Fixes tests numerical accuracy and warnings

Author: fakufaku

Diff for: pyroomacoustics/directivities/tests/test_source_directivities.py

@@ -30,7 +30,7 @@
 class TestSourceDirectivity(TestCase):
     def test_zero_gain(self):
         gain = np.amax(room.rir[0][0])
-        self.assertTrue(gain < (10**-10))
+        self.assertTrue(gain < 1e-7)
 
 
 def get_error():

Diff for: pyroomacoustics/directivities/tests/test_source_directivities_nonshoebox.py

@@ -69,5 +69,9 @@ def test_source_directions_nonshoebox():
     images_expected_reordered = images_expected[order_expected, :]
     directions_expected_reordered = directions_expected[order_expected, :]
 
-    np.testing.assert_almost_equal(images_obtained, images_expected_reordered)
-    np.testing.assert_almost_equal(directions_obtained, directions_expected_reordered)
+    np.testing.assert_almost_equal(
+        images_obtained, images_expected_reordered, decimal=5
+    )
+    np.testing.assert_almost_equal(
+        directions_obtained, directions_expected_reordered, decimal=5
+    )

Diff for: pyroomacoustics/random/tests/test_rejection.py

@@ -36,7 +36,7 @@
         hist.push(points)
         hist.plot()
 
-        """
+        r"""
         ax.scatter(X, Y, Z, s=50)
         ax.plot(
             *np.stack((torch.zeros_like(loc), loc)).T,

Diff for: pyroomacoustics/random/tests/test_spherical.py

@@ -34,7 +34,7 @@ def test_stat_prop_power_spherical():
         X, Y, Z = pra.random.power_spherical(loc=loc, scale=scale, size=1000).T
 
         ax.scatter(X, Y, Z, s=50)
-        """
+        r"""
         ax.plot(
             *np.stack((torch.zeros_like(loc), loc)).T,
             linewidth=4,

Diff for: pyroomacoustics/room.py

@@ -2237,7 +2237,9 @@ def image_source_model(self):
                 self.visibility.append(np.zeros((self.mic_array.M, 1), dtype=np.int32))
                 # We also need a fake array of directions as this is expected later in
                 # the code.
-                source.directions = np.zeros((self.mic_array.M, self.dim, 1), dtype=np.float32)
+                source.directions = np.zeros(
+                    (self.mic_array.M, self.dim, 1), dtype=np.float32
+                )
 
         # Update the state
         self.simulator_state["ism_done"] = True