def test_derived_points_with_bounds(self):
self.sigma.guess_bounds()
self.zlev.guess_bounds()
# Broadcast expected points given the known dimensional mapping.
sigma = self.sigma.points[..., np.newaxis, np.newaxis]
eta = self.eta.points[np.newaxis, ...]
depth = self.depth.points[np.newaxis, ...]
depth_c = self.depth_c.points
nsigma = self.nsigma.points
zlev = self.zlev.points[..., np.newaxis, np.newaxis]
# Calculate the expected coordinate with points.
expected_coord = self.derive(sigma, eta, depth, depth_c, nsigma, zlev)
# Broadcast expected bounds given the known dimensional mapping.
sigma = self.sigma.bounds.reshape(sigma.shape + (2,))
eta = self.eta.points.reshape(eta.shape + (1,))
depth = self.depth.points.reshape(depth.shape + (1,))
depth_c = self.depth_c.points.reshape(depth_c.shape + (1,))
nsigma = self.nsigma.points.reshape(nsigma.shape + (1,))
zlev = self.zlev.bounds.reshape(zlev.shape + (2,))
# Calculate the expected bounds.
bounds = self.derive(sigma, eta, depth, depth_c, nsigma, zlev,
coord=False)
expected_coord.bounds = bounds
# Calculate the actual result.
factory = OceanSigmaZFactory(**self.kwargs)
coord = factory.make_coord(self.coord_dims)
self.assertEqual(expected_coord, coord)
def test_derived_points_with_bounds(self):
self.sigma.guess_bounds()
self.zlev.guess_bounds()
# Broadcast expected points given the known dimensional mapping.
sigma = self.sigma.points[..., np.newaxis, np.newaxis]
eta = self.eta.points[np.newaxis, ...]
depth = self.depth.points[np.newaxis, ...]
depth_c = self.depth_c.points
nsigma = self.nsigma.points
zlev = self.zlev.points[..., np.newaxis, np.newaxis]
# Calculate the expected coordinate with points.
expected_coord = self.derive(sigma, eta, depth, depth_c, nsigma, zlev)
# Broadcast expected bounds given the known dimensional mapping.
sigma = self.sigma.bounds.reshape(sigma.shape + (2, ))
eta = self.eta.points.reshape(eta.shape + (1, ))
depth = self.depth.points.reshape(depth.shape + (1, ))
depth_c = self.depth_c.points.reshape(depth_c.shape + (1, ))
nsigma = self.nsigma.points.reshape(nsigma.shape + (1, ))
zlev = self.zlev.bounds.reshape(zlev.shape + (2, ))
# Calculate the expected bounds.
bounds = self.derive(sigma,
eta,
depth,
depth_c,
nsigma,
zlev,
coord=False)
expected_coord.bounds = bounds
# Calculate the actual result.
factory = OceanSigmaZFactory(**self.kwargs)
coord = factory.make_coord(self.coord_dims)
self.assertEqual(expected_coord, coord)
def test_derived_points(self):
# Broadcast expected points given the known dimensional mapping.
sigma = self.sigma.points[..., np.newaxis, np.newaxis]
eta = self.eta.points[np.newaxis, ...]
depth = self.depth.points[np.newaxis, ...]
depth_c = self.depth_c.points
nsigma = self.nsigma.points
zlev = self.zlev.points[..., np.newaxis, np.newaxis]
# Calculate the expected result.
expected_coord = self.derive(sigma, eta, depth, depth_c, nsigma, zlev)
# Calculate the actual result.
factory = OceanSigmaZFactory(**self.kwargs)
coord = factory.make_coord(self.coord_dims)
self.assertEqual(expected_coord, coord)
def test_derived_points(self):
# Broadcast expected points given the known dimensional mapping.
sigma = self.sigma.points[..., np.newaxis, np.newaxis]
eta = self.eta.points[np.newaxis, ...]
depth = self.depth.points[np.newaxis, ...]
depth_c = self.depth_c.points
nsigma = self.nsigma.points
zlev = self.zlev.points[..., np.newaxis, np.newaxis]
# Calculate the expected result.
expected_coord = self.derive(sigma, eta, depth, depth_c, nsigma, zlev)
# Calculate the actual result.
factory = OceanSigmaZFactory(**self.kwargs)
coord = factory.make_coord(self.coord_dims)
self.assertEqual(expected_coord, coord)
