From aade38cfd35175a5e0664ef4cb84516161b4eb24 Mon Sep 17 00:00:00 2001
From: Bas Nijholt <basnijholt@gmail.com>
Date: Wed, 13 Sep 2017 16:18:40 +0200
Subject: [PATCH] 2D: remove self.tri because self.tri.points != self.points,
different order
---
adaptive/learner.py | 19 ++++++-------------
1 file changed, 6 insertions(+), 13 deletions(-)
diff --git a/adaptive/learner.py b/adaptive/learner.py
index 87e0bdd5..5f612df4 100644
--- a/adaptive/learner.py
+++ b/adaptive/learner.py
@@ -620,7 +620,6 @@ class Learner2D(BaseLearner):
self._stack = []
self._interp = {}
self._loss_improvements = []
- self.tri = None
self.tri_combined = None
# Keeps track till which index _points and _values are filled
@@ -664,15 +663,11 @@ class Learner2D(BaseLearner):
@property
def ip(self):
- # Create the Delaunay object
- if self.tri is None:
- self.tri = spatial.Delaunay(self.points, incremental=True,
- qhull_options='Q11 QJ')
-
- return interpolate.LinearNDInterpolator(self.tri, self.values)
+ return interpolate.LinearNDInterpolator(self.points, self.values)
@property
def ip_combined(self):
+ # Create the Delaunay object
if self.tri_combined is None:
self.tri_combined = spatial.Delaunay(self.points_combined,
incremental=True,
@@ -718,13 +713,10 @@ class Learner2D(BaseLearner):
self._stack.pop(i)
break
- # Add the points to the Delaunay objects
+ # Add the points to the Delaunay object
if self.tri_combined and not old_point:
self.tri_combined.add_points([point])
- if self.tri and value is not None:
- self.tri.add_points([point])
-
def _deviation_from_linear_estimate(self, ip, gradients):
tri = ip.tri
p = tri.points[tri.vertices]
@@ -744,7 +736,6 @@ class Learner2D(BaseLearner):
def tri_radius(self, points):
center = points.mean(axis=-2) / (self.ndim + 1)
- center_val = self.ip_combined(center)
return np.linalg.norm(points - center, axis=1).max()
def _fill_stack(self, stack_till=None):
@@ -767,7 +758,7 @@ class Learner2D(BaseLearner):
# Interpolate
ip = self.ip_combined
- tri = ip.tri
+ tri = self.tri_combined
# Gradients
grad = interpolate.interpnd.estimate_gradients_2d_global(
@@ -863,6 +854,8 @@ class Learner2D(BaseLearner):
def remove_unfinished(self):
self._points = self.points
self._values = self.values
+ self.tri_combined = spatial.Delaunay(self.points, incremental=True,
+ qhull_options='Q11 QJ')
self.n -= len(self._interp)
self._interp = {}
--
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