test objectbased hoa

ear/core/objectbased/test/test_gain_calc_hoa.py

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+import numpy as np
+import pytest
+
+from ....fileio.adm.elements import (
+    AudioBlockFormatObjects,
+    ObjectDivergence,
+    ObjectPolarPosition,
+)
+from ...hoa import sph_harm
+from ...hoa_adapter import HOAFormat
+from ...metadata_input import ExtraData, ObjectTypeMetadata
+from ..gain_calc_hoa import GainCalcHOA
+
+
+@pytest.fixture(scope="module")
+def fmt():
+    return HOAFormat(max_order=1, normalization="SN3D", channel_order="ACN")
+
+
+@pytest.fixture(scope="module")
+def gain_calc(fmt):
+    return GainCalcHOA(fmt)
+
+
+@pytest.fixture(scope="module")
+def pan(fmt):
+    def f(az, el):
+        n, m = fmt.orders_degrees
+        return sph_harm(n, m, np.radians(az), np.radians(el), fmt.norm_fn)
+
+    return f
+
+
+@pytest.fixture(scope="module")
+def run_test(fmt, gain_calc, pan):
+    def f(
+        block_format,
+        extra_data=ExtraData(),
+        direct_gains=None,
+        diffuse_gains=None,
+        direct_position=None,
+        diffuse_position=None,
+        atol=1e-10,
+        rtol=1e-6,
+    ):
+        block_format = AudioBlockFormatObjects(**block_format)
+
+        actual = gain_calc.render(
+            ObjectTypeMetadata(block_format=block_format, extra_data=extra_data)
+        )
+
+        if direct_position is not None:
+            direct_gains = pan(*direct_position)
+        if diffuse_position is not None:
+            diffuse_gains = pan(*diffuse_position)
+
+        if direct_gains is None:
+            direct_gains = np.zeros(fmt.num_channels)
+        if diffuse_gains is None:
+            diffuse_gains = np.zeros(fmt.num_channels)
+
+        np.testing.assert_allclose(actual.direct, direct_gains, atol=atol, rtol=rtol)
+        np.testing.assert_allclose(actual.diffuse, diffuse_gains, atol=atol, rtol=rtol)
+
+    return f
+
+
+@pytest.mark.parametrize(
+    "az,el",
+    [
+        (0.0, 0.0),
+        (90.0, 0.0),
+        (-90.0, 0.0),
+        (180.0, 0.0),
+        (0.0, 90.0),
+        (0.0, -90.0),
+    ],
+)
+def test_direct_pos(run_test, az, el):
+    run_test(
+        dict(position=ObjectPolarPosition(azimuth=az, elevation=el)),
+        direct_position=(az, el),
+    )
+
+
+def test_gain(run_test, pan):
+    run_test(
+        dict(position=ObjectPolarPosition(azimuth=0.0, elevation=0.0), gain=0.5),
+        direct_gains=pan(0.0, 0.0) * 0.5,
+    )
+
+
+def test_full_diffuse(run_test, pan):
+    run_test(
+        dict(position=ObjectPolarPosition(azimuth=0.0, elevation=0.0), diffuse=1.0),
+        diffuse_position=(0.0, 0.0),
+    )
+
+
+def test_half_diffuse(run_test, pan):
+    run_test(
+        dict(position=ObjectPolarPosition(azimuth=0.0, elevation=0.0), diffuse=0.5),
+        direct_gains=pan(0.0, 0.0) * np.sqrt(0.5),
+        diffuse_gains=pan(0.0, 0.0) * np.sqrt(0.5),
+    )
+
+
+def test_spread_small(run_test, pan):
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=0.0, elevation=0.0),
+            width=10.0,
+            height=10.0,
+        ),
+        direct_gains=[1, 0, 0, 0.99],
+        atol=1e-2,
+    )
+
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=180.0, elevation=0.0),
+            width=10.0,
+            height=10.0,
+        ),
+        direct_gains=[1, 0, 0, -0.99],
+        atol=1e-2,
+    )
+
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=90.0, elevation=0.0),
+            width=10.0,
+            height=10.0,
+        ),
+        direct_gains=[1, 0.99, 0, 0],
+        atol=1e-2,
+    )
+
+
+def test_spread_large(run_test, pan):
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=0.0, elevation=0.0),
+            width=360.0,
+            height=360.0,
+        ),
+        direct_gains=[1, 0, 0, 0],
+        atol=1e-2,
+    )
+
+    # for FOA, full width is equivalent to full extent
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=0.0, elevation=0.0),
+            width=360.0,
+            height=0.0,
+        ),
+        direct_gains=[1, 0, 0, 0],
+        atol=1e-2,
+    )
+
+
+def test_diverge(run_test, pan):
+    run_test(
+        dict(
+            position=ObjectPolarPosition(azimuth=0.0, elevation=0.0),
+            objectDivergence=ObjectDivergence(0.5, azimuthRange=360 / 3),
+        ),
+        direct_gains=[1, 0, 0, 0],
+    )