547 lines
23 KiB
JavaScript
547 lines
23 KiB
JavaScript
// ------------------------------------------------------------------------
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// compute.js - Build the per-hour display rows from the raw API data.
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//
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// Pure-ish function: feed in (forecast, airQuality, location, vehicleType,
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// vehicleVent, buildingType) and get back { hourlyRows, days, utcOffsetMs }.
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//
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// Open-Meteo with timezone=auto returns local wall-clock strings like
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// "2026-05-13T14:00" - no Z suffix. Two forms are used in each row:
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// - String slices (iso.slice(...)) for display & day grouping
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// - A true UTC Date (dt) for solarElevationDeg (which uses .getUTC*).
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// ------------------------------------------------------------------------
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import {
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vaporPressureHpa, solarElevationDeg, calcTmrt, utciApprox,
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calcConcreteTempPass, calcVehicleInteriorTemp,
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calcIndoorTempPass, calcManagedIndoorTempPass,
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} from './physics.js';
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import { windCompass8, uvSplit, cloudCategory, precipPenalty, sunburnMinutes, burnLabel } from './utils.js';
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import { UTCI_ENVIRONMENTS } from './config.js';
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export function buildHourlyRows({ forecast, airQuality, location, vehicleType, vehicleVent, buildingType, utciEnv }) {
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const env = UTCI_ENVIRONMENTS[utciEnv] ?? UTCI_ENVIRONMENTS.open;
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const utcOffsetMs = (forecast?.utc_offset_seconds ?? 0) * 1000;
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// Build a fast lookup map from the air quality hourly data: ISO string - index.
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// Normalise to "YYYY-MM-DDTHH" (13 chars) so forecast timestamps like
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// "2026-05-17T14:00" match AQ timestamps like "2026-05-17T14".
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const aqTimeMap = {};
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if (airQuality?.hourly?.time) {
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airQuality.hourly.time.forEach((t, i) => { aqTimeMap[t.slice(0, 13)] = i; });
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}
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const getAq = (field, iso) => {
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if (!airQuality?.hourly?.[field]) return null;
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const i = aqTimeMap[iso.slice(0, 13)];
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if (i === undefined) return null;
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return airQuality.hourly[field][i] ?? null;
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};
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const hourlyRows = forecast ? forecast.hourly.time.map((iso, i) => {
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const h = forecast.hourly;
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const Ta = h.temperature_2m[i];
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const RH = h.relative_humidity_2m[i];
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const dew = h.dew_point_2m ? h.dew_point_2m[i] : null;
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const va = h.wind_speed_10m[i];
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const wd = h.wind_direction_10m ? h.wind_direction_10m[i] : null;
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const gust = h.wind_gusts_10m ? h.wind_gusts_10m[i] : null;
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const dir = h.direct_radiation[i] || 0;
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const dif = h.diffuse_radiation[i] || 0;
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const glob = h.shortwave_radiation[i] || 0;
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const cc = h.cloud_cover[i];
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const ccLow = h.cloud_cover_low ? h.cloud_cover_low[i] : null;
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const ccMid = h.cloud_cover_mid ? h.cloud_cover_mid[i] : null;
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const ccHigh = h.cloud_cover_high ? h.cloud_cover_high[i] : null;
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const uv = h.uv_index ? (h.uv_index[i] || 0) : 0;
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const precip = h.precipitation[i] || 0;
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const precipProb = h.precipitation_probability ? (h.precipitation_probability[i] ?? 0) : 0;
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const snow = h.snowfall[i] || 0;
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const soilT0 = h.soil_temperature_0cm ? h.soil_temperature_0cm[i] : null;
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const soilT6 = h.soil_temperature_6cm ? h.soil_temperature_6cm[i] : null;
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const soilM = h.soil_moisture_0_to_1cm ? h.soil_moisture_0_to_1cm[i] : null;
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// iso is a local wall-clock string e.g. "2026-05-13T14:00" (no Z).
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// For display we slice the string directly - no Date object needed.
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// For solarElevationDeg (which uses .getUTC* internally) we need the
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// true UTC instant: treat the local time as UTC then subtract the offset.
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// e.g. Brisbane UTC+10: local 14:00 - parse as UTC 14:00 - subtract 10h - UTC 04:00 -
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// iso is a local wall-clock string e.g. "2026-05-13T14:00" (no Z).
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// For solarElevationDeg (which uses .getUTC* internally) we need the
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// true UTC instant: treat the local time as UTC then subtract the offset.
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const dt = new Date(Date.parse(iso + 'Z') - utcOffsetMs);
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const elev = solarElevationDeg(location.lat, location.lon, dt);
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// Use direct_radiation (beam sunlight) + a fraction of diffuse for concrete.
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// direct_radiation is zero on fully overcast days - far more accurate than
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// shortwave_radiation which can be unreliably high even at 100% cloud cover.
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// Diffuse (scattered light through cloud) contributes ~20% as much heat to
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// a surface as direct beam, so we weight it accordingly.
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const effectiveRad = dir + dif * 0.2;
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// concreteT is now stamped in the two-pass section below (thermal lag).
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const vehicleT = calcVehicleInteriorTemp(Ta, glob, elev, vehicleType, vehicleVent);
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const eh = vaporPressureHpa(Ta, RH);
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// Apply environment modifier - adjust solar inputs and air temp for shaded environments.
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const TaEnv = Ta + env.taOffset;
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const dirEnv = dir * env.dirFactor;
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const difEnv = dif * env.difFactor;
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const globEnv = glob * env.globFactor;
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const Tmrt = calcTmrt(TaEnv, dirEnv, difEnv, globEnv, elev);
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const utci = utciApprox(TaEnv, Tmrt, va, eh);
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const utciAdj = utci + precipPenalty(precip, snow, va);
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// Derived
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const compass = windCompass8(wd);
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const { uvA, uvB } = uvSplit(uv, elev);
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const cloudCat = cloudCategory(cc, ccLow, ccMid, ccHigh);
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// Visibility from the main forecast API (metres - km).
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const visKm = (() => { const v = h.visibility ? h.visibility[i] : null; return v != null ? v / 1000 : null; })();
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const aqi = getAq('european_aqi', iso);
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const grassPollen = getAq('grass_pollen', iso);
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const birchPollen = getAq('birch_pollen', iso);
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const alderPollen = getAq('alder_pollen', iso);
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const mugwortPollen= getAq('mugwort_pollen', iso);
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const olivePollen = getAq('olive_pollen', iso);
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const ragweedPollen= getAq('ragweed_pollen', iso);
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// -- FUTURE FEATURE: Activity "What If" Modifier ---------------------------
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// Add two extra columns driven by a user-selected activity level. These are
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// intentionally kept SEPARATE from the core columns above so that baseline
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// profile data stays consistent and comparable across profiles.
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//
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// The user picks an activity from a simple UI picker (no live data needed -
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// this is a forecast/planning tool, not a tracker):
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// Resting - Walking - Cycling - Running - Sport/Intense
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//
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// Two output columns only (keep it clean):
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//
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// adjustedSafeTime - baseline UV safe exposure time - an activity multiplier.
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// Higher activity = shorter safe time, because:
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// - metabolic heat raises core body temp
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// - sweating washes away sunscreen faster
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// - more skin blood flow = higher UV sensitivity
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// Suggested multipliers (tune with real data):
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// Resting: 1.0 (no change)
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// Walking: 0.85
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// Cycling: 0.75
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// Running: 0.60
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// Sport: 0.50
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//
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// heatStressLevel - a simple label: 'Low' | 'Moderate' | 'High' | 'Very High'
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// Derived from UTCI + activity heat load. A runner at
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// UTCI 28-C should read 'High' even if a resting person
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// would read 'Moderate' at the same UTCI.
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// Colour code in the UI: - - - -
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//
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// Implementation sketch:
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// 1. Accept 'activityLevel' as a new param to buildHourlyRows() alongside
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// vehicleType, buildingType etc.
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// 2. Define ACTIVITY_PRESETS in utils.js (multiplier + utciOffset per level).
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// 3. Compute adjustedSafeTime = baseSafeTime * preset.multiplier
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// 4. Compute heatStressLevel from (utci + preset.utciOffset) banded into labels.
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// 5. Add both fields to the returned row object below.
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// 6. In components.js, render these as optional columns that only appear when
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// an activity other than 'Resting' is selected - keeps the default table clean.
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// -----------------------------------------------------------------------------
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return {
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iso, dt, Ta, RH, dew, va, wd, gust, dir, dif, glob,
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cc, ccLow, ccMid, ccHigh, cloudCat,
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uv, uvA, uvB,
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precip, precipProb, snow,
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soilT0, soilT6, soilM, vehicleT,
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effectiveRad,
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elev, Tmrt, utci, utciAdj, eh, compass,
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visKm, aqi,
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grassPollen, birchPollen, alderPollen, mugwortPollen, olivePollen, ragweedPollen,
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};
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}) : [];
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// Two-pass calculations: concrete thermal lag + indoor temperature.
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// Both need the full hourly arrays so they can look back at previous
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// hours. Run after hourlyRows is built, then stamp each row.
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if (hourlyRows.length > 0) {
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const TaArr = hourlyRows.map(r => r.Ta);
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const globArr = hourlyRows.map(r => r.glob);
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const elevArr = hourlyRows.map(r => r.elev);
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const radArr = hourlyRows.map(r => r.effectiveRad);
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const vaArr = hourlyRows.map(r => r.va);
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const uvArr = hourlyRows.map(r => r.uv);
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const cloudCatArr = hourlyRows.map(r => r.cloudCat);
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const soilMArr = hourlyRows.map(r => r.soilM);
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const precipArr = hourlyRows.map(r => r.precip);
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const snowArr = hourlyRows.map(r => r.snow);
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// Concrete surface temperature with thermal lag (1.5 h time constant).
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// A slab baking in the sun retains heat when cloud rolls in, and takes
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// a couple of hours of sunshine to fully heat up from a cold start.
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const concreteTemps = calcConcreteTempPass(
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TaArr, radArr, vaArr, elevArr, uvArr, cloudCatArr, soilMArr, precipArr, snowArr
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);
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hourlyRows.forEach((r, i) => { r.concreteT = concreteTemps[i]; });
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const indoorTemps = calcIndoorTempPass(TaArr, globArr, elevArr, buildingType);
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const managedTemps = calcManagedIndoorTempPass(TaArr, globArr, elevArr, buildingType);
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hourlyRows.forEach((r, i) => { r.indoorT = indoorTemps[i]; r.managedT = managedTemps[i]; });
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}
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// Group those hourly rows into days for the day tabs.
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const days = [];
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hourlyRows.forEach(row => {
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const key = row.iso.slice(0, 10);
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let day = days.find(d => d.key === key);
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if (!day) { day = { key, rows: [] }; days.push(day); }
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day.rows.push(row);
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});
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// -- FUTURE FEATURE v2: Today Summary + Alert System --------------------------
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// After grouping rows into days, generate a per-day summary object that powers
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// a stylish "Today at a Glance" panel shown above or below the main dial.
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//
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// The summary is NOT a live alert/push system - it's a forecast digest that
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// refreshes with the forecast data. Think of it as a smart briefing card.
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//
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// WHAT TO COMPUTE (per day, from that day's rows):
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// - Peak UTCI+P and time it occurs - heat stress headline
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// - Min UTCI+P and time - cold stress headline
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// - Peak UV index and time - UV warning
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// - Max precipitation rate and time - rain/ice warning
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// - Max vehicle cabin temp - "dangerous to leave pets/children in car"
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// - Max pollen level + type - pollen advisory
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// - Road condition risk (low air temp + precip - ice risk)
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//
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// ALERT CATEGORIES (each generates a styled warning card if threshold exceeded):
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// -- Heat warning UTCI+P > 32-C
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// - Cold warning UTCI+P < 0-C
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// -- UV warning UV index > 6
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// -- Heavy rain precip > 4mm/h
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// - Ice/road risk Ta < 3-C + any precip (or recent precip overnight)
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// - Vehicle danger vehicleT > 35-C ("don't leave pets or children in car")
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// - High pollen any pollen type > 50 grains/m-
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//
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// DESIGN NOTES:
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// - Cards should be concise - one line of bold text + a short explanation
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// - Colour-coded to match the existing UTCI stress band palette
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// - Collapsible - show top 2-3 alerts by default, expand for full list
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// - For today only (days[0]); optionally extend to day tabs in a later pass
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// - The "X-C above seasonal norm" historical context line (see app.js comment)
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// could live here too, as a subtle subheading under the dial temperature
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//
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// Suggested return shape - add to the return value below:
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// daySummaries: days.map(day => buildDaySummary(day.rows))
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//
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// where buildDaySummary() is a new helper in this file (or a separate
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// summary.js module if it grows large).
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// -----------------------------------------------------------------------------
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return { hourlyRows, days, utcOffsetMs };
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}
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// ------------------------------------------------------------------------
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// computeWhyFeelsLike(row, env) - Break down the felt-temp delta into its
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// contributing factors for the "Why it feels like this" panel.
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//
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// Returns contributions in degrees C relative to plain air temperature.
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// Positive = warmer than air temp, negative = cooler.
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//
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// Attribution method - sequential isolation using utciApprox:
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// sunAndSky - Tmrt vs Ta. Mean radiant temp captures net heat from
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// direct sun, sky scatter, and ground reflection combined.
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// wind - UTCI with wind vs without (Tmrt = Ta, neutral RH 50%).
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// Almost always negative - wind cools.
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// humidity - UTCI at actual vapour pressure vs neutral RH 50%.
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// Positive when muggy, near-zero when dry.
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// environment - taOffset from the active UTCI environment modifier.
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// e.g. urban +2.5, forest -2.0, desert +3.5.
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// precipitation - precipPenalty() - always 0 or negative.
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// ------------------------------------------------------------------------
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export function computeWhyFeelsLike(row, env) {
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if (!row) return null;
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const { Ta, Tmrt, va, eh, precip, snow } = row;
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const r1 = (v) => Math.round(v * 10) / 10;
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// Radiation - mean radiant temp above or below air temp.
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const sunAndSky = r1(Tmrt - Ta);
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// Wind - UTCI with actual wind vs calm, holding Tmrt = Ta and RH neutral.
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const ehNeutral = vaporPressureHpa(Ta, 50);
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const wind = r1(utciApprox(Ta, Ta, va, ehNeutral) - utciApprox(Ta, Ta, 0, ehNeutral));
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// Humidity - actual vapour pressure vs neutral RH 50%, no wind or sun.
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const humidity = r1(utciApprox(Ta, Ta, 0, eh) - utciApprox(Ta, Ta, 0, ehNeutral));
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// Environment modifier - explicit temperature offset from the env config.
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const environment = env ? r1(env.taOffset) : 0;
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// Precipitation soak penalty - negative or zero.
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const precipitation = precipPenalty(precip, snow, va);
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return { sunAndSky, wind, humidity, environment, precipitation };
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}
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// ------------------------------------------------------------------------
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// computeGlanceSummary(todayRows, profile, variant, skinType) - Build the
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// environment-aware "Today at a Glance" items for the current day.
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//
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// Returns an array of { icon, label, value, alert } objects (4-5 items).
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// Content varies by profile and sub-variant so it stays relevant to
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// whatever the user is actually doing.
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//
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// Parameters:
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// todayRows - hourlyRows for the selected day
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// profile - active profile key e.g. "farming", "vehicle", "home"
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// variant - active sub-variant key e.g. "running", "beach" (or null)
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// skinType - Fitzpatrick skin type key for UV burn time
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// ------------------------------------------------------------------------
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export function computeGlanceSummary(todayRows, profile, variant, skinType) {
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if (!todayRows || todayRows.length === 0) return [];
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const hhmm = (iso) => iso ? iso.slice(11, 16) : null;
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const dayRows = todayRows.filter(r => r.elev > 0);
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const peakRow = (field) => todayRows.reduce((best, r) =>
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(r[field] != null && (best == null || r[field] > best[field])) ? r : best, null);
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const maxRainProb = Math.max(0, ...todayRows.map(r => r.precipProb ?? 0));
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// Longest run of rows that satisfy a predicate.
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const longestWindow = (rows, cond) => {
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let best = null, cur = null;
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for (const r of rows) {
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if (cond(r)) {
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cur = cur ? { start: cur.start, end: r, len: cur.len + 1 } : { start: r, end: r, len: 1 };
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if (!best || cur.len > best.len) best = { ...cur };
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} else {
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cur = null;
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}
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}
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return best;
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};
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const pollenLabel = (v) => {
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if (v == null || v < 0) return null;
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if (v < 10) return 'Low';
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if (v < 50) return 'Moderate';
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if (v < 200) return 'High';
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return 'Very High';
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};
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const aqiLabel = (v) => {
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if (v == null) return null;
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if (v < 20) return 'Good';
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if (v < 40) return 'Fair';
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if (v < 60) return 'Moderate';
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return 'Poor';
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};
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const moistureLabel = (v) => {
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if (v == null) return null;
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if (v < 0.15) return 'Dry';
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if (v < 0.30) return 'Slightly dry';
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if (v < 0.45) return 'Moist';
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return 'Saturated';
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};
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const rainItem = {
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icon: '🌧',
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label: 'Rain risk',
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value: `${Math.round(maxRainProb)}%`,
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alert: maxRainProb >= 60,
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};
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// ── Farming ────────────────────────────────────────────────────────────
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if (profile === 'farming') {
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const fieldWindow = longestWindow(dayRows, r =>
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r.utciAdj >= 8 && r.utciAdj <= 32 && r.precipProb < 30 && r.va < 12
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);
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const soilWarmRow = todayRows.find(r => r.soilT0 != null && r.soilT0 >= 10);
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const soilM = todayRows.find(r => r.soilM != null)?.soilM ?? null;
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const maxPollen = Math.max(0, ...todayRows.map(r => r.grassPollen ?? 0));
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return [
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{
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icon: '⏱',
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label: 'Best field work',
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value: fieldWindow
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? `${hhmm(fieldWindow.start.iso)} – ${hhmm(fieldWindow.end.iso)}`
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: 'No suitable window',
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alert: !fieldWindow,
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},
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{
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icon: '🌱',
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label: 'Soil warms to 10°C by',
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value: soilWarmRow ? hhmm(soilWarmRow.iso) : 'Not today',
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alert: !soilWarmRow,
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},
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rainItem,
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{
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icon: '💧',
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label: 'Soil moisture',
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value: moistureLabel(soilM) ?? '-',
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alert: soilM != null && (soilM < 0.10 || soilM > 0.50),
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},
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...(maxPollen >= 10 ? [{
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icon: '🌿',
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label: 'Grass pollen',
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value: pollenLabel(maxPollen),
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alert: maxPollen >= 50,
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}] : []),
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];
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}
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// ── Vehicle ────────────────────────────────────────────────────────────
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if (profile === 'vehicle') {
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const peakCabin = peakRow('vehicleT');
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const dangerFrom = todayRows.find(r => r.vehicleT != null && r.vehicleT >= 35);
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return [
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{
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icon: '🌡',
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label: 'Peak cabin temp',
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value: peakCabin ? `${Math.round(peakCabin.vehicleT)}° at ${hhmm(peakCabin.iso)}` : '-',
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alert: !!(peakCabin && peakCabin.vehicleT >= 35),
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},
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{
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icon: '🧒',
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label: 'Children/pets in car',
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value: dangerFrom ? `Unsafe from ${hhmm(dangerFrom.iso)}` : 'Safe all day',
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alert: !!dangerFrom,
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},
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rainItem,
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{
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icon: '🌤',
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label: 'Best travel comfort',
|
||
value: (() => {
|
||
const best = todayRows.reduce((b, r) =>
|
||
(b == null || r.utciAdj < b.utciAdj) ? r : b, null);
|
||
return best ? `${hhmm(best.iso)} (${Math.round(best.utciAdj)}° felt)` : '-';
|
||
})(),
|
||
alert: false,
|
||
},
|
||
];
|
||
}
|
||
|
||
// ── Home ───────────────────────────────────────────────────────────────
|
||
if (profile === 'home') {
|
||
const peakIndoor = peakRow('indoorT');
|
||
const peakManaged = peakRow('managedT');
|
||
const ventWindow = longestWindow(todayRows, r =>
|
||
r.Ta != null && r.indoorT != null && r.Ta < r.indoorT && r.precipProb < 20
|
||
);
|
||
const peakAqi = Math.max(0, ...todayRows.map(r => r.aqi ?? 0));
|
||
const maxPollen = Math.max(0, ...todayRows.map(r => r.grassPollen ?? 0));
|
||
|
||
return [
|
||
{
|
||
icon: '🌡',
|
||
label: 'Peak indoor (unmanaged)',
|
||
value: peakIndoor ? `${Math.round(peakIndoor.indoorT)}° at ${hhmm(peakIndoor.iso)}` : '-',
|
||
alert: !!(peakIndoor && peakIndoor.indoorT >= 28),
|
||
},
|
||
{
|
||
icon: '🌡',
|
||
label: 'Peak indoor (managed)',
|
||
value: peakManaged ? `${Math.round(peakManaged.managedT)}°` : '-',
|
||
alert: !!(peakManaged && peakManaged.managedT >= 28),
|
||
},
|
||
{
|
||
icon: '🪟',
|
||
label: 'Open windows',
|
||
value: ventWindow
|
||
? `${hhmm(ventWindow.start.iso)} – ${hhmm(ventWindow.end.iso)}`
|
||
: 'Keep closed',
|
||
alert: false,
|
||
},
|
||
{
|
||
icon: '💨',
|
||
label: 'Air quality',
|
||
value: peakAqi > 0 ? aqiLabel(peakAqi) : '-',
|
||
alert: peakAqi >= 60,
|
||
},
|
||
...(maxPollen >= 10 ? [{
|
||
icon: '🌼',
|
||
label: 'Pollen',
|
||
value: pollenLabel(maxPollen),
|
||
alert: maxPollen >= 50,
|
||
}] : []),
|
||
];
|
||
}
|
||
|
||
// ── Activities - running / cycling ─────────────────────────────────────
|
||
if (variant === 'running' || variant === 'cycling') {
|
||
const coolWindow = longestWindow(dayRows, r =>
|
||
r.utciAdj >= 5 && r.utciAdj <= 22 && r.precipProb < 30
|
||
);
|
||
const peakUvRow = peakRow('uv');
|
||
const peakAqi = Math.max(0, ...todayRows.map(r => r.aqi ?? 0));
|
||
const maxPollen = Math.max(0, ...todayRows.map(r => r.grassPollen ?? 0));
|
||
const burnMins = peakUvRow && peakUvRow.uv > 0
|
||
? burnLabel(sunburnMinutes(peakUvRow.uv, skinType))
|
||
: null;
|
||
|
||
return [
|
||
{
|
||
icon: '⏱',
|
||
label: `Best ${variant} window`,
|
||
value: coolWindow
|
||
? `${hhmm(coolWindow.start.iso)} – ${hhmm(coolWindow.end.iso)}`
|
||
: 'No cool window today',
|
||
alert: !coolWindow,
|
||
},
|
||
rainItem,
|
||
...(burnMins ? [{
|
||
icon: '☀',
|
||
label: 'UV burn time (peak)',
|
||
value: burnMins,
|
||
alert: !!(peakUvRow && peakUvRow.uv >= 6),
|
||
}] : []),
|
||
{
|
||
icon: '💨',
|
||
label: 'Air quality',
|
||
value: peakAqi > 0 ? aqiLabel(peakAqi) : '-',
|
||
alert: peakAqi >= 60,
|
||
},
|
||
...(maxPollen >= 10 ? [{
|
||
icon: '🌿',
|
||
label: 'Pollen',
|
||
value: pollenLabel(maxPollen),
|
||
alert: maxPollen >= 50,
|
||
}] : []),
|
||
];
|
||
}
|
||
|
||
// ── Outdoors - beach, park, events etc. (and fallback) ─────────────────
|
||
const comfortWindow = longestWindow(dayRows, r =>
|
||
r.utciAdj >= 9 && r.utciAdj <= 26 && r.precipProb < 30
|
||
);
|
||
const peakFelt = peakRow('utciAdj');
|
||
const peakUvRow = peakRow('uv');
|
||
const peakAqi = Math.max(0, ...todayRows.map(r => r.aqi ?? 0));
|
||
const burnMins = peakUvRow && peakUvRow.uv > 0
|
||
? burnLabel(sunburnMinutes(peakUvRow.uv, skinType))
|
||
: null;
|
||
|
||
return [
|
||
{
|
||
icon: '🌤',
|
||
label: 'Comfortable window',
|
||
value: comfortWindow
|
||
? `${hhmm(comfortWindow.start.iso)} – ${hhmm(comfortWindow.end.iso)}`
|
||
: 'No comfortable window',
|
||
alert: !comfortWindow,
|
||
},
|
||
{
|
||
icon: '🌡',
|
||
label: 'Peak felt temp',
|
||
value: peakFelt ? `${Math.round(peakFelt.utciAdj)}° at ${hhmm(peakFelt.iso)}` : '-',
|
||
alert: !!(peakFelt && (peakFelt.utciAdj >= 32 || peakFelt.utciAdj < 0)),
|
||
},
|
||
...(burnMins ? [{
|
||
icon: '☀',
|
||
label: 'UV burn time (peak)',
|
||
value: burnMins,
|
||
alert: !!(peakUvRow && peakUvRow.uv >= 6),
|
||
}] : []),
|
||
rainItem,
|
||
{
|
||
icon: '💨',
|
||
label: 'Air quality',
|
||
value: peakAqi > 0 ? aqiLabel(peakAqi) : '-',
|
||
alert: peakAqi >= 60,
|
||
},
|
||
];
|
||
} |