TL: remove default weight scaling in LagrangeApproximation

Parallel-in-Time · Jun 21, 2024 · 85a9b94 · 85a9b94
1 parent 271e25b
commit 85a9b94
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Showing 2 changed files with 4 additions and 3 deletions.
diff --git a/qmat/lagrange.py b/qmat/lagrange.py
@@ -120,7 +120,7 @@ class LagrangeApproximation(object):
            "Barycentric Lagrange interpolation." SIAM review, 46(3), 501-517.
     """
 
-    def __init__(self, points, weightComputation='AUTO', scaleRef='MAX', fValues=None):
+    def __init__(self, points, weightComputation='AUTO', scaleWeights=False, scaleRef='MAX', fValues=None):
         points = np.asarray(points).ravel()
         assert np.unique(points).size == points.size, "distinct interpolation points are required"
 
@@ -173,7 +173,8 @@ def chebfun(diffs):
             raise NotImplementedError(
                 f'weightComputation={weightComputation}')
         weights = invProd
-        weights /= np.max(np.abs(weights))
+        if scaleWeights:
+            weights /= np.max(np.abs(weights))
 
         # Store attributes
         self.points = points

diff --git a/tests/test_2_lagrange.py b/tests/test_2_lagrange.py
@@ -24,7 +24,7 @@ def referenceWeights(pType, n):
 def testWeights(pType, weightComputation):
     for n in nNodeTests:
         points, weights = referenceWeights(pType, n)
-        approx = LagrangeApproximation(points, weightComputation=weightComputation)
+        approx = LagrangeApproximation(points, weightComputation=weightComputation, scaleWeights=True)
         assert np.allclose(approx.weights, weights), f"discrepancy with reference weights for n={n}"