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17 changes: 9 additions & 8 deletions adaptive/learner/learner2D.py
Original file line number Diff line number Diff line change
Expand Up @@ -35,9 +35,10 @@ def deviations(ip):
ip.tri, values, tol=1e-6
)

p = ip.tri.points[ip.tri.vertices]
vs = values[ip.tri.vertices]
gs = gradients[ip.tri.vertices]
simplices = ip.tri.simplices
p = ip.tri.points[simplices]
vs = values[simplices]
gs = gradients[simplices]

def deviation(p, v, g):
dev = 0
Expand Down Expand Up @@ -68,7 +69,7 @@ def areas(ip):
areas : numpy.ndarray
The area per triangle in ``ip.tri``.
"""
p = ip.tri.points[ip.tri.vertices]
p = ip.tri.points[ip.tri.simplices]
q = p[:, :-1, :] - p[:, -1, None, :]
areas = abs(q[:, 0, 0] * q[:, 1, 1] - q[:, 0, 1] * q[:, 1, 0]) / 2
return areas
Expand Down Expand Up @@ -172,8 +173,8 @@ def minimize_triangle_surface_loss(ip):
>>>
"""
tri = ip.tri
points = tri.points[tri.vertices]
values = ip.values[tri.vertices]
points = tri.points[tri.simplices]
values = ip.values[tri.simplices]
values = values / (ip.values.ptp(axis=0).max() or 1)

def _get_vectors(points):
Expand Down Expand Up @@ -567,7 +568,7 @@ def _fill_stack(self, stack_till=1):
losses_new = []
for j, _ in enumerate(losses):
jsimplex = np.argmax(losses)
triangle = ip.tri.points[ip.tri.vertices[jsimplex]]
triangle = ip.tri.points[ip.tri.simplices[jsimplex]]
point_new = choose_point_in_triangle(triangle, max_badness=5)
point_new = tuple(self._unscale(point_new))

Expand Down Expand Up @@ -685,7 +686,7 @@ def plot(self, n=None, tri_alpha=0):
im = hv.Image(np.rot90(z), bounds=lbrt)

if tri_alpha:
points = self._unscale(ip.tri.points[ip.tri.vertices])
points = self._unscale(ip.tri.points[ip.tri.simplices])
points = np.pad(
points[:, [0, 1, 2, 0], :],
pad_width=((0, 0), (0, 1), (0, 0)),
Expand Down