Senior Data Scientist, MassMutual
Lecturer, UC Berkeley MIDS
--
PhD Applied Math, Computational Story Lab, UVM
MS Applied Math, UVM
BS Math, Virginia Tech
viewof enrollment = Inputs.date({
label: "Enrollment date",
value: "2022-12-20"
})
viewof now = Inputs.date({
label: "Current date",
value: dayjs()
})
points = [
{
name: "Sleep",
value: d3.sum(sleepSummaryPoints, (d) => d.points),
icon: "💤"
},
{
name: "Activity",
value: d3.sum(currentWeekActivePoints, (d) => d.points),
icon: "🏃♀️"
}
// { name: "Rest", value: 300, icon: "" }
]
sleep_devices = [
...d3
.group(
currentWeekSleepRecords.filter((d) => !d.sourceName.includes("iPhone")),
(d) => d.sourceName
)
.keys()
]
sleepSummaryPoints = d3
.rollups(
currentWeekSleepRecords
.filter(
(d) =>
d.sourceName === sleep_device &&
d.value.includes("HKCategoryValueSleepAnalysisAsleep")
)
.map((d) => ({
...d,
offsetStartDate: d.startDate.add(12, "hours"),
sleep_minutes: (d.endDate - d.startDate) / 1000 / 60
}))
.map((d) => ({
...d,
offsetStartDay: new Date(
d.offsetStartDate.$y,
d.offsetStartDate.$M,
d.offsetStartDate.$D
)
})),
(v) => Math.round(d3.sum(v, (d) => d.sleep_minutes)),
(d) => d.offsetStartDay
)
.map((d) => ({
date: d[0],
sleep_minutes: d[1],
points: point_lookup_fun(SLEEP_LOOKUP, d[1])
}))
bmr_hourly = d3.median(currentWeekBasalEnergyBurned, (d) => d.value) * 4
currentWeekActivePoints = currentWeekActiveEnergyBurned.map((d) => ({
...d,
points: (d.value / (bmr_hourly * MET_THRESHOLD)) * MAX_POINTS_ACTIVITIES
}))
Plot.plot({
width: width,
y: {
grid: true,
label: "Calories"
},
x: { type: "time" },
marks: [
Plot.rect(currentWeekBasalEnergyBurned, {
y1: 0,
y2: (d) => d.value,
x1: (d) => new Date(d.aggTime), // .format("YYYY-MM-DD hh:mm"),
x2: (d) => new Date(d.aggTime.add(15, "minutes")),
// width: 100,
fill: "steelblue"
})
]
})
Plot.plot({
width: width,
y: {
grid: true,
label: "Calories"
},
x: { type: "time" },
marks: [
Plot.rect(currentWeekActiveEnergyBurned, {
y1: 0,
y2: (d) => d.value,
x1: (d) => new Date(d.aggTime), // .format("YYYY-MM-DD hh:mm"),
x2: (d) => new Date(d.aggTime.add(15, "minutes")),
// width: 100,
fill: "steelblue"
})
]
})
Plot.plot({
width: width,
y: {
grid: true,
label: "Calories"
},
marks: [
Plot.rectY(
currentWeekBasalEnergyBurned,
Plot.binX(
{ y: "sum" },
{
y: (d) => d.value,
x: (d) => d.aggTime,
thresholds: d3.utcDay,
fill: "steelblue"
}
)
)
]
})
Plot.plot({
width: width,
y: {
grid: true,
label: "Calories"
},
marks: [
Plot.rectY(
currentWeekActiveEnergyBurned,
Plot.binX(
{ y: "sum" },
{
y: (d) => d.value,
x: (d) => d.aggTime,
thresholds: d3.utcDay,
fill: "steelblue"
}
)
)
]
})
currentWeekActiveEnergyBurned = getAggByInterval(
startOfWeek,
now,
currentWeekRecordsActiveEnergyBurned
)
currentWeekBasalEnergyBurned = getAggByInterval(
startOfWeek,
now,
currentWeekRecordsBasalEnergyBurned
)
startOfWeek = dayjs(now)
.utc(true)
.subtract(dayjs(now).day() - 1, "day")
.hour(0)
.minute(0)
.millisecond(0)
// weekyear: d.weekYear(),
// week: d.week(),
// weekday: d.day(),
currentWeekRecordsActiveEnergyBurned = currentWeekRecords.filter(
(d) => d.type === "HKQuantityTypeIdentifierActiveEnergyBurned"
)
currentWeekRecordsBasalEnergyBurned = currentWeekRecords
.filter((d) => d.type === "HKQuantityTypeIdentifierBasalEnergyBurned")
.map((d) => ({
...d,
source: basalEnergyBurnedRanking.indexOf(d.sourceName)
}))
activeEnergyBurnedRanking.indexOf("Connect")
activeEnergyBurnedRanking
activeEnergyBurnedRankingDebounced = debounce(viewof activeEnergyBurnedRanking)
currentWeekRecords = healthjson.HealthData.Record.map((d) => ({
...d,
// value: +d.value,
// startDate: new Date(d.startDate),
startDate: dayjs(d.startDate).utc(true),
// endDate: new Date(d.endDate),
endDate: dayjs(d.endDate).utc(true),
// creationDate: new Date(d.creationDate)
creationDate: dayjs(d.creationDate).utc(true),
source: activeEnergyBurnedRankingDebounced.indexOf(d.sourceName)
})).filter(
(d) =>
true &&
[
"HKQuantityTypeIdentifierActiveEnergyBurned",
"HKQuantityTypeIdentifierBasalEnergyBurned",
"HKQuantityTypeIdentifierStepCount"
].includes(d.type) &&
d.endDate >= startOfWeek
)
currentWeekSleepRecords = healthjson.HealthData.Record.map((d) => ({
...d,
// value: +d.value,
// startDate: new Date(d.startDate),
startDate: dayjs(d.startDate).utc(true),
// endDate: new Date(d.endDate),
endDate: dayjs(d.endDate).utc(true),
// creationDate: new Date(d.creationDate)
creationDate: dayjs(d.creationDate).utc(true)
})).filter(
(d) =>
true &&
["HKCategoryTypeIdentifierSleepAnalysis"].includes(d.type) &&
d.endDate >= startOfWeek.subtract(1, 'day').hour(14)
)
historicalDataLowRes = {
return {};
}
historicalDataHighRes = {
return {};
}
healthjson
import {
ArcChart,
mini_circle_fun
} from "@andyreagan/sleep-activity-combined-arc"
import { getAggByInterval } from "@andyreagan/split-overlapping-time-objects"
import { healthjson } with { zipfile as zipfile } from "@berkeleyvis/apple-health-xml-parse"
import {
instructions,
SLEEP_LOOKUP,
point_lookup_fun,
MAX_POINTS,
MAX_POINTS_ACTIVITIES,
MET_THRESHOLD,
blankInput as dummyInput
} from "@berkeleyvis/analyze-your-apple-health-data"
import { dayjs } from "@andyreagan/dayjs-loader"
import { debounce } from "@mbostock/debouncing-input"
import { SortableList } from "@andyreagan/sortable-list"
platforms = ["ios", "android"]
Object.keys(allowed_devices)
Object.keys(Object.fromEntries(platforms.map((d) => [d, {}])))
allowed_devices_byplatform = {
var tmp = Object.fromEntries(platforms.map((d) => [d, {}]));
for (const platform in tmp) {
for (const brand in allowed_devices) {
const filtered = allowed_devices[brand].devices.filter(
(d) => d[platform]
);
if (filtered.length > 0) {
tmp[platform][allowed_devices[brand].brand] = filtered;
}
}
}
return tmp;
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
