fix axis use for sum

mrmustard/lab_dev/circuit_components.py

@@ -337,7 +337,7 @@ def quadrature(self, quad: Batch[Vector], phi: float = 0.0) -> ComplexTensor:
             # Find where all the bras and kets are so they can be conjugated appropriately
             conjugates = [i not in self.wires.ket.indices for i in range(len(self.wires.indices))]
             quad_basis = math.sum(
-                [quadrature_basis(array, quad, conjugates, phi) for array in fock_arrays], axis=[0]
+                [quadrature_basis(array, quad, conjugates, phi) for array in fock_arrays], axis=0
             )
             return quad_basis
 

mrmustard/lab_dev/states/base.py

@@ -386,7 +386,7 @@ def visualize_2d(
         shape = [max(min_shape, d) for d in self.auto_shape()]
         state = self.to_fock(tuple(shape))
         state = state.dm()
-        dm = math.sum(state.ansatz.array, axis=[0])
+        dm = math.sum(state.ansatz.array, axis=0)
 
         x, prob_x = quadrature_distribution(dm)
         p, prob_p = quadrature_distribution(dm, np.pi / 2)
@@ -502,7 +502,7 @@ def visualize_3d(
         shape = [max(min_shape, d) for d in self.auto_shape()]
         state = self.to_fock(tuple(shape))
         state = state.dm()
-        dm = math.sum(state.ansatz.array, axis=[0])
+        dm = math.sum(state.ansatz.array, axis=0)
 
         xvec = np.linspace(*xbounds, resolution)
         pvec = np.linspace(*pbounds, resolution)
@@ -576,7 +576,7 @@ def visualize_dm(
             raise ValueError("DM visualization not available for multi-mode states.")
         state = self.to_fock(cutoff)
         state = state.dm()
-        dm = math.sum(state.ansatz.array, axis=[0])
+        dm = math.sum(state.ansatz.array, axis=0)
 
         fig = go.Figure(
             data=go.Heatmap(z=abs(dm), colorscale="viridis", name="abs(ρ)", showscale=False)

mrmustard/math/backend_manager.py

@@ -1102,17 +1102,17 @@ def sqrtm(self, tensor: Tensor, dtype=None) -> Tensor:
             The square root of ``x``"""
         return self._apply("sqrtm", (tensor, dtype))
 
-    def sum(self, array: Tensor, axis: Sequence[int] = None):
+    def sum(self, array: Tensor, axis: int | Sequence[int] | None = None):
         r"""The sum of array.
 
         Args:
             array: The array to take the sum of
-            axes (tuple): The axis/axes to sum over
+            axis (int | Sequence[int] | None): The axis/axes to sum over
 
         Returns:
             The sum of array
         """
-        if axis is not None:
+        if axis is not None and not isinstance(axis, int):
             neg = [a for a in axis if a < 0]
             pos = [a for a in axis if a >= 0]
             axis = tuple(sorted(neg) + sorted(pos)[::-1])

mrmustard/math/backend_numpy.py

@@ -390,7 +390,7 @@ def sort(self, array: np.ndarray, axis: int = -1) -> np.ndarray:
     def sqrt(self, x: np.ndarray, dtype=None) -> np.ndarray:
         return np.sqrt(self.cast(x, dtype))
 
-    def sum(self, array: np.ndarray, axis: Sequence[int] = None):
+    def sum(self, array: np.ndarray, axis: int | tuple[int] | None = None):
         return np.sum(array, axis=axis)
 
     @Autocast()

mrmustard/math/backend_tensorflow.py

@@ -336,7 +336,7 @@ def sort(self, array: tf.Tensor, axis: int = -1) -> tf.Tensor:
     def sqrt(self, x: tf.Tensor, dtype=None) -> tf.Tensor:
         return tf.sqrt(self.cast(x, dtype))
 
-    def sum(self, array: tf.Tensor, axis: Sequence[int] = None):
+    def sum(self, array: tf.Tensor, axis: int | tuple[int] | None = None):
         return tf.reduce_sum(array, axis)
 
     @Autocast()

mrmustard/physics/ansatz/array_ansatz.py

@@ -223,7 +223,7 @@ def sum_batch(self) -> ArrayAnsatz:
         Returns:
             The collapsed ArrayAnsatz object.
         """
-        return ArrayAnsatz(math.expand_dims(math.sum(self.array, axis=[0]), 0), batched=True)
+        return ArrayAnsatz(math.expand_dims(math.sum(self.array, axis=0), 0), batched=True)
 
     def to_dict(self) -> dict[str, ArrayLike]:
         return {"array": self.data}

mrmustard/physics/ansatz/polyexp_ansatz.py

@@ -411,12 +411,12 @@ def _call_all(self, z: Batch[Vector]) -> PolyExpAnsatz:
             self.A[..., :dim_alpha, :dim_alpha] * zz, axis=[-1, -2]
         )  # sum((b_arg,1,n,n) * (b_abc,n,n), [-1,-2]) ~ (b_arg,b_abc)
         b_part = math.sum(
-            self.b[..., :dim_alpha] * z[..., None, :], axis=[-1]
+            self.b[..., :dim_alpha] * z[..., None, :], axis=-1
         )  # sum((b_arg,1,n) * (b_abc,n), [-1]) ~ (b_arg,b_abc)
 
         exp_sum = math.exp(1 / 2 * A_part + b_part)  # (b_arg, b_abc)
         if dim_beta == 0:
-            val = math.sum(exp_sum * self.c, axis=[-1])  # (b_arg)
+            val = math.sum(exp_sum * self.c, axis=-1)  # (b_arg)
         else:
             b_poly = math.astensor(
                 math.einsum(
@@ -441,7 +441,7 @@ def _call_all(self, z: Batch[Vector]) -> PolyExpAnsatz:
                     poly * self.c,
                     axis=math.arange(2, 2 + dim_beta, dtype=math.int32).tolist(),
                 ),
-                axis=[-1],
+                axis=-1,
             )  # (b_arg)
         return val
 

mrmustard/physics/gaussian_integrals.py

@@ -382,7 +382,7 @@ def complex_gaussian_integral_1(
         inv_M = math.inv(M)
         c_post = c * math.reshape(
             math.sqrt(math.cast((-1) ** m / det_M, "complex128"))
-            * math.exp(-0.5 * math.sum(bM * math.solve(M, bM), axis=[-1])),
+            * math.exp(-0.5 * math.sum(bM * math.solve(M, bM), axis=-1)),
             c.shape[:1] + (1,) * (len(c.shape) - 1),
         )
         A_post = R - math.einsum("bij,bjk,blk->bil", D, inv_M, D)

mrmustard/physics/representations.py

@@ -155,7 +155,7 @@ def fock_array(self, shape: int | Sequence[int], batched=False) -> ComplexTensor
                     f"Expected Fock shape of length {num_vars}, got length {len(shape)}"
                 ) from e
             arrays = self.ansatz.reduce(shape).array
-        array = math.sum(arrays, axis=[0])
+        array = math.sum(arrays, axis=0)
         arrays = math.expand_dims(array, 0) if batched else array
         return arrays
 

tests/test_lab_dev/test_transformations/test_cft.py

@@ -41,7 +41,7 @@ def test_wigner_function(self):
 
         state = Ket.random([0]) >> Dgate([0], x=1.0, y=0.1)
 
-        dm = math.sum(state.to_fock(100).dm().ansatz.array, axis=[0])
+        dm = math.sum(state.to_fock(100).dm().ansatz.array, axis=0)
         vec = np.linspace(-5, 5, 100)
         wigner, _, _ = wigner_discretized(dm, vec, vec)