modAL.acquisition std shape bug fixed

Author: cosmic-cortex

examples/bayesian_optimization.py

@@ -14,12 +14,14 @@
 
 def PI(optimizer, X, tradeoff=0):
     mean, std = optimizer.predict(X, return_std=True)
+    std = std.reshape(-1, 1)
 
     return ndtr((mean - optimizer.max_val - tradeoff)/std)
 
 
 def EI(optimizer, X, tradeoff=0):
     mean, std = optimizer.predict(X, return_std=True)
+    std = std.reshape(-1, 1)
     z = (mean - optimizer.max_val - tradeoff)/std
 
     return (mean - optimizer.max_val - tradeoff)*ndtr(z) + std*norm.pdf(z)
@@ -30,6 +32,7 @@ def UCB(optimizer, X, beta=1):
     Ref: https://arxiv.org/abs/0912.3995
     """
     mean, std = optimizer.predict(X, return_std=True)
+    std = std.reshape(-1, 1)
 
     return mean + beta*std
 

modAL/acquisition.py

@@ -128,8 +128,8 @@ def test_make_query_strategy(self):
 class TestAcquisitionFunctions(unittest.TestCase):
     def test_PI(self):
         for n_samples in range(1, 100):
-            mean = np.random.rand(n_samples, )
-            std = np.random.rand(n_samples, )
+            mean = np.random.rand(n_samples, 1)
+            std = np.random.rand(n_samples, 1)
             tradeoff = np.random.rand()
             max_val = np.random.rand()
 
@@ -147,8 +147,8 @@ def test_PI(self):
 
     def test_EI(self):
         for n_samples in range(1, 100):
-            mean = np.random.rand(n_samples, )
-            std = np.random.rand(n_samples, )
+            mean = np.random.rand(n_samples, 1)
+            std = np.random.rand(n_samples, 1)
             tradeoff = np.random.rand()
             max_val = np.random.rand()
 
@@ -169,8 +169,8 @@ def test_EI(self):
 
     def test_UCB(self):
         for n_samples in range(1, 100):
-            mean = np.random.rand(n_samples, )
-            std = np.random.rand(n_samples, )
+            mean = np.random.rand(n_samples, 1)
+            std = np.random.rand(n_samples, 1)
             beta = np.random.rand()
 
             mock_estimator = mock.MockEstimator(