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allDays = flatUserArray.map((d) => d.days)
color = d3
.scaleLinear()
.domain([25, 13, 0])
.range(["#F081A1", "#E5ADFF", "#3AC9E9"])
.clamp(true)
expScale = d3.scalePow().exponent(Math.E).domain([0, 25])
flatUserArray = Array.from(userDataByDays).map((value, key) => {
return {
id: value[0],
days: Array.from(value[1]).map((d) => {
let glucoseValues = d[1].map((e) => {
return e.value;
});
return {
day: d[0],
values: d[1],
deviation: d3.deviation(glucoseValues)
};
})
};
})
allUserDeviation = flatUserArray
.map((d) => {
return d.days.map((e) => {
return e.deviation;
});
})
.flat()
ids = Array.from(userDataByDays.keys())
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x))
// normal_curve = {
// const points = [];
// for (let value of d3.range(...x.domain(), bin_width / 10)) {
// points.push([
// value,
// dnorm(value, sample_mean, sample_sd) * bin_width * sample_size
// ]);
// }
// return points;
// }
sample_sd = ssd(sample)
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