def test_compare_with_mesh():
image = np.zeros([5, 5])
points = np.array([
[0, 0],
[0, 2],
[2, 2],
[2, 0],
[3, 3],
[3, 4],
[4, 4],
[4, 3],
])
cells = np.array([
[0, 1, 2],
[0, 3, 2],
[4, 5, 6],
[4, 7, 6],
])
# 1: small square, 0: big square
labels = np.array([0, 0, 1, 1])
mesh = TriangleMesh(points=points, cells=cells, labels=labels)
compare_mesh_with_image(image, mesh)
def generate_contour(
self,
level: float = None,
):
"""Generate contours using marching cubes algorithm.
Also generates an envelope around the entire data volume
corresponding to the bounding box.
The bounding box equals the dimensions of the data volume.
Parameters
----------
level : float, optional
Contour value to search for isosurfaces (i.e. the threshold value).
By default takes the average of the min and max value. Can be
ignored if a binary image is passed to `Mesher3D`.
"""
from nanomesh.mesh import TriangleMesh
points, cells, *_ = measure.marching_cubes(
self.image,
level=level,
allow_degenerate=False,
)
mesh = TriangleMesh(points=points, cells=cells)
bbox = BoundingBox.from_shape(self.image.shape)
mesh = generate_envelope(mesh, bbox=bbox)
logger.info(f'Generated contour with {len(mesh.cells)} cells')
self.contour = mesh
def simple_mesh():
return TriangleMesh(points=np.array([
[0., 0.],
[0., 1.],
[1., 1.],
[1., 0.],
]),
cells=np.array([[1, 0, 3], [3, 2, 1]]))
def mesh():
"""Box triangle mesh."""
points = np.array([[0., 0., 0.], [10., 0., 0.], [0., 20., 0.],
[10., 20., 0.], [0., 0., 30.], [10., 0., 30.],
[0., 20., 30.], [10., 20., 30.]])
cells = np.array([[0, 4, 6], [0, 6, 2], [5, 1, 3], [5, 3, 7], [0, 1, 5],
[0, 5, 4], [6, 7, 3], [6, 3, 2], [1, 0, 2], [1, 2, 3],
[4, 5, 7], [4, 7, 6]])
return TriangleMesh(points=points, cells=cells)
def close_side(mesh: TriangleMesh,
*,
side: str,
bbox: BoundingBox,
ax: plt.Axes = None):
"""Fill a side of the bounding box with triangles.
Parameters
----------
mesh : TriangleMesh
Input contour mesh.
side : str
Side of the volume to close. Must be one of
`left`, `right`, `top`, `bottom`, `front`, `back`.
bbox : BoundingBox
Coordinates of the bounding box.
ax : plt.Axes, optional
Plot the generated side on a matplotlib axis.
Returns
-------
mesh : TriangleMesh
Triangle mesh with the given side closed.
Raises
------
ValueError
When the value of `side` is invalid.
"""
from nanomesh.mesh import TriangleMesh
all_points = mesh.points
if side == 'top':
edge_col = 2
edge_value = bbox.zmin
elif side == 'bottom':
edge_col = 2
edge_value = bbox.zmax
elif side == 'left':
edge_col = 1
edge_value = bbox.ymin
elif side == 'right':
edge_col = 1
edge_value = bbox.ymax
elif side == 'front':
edge_col = 0
edge_value = bbox.xmin
elif side == 'back':
edge_col = 0
edge_value = bbox.xmax
else:
raise ValueError('Side must be one of `right`, `left`, `bottom`'
f'`top`, `front`, `back`. Got {side=}')
keep_cols = [col for col in (0, 1, 2) if col != edge_col]
is_edge = all_points[:, edge_col] == edge_value
coords = all_points[is_edge][:, keep_cols]
edge_mesh = simple_triangulate(points=coords, opts='')
cells = edge_mesh.cells_dict['triangle'].copy()
shape = cells.shape
new_cells = cells.ravel()
mesh_edge_index = np.argwhere(is_edge).flatten()
new_edge_index = np.arange(len(mesh_edge_index))
mapping = np.vstack([new_edge_index, mesh_edge_index])
mask = np.in1d(new_cells, mapping[0, :])
new_cells[mask] = mapping[1,
np.searchsorted(mapping[0, :], new_cells[mask])]
new_cells = new_cells.reshape(shape)
new_labels = np.ones(len(new_cells))
points = all_points
cells = np.vstack([mesh.cells, new_cells])
labels = np.hstack([mesh.labels, new_labels])
mesh = TriangleMesh(points=points, cells=cells, labels=labels)
if ax:
edge_mesh.plot(ax=ax)
ax.set_title(side)
return mesh
def triangle_mesh():
"""Generate mesh.
This mesh is a cube with a rectangular 'pore' through the middle.
"""
points = np.array([
# cube
[0.0, 0.0, 0.0], # A
[4.0, 0.0, 0.0], # B
[4.0, 4.0, 0.0], # C
[0.0, 4.0, 0.0], # D
[0.0, 0.0, 4.0], # E
[4.0, 0.0, 4.0], # F
[4.0, 4.0, 4.0], # G
[0.0, 4.0, 4.0], # H
# inside rectangle ('pore')
[1.0, 1.0, 0.0], # a
[3.0, 1.0, 0.0], # b
[3.0, 3.0, 0.0], # c
[1.0, 3.0, 0.0], # d
[1.0, 1.0, 4.0], # e
[3.0, 1.0, 4.0], # f
[3.0, 3.0, 4.0], # g
[1.0, 3.0, 4.0], # h
])
cells = np.array([
# top face
[0, 11, 8],
[1, 8, 9],
[2, 9, 10],
[3, 10, 11],
[0, 8, 1],
[1, 9, 2],
[2, 10, 3],
[3, 11, 0],
# side faces
[0, 1, 5],
[5, 4, 0],
[1, 2, 6],
[6, 5, 1],
[3, 2, 6],
[6, 7, 3],
[0, 3, 7],
[7, 4, 0],
# bottom face
[4, 15, 12],
[5, 12, 13],
[6, 13, 14],
[7, 14, 15],
[4, 12, 5],
[5, 13, 6],
[6, 14, 7],
[7, 15, 4],
# inside rectangle ('pore')
[8, 9, 10],
[10, 11, 8],
[8, 9, 13],
[13, 12, 8],
[9, 10, 14],
[14, 13, 9],
[11, 10, 14],
[14, 15, 11],
[8, 11, 15],
[15, 12, 8],
[13, 14, 15],
[15, 12, 13],
])
mesh = TriangleMesh(points=points, cells=cells)
return mesh