- Add tests for hype algorithm

- Increase the sampling rate for the hype algorithm in MO-CMA

Author: Tanguy Pierre Louis Damart

bluepyopt/deapext/CMA_MO.py

@@ -71,7 +71,7 @@ def get_hyped(pop, ubound_score=250., threshold_improvement=240.):
     ubounds = numpy.max(points, axis=0) + 2.0
 
     hv = hype.hypeIndicatorSampled(
-        points=points, bounds=ubounds, k=5, nrOfSamples=200000
+        points=points, bounds=ubounds, k=5, nrOfSamples=1000000
     )
     return hv
 

bluepyopt/tests/test_deapext/test_hype.py

@@ -0,0 +1,38 @@
+"""bluepyopt.deapext.hype tests"""
+
+import numpy
+
+import bluepyopt.deapext.hype
+
+import pytest
+
+
+@pytest.mark.unit
+def test_hypeIndicatorExact():
+    """deapext.hype: Testing hypeIndicatorExact"""
+
+    points = numpy.asarray([[250., 250.], [0., 0.], [240., 240.]])
+    bounds = numpy.asarray([250., 250.])
+
+    hv = bluepyopt.deapext.hype.hypeIndicatorExact(points, bounds, k=5)
+
+    assert hv[0] == 0
+    assert hv[1] == 62500
+    assert hv[2] == 100
+
+
+@pytest.mark.unit
+def test_hypeIndicatorSampled():
+    """deapext.hype: Testing hypeIndicatorSampled"""
+
+    points = numpy.asarray([[250., 250.], [0., 0.], [240., 240.]])
+    bounds = numpy.asarray([250., 250.])
+
+    numpy.random.seed(42)
+    hv = bluepyopt.deapext.hype.hypeIndicatorSampled(
+        points, bounds, nrOfSamples=1000000, k=5
+    )
+
+    assert hv[0] == 0
+    assert hv[1] == 62500
+    assert numpy.abs((hv[2] / 100) - 1) < 0.05

bluepyopt/tests/test_deapext/test_optimisationsCMA.py

@@ -55,6 +55,6 @@ def test_optimisationsCMA_MO_run():
     )
     pop, hof, log, hist = optimisation.run(max_ngen=2)
 
-    assert abs(log.select("avg")[-1] - 120.) < 1e-4
-    assert abs(log.select("std")[-1] - 74.8331) < 1e-4
-    assert pop[0] == [0.07506300058169628, 0.01000000003249999]
+    assert abs(log.select("avg")[-1] - 40.) < 1e-4
+    assert abs(log.select("std")[-1] - 16.32993) < 1e-4
+    assert pop[0] == [0.09601241274168831, 0.024646650865379722]