fixing bug in interaction between MultiPolygonBoundaryComp and design vars

setup.py

@@ -41,5 +41,6 @@ setup(name='topfarm',
               'mock',  # replace variables during tests
               'tensorflow',  # loads examples with surrogates
               'shapely', # for multiple polygon boundaries and exclusion zones
-      ],
+              'memory_profiler',  # memory profiling
+              ],
       zip_safe=True)

topfarm/constraint_components/boundary.py

@@ -33,7 +33,7 @@ class XYBoundaryConstraint(Constraint):
             if np.ndim(boundary[0][0]) < 2:
                 self.multi_boundary = [(np.asarray(boundary), 1)]
             else:
-                self.multi_boundary = boundary
+                self.multi_boundary = [(np.asarray(bound), boolean) for bound, boolean in boundary]
                 boundary = boundary[0][0]
         self.boundary = np.asarray(boundary)
         self.boundary_type = boundary_type
@@ -56,9 +56,15 @@ class XYBoundaryConstraint(Constraint):
         return self.boundary_comp
 
     def set_design_var_limits(self, design_vars):
+        if hasattr(self, 'multi_boundary'):
+            bound_min = np.vstack([(bound[0]).min(0) for bound in self.multi_boundary]).min(0)
+            bound_max = np.vstack([(bound[0]).max(0) for bound in self.multi_boundary]).max(0)
+        else:
+            bound_min = self.boundary_comp.xy_boundary.min(0)
+            bound_max = self.boundary_comp.xy_boundary.max(0)
         for k, l, u in zip([topfarm.x_key, topfarm.y_key],
-                           self.boundary_comp.xy_boundary.min(0),
-                           self.boundary_comp.xy_boundary.max(0)):
+                           bound_min,
+                           bound_max):
             if k in design_vars:
                 if len(design_vars[k]) == 4:
                     design_vars[k] = (design_vars[k][0], np.maximum(design_vars[k][1], l),
@@ -175,7 +181,7 @@ class BoundaryBaseComp(ConstraintComponent):
         """Plot boundary"""
         if isinstance(self, MultiPolygonBoundaryComp):
             colors = ['--k', 'k']
-            for bound, io in self.xy_multi_boundary:
+            for bound, io in self.boundaries:
                 ax.plot(np.asarray(bound)[:, 0].tolist() + [np.asarray(bound)[0, 0]],
                         np.asarray(bound)[:, 1].tolist() + [np.asarray(bound)[0, 1]], colors[io])
         else:

topfarm/tests/deprecated_tests/test_constraints/test_boundary_polygon.py

@@ -20,24 +20,6 @@ def testPolygonConcave():
     plot_comp.show()
 
 
-def testMultiPolygon():
-    optimal = [(1.75, 1.3), (4, 1)]
-    boundary = [([(0, 0), (5, 0), (5, 2), (3, 2), (3, 1), (2, 1), (2, 2), (0, 2), (0, 0)], 1),
-                ([(3.5, 0.5), (4.5, 0.5), (4.5, 1.5), (3.5, 1.5)], 1),
-                ([(0.5, 0.5), (1.75, 0.5), (1.75, 1.5), (0.5, 1.5)], 0),
-                ([(0.75, 0.75), (1.25, 0.75), (1.25, 1.25), (0.75, 1.25)], 0),
-                ]
-    plot_comp = NoPlot()  # DummyCostPlotComp(optimal)
-    initial = [(-0, .1), (4, 1.5)][::-1]
-    tf = TopFarm(initial, DummyCost(optimal, inputs=['x', 'y']), 0,
-                 boundary=boundary, boundary_type='multi_polygon', plot_comp=plot_comp,
-                 driver=EasyScipyOptimizeDriver(tol=1e-8, disp=False))
-    tf.evaluate()
-    tf.optimize()
-    np.testing.assert_array_almost_equal(tf.turbine_positions[:, :2], optimal, 4)
-    plot_comp.show()
-
-
 def testPolygonTwoRegionsStartInWrong():
     optimal = [(1, 1), (4, 1)]
     boundary = [(0, 0), (5, 0), (5, 2), (3, 2), (3, 0), (2, 0), (2, 2), (0, 2), (0, 0)]

topfarm/tests/test_constraint/test_boundary_polygon.py

@@ -52,3 +52,21 @@ def testPolygonTwoRegionsStartInWrong():
     tf.optimize()
     plot_comp.show()
     np.testing.assert_array_almost_equal(tf.turbine_positions[:, :2], optimal, 4)
+
+
+def testMultiPolygon():
+    optimal = [(1.75, 1.3), (4, 1)]
+    boundary = [([(0, 0), (5, 0), (5, 2), (3, 2), (3, 1), (2, 1), (2, 2), (0, 2), (0, 0)], 1),
+                ([(3.5, 0.5), (4.5, 0.5), (4.5, 1.5), (3.5, 1.5)], 1),
+                ([(0.5, 0.5), (1.75, 0.5), (1.75, 1.5), (0.5, 1.5)], 0),
+                ([(0.75, 0.75), (1.25, 0.75), (1.25, 1.25), (0.75, 1.25)], 0),
+                ]
+    plot_comp = NoPlot()  # DummyCostPlotComp(optimal)
+    initial = [(-0, .1), (4, 1.5)][::-1]
+    tf = TopFarm(initial, DummyCost(optimal, inputs=['x', 'y']), 0,
+                 boundary=boundary, boundary_type='multi_polygon', plot_comp=plot_comp,
+                 driver=EasyScipyOptimizeDriver(tol=1e-8, disp=False))
+    tf.evaluate()
+    tf.optimize()
+    np.testing.assert_array_almost_equal(tf.turbine_positions[:, :2], optimal, 4)
+    plot_comp.show()