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()
