class TestMatrixContentSingle(unittest.TestCase):
def setUp(self):
self.kernel = TDKernelDMVW(min_x,
min_y,
max_x,
max_y,
cell_size,
kernel_size,
wind_scale,
time_scale,
low_confidence_calculation_zero=True,
evaluation_radius=evaluation_radius)
def calculate(self):
self.kernel.set_measurements(positions_x, positions_y, concentrations,
timestamps, wind_speeds, wind_directions)
self.kernel.calculate_maps()
def testMeanValues(self):
self.calculate()
# Implies, that x is the first index (0)
self.assertEqual(71, self.kernel.mean_map.shape[0])
self.assertEqual(51, self.kernel.mean_map.shape[1])
self.assertTrue(self.kernel.importance_weight_map[20][40] >
self.kernel.importance_weight_map[40][20])
self.assertTrue(
self.kernel.mean_map[20][40] > self.kernel.mean_map[40][20])
def setUp(self):
self.kernel = TDKernelDMVW(min_x,
min_y,
max_x,
max_y,
cell_size,
kernel_size,
wind_scale,
time_scale,
low_confidence_calculation_zero=True,
evaluation_radius=evaluation_radius)
evaluation_radius = 10 * kernel_size
# Create dummy measurement vectors
positions_x = [4, 6.5, 15]
positions_y = [2, 6.5, 15]
concentrations = [2, 2, 2]
wind_directions = [0, 60, 0]
wind_speeds = [0, 1, 0]
timestamps = [0, 60, 60]
# call Kernel
kernel = TDKernelDMVW(min_x,
min_y,
max_x,
max_y,
cell_size,
kernel_size,
wind_scale,
time_scale,
low_confidence_calculation_zero=True,
evaluation_radius=evaluation_radius)
kernel.set_measurements(positions_x, positions_y, concentrations, timestamps,
wind_speeds, wind_directions)
kernel.calculate_maps()
# Show result as map
plt.figure()
plt.title("mean map")
plt.contourf(kernel.cell_grid_x, kernel.cell_grid_y, kernel.mean_map)
plt.colorbar()
plt.figure()
class TestMatrixShape(unittest.TestCase):
def setUp(self):
self.kernel = TDKernelDMVW(min_x,
min_y,
max_x,
max_y,
cell_size,
kernel_size,
wind_scale,
time_scale,
low_confidence_calculation_zero=True,
evaluation_radius=evaluation_radius)
def calculate(self):
self.kernel.set_measurements(positions_x, positions_y, concentrations,
timestamps, wind_speeds, wind_directions)
self.kernel.calculate_maps()
def testBBox(self):
self.assertEqual(number_of_x_cells, self.kernel.number_of_x_cells)
self.assertEqual(number_of_y_cells, self.kernel.number_of_y_cells)
self.assertEqual(min_x, self.kernel.min_x)
self.assertEqual(min_y, self.kernel.min_y)
# BBox is increased to handle python floats properly
self.assertEqual(min_x + round(number_of_x_cells * cell_size, 10),
self.kernel.max_x)
self.assertEqual(min_y + round(number_of_y_cells * cell_size, 10),
self.kernel.max_y)
def testCellGrids(self):
self.assertEqual(number_of_x_cells, self.kernel.cell_grid_x.shape[0])
self.assertEqual(number_of_x_cells, self.kernel.cell_grid_y.shape[0])
self.assertEqual(number_of_y_cells, self.kernel.cell_grid_x.shape[1])
self.assertEqual(number_of_y_cells, self.kernel.cell_grid_y.shape[1])
def testMeanShape(self):
self.calculate()
self.assertEqual(number_of_x_cells, self.kernel.mean_map.shape[0])
self.assertEqual(number_of_y_cells, self.kernel.mean_map.shape[1])
def testVarianceShape(self):
self.calculate()
self.assertEqual(number_of_x_cells, self.kernel.variance_map.shape[0])
self.assertEqual(number_of_y_cells, self.kernel.variance_map.shape[1])
def testConfidenceShape(self):
self.calculate()
self.assertEqual(number_of_x_cells,
self.kernel.confidence_map.shape[0])
self.assertEqual(number_of_y_cells,
self.kernel.confidence_map.shape[1])
def testImportanceShape(self):
self.calculate()
self.assertEqual(number_of_x_cells,
self.kernel.importance_weight_map.shape[0])
self.assertEqual(number_of_y_cells,
self.kernel.importance_weight_map.shape[1])