=True
+ )]
+ if df.empty:
+ raise PreventUpdate
+
+ l_test_id = df["test_id"].iloc[0].split(".")
+ area = ".".join(l_test_id[3:-2])
+
+ r_sel = {
+ "id": f"{test}-{ttype}",
+ "rls": rls,
+ "dut": dut,
+ "dutver": dutver,
+ "phy": phy,
+ "area": area,
+ "test": test,
+ "framesize": framesize,
+ "core": core,
+ "testtype": ttype
+ }
+
+ c_sel = deepcopy(r_sel)
+ param = cp_sel["compare"]["parameter"]
+ val = cp_sel["compare"]["value"].lower()
+ if param == "dutver":
+ c_sel["rls"], c_sel["dutver"] = val.split("-", 1)
+ elif param == "ttype":
+ c_sel["id"] = f"{test}-{val}"
+ c_sel["testtype"] = val
+ elif param == "infra":
+ c_sel["phy"] = val
+ else:
+ c_sel[param] = val
+
+ r_sel["id"] = "-".join(
+ (r_sel["phy"], r_sel["framesize"], r_sel["core"], r_sel["id"])
+ )
+ c_sel["id"] = "-".join(
+ (c_sel["phy"], c_sel["framesize"], c_sel["core"], c_sel["id"])
+ )
+ selected = [r_sel, c_sel]
+
+ indexes = ("tput", "bandwidth", "lat")
+ graphs = graph_iterative(
+ self._data,
+ selected,
+ self._graph_layout,
+ bool(normalize),
+ bool(outliers)
+ )
+ cols = list()
+ for graph, idx in zip(graphs, indexes):
+ if graph:
+ cols.append(dbc.Col(dcc.Graph(
+ figure=graph,
+ id={"type": "graph-iter", "index": idx},
+ )))
+ if not cols:
+ cols="No data."
+ ret_val = [
+ dbc.Row(
+ class_name="g-0 p-0",
+ children=dbc.Alert(test, color="info"),
+ ),
+ dbc.Row(class_name="g-0 p-0", children=cols)
+ ]
+
+ return True, ret_val
+
+ @app.callback(
+ Output("metadata-tput-lat", "children"),
+ Output("metadata-hdrh-graph", "children"),
+ Output("offcanvas-metadata", "is_open"),
+ Input({"type": "graph-iter", "index": ALL}, "clickData"),
+ prevent_initial_call=True
+ )
+ def _show_metadata_from_graph(iter_data: dict) -> tuple:
+ """Generates the data for the offcanvas displayed when a particular
+ point in a graph is clicked on.
+ """
+
+ trigger = Trigger(callback_context.triggered)
+ if not trigger.value:
+ raise PreventUpdate
+
+ if trigger.type == "graph-iter":
+ return show_iterative_graph_data(
+ trigger, iter_data, self._graph_layout)
+ else:
+ raise PreventUpdate
Code Review / csit.git / commitdiff