class TestGpuGridGaussianCompute_2x2(TestCase): def setUp(self): self.size = getDimensions(self) a = np.array([[0, 0], [1, 1], [0, 1], [1, 0], [.5, .5]]).astype(np.float32).reshape(5, 2) sigma = .1 test_set = CellTypeDataSet("", a, rgb=(0, .5, .5)) # These are the individual tiles that will have information about the dataset test_tile = ViewTile((test_set,), (0, 1, 0, 1)) self.new = GpuGridGaussian(test_tile, self.size, sigma) self.new.compute_grid() self.old = GpuGaussianOld(test_tile.get_Data()[0].getDataSet(), test_tile.get_View().view(), self.size, sigma) self.old.compute_grid() def doCleanups(self): self.new.clean_cuda() self.old.clean_cuda() def test_equiv_arrays(self): new_data = self.new.get_grid_data() old_data = self.old.get_grid_data() assert np.array_equiv(new_data, old_data) def test_equal_arrays(self): new_data = self.new.get_grid_data() old_data = self.old.get_grid_data() assert np.array_equal(new_data, old_data) def test_size(self): new_data = self.new.get_grid_data() assert new_data.shape == self.size old_data = self.old.get_grid_data() assert old_data.shape == self.size
def setUp(self): self.size = getDimensions(self) a = np.array([[0, 0], [1, 1], [0, 1], [1, 0], [.5, .5]]).astype(np.float32).reshape(5, 2) sigma = .1 test_set = CellTypeDataSet("", a, rgb=(0, .5, .5)) test_tile = ViewTile((test_set,), (0, 1, 0, 1)) self.new = GpuGridGaussian(test_tile, self.size, sigma) self.new.compute_grid() self.old = GpuGaussianOld(a, (0, 1, 0, 1), self.size, sigma) self.old.compute_grid()
class TestGpuGridGaussianCompute_32x32(TestCase): def setUp(self): self.size = getDimensions(self) a = np.array([[0, 0], [1, 1], [0, 1], [1, 0], [.5, .5]]).astype(np.float32).reshape(5, 2) sigma = .1 test_set = CellTypeDataSet("", a, rgb=(0, .5, .5)) test_tile = ViewTile((test_set,), (0, 1, 0, 1)) self.new = GpuGridGaussian(test_tile, self.size, sigma) self.new.compute_grid() self.old = GpuGaussianOld(a, (0, 1, 0, 1), self.size, sigma) self.old.compute_grid() def doCleanups(self): self.new.clean_cuda() self.old.clean_cuda() def test_equiv_arrays(self): new_data = self.new.get_grid_data() old_data = self.old.get_grid_data() assert np.array_equiv(new_data, old_data) def test_equal_arrays(self): new_data = self.new.get_grid_data() old_data = self.old.get_grid_data() assert np.array_equal(new_data, old_data) def test_size(self): new_data = self.new.get_grid_data() assert new_data.shape == self.size
def setUp(self): self.grid_size = getDimensions(self) a = np.array([[3, 3], [5, 5], [3, 5], [5, 3], [4, 4]]).astype(np.float32).reshape(5, 2) sigma = .07 test_set = CellTypeDataSet("", a, rgb=(0, .5, .5)) # These are the individual tiles that will have information about the dataset test_tile = ViewTile((test_set,), (3, 5, 3, 5)) self.new = GpuGridGaussian(test_tile, self.grid_size, sigma) self.new.compute_grid() self.old = GpuGaussianOld(test_tile.get_Data()[0].getDataSet(), test_tile.get_View().view(), self.grid_size, sigma) self.old.compute_grid()