def test_Tile(self):
"""
Test for TileMap
"""
rxLocs = np.random.randn(3, 3) * 20
h = [5, 5, 5]
padDist = np.ones((3, 2)) * 100
local_meshes = []
for ii in range(rxLocs.shape[0]):
local_mesh = mesh_builder_xyz(rxLocs,
h,
padding_distance=padDist,
mesh_type="tree")
local_mesh = refine_tree_xyz(
local_mesh,
rxLocs[ii, :].reshape((1, -1)),
method="radial",
octree_levels=[1],
finalize=True,
)
local_meshes.append(local_mesh)
mesh = mesh_builder_xyz(rxLocs,
h,
padding_distance=padDist,
mesh_type="tree")
# This garantees that the local meshes are always coarser or equal
for local_mesh in local_meshes:
mesh.insert_cells(
local_mesh.gridCC,
local_mesh.cell_levels_by_index(np.arange(local_mesh.nC)),
finalize=False,
)
mesh.finalize()
# Define an active cells from topo
activeCells = utils.surface2ind_topo(mesh, rxLocs)
model = np.random.randn(int(activeCells.sum()))
total_mass = (model * mesh.vol[activeCells]).sum()
for local_mesh in local_meshes:
tile_map = maps.TileMap(
mesh,
activeCells,
local_mesh,
)
local_mass = ((tile_map * model) *
local_mesh.vol[tile_map.local_active]).sum()
self.assertTrue((local_mass - total_mass) / total_mass < 1e-8)
# Add noise and uncertainties
# We add some random Gaussian noise (1nT)
synthetic_data = d + np.random.randn(len(d)) * 1e-3
wd = np.ones(len(synthetic_data)) * 1e-3 # Assign flat uncertainties
###############################################################
# Tiled misfits
#
#
#
#
local_misfits = []
for ii, local_survey in enumerate(local_surveys):
tile_map = maps.TileMap(mesh, activeCells, local_meshes[ii])
local_actives = tile_map.local_active
# Create the forward simulation
simulation = gravity.simulation.Simulation3DIntegral(
survey=local_survey,
mesh=local_meshes[ii],
rhoMap=tile_map,
actInd=local_actives,
sensitivity_path=f"Inversion\Tile{ii}.zarr",
)
data_object = data.Data(
local_survey,
dobs=synthetic_data[local_indices[ii]],