wip: N-D LinearOperator

[skip ci]

Author: lucascolley

scipy/sparse/_sputils.py

@@ -369,14 +369,14 @@ def isintlike(x) -> bool:
     return True
 
 
-def isshape(x, nonneg=False, *, allow_nd=(2,)) -> bool:
+def isshape(x, nonneg=False, *, allow_nd=(2,), check_nd=True) -> bool:
     """Is x a valid tuple of dimensions?
 
     If nonneg, also checks that the dimensions are non-negative.
     Shapes of length in the tuple allow_nd are allowed.
     """
     ndim = len(x)
-    if ndim not in allow_nd:
+    if check_nd and ndim not in allow_nd:
         return False
 
     for d in x:

scipy/sparse/linalg/_eigen/_svds.py

@@ -34,6 +34,8 @@ def _iv(A, k, ncv, tol, which, v0, maxiter,
     if math.prod(A.shape) == 0:
         message = "`A` must not be empty."
         raise ValueError(message)
+    if len(A.shape) != 2:
+        raise ValueError("Only 2-D input is supported for `A` (a single matrix)")
 
     # input validation/standardization for `k`
     kmax = min(A.shape) if solver == 'propack' else min(A.shape) - 1

scipy/sparse/linalg/_eigen/tests/test_svds.py

@@ -133,7 +133,7 @@ class SVDSCommonTests:
     _A_empty_msg = "`A` must not be empty."
     _A_dtype_msg = "`A` must be of numeric data type"
     _A_type_msg = "type not understood"
-    _A_ndim_msg = "array must have ndim <= 2"
+    _A_ndim_msg = "Only 2-D input"
     _A_validation_inputs = [
         (np.asarray([[]]), ValueError, _A_empty_msg),
         (np.array([['a', 'b'], ['c', 'd']], dtype='object'), ValueError, _A_dtype_msg),