Add documentation / tests for warm starting

cyipopt/cython/ipopt_wrapper.pyx

@@ -592,6 +592,15 @@ cdef class Problem:
         x : array-like, shape(n, )
             Initial guess.
 
+        lagrange : array-like, shape(m, ), optional (default=[])
+            Initial values for the constraint multipliers (only if warm start option is chosen).
+
+        zl : array-like, shape(n, ), optional (default=[])
+            Initial values for the multipliers for lower variable bounds (only if warm start option is chosen).
+
+        zu : array-like, shape(n, ), optional (default=[])
+            Initial values for the multipliers for upper variable bounds (only if warm start option is chosen).
+
         Returns
         -------
         x : array, shape(n, )
@@ -625,14 +634,27 @@ cdef class Problem:
         cdef ApplicationReturnStatus stat
         cdef np.ndarray[DTYPEd_t, ndim=1] g = np.zeros((self.__m,), dtype=DTYPEd)
 
-        if lagrange == []:
+        lagrange = np.atleast_1d(lagrange)
+        zl = np.atleast_1d(zl)
+        zu = np.atleast_1d(zu)
+
+        if len(lagrange) == 0:
             lagrange = np.zeros((self.__m,), dtype=DTYPEd)
+        elif self.__m != len(lagrange):
+            raise ValueError("Wrong length of lagrange.")
+
         cdef np.ndarray[DTYPEd_t, ndim=1] mult_g = np.array(lagrange, dtype=DTYPEd).flatten()
 
-        if zl == []:
+        if len(zl) == 0:
             zl = np.zeros((self.__n,), dtype=DTYPEd)
-        if zu == []:
+        elif self.__n != len(zl):
+            raise ValueError("Wrong length of zl.")
+
+        if len(zu) == 0:
             zu = np.zeros((self.__n,), dtype=DTYPEd)
+        elif self.__n != len(zu):
+            raise ValueError("Wrong length of zu.")
+
         cdef np.ndarray[DTYPEd_t, ndim=1] mult_x_L = np.array(zl, dtype=DTYPEd).flatten()
         cdef np.ndarray[DTYPEd_t, ndim=1] mult_x_U = np.array(zu, dtype=DTYPEd).flatten()
 

cyipopt/tests/integration/test_hs071.py

@@ -18,6 +18,39 @@ def test_hs071_solve(hs071_initial_guess_fixture,
 	np.testing.assert_allclose(x, expected_x)
 
 
+def test_hs071_warm_start(hs071_initial_guess_fixture,
+                          hs071_optimal_solution_fixture,
+                          hs071_problem_instance_fixture):
+    x0 = hs071_initial_guess_fixture
+    nlp = hs071_problem_instance_fixture
+
+    _, info = nlp.solve(x0)
+
+    x_opt, _ = hs071_optimal_solution_fixture
+    np.testing.assert_allclose(info['x'], x_opt)
+
+    x_init = info['x']
+    lagrange = info['mult_g']
+    zl = info['mult_x_L']
+    zu = info['mult_x_U']
+
+    # Set parameters to avoid push the solution
+    # away from the variable bounds
+    nlp.add_option('warm_start_init_point', 'yes')
+    nlp.add_option("warm_start_bound_frac", 1e-6)
+    nlp.add_option("warm_start_bound_push", 1e-6)
+    nlp.add_option("warm_start_slack_bound_frac", 1e-6)
+    nlp.add_option("warm_start_slack_bound_push", 1e-6)
+    nlp.add_option("warm_start_mult_bound_push", 1e-6)
+
+    _, info = nlp.solve(x_init,
+                        lagrange=lagrange,
+                        zl=zl,
+                        zu=zu)
+
+    np.testing.assert_allclose(info['x'], x_opt)
+
+
 def _make_problem(definition, lb, ub, cl, cu):
     n = len(lb)
     m = len(cl)