def test_batch_left_interp_on_a_batch_matrix():
batch_matrix = torch.randn(2, 6, 3)
res = left_interp(batch_interp_indices, batch_interp_values,
Variable(batch_matrix)).data
actual = torch.matmul(batch_interp_matrix, batch_matrix)
assert approx_equal(res, actual)
def test_batch_left_interp_on_a_vector():
vector = torch.randn(6)
actual = torch.matmul(batch_interp_matrix,
vector.unsqueeze(-1).unsqueeze(0)).squeeze(0)
res = left_interp(batch_interp_indices, batch_interp_values,
Variable(vector)).data
assert approx_equal(res, actual)
def test_left_interp_on_a_vector(self):
vector = torch.randn(6)
res = left_interp(
self.interp_indices, self.interp_values, Variable(vector)
).data
actual = torch.matmul(self.interp_matrix, vector)
self.assertTrue(approx_equal(res, actual))
def test_batch_left_interp_on_a_batch_matrix(self):
batch_matrix = torch.randn(2, 6, 3)
res = left_interp(
self.batch_interp_indices, self.batch_interp_values, Variable(batch_matrix)
).data
actual = torch.matmul(self.batch_interp_matrix, batch_matrix)
self.assertTrue(approx_equal(res, actual))
def test_left_interp_on_a_matrix(self):
matrix = torch.randn(6, 3)
res = left_interp(
self.interp_indices,
self.interp_values,
Variable(matrix),
).data
actual = torch.matmul(self.interp_matrix, matrix)
self.assertTrue(approx_equal(res, actual))
def test_batch_left_interp_on_a_vector(self):
vector = torch.randn(6)
actual = torch.matmul(self.batch_interp_matrix,
vector.unsqueeze(-1).unsqueeze(0)).squeeze(0)
res = left_interp(
self.batch_interp_indices,
self.batch_interp_values,
Variable(vector),
).data
self.assertTrue(approx_equal(res, actual))
def test_interpolation(self):
x = torch.linspace(0.01, 1, 100).unsqueeze(1)
grid = torch.linspace(-0.05, 1.05, 50).unsqueeze(0)
indices, values = Interpolation().interpolate(Variable(grid), Variable(x))
indices = indices.squeeze_(0)
values = values.squeeze_(0)
test_func_grid = grid.squeeze(0).pow(2)
test_func_x = x.pow(2).squeeze(-1)
interp_func_x = utils.left_interp(indices.data, values.data, test_func_grid.unsqueeze(1)).squeeze()
self.assertTrue(utils.approx_equal(interp_func_x, test_func_x))
def test_interpolation():
x = torch.linspace(0.01, 1, 100).unsqueeze(1)
grid = torch.linspace(-0.05, 1.05, 50).unsqueeze(0)
indices, values = Interpolation().interpolate(grid, x)
indices.squeeze_(0)
values.squeeze_(0)
test_func_grid = grid.squeeze(0).pow(2)
test_func_x = x.pow(2).squeeze(-1)
interp_func_x = utils.left_interp(indices, values,
test_func_grid.unsqueeze(1)).squeeze()
assert utils.approx_equal(interp_func_x, test_func_x)
def test_left_interp_on_a_matrix():
matrix = torch.randn(6, 3)
res = left_interp(interp_indices, interp_values, Variable(matrix)).data
actual = torch.matmul(interp_matrix, matrix)
assert approx_equal(res, actual)
def test_left_interp_on_a_vector():
vector = torch.randn(6)
res = left_interp(interp_indices, interp_values, Variable(vector)).data
actual = torch.matmul(interp_matrix, vector)
assert approx_equal(res, actual)
