Fixes real spherical harmonics directivity test. Modify random methods to use the package wide rng by default.

Author: fakufaku

pyroomacoustics/directivities/harmonics.py

@@ -160,3 +160,7 @@ def get_response(
             azimuth,
             condon_shortley_phase=self.condon_shortley_phase,
         )[:, np.newaxis]
+
+    def sample_rays(self, n_rays, rng=None):
+        """Not yet implemented."""
+        raise NotImplementedError

pyroomacoustics/libroom_src/room.cpp

@@ -957,7 +957,7 @@ void Room<D>::ray_tracing(
     const Eigen::Matrix<float, Eigen::Dynamic, D> &unit_vectors,
     const Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic> &energies,
     const Vectorf<D> &source_pos) {
-  float energy_0 = energy_0_numerator / unit_vectors.rows();
+  float energy_0 = constants::ENERGY_0 / unit_vectors.rows();
 
   if (unit_vectors.rows() != energies.rows()) {
     throw std::runtime_error("Error: The same number of rays and energies is expected.");

pyroomacoustics/random/distributions.py

@@ -3,6 +3,7 @@
 import numpy as np
 import scipy
 
+from .generator import get_rng
 from .spherical import power_spherical, uniform_spherical
 
 
@@ -77,6 +78,8 @@ def pdf(self, x):
         return np.ones_like(x, shape=x.shape[:-1]) * scale
 
     def sample(self, size=None, rng=None):
+        if rng is None:
+            rng = get_rng()
         return uniform_spherical(dim=self.dim, size=size, rng=rng)
 
 
@@ -137,6 +140,8 @@ def scale(self):
         return self._scale
 
     def sample(self, size=None, rng=None):
+        if rng is None:
+            rng = get_rng()
         return power_spherical(loc=self._loc, scale=self._scale, size=size, rng=rng)
 
     def pdf(self, x):

pyroomacoustics/random/spherical.py

@@ -1,5 +1,7 @@
 import numpy as np
 
+from .generator import get_rng
+
 _eps = 1e-7
 
 
@@ -30,7 +32,7 @@ def uniform_spherical(dim=3, size=None, rng=None):
         size = list(size) + [dim]
 
     if rng is None:
-        rng = np.random.default_rng()
+        rng = get_rng()
 
     out = rng.standard_normal(size=size)
     out /= np.linalg.norm(out, axis=-1, keepdims=True)
@@ -86,7 +88,7 @@ def power_spherical(loc=None, scale=None, size=None, rng=None):
         scale = 1.0
 
     if rng is None:
-        rng = np.random.default_rng()
+        rng = get_rng()
 
     z = rng.beta((dim - 1.0) / 2.0 + scale, (dim - 1) / 2.0, size=size[:-1])
     v = uniform_spherical(size=size[:-1], dim=dim - 1)