osh-js
Version:
OSH javascript Toolkit
95 lines • 4.29 kB
JavaScript
var __extends = (this && this.__extends) || (function () {
var extendStatics = function (d, b) {
extendStatics = Object.setPrototypeOf ||
({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||
function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };
return extendStatics(d, b);
};
return function (d, b) {
if (typeof b !== "function" && b !== null)
throw new TypeError("Class extends value " + String(b) + " is not a constructor or null");
extendStatics(d, b);
function __() { this.constructor = d; }
d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());
};
})();
import AudioVisualizer from "./AudioVisualizer";
import { isDefined } from "../../../../utils/Utils";
/**
* This abstract class is in charge of visualizing Audio based on a canvas and using a decoded AudioBuffer.
* @extends AudioVisualizer
*/
var AudioCanvasVisualizer = /** @class */ (function (_super) {
__extends(AudioCanvasVisualizer, _super);
/**
* Create a visualizer.
* @param {Object} [properties={}] - the properties of the visualizer
* @param {string} [properties.css=''] - The css classes to set, can be multiple if separate by spaces
* @param {Number} properties.fftSize - The fftSize property of the AnalyserNode interface is an unsigned long value and represents the window size in samples that is used when performing a Fast Fourier Transform (FFT) to get frequency/time domain data.
* @param {string} properties.container - The div element to attach to
*/
function AudioCanvasVisualizer(properties) {
var _this = _super.call(this, properties) || this;
_this.initCanvas(properties);
_this.subSamplingFrequency = 4000;
_this.sampleNumber = 0;
_this.animate();
return _this;
}
// abstract
AudioCanvasVisualizer.prototype.draw = function (decodedSample) { };
AudioCanvasVisualizer.prototype.onended = function (decodedSample) { };
AudioCanvasVisualizer.prototype.initCanvas = function (properties) {
var domNode = document.getElementById(properties.container);
this.canvas = document.createElement("canvas");
if (this.properties.hasOwnProperty('css')) {
this.canvas.setAttribute("class", this.properties.css);
}
var bounds = domNode.getBoundingClientRect();
this.canvas.setAttribute("width", bounds.width);
this.canvas.setAttribute("height", bounds.height);
domNode.appendChild(this.canvas);
this.canvasCtx = this.canvas.getContext("2d");
};
AudioCanvasVisualizer.prototype.checkSubsampling = function (decodedSample) {
if (isDefined(this.lastSubSampingClockTime)) {
var endClockTime = performance.now();
var deltaClockTime = endClockTime - this.lastSubSampingClockTime;
if (deltaClockTime < this.frequency) {
console.warn('skipping audioBuffer');
return false;
}
}
else {
this.frequency = 1000 / (this.subSamplingFrequency / decodedSample.buffer.length);
}
this.lastSubSampingClockTime = performance.now();
return true;
};
AudioCanvasVisualizer.prototype.checkUpdate = function () {
if (!isDefined(this.lastClockTime)) {
this.lastClockTime = performance.now();
return true;
}
var endClockTime = performance.now();
var deltaClockTime = endClockTime - this.lastClockTime;
if (deltaClockTime > 1000 / 15) {
this.lastClockTime = performance.now();
return true;
}
return false;
};
AudioCanvasVisualizer.prototype.animate = function () {
var _this = this;
setInterval(function () {
if (_this.sampleNumber === 0) {
return;
}
_this.render();
}, 1000 / 10); // 15Hz
};
AudioCanvasVisualizer.prototype.render = function () { };
return AudioCanvasVisualizer;
}(AudioVisualizer));
export default AudioCanvasVisualizer;
//# sourceMappingURL=AudioCanvasVisualizer.js.map