Fix unused variable lint errors etc.

Author: ishii-norimi

js/data/mnist.js

@@ -101,8 +101,8 @@ export default class MNISTData extends FixData {
 
 	async _readyData() {
 		this._cols = []
-		for (let i = 0, p = 0; i < 28; i++) {
-			for (let j = 0; j < 28; j++, p++) {
+		for (let i = 0; i < 28; i++) {
+			for (let j = 0; j < 28; j++) {
 				this._cols.push(`${i},${j}`)
 			}
 		}

js/renderer/document.js

@@ -50,7 +50,7 @@ export default class DocumentScatterRenderer extends BaseRenderer {
 
 	testData() {
 		const x = this.datas.x[0]
-		const [words, idxs] = DocumentLoader.ordinal(x)
+		const [words] = DocumentLoader.ordinal(x)
 		return words
 	}
 

js/view/sdar.js

@@ -1,38 +1,26 @@
 import SDAR from '../../lib/model/sdar.js'
+import Controller from '../controller.js'
 
-var dispSDAR = (elm, platform) => {
+export default function (platform) {
+	platform.setting.ml.draft = true
+	platform.setting.ml.usage = 'Click and add data point. Click "fit" to update.'
+	const controller = new Controller(platform)
 	const fitModel = () => {
-		const p = +elm.select('[name=p]').property('value')
-		const c = +elm.select('[name=c]').property('value')
 		const tx = platform.trainInput
-		const model = new SDAR()
+		const model = new SDAR(p.value)
 		const pred = []
-		for (let i = 0; i < c; pred[i++] = []);
+		for (let i = 0; i < c.value; pred[i++] = []);
 		for (let d = 0; d < tx[0].length; d++) {
 			const xd = tx.map(v => v[d])
-			const p = model.predict(xd, c)
+			const p = model.predict(xd, c.value)
 			for (let i = 0; i < pred.length; i++) {
 				pred[i][d] = p[i]
 			}
 		}
 		platform.trainResult = pred
 	}
 
-	elm.append('span').text('p')
-	elm.append('input').attr('type', 'number').attr('name', 'p').attr('min', 1).attr('max', 1000).attr('value', 1)
-	elm.append('input').attr('type', 'button').attr('value', 'Fit').on('click', fitModel)
-	elm.append('span').text('predict count')
-	elm.append('input')
-		.attr('type', 'number')
-		.attr('name', 'c')
-		.attr('min', 1)
-		.attr('max', 100)
-		.attr('value', 100)
-		.on('change', fitModel)
-}
-
-export default function (platform) {
-	platform.setting.ml.draft = true
-	platform.setting.ml.usage = 'Click and add data point. Click "fit" to update.'
-	dispSDAR(platform.setting.ml.configElement, platform)
+	const p = controller.input.number({ label: 'p', min: 1, max: 1000, value: 1 })
+	controller.input.button('Fit').on('click', fitModel)
+	const c = controller.input.number({ label: 'predict count', min: 1, max: 100, value: 100 }).on('change', fitModel)
 }

lib/model/bms.js

@@ -70,7 +70,6 @@ export default class BlurringMeanShift {
 	 * @returns {number[]} Predicted values
 	 */
 	predict() {
-		let categories = 0
 		const p = []
 		for (let i = 0; i < this._c.length; i++) {
 			let category = i
@@ -80,7 +79,6 @@ export default class BlurringMeanShift {
 					break
 				}
 			}
-			if (category === i) categories++
 			p[i] = category
 		}
 		return p

lib/model/nns/onnx/operators/gemm.js

@@ -23,7 +23,7 @@ export default {
 		const layers = []
 		let inputName = inputList[0]
 		if (attrs.transA) {
-			layers.push({ type: 'transpose', input: [inputName], name: inputName + '_t', axis: [1, 0] })
+			layers.push({ type: 'transpose', input: [inputName], name: `${inputName}_t`, axis: [1, 0] })
 			inputName += '_t'
 		}
 		const initializers = {}

tests/gui/view/sdar.test.js

@@ -0,0 +1,40 @@
+import { getPage } from '../helper/browser'
+
+describe('timeseries prediction', () => {
+	/** @type {Awaited<ReturnType<getPage>>} */
+	let page
+	beforeEach(async () => {
+		page = await getPage()
+		const taskSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(5) select')
+		await taskSelectBox.selectOption('TP')
+		const modelSelectBox = page.locator('#ml_selector .model_selection #mlDisp')
+		await modelSelectBox.selectOption('sdar')
+	})
+
+	afterEach(async () => {
+		await page?.close()
+	})
+
+	test('initialize', async () => {
+		const methodMenu = page.locator('#ml_selector #method_menu')
+		const buttons = methodMenu.locator('.buttons')
+
+		const p = buttons.locator('input:nth-of-type(1)')
+		await expect(p.inputValue()).resolves.toBe('1')
+		const count = buttons.locator('input:nth-of-type(3)')
+		await expect(count.inputValue()).resolves.toBe('100')
+	})
+
+	test('learn', async () => {
+		const methodMenu = page.locator('#ml_selector #method_menu')
+		const buttons = methodMenu.locator('.buttons')
+
+		const fitButton = buttons.locator('input[value=Fit]')
+		await fitButton.dispatchEvent('click')
+
+		const svg = await page.waitForSelector('#plot-area svg')
+		const path = await svg.waitForSelector('.tile-render path')
+		const d = await path.getAttribute('d')
+		expect(d.split('L')).toHaveLength(101)
+	})
+})