<!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/audit-util.js"></script>
    <script src="../resources/audit.js"></script>
    <script src="../resources/panner-formulas.js"></script>
  </head>
  <body>
    <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],
        },
        {
          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
            }
          ],
        },
        {
          distanceModel: {model: 'exponential', rolloff: 1.5},
          startPosition: [0, 0, 1],
          endPosition: [20000, 30000, 10000],
          errorThreshold:
              [{relativeThreshold: 5.0783e-7}, {relativeThreshold: 5.2180e-7}]
        },
        {
          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());
          }
        };

        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.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.
        context = new OfflineAudioContext(5, renderFrames, sampleRate);

        // Stereo source for the panner.
        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';

        // Source and gain node for the z-coordinate calculation.
        let dist = context.createBufferSource();
        dist.buffer = createConstantBuffer(context, 1, 1);
        dist.loop = true;
        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.

        // 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);
        gainY.gain.setValueAtTime(options.startPosition[1], 0);
        gainY.gain.linearRampToValueAtTime(
            options.endPosition[1], endAutomationTime);
        gainZ.gain.setValueAtTime(options.startPosition[2], 0);
        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.
        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.
        splitter.connect(merger, 0, 0);
        splitter.connect(merger, 1, 1);
        gainX.connect(merger, 0, 2);
        gainY.connect(merger, 0, 3);
        gainZ.connect(merger, 0, 4);

        merger.connect(context.destination);

        // Initialize starting point of the panner.
        panner.positionX.setValueAtTime(options.startPosition[0], 0);
        panner.positionY.setValueAtTime(options.startPosition[1], 0);
        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);

        source.start();

        // Go!
        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])
            }
          } else if (panner.distanceModel === 'linear') {
            for (let k = 0; k < distanceGain.length; ++k) {
              distanceGain[k] =
                  linearDistance(panner, xcoord[k], ycoord[k], zcoord[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]

            should(data0, prefix + 'distanceModel: ' + info + ', left channel')
                .beCloseToArray(expected0, {absoluteThreshold: errorThreshold});
          should(data1, prefix + 'distanceModel: ' + info + ', right channel')
              .beCloseToArray(expected1, {absoluteThreshold: errorThreshold});
        });
      }
    </script>
  </body>
</html>