Reject unsupported ndarray ranks in isvector (#239)

isvector() accepts higher-rank arrays and crashes on zero-dimensional
arrays. Require two dimensions before checking row/column shapes,
matching its documented contract and preventing homogeneous conversions
from silently flattening unsupported inputs. Restore positive controls
hidden by a duplicate test name.

Thirteen regressions fail before the fix. Full suites pass on Windows
Python 3.10/3.12/3.14 and Linux Python 3.13: 351 passed, three skipped,
18 subtests passed. Changed-file pre-commit checks and package builds
pass.

Author: MokiMeow

spatialmath/base/argcheck.py

@@ -510,8 +510,8 @@ def isvector(v: Any, dim: Optional[int] = None) -> bool:
         if dim is None:
             return (
                 (len(s) == 1 and s[0] > 0)
-                or (s[0] == 1 and s[1] > 0)
-                or (s[0] > 0 and s[1] == 1)
+                or (len(s) == 2 and s[0] == 1 and s[1] > 0)
+                or (len(s) == 2 and s[0] > 0 and s[1] == 1)
             )
         else:
             return s == (dim,) or s == (1, dim) or s == (dim, 1)

tests/base/test_argcheck.py

@@ -11,6 +11,7 @@
 import numpy.testing as nt
 
 from spatialmath.base.argcheck import *
+from spatialmath.base.transformsNd import e2h, h2e
 
 
 class Test_check(unittest.TestCase):
@@ -212,10 +213,30 @@ def test_isvector(self):
         self.assertFalse(isvector(np.array([[1, 2, 3]]), 4))
         self.assertFalse(isvector(np.array([[1], [2], [3]]), 4))
 
-    def test_isvector(self):
+    def test_assertvector(self):
         l = [1, 2, 3]
         nt.assert_raises(ValueError, assertvector, l, 4)
 
+    def test_isvector_unsupported_array_shapes(self):
+        for shape in [(), (2, 3), (1, 3, 2), (3, 1, 2), (1, 1, 1), (1, 3, 0)]:
+            with self.subTest(shape=shape):
+                value = np.ones(shape)
+                self.assertFalse(isvector(value))
+                with self.assertRaises(ValueError):
+                    assertvector(value)
+
+    def test_isvector_empty_arrays(self):
+        for shape in [(0,), (1, 0), (0, 1), (0, 0)]:
+            with self.subTest(shape=shape):
+                self.assertFalse(isvector(np.empty(shape)))
+
+    def test_homogeneous_conversion_unsupported_array_shapes(self):
+        for convert in [e2h, h2e]:
+            for shape in [(), (1, 3, 2), (3, 1, 2), (1, 1, 1)]:
+                with self.subTest(convert=convert.__name__, shape=shape):
+                    with self.assertRaises(ValueError):
+                        convert(np.ones(shape))
+
     def test_getvector(self):
         l = [1, 2, 3]
         t = (1, 2, 3)