get all the tests working again

Author: John Tencer

romtools/workflows/greedy/run_greedy.py

@@ -88,6 +88,7 @@
 
 from romtools.workflows.greedy.\
     greedy_coupler_base import GreedyCouplerBase
+from romtools.workflows.parameter_spaces import MonteCarloSample
 
 
 def run_fom_sample(coupler: GreedyCouplerBase,
@@ -128,7 +129,7 @@ def run_greedy(greedy_coupler: GreedyCouplerBase,
 
     # create parameter domain
     parameter_space = greedy_coupler.get_parameter_space()
-    parameter_samples = parameter_space.generate_samples(testing_sample_size)
+    parameter_samples = MonteCarloSample(parameter_space, testing_sample_size)
 
     # Make FOM/ROM directories
     greedy_coupler.create_fom_and_rom_cases(starting_sample_index,
@@ -239,7 +240,7 @@ def run_greedy(greedy_coupler: GreedyCouplerBase,
         basis_time += time.time() - t0
 
         # Add a new sample
-        new_parameter_sample = parameter_space.generate_samples(1)
+        new_parameter_sample = MonteCarloSample(parameter_space, 1)
         parameter_samples = np.append(parameter_samples,
                                       new_parameter_sample, axis=0)
         new_sample_number = testing_sample_size + outer_loop_counter - 1

romtools/workflows/parameter_spaces.py

@@ -118,7 +118,8 @@ def generate_samples(self, uniform_dist_samples: np.array) -> np.array:
         for param in self.get_parameter_list():
             param_samples = param.generate_samples(uniform_dist_samples[:, param_idx:param_idx+param.get_dimensionality()])
             samples.append(param_samples)
-        return samples
+            print(param_samples.shape)
+        return np.concatenate(samples, axis=1)
 
 
 def MonteCarloSample(param_space: ParameterSpace, number_of_samples: int):
@@ -158,6 +159,9 @@ def get_dimensionality(self) -> int:
 
     def generate_samples(self, uniform_dist_samples: np.array) -> np.array:
         assert uniform_dist_samples.shape[1] == self.get_dimensionality()
+        print(self._lower_bound)
+        print(self._upper_bound)
+        print(uniform_dist_samples)
         return qmc.scale(uniform_dist_samples,
                          self._lower_bound,
                          self._upper_bound)

romtools/workflows/sampling/sampling.py

@@ -49,6 +49,7 @@
 
 from romtools.workflows.sampling.\
     sampling_coupler_base import SamplingCouplerBase
+from romtools.workflows.parameter_spaces import MonteCarloSample
 
 
 def run_sampling(sampling_coupler: SamplingCouplerBase,
@@ -61,7 +62,7 @@ def run_sampling(sampling_coupler: SamplingCouplerBase,
 
     # create parameter domain
     parameter_space = sampling_coupler.get_parameter_space()
-    parameter_samples = parameter_space.generate_samples(testing_sample_size)
+    parameter_samples = MonteCarloSample(parameter_space, testing_sample_size)
 
     # Make FOM/ROM directories
     starting_sample_index = 0

tests/romtools/workflows/test_parameter_spaces.py

@@ -7,24 +7,27 @@
 
 
 def test_uniform_parameter():
-    np.random.seed(12)
     param = UniformParameter('p1', -1, 1)
     assert param.get_name() == 'p1'
     assert param.get_dimensionality() == 1
-    s = param.generate_samples(3)
-    assert s.shape == (3, 1)
-    gold = [[-0.69167432],
-            [ 0.48009939],
-            [-0.47336997]]
+
+    germ = np.array([[0.1], [0.5], [0.7]])
+    s = param.generate_samples(germ)
+    assert s.shape == germ.shape
+    gold = [[-0.8],
+            [ 0.0],
+            [ 0.4]]
     np.testing.assert_allclose(s, gold, rtol=1e-5, atol=1e-8)
 
 
 def test_string_parameter():
     param = StringParameter('p1', 'p1val')
     assert param.get_name() == 'p1'
     assert param.get_dimensionality() == 1
-    s = param.generate_samples(3)
-    assert s.shape == (3, 1)
+
+    germ = np.array([[0.1], [0.5], [0.7]])
+    s = param.generate_samples(germ)
+    assert s.shape == germ.shape
     assert (s == [['p1val', 'p1val', 'p1val']]).all()
 
 
@@ -33,20 +36,25 @@ def test_uniform_param_space():
     param_space = UniformParameterSpace(['p1', 'p2'], [-1, 0], [1, 3])
     assert param_space.get_names() == ['p1', 'p2']
     assert param_space.get_dimensionality() == 2
-    s = param_space.generate_samples(4)
-    assert s.shape == (4, 2)
-    gold = [[-0.69167432, 0.04372489],
-            [ 0.48009939, 2.75624102],
-            [-0.47336997, 2.70214456],
-            [ 0.06747879, 0.10026428]]
+
+    germ = np.array([[0.1, 0.2], [0.5, 0.6], [0.7, 0.8]])
+    s = param_space.generate_samples(germ)
+    assert s.shape == (3, 2)
+    gold = [[-0.8, 0.3],
+            [ 0.0, 1.5],
+            [ 0.4, 2.1]]
     np.testing.assert_allclose(s, gold, rtol=1e-5, atol=1e-8)
 
 
 def test_const_param_space():
     param_space = ConstParameterSpace(['p1', 'p2', 'p3'], [1, 3, 'p3val'])
     assert param_space.get_names() == ['p1', 'p2', 'p3']
     assert param_space.get_dimensionality() == 3
-    s = param_space.generate_samples(4)
+    germ = np.array([[0.1, 0.2, 0.3],
+                     [0.4, 0.5, 0.6],
+                     [0.7, 0.8, 0.9],
+                     [0.0, 1.0, 0.5]])
+    s = param_space.generate_samples(germ)
     assert s.shape == (4, 3)
     assert (s == [['1', '3', 'p3val'],
                   ['1', '3', 'p3val'],
@@ -57,16 +65,21 @@ def test_const_param_space():
 def test_hetero_param_space():
     np.random.seed(12)
     param1 = UniformParameter('p1', -1, 1)
-    param2 = UniformParameter('p2', 0, 0)
+    param2 = UniformParameter('p2', 0, 1)
     param3 = StringParameter('p3', 'p3val')
     param_space = HeterogeneousParameterSpace((param1, param2, param3))
 
     assert param_space.get_names() == ['p1', 'p2', 'p3']
     assert param_space.get_dimensionality() == 3
-    s = param_space.generate_samples(4)
+
+    germ = np.array([[0.1, 0.2, 0.3],
+                     [0.4, 0.5, 0.6],
+                     [0.7, 0.8, 0.9],
+                     [0.0, 1.0, 0.5]])
+    s = param_space.generate_samples(germ)
     assert s.shape == (4, 3)
-    print(s)
-    assert (s == [['-0.6916743152406553', '0.0', 'p3val'],
-                  ['0.4800993930308095', '0.0', 'p3val'],
-                  ['-0.47336996962973066', '0.0', 'p3val'],
-                  ['0.06747878676059549', '0.0', 'p3val']]).all()
+    np.testing.assert_allclose(s[:, 0].astype(float), [-0.8, -0.2, 0.4, -1.0],
+                               rtol=1e-5, atol=1e-8)
+    np.testing.assert_allclose(s[:, 1].astype(float), [0.1, 0.4, 0.7, 0.0],
+                               rtol=1e-5, atol=1e-8)
+    assert (s[:, 2] == ['p3val', 'p3val', 'p3val', 'p3val']).all()