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254 lines
12 KiB
254 lines
12 KiB
<!DOCTYPE html>
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<html>
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<head>
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<title>M-Tree vs Sequential Search Comparison</title>
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<style>
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body {
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font-family: Arial, sans-serif;
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}
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#results {
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padding: 20px;
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border: 1px solid #ccc;
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border-radius: 10px;
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box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
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}
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table {
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border-collapse: collapse;
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}
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th,
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td {
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padding: 5px;
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border: 1px solid #ccc;
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}
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</style>
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</head>
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<body>
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<h1>M-Tree vs Sequential Search Comparison</h1>
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<form id="test-form">
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<label>
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Dataset size (points):
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<input type="number" id="dataset-size-min" value="1000" step="1000" />
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to
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<input type="number" id="dataset-size-max" value="100000" step="1000" />
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by
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<input type="number" id="dataset-size-step" value="1000" step="1000" />
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</label>
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<br>
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<label>
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Dimension:
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<input type="number" id="dimension-min" value="2" step="1" />
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to
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<input type="number" id="dimension-max" value="10" step="1" />
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by
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<input type="number" id="dimension-step" value="1" step="1" />
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</label>
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<br>
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<label>
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M-Tree node size:
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<input type="number" id="m-tree-node-size-min" value="4" step="1" />
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to
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<input type="number" id="m-tree-node-size-max" value="10" step="1" />
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by
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<input type="number" id="m-tree-node-size-step" value="1" step="1" />
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</label>
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<br>
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<button id="run-tests" type="submit">Run tests</button>
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</form>
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<div id="results"></div>
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<br>
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<button id="export-results" type="button">Export results to CSV</button>
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<script>
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const exportButton = document.getElementById('export-results');
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exportButton.addEventListener('click', () => {
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const table = resultsDiv.firstElementChild;
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const csv = [];
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for (const row of table.rows) {
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const rowArray = [];
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for (const cell of row.cells) {
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rowArray.push(cell.textContent);
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}
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csv.push(rowArray.join(','));
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}
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const csvString = csv.join('\n');
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const blob = new Blob([csvString], { type: 'text/csv' });
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const link = document.createElement('a');
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link.href = URL.createObjectURL(blob);
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//const configName = `dataset_${datasetSizeMin}`;//-${datasetSizeMax}_dimension_${dimensionMin}-${dimensionMax}_nodeSize_${mTreeNodeSizeMin}-${mTreeNodeSizeMax}`;
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link.download = `m-tree-test_${document.getElementById('dataset-size-min').value}.csv`;
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link.click();
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});
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</script>
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<script>
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const form = document.getElementById('test-form');
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const resultsDiv = document.getElementById('results');
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form.addEventListener('submit', (e) => {
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e.preventDefault();
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const datasetSizeMin = Number(document.getElementById('dataset-size-min').value);
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const datasetSizeMax = Number(document.getElementById('dataset-size-max').value);
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const datasetSizeStep = Number(document.getElementById('dataset-size-step').value);
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const dimensionMin = Number(document.getElementById('dimension-min').value);
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const dimensionMax = Number(document.getElementById('dimension-max').value);
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const dimensionStep = Number(document.getElementById('dimension-step').value);
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const mTreeNodeSizeMin = Number(document.getElementById('m-tree-node-size-min').value);
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const mTreeNodeSizeMax = Number(document.getElementById('m-tree-node-size-max').value);
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const mTreeNodeSizeStep = Number(document.getElementById('m-tree-node-size-step').value);
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resultsDiv.innerHTML = '';
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runTestsLoop(datasetSizeMin, datasetSizeMax, datasetSizeStep, dimensionMin, dimensionMax, dimensionStep, mTreeNodeSizeMin, mTreeNodeSizeMax, mTreeNodeSizeStep);
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});
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async function runTestsLoop(datasetSizeMin, datasetSizeMax, datasetSizeStep, dimensionMin, dimensionMax, dimensionStep, mTreeNodeSizeMin, mTreeNodeSizeMax, mTreeNodeSizeStep) {
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const table = document.createElement('table');
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const thead = document.createElement('thead');
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const tbody = document.createElement('tbody');
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table.appendChild(thead);
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table.appendChild(tbody);
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resultsDiv.appendChild(table);
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const headerRow = document.createElement('tr');
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['Dataset size', 'Dimension', 'M-Tree node size', 'Tree creation time', 'Range query time (MTree)', 'Range query time (Sequential)', 'KNN query time (MTree)', 'KNN query time (Sequential)', 'MTree range query calls', 'Sequential range query calls', 'MTree KNN query calls', 'Sequential KNN query calls']
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.forEach(header => {
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headerRow.appendChild(document.createElement('th')).textContent = header;
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});
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thead.appendChild(headerRow);
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for (let datasetSize = datasetSizeMin; datasetSize <= datasetSizeMax; datasetSize += datasetSizeStep) {
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for (let dimension = dimensionMin; dimension <= dimensionMax; dimension += dimensionStep) {
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for (let mTreeNodeSize = mTreeNodeSizeMin; mTreeNodeSize <= mTreeNodeSizeMax; mTreeNodeSize += mTreeNodeSizeStep) {
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const result = await runTests(datasetSize, dimension, mTreeNodeSize);
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const row = document.createElement('tr');
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[
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datasetSize,
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dimension,
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mTreeNodeSize,
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`${Number(result.timingResults.treeCreationTime).toFixed(5)}`,
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`${Number(result.timingResults.rangeQueryTime.mtreeRangeQuery).toFixed(5)}`,
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`${Number(result.timingResults.rangeQueryTime.sequentialSearch).toFixed(5)}`,
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`${Number(result.timingResults.knnQueryTime.mtreeKNNQuery).toFixed(5)}`,
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`${Number(result.timingResults.knnQueryTime.sequentialSearch).toFixed(5)}`,
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`${result.functionCallCounts.rangeQuery.mtreeRangeQuery}`,
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`${result.functionCallCounts.rangeQuery.sequentialSearch}`,
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`${result.functionCallCounts.knnQuery.mtreeKNNQuery}`,
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`${result.functionCallCounts.knnQuery.sequentialSearch}`,
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].forEach((value, index) => {
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row.appendChild(document.createElement('td')).textContent = value;
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});
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tbody.appendChild(row);
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}
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}
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}
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};
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async function runTests(datasetSize, dimension, mTreeNodeSize) {
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console.log(`running tests for dataset size ${datasetSize}, dimension ${dimension}, m-tree node size ${mTreeNodeSize}`);
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try {
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const startTime = performance.now();
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const timingResults = {
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treeCreationTime: 0,
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rangeQueryTime: {
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mtreeRangeQuery: 0,
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sequentialSearch: 0
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},
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knnQueryTime: {
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mtreeKNNQuery: 0,
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sequentialSearch: 0
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}
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};
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const functionCallCounts = {
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rangeQuery: {
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mtreeRangeQuery: 0,
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sequentialSearch: 0
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},
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knnQuery: {
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mtreeKNNQuery: 0,
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sequentialSearch: 0
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}
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};
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for (let j = 0; j < 2; j++) {
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const response = await fetch('/recreate', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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dimensions: dimension,
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pointCount: datasetSize,
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capacity: mTreeNodeSize,
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distanceFunction: 'euclidean'
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}),
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timeout: 6000000
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});
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if (!response.ok) {
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throw new Error(`error recreating tree: ${await response.text()}`);
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}
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const { treeCreationTime } = await response.json();
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timingResults.treeCreationTime += treeCreationTime;
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for (let i = 0; i < 4; i++) {
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const queryPoint = Array(dimension).fill(i / 4);
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const knnResponse = await fetch(`/kNNQuery?queryPoint=${encodeURIComponent(JSON.stringify(queryPoint))}&k=${encodeURIComponent((i + 1)*3)}`);
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if (!knnResponse.ok) {
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throw new Error(`error running KNN query: ${knnResponse.status} ${await knnResponse.text()}`);
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}
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const knnResult = await knnResponse.json();
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const radius = knnResult.values[knnResult.values.length - 1].distance;
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const rangeResponse = await fetch(`/rangeQuery?queryPoint=${encodeURIComponent(JSON.stringify(queryPoint))}&radius=${encodeURIComponent(radius)}`);
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if (!rangeResponse.ok) {
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throw new Error(`error running range query: ${rangeResponse.status} ${await rangeResponse.text()}`);
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}
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const rangeResult = await rangeResponse.json();
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if (!rangeResult || !rangeResult.timingResult || !rangeResult.functionCalls) {
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throw new Error('error parsing result');
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}
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timingResults.rangeQueryTime.mtreeRangeQuery += rangeResult.timingResult.mtreeRangeQuery;
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functionCallCounts.rangeQuery.mtreeRangeQuery += rangeResult.functionCalls.mtreeRangeQuery;
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timingResults.rangeQueryTime.sequentialSearch += rangeResult.timingResult.sequentialSearch;
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functionCallCounts.rangeQuery.sequentialSearch += rangeResult.functionCalls.sequentialSearch;
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timingResults.knnQueryTime.mtreeKNNQuery += knnResult.timingResult.mtreeKNNQuery;
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functionCallCounts.knnQuery.mtreeKNNQuery += knnResult.functionCalls.mtreeKNNQuery;
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timingResults.knnQueryTime.sequentialSearch += knnResult.timingResult.sequentialSearch;
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functionCallCounts.knnQuery.sequentialSearch += knnResult.functionCalls.sequentialSearch;
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}
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}
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timingResults.treeCreationTime /= 2;
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timingResults.rangeQueryTime.mtreeRangeQuery /= 8;
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functionCallCounts.rangeQuery.mtreeRangeQuery /= 8;
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timingResults.rangeQueryTime.sequentialSearch /= 8;
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functionCallCounts.rangeQuery.sequentialSearch /= 8;
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timingResults.knnQueryTime.mtreeKNNQuery /= 8;
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functionCallCounts.knnQuery.mtreeKNNQuery /= 8;
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timingResults.knnQueryTime.sequentialSearch /= 8;
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functionCallCounts.knnQuery.sequentialSearch /= 8;
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const endTime = performance.now();
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console.log(`finished at ${endTime} after ${endTime - startTime}ms`);
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return { timingResults, functionCallCounts };
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} catch (error) {
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console.error('error running tests:', error);
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return {};
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}
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}
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</script>
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</body>
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</html> |