Merge pull request #282 from novonordisk-research/281-sum_constraints…

…-with-later-dimensions

Fixes sum constraints with later dimensions

CHANGELOG.md

@@ -8,7 +8,10 @@
 
 ### Bugfixes
 
--
+- Fixed a bug where sum_equals constraints would break if used with dimensions other than 
+  an increasing list from 0. E.g. constraining dimensions [0, 1, 2] would work, but 
+  constraining [1, 2, 3] would not. 
+
 
 ## Version 1.0.1 (October 2024)
 

ProcessOptimizer/space/constraints.py

@@ -252,9 +252,9 @@ def phi(d):
             sample_candidate = sample_candidate[0]
             # Check that the candidate is inside the original parameter space
             inspace = [
-                (sample_candidate[i] >= self.space.bounds[i][0]) and
-                (sample_candidate[i] <= self.space.bounds[i][1])
-                for i in range(d)
+                (sample_candidate[i] >= self.space.bounds[dim][0]) and
+                (sample_candidate[i] <= self.space.bounds[dim][1])
+                for i, dim in enumerate(self.sum_equals[0].dimensions)
             ]
             # Only accept the candidate if it is in our space
             if all(inspace):

ProcessOptimizer/tests/test_constraints.py

@@ -234,6 +234,48 @@ 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 the constraint works, irrespective of which dimensions we use
+    dimensions = [
+        (200.0, 450.0),
+        (50.0, 450.0),
+        (0.0, 450.0),
+        (10.0, 60.0),
+    ]
+    # Build optimizer
+    opt = Optimizer(
+        dimensions=dimensions,
+        lhs=False,
+        acq_func="EI",
+        n_initial_points=5,
+        random_state=42,
+    )
+    # Constrain the first three dimensions, and leave out the fourth
+    constraints = [SumEquals(dimensions=[0, 1, 2], value=450)]
+    opt.set_constraints(constraints)    
+    x1 = opt.ask(1)
+    # Change the order of the dimensions
+    dimensions = [
+        (10.0, 60.0),
+        (200.0, 450.0),
+        (50.0, 450.0),
+        (0.0, 450.0),        
+    ]
+    # Build optimizer
+    opt = Optimizer(
+        dimensions=dimensions,
+        lhs=False,
+        acq_func="EI",
+        n_initial_points=5,
+        random_state=42,
+    )
+    # Constrain the same dimensions, that are now second to fourth
+    constraints = [SumEquals(dimensions=[1, 2, 3], value=450)]
+    opt.set_constraints(constraints)    
+    x2 = opt.ask()
+    # The values suggested for the constrained dimensions should be the same 
+    # irrespective of their order in the dimension list
+    assert x1[:3] == x2[1:]
 
 @pytest.mark.fast_test
 def test_Conditional():