def parse(self, resolution=0.001):
interped = np.linspace(0, 1, int(1/resolution))
self._mainCenterline = Curve(self.parse_filepath(
self.main_centerline_id).data)(interped)
self._bifurCenterline = Curve(self.parse_filepath(
self.bifur_centerline_id).data)(interped)
self._sorMainDistalToProximal()
self._sortBifurCenterlinebyMainCenterline()
return self.data()
def plot3d(self, *args, **kwargs):
color = kwargs.pop('color', 'blue')
long = self.shape[-1]
for i in range(long):
f, ax, obj = Curve.plot3d(
self[:, :, i], *args, color=color, **kwargs)
return f, ax, obj
def __init__(self, contour, refinement=None):
assert isinstance(contour, Contour)
self._contour = contour
if refinement is None:
refinement = contour.shape[-1] // 4
# c_1 = Curve(contour(np.linspace(0, 0.25, refinement)))
# c_4 = Curve(contour(np.linspace(0.25, 0.5, refinement)))
# c_3 = Curve(np.fliplr(np.array(contour(np.linspace(0.5, 0.75, refinement)))))
# c_2 = Curve(np.fliplr(np.array(contour(np.linspace(0.75, 1.0, refinement)))))
# super().__init__(c_1, c_2, c_3, c_4)
c_1 = Curve(contour(np.linspace(0, 0.25, refinement)))
c_2 = Curve(contour(np.linspace(0.25, 0.5, refinement)))
c_3 = Curve(
np.fliplr(np.array(contour(np.linspace(0.5, 0.75, refinement)))))
c_4 = Curve(
np.fliplr(np.array(contour(np.linspace(0.75, 1.0, refinement)))))
super().__init__(c_1, c_2, c_3, c_4)
def interpolate_long(self, npts, *args, centerline_reparam=False, **kwargs):
newsurface = np.zeros(
(self.shape[0], self.shape[1], npts)
)
if centerline_reparam:
centroids = np.concatenate([Contour(self[:,:, i]).centroid for i in range(self.shape[-1])], axis=-1)
centerline = Curve(centroids)
centerline_s = centerline.s_frac
for i in range(self.shape[1]):
line = Curve(self[:, i, :], **kwargs)
if not centerline_reparam:
newsurface[:, i, :] = line(
np.linspace(0, 1, npts)
)
else:
newsurface[:, i, :] = line(
np.linspace(0, 1, npts), reparam_curve=centerline_s
)
return self.__class__(newsurface)
def __call__(self, U, V, close=True, reparam=True):
centroids = np.concatenate([Contour(self[:,:, i]).centroid for i in range(self.shape[-1])], axis=-1)
centerline = Curve(centroids)
if reparam:
centerline_s = centerline.s_frac
else:
centerline_s = None
surface = np.stack(
[Curve(self[:, i, :], reparam_curve=centerline_s)(V) for i in range(self.shape[1])],
axis=1
)
if any([U[-1] != 1, U[0] != 0]):
surface = np.stack(
[Curve(surface[:, :, i])(U) for i in range(surface.shape[-1])],
axis=-1
)
else:
surface = np.stack(
[FlatContour(surface[:, :, i])(U) for i in range(surface.shape[-1])],
axis=-1
)
return self.__class__(surface)
def _sorMainDistalToProximal(self):
am, bm = self._mainCenterline[:, 0], self._mainCenterline[:, -1]
ab, bb = self._bifurCenterline[:, 0], self._bifurCenterline[:, -1]
shortestDistanceStart = min(
math.l2_norm(am-ab),
math.l2_norm(am-bb)
)
shortestDistanceEnd = min(
math.l2_norm(bm-ab),
math.l2_norm(bm-bb)
)
if shortestDistanceStart < shortestDistanceEnd:
self._mainCenterline = Curve(np.flipud(self._mainCenterline.T).T)
def get_centerline(self):
centroids = np.concatenate([Contour(self[:,:, i]).centroid for i in range(self.shape[-1])], axis=-1)
centerline = Curve(centroids)
return centerline
def _sortBifurCenterlinebyMainCenterline(self):
am = self._mainCenterline[:, 0]
ab, bb = self._bifurCenterline[:, 0], self._bifurCenterline[:, -1]
if math.l2_norm(am - ab) > math.l2_norm(am - bb):
self._bifurCenterline = Curve(np.flipud(self._bifurCenterline.T).T)
def data(self):
return dict(
main=Curve(self._mainCenterline),
bifur=Curve(self._bifurCenterline),
)