Swarthmore Battery OptimizationHorton AWS SimulationsHorton AWS ResultsNYC TypologiesYale Berkeley UpdateNYC Electrification Results - Capacity ConstraintsBay Area CFE AppendixNYC Electrification Results - Updated MetricsCoorsTek 9th St. RedevelopmentCharacterization Experiments100 (ish) cities to simulateDisaggregation ExplorationsUtilitiesDisaggregation Graph V2Combinations TestCharacterization ExperimentsCombinations Test First Week ConstrainedCharacterization Graph V2Model Input CalibrationUT Model ResultsMIT Model Input CalibrationMIT EEMsMIT Final Model ResultsMIT EEM All BuildingsMIT Monthly Baseline ResultsHorton Analysis ResultsHorton Solar + StorageGoogle Input CalibrationGoogle Monthly Baseline ResultsGoogle EEMsDC Energy Data AggregationEmissions VisualizationEPW ReaderSunpath DiagramPyschrometric Chart
UT EEM All Buildings
md`# UT EEM All Buildings`
xlsx = require('https://bundle.run/xlsx@0.14.1')
viewof binary = html`<input type=file>`
input = new Uint8Array(await Files.buffer(binary))
wb = xlsx.read(input, {type: 'array'})
excel = wb.Sheets["Baseline"];
data = xlsx.utils.sheet_to_json(excel);
height = 775
d3 = require("d3@^6.1")
_ = require('lodash@4.17.15/lodash.js').catch(() => window["_"])
chroma = require('chroma-js')
ecm_data = {
const map = new Map();
for (const key of Object.keys(wb.Sheets)) {
let excel = wb.Sheets[key];
let dat = xlsx.utils.sheet_to_json(excel);
let f = dat.map(d => Math.max(d["SAVINGS"], 0));
map.set(key, quartiles(f));
}
return map;
}
quartiles = (data) => {
const values = data.sort((a, b) => a - b);
const min = values[0];
const max = values[values.length - 1];
const q1 = d3.quantile(values, 0.25);
const q2 = d3.quantile(values, 0.50);
const q3 = d3.quantile(values, 0.75);
const iqr = q3 - q1; // interquartile range
const r0 = Math.max(min, q1 - iqr * 1.5);
const r1 = Math.min(max, q3 + iqr * 1.5);
values.quartiles = [q1, q2, q3];
values.range = [r0, r1];
values.outliers = values.filter(v => v < r0 || v > r1); // TODO
return values;
}
lookup = ({
"Envelope": "Envelope",
"LPD": "LPD Reductions",
"HRV": "Heat Recovery",
"VENT2": "Ventilation Measures",
"VENT3": "Enhanced Ventilation",
"FanPower": "Fan Energy Reductions",
"Combined": "All Measures Combined"
// "STR60": "Supply Air Temperature Reset",
// "WAC": "Enhanced SAT Reset",
})
Array.from(ecm_data.values()).map(d => d.range[1])
y = d3.scaleBand()
.domain(Object.keys(wb.Sheets).reverse())
.range([height - margin.bottom, margin.top])
.padding(.1)
.paddingOuter(.5)
x = d3.scaleLinear()
.domain([1, d3.max(Array.from(ecm_data.values()).map(d => d.range[1]))]).nice()
.range([margin.left, width - margin.right])
margin = ({top: 80, right: 100, bottom: 50, left: 340})
xAxis = g => g
.attr("transform", `translate(0,${margin.top})`)
.call(d3.axisTop(x).tickPadding(10).tickFormat(d3.format("~s")))
// .call(g => g.select(".domain").remove())
.call(g => g.select(".tick:first-of-type text").clone()
.attr("y", -50)
.attr("x", -3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.html("Annual GHG Reductions (Tons CO2e/yr)"))
.call(g => g.selectAll(".tick line").clone()
.attr("stroke-opacity", 0.1)
.attr("y2", height - margin.bottom - 80))
display = d => {
let [building, measure] = d.split("-");
return `${building} ${lookup[measure]}`;
}
yAxis = g => g
.attr("transform", `translate(${5},0)`)
.call(d3.axisRight(y).tickFormat(d => display(d)))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").remove())
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.
