Index: third_party/WebKit/LayoutTests/webaudio/Panner/panner-automation-position.html |
diff --git a/third_party/WebKit/LayoutTests/webaudio/Panner/panner-automation-position.html b/third_party/WebKit/LayoutTests/webaudio/Panner/panner-automation-position.html |
index 9e19068d9fca750c43e61e81ad0f4629cf902ec8..7beabb2edff26c65af6210d36531d73c8728f0ec 100644 |
--- a/third_party/WebKit/LayoutTests/webaudio/Panner/panner-automation-position.html |
+++ b/third_party/WebKit/LayoutTests/webaudio/Panner/panner-automation-position.html |
@@ -1,150 +1,152 @@ |
-<!doctype html> |
+<!DOCTYPE html> |
<html> |
<head> |
+ <title> |
+ Test Automation of PannerNode Positions |
+ </title> |
<script src="../../resources/testharness.js"></script> |
- <script src="../../resources/testharnessreport.js"></script> |
+ <script src="../../resources/testharnessreport.js"></script> |
<script src="../resources/audit-util.js"></script> |
<script src="../resources/audit.js"></script> |
<script src="../resources/panner-formulas.js"></script> |
- <title>Test Automation of PannerNode Positions</title> |
</head> |
- |
<body> |
- <script> |
- var sampleRate = 48000; |
- // These tests are quite slow, so don't run for many frames. 256 frames should be enough to |
- // demonstrate that automations are working. |
- var renderFrames = 256; |
- var renderDuration = renderFrames / sampleRate; |
- |
- var context; |
- var panner; |
- |
- var audit = Audit.createTaskRunner(); |
- |
- // Set of tests for the panner node with automations applied to the position of the source. |
- var testConfigs = [{ |
- // Distance model parameters for the panner |
- distanceModel: { |
- model: "inverse", |
- rolloff: 1 |
- }, |
- // Initial location of the source |
- startPosition: [0, 0, 1], |
- // Final position of the source. For this test, we only want to move on the z axis which |
- // doesn't change the azimuth angle. |
- endPosition: [0, 0, 10000], |
- }, { |
- distanceModel: { |
- model: "inverse", |
- rolloff: 1 |
+ <script id="layout-test-code"> |
+ let sampleRate = 48000; |
+ // These tests are quite slow, so don't run for many frames. 256 frames |
+ // should be enough to demonstrate that automations are working. |
+ let renderFrames = 256; |
+ let renderDuration = renderFrames / sampleRate; |
+ |
+ let context; |
+ let panner; |
+ |
+ let audit = Audit.createTaskRunner(); |
+ |
+ // Set of tests for the panner node with automations applied to the |
+ // position of the source. |
+ let testConfigs = [ |
+ { |
+ // Distance model parameters for the panner |
+ distanceModel: {model: 'inverse', rolloff: 1}, |
+ // Initial location of the source |
+ startPosition: [0, 0, 1], |
+ // Final position of the source. For this test, we only want to move |
+ // on the z axis which |
+ // doesn't change the azimuth angle. |
+ endPosition: [0, 0, 10000], |
}, |
- startPosition: [0, 0, 1], |
- // An essentially random end position, but it should be such that azimuth angle changes as |
- // we move from the start to the end. |
- endPosition: [20000, 30000, 10000], |
- errorThreshold: [{ |
- // Error threshold for 1-channel case |
- relativeThreshold: 4.8124e-7 |
- }, { |
- // Error threshold for 2-channel case |
- relativeThreshold: 4.3267e-7 |
- }], |
- }, { |
- distanceModel: { |
- model: "exponential", |
- rolloff: 1.5 |
+ { |
+ distanceModel: {model: 'inverse', rolloff: 1}, |
+ startPosition: [0, 0, 1], |
+ // An essentially random end position, but it should be such that |
+ // azimuth angle changes as |
+ // we move from the start to the end. |
+ endPosition: [20000, 30000, 10000], |
+ errorThreshold: [ |
+ { |
+ // Error threshold for 1-channel case |
+ relativeThreshold: 4.8124e-7 |
+ }, |
+ { |
+ // Error threshold for 2-channel case |
+ relativeThreshold: 4.3267e-7 |
+ } |
+ ], |
}, |
- startPosition: [0, 0, 1], |
- endPosition: [20000, 30000, 10000], |
- errorThreshold: [{ |
- relativeThreshold: 5.0783e-7 |
- }, { |
- relativeThreshold: 5.2180e-7 |
- }] |
- }, { |
- distanceModel: { |
- model: "linear", |
- rolloff: 1 |
+ { |
+ distanceModel: {model: 'exponential', rolloff: 1.5}, |
+ startPosition: [0, 0, 1], |
+ endPosition: [20000, 30000, 10000], |
+ errorThreshold: |
+ [{relativeThreshold: 5.0783e-7}, {relativeThreshold: 5.2180e-7}] |
}, |
- startPosition: [0, 0, 1], |
- endPosition: [20000, 30000, 10000], |
- errorThreshold: [{ |
- relativeThreshold: 6.5324e-6 |
- }, { |
- relativeThreshold: 6.5756e-6 |
- }] |
- }]; |
- |
- for (var k = 0; k < testConfigs.length; ++k) { |
- var config = testConfigs[k]; |
- var tester = function (c, channelCount) { |
+ { |
+ distanceModel: {model: 'linear', rolloff: 1}, |
+ startPosition: [0, 0, 1], |
+ endPosition: [20000, 30000, 10000], |
+ errorThreshold: [ |
+ {relativeThreshold: 6.5324e-6}, {relativeThreshold: 6.5756e-6} |
+ ] |
+ } |
+ ]; |
+ |
+ for (let k = 0; k < testConfigs.length; ++k) { |
+ let config = testConfigs[k]; |
+ let tester = function(c, channelCount) { |
return (task, should) => { |
- runTest(should, c, channelCount) |
- .then(() => task.done()); |
+ runTest(should, c, channelCount).then(() => task.done()); |
} |
}; |
- var baseTestName = config.distanceModel.model + " rolloff: " + config.distanceModel.rolloff; |
+ let baseTestName = config.distanceModel.model + |
+ ' rolloff: ' + config.distanceModel.rolloff; |
// Define tasks for both 1-channel and 2-channel |
- audit.define(k + ": 1-channel " + baseTestName, tester(config, 1)); |
- audit.define(k + ": 2-channel " + baseTestName, tester(config, 2)); |
+ audit.define(k + ': 1-channel ' + baseTestName, tester(config, 1)); |
+ audit.define(k + ': 2-channel ' + baseTestName, tester(config, 2)); |
} |
audit.run(); |
function runTest(should, options, channelCount) { |
- // Output has 5 channels: channels 0 and 1 are for the stereo output of the panner node. |
- // Channels 2-5 are the for automation of the x,y,z coordinate so that we have actual |
- // coordinates used for the panner automation. |
+ // Output has 5 channels: channels 0 and 1 are for the stereo output of |
+ // the panner node. Channels 2-5 are the for automation of the x,y,z |
+ // coordinate so that we have actual coordinates used for the panner |
+ // automation. |
context = new OfflineAudioContext(5, renderFrames, sampleRate); |
// Stereo source for the panner. |
- var source = context.createBufferSource(); |
- source.buffer = createConstantBuffer(context, renderFrames, channelCount == 1 ? 1 : [1, 2]); |
+ let source = context.createBufferSource(); |
+ source.buffer = createConstantBuffer( |
+ context, renderFrames, channelCount == 1 ? 1 : [1, 2]); |
panner = context.createPanner(); |
panner.distanceModel = options.distanceModel.model; |
panner.rolloffFactor = options.distanceModel.rolloff; |
- panner.panningModel = "equalpower"; |
+ panner.panningModel = 'equalpower'; |
// Source and gain node for the z-coordinate calculation. |
- var dist = context.createBufferSource(); |
+ let dist = context.createBufferSource(); |
dist.buffer = createConstantBuffer(context, 1, 1); |
dist.loop = true; |
- var gainX = context.createGain(); |
- var gainY = context.createGain(); |
- var gainZ = context.createGain(); |
+ let gainX = context.createGain(); |
+ let gainY = context.createGain(); |
+ let gainZ = context.createGain(); |
dist.connect(gainX); |
dist.connect(gainY); |
dist.connect(gainZ); |
- // Set the gain automation to match the z-coordinate automation of the panner. |
+ // Set the gain automation to match the z-coordinate automation of the |
+ // panner. |
- // End the automation some time before the end of the rendering so we can verify that |
- // automation has the correct end time and value. |
- var endAutomationTime = 0.75 * renderDuration; |
+ // End the automation some time before the end of the rendering so we |
+ // can verify that automation has the correct end time and value. |
+ let endAutomationTime = 0.75 * renderDuration; |
gainX.gain.setValueAtTime(options.startPosition[0], 0); |
- gainX.gain.linearRampToValueAtTime(options.endPosition[0], endAutomationTime); |
+ gainX.gain.linearRampToValueAtTime( |
+ options.endPosition[0], endAutomationTime); |
gainY.gain.setValueAtTime(options.startPosition[1], 0); |
- gainY.gain.linearRampToValueAtTime(options.endPosition[1], endAutomationTime); |
+ gainY.gain.linearRampToValueAtTime( |
+ options.endPosition[1], endAutomationTime); |
gainZ.gain.setValueAtTime(options.startPosition[2], 0); |
- gainZ.gain.linearRampToValueAtTime(options.endPosition[2], endAutomationTime); |
+ gainZ.gain.linearRampToValueAtTime( |
+ options.endPosition[2], endAutomationTime); |
dist.start(); |
- // Splitter and merger to map the panner output and the z-coordinate automation to the |
- // correct channels in the destination. |
- var splitter = context.createChannelSplitter(2); |
- var merger = context.createChannelMerger(5); |
+ // Splitter and merger to map the panner output and the z-coordinate |
+ // automation to the correct channels in the destination. |
+ let splitter = context.createChannelSplitter(2); |
+ let merger = context.createChannelMerger(5); |
source.connect(panner); |
// Split the output of the panner to separate channels |
panner.connect(splitter); |
- // Merge the panner outputs and the z-coordinate output to the correct destination channels. |
+ // Merge the panner outputs and the z-coordinate output to the correct |
+ // destination channels. |
splitter.connect(merger, 0, 0); |
splitter.connect(merger, 1, 1); |
gainX.connect(merger, 0, 2); |
@@ -159,101 +161,104 @@ |
panner.positionZ.setValueAtTime(options.startPosition[2], 0); |
// Automate z coordinate to move away from the listener |
- panner.positionX.linearRampToValueAtTime(options.endPosition[0], 0.75 * renderDuration); |
- panner.positionY.linearRampToValueAtTime(options.endPosition[1], 0.75 * renderDuration); |
- panner.positionZ.linearRampToValueAtTime(options.endPosition[2], 0.75 * renderDuration); |
+ panner.positionX.linearRampToValueAtTime( |
+ options.endPosition[0], 0.75 * renderDuration); |
+ panner.positionY.linearRampToValueAtTime( |
+ options.endPosition[1], 0.75 * renderDuration); |
+ panner.positionZ.linearRampToValueAtTime( |
+ options.endPosition[2], 0.75 * renderDuration); |
source.start(); |
// Go! |
- return context.startRendering() |
- .then(function (renderedBuffer) { |
- // Get the panner outputs |
- var data0 = renderedBuffer.getChannelData(0); |
- var data1 = renderedBuffer.getChannelData(1); |
- var xcoord = renderedBuffer.getChannelData(2); |
- var ycoord = renderedBuffer.getChannelData(3); |
- var zcoord = renderedBuffer.getChannelData(4); |
- |
- // We're doing a linear ramp on the Z axis with the equalpower panner, so the equalpower |
- // panning gain remains constant. We only need to model the distance effect. |
- |
- // Compute the distance gain |
- var distanceGain = new Float32Array(xcoord.length);; |
- |
- if (panner.distanceModel === "inverse") { |
- for (var k = 0; k < distanceGain.length; ++k) { |
- distanceGain[k] = inverseDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
- } |
- } else if (panner.distanceModel === "linear") { |
- for (var k = 0; k < distanceGain.length; ++k) { |
- distanceGain[k] = linearDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
- } |
- } else if (panner.distanceModel === "exponential") { |
- for (var k = 0; k < distanceGain.length; ++k) { |
- distanceGain[k] = exponentialDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
- } |
+ return context.startRendering().then(function(renderedBuffer) { |
+ // Get the panner outputs |
+ let data0 = renderedBuffer.getChannelData(0); |
+ let data1 = renderedBuffer.getChannelData(1); |
+ let xcoord = renderedBuffer.getChannelData(2); |
+ let ycoord = renderedBuffer.getChannelData(3); |
+ let zcoord = renderedBuffer.getChannelData(4); |
+ |
+ // We're doing a linear ramp on the Z axis with the equalpower panner, |
+ // so the equalpower panning gain remains constant. We only need to |
+ // model the distance effect. |
+ |
+ // Compute the distance gain |
+ let distanceGain = new Float32Array(xcoord.length); |
+ ; |
+ |
+ if (panner.distanceModel === 'inverse') { |
+ for (let k = 0; k < distanceGain.length; ++k) { |
+ distanceGain[k] = |
+ inverseDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
} |
- |
- // Compute the expected result. Since we're on the z-axis, the left and right channels |
- // pass through the equalpower panner unchanged. Only need to apply the distance gain. |
- var buffer0 = source.buffer.getChannelData(0); |
- var buffer1 = channelCount == 2 ? source.buffer.getChannelData(1) : buffer0; |
- |
- var azimuth = new Float32Array(buffer0.length); |
- |
- for (var k = 0; k < data0.length; ++k) { |
- azimuth[k] = calculateAzimuth([ |
- xcoord[k], |
- ycoord[k], |
- zcoord[k] |
- ], [ |
- context.listener.positionX.value, |
- context.listener.positionY.value, |
- context.listener.positionZ.value |
- ], [ |
- context.listener.forwardX.value, |
- context.listener.forwardY.value, |
- context.listener.forwardZ.value |
- ], [ |
- context.listener.upX.value, |
- context.listener.upY.value, |
- context.listener.upZ.value |
- ]); |
+ } else if (panner.distanceModel === 'linear') { |
+ for (let k = 0; k < distanceGain.length; ++k) { |
+ distanceGain[k] = |
+ linearDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
} |
- |
- var expected = applyPanner(azimuth, buffer0, buffer1, channelCount); |
- var expected0 = expected.left; |
- var expected1 = expected.right; |
- |
- for (var k = 0; k < expected0.length; ++k) { |
- expected0[k] *= distanceGain[k]; |
- expected1[k] *= distanceGain[k]; |
+ } else if (panner.distanceModel === 'exponential') { |
+ for (let k = 0; k < distanceGain.length; ++k) { |
+ distanceGain[k] = |
+ exponentialDistance(panner, xcoord[k], ycoord[k], zcoord[k]) |
} |
+ } |
+ |
+ // Compute the expected result. Since we're on the z-axis, the left |
+ // and right channels pass through the equalpower panner unchanged. |
+ // Only need to apply the distance gain. |
+ let buffer0 = source.buffer.getChannelData(0); |
+ let buffer1 = |
+ channelCount == 2 ? source.buffer.getChannelData(1) : buffer0; |
+ |
+ let azimuth = new Float32Array(buffer0.length); |
+ |
+ for (let k = 0; k < data0.length; ++k) { |
+ azimuth[k] = calculateAzimuth( |
+ [xcoord[k], ycoord[k], zcoord[k]], |
+ [ |
+ context.listener.positionX.value, |
+ context.listener.positionY.value, |
+ context.listener.positionZ.value |
+ ], |
+ [ |
+ context.listener.forwardX.value, |
+ context.listener.forwardY.value, |
+ context.listener.forwardZ.value |
+ ], |
+ [ |
+ context.listener.upX.value, context.listener.upY.value, |
+ context.listener.upZ.value |
+ ]); |
+ } |
+ |
+ let expected = applyPanner(azimuth, buffer0, buffer1, channelCount); |
+ let expected0 = expected.left; |
+ let expected1 = expected.right; |
+ |
+ for (let k = 0; k < expected0.length; ++k) { |
+ expected0[k] *= distanceGain[k]; |
+ expected1[k] *= distanceGain[k]; |
+ } |
+ |
+ let info = options.distanceModel.model + |
+ ', rolloff: ' + options.distanceModel.rolloff; |
+ let prefix = channelCount + '-channel ' + |
+ '[' + options.startPosition[0] + ', ' + options.startPosition[1] + |
+ ', ' + options.startPosition[2] + '] -> [' + |
+ options.endPosition[0] + ', ' + options.endPosition[1] + ', ' + |
+ options.endPosition[2] + ']: '; |
+ |
+ let errorThreshold = 0; |
+ |
+ if (options.errorThreshold) |
+ errorThreshold = options.errorThreshold[channelCount - 1] |
- var info = options.distanceModel.model + ", rolloff: " + options.distanceModel.rolloff; |
- var prefix = channelCount + "-channel " |
- + "[" + options.startPosition[0] + ", " |
- + options.startPosition[1] + ", " |
- + options.startPosition[2] + "] -> [" |
- + options.endPosition[0] + ", " |
- + options.endPosition[1] + ", " |
- + options.endPosition[2] + "]: "; |
- |
- var errorThreshold = 0; |
- |
- if (options.errorThreshold) |
- errorThreshold = options.errorThreshold[channelCount - 1] |
- |
- should(data0, prefix + "distanceModel: " + info + ", left channel") |
- .beCloseToArray(expected0, { |
- absoluteThreshold: errorThreshold |
- }); |
- should(data1, prefix + "distanceModel: " + info + ", right channel") |
- .beCloseToArray(expected1, { |
- absoluteThreshold: errorThreshold |
- }); |
- }); |
+ should(data0, prefix + 'distanceModel: ' + info + ', left channel') |
+ .beCloseToArray(expected0, {absoluteThreshold: errorThreshold}); |
+ should(data1, prefix + 'distanceModel: ' + info + ', right channel') |
+ .beCloseToArray(expected1, {absoluteThreshold: errorThreshold}); |
+ }); |
} |
</script> |
</body> |