def estimate_surface_area(self):
"""
Estimate the surface area by summing the areas of a trianglation
of the nodules surface in 3d. Returned units are mm^2.
"""
mask = self.get_boolean_mask()
mask = np.pad(mask, [(1,1), (1,1), (1,1)], 'constant') # Cap the ends.
dist = dtrans(mask) - dtrans(~mask)
rxy = self.scan.pixel_spacing
rz = self.scan.slice_thickness
verts, faces, _, _ = marching_cubes(dist, 0, spacing=(rxy, rxy, rz))
return mesh_surface_area(verts, faces)
def visualize_in_3d(self, edgecolor='0.2', cmap='viridis'):
"""
Visualize in 3d a triangulation of the nodule's surface.
edgecolor: string color or rgb 3-tuple
Sets edgecolors of triangulation.
cmap: matplotlib colormap string.
Sets the facecolors of the triangulation.
See `matplotlib.cm.cmap_d.keys()` for all available.
Example:
>>> ann = pl.query(pl.Annotation).first()
>>> ann.visualize_in_3d(edgecolor='green', cmap='autumn')
"""
if cmap not in plt.cm.cmap_d.keys():
raise ValueError("Invalid `cmap`. See `plt.cm.cmap_d.keys()`.")
mask = self.get_boolean_mask()
mask = np.pad(mask, [(1, 1), (1, 1), (1, 1)],
'constant') # Cap the ends.
dist = dtrans(mask) - dtrans(~mask)
rxy = self.scan.pixel_spacing
rz = self.scan.slice_thickness
verts, faces, _, _ = marching_cubes(dist, 0, spacing=(rxy, rxy, rz))
maxes = np.ceil(verts.max(axis=0))
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
t = np.linspace(0, 1, faces.shape[0])
mesh = Poly3DCollection(verts[faces],
edgecolor=edgecolor,
facecolors=plt.cm.cmap_d[cmap](t))
ax.add_collection3d(mesh)
ax.set_xlim(0, maxes[0])
ax.set_xlabel('length (mm)')
ax.set_ylim(0, maxes[1])
ax.set_ylabel('length (mm)')
ax.set_zlim(0, maxes[2])
ax.set_zlabel('length (mm)')
plt.tight_layout()
plt.show()
def visualize_in_3d(self, edgecolor='0.2', cmap='viridis',
backend='matplotlib'):
"""
Visualize in 3d a triangulation of the nodule's surface.
edgecolor: string color or rgb 3-tuple
Sets edgecolors of triangulation.
Ignored if backend != matplotlib.
cmap: matplotlib colormap string.
Sets the facecolors of the triangulation.
See `matplotlib.cm.cmap_d.keys()` for all available.
Ignored if backend != matplotlib.
backend: string
The backend for visualization. Default is matplotlib.
Execute `from pylidc.Annotation import viz3dbackends` to
see available backends.
Example:
>>> ann = pl.query(pl.Annotation).first()
>>> ann.visualize_in_3d(edgecolor='green', cmap='autumn')
>>> ann.visualize_in_3d(backend='mayavi') # If mayavi available.
"""
if backend not in viz3dbackends:
raise ValueError("backend should be in %s." % viz3dbackends)
if backend == 'matplotlib':
if cmap not in plt.cm.cmap_d.keys():
raise ValueError("Invalid `cmap`. See `plt.cm.cmap_d.keys()`.")
mask = self.get_boolean_mask()
mask = np.pad(mask, [(1,1), (1,1), (1,1)], 'constant') # Cap the ends.
# The zero set of the distance transform
# makes for a little nicer surface.
dist = dtrans(mask) - dtrans(~mask)
rxy = self.scan.pixel_spacing
rz = self.scan.slice_thickness
if backend == 'matplotlib':
verts, faces, _, _= marching_cubes(dist, 0, spacing=(rxy, rxy, rz))
maxes = np.ceil(verts.max(axis=0))
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
t = np.linspace(0, 1, faces.shape[0])
mesh = Poly3DCollection(verts[faces],
edgecolor=edgecolor,
facecolors=plt.cm.cmap_d[cmap](t))
ax.add_collection3d(mesh)
ax.set_xlim(0, maxes[0])
ax.set_xlabel('length (mm)')
ax.set_ylim(0, maxes[1])
ax.set_ylabel('length (mm)')
ax.set_zlim(0, maxes[2])
ax.set_zlabel('length (mm)')
plt.tight_layout()
plt.show()
elif backend == 'mayavi':
try:
from mayavi import mlab
sf = mlab.pipeline.scalar_field(dist)
sf.spacing = [rxy, rxy, rz]
mlab.pipeline.iso_surface(sf, contours=[0.0])
mlab.show()
except ImportError:
print("Mayavi could not be imported. Is it installed?")