67 lines
2.4 KiB
JavaScript
67 lines
2.4 KiB
JavaScript
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class BandpassProcessor extends AudioWorkletProcessor {
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process(inputs, outputs, parameters) {
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const input = inputs[0];
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const output = outputs[0];
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const frequency = parameters.frequency;
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const Q = parameters.Q;
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for (let channel = 0; channel < input.length; channel++) {
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const inputChannel = input[channel];
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const outputChannel = output[channel];
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for (let i = 0; i < inputChannel.length; i++) {
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// Apply bandpass filter to inputChannel[i] and store the result in outputChannel[i]
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// using the provided frequency and Q parameters
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}
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}
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// Calculate the RMS value of the output audio data
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const rms = this.calculateRMS(output);
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// Calculate the dB values
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const dbValues = this.convertToDB(output);
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// Calculate the 10th and 90th percentile values
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const percentile10 = this.calculatePercentile(dbValues, 10);
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const percentile90 = this.calculatePercentile(dbValues, 90);
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// Send the processed data to the main thread
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this.port.postMessage({ rms, dbValues, percentile10, percentile90 });
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return true;
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}
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calculateRMS(data) {
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let sumOfSquares = 0;
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for (let channel = 0; channel < data.length; channel++) {
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const channelData = data[channel];
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for (let i = 0; i < channelData.length; i++) {
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sumOfSquares += channelData[i] * channelData[i];
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}
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}
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const meanSquare = sumOfSquares / (data.length * data[0].length);
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const rms = Math.sqrt(meanSquare);
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return rms;
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}
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calculatePercentile(data, percentile) {
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const sortedData = data.slice().sort((a, b) => a - b);
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const index = Math.floor((percentile / 100) * sortedData.length);
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return sortedData[index];
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}
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convertToDB(data) {
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const dbValues = [];
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for (let channel = 0; channel < data.length; channel++) {
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const channelData = data[channel];
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for (let i = 0; i < channelData.length; i++) {
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const amplitude = Math.abs(channelData[i]);
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const db = 20 * Math.log10(amplitude + this.minAmplitude);
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dbValues.push(db);
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}
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}
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return dbValues;
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}
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}
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export default registerProcessor('bandpass-processor', BandpassProcessor);
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