4

test.php

willwheeler edited this page 2026-06-18 20:49:00 +00:00

Table of Contents

• BAS Forecast & Dashboard
• On this page
• Overview & quick start
• Install & run
• View in browser
• Default forecast points (forecast.py → JOBS)
• test.php URL flags
• Main BasData app (context)
• Pipeline
• forecast.py
• Run
• Settings
• Algorithm (per point)
• Model stack
• Console example
• forecast_comp.py
• Run
• Settings (top of file)
• Output example
• Quality warnings
• forecast_output.json
• Schema
• Keys (default JOBS)
• How test.php uses it
• test.php dashboard
• Modes
• Charts
• Live data flow
• Header buttons
• Troubleshooting

<-- Home

BAS Forecast & Dashboard

Python forecasting scripts plus a browser dashboard for validating BACnet trend charts and forecast overlays. Runs offline first on sample JS files, then optionally against live getData from BasData.

---

On this page

• Overview & quick start
• Pipeline
• forecast.py
• forecast_comp.py
• forecast_output.json
• test.php dashboard
• Troubleshooting

---

Overview & quick start

Component	Description
forecast.py	Train models, backtest on last 20%, write forecast_output.json
forecast_comp.py	Compare target-only vs target + extra points (console MAE)
forecast_output.json	Predictions + MAE per point for the dashboard
test.php	ApexCharts lab: sparks, heatmap, line, phases, HVAC, forecast overlay
js/test.js	Chart colors, wordbank, point → chart mapping
js/veris-sample.js	Veris meter sample data
js/rtu-sample.js	RTU sample data

Install & run

pip install pandas scikit-learn skforecast
python forecast.py

View in browser

/test.php?sample=1&forecast=1

Or open test.php, load sample or live data, then click Load forecast.

Default forecast points (forecast.py → JOBS)

Sample file	Points
js/veris-sample.js	P, Ia, Ib, Ic
js/rtu-sample.js	ServRmTmp

test.php URL flags

Parameter	Example	Effect
sample=1	?sample=1	Use sample JS; no live fetch
forecast=1	?forecast=1	Auto-load forecast_output.json
interval=N	?interval=24	Live trend window (8-36 hours)
keyid=N	?keyid=1	Override automation-server id
embed=1	?embed=1	Minimal header (iframe)

Main BasData app (context)

Page	Role
index.php	Production viewer + getData API
reports.php	Report JSON builder
test.php	Chart/forecast lab before shipping to reports/index

---

Pipeline

veris-sample.js / rtu-sample.js
        │
        ▼
   forecast.py  ──►  forecast_output.json
        │
        ▼
    test.php  ◄──  (optional) live getData from index.php
        │
        ▼
   ApexCharts (dashed forecast on P line + phase compare)

forecast_comp.py  →  console MAE only (experiments, no JSON)

---

forecast.py

Trains one time-series model per BACnet point, evaluates MAE on the last 20% of history, predicts 100 steps ahead, writes forecast_output.json.

Run

python forecast.py

No CLI args — edit constants at the top of the file.

Settings

Constant	Default	Meaning
FUTURE_STEPS	100	How many future readings to predict
LAGS	25	How many past readings the model uses each step
JOBS	veris + rtu	List of (js_file, [point_names])

Default JOBS:

JOBS = [
    ("js/veris-sample.js", ["P", "Ia", "Ib", "Ic"]),
    ("js/rtu-sample.js", ["ServRmTmp"]),
]

Algorithm (per point)

1. Load — Parse var xxxData = { ... }; from the .js file.
2. Series — pandas Series indexed by timestamp (x = ms, y = float).
3. Resample — Even spacing from median step; interpolate gaps.
4. Backtest — First 80% train, last 20% predict → MAE printed.
5. Forecast — Retrain on full series → FUTURE_STEPS ahead.
6. Write — { "mae", "future": [{x,y},...] } per point to JSON.

Model stack

• skforecast ForecasterRecursive
• sklearn Ridge
• Metric: mean absolute error on the hidden 20%

Console example

P — 432 readings
  MAE (last 20%): 11.17

Saved forecasts for: P, Ia, Ib, Ic, ServRmTmp

---

forecast_comp.py

Research script: does adding other points improve predictions for a target?

Compares two models on the same 80/20 backtest:

Model	Inputs
A — alone	Target point history only
B — combined	Target + WITH_POINTS at each timestamp

Does not write JSON or change charts.

Run

python forecast_comp.py

Settings (top of file)

Constant	Example	Meaning
JS_FILE	js/rtu-sample.js	Sample data source
TARGET	RaTmp	Point to predict
WITH_POINTS	["FanCmdOvr"]	Extra columns for model B
LAGS	26	Lag window

Output example

Backtest on last 20% of sample data:
  RaTmp only:                    MAE = 1.24
  RaTmp + [FanCmdOvr]:           MAE = 0.89

Extra points helped — about 0.35 better on average.

Quality warnings

Script warns when MAE is misleading:

• Flat target in test slice (MAE ≈ 0, model learned nothing useful)
• Exog column identical or nearly identical to target
• Exog fully determines target (lookup table)
• Flat exog in test slice

Use forecast_comp.py to experiment; use forecast.py to ship JSON to the dashboard.

---

forecast_output.json

Generated by forecast.py. Loaded by test.php for dashed forecast overlays.

Schema

{
  "P": {
    "mae": 11.17,
    "future": [
      { "x": 1781713080000, "y": 19.05 },
      { "x": 1781713200000, "y": 19.04 }
    ]
  }
}

Field	Meaning
mae	Backtest error on last 20% (same units as point)
future	Predicted readings after last historical sample
x	Unix time in milliseconds (matches sample JS / getData)
y	Predicted value (2 decimals)

Keys (default JOBS)

Key	Source	Dashboard use
P	veris-sample.js	Power line chart
Ia, Ib, Ic	veris-sample.js	Phase compare
ServRmTmp	rtu-sample.js	In JSON; RTU chart overlay TBD

How test.php uses it

1. fetch("forecast_output.json") → basForecastData
2. basForecastSeries(actualData, pointName) → last real point + future array
3. ApexCharts: dashed red series, "Forecast →" at last live timestamp

Charts with forecast today: Line P, Phase compare.

mae is stored but not shown in UI yet.

---

test.php dashboard

Device Snapshot — ApexCharts lab for BasData chart prototyping.

Modes

Mode	How
Live	Log in on index.php → pick office / building / asp → open test.php
Sample	?sample=1 loads rtu-sample.js + veris-sample.js
Forecast	?forecast=1 or Load forecast (needs chart data loaded first)

Hardcoded devices (for now): RTU_3, VerisMeter.

Charts

Toolbar slot	Chart	Typical points
sparks	Fan / room / power mini charts	FanSts, ServRmTmp, P
heatmap	All Veris points	all keys in bundle
lineP	Power trend (+ forecast)	P, Demand
phaseCompare	Ia / Ib / Ic (+ forecast)	Ia, Ib, Ic
hvacMode	HVAC mode timeline	HVACMode
trigger	Fan start counts per bucket	FanSts
radialBar	Temp vs setpoint	ServRmTmp + setpoint pair

Toggle charts with toolbar checkboxes. Point → slot mapping: js/test.js → BAS_CHART_SLOTS, basResolveDashboard().

Live data flow

test.php  --POST-->  index.php (getData=true&keyid=&name=&interval=&tstamp=)
         <--JSON--  { PointName: [{x,y}, ...], ... }
         -->  basApplyDashboard(rtu, veris)

Same contract as the index sidebar.

Header buttons

Button	Action
Load sample data	Offline JS bundles
Load forecast	Fetch JSON, redraw P + phase charts
Status bar	Loading / ok / partial fail / errors

---

Troubleshooting

Problem	Likely cause	Fix
"No forecast_output.json"	File missing	Run python forecast.py from project root
Forecast button, no lines	No chart data	?sample=1 or log in and load live data first
MAE ≈ 0 in comp script	Flat or duplicate data	Read warnings in console output
Live RTU charts empty	Long interval, huge payload	Shorter window; see server memory notes
Point missing from JSON	Not in JOBS	Add to forecast.py and re-run

---

BasData forecast & dashboard wiki — single-page reference.