From 4b416745daa0ab549572cbc851ce4b286fcf5393 Mon Sep 17 00:00:00 2001
From: Jan Petykiewicz <jan@mpxd.net>
Date: Wed, 1 Apr 2026 19:21:47 -0700
Subject: [PATCH] [repetition.Grid] check for invalid displacements or counts

---
 masque/repetition.py           | 21 ++++++++++++++++++++-
 masque/test/test_repetition.py | 26 ++++++++++++++++++++++++++
 2 files changed, 46 insertions(+), 1 deletion(-)

diff --git a/masque/repetition.py b/masque/repetition.py
index 99e1082..1e12fcd 100644
--- a/masque/repetition.py
+++ b/masque/repetition.py
@@ -184,6 +184,8 @@ class Grid(Repetition):
     def a_count(self, val: int) -> None:
         if val != int(val):
             raise PatternError('a_count must be convertable to an int!')
+        if int(val) < 1:
+            raise PatternError(f'Repetition has too-small a_count: {val}')
         self._a_count = int(val)
 
     # b_count property
@@ -195,6 +197,8 @@ class Grid(Repetition):
     def b_count(self, val: int) -> None:
         if val != int(val):
             raise PatternError('b_count must be convertable to an int!')
+        if int(val) < 1:
+            raise PatternError(f'Repetition has too-small b_count: {val}')
         self._b_count = int(val)
 
     @property
@@ -325,7 +329,22 @@ class Arbitrary(Repetition):
 
     @displacements.setter
     def displacements(self, val: ArrayLike) -> None:
-        vala = numpy.array(val, dtype=float)
+        try:
+            vala = numpy.array(val, dtype=float)
+        except (TypeError, ValueError) as exc:
+            raise PatternError('displacements must be convertible to an Nx2 ndarray') from exc
+
+        if vala.size == 0:
+            self._displacements = numpy.empty((0, 2), dtype=float)
+            return
+
+        if vala.ndim == 1:
+            if vala.size != 2:
+                raise PatternError('displacements must be convertible to an Nx2 ndarray')
+            vala = vala.reshape(1, 2)
+        elif vala.ndim != 2 or vala.shape[1] != 2:
+            raise PatternError('displacements must be convertible to an Nx2 ndarray')
+
         order = numpy.lexsort(vala.T[::-1])     # sortrows
         self._displacements = vala[order]
 
diff --git a/masque/test/test_repetition.py b/masque/test/test_repetition.py
index f423ab2..0d0be41 100644
--- a/masque/test/test_repetition.py
+++ b/masque/test/test_repetition.py
@@ -1,7 +1,9 @@
+import pytest
 from numpy.testing import assert_equal, assert_allclose
 from numpy import pi
 
 from ..repetition import Grid, Arbitrary
+from ..error import PatternError
 
 
 def test_grid_displacements() -> None:
@@ -51,6 +53,30 @@ def test_arbitrary_transform() -> None:
     assert_allclose(arb.displacements, [[0, -10]], atol=1e-10)
 
 
+def test_arbitrary_empty_repetition_is_allowed() -> None:
+    arb = Arbitrary([])
+    assert arb.displacements.shape == (0, 2)
+    assert arb.get_bounds() is None
+
+
+def test_arbitrary_rejects_non_nx2_displacements() -> None:
+    for displacements in ([[1], [2]], [[1, 2, 3]], [1, 2, 3]):
+        with pytest.raises(PatternError, match='displacements must be convertible to an Nx2 ndarray'):
+            Arbitrary(displacements)
+
+
+def test_grid_count_setters_reject_nonpositive_values() -> None:
+    for attr, value, message in (
+            ('a_count', 0, 'a_count'),
+            ('a_count', -1, 'a_count'),
+            ('b_count', 0, 'b_count'),
+            ('b_count', -1, 'b_count'),
+            ):
+        grid = Grid(a_vector=(10, 0), b_vector=(0, 5), a_count=2, b_count=2)
+        with pytest.raises(PatternError, match=message):
+            setattr(grid, attr, value)
+
+
 def test_repetition_less_equal_includes_equality() -> None:
     grid_a = Grid(a_vector=(10, 0), a_count=2)
     grid_b = Grid(a_vector=(10, 0), a_count=2)