import { aq, op } from "@uwdata/arquero"

bucket_base = "https://d33173dkfxwa5x.cloudfront.net/www/"

FA = FileAttachment

  import {aq as aq, op as op} from "@uwdata/arquero"

bucket_base = "https://d33173dkfxwa5x.cloudfront.net/www/"

FA = ƒ(name)

mutable myLocation = null
mutable geolocateStatus = "default"

getLocation = {
  yield null

  yield navigator.geolocation.getCurrentPosition(
    pos => {
      mutable myLocation = {
        lat: pos.coords.latitude,
        lon: pos.coords.longitude
      }
      mutable geolocateStatus = "granted"
    },
    e => {
      console.log("Geolocation error", e),
      mutable geolocateStatus = "error"
    },
    {
      enableHighAccuracy: false
    })
}

mutable myLocation = Mutable {}

myLocation = null

mutable geolocateStatus = Mutable {}

geolocateStatus = "default"

getLocation = undefined

geolocateStatus == "default" ?
  md`Allow location to see local station` :
    geolocateStatus == "error" ?
      md`Problem getting location` :
      md``

Allow location to see local station

myLocation != null ?
  md`Location is lat: ${myLocation.lat}, lon: ${myLocation.lon}` :
  md`Location permission not granted`

Location permission not granted

// on the home page, get station id from:
//   * _geolocator.qmd's myLocation, plus
//   * _map.qmd's statsAll

stationId = {
  
  // fallback to sydney?
  if (myLocation == null) {
    return "023000"
  }

  // otherwise, find closest station on statsAll
  const closestStation = aq.from(statsAll)
    .params({
      currentLat: myLocation.lat,
      currentLon: myLocation.lon,
    })
    .derive({
      dist: (d, $) => Math.sqrt(
        ($.currentLat - d.isit_lat) ** 2 + ($.currentLon - d.isit_lon) ** 2)
    })
    .orderby("dist")
    .slice(0, 1)
    .array("id")

  return closestStation[0]
}

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statsPlace = FA(bucket_base + "stats/stats_" + stationId + ".json").json()

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Is it hot in

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right now?

answers = ({
  "Hell no!":   {color: "white",   fill1: "#5287d1", fill2: "#2166ac" },
  "No!":        {color: "white",   fill1: "#a2cdeb", fill2: "#67a9cf" },
  "Nope":       {color: "#333333", fill1: "#f5f8fa", fill2: "#d1e5f0" },
  "Not really": {color: "#333333", fill1: "#f7f7f7", fill2: "#ebebeb" },
  "Yup":        {color: "#333333", fill1: "#fddcca", fill2: "#f7cfb7" },
  "Yeah!":      {color: "white",   fill1: "#de7b49", fill2: "#fc946a" },
  "Hell yeah!": {color: "white",   fill1: "#d1231d", fill2: "#b2182b" }
})

html`
<div class="answer-icon-and-label">
  <span class="answer-icon" style="background-color: ${answers[statsPlace.isit_answer].fill2};">
  </span>
  <span>${statsPlace.isit_answer}</span>
</div>`

answers = Object {Hell no!: Object, No!: Object, Nope: Object, Not really: Object, Yup: Object, Yeah!: Object, Hell yeah!: Object}

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md`${statsPlace.isit_comment}`

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Here’s how today compares…

datefns = import("https://cdn.skypack.dev/date-fns@3.3.1?min")
tmaxWhen = new Date(Date.parse(statsPlace.isit_maximum_dt || null))
tminWhen = new Date(Date.parse(statsPlace.isit_minimum_dt || null))

tmaxWhenFriendly = isFinite(tmaxWhen) ?
  datefns.formatRelative(tmaxWhen, new Date()) : ""
tminWhenFriendly = isFinite(tminWhen) ?
  datefns.formatRelative(tminWhen, new Date()) : ""

percentRating = statsPlace.isit_average.toFixed(1) + "%"

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md`${statsPlace.isit_minimum} °C  `

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md`${tminWhenFriendly}`

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md`${statsPlace.isit_maximum} °C  `

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md`${tmaxWhenFriendly}`

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html`
<div class="answer-icon-and-label">
  <span class="answer-icon" style="background-color: ${answers[statsPlace.isit_answer].fill2};"></span>
  <span>${statsPlace.isit_current.toFixed(1)} °C</span>
</div>`

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md`Average so far<br>hotter than **${percentRating}** of days for this time of year.`

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md`![](${bucket_base + "plots/timeseries/timeseries-" + stationId + ".png"})`

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This is the distribution of temperatures typical for this time of year, which we’ve defined as a seven day window either side of today. Just like a bell curve, the plot is higher at more common temperatures and lower at rare temperatures.

md`![](${bucket_base + "plots/distribution/distribution-" + stationId + ".png"})`

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… and the rest of the year.

We’ve compared every day this year at

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to similar times of year in the past. Red days were hot compared to records; blue days were cold.

heatmapYear = (new Date()).toLocaleString("en-US", {timeZone: "Australia/Melbourne", year: "numeric"})
md`![](${bucket_base + "plots/heatmap/heatmap-" + stationId + "-" + heatmapYear + ".png"})`

heatmapYear = "2025"

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Here’s how the rest of Australia looks today so far.

nowHour = (new Date()).getUTCHours()
nowHour >= 10 && nowHour <= 22 ?
  md`Some places may still be cooling off as the night continues.` :
  md`Some places may still be heating up as the day continues.`

nowHour = 7

Some places may still be heating up as the day continues.

statsAllRaw = FA(bucket_base + "stats/stats_all.json").json()

// statsAllRaw is an object with keys by station id, but we
// need an array with an id field. let's move the ids in
statsAll = {
  const statsArray = []
  Object.keys(statsAllRaw).map(k => statsArray.push({...statsAllRaw[k], id: k}))
  const tidiedStats = aq.from(statsArray)
    .derive({
      lat: d => op.parse_float(d.isit_lat),
      lon: d => op.parse_float(d.isit_lon),
      isit_average: d => op.parse_float(d.isit_average),
      // current? (that's the actual avg temp)
      isit_maximum: d => op.parse_float(d.isit_maximum),
      isit_minimum: d => op.parse_float(d.isit_minimum),
      max_when: d => op.parse_date(d.isit_maximum_dt),
      min_when: d => op.parse_date(d.isit_minimum_dt),
      slug: d =>
        op.replace(
          op.replace(
            op.replace(
              op.lower(d.isit_label),
              /\s-\s/g, "-"),
            /\s/g, "-"),
          /[()]/g, "")
    })
    // mark as stale if latest obs are > 24 hours old
    .derive({
      max_stale:
        d => ((d.max_when - op.now()) / (1000 * 60)) / (24 * 60) > 1,
      min_stale:
        d => ((d.min_when - op.now()) / (1000 * 60)) / (24 * 60) > 1
    })
    .objects()
  return(tidiedStats)
}

statsAllRaw = Object {066214: Object, 067105: Object, 048245: Object, 086338: Object, 087031: Object, 070351: Object, 094029: Object, 040842: Object, 015590: Object, 014015: Object, 023000: Object, 009021: Object, 004032: Object, 091311: Object, 076031: Object, 017043: Object, 039128: Object, 039083: Object, 033119: Object, 065070: Object, …}

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currentStats = statsAll.filter(d => (!d.max_stale) && (!d.min_stale))
staleStats = statsAll.filter(d => d.max_stale || d.min_stale)

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australia = FileAttachment("/assets/australia.geojson").json()

Plot = import("https://esm.run/@observablehq/plot")

answer_domain = [
  "Hell no!",
  "No!",
  "Nope",
  "Not really",
  "Yup",
  "Yeah!",
  "Hell yeah!"]

Plot.plot({
  projection: {
    type: "equirectangular",
    rotate: [-133, 28],
    domain: d3.geoCircle().center([133, -28]).radius(18)()
  },
  marks: [
    // Plot.graticule(),
    Plot.geo(australia, {
      fill: "#00000009",
      stroke: "#dddddd"
    }),
    // replace stale locations with crosses
    Plot.dot(staleStats, {
      x: "lon",
      y: "lat",
      stroke: "lightgrey",
      r: 6,
      symbol: "times"
    }),
    Plot.dot(currentStats, {
      x: "lon",
      y: "lat",
      fill: "isit_answer",
      stroke: d =>
        d.isit_answer == "Hell no!" || d.isit_answer == "Hell yeah!" ?
        "black" :
        "#00000099",
      strokeWidth: 0.75,
      r: 6,
    }),
    Plot.tip(currentStats, tipTemplate),
    // enlarge dot you're pointing to
    Plot.dot(currentStats, Plot.pointer({
      x: "lon",
      y: "lat",
      fill: "isit_answer",
      stroke: d =>
        d.isit_answer == "Hell no!" || d.isit_answer == "Hell yeah!" ?
        "black" :
        "#00000099",
      strokeWidth: 0.75,
      r: 12,
    })),
    // enlargen clickable areas with invisible voronoi polys
    Plot.voronoi(currentStats, {
      x: "lon",
      y: "lat",
      fill: "transparent",
      stroke: "transparent",
      href: d => "/places/" + d.slug,
    }),

  ],
  color: {
    type: "ordinal",
    domain: answer_domain,
    range: ["#2166acff",
            "#67a9cfff",
            "#d1e5f0ff",
            "#f7f7f7ff",
            "#fddbc7ff",
            "#ef8a62ff",
            "#b2182bff"]
  },
  height: 600
})

australia = Object {type: "FeatureCollection", name: "australia", crs: Object, features: Array(1)}

answer_domain = Array(7) ["Hell no!", "No!", "Nope", "Not really", "Yup", "Yeah!", "Hell yeah!"]

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// breaking out the pointer layer for readability
// (and in case we decide to customise it later)
tipTemplate = Plot.pointer({
  x: "lon",
  y: "lat",
  channels: {
    place: {
      label: "",
      value: d => d.isit_label,
    },
    label: {
      label: "",
      value: d => d.isit_comment
    },
    separator: {
      label: "",
      value: d => ""
    },
    isit_maximum: {
      label: "Max:",
      value: d => d.isit_maximum + "°C"
    },
    isit_minimum: {
      label: "Min:",
      value: d => d.isit_minimum + "°C"
    }
  },
  fontSize: 20,
  fontFamily: "Roboto Condensed",
  format: {
    x: null,
    y: null
  },
  lineWidth: 20,
  lineHeight: 1.25,
  pointerSize: 0,
  fillOpacity: 0.8,
  strokeOpacity: 0
})