Published
Edited
Sep 16, 2022
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argentina = topojson.feature(filteredArg, filteredArg.objects.localidades)
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zip = FileAttachment("DL_FIRE_J1V-C2_24255.zip").zip()
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data1 = Promise.all(
zip.filenames.map((f) => zip.file(f).csv({ typed: true }))
).then((d) => d.flat())
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J1_08_2020_ARG = data1//d3.csvParse(await FileAttachment("fire_nrt_J1V-C2_157725.csv").text(), d3.autoType)
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acumulado = d3.rollups(data1,v=>v.length, d=>dateformat(new Date(+d.acq_date)))
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Plot.plot({
marks: [
Plot.ruleY([0]),
//Plot.lineY(acumulado, {x: d=>new Date(d[0]), y: d=>d[1], z: "industry"})
Plot.lineY(acumulado,Plot.windowY({x:d=>new Date(d[0]), y: d=>d[1], k: 7, reduce: "mean", curve: "monotone-x"})),
]
})
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daily_J1_08_2020_ARG = d3.group(J1_08_2020_ARG, d => dateformat(new Date(+d.acq_date + 100000000)))
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viewof day_2020 = Scrubber(daily_J1_08_2020_ARG.keys(), {delay: 300, loop: false})
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daily_J1_08_2020_ARG.get(day_2020)
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frpdata = J1_08_2020_ARG.map(d => d.frp)
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frpColor = d3.scaleSequential(d3.interpolateReds)
.domain(d3.extent(frpdata))
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frpColor(2)
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t31Color = d3.scaleSequential(d3.interpolateMagma)
.domain(d3.extent(t31data))
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viewof day2_2020 = Scrubber(daily_J1_08_2020_ARG.keys(), {delay: 300, loop: false})
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controller = graphic.update(time)
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time = day3_2020
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height = 500
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numformat = d3.format(",d")
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dateformat = d3.timeFormat("%Y-%m-%d")
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