Add “Grading” parameter to Adaptive 1D hypothesis

[modules/smesh.git] / doc / salome / examples / defining_hypotheses_adaptive1d.py

diff --git a/doc/salome/examples/defining_hypotheses_adaptive1d.py b/doc/salome/examples/defining_hypotheses_adaptive1d.py
index 96e2fabfe1912ce45ff7bcdad8640cd474d92771..0110ebc886acc62a5ce424ee58eddfd7726c5e96 100644 (file)
--- a/doc/salome/examples/defining_hypotheses_adaptive1d.py
+++ b/doc/salome/examples/defining_hypotheses_adaptive1d.py
@@ -19,12 +19,14 @@ shape = geompy.MakeCut( shape, tool, theName="shape" )
 # Parameters of Adaptive hypothesis. minSize and maxSize are such that they do not limit
 # size of segments because size of geometrical features lies within [2.-100.] range, hence
 # size of segments is defined by deflection parameter and size of geometrical features only.
+# grading is defined how much size of adjacent elements can differ.
 minSize = 0.1
 maxSize = 200
 deflection = 0.05
+grading = 0.7
 
 mesh = smesh.Mesh( shape )
-mesh.Segment().Adaptive( minSize, maxSize, deflection )
+mesh.Segment().Adaptive( minSize, maxSize, deflection, grading )
 mesh.Triangle().MaxElementArea( 300 )
 mesh.Compute()