Check for blockarray inputs in from_operator (#229)

scico/linop/_circconv.py

@@ -18,6 +18,7 @@
 
 import scico.numpy as snp
 from scico._generic_operators import Operator
+from scico.array import is_nested
 from scico.typing import DType, JaxArray, Shape
 
 from ._linop import LinearOperator, _wrap_add_sub, _wrap_mul_div_scalar
@@ -234,6 +235,7 @@ def __truediv__(self, scalar):
             h_is_dft=True,
         )
 
+    @staticmethod
     def from_operator(
         H: Operator, ndims: Optional[int] = None, center: Optional[Shape] = None, jit: bool = True
     ):
@@ -251,6 +253,13 @@ def from_operator(
             jit: If ``True``, jit the resulting `CircularConvolve`.
         """
 
+        if is_nested(H.input_shape):
+            raise ValueError(
+                f"H.input_shape ({H.input_shape}) suggests that H "
+                "takes a BlockArray as input, which is not supported "
+                "by this function."
+            )
+
         if ndims is None:
             ndims = len(H.input_shape)
         else:

scico/test/linop/test_circconv.py

@@ -7,7 +7,7 @@
 import pytest
 
 import scico.numpy as snp
-from scico.linop import CircularConvolve, Convolve
+from scico.linop import CircularConvolve, Convolve, Diagonal
 from scico.random import randint, randn, uniform
 from scico.test.linop.test_linop import adjoint_test
 
@@ -138,3 +138,12 @@ def test_from_operator(self, axes_shape_spec, input_dtype, jit_old_op, jit_new_o
         B = CircularConvolve.from_operator(A, ndims, jit=jit_new_op)
 
         np.testing.assert_allclose(A @ x, B @ x, atol=1e-5)
+
+    def test_from_operator_block_array(self):
+        """`from_operator` should throw an exception if asked to work
+        on an operator with blockarray inputs."""
+
+        H = Diagonal(snp.zeros(((1, 2), (3,))))
+
+        with pytest.raises(ValueError):
+            CircularConvolve.from_operator(H)