Import from FEniCS and simplify code.

BenjaminRodenberg · Nov 16, 2023 · b1f1639 · b1f1639
1 parent fe5d6bd
commit b1f1639
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Showing 2 changed files with 9 additions and 24 deletions.
diff --git a/partitioned-heat-conduction/fenics/heat.py b/partitioned-heat-conduction/fenics/heat.py
@@ -26,9 +26,8 @@
 
 from __future__ import print_function, division
 from fenics import Function, FunctionSpace, Expression, Constant, DirichletBC, TrialFunction, TestFunction, \
-    File, solve, lhs, rhs, grad, inner, dot, dx, ds, interpolate, VectorFunctionSpace, MeshFunction, MPI
+    File, solve, lhs, rhs, grad, inner, dot, dx, ds, interpolate, VectorFunctionSpace, MeshFunction, MPI, MixedElement, split
 from fenicsprecice import Adapter
-from ufl_legacy import MixedElement, split
 
 from errorcomputation import compute_errors
 from my_enums import ProblemType, DomainPart

diff --git a/partitioned-heat-conduction/fenics/utils/utils.py b/partitioned-heat-conduction/fenics/utils/utils.py
@@ -13,20 +13,13 @@ def b_splines(precice, degree, dt):
     '''
     # use equidistant samples
     # apparently you need 2k+2 samples for degree k
-    x_dist = float(dt) / (2 * degree + 2)
-    nodes = []
+    nodes = np.linspace(0,dt,2*3+3)  # <-- But these are 2k+3 samples
     weights = []
     b_splines = {}
-    for i in range(2 * degree + 3):
-        if i==0:
-            nodes.append(0)
-            weights.append(precice.read_data(0))
-        elif i==2*degree+2:
-            nodes.append(dt)
-            weights.append(precice.read_data(dt))
-        else:
-            nodes.append(x_dist * i)
-            weights.append(precice.read_data(x_dist * i))
+
+    for node in nodes:
+        weights.append(precice.read_data(node))
+
     for k in weights[0].keys():
         weights_k = []
         for i in range(2 * degree + 3):
@@ -47,17 +40,10 @@ def b_splines_tmp(prec, u_expr, x_, y_, t_, t, degree, dt):
     keys = prec.read_data(0).keys()
     # use equidistant samples
     # apparently you need 2k+2 samples for degree k
-    x_dist = float(dt) / (2 * degree + 2)
-    nodes = []
+    nodes = np.linspace(0,dt,2*3+3)  # <-- But these are 2k+3 samples
+
     b_splines = {}
-    # set times of samples
-    for i in range(2*degree+3):
-        if i == 0:
-            nodes.append(0)
-        elif i==2*degree+2:
-            nodes.append(dt)
-        else:
-            nodes.append(x_dist * i)
+
     for k in keys:
         weights = []
         for i in range(2 * degree + 3):