Iframe-PlotlyJs-Comp.vue
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@ -1,30 +1,37 @@
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<script setup lang="ts">
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const src = computed(() => `${import.meta.env.BASE_URL}iframe/for-plotly.html`);
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type I频谱图数据 = number[];
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type I数据 = number[];
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type WindowWithPlotly = Window & {
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Plotly: typeof import('plotly.js-dist-min');
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};
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const iframeRef = useTemplateRef<HTMLIFrameElement>('iframeRef');
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let contentWindow: null | WindowWithPlotly = null;
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let plotlyElement: import('plotly.js-dist-min').PlotlyHTMLElement | null = null;
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let 频谱图Element: import('plotly.js-dist-min').PlotlyHTMLElement | null = null;
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// let 瀑布图Element: import('plotly.js-dist-min').PlotlyHTMLElement | null = null;
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let _readyPromiseReslove = () => {};
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const readyPromise = new Promise<void>((resolve) => {
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_readyPromiseReslove = resolve;
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});
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const 频谱图Trace = {
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name: '频谱',
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x: [],
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y: [],
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type: 'scatter',
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line: { color: 'blue' },
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} satisfies import('plotly.js-dist-min').Data;
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const 频谱瀑布图Layout = {
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title: '频谱瀑布图',
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xaxis: {
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title: '频率 (Hz)',
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// range: [0, 22_050],
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showgrid: false,
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},
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yaxis: {
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title: '时间步',
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showgrid: false,
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},
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margin: { l: 60, r: 40, b: 40, t: 60 },
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};
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const data = [频谱图Trace];
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const 频谱图layout = {
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const 频谱图Layout = {
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title: '频谱图',
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xaxis: {
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title: '频率 (Hz)',
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@ -39,35 +46,39 @@ const 频谱图layout = {
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gridcolor: '#eee',
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tickformat: ',d', // 设置为带逗号的整数格式 (推荐,更易读)
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},
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margin: { l: 60, r: 40, b: 60, t: 60 },
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margin: { l: 60, r: 40, b: 40, t: 60 },
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} satisfies Partial<import('plotly.js-dist-min').Layout>;
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defineExpose({
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执行画图: async (数据: I频谱图数据, FFT大小: number /* 也叫快速傅里叶变换大小 */, 采样率: number) => {
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console.debug('[执行画图被调用]', `数据.length :>> `, 数据.length);
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await readyPromise;
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添加数据: async (DB数据: I数据, FFT大小: number /* 也叫快速傅里叶变换大小 */, 采样率: number) => {
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const 频率分辨率 = 采样率 / FFT大小;
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const x数据 = Array.from({ length: 数据.length }, (_, i) => i * 频率分辨率);
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contentWindow!.Plotly.addTraces(plotlyElement!, {
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x: x数据,
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y: 数据,
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});
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// // 清除之前的数据并添加新数据
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// contentWindow!.Plotly.newPlot(plotlyElement!, [{
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// x: x数据,
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// y: data,
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// type: 'scatter',
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// line: { color: 'blue' },
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// name: '频谱'
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// }], 频谱图layout);
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{
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// 频谱图
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console.debug('[添加数据被调用]', `数据.length :>> `, DB数据.length);
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await readyPromise;
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// 先清空之前的数据
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await contentWindow!.Plotly.react(频谱图Element!, [], 频谱图Layout);
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const x频率数据 = Array.from({ length: DB数据.length }, (_, i) => i * 频率分辨率);
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await contentWindow!.Plotly.addTraces(频谱图Element!, {
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x: x频率数据,
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y: DB数据,
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type: 'scatter',
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line: { color: 'blue' },
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});
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}
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{
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// 瀑布图
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}
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},
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});
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async function onIframeLoad() {
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console.debug('[onIframeLoad] iframe 加载完成');
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contentWindow = iframeRef.value!.contentWindow as WindowWithPlotly;
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plotlyElement = await contentWindow.Plotly.newPlot('PLOTLY_CHART', data, 频谱图layout);
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频谱图Element = await contentWindow.Plotly.newPlot('PLOTLY_CHART_spectrogram', [], 频谱图Layout);
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瀑布图Element = await contentWindow.Plotly.newPlot('PLOTLY_CHART_waterfall', [], 频谱瀑布图Layout);
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_readyPromiseReslove();
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}
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onMounted(() => {
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@ -5,7 +5,7 @@ const compRef = useTemplateRef('compRef');
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onMounted(() => {
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console.debug('[onMounted] page 加载完成');
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compRef.value!.执行画图(
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compRef.value!.添加数据(
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频谱图数据, // 实际数据点为32768
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65_536, // FFT大小为65536
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96_000, // 采样率为96000
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@ -14,7 +14,7 @@ onMounted(() => {
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</script>
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<template>
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<IframePlotlyJsComp ref="compRef" style="width: 1400px; height: 400px; max-width: 100%" />
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<IframePlotlyJsComp ref="compRef" style="width: 1400px; height: 600px; max-width: 100%" />
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</template>
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<style scoped></style>
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