def test_subtract_means_masked_and_channel_masked(self):
subtract_means(self.X, [9.25], mask=self.M,
channel_mask=self.cm)
means = get_means(self.X, mask=self.M, channel_mask=self.cm)
assert_allclose(means, [0.])
means = get_means(self.X, mask=self.M)
assert_allclose(means, [8.25, 0.])
def test_center_dataset_masked(self):
ds = {
'training': (self.X, FramewiseTargets(self.X, self.M)),
'validation': (self.X + 1, FramewiseTargets(self.X, self.M)),
'test': (self.X * 2, FramewiseTargets(self.X, self.M))
}
assert_allclose(get_means(ds['training'][0], self.M), [8.25, 9.25])
assert_allclose(get_means(ds['validation'][0], self.M), [9.25, 10.25])
assert_allclose(get_means(ds['test'][0], self.M), [16.5, 18.5])
center_dataset(ds)
assert_allclose(get_means(ds['training'][0], self.M), [0., 0.])
assert_allclose(get_means(ds['validation'][0], self.M), [1., 1.])
assert_allclose(get_means(ds['test'][0], self.M), [8.25, 9.25])
def test_center_dataset_masked(self):
ds = {
'training': (self.X, FramewiseTargets(self.X, self.M)),
'validation': (self.X + 1, FramewiseTargets(self.X, self.M)),
'test': (self.X * 2, FramewiseTargets(self.X, self.M))
}
assert_allclose(get_means(ds['training'][0], self.M), [8.25, 9.25])
assert_allclose(get_means(ds['validation'][0], self.M), [9.25, 10.25])
assert_allclose(get_means(ds['test'][0], self.M), [16.5, 18.5])
center_dataset(ds)
assert_allclose(get_means(ds['training'][0], self.M), [0., 0.])
assert_allclose(get_means(ds['validation'][0], self.M), [1., 1.])
assert_allclose(get_means(ds['test'][0], self.M), [8.25, 9.25])
def test_center_dataset(self):
ds = {
'training': (self.X, FramewiseTargets(self.X)),
'validation': (self.X + 1, FramewiseTargets(self.X)),
'test': (self.X * 2, FramewiseTargets(self.X))
}
assert_allclose(get_means(ds['training'][0]), [11., 12.])
assert_allclose(get_means(ds['validation'][0]), [12., 13.])
assert_allclose(get_means(ds['test'][0]), [22., 24.])
center_dataset(ds)
assert_allclose(get_means(ds['training'][0]), [0., 0.], atol=1e-6)
assert_allclose(get_means(ds['validation'][0]), [1., 1.], atol=1e-6)
assert_allclose(get_means(ds['test'][0]), [11., 12.], atol=1e-6)
def test_center_dataset(self):
ds = {
'training': (self.X, FramewiseTargets(self.X)),
'validation': (self.X + 1, FramewiseTargets(self.X)),
'test': (self.X * 2, FramewiseTargets(self.X))
}
assert_allclose(get_means(ds['training'][0]), [11., 12.])
assert_allclose(get_means(ds['validation'][0]), [12., 13.])
assert_allclose(get_means(ds['test'][0]), [22., 24.])
center_dataset(ds)
assert_allclose(get_means(ds['training'][0]), [0., 0.], atol=1e-6)
assert_allclose(get_means(ds['validation'][0]), [1., 1.], atol=1e-6)
assert_allclose(get_means(ds['test'][0]), [11., 12.], atol=1e-6)
def test_subtract_means_masked(self):
subtract_means(self.X, [8.25, 9.25], mask=self.M)
means = get_means(self.X, self.M)
assert_allclose(means, [0., 0.])
self.assertEqual(self.X[2, 0, 0], 16.)
self.assertEqual(self.X[2, 0, 1], 17.)
def test_subtract_means_channel_masked(self):
subtract_means(self.X, [12], channel_mask=self.cm)
means = get_means(self.X, channel_mask=self.cm)
assert_allclose(means, [0.])
means = get_means(self.X)
assert_allclose(means, [11., 0.])
def test_get_means_masked_and_channel_masked(self):
means = get_means(self.X, mask=self.M,
channel_mask=self.cm)
assert_allclose(means, [9.25])
def test_subtract_means(self):
subtract_means(self.X, [11, 12])
means = get_means(self.X)
assert_allclose(means, [0., 0.])
def test_get_means_masked(self):
means = get_means(self.X, self.M)
assert_allclose(means, [8.25, 9.25])
def test_get_means_channel_masked(self):
means = get_means(self.X, channel_mask=self.cm)
assert_allclose(means, [12])
def test_get_means(self):
means = get_means(self.X)
assert_allclose(means, [11., 12.])
def test_get_means(self):
means = get_means(self.X)
assert_allclose(means, [11., 12.])
def test_subtract_means_masked_and_channel_masked(self):
subtract_means(self.X, [9.25], mask=self.M, channel_mask=self.cm)
means = get_means(self.X, mask=self.M, channel_mask=self.cm)
assert_allclose(means, [0.])
means = get_means(self.X, mask=self.M)
assert_allclose(means, [8.25, 0.])
def test_get_means_masked(self):
means = get_means(self.X, self.M)
assert_allclose(means, [8.25, 9.25])
def test_subtract_means_channel_masked(self):
subtract_means(self.X, [12], channel_mask=self.cm)
means = get_means(self.X, channel_mask=self.cm)
assert_allclose(means, [0.])
means = get_means(self.X)
assert_allclose(means, [11., 0.])
def test_subtract_means_masked(self):
subtract_means(self.X, [8.25, 9.25], mask=self.M)
means = get_means(self.X, self.M)
assert_allclose(means, [0., 0.])
self.assertEqual(self.X[2, 0, 0], 16.)
self.assertEqual(self.X[2, 0, 1], 17.)
def test_subtract_means(self):
subtract_means(self.X, [11, 12])
means = get_means(self.X)
assert_allclose(means, [0., 0.])
def test_get_means_masked_and_channel_masked(self):
means = get_means(self.X, mask=self.M, channel_mask=self.cm)
assert_allclose(means, [9.25])
def test_get_means_channel_masked(self):
means = get_means(self.X, channel_mask=self.cm)
assert_allclose(means, [12])