WIP: Allow multiple points from opt.ask() as long as we are below n_initial points

ProcessOptimizer/optimizer/optimizer.py

@@ -467,11 +467,21 @@ def ask(self, n_points=None, strategy="stbr_fill"):
                 + "got %s" % strategy
             )
 
-        if strategy in ["stbr_fill", "stbr_full"] and self.get_constraints() is not None:
-            raise ValueError(
-                "Steinerberger (default setting) sampling can not be used with constraints,\
-                try using another strategy like 'opt.ask(n,strategy='cl_min')'"
+        if (n_points > self._n_initial_points 
+            and strategy in ["stbr_fill", "stbr_full"] 
+            and self.get_constraints() is not None):
+                raise ValueError(
+                    "Steinerberger (default setting) sampling can not be used with constraints, "
+                    + "try using another strategy like 'opt.ask(n,strategy='cl_min')'"
+                )
+        elif (strategy in ["stbr_fill", "stbr_full"]
+              and self.get_constraints() is not None):
+            warnings.warn(
+                "Steinerberger (default setting) sampling can not be used with constraints, "
+                +f"and you will get an error once you ask for more than {self._n_initial_points} new suggestions. "
+                +"Try using another strategy like 'opt.ask(n,strategy='cl_min')'"
             )
+
         # Caching the result with n_points not None. If some new parameters
         # are provided to the ask, the cache_ is not used.
         if (n_points, strategy) in self.cache_:

ProcessOptimizer/tests/test_constraints.py

@@ -234,6 +234,32 @@ def test_SumEquals():
     # Check that the other dimensions have correct type
     assert isinstance(samples[0][3], str)
     assert not isinstance(samples[0][2], str)
+
+    # Test that we can ask for multiple points at a time, as long as we have 
+    # less than n_initial_points of data
+    space = Space([[0.0, 10.0], [0.0, 10.0]])
+    cons = Constraints([SumEquals((0, 1), 5)], space)
+    opt = Optimizer(
+        dimensions=space,
+        lhs=False,
+        n_initial_points=10,
+    )
+    opt.set_constraints(cons)
+    # Check that we can ask for 10 points
+    assert opt.ask(10)
+    # We should not be able to ask for 11
+    with raises(ValueError):
+        opt.ask(11)
+    # Check that we can ask for multiple experiments piecemeal up to 
+    # n_initial_points (here 10), but not after
+    for i in range(5):
+        x = opt.ask(2)
+        y = [2, 2]
+        opt.tell(x, y)
+    with raises(ValueError):
+        opt.ask(2)
+
+
 
 @pytest.mark.fast_test
 def test_Conditional():