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<div id="text1" class="text-container">
<p>
Everyone needs access to clean water. Water insecurity is influenced by a number of social vulnerability indicators. This includes
<span
:class="['highlight', 'Demographiccharacteristics', { checked: isChecked.Demographiccharacteristics }]"
@click="toggleCategory('Demographiccharacteristics')"
:class="['highlight', 'Health', { checked: isChecked.Health }]"
@click="toggleCategory('Health')"
:class="['highlight', 'Livingconditions', { checked: isChecked.Livingconditions }]"
@click="toggleCategory('Livingconditions')"
:class="['highlight', 'Socioeconomicstatus', { checked: isChecked.Socioeconomicstatus }]"
@click="toggleCategory('Socioeconomicstatus')"
:class="['highlight', 'Riskperception', { checked: isChecked.Riskperception }]"
@click="toggleCategory('Riskperception')"
:class="['highlight', 'Landtenure', { checked: isChecked.Landtenure }]"
@click="toggleCategory('Landtenure')"
:class="['highlight', 'Exposure', { checked: isChecked.Exposure }]"
@click="toggleCategory('Exposure')"
>
exposure to stressors
</span> (like drought or pollution).
</p>
</div>
<div id="beeswarm-chart-container">
<div id="tooltip" style="position: absolute; opacity: 0; background: #f9f9f9; padding: 5px; border: 1px solid #ccc; border-radius: 5px;"></div>
</div>
import * as d3 from 'd3';
// Global variables
const publicPath = import.meta.env.BASE_URL;
const dataSet1 = ref([]);
const dataSet2 = ref([]);
const selectedDataSet = ref('dataSet1');
const data = ref([]);
let simulation;
// Set up SVG
let svg;
const height = 800;
const width = 800;
const margin = { top: 50, right: 20, bottom: 50, left: 50 };
const isChecked = ref({
Demographiccharacteristics: true,
Health: true,
Livingconditions: true,
Socioeconomicstatus: true,
Riskperception: true,
Landtenure: true,
Exposure: true
});
// Set colors for bubble charts
const dimensionColors = {
Demographiccharacteristics: "#092836",
Landtenure: "#1b695e",
Livingconditions: "#7a5195",
Socioeconomicstatus: "#2a468f",
Health: "#ef5675",
Riskperception: "#ff764a",
Exposure: "#ffa600"
};
// Load data and then make chart
onMounted(async () => {
try {
await loadDatasets();
data.value = selectedDataSet.value === 'dataSet1' ? dataSet1.value : dataSet2.value;
if (data.value.length > 0) {
createBeeswarmChart();
} else {
console.error('Error loading data');
} catch (error) {
console.error('Error during component mounting', error);
});
async function loadDatasets() {
try {
dataSet1.value = await loadData('determinant_uncertainty.csv');
dataSet2.value = await loadData('indicator_uncertainty.csv');
console.log('data in')
} catch (error) {
console.error('Error loading datasets', error);
}
async function loadData(fileName) {
try {
const data = await d3.csv(publicPath + fileName, d => {
d.level_agreement = +(+d.level_agreement).toFixed(2);
d.evidence_val = +d.evidence_val;
d.sig_value = +d.sig_value;
return d;
});
return data;
} catch (error) {
console.error(`Error loading data from ${fileName}`, error);
return [];
function createBeeswarmChart() {
svg = d3
.select('#beeswarm-chart-container')
.append('svg')
.attr('class', 'beeswarmSvg')
.attr('width', width)
.attr('height', height);
const yScale = d3.scaleLinear()
.domain([40, d3.max(data.value, d => d.level_agreement)])
.range([height-margin.bottom, margin.top]);
// Set radius based on evidence value
const radiusScale = d3.scaleLinear()
.domain([d3.min(data.value, d => d.evidence_val), d3.max(data.value, d => d.evidence_val)])
.call(d3.axisLeft(yScale).ticks(5))
.attr("stroke-width", 2)
.attr("font-size", 20);
// Add label to y axis
svg.append('text')
.attr("class", "yLabel")
.attr("text-anchor", "left")
.attr("transform", `translate(${margin.left}, ${margin.top/2})`)
.text("Level of Agreement");
svg.append('text')
.attr("class", "yLabel")
.attr("transform", `translate(${margin.left}, ${height - (margin.bottom/2)})`)
const forceY = d3.forceY(d => yScale(d.level_agreement)).strength(0.5);
const forceX = d3.forceX(margin.left + (width / 2)).strength(0.5);
const forceCollide = d3.forceCollide(d => radiusScale(d.evidence_val) + 5).iterations(20);
const forceManyBody = d3.forceManyBody().strength(-5);
const bubbles = svg
.selectAll('.bubble')
.data(data.value)
.enter()
.append('circle')
.attr('class', 'bubble')
.attr('r', d => radiusScale(d.evidence_val))
.style('fill', d => dimensionColors[d.dimension.replace(' ', '')])
.on('mouseover', function (event, d) {
const [x, y] = d3.pointer(event);
d3.select('#tooltip')
.style('opacity', 1)
.html(`<strong>${d.determinant}</strong><br>appeared in ${d.evidence_val} studies`)
.style('left', (x + 10) + 'px')
.style('top', (y - 28) + 'px');
d3.select(this)
.attr('stroke', d => dimensionColors[d.dimension.replace(' ', '')])
.attr('stroke-width', 15);
})
.on('mouseout', function () {
d3.select('#tooltip').style('opacity', 0);
d3.select(this)
.attr('stroke', null)
.attr('stroke-width', null);
// Run simulation
simulation = d3.forceSimulation()
.force('x', forceX)
.force('y', forceY)
.force('collide', forceCollide)
.force('charge', forceManyBody)
.nodes(data.value)
.on('tick', ticked)
.attr("cx", d => Math.max(margin.left +radiusScale(d.evidence_val), Math.min(width - margin.right - radiusScale(d.evidence_val), d.x)))
.attr("cy", d => Math.max(radiusScale(d.evidence_val), Math.min(height - radiusScale(d.evidence_val), d.y)))
.each(d => { d.y = Math.max(radiusScale(d.evidence_val), Math.min(height - radiusScale(d.evidence_val), yScale(d.level_agreement))); });
}
function toggleCategory(category) {
//console.log(`Toggle category called for: ${category}`);
isChecked.value[category] = !isChecked.value[category];
console.log(`Category toggled: ${category}, new value: ${isChecked.value[category]}`);
updateChart();
}
function updateChart() {
console.log('Update chart called');
const yScale = d3.scaleLinear()
.domain([40, d3.max(data.value, d => d.level_agreement)])
.range([height-margin.bottom, margin.top]);
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// Set radius based on evidence value
const radiusScale = d3.scaleLinear()
.domain([d3.min(data.value, d => d.evidence_val), d3.max(data.value, d => d.evidence_val)])
.range([10, 90]);
// Filter data based on active categories
const activeCategories = Object.keys(isChecked.value).filter(category => isChecked.value[category]);
const dataPoints = data.value.filter(d => activeCategories.includes(d.dimension.replace(' ', '')));
console.log('Active categories:', activeCategories);
console.log('Filtered data points:', dataPoints);
// Update existing bubbles and add new bubbles
const bubbles = svg.selectAll(".bubble")
.data(dataPoints, d => d.id);
// Remove old bubbles
bubbles.exit().remove();
// Update existing bubbles
bubbles
.attr('r', d => radiusScale(d.evidence_val))
.style('fill', d => dimensionColors[d.dimension.replace(' ', '')]);
// Add new bubbles
bubbles.enter()
.append('circle')
.attr('class', 'bubble')
.attr('r', d => radiusScale(d.evidence_val))
.style('fill', d => dimensionColors[d.dimension.replace(' ', '')])
.merge(bubbles) // Merge to apply forces to new and existing bubbles
.force('y', forceY)
.force('collide', forceCollide)
.force('charge', forceManyBody)
.alpha(0.2)
.restart();
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}
</script>
<style scoped lang="scss">
$switchWidth: 12rem;
$Demographiccharacteristics: #092836;
$Landtenure: #1b695e;
$Livingconditions: #7a5195;
$Socioeconomicstatus: #2a468f;
$Health: #ef5675;
$Riskperception: #ff764a;
$Exposure: #ffa600;
#beeswarm-chart-container {
text-align: center;
position: relative;
}
#beeswarm-chart-container svg {
max-width: 100%;
max-height: 100%;
height: auto; /* Maintain aspect ratio */
display: inline-block;
}
.bubble {
stroke: black;
stroke-width: 2px;
fill-opacity: 0.8;
}
.chart-text {
user-select: none;
}
.yLabel {
font-weight: bold;
}
.highlight {
color: white;
padding: 0.25px 5px;
border-radius: 10px;
white-space: nowrap;
font-weight: bold;
cursor: pointer; /* Add cursor pointer for better UX */
transition: all 0.1s; /* Smooth transition for background color and border */
}
.highlight:not(.checked) {
background-color: white;
border: 2px solid;
}
.highlight.Demographiccharacteristics {
background-color: $Demographiccharacteristics;
}
.highlight.Demographiccharacteristics:not(.checked) {
color: $Demographiccharacteristics;
border-color: $Demographiccharacteristics;
}
.highlight.Landtenure {
background-color: $Landtenure;
}
.highlight.Landtenure:not(.checked) {
color: $Landtenure;
border-color: $Landtenure;
}
.highlight.Livingconditions {
background-color: $Livingconditions;
}
.highlight.Livingconditions:not(.checked) {
color: $Livingconditions;
border-color: $Livingconditions;
}
.highlight.Socioeconomicstatus {
background-color: $Socioeconomicstatus;
}
.highlight.Socioeconomicstatus:not(.checked) {
color: $Socioeconomicstatus;
border-color: $Socioeconomicstatus;
}
.highlight.Health {
background-color: $Health;
}
.highlight.Health:not(.checked) {
color: $Health;
border-color: $Health;
}
.highlight.Riskperception {
background-color: $Riskperception;
}
.highlight.Riskperception:not(.checked) {
color: $Riskperception;
border-color: $Riskperception;
}
.highlight.Exposure {
background-color: $Exposure;
}
.highlight.Exposure:not(.checked) {
color: $Exposure;
border-color: $Exposure;
}
#tooltip {
position: absolute;
opacity: 0;
background: #f9f9f9;
padding: 5px;
border: 15px solid black;
border-radius: 15px;
pointer-events: none; /* Prevent tooltip from blocking mouse events */
}