tests: cover when approx is None

differt2d/logic.py

@@ -259,7 +259,7 @@ def logical_or(x: Array, y: Array, approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.maximum(x, y) if approx else jnp.logical_or(x, y)
 
@@ -277,7 +277,7 @@ def logical_and(x: Array, y: Array, approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.minimum(x, y) if approx else jnp.logical_and(x, y)
 
@@ -295,7 +295,7 @@ def logical_not(x: Array, approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.subtract(1.0, x) if approx else jnp.logical_not(x)
 
@@ -321,7 +321,7 @@ def greater(
         Keyword arguments to be passed to :func:`activation`.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return activation(jnp.subtract(x, y), **kwargs) if approx else jnp.greater(x, y)
 
@@ -344,7 +344,7 @@ def greater_equal(
         Keyword arguments to be passed to :func:`activation`.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return (
         activation(jnp.subtract(x, y), **kwargs) if approx else jnp.greater_equal(x, y)
@@ -367,7 +367,7 @@ def less(x: Array, y: Array, approx: Optional[bool] = None, **kwargs: Any) -> Ar
         Keyword arguments to be passed to :func:`activation`.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return activation(jnp.subtract(y, x), **kwargs) if approx else jnp.less(x, y)
 
@@ -393,7 +393,7 @@ def less_equal(
         Keyword arguments to be passed to :func:`activation`.
     :return: Output array, with element-wise comparison.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return activation(jnp.subtract(y, x), **kwargs) if approx else jnp.less_equal(x, y)
 
@@ -416,7 +416,7 @@ def logical_all(
     :param approx: Whether approximation is enabled or not.
     :return: Output array.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     arr = jnp.asarray(x)
     return jnp.min(arr, axis=axis) if approx else jnp.all(arr, axis=axis)
@@ -440,7 +440,7 @@ def logical_any(
     :param approx: Whether approximation is enabled or not.
     :return: Output array.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     arr = jnp.asarray(x)
     return jnp.max(arr, axis=axis) if approx else jnp.any(arr, axis=axis)
@@ -460,7 +460,7 @@ def is_true(x: Array, tol: float = 0.5, approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: True array if the value is considered to be true.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.greater(x, 1.0 - tol) if approx else jnp.asarray(x)
 
@@ -479,7 +479,7 @@ def is_false(x: Array, tol: float = 0.5, approx: Optional[bool] = None) -> Array
     :param approx: Whether approximation is enabled or not.
     :return: True if the value is considered to be false.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.less(x, tol) if approx else jnp.logical_not(x)
 
@@ -494,7 +494,7 @@ def true_value(approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: A value that evaluates to true.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.array(1.0) if approx else jnp.array(True)
 
@@ -509,6 +509,6 @@ def false_value(approx: Optional[bool] = None) -> Array:
     :param approx: Whether approximation is enabled or not.
     :return: A value that evaluates to false.
     """
-    if approx is None:  # pragma: no cover
+    if approx is None:
         approx = jax.config.jax_enable_approx  # type: ignore[attr-defined]
     return jnp.array(0.0) if approx else jnp.array(False)

differt2d/scene.py

@@ -375,7 +375,12 @@ def random_uniform_scene(
         return cls(emitters=emitters, receivers=receivers, objects=walls)
 
     @classmethod
-    def basic_scene(cls, *, tx_coords: Array = jnp.array([0.1, 0.1]), rx_coords: Array = jnp.array([0.302, 0.2147])) -> "Scene":
+    def basic_scene(
+        cls,
+        *,
+        tx_coords: Array = jnp.array([0.1, 0.1]),
+        rx_coords: Array = jnp.array([0.302, 0.2147]),
+    ) -> "Scene":
         """
         Instantiates a basic scene with a main room, and a second inner room in the
         lower left corner, with a small entrance.
@@ -425,7 +430,12 @@ def basic_scene(cls, *, tx_coords: Array = jnp.array([0.1, 0.1]), rx_coords: Arr
         return cls(emitters=dict(tx=tx), receivers=dict(rx=rx), objects=walls)
 
     @classmethod
-    def square_scene(cls, *, tx_coords: Array = jnp.array([0.2, 0.2]), rx_coords: Array = jnp.array([0.5, 0.6])) -> "Scene":
+    def square_scene(
+        cls,
+        *,
+        tx_coords: Array = jnp.array([0.2, 0.2]),
+        rx_coords: Array = jnp.array([0.5, 0.6]),
+    ) -> "Scene":
         """
         Instantiates a square scene with one main room.
 
@@ -469,7 +479,13 @@ def square_scene(cls, *, tx_coords: Array = jnp.array([0.2, 0.2]), rx_coords: Ar
         return Scene(emitters=dict(tx=tx), receivers=dict(rx=rx), objects=walls)
 
     @classmethod
-    def square_scene_with_wall(cls, ratio: float = 0.1, *, tx_coords: Array = jnp.array([0.2, 0.5]), rx_coords: Array = jnp.array([0.8, 0.5])) -> "Scene":
+    def square_scene_with_wall(
+        cls,
+        ratio: float = 0.1,
+        *,
+        tx_coords: Array = jnp.array([0.2, 0.5]),
+        rx_coords: Array = jnp.array([0.8, 0.5]),
+    ) -> "Scene":
         """
         Instantiates a square scene with one main room, and vertical wall in the middle.
 

docs/source/index.md

@@ -41,7 +41,7 @@ If you are intersted in contributing to this tool, please checkout the
     ax = plt.gca()
     scene = Scene.basic_scene()
     X, Y = scene.grid(n=300)
-    
+
     Z = scene.accumulate_on_receivers_grid_over_paths(
         X,
         Y,

docs/source/quickstart.md

@@ -45,7 +45,7 @@ pretty useful for optimization problems.
 
     from differt2d.geometry import Wall
 
-    wall = Wall(points=jnp.array([[.8, .2], [.8, .8]]))
+    wall = Wall(points=jnp.array([[0.8, 0.2], [0.8, 0.8]]))
     scene.add_objects([wall])
 
 Plotting utils
@@ -96,7 +96,7 @@ The easiest way to trace all paths from every emitter to every receiver is to us
     wall = Wall(points=jnp.array([[.8, .2], [.8, .8]]))
     scene.add_objects([wall])
     scene.plot(ax)
-    
+
     for _, _, path, _ in scene.all_valid_paths():
         path.plot(ax, zorder=-1)  # -1 to draw below the scene objects
 
@@ -125,7 +125,7 @@ like the received power, on a grid and plot it:
     wall = Wall(points=jnp.array([[.8, .2], [.8, .8]]))
     scene.add_objects([wall])
     scene.plot(ax)
-    
+
     X, Y = scene.grid(n=300)
     Z = scene.accumulate_on_receivers_grid_over_paths(
         X,
@@ -157,7 +157,7 @@ if we were to simulate a higher order of interacion, e.g.:
     wall = Wall(points=jnp.array([[.8, .2], [.8, .8]]))
     scene.add_objects([wall])
     scene.plot(ax)
-    
+
     X, Y = scene.grid(n=300)
     Z = scene.accumulate_on_receivers_grid_over_paths(
         X,

tests/test_logic.py

@@ -23,7 +23,7 @@
     true_value,
 )
 
-approx = pytest.mark.parametrize(("approx",), [(True,), (False,)])
+approx = pytest.mark.parametrize(("approx",), [(True,), (False,), (None,)])
 alpha = pytest.mark.parametrize(
     ("alpha",), [(1e-3,), (1e-2,), (1e-1,), (1e-0,), (1e1,)]
 )
@@ -233,7 +233,7 @@ def test_invalid_activation(function):
 @approx
 def test_logical_or(xy, approx):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = jnp.maximum(x, y)
     else:
         expected = jnp.logical_or(x, y)
@@ -246,7 +246,7 @@ def test_logical_or(xy, approx):
 @approx
 def test_logical_and(xy, approx):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = jnp.minimum(x, y)
     else:
         expected = jnp.logical_and(x, y)
@@ -258,7 +258,7 @@ def test_logical_and(xy, approx):
 
 @approx
 def test_logical_not(x, approx):
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = jnp.subtract(1.0, x)
     else:
         expected = jnp.logical_not(x)
@@ -270,7 +270,7 @@ def test_logical_not(x, approx):
 
 @approx
 def test_logical_all(x, approx):
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         x = jnp.array([0.8, 0.2, 0.3])
         expected = jnp.min(x)
     else:
@@ -284,7 +284,7 @@ def test_logical_all(x, approx):
 
 @approx
 def test_logical_any(x, approx):
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         x = jnp.array([0.8, 0.2, 0.3])
         expected = jnp.max(x)
     else:
@@ -301,7 +301,7 @@ def test_logical_any(x, approx):
 @function
 def test_greater(xy, approx, alpha, function):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = activation(x - y, alpha=alpha, function=function)
     else:
         expected = jnp.greater(x, y)
@@ -316,7 +316,7 @@ def test_greater(xy, approx, alpha, function):
 @function
 def test_greater_equal(xy, approx, alpha, function):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = activation(x - y, alpha=alpha, function=function)
     else:
         expected = jnp.greater_equal(x, y)
@@ -331,7 +331,7 @@ def test_greater_equal(xy, approx, alpha, function):
 @function
 def test_less(xy, approx, alpha, function):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = activation(y - x, alpha=alpha, function=function)
     else:
         expected = jnp.less(x, y)
@@ -346,7 +346,7 @@ def test_less(xy, approx, alpha, function):
 @function
 def test_less_equal(xy, approx, alpha, function):
     x, y = xy
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = activation(y - x, alpha=alpha, function=function)
     else:
         expected = jnp.less_equal(x, y)
@@ -359,7 +359,7 @@ def test_less_equal(xy, approx, alpha, function):
 @approx
 @tol
 def test_is_true(x, approx, tol):
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = jnp.greater(x, 1.0 - tol)
     else:
         x = jnp.greater(x, 1.0 - tol)
@@ -373,7 +373,7 @@ def test_is_true(x, approx, tol):
 @approx
 @tol
 def test_is_false(x, approx, tol):
-    if approx:
+    if approx or (approx is None and jax.config.jax_enable_approx):
         expected = jnp.less(x, tol)
     else:
         x = jnp.greater(x, tol)
@@ -394,5 +394,6 @@ def test_true_value(approx, tol):
 @approx
 @tol
 def test_false_value(approx, tol):
+    print("approx", approx, jax.config.jax_enable_approx)
     x = false_value(approx=approx)
     assert is_false(x, tol=tol, approx=approx)