def test_prepare_experiments(self):
x = pd.DataFrame([(0,1,2,1),
(2,5,6,1),
(3,2,1,1)],
columns=['a', 'b', 'c', 'd'])
x, _ = fs._prepare_experiments(x)
correct = np.array([[0,1,2,1],
[2,5,6,1],
[3,2,1,1]], dtype=np.float)
self.assertTrue(np.all(x==correct))
# heterogeneous without NAN
x = pd.DataFrame({'a':[0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, 1.0],
'b':[0,1,2,3,4,5,6,7,8,9],
'c':['a','b','a','b','a','a',
'b','a','b','a', ]})
x, _ = fs._prepare_experiments(x)
correct = np.array([[0.1, 0, 0],
[0.2, 1, 1],
[0.3, 2, 0],
[0.4, 3, 1],
[0.5, 4, 0],
[0.6, 5, 0],
[0.7, 6, 1],
[0.8, 7, 0],
[0.9, 8, 1],
[1.0, 9, 0]
], dtype=np.float)
self.assertTrue(np.all(x==correct))
def test_prepare_experiments(self):
x = pd.DataFrame([(0,1,2,1),
(2,5,6,1),
(3,2,1,1)],
columns=['a', 'b', 'c', 'd'])
x, _ = fs._prepare_experiments(x)
correct = np.array([[0,1,2,1],
[2,5,6,1],
[3,2,1,1]], dtype=np.float)
self.assertTrue(np.all(x==correct))
# heterogeneous without NAN
x = pd.DataFrame({'a':[0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, 1.0],
'b':[0,1,2,3,4,5,6,7,8,9],
'c':['a','b','a','b','a','a',
'b','a','b','a', ]})
x, _ = fs._prepare_experiments(x)
correct = np.array([[0.1, 0, 0],
[0.2, 1, 1],
[0.3, 2, 0],
[0.4, 3, 1],
[0.5, 4, 0],
[0.6, 5, 0],
[0.7, 6, 1],
[0.8, 7, 0],
[0.9, 8, 1],
[1.0, 9, 0]
], dtype=np.float)
self.assertTrue(np.all(x==correct))
def test_prepare_experiments(self):
x = np.array([(0,1,2,1),
(2,5,6,1),
(3,2,1,1)],
dtype=[('a', np.float),
('b', np.float),
('c', np.float),
('d', np.float)])
x = fs._prepare_experiments(x)
correct = np.array([[0,1,2,1],
[2,5,6,1],
[3,2,1,1]], dtype=np.float)
self.assertTrue(np.all(x==correct))
# heterogeneous without NAN
dtype = [('a', np.float),('b', np.int), ('c', np.object)]
x = np.empty((10, ), dtype=dtype)
x['a'] = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
x['b'] = [0,1,2,3,4,5,6,7,8,9]
x['c'] = ['a','b','a','b','a','a','b','a','b','a', ]
x = fs._prepare_experiments(x)
correct = np.array([[0.1, 0, 0],
[0.2, 1, 1],
[0.3, 2, 0],
[0.4, 3, 1],
[0.5, 4, 0],
[0.6, 5, 0],
[0.7, 6, 1],
[0.8, 7, 0],
[0.9, 8, 1],
[1.0, 9, 0]
], dtype=np.float)
self.assertTrue(np.all(x==correct))
def test_prepare_experiments(self):
x = np.array([(0, 1, 2, 1), (2, 5, 6, 1), (3, 2, 1, 1)],
dtype=[('a', np.float), ('b', np.float), ('c', np.float),
('d', np.float)])
x = fs._prepare_experiments(x)
correct = np.array([[0, 1, 2, 1], [2, 5, 6, 1], [3, 2, 1, 1]],
dtype=np.float)
self.assertTrue(np.all(x == correct))
# heterogeneous without NAN
dtype = [('a', np.float), ('b', np.int), ('c', np.object)]
x = np.empty((10, ), dtype=dtype)
x['a'] = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
x['b'] = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
x['c'] = [
'a',
'b',
'a',
'b',
'a',
'a',
'b',
'a',
'b',
'a',
]
x = fs._prepare_experiments(x)
correct = np.array(
[[0.1, 0, 0], [0.2, 1, 1], [0.3, 2, 0], [0.4, 3, 1], [0.5, 4, 0],
[0.6, 5, 0], [0.7, 6, 1], [0.8, 7, 0], [0.9, 8, 1], [1.0, 9, 0]],
dtype=np.float)
self.assertTrue(np.all(x == correct))