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interesting.html
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<!--
This is an experiment in auto-styling dataset visualizations based on auto-detected datatypes.
Example dataset:
http://192.168.1.108:8080/auto-styling.html?dataset=8581a7460e144ae09ad25d47f8e82af8_0
-->
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="initial-scale=1,maximum-scale=1,user-scalable=no"
/>
<title>Interesting</title>
<link href="interesting.css" rel="stylesheet">
<script src="https://unpkg.com/[email protected]/lodash.js"></script>
<!-- <link rel="stylesheet" href="https://s3-us-west-1.amazonaws.com/patterns.esri.com/files/calcite-web/1.2.5/css/calcite-web.min.css"> -->
<!-- <script src="https://s3-us-west-1.amazonaws.com/patterns.esri.com/files/calcite-web/1.2.5/js/calcite-web.min.js"></script> -->
<!-- calcite components -->
<script
type="module"
src="https://unpkg.com/@esri/[email protected]/dist/calcite/calcite.esm.js"
></script>
<link
rel="stylesheet"
type="text/css"
href="https://unpkg.com/@esri/[email protected]/dist/calcite/calcite.css"
/>
<!-- 3rd party libraries -->
<script src="https://d3js.org/d3.v4.js"></script>
<script src="https://cdn.jsdelivr.net/npm/jstat@latest/dist/jstat.min.js"></script>
<script type="module">
import { loadModules, setDefaultOptions } from 'https://unpkg.com/esri-loader/dist/esm/esri-loader.js';
(async () => {
setDefaultOptions({
css: true,
// url: 'http://localhost:8000/buildOutput/init.js',
// url: 'https://jscore.esri.com/debug/4.16/dojo/dojo.js',
// version: 'next',
});
const [
Map,
MapView,
FeatureLayer,
generateHistogram,
HistogramRangeSlider,
Histogram,
uniqueValues,
Legend,
Renderer,
colorRamps,
Color,
] = await loadModules([
"esri/Map",
"esri/views/MapView",
"esri/layers/FeatureLayer",
"esri/renderers/smartMapping/statistics/histogram",
"esri/widgets/HistogramRangeSlider",
"esri/widgets/Histogram",
"esri/renderers/smartMapping/statistics/uniqueValues",
"esri/widgets/Legend",
"esri/renderers/Renderer",
"esri/renderers/smartMapping/symbology/support/colorRamps",
"esri/renderers/smartMapping/symbology/color",
]);
// data urls
var datasets = {
'Citclops Water': "8581a7460e144ae09ad25d47f8e82af8_0",
'Tucson Demographics': "35fda63efad14a7b8c2a0a68d77020b7_0",
'Seattle Bike Facilities': "f4f509fa13504fb7957cef168fad74f0_1",
'Traffic Circles': "717b10434d4945658355eba78b66971a_6",
'Black Cat Range': "28b0a8a0727d4cc5a2b9703cf6ca4425_0",
'King County Photos': "383878300c4c4f8c940272ba5bfcce34_1036",
'NYC bags': "7264acdf886941199f7c01648ba04e6b_0",
}
// dataset switcher
var datasetList = document.getElementById('datasetList');
for (let [key, value] of Object.entries(datasets)) {
// create new option element and add it to the dropdown
var opt = document.createElement('option');
opt.text = key;
opt.value = value;
datasetList.appendChild(opt);
}
datasetList.addEventListener('change', async event => {
({ layer, dataset } = await loadDataset({ datasetId: event.target.value, env: 'prod' }));
});
// track widgets and state
var timeSlider = null;
var dataset = null;
var layer = null;
// var zoomToDataCheckbox;
var attributeList;
// URL params
const params = new URLSearchParams(window.location.search);
var env = 'prod';
if (Array.from(params).length != 0) {
var datasetId = params.get('dataset');
const datasetSlug = params.get('slug');
({ layer, dataset } = await loadDataset({ datasetId: datasetId, datasetSlug: datasetSlug, env: env }));
env = params.get('env');
} else {
var datasetId = datasetList.options[datasetList.selectedIndex].value;
({ layer, dataset } = await loadDataset({ datasetId: datasetId, env: env }));
}
// add event listener to dropdown, to create visualizations
attributeList.addEventListener('calciteDropdownItemSelected', switchSelected);
async function switchSelected (event, fieldName = null) {
fieldName = fieldName ? fieldName : event.target.getAttribute('data-field');
const field = getDatasetField(dataset, fieldName);
document.querySelector('#attributeListButton').innerHTML = fieldName;
// Reset UI state
document.getElementById('widget').innerHTML = ''; // clear previous widget
document.getElementById('widgetMessage').innerHTML = ''; // clear previous message
// guess at a style for this field
try {
// initialize a new layer
var layer = new FeatureLayer({
renderer: {type: 'simple'},
url: dataset.attributes.url
});
switchStyles(null, layer, fieldName);
} catch(e) {
console.log('e:', e)
}
}
async function switchStyles(view, layer, fieldName) {
var field;
try {
if (!view) {
var view = await drawMap(layer, dataset)
}
widgetMessage.innerText = 'Drawing '+fieldName+'.';
const layerView = await view.whenLayerView(layer);
} catch(e) {
console.error(new Error(e));
const layerView = await view.whenLayerView(layer);
}
var {renderer, stats} = await autoStyle(fieldName, dataset, layer);
field = getDatasetField(dataset, fieldName);
layer.renderer = renderer;
layer.minScale = 0; // draw at all scales
layer.outFields = ["*"]; // get all fields (easier for prototyping, optimize by managing for necessary fields)
// clear previous filters
if (typeof layerView != 'undefined') {
updateLayerViewEffect(layerView, { updateExtent: true });
}
// Numeric fields - histogram
if (field.simpleType === 'numeric' || field.simpleType === 'date') {
// add a result row and get the container for a minihistogram
let minicontainer = addResultRow(stats);
const histogram = await createHistogram({ dataset, fieldName, layer, layerView, container: minicontainer, slider: false });
}
else {
widgetMessage.innerText += '\nThis field\'s datatype is ""'+field.simpleType+'""; things might be funky.';
}
};
function addResultRow(stats) {
let table = document.getElementById('resultsTable')
.getElementsByTagName('table')[0];
table = table.getElementsByTagName('tbody')[0] ? table.getElementsByTagName('tbody')[0] : table;
window.table = table;
if (table.getElementsByTagName('tr').length == 0) {
// make a headings row
const row = document.createElement('tr');
var columns = Object.keys(stats);
for (let x in columns) {
var cell = row.appendChild(document.createElement('td'));
cell.innerHTML = columns[x];
}
table.appendChild(row);
}
// make a values row
let row = document.createElement('tr');
columns = Object.values(stats);
table.appendChild(row);
let cells = row.getElementsByTagName('td');
columns = Object.keys(stats);
for (let x in columns) {
var cell = row.appendChild(document.createElement('td'));
cell.innerHTML = stats[columns[x]];
}
// one more td for the chart
let target = row.appendChild(document.createElement('td'));
const minicontainer = document.createElement('div');
minicontainer.classList.add('miniHistogram');
target.appendChild(minicontainer);
return minicontainer;
}
async function drawMap(layer, dataset) {
const map = new Map({
basemap: "dark-gray-vector",
layers: layer,
});
const view = new MapView({
container: "viewDiv",
map: map,
extent: getDatasetExtent(dataset),
ui: { components: [] }
});
const layerView = await view.whenLayerView(layer).then((layerView) => {
// var legend = await new Legend({
// view: view,
// layerInfos: [{
// layer: layer,
// title: "Legend"
// }]
// });
// view.ui.add(legend, "bottom-right");
});
// put vars on window for debugging
Object.assign(window, { view, map, dataset, layer, layerView, getDatasetField, getDatasetFieldUniqueValues, /*histogram, histogramValues,*/ generateHistogram, HistogramRangeSlider, uniqueValues });
// Dataset info
document.querySelector('#datasetName').innerHTML = dataset.attributes.name;
document.querySelector('#orgName').innerHTML = dataset.attributes.orgName || '';
document.querySelector('#recordCount').innerHTML = `${dataset.attributes.recordCount} records`;
return view;
}
// update layerview filter based on histogram widget, throttled
const updateLayerViewWithHistogram = _.throttle(
async (layerView, fieldName, where) => {
await updateLayerViewEffect(layerView, { where: where, updateExtent: true });
},
50
);
async function loadDataset (args) {
if (args.url) { // dataset url provided directly
const datasetURL = args.url;
try {
// dataset = (await fetch(datasetURL).then(r => r.json()));
dataset = {attributes: {url: args.url}}
} catch(e) { console.log('failed to load dataset from url:', args.url, e); }
} else if (args.datasetId) { // dataset id provided directly
// https://opendataqa.arcgis.com/api/v3/datasets/97a641ac39904f349fb5fc25b94207f6
const datasetURL = `https://opendata${args.env === 'qa' ? 'qa' : ''}.arcgis.com/api/v3/datasets/${args.datasetId}`;
try {
dataset = (await fetch(datasetURL).then(r => r.json())).data;
} catch(e) { console.log('failed to load dataset from id', args.datasetId, e); }
} else if (args.datasetSlug) { // dataset slug provided as alternate
// https://opendata.arcgis.com/api/v3/datasets?filter%5Bslug%5D=kingcounty%3A%3Aphoto-centers-for-2010-king-county-orthoimagery-project-ortho-image10-point
const filter = `${encodeURIComponent('filter[slug]')}=${encodeURIComponent(args.datasetSlug)}`
const datasetURL = `https://opendata${args.env === 'qa' ? 'qa' : ''}.arcgis.com/api/v3/datasets?${filter}`;
try {
dataset = (await fetch(datasetURL).then(r => r.json())).data[0];
} catch(e) { console.log('failed to load dataset from slug', args.datasetSlug, e); }
}
attributeList = updateAttributeList(dataset)
let predefinedStyle = dataset.attributes?.layer?.drawingInfo;
var renderer;
let fieldName = Object.keys(dataset.attributes.statistics.numeric)[0]
let field = getDatasetField(dataset, fieldName)
switchSelected(null, field.name);
for (let x in Object.keys(dataset.attributes.statistics.numeric)) {
let fieldName = Object.keys(dataset.attributes.statistics.numeric)[x]
let field = getDatasetField(dataset, fieldName)
switchSelected(null, field.name);
}
return { dataset, layer };
}
// analyze a dataset and choose an initial best-guess symbology for it
async function autoStyle(fieldName, dataset, layer) {
const geometryType = dataset.attributes.geometryType;
var field = getDatasetField(dataset, fieldName);
let datasetStats = dataset.attributes.statistics[field.simpleType][fieldName.toLowerCase()].statistics;
let fieldStats = field.statistics;
let minValue = fieldStats.values.min;
let maxValue = fieldStats.values.max;
let symbol;
var geotype = (geometryType == 'esriGeometryPoint') ? 'point'
: (geometryType == 'esriGeometryMultiPoint') ? 'point'
: (geometryType == 'esriGeometryPolygon') ? 'polygon'
: (geometryType == 'esriGeometryLine') ? 'line'
: (geometryType == 'esriGeometryPolyline') ? 'line'
: geometryType;
if (!!layer) {
var query = layer.createQuery();
// query.outFields = [fieldName]
try {
let uniqueValues = (await getDatasetFieldUniqueValues(dataset, fieldName, layer)).values;
let domain = [Math.min(...uniqueValues.map(a => a.value)),
Math.max(...uniqueValues.map(a => a.value))]
// remove nulls
var filtered = uniqueValues.filter(a => a.value != null);
// manually reconstruct a feature values array from the unique values and their counts -
// normalize array length to 1000, as precision isn't as important as speed here
// const divisor = dataset.attributes.recordCount / 1000;
// use the whole set
const divisor = 1;
let arr = [];
for (let x = 0; x < filtered.length; x++) {
for (let y = 0; y < Math.ceil(filtered[x].count/divisor); y++) {
arr.push(filtered[x].value);
};
}
var numBins = (uniqueValues.length > 30 ? 30 : uniqueValues.length)
// use d3 to bin histograms
let d3bins = d3.histogram() // create layout object
.domain([Math.min(...filtered.map(a => a.value)),
Math.max(...filtered.map(a => a.value))]) // to cover range
.thresholds(numBins - 1) // separated into 30 bins
(arr); // pass the array
// convert the d3 bins array to a bins object
var bins = [];
for (let x = 0; x < d3bins.length; x++) {
bins.push({
minValue: d3bins[x]['x0'],
maxValue: d3bins[x]['x1'],
count: d3bins[x].length,
});
}
// put the bins in the params object
var values = {
'bins': bins,
'minValue': Math.min(...filtered.map(a => a.value)),
'maxValue': Math.max(...filtered.map(a => a.value)),
}
const featureCount = arr.length;
var source = 'layerQuery';
var coverage = 1;
} catch(e) {
// histogram generation failed with unique values, try using features in layer view
console.log('histogram generation failed with unique values, try using features in layer view:');
console.error(new Error(e));
if (typeof layerView != 'undefined') {
const { features } = await layerView.queryFeatures();
const featureCount = await layer.queryFeatureCount();
var values = await generateHistogram(params);
var source = 'layerView';
var coverage = params.features.length / featureCount;
} else {
console.warn('No layerView')
}
}
var {features} = await layer.queryFeatures(query);
var numValues = datasetStats.values.count;
// v simple way to vary point size with number of data points
// 1-9: 20px
// 10-99: 10px
// 100-999: 5px
// 1000-9999: 2.5px
var pointSize = 20/(datasetStats.values.count+'').length; // convert to string to get power of 10
var opacity = 1;
if (geotype == "point" || geotype == "line") {
if (numValues > 5000) {
opacity = .50;
} else if (numValues > 1000) {
opacity = .75;
}
}
if (features) {
var values = Object.values(features).map(v => v.attributes[fieldName])
var distribution = getDistribution(values, datasetStats.values, field.simpleType);
var interestingness = distribution.interesting;
widgetMessage.innerHTML += '<br>'+distribution.message+'.';
} else {
console.log('no features returned for', fieldName)
}
}
if (geometryType === 'esriGeometryPoint') {
let stats = dataset.attributes.statistics
// scale point size based on viewport size, number of points, and "clumpiness" of the data,
// in order to reduce overlap of points
// if there's still a lot of points, adjust opacity to show points through each other
// pick a color scheme based on distribution of the data:
// if a linear distribution, choose a linear–
// if a log or exp distribution, choose log or exp –
// if a normal distribution or something similar, choose "extremes"
// choose colors based on background theme – dark on light, light on dark
symbol = {
type: "simple-marker",
outline: {
// makes the outlines of all features consistently light gray
color: "lightgray",
width: 0.05*pointSize
},
size: pointSize+'px',
opacity: opacity,
}
}
else if (geometryType === 'esriGeometryPolyline') {
symbol = {type: 'simple-line', width: '4px' };
}
else if (geometryType === 'esriGeometryPolygon') {
symbol = {type: 'simple-fill' };
}
// choose ramp
let thisramp = colorRamps.byName("Heatmap 9");
var rampColors = thisramp.colors;
widgetMessage.innerText += '\nShowing '+fieldStats.values.count+' '+field.simpleType+' values.';
var rMin = rampColors[0];
var rMid = rampColors[Math.floor((rampColors.length-1)/2)];
var rMax = rampColors[rampColors.length-1];
var renderer = {
type: "simple", // autocasts as new SimpleRenderer()
symbol: symbol,
visualVariables: [{
type: "color", // indicates this is a color visual variable
field: fieldName,
// normalizationField: "TOTPOP_CY", // total population
stops: [{
value: minValue,
color: {r: rMin.r, g: rMin.g, b: rMin.b, a: opacity},
label: minValue
},{
value: (maxValue+minValue)/2,
color: {r: rMid.r, g: rMid.g, b: rMid.b, a: opacity},
label: (maxValue+minValue)/2,
},{
value: maxValue,
color: {r: rMax.r, g: rMax.g, b: rMax.b, a: opacity},
label: maxValue
}]
}]
};
return {renderer: renderer, stats: distribution.stats};
}
function getDistribution(values, stats, type) {
let msg = [];
let js = jStat(values)
let uniqueValues = new Set(values);
let sampleCount = values.length;
msg.push('Sample count: '+sampleCount)
let uniquesCount = uniqueValues.size;
let uniqueness = uniqueValues.size/values.length;
msg.push('Uniqueness: '+uniqueness)
let result = {};
if (uniquesCount === 1) {
msg.push('- no unique values')
uniqueness = 0;
} else {
if (uniqueness < .25) msg.push('- very few unique values ('+uniquesCount+')')
else if (uniqueness < .5) msg.push('- few unique values')
else if (uniqueness < .75) msg.push('- few repeated values')
else if (uniqueness < 1) msg.push('- very few repeated values')
else msg.push('- no repeated values')
}
if (type != "string") {
if (stats) {
var min = stats.min;
var max = stats.max;
var midpoint = max-min/2;
var range = max-min; // distance between min and max
var mean = stats.avg;
var variance = stats.var;
var stdev = stats.stddev;
var count = stats.count;
} else {
var min = jStat.min(values);
var max = jStat.max(values);
var midpoint = max-min/2;
var range = max-min; // distance between min and max
var mean = jStat.mean(values);
var variance = jStat.variance(values);
var stdev = jStat.stdev(values);
var count = values.length;
}
let mode = jStat.mode(values);
let stddev = jStat.stdev(values); // standard deviation
let meddev = jStat.meddev(values); // median absolute deviation
let diffdev = meddev - stddev; // difference between the two – detects outliers
let quartiles = jStat.quartiles(values);
let IQR = quartiles[2]-quartiles[0];
let IQRrange = IQR/range;
msg.push('Min: '+min+', Max: '+max+', Range: '+range)
msg.push('Mean: '+mean)
msg.push('IQR: '+IQR)
msg.push('IQR/Range: '+ (IQR/range))
let clustered = IQR/range;
let interesting = 0;
if (!clustered) {
clustered = 0;
interesting += 1;
msg.push('- highly clustered')
} else if (clustered < .2) {
msg.push('- highly clustered')
interesting += .8;
}
else if (clustered < .4) {
msg.push('- somewhat clustered');
interesting += .6;
} else if (clustered < .6) {
msg.push("- roughly uniform");
interesting += .4;
}
else if (clustered < .8) {
msg.push('- somewhat dispersed')
interesting += .2;
} else {
msg.push('- highly dispersed')
}
if (uniqueness != 1) {
if (!!mode) {
if (typeof mode === "Array") {
msg.push(mode.length+" Modes")
} else {
msg.push('Mode: '+mode);
}
msg.push('jsapi Stdev: '+stdev)
msg.push('jStat Stdev: '+stddev)
msg.push('Meddev: '+meddev)
msg.push('Diffdev: '+diffdev)
if (mode.length > 1) {
msg.push('- with '+mode.length+' modes')
} else {
interesting += 1;
}
}
}
let meanLocation = (mean-min)/range; // how far along in the range is the mean? subtract min to account for offsets
msg.push('meanLocation: '+meanLocation)
if (!!meanLocation) {
if (meanLocation < .3) {
msg.push('- skewed low')
interesting += 1;
}
else if (meanLocation < .45) {
msg.push('- skewed a bit low')
interesting += .5;
}
else if (meanLocation < .55) {
msg.push('- roughly symmetrical')
}
else if (meanLocation < .7) {
msg.push('- skewed a bit high')
interesting += .5;
}
else {
msg.push('- skewed high')
interesting += 1;
}
if ((mode === min && meanLocation < .25) || (mode === max && meanLocation > .5)) {
msg.push('- possibly exponential');
interesting += 1;
} else if ((mode === min && meanLocation > .75) || (mode === max && meanLocation < .5)) {
msg.push('- possibly logarithmic');
interesting += 1;
}
}
let variability = meddev/range;
msg.push('Variablility: '+variability)
if (!!variability) {
if (variability < .2) {
msg.push('- highly regular');
} else if (variability < .4) {
msg.push('- generally regular');
} else if (variability < .6) {
msg.push('- slightly variable');
} else if (variability < .8) msg.push('- moderately variable')
else msg.push('- highly variable')
} else {
msg.push('- with no apparent variability')
variability = 0;
interesting += .5;
}
mode = mode.length ? mode.reduce((a, b) => a + b) / mode.length : mode;
console.log('mode:', mode);
result.stats = {
min: min < 1 ? Math.round(min) : min.toPrecision(2),
max: max > 1 ? Math.round(max) : max.toPrecision(2),
mode: mode.toPrecision(2),
uniqueness: uniqueness.toPrecision(2),
variability: variability.toPrecision(2),
meanLocation: meanLocation.toPrecision(2),
clustered: clustered.toPrecision(2),
interesting: interesting,
}
}
msg = msg.join('<br>');
result.message = msg;
return result;
}
window.getDistribution = getDistribution;
function loadRenderer (type, props) {
return loadModules(
[`esri/renderers/smartMapping/creators/${type}`]
).then(([rendererCreator]) => {
const creatorFn = type === 'color'
? 'createContinuousRenderer'
: type === 'size'
? 'createContinuousRenderer' // 'createClassBreaksRenderer'
: 'createRenderer';
return rendererCreator[creatorFn](props)
.then(response => response.renderer);
});
}
function getDatasetExtent (dataset) {
const extent = dataset.attributes.extent;
return {
xmin: extent.coordinates[0][0],
ymin: extent.coordinates[0][1],
xmax: extent.coordinates[1][0],
ymax: extent.coordinates[1][1],
spatialReference: extent.spatialReference
};
}
function getDatasetField (dataset, fieldName) {
fieldName = fieldName.toLowerCase();
const field = dataset.attributes.fields.find(f => f.name.toLowerCase() === fieldName);
const stats = [...Object.entries(dataset.attributes.statistics).values()].find(([, fields]) => fields[fieldName]);
// add "simple type" (numeric, date, string) and stats into rest of field definition
return {
...field,
simpleType: stats && stats[0],
statistics: stats && stats[1][fieldName].statistics
}
}
const DATASET_FIELD_UNIQUE_VALUES = {}; // cache by field name
async function getDatasetFieldUniqueValues (dataset, fieldName, layer) {
if (!DATASET_FIELD_UNIQUE_VALUES[fieldName]) {
const field = getDatasetField(dataset, fieldName);
let stats;
if (field.statistics && field.statistics.uniqueCount) {
stats = { ...field.statistics };
} else {
const uniqueValueInfos = (await uniqueValues({ layer, field: fieldName }))
.uniqueValueInfos
.sort((a, b) => a.count > b.count ? -1 : 1);
const count = uniqueValueInfos.reduce((count, f) => count + f.count, 0);
stats = {
count,
uniqueCount: uniqueValueInfos.length,
values: uniqueValueInfos
}
}
// add percent of records
stats.values = stats.values
// .filter(v => v.value != null && (typeof v.value !== 'string' || v.value.trim() !== ''))
.map(v => ({ ...v, pct: v.count / stats.count }));
// get top values
const maxTopValCount = 12;
// stats.topValues = stats.values.slice(0, maxTopValCount);
stats.topValues = [];
if (stats.uniqueCount < maxTopValCount) {
stats.topValues = stats.values;
} else {
let coverage = 0;
for (let i=0, coverage=0; i < stats.values.length; i++) {
// let stat = { ...stats.values[i], pct: stats.values[i].count / recordCount };
const stat = stats.values[i];
// if (coverage >= 0.80 && stat.pct < 0.05 && stats.topValues.length >= maxTopValCount) break;
if (stat.pct < 0.015 || stats.topValues.length >= maxTopValCount) break;
stats.topValues.push(stat);
coverage += stat.pct;
}
}
DATASET_FIELD_UNIQUE_VALUES[fieldName] = stats;
}
return DATASET_FIELD_UNIQUE_VALUES[fieldName];
}
// Determine if field is an integer
async function datasetFieldIsInteger (field) {
if (field.type.toLowerCase().includes('integer')) { // explicit integer type
return true;
} else { // or check the known values to see if they're all integers
const stats = await getDatasetFieldUniqueValues(dataset, field.name, layer);
return stats.values.every(v => v.value == null || Number.isInteger(v.value));
}
}
// Add an entry to the attribute dropdown
function updateAttributeList (dataset) {
// create <calcite-dropdown-item> for each attribute
const attributeList = document.querySelector('#attributeList > calcite-dropdown-group');
// clear existing entries
Array.from(attributeList.children)
.forEach(i => attributeList.removeChild(i))
const attributes = [
...Object.entries(dataset.attributes.statistics.numeric || {}),
...Object.entries(dataset.attributes.statistics.date || {}),
...Object.entries(dataset.attributes.statistics.string || {})
];
attributes
.map(([fieldName, { statistics: fieldStats }]) => [fieldName, fieldStats]) // grab stats
.filter(([fieldName, fieldStats]) => { // exclude fields with one value
return !fieldStats ||
!fieldStats.values ||
fieldStats.uniqueCount > 1 || // unique count reported as 0 for sampled data
fieldStats.values.min !== fieldStats.values.max
})
.forEach(([fieldName, fieldStats]) => {
// dataset.attributes.fieldNames
// .map(fieldName => [fieldName, getDatasetField(dataset, fieldName)])
// .filter(([fieldName, field]) => !field.statistics || field.statistics.values.min !== field.statistics.values.max)
// .forEach(([fieldName, field]) => {
const field = getDatasetField(dataset, fieldName);
// const fieldStats = field.statistics.values;
const item = document.createElement('calcite-dropdown-item');
item.innerHTML = `${field.alias || fieldName}`;
if (fieldStats && fieldStats.values && fieldStats.values.min != null && fieldStats.values.max != null) {
if (field.simpleType === 'numeric') {
// TODO: vary precision based on value range
item.innerHTML += `<br><small>(${fieldStats.values.min.toFixed(2)} to ${fieldStats.values.max.toFixed(2)})</small>`;
} else if (field.simpleType === 'date') {
item.innerHTML += ` (${formatDate(fieldStats.values.min)} to ${formatDate(fieldStats.values.max)})`;
}
} else if (fieldStats && fieldStats.uniqueCount && field.simpleType === 'string') {
item.innerHTML += ` (${fieldStats.uniqueCount} values)`;
}
// add icon for field type
if (field.simpleType === 'numeric') {
item.iconEnd = 'number';
} else if (field.simpleType === 'string') {
item.iconEnd = 'description';
} else if (field.simpleType === 'date') {
item.iconEnd = 'calendar';
}
item.setAttribute('data-field', field.name);
attributeList.appendChild(item);
});
return attributeList;
}
async function updateLayerViewEffect(layerView, { where = undefined, updateExtent = true } = {}) {
layerView.filter = null;
if (where) {
layerView.effect = {
filter: {
where,
},
excludedEffect: 'grayscale(100%) opacity(15%)'
};
}
// adjust view extent (in or out) to fit all filtered data
if (updateExtent) {
try {
let featureExtent;
const queriedExtent = await layerView.layer.queryExtent({
where: (layerView.effect && layerView.effect.filter && layerView.effect.filter.where) || '1=1',
outSpatialReference: layerView.view.spatialReference
});
if (queriedExtent.count > 0) {
featureExtent = queriedExtent.extent.expand(1.10);
} else {
return;
}
if (!layerView.view.extent.contains(featureExtent) ||
(featureExtent.width * featureExtent.height) / (layerView.view.extent.width * layerView.view.extent.height) < 0.20) {
layerView.view.goTo(featureExtent, { duration: 350 });
}
} catch(e) {
console.log('could not query or project feature extent to update viewport', e);
}
}
}
async function createHistogram ({dataset, fieldName, layer, layerView, container, slider = false }) {
// wrap in another container to handle height without fighting w/JSAPI and rest of sidebar
const parentContainer = container;
container = document.createElement('div');
parentContainer.appendChild(container);
let uniqueValues = (await getDatasetFieldUniqueValues(dataset, fieldName, layer)).values;
var numBins = (uniqueValues.length > 30 ? 30 : uniqueValues.length)
try {
const params = {
layer: layer,
field: fieldName,
numBins: numBins
};
let values, source, coverage;
try {
values = await generateHistogram(params);
source = 'widget';
coverage = 1;
} catch(e) {
try {
// histogram generation failed with automated server call, try using features from server query
console.log('histogram generation failed with automated server call, try using features from server query');
params.features = (await layer.queryFeatures()).features;
const featureCount = await layer.queryFeatureCount();
values = await generateHistogram(params);
source = 'layerQuery';
// coverage = params.features.length / featureCount;
coverage = 1;
} catch(e) {
// histogram generation failed with server call, try using features in layer view
console.log('histogram generation failed with server call, try using features in layer view');
params.features = (await layerView.queryFeatures()).features;
const featureCount = await layer.queryFeatureCount();
values = await generateHistogram(params);
source = 'layerView';
coverage = params.features.length / featureCount;
}
}
// Determine if field is an integer
const field = getDatasetField(dataset, fieldName);
const integer = await datasetFieldIsInteger(field);
let widget;
if (slider) {
// Histogram range slider widget
widget = new HistogramRangeSlider({
bins: values.bins,
min: values.minValue,
max: values.maxValue+1,
values: [values.minValue, values.maxValue+1],
precision: integer ? 0 : 2,
container: container,
excludedBarColor: "#dddddd",
rangeType: "between",
labelFormatFunction: (value, type) => {
// apply date formatting to histogram
if (field.simpleType == 'date') {
return formatDate(value);
}
return value;
}
});
} else {
// plain histogram, for miniHistogram nested in timeSlider
widget = new Histogram({
bins: values.bins,
min: values.minValue,
max: values.maxValue,
container: container,
rangeType: "between",
});
}
return { widget, values, source, coverage };
}
catch(e) {
console.log('histogram generation failed', e);
return {};
}
}
async function createTimeSlider ({ dataset, fieldName, layerView, container }) {
try {
const field = getDatasetField(dataset, fieldName);
// let {min: startDate, max: endDate } = dataset.attributes.statistics.date[fieldname.toLowerCase()].statistics.values;
const startDate = new Date(field.statistics.values.min);
const endDate = new Date(field.statistics.values.max);
const widget = new TimeSlider({
container: container,
// view: view,
mode: "time-window",
fullTimeExtent: {
start: startDate,
end: endDate,
},
values: [
startDate,
endDate
],
});
// handle play button behavior
let selectionWasFullExtent;
widget.watch('viewModel.state', function(state){
if (state == "playing") {
// check values (date selection) against fullTimeExtent
// convert to numeric values with unary + operator to check equivalence (with a 10% tolerance)
if ( +this.values[0] == +this.fullTimeExtent.start &&
Math.abs(+this.values[1] - +this.fullTimeExtent.end) <
(+new Date(this.fullTimeExtent.end) - +new Date(this.fullTimeExtent.start))/ 10 ) {
// make a note
selectionWasFullExtent = true;
// set new selection end to 10% through the date range
this.values[1] = new Date(+new Date(this.fullTimeExtent.start) + (+new Date(this.fullTimeExtent.end) - +new Date(this.fullTimeExtent.start)) / 10);
}
}
else if (state == "ready" && selectionWasFullExtent) {
// reset note
selectionWasFullExtent = false;
this.values = [this.fullTimeExtent.start, this.fullTimeExtent.end];
}
});
return { widget };
}
catch(e) {
console.log(e);
return {};
}
}
function formatDate (timestamp) {
const date = new Date(timestamp);
return `${date.getMonth()+1}/${date.getDate()}/${date.getFullYear()}`;
}
function simpleFieldType (fieldType) {
const fieldTypes = {
esriFieldTypeGlobalID: 'text',
esriFieldTypeGUID: 'text',
esriFieldTypeDate: 'date-time',
esriFieldTypeString: 'string',
esriFieldTypeSingle: 'number',
esriFieldTypeFloat: 'number',
esriFieldTypeDouble: 'number',
esriFieldTypeInteger: 'number',
esriFieldTypeSmallInteger: 'number',
esriFieldTypeOID: 'number',
};