From b98a2dff0e08ce6a64297641a2588dfb681a3a07 Mon Sep 17 00:00:00 2001
From: Manan Gupta <mnn@yogins.com>
Date: Sun, 9 Aug 2026 11:57:14 -0700
Subject: [PATCH] Fix SPSA optimizer ignoring parameter bounds

_check_bounds returned None when one (min, max) pair was given per
variable, so _jail_inside treated it as no bounds and never clipped.
The single-pair branch multiplied the bounds array by d instead of
repeating the pair d times.
---
 pyqpanda-algorithm/pyqpanda_alg/QAOA/spsa.py |  5 +-
 test/QAOA/Test_spsa_minimize.py              | 49 +++++++++++++++++++-
 2 files changed, 51 insertions(+), 3 deletions(-)

diff --git a/pyqpanda-algorithm/pyqpanda_alg/QAOA/spsa.py b/pyqpanda-algorithm/pyqpanda_alg/QAOA/spsa.py
index 6d7ae7b1..7f62924c 100644
--- a/pyqpanda-algorithm/pyqpanda_alg/QAOA/spsa.py
+++ b/pyqpanda-algorithm/pyqpanda_alg/QAOA/spsa.py
@@ -15,7 +15,7 @@
 
 
 def _check_bounds(d, bounds):
-    """Check if the given bounds fits the variables."""
+    """Check if the given bounds fits the variables. Returns d (min, max) pairs, or None."""
     bounds = np.array(bounds)
     bn = len(bounds)
     if bn == 0:
@@ -29,8 +29,9 @@ def _check_bounds(d, bounds):
     elif bn > 1:
         if d != bn:
             raise IndexError('Dimension of ``bounds`` does not match the dimension of variable ``x``.')
+        return bounds
     elif bn == 1:
-        return bounds * d
+        return np.tile(bounds, (d, 1))
 
 
 def _jail_inside(x, bounds):
diff --git a/test/QAOA/Test_spsa_minimize.py b/test/QAOA/Test_spsa_minimize.py
index 819e394c..ad57fc9f 100644
--- a/test/QAOA/Test_spsa_minimize.py
+++ b/test/QAOA/Test_spsa_minimize.py
@@ -54,5 +54,52 @@ def test_spsa_basic_functionality(self, noise_function):
         # 验证回调函数被调用
         assert len(noise_function.history) > 0
         assert noise_function.eval_count > 0
-    
+
+    def test_spsa_bounds_respected(self, simple_function):
+        """Result stays inside per-variable bounds."""
+        np.random.seed(0)
+        x0 = np.array([5.0, 5.0])
+        bounds = [(1.0, 2.0), (1.0, 2.0)]
+
+        result = spsa.spsa_minimize(simple_function, x0, bounds=bounds, maxiter=100)
+
+        assert (result >= 1.0).all()
+        assert (result <= 2.0).all()
+
+    def test_spsa_single_pair_bounds_respected(self, simple_function):
+        """A single (min, max) pair applies to every variable."""
+        np.random.seed(0)
+        x0 = np.array([5.0, 5.0, 5.0])
+
+        result = spsa.spsa_minimize(simple_function, x0, bounds=[(1.0, 2.0)], maxiter=100)
+
+        assert result.shape == x0.shape
+        assert (result >= 1.0).all()
+        assert (result <= 2.0).all()
+
+    def test_check_bounds_per_variable(self):
+        """One pair per variable is returned as given."""
+        bounds = [(0.0, 1.0), (-2.0, 2.0), (3.0, 4.0)]
+
+        checked = spsa._check_bounds(3, bounds)
+
+        assert checked is not None
+        assert np.array_equal(checked, np.array(bounds))
+
+    def test_check_bounds_single_pair_tiled(self):
+        """A single pair is tiled, not multiplied."""
+        checked = spsa._check_bounds(3, [(0, 1)])
+
+        assert np.array_equal(checked, np.array([[0, 1], [0, 1], [0, 1]]))
+
+    def test_check_bounds_validation(self):
+        """Invalid bounds still raise, empty bounds still mean no bounds."""
+        with pytest.raises(ValueError):
+            spsa._check_bounds(2, [(2, 1), (0, 1)])
+
+        with pytest.raises(IndexError):
+            spsa._check_bounds(3, [(0, 1), (0, 1)])
+
+        assert spsa._check_bounds(2, []) is None
+