From 3b2b273e5fa647dd4be2b7661182733c5ba8425b Mon Sep 17 00:00:00 2001
From: Matt Haberland <mhaberla@calpoly.edu>
Date: Fri, 19 May 2023 21:26:40 -0700
Subject: [PATCH] MAINT: minimize_ipopt: fix late binding bug

---
 cyipopt/scipy_interface.py                |  7 +++++--
 cyipopt/tests/unit/test_scipy_optional.py | 20 ++++++++++++++++++++
 2 files changed, 25 insertions(+), 2 deletions(-)

diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py
index b74ac010..4843c463 100644
--- a/cyipopt/scipy_interface.py
+++ b/cyipopt/scipy_interface.py
@@ -157,8 +157,11 @@ def __init__(self,
             con_hessian = con.get('hess', None)
             con_kwargs = con.get('kwargs', {})
             if con_jac is None:
-                con_jac = lambda x0, *args, **kwargs: approx_fprime(
-                    x0, con_fun, eps, *args, **kwargs)
+                # beware of late binding!
+                def con_jac(x, *args, con_fun=con_fun, **kwargs):
+                    def wrapped(x):
+                        return con_fun(x, *args, **kwargs)
+                    return approx_fprime(x, wrapped, eps)
             elif con_jac is True:
                 con_fun = MemoizeJac(con_fun)
                 con_jac = con_fun.derivative
diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py
index e636a613..be690028 100644
--- a/cyipopt/tests/unit/test_scipy_optional.py
+++ b/cyipopt/tests/unit/test_scipy_optional.py
@@ -365,3 +365,23 @@ def con_ineq_hess(x, v):
     assert res.get("success") is True
     expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083])
     np.testing.assert_allclose(res.get("x"), expected_res)
+
+
+@pytest.mark.skipif("scipy" not in sys.modules,
+                    reason="Test only valid if Scipy available.")
+def test_minimize_late_binding_bug():
+    # `IpoptProblemWrapper` had a late binding bug when constraint Jacobians
+    # were defined with `optimize.approx_fprime`. Check that this is resolved.
+    from scipy.optimize import minimize
+
+    fun = lambda x: (x[0] - 1)**2 + (x[1] - 2.5)**2
+    cons = ({'type': 'ineq', 'fun': lambda x:  x[0] - 2 * x[1] + 2},
+            {'type': 'ineq', 'fun': lambda x: -x[0] - 2 * x[1] + 6},
+            {'type': 'ineq', 'fun': lambda x: -x[0] + 2 * x[1] + 2})
+    bnds = ((0, None), (0, None))
+
+    res = cyipopt.minimize_ipopt(fun, (2, 0), bounds=bnds, constraints=cons)
+    ref = minimize(fun, (2, 0), bounds=bnds, constraints=cons)
+    assert res.success
+    np.testing.assert_allclose(res.x, ref.x)
+    np.testing.assert_allclose(res.fun, ref.fun)