diff options
Diffstat (limited to 'resources/tools/dash/app/pal')
| -rw-r--r-- | resources/tools/dash/app/pal/stats/graphs.py | 12 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/stats/layout.py | 293 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/trending/graphs.py | 10 |
3 files changed, 287 insertions, 28 deletions
diff --git a/resources/tools/dash/app/pal/stats/graphs.py b/resources/tools/dash/app/pal/stats/graphs.py index 2fabf8e6ae..37fc1b2e73 100644 --- a/resources/tools/dash/app/pal/stats/graphs.py +++ b/resources/tools/dash/app/pal/stats/graphs.py @@ -40,8 +40,10 @@ def graph_statistics(df: pd.DataFrame, job:str, layout: dict, if data.empty: return None, None - x_axis = [d for d in data["start_time"] if d >= start and d <= end] - if not x_axis: + data = data.loc[( + (data["start_time"] >= start) & (data["start_time"] <= end) + )] + if data.empty: return None, None hover = list() @@ -62,7 +64,7 @@ def graph_statistics(df: pd.DataFrame, job:str, layout: dict, # Job durations: fig_duration = go.Figure( data=go.Scatter( - x=x_axis, + x=data["start_time"], y=data["duration"], name=u"Duration", text=hover, @@ -87,14 +89,14 @@ def graph_statistics(df: pd.DataFrame, job:str, layout: dict, fig_passed = go.Figure( data=[ go.Bar( - x=x_axis, + x=data["start_time"], y=data["passed"], name=u"Passed", hovertext=hover, hoverinfo=u"text" ), go.Bar( - x=x_axis, + x=data["start_time"], y=data["failed"], name=u"Failed", hovertext=hover, diff --git a/resources/tools/dash/app/pal/stats/layout.py b/resources/tools/dash/app/pal/stats/layout.py index 0c5c22e81b..405fd8b1a3 100644 --- a/resources/tools/dash/app/pal/stats/layout.py +++ b/resources/tools/dash/app/pal/stats/layout.py @@ -21,10 +21,11 @@ from flask import Flask from dash import dcc from dash import html from dash import callback_context, no_update -from dash import Input, Output +from dash import Input, Output, State from dash.exceptions import PreventUpdate from yaml import load, FullLoader, YAMLError from datetime import datetime, timedelta +from copy import deepcopy from ..data.data import Data from .graphs import graph_statistics @@ -34,6 +35,8 @@ class Layout: """ """ + DEFAULT_JOB = "csit-vpp-perf-mrr-daily-master-2n-icx" + def __init__(self, app: Flask, html_layout_file: str, spec_file: str, graph_layout_file: str, data_spec_file: str, time_period: int=None) -> None: @@ -68,6 +71,36 @@ class Layout: self._time_period = data_time_period self._jobs = sorted(list(data_stats["job"].unique())) + job_info = { + "job": list(), + "dut": list(), + "ttype": list(), + "cadence": list(), + "tbed": list() + } + for job in self._jobs: + lst_job = job.split("-") + job_info["job"].append(job) + job_info["dut"].append(lst_job[1]) + job_info["ttype"].append(lst_job[3]) + job_info["cadence"].append(lst_job[4]) + job_info["tbed"].append("-".join(lst_job[-2:])) + self.df_job_info = pd.DataFrame.from_dict(job_info) + + lst_job = self.DEFAULT_JOB.split("-") + self._default = { + "job": self.DEFAULT_JOB, + "dut": lst_job[1], + "ttype": lst_job[3], + "cadence": lst_job[4], + "tbed": "-".join(lst_job[-2:]), + "duts": self._generate_options(self._get_duts()), + "ttypes": self._generate_options(self._get_ttypes(lst_job[1])), + "cadences": self._generate_options(self._get_cadences( + lst_job[1], lst_job[3])), + "tbeds": self._generate_options(self._get_test_beds( + lst_job[1], lst_job[3], lst_job[4])) + } tst_info = { "job": list(), @@ -129,7 +162,7 @@ class Layout: ) self._default_fig_passed, self._default_fig_duration = graph_statistics( - self.data, self.jobs[0], self.layout + self.data, self._default["job"], self.layout ) # Callbacks: @@ -149,12 +182,54 @@ class Layout: return self._graph_layout @property - def jobs(self) -> list: - return self._jobs + def time_period(self) -> int: + return self._time_period @property - def time_period(self): - return self._time_period + def default(self) -> any: + return self._default + + def _get_duts(self) -> list: + """ + """ + return sorted(list(self.df_job_info["dut"].unique())) + + def _get_ttypes(self, dut: str) -> list: + """ + """ + return sorted(list(self.df_job_info.loc[( + self.df_job_info["dut"] == dut + )]["ttype"].unique())) + + def _get_cadences(self, dut: str, ttype: str) -> list: + """ + """ + return sorted(list(self.df_job_info.loc[( + (self.df_job_info["dut"] == dut) & + (self.df_job_info["ttype"] == ttype) + )]["cadence"].unique())) + + def _get_test_beds(self, dut: str, ttype: str, cadence: str) -> list: + """ + """ + return sorted(list(self.df_job_info.loc[( + (self.df_job_info["dut"] == dut) & + (self.df_job_info["ttype"] == ttype) & + (self.df_job_info["cadence"] == cadence) + )]["tbed"].unique())) + + def _get_job(self, dut, ttype, cadence, testbed): + """Get the name of a job defined by dut, ttype, cadence, testbed. + + Input information comes from control panel. + """ + return self.df_job_info.loc[( + (self.df_job_info["dut"] == dut) & + (self.df_job_info["ttype"] == ttype) & + (self.df_job_info["cadence"] == cadence) & + (self.df_job_info["tbed"] == testbed) + )]["job"].item() + def add_content(self): """ @@ -163,6 +238,9 @@ class Layout: return html.Div( id="div-main", children=[ + dcc.Store( + id="control-panel" + ), dbc.Row( id="row-navbar", class_name="g-0", @@ -296,12 +374,74 @@ class Layout: dbc.Row( class_name="g-0 p-2", children=[ - dbc.Label("Choose the Trending Job"), - dbc.RadioItems( - id="ri_job", - value=self.jobs[0], - options=[ - {"label": i, "value": i} for i in self.jobs + dbc.Row( + class_name="gy-1", + children=[ + dbc.Label( + "Device under Test", + class_name="p-0" + ), + dbc.RadioItems( + id="ri-duts", + inline=True, + value=self.default["dut"], + options=self.default["duts"] + ) + ] + ), + dbc.Row( + class_name="gy-1", + children=[ + dbc.Label( + "Test Type", + class_name="p-0" + ), + dbc.RadioItems( + id="ri-ttypes", + inline=True, + value=self.default["ttype"], + options=self.default["ttypes"] + ) + ] + ), + dbc.Row( + class_name="gy-1", + children=[ + dbc.Label( + "Cadence", + class_name="p-0" + ), + dbc.RadioItems( + id="ri-cadences", + inline=True, + value=self.default["cadence"], + options=self.default["cadences"] + ) + ] + ), + dbc.Row( + class_name="gy-1", + children=[ + dbc.Label( + "Test Bed", + class_name="p-0" + ), + dbc.Select( + id="dd-tbeds", + placeholder="Select a test bed...", + value=self.default["tbed"], + options=self.default["tbeds"] + ) + ] + ), + dbc.Row( + class_name="gy-1", + children=[ + dbc.Alert( + id="al-job", + color="info", + children=self.default["job"] + ) ] ) ] @@ -329,29 +469,148 @@ class Layout: ] ) + class ControlPanel: + def __init__(self, panel: dict, default: dict) -> None: + self._defaults = { + "ri-ttypes-options": default["ttypes"], + "ri-cadences-options": default["cadences"], + "dd-tbeds-options": default["tbeds"], + "ri-duts-value": default["dut"], + "ri-ttypes-value": default["ttype"], + "ri-cadences-value": default["cadence"], + "dd-tbeds-value": default["tbed"], + "al-job-children": default["job"] + } + self._panel = deepcopy(self._defaults) + if panel: + for key in self._defaults: + self._panel[key] = panel[key] + + def set(self, kwargs: dict) -> None: + for key, val in kwargs.items(): + if key in self._panel: + self._panel[key] = val + else: + raise KeyError(f"The key {key} is not defined.") + + @property + def defaults(self) -> dict: + return self._defaults + + @property + def panel(self) -> dict: + return self._panel + + def get(self, key: str) -> any: + return self._panel[key] + + def values(self) -> list: + return list(self._panel.values()) + + @staticmethod + def _generate_options(opts: list) -> list: + """ + """ + return [{"label": i, "value": i} for i in opts] + def callbacks(self, app): @app.callback( + Output("control-panel", "data"), # Store Output("graph-passed", "figure"), Output("graph-duration", "figure"), - Input("ri_job", "value"), + Output("ri-ttypes", "options"), + Output("ri-cadences", "options"), + Output("dd-tbeds", "options"), + Output("ri-duts", "value"), + Output("ri-ttypes", "value"), + Output("ri-cadences", "value"), + Output("dd-tbeds", "value"), + Output("al-job", "children"), + State("control-panel", "data"), # Store + Input("ri-duts", "value"), + Input("ri-ttypes", "value"), + Input("ri-cadences", "value"), + Input("dd-tbeds", "value"), Input("dpr-period", "start_date"), Input("dpr-period", "end_date"), prevent_initial_call=True ) - def _update_ctrl_panel(job:str, d_start: str, d_end: str) -> tuple: + def _update_ctrl_panel(cp_data: dict, dut:str, ttype: str, cadence:str, + tbed: str, d_start: str, d_end: str) -> tuple: """ """ + ctrl_panel = self.ControlPanel(cp_data, self.default) + d_start = datetime(int(d_start[0:4]), int(d_start[5:7]), int(d_start[8:10])) d_end = datetime(int(d_end[0:4]), int(d_end[5:7]), int(d_end[8:10])) - fig_passed, fig_duration = graph_statistics( - self.data, job, self.layout, d_start, d_end + trigger_id = callback_context.triggered[0]["prop_id"].split(".")[0] + if trigger_id == "ri-duts": + ttype_opts = self._generate_options(self._get_ttypes(dut)) + ttype_val = ttype_opts[0]["value"] + cad_opts = self._generate_options( + self._get_cadences(dut, ttype_val)) + cad_val = cad_opts[0]["value"] + tbed_opts = self._generate_options( + self._get_test_beds(dut, ttype_val, cad_val)) + tbed_val = tbed_opts[0]["value"] + ctrl_panel.set({ + "ri-duts-value": dut, + "ri-ttypes-options": ttype_opts, + "ri-ttypes-value": ttype_val, + "ri-cadences-options": cad_opts, + "ri-cadences-value": cad_val, + "dd-tbeds-options": tbed_opts, + "dd-tbeds-value": tbed_val + }) + elif trigger_id == "ri-ttypes": + cad_opts = self._generate_options( + self._get_cadences(ctrl_panel.get("ri-duts-value"), ttype)) + cad_val = cad_opts[0]["value"] + tbed_opts = self._generate_options( + self._get_test_beds(ctrl_panel.get("ri-duts-value"), + ttype, cad_val)) + tbed_val = tbed_opts[0]["value"] + ctrl_panel.set({ + "ri-ttypes-value": ttype, + "ri-cadences-options": cad_opts, + "ri-cadences-value": cad_val, + "dd-tbeds-options": tbed_opts, + "dd-tbeds-value": tbed_val + }) + elif trigger_id == "ri-cadences": + tbed_opts = self._generate_options( + self._get_test_beds(ctrl_panel.get("ri-duts-value"), + ctrl_panel.get("ri-ttypes-value"), cadence)) + tbed_val = tbed_opts[0]["value"] + ctrl_panel.set({ + "ri-cadences-value": cadence, + "dd-tbeds-options": tbed_opts, + "dd-tbeds-value": tbed_val + }) + elif trigger_id == "dd-tbeds": + ctrl_panel.set({ + "dd-tbeds-value": tbed + }) + elif trigger_id == "dpr-period": + pass + + job = self._get_job( + ctrl_panel.get("ri-duts-value"), + ctrl_panel.get("ri-ttypes-value"), + ctrl_panel.get("ri-cadences-value"), + ctrl_panel.get("dd-tbeds-value") ) + ctrl_panel.set({"al-job-children": job}) + fig_passed, fig_duration = graph_statistics( + self.data, job, self.layout, d_start, d_end) - return fig_passed, fig_duration + ret_val = [ctrl_panel.panel, fig_passed, fig_duration] + ret_val.extend(ctrl_panel.values()) + return ret_val @app.callback( Output("download-data", "data"), diff --git a/resources/tools/dash/app/pal/trending/graphs.py b/resources/tools/dash/app/pal/trending/graphs.py index 16cb5a2cb3..1d9fd1ccfa 100644 --- a/resources/tools/dash/app/pal/trending/graphs.py +++ b/resources/tools/dash/app/pal/trending/graphs.py @@ -201,11 +201,12 @@ def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame, df = df.dropna(subset=[_VALUE[ttype], ]) if df.empty: return list() - - x_axis = [d for d in df["start_time"] if d >= start and d <= end] - if not x_axis: + df = df.loc[((df["start_time"] >= start) & (df["start_time"] <= end))] + if df.empty: return list() + x_axis = df["start_time"].tolist() + anomalies, trend_avg, trend_stdev = _classify_anomalies( {k: v for k, v in zip(x_axis, df[_VALUE[ttype]])} ) @@ -327,9 +328,6 @@ def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame, u"len": 0.8, u"title": u"Circles Marking Data Classification", u"titleside": u"right", - # u"titlefont": { - # u"size": 14 - # }, u"tickmode": u"array", u"tickvals": [0.167, 0.500, 0.833], u"ticktext": _TICK_TEXT_LAT \ |