Generator: mesh generation module
Preamble
Generator module works on arrays (as defined in Converter) or on CGNS/python trees (pyTrees) containing grid information (coordinates must be defined).
This module is part of Cassiopee, a free opensource pre and postprocessor for CFD simulations.
For use with the array interface, you have to import Generator module:
import Generator as G
For use with the pyTree interface:
import Generator.PyTree as G
List of functions
– Basic grid generation

Create a cartesian mesh defined by a structured array. 

Create a structured cartesian mesh with geometric distribution. 

Create a structured cartesian mesh with geometric distribution fixing last point. 

Create a cartesian mesh defined by an hexaedrical array. 

Create a cartesian mesh defined by a tetraedrical array. 

Create a cartesian mesh defined by a prismatic array. 

Create a cartesian mesh defined by a pyramidal array. 

Create a cartesian mesh defined by a NGON array. 

Create a portion of regular cylindrical grid. 

Create a portion of cylindrical grid. 

Create a portion of cylindrical grid. 
– General purpose grid generators

Create a delaunay mesh given a set of points defined by array. 

Create a constrainedDelaunay mesh starting from a BARarray defining the contour. 

Check if the Delaunay triangulation defined by tri is inside the contour. 

Create a delaunay mesh given a set of points defined by a. 

Create a TRI/TETRA mesh given a set of BAR or surfaces in a. 

Generate a transfinite interpolation mesh from boundaries. 

Generate a transfinite interpolation mesh from 3 input curves. 
Generate a transfinite interpolation mesh for 1 input curve. 


Generate a transfinite interpolation mesh for 2 input curves. 

Generate a transfinite interpolation mesh for 2 input curves. 
Generate a transfinite interpolation mesh for a list of input curves. 


Generate an hyperbolic mesh. 

Generate a multiple mesh for a polyline. 

Generate a multiple mesh for a C1 curve (polyC1). 

Create a structured surface defined by a contour and a point (x,y,z). 

Create a structured surface defined by a contour and an offset (dx,dy,dz). 

Generate a surface mesh by a walk on a list of surfaces, starting from a contour c and following constraints. 

Generates a collar mesh starting from s1 and s2 surfaces, distributions along the surfaces and along the normal direction, with respect to the assembly type between grids. 
– Cartesian grid generators

Generate a muliblock Cartesian mesh. 

Generate an octree (or a quadtree) mesh starting from a list of TRI (or BAR) arrays defining bodies, a list of corresponding snears, and the extension dfar of the mesh. 

Generates a structured set of regular Cartesian grid starting from an octree HEXA or QUAD mesh. 

Adapt an unstructured octree w.r.t. 

Expand the layer of octree elements of level l of one additional layer. 

Create a set of regular cartesian grids. 

Create a set of regular and geometric cartesian grids with double steps. 
– Operations on meshes

Close a mesh defined by an array gathering points closer than tol. 

Select elements whose center is in the surface delimited by curves. 

Map a distribution on a curve or a surface. 

Split a curve and map a distribution on the set of split curves. 

Refine a mesh of power power along all the directions or on a specified one. 

Remesh with a step proportional to curvature. 

Densify a mesh. 

Grow a surface array of one layer by deplacing points of vector. 

Stack two meshes (with same nixnj) into a single mesh. 

Generate N layers to a surface following normals. 

Smooth a mesh with ThompsonMastin elliptic generator. 

Adapt meshes to a given surface (cellN defined). 

Adapt meshes to a given surface sharp edges. 
– Operations on surface meshes

Generate a structured points cloud over a BAR. 

Fix a gap defined by a contour bar and a point cloud representing the gap surface. 

Fix a gap between several component surfaces (list of arrays). 

Surface remeshing using MMGS. 
– Information on generated meshes

Get the barycenter of an array. 

Returns the bounding box of a list of arrays. 

Return the bounding box of all cells of an array. 

Return the axisaligned or oriented bounding box of an array as an array. 

Get the Cartesian Elements bounding box intersection of 2 arrays. 

Return the intersection of bounding boxes of 2 arrays. 

Check if point P is in the Cartesian Elements Bounding Box of array. 

Return the volume map in an array. 

Return the map of surface normals in an array. 

Return the map of smoothed surface normals in an array. 
Return the orthogonality map in an array. 


Return the regularity map in an array. 

Return a TRI quality measure map in an array. 

Return the cell planarity of a surface mesh in an array. 

Return the map of circum circle radius of any cell in a TRI array. 

Return the map of inscribed circle radius of any cell in a TRI array. 

Computes the ratio between the max and min lengths of all the edges of cells in an array. 

Computes the max length of all the edges of cells in an array. 

Return informations on mesh quality. 
– Operations on distributions

Enforce a x0centered line in a distribution defined by an array. 

Enforce the last Xline in a distribution (one sided, left). 

Enforce the first Xline in a distribution defined by an array. 

Enforce a line in a distribution. 

Enforce a point in a distribution. 

Enforce curvature of a curve in a distribution. 

Add a point in a distribution defined by array. 
Contents
Basic grid generation

Generator.
cart
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create a structured Cartesian mesh with ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk).
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cart (array)  import Converter as C import Generator as G a = G.cart((0.,0.,0.), (0.1,0.1,0.2), (10,10,10)) C.convertArrays2File(a, 'out.plt')
#  cart (pyTree)  import Converter.PyTree as C import Generator.PyTree as G a = G.cart((0.,0.,0.), (0.1,0.1,0.2), (10,11,12)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartr1
((xo, yo, zo), (hi, hj, hk), (ri, rj, rk), (ni, nj, nk)) Create a structured Cartesian mesh with geometric distribution of factors r. (hi,hj,hk) are the steps of first cell.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – Step of first cell in the three directions
(ri,rj,rk) (3tuple of floats) – geometric factors in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cartr1 (array)  import Generator as G import Converter as C a = G.cartr1((0,0,0), (1.,1.,1.), (1.1,1.2,1.), (10,10,10)) C.convertArrays2File(a, 'out.plt')
#  cartr1 (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartr1((0,0,0), (1.,1.,1.), (1.1,1.2,1.), (10,10,10)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartr2
((xo, yo, zo), (hi, hj, hk), (ri, rj, rk), (xf, yf, zf)) Create a structured Cartesian mesh with geometric distribution of factors r. (hi,hj,hk) are the steps of first cell. (xf,yf,zf) are coordinates of last point. (hi,hj,hk) or (ri,rj,rk) can be slightly modified to match (xf,yf,zf).
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – Step of first cell in the three directions
(ri,rj,rk) (3tuple of floats) – geometric factors in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cartr2 (array)  import Generator as G import Converter as C a = G.cartr2((10,5,1), (1,1,1), (1.5,1.3,1.), (200.,100.,100.)) C.convertArrays2File(a, 'out.plt')
#  cartr2 (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartr2((10,5,1), (1,1,1), (1.5,1.3,1.), (200.,100.,100.)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartHexa
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create an unstructured hexahedral mesh defined from a Cartesian grid of ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk). Type of elements are ‘QUAD’ for 2D arrays and ‘HEXA’ for 3D arrays.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D unstructured mesh
 Return type
array or pyTree zone
Example of use:
#  cartHexa (array)  import Generator as G import Converter as C a = G.cartHexa((0.,0.,0.), (0.1,0.1,0.2), (10,10,10)) C.convertArrays2File([a], 'out.plt')
#  cartHexa (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartHexa((0.,0.,0.), (0.1,0.1,0.2), (10,10,1)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartTetra
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create an unstructured tetrahedral mesh defined from a Cartesian grid of ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk). Type of elements are ‘TRI’ for 2D arrays and ‘TETRA’ for 3D arrays.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D unstructured mesh
 Return type
array or pyTree zone
Example of use:
#  cartTetra (array)  import Generator as G import Converter as C a = G.cartTetra((0.,0.,0.), (0.1,0.1,0.2), (10,10,1)) C.convertArrays2File(a, 'out.plt')
#  cartTetra (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartTetra((0.,0.,0.), (0.1,0.1,0.2), (10,10,1)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartPenta
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create an unstructured prismatic mesh defined from a regular Cartesian mesh. The initial Cartesian mesh is defined by ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk). Type of elements is ‘PENTA’.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D unstructured mesh
 Return type
array or pyTree zone
Example of use:
#  cartPenta (array)  import Generator as G import Converter as C a = G.cartPenta((0.,0.,0.), (0.1,0.1,0.2), (10,10,10)) C.convertArrays2File([a], "out.plt")
#  cartPenta (pyTree) import Generator.PyTree as G import Converter.PyTree as C a = G.cartPenta((0.,0.,0.), (0.1,0.1,0.2), (10,10,10)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartPyra
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create an unstructured pyramidal mesh defined from a regular Cartesian mesh. The initial Cartesian mesh is defined by ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk). Type of elements is ‘PYRA’.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D unstructured mesh
 Return type
array or pyTree zone
Example of use:
#  cartHexa (array)  import Generator as G import Converter as C a = G.cartPyra((0.,0.,0.), (1,1,1), (20,20,20)) C.convertArrays2File(a, 'out.tp')
#  cartPyra (pyTree) import Generator.PyTree as G import Converter.PyTree as C a = G.cartPyra((0.,0.,0.), (0.1,0.1,0.2), (10,10,10)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cartNGon
((xo, yo, zo), (hi, hj, hk), (ni, nj, nk)) Create a NGON mesh defined from a regular Cartesian mesh. The initial Cartesian mesh is defined by ni x nj x nk points starting from point (xo,yo,zo) and of step (hi,hj,hk). Type of elements is ‘NGON’.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
(hi,hj,hk) (3tuple of floats) – values of advancing step in the three directions
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 1D, 2D or 3D unstructured mesh
 Return type
array or pyTree zone
Example of use:
#  cartNGon (array)  import Generator as G import Converter as C a = G.cartNGon((0.,0.,0.), (0.1,0.1,0.2), (20,20,20)) C.convertArrays2File(a, 'out.plt')
#  cartNGon (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartNGon((0.,0.,0.), (0.1,0.1,0.2), (2,2,2)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cylinder
((xo, yo, zo), R1, R2, tetas, tetae, H, (ni, nj, nk)) Create a regular cylindrical grid (or a portion of cylinder between tetas and tetae) with ni x nj x nk points, of centerbottom point (xo,yo,zo), of inner radius R1, outer radius R2 and height H. For a direct mesh, use tetae < tetas.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
R1 (float) – value of inner radius
R2 (float) – value of outer radius
tetas (float) – start angle (in degree)
tetae (float) – end angle (in degree)
(ni,nj,nk) (3tuple of integers) – number of points in each direction
 Returns
a 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cylinder (array)  import Generator as G import Converter as C a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,30)) C.convertArrays2File([a], "out.plt")
#  cylinder (pyTree)  import Converter.PyTree as C import Generator.PyTree as G a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,30)) C.convertPyTree2File(a, 'out.cgns')

Generator.
cylinder2
((xo, yo, zo), R1, R2, tetas, tetae, H, arrayR, arrayTeta, arrayZ) Create an irregular cylindrical grid (or a portion of cylinder between tetas and tetae) with ni x nj x nk points, of centerbottom point (xo,yo,zo), of inner radius R1, outer radius R2, height H and with distributions in r, teta, z. Distributions are arrays defining 1D meshes (x and i varying) giving a distribution in [0,1]. Their number of points gives ni, nj, nk.
 Parameters
(xo,yo,zo) (3tuple of floats) – coordinates of the starting point
R1 (float) – value of inner radius
R2 (float) – value of outer radius
tetas (float) – start angle (in degree)
tetae (float) – end angle (in degree)
H (float) – value of cylinder height
arrayR (array) – distribution along radius
arrayTeta (array) – distribution along azimuth
arrayZ (array) – distribution along height
 Returns
a 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cylinder2 (array)  import Converter as C import Generator as G r = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) teta = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) z = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) cyl = G.cylinder2( (0.,0.,0.), 0.5, 1., 360., 0., 10., r, teta, z) C.convertArrays2File([cyl], "out.plt")
#  cylinder2 (pyTree)  import Converter.PyTree as C import Generator.PyTree as G r = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) teta = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) z = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) cyl = G.cylinder2( (0.,0.,0.), 0.5, 1., 360., 0., 10., r, teta, z) C.convertPyTree2File(cyl, 'out.cgns')

Generator.
cylinder3
(a, tetas, tetae, arrayTeta) Create an irregular cylindrical grid (or a portion of cylinder between tetas and tetae) from a xz plane mesh defined by a and a teta distribution defined by arrayTeta.
 Parameters
a ([array, list of arrays] or [zone, list of zones, base, pyTree]) – definition of the xz plane mesh
tetas (float) – start angle (in degree)
tetae (float) – end angle (in degree)
arrayTeta (array) – distribution along azimuth
 Returns
a 3D structured mesh
 Return type
array or pyTree zone
Example of use:
#  cylinder3 (array)  import Generator as G import Converter as C teta = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) xz = G.cart((0.1,0.,0.), (0.1,1.,0.2), (20, 1, 30)) cyl = G.cylinder3( xz, 0., 90., teta) C.convertArrays2File([cyl], 'out.plt')
#  cylinder3 (pyTree)  import Converter.PyTree as C import Generator.PyTree as G teta = G.cart((0.,0.,0.), (0.1, 1., 1.), (11, 1, 1)) xz = G.cart((0.1,0.,0.), (0.1,1.,0.2), (20, 1, 30)) cyl = G.cylinder3(xz, 0., 90., teta) C.convertPyTree2File(cyl, 'out.cgns')
General purpose grid generator

Generator.
delaunay
(a, tol=1.e10, keepBB=0) Create a 2D Delaunay type mesh from an array. The array can be a 2D structured array, or an unstructured array of type ‘NODE’, ‘TRI’ or ‘QUAD’. Tol is a geometric tolerance. Points nearer than tol are merged. If keepBB is set to 1, the bounding box is kept in the final triangulation.
 Parameters
a ([array] or [zone]) – structured or unstructured 2D mesh
tol (float) – geometric tolerance
keepBB (integer (0 or 1)) – keep bounding box in result?
 Returns
a 2D unstructured mesh
 Return type
Identical to a
Example of use:
#  delaunay (array)  import Generator as G import Converter as C ni = 11; nj = 11; nk = 1 hi = 1./(ni1); hj = 1./(nj1); hk = 1. a = G.cart((0.,0.,0.), (hi,hj,hk), (ni,nj,nk)) b = G.delaunay(a) C.convertArrays2File([a,b], "out.plt")
#  delaunay (pyTree)  import Converter.PyTree as C import Generator.PyTree as G ni = 11; nj = 11; nk = 1 hi = 1./(ni1); hj = 1./(nj1); hk = 1. a = G.cart((0.,0.,0.), (hi,hj,hk), (ni,nj,nk)) b = G.delaunay(a); b[0] = 'delaunay' t = C.newPyTree(['Base', 2, a,b]) C.convertPyTree2File(t, 'out.cgns')

Generator.
constrainedDelaunay
(c, tol=1.e10, keepBB=0) Create a constrained Delaunay triangulation of the convex hull of a contour c. Contour must be a BARarray and must be in the plane (x,y). Tol is a geometric tolerance. Points nearer than tol are merged. If keepBB is set to 1, the bounding box is kept in the final triangulation.
 Parameters
c (BARarray) – contour in xy plane
tol (float) – geometric tolerance
keepBB (integer (0 or 1)) – keep bounding box in result?
 Returns
a 2D unstructured mesh
 Return type
Identical to a
Example of use:
#  constrainedDelaunay (array)  import Converter as C import Generator as G import Transform as T import Geom as D A = D.text1D('CASSIOPEE') A = C.convertArray2Tetra(A); a = T.join(A) # Triangulation respecting given contour tri = G.constrainedDelaunay(a) C.convertArrays2File([a,tri], "out.plt")
#  constrainedDelaunay (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D import Transform.PyTree as T A = D.text1D('CASSIOPEE') A = C.convertArray2Tetra(A); a = T.join(A) # Triangulation respecting given contour tri = G.constrainedDelaunay(a) C.convertPyTree2File(tri, 'out.cgns')

Generator.
checkDelaunay
(c, tri) Check if the Delaunay triangulation defined in tri is inside the contour c.
 Parameters
c (BARarray) – contour in xy plane
tri (array or pyTree) – 2D Delaunay triangulation mesh
 Returns
contour
 Return type
BARarray
Example of use:
#  checkDelaunay (array)  import Converter as C import Generator as G import Transform as T import Geom as D A = D.text1D('CASSIOPEE') A = C.convertArray2Tetra(A); a = T.join(A) # Triangulation respecting given contour tri = G.constrainedDelaunay(a) res = G.checkDelaunay(a, tri) C.convertArrays2File([res], "out.plt")
#  checkDelaunay (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D import Transform.PyTree as T A = D.text1D('CASSIOPEE') A = C.convertArray2Tetra(A); a = T.join(A) # Triangulation respecting given contour tri = G.constrainedDelaunay(a) res = G.checkDelaunay(a, tri) C.convertPyTree2File(res, "out.cgns")

Generator.
T3mesher2D
(a, triangulateOnly=0, grading=1.2, metricInterpType=0) Creates a 2D Delaunay mesh given a BAR defined in a. If triangulateOnly=1 then only points of a are triangulated, if triangulateOnly=0, then interior points are inserted.
The grading parameter allows to control the growth ratio of the mesh metric : a value greater(lesser) than 1. tends to produce a coarser (finer) mesh in the region far from the boundaries. A value equal to 1. provides a uniform mesh over the domain. This grading is related to the metric field, it is not the size ratio between two adjacent edges or triangles.
The metricInterpType parameter controls the metrics interpolation type: either linear or geometric. A geometric metric interpolation tends to promote smaller sizes.
 Parameters
c ([array, list of arrays] or [pyTree, base, zone, list of zones]) – BARcontour (soup of conformal edges defining an enclosed 2Ddomain, can be nonmanifold, i.e. having inner edges or subdomains)
triangulateOnly (integer (0 or 1)) – insertion or not of interior points for the triangulation
grading (float (strictly positive value)) – metric growth ratio
metricInterpType (integer (0 or 1)) – metric interpolation type, linear(0) or geometric(1)
 Returns
2D mesh
 Return type
Identical to input
Example of use:
#  T3mesher2D (array)  import Generator as G import Converter as C import Geom as D a = D.circle((0,0,0), 1, N=50) a = C.convertArray2Tetra(a) a = G.close(a) b = G.T3mesher2D(a, triangulateOnly=0, grading=1.2, metricInterpType=0) # linear metric interpolation C.convertArrays2File([a,b], 'outL.plt') b = G.T3mesher2D(a, triangulateOnly=0, grading=1.2, metricInterpType=1) # geometric metric interpolation C.convertArrays2File([a,b], 'outG.plt')
#  T3mesher2D (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D a = D.circle((0,0,0), 1, N=50) a = C.convertArray2Tetra(a) a = G.close(a) b = G.T3mesher2D(a, triangulateOnly=0, grading=1.2, metricInterpType=0) # linear metric interpolation C.convertPyTree2File(b, 'outL.cgns') b = G.T3mesher2D(a, triangulateOnly=0, grading=1.2, metricInterpType=1) # geometric metric interpolation C.convertPyTree2File(b, 'outG.cgns')

Generator.
tetraMesher
(a, maxh=1., grading=0.4, algo=1, optionString="") Create a 3D tetra mesh given a TRI surface defined in a. If the TRI surface has external normals, tetras are filled inside the surface. If algo=0, netgen is used, if algo=1, tetgen is used.
 Parameters
c ([array, list of arrays] or [zone, list of zones, base, pyTree]) – triangulated surface mesh
maxh (float) – max cell size of generated mesh [tetgen]
grading (float) – max adjacent cell ratio [tetgen]
optionString (string) – string of options identical to tetgen [tetgen]
algo (integer (0 or 1)) – choice parameter between netgen and tetgen
 Returns
3D mesh
 Return type
[array] or [pyTree zone]
Example of use:
#  tetraMesher (array)  import Generator as G import Converter as C import Post as P import Transform as T a = G.cart((0,0,0), (1,1,1), (3,3,3)) ext = P.exteriorFaces(a) ext = C.convertArray2Tetra(ext) ext = G.close(ext) ext = T.reorder(ext, (1,)) m = G.tetraMesher(ext, algo=1) C.convertArrays2File(m, 'out.plt')
#  tetraMesher (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Post.PyTree as P import Transform.PyTree as T a = G.cart((0,0,0), (1,1,1), (3,3,3)) ext = P.exteriorFaces(a) ext = C.convertArray2Tetra(ext) ext = G.close(ext) ext = T.reorder(ext, (1,)) m = G.tetraMesher(ext, algo=1) C.convertPyTree2File(m, 'out.cgns')

Generator.
TFI
([imin, imax, jmin, jmax, kmin, kmax]) Generate a mesh by transfinite interpolation (TFI). Generated mesh can be 2D or 3D structured, or unstructured TRI or PENTA mesh. Warning: the boundaries can be in a different order from the examples below, except for the PENTA TFI meshes. 2D structured mesh is built from imin, imax, jmin, jmax boundaries. 3D structured mesh is built from imin, imax, jmin, jmax, kmin, kmax boundaries. Dimensions must be equal for each pair (imin,imax), (jmin,jmax)… TRI mesh is built from imin, jmin, diag boundaries. Each boundary is a structured array with the same dimension. PENTA mesh is built from Tmin, Tmax triangles boundary and imin, imax, diag boundaries. Tmin, Tmax must be structured triangles of dimension nxn. imin, jmin, diag must be structured n*p arrays.
 Parameters
imin (array) – Idirection minimum boundary
imax (array) – Idirection maximum boundary
jmin (array) – Jdirection minimum boundary
jmax (array) – Jdirection maximum boundary
kmin (array) – Kdirection minimum boundary
kmax (array) – Kdirection maximum boundary
diag (array) – third direction boundary for TRI or PENTA meshes
 Returns
2D or 3D mesh
 Return type
array or pyTree
Example of use:
#  TFI 2D structured (array) #  TFI 3D structured (array) #  TFI TRI (array) import Converter as C import Generator as G import Geom as D import Transform as T # # TFI 2D structured # P0 = (0,0,0); P1 = (5,0,0); P2 = (0,7,0); P3 = (5,7,0) # Geometrie d1 = D.line(P0, P1); d2 = D.line(P2, P3) pts = C.array('x,y,z',5,1,1) x = pts[1][0]; y = pts[1][1]; z = pts[1][2] x[0] = 0.; y[0] = 0.; z[0] = 0. x[1] =2.; y[1] = 2.; z[1] = 0. x[2] =3.; y[2] = 3.; z[2] = 0. x[3] = 2.; y[3] = 5.; z[3] = 0. x[4] = 0.; y[4] = 7.; z[4] = 0. b1 = D.bezier(pts) pts = C.array('x,y,z',5,1,1) x = pts[1][0]; y = pts[1][1]; z = pts[1][2] x[0] = 5.; y[0] = 0.; z[0] = 0. x[1] = 3.; y[1] = 2.; z[1] = 0. x[2] = 2.; y[2] = 3.; z[2] = 0. x[3] = 6.; y[3] = 5.; z[3] = 0. x[4] = 5.; y[4] = 7.; z[4] = 0. b2 = D.bezier( pts ) C.convertArrays2File([d1, d2, b1, b2], "geom.plt") # Regular discretisation of each line Ni = 20 Nj = 10 r = G.cart((0,0,0), (1./(Ni1),1,1), (Ni,1,1)) q = G.cart((0,0,0), (1./(Nj1),1,1), (Nj,1,1)) r1 = G.map(d1, r) r2 = G.map(d2, r) r3 = G.map(b1, q) r4 = G.map(b2, q) # TFI 2D m = G.TFI([r1, r2, r3, r4]) C.convertArrays2File([r1,r2,r3,r4,m], 'tfi2d.plt') # # TFI 3D structured # xo = 0.; yo = 0.; zo = 0. nx = 21; ny = 21; nz = 21 hx = 1./(nx1); hy = 1./(ny1); hz = 1./(nz1) # z = cste fzmin = G.cart((xo,yo,zo), (hx,hy,1.), (nx,ny,1)) fzmax = T.translate(fzmin, (0.,0.,1.)) # x = cste fxmin = G.cart((xo,yo,zo),(1,hy,hz),(1,ny,nz)) fxmin = T.reorder(fxmin,(3,1,2)) fxmax = T.translate(fxmin, (1.,0.,0.)) # y = cste fymin = G.cart((xo,yo,zo),(hx,1.,hz),(nx,1,nz)) fymin = T.reorder(fymin,(1,3,2)) fymax = T.translate(fymin, (0.,1.,0.)) r = [fxmin,fxmax,fymin,fymax,fzmin,fzmax] m = G.TFI(r) C.convertArrays2File(r+[m], 'tfi3d.plt') # # TFI TRI # l1 = D.line((0,0,0),(0,1,0), 15) l2 = D.line((0,0,0),(1,0,0), 15) l3 = D.line((1,0,0),(0,1,0), 15) tri = G.TFI([l1,l2,l3]) C.convertArrays2File([tri], 'tfitri.plt')
#  TFI (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D # Geometry P0 = (0,0,0); P1 = (5,0,0); P2 = (0,7,0); P3 = (5,7,0) Ni = 20; Nj = 10 d1 = D.line(P0, P1,Ni); d2 = D.line(P2, P3,Ni) d3 = D.line(P0, P2,Nj); d4 = D.line(P1, P3,Nj) m = G.TFI([d1, d2, d3, d4]) C.convertPyTree2File(m, 'out.cgns')

Generator.
TFITri
(a1, a2, a3) Generate three structured meshes by transfinite interpolation around three given curves a1, a2, a3. N3N2+N1 must be odd.
 Parameters
a1 (array) – first curve
a2 (array) – second curve
a3 (array) – third curve
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  TFITri (array) import Converter as C import Generator as G import Geom as D P0 = (0,0,0); P1 = (5,0,0); P2 = (1,7,0) # 3 curves (dont need to be lines) d1 = D.line(P0, P1, N=11) d2 = D.line(P1, P2, N=11) d3 = D.line(P0, P2, N=11) r = G.TFITri(d1, d2, d3) C.convertArrays2File(r, 'out.plt')
#  TFITri (pyTree) import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D P0 = (0,0,0); P1 = (5,0,0); P2 = (1,7,0) # 3 curves (dont need to be lines) d1 = D.line(P0, P1, N=11) d2 = D.line(P1, P2, N=11) d3 = D.line(P0, P2, N=11) r = G.TFITri(d1, d2, d3) C.convertPyTree2File(r, 'out.cgns')

Generator.
TFIO
(a) Generate five meshes by transfinite interpolation around one given curve a. The number of points of a must be odd.
 Parameters
a (array) – curve
 Returns
2D structured mesh (butterfly OH topology)
 Return type
array or pyTree
Example of use:
#  TFIO (array)  import Converter as C import Generator as G import Geom as D a = D.circle((0,0,0), 1., N=41) r = G.TFIO(a) C.convertArrays2File(r, 'out.plt')
#  TFIO (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D a = D.circle((0,0,0), 1., N=41) r = G.TFIO(a) C.convertPyTree2File(r, 'out.cgns')

Generator.
TFIHalfO
(a1, a2) Generate four meshes by transfinite interpolation around two given curves a1 and a2 forming a halfO. N1, the number of points of a1 and N2, the number of points of a2 must be odd.
 Parameters
a1 (array or Zone) – first curve
a2 (array or Zone) – second curve
 Returns
2D structured mesh (half butterfly CH topology)
 Return type
array or Zone
Example of use:
#  TFIHalfO (array)  import Converter as C import Generator as G import Geom as D a1 = D.circle((0,0,0), 1., tetas=0, tetae=180., N=41) a2 = D.line((1,0,0),(1,0,0), N=21) r = G.TFIHalfO(a1, a2) C.convertArrays2File(r, 'out.plt')
#  TFIHalfO (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D a1 = D.circle((0,0,0), 1., tetas=0, tetae=180., N=41) a2 = D.line((1,0,0),(1,0,0), N=21) r = G.TFIHalfO(a1, a2) C.convertPyTree2File(r, 'out.cgns')

Generator.
TFIMono
(a1, a2) Generate one mesh by transfinite interpolation around two given curves a1 and a2 forming a halfO. N1N2 must be even.
 Parameters
a1 (array) – first curve
a2 (array) – second curve
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  TFIMono (array)  import Converter as C import Generator as G import Geom as D a1 = D.circle((0,0,0), 1., tetas=0, tetae=180., N=41) a2 = D.line((1,0,0),(1,0,0), N=21) r = G.TFIMono(a1, a2) C.convertArrays2File(r, 'out.plt')
#  TFIMono (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D a1 = D.circle((0,0,0), 1., tetas=0, tetae=180., N=41) a2 = D.line((1,0,0),(1,0,0), N=21) r = G.TFIMono(a1, a2) C.convertPyTree2File(r, 'out.cgns')

Generator.
TFIStar
(a) Generate a set of meshes by transfinite interpolation a list of given curves.
 Parameters
a (list of structured arrays or zones) – input curves
 Returns
list of 2D structured mesh
 Return type
arrays or pyTree
Example of use:
#  TFIStar (array) import Converter as C import Generator as G import Geom as D P0 = (0,0,0); P1 = (5,0,0); P2 = (7,3,0); P3 = (4,5,0); P4 = (2,2,0) # 5 curves (dont need to be lines) d1 = D.line(P0, P1, N=11) d2 = D.line(P1, P2, N=11) d3 = D.line(P2, P3, N=11) d4 = D.line(P3, P4, N=11) d5 = D.line(P4, P0, N=11) r = G.TFIStar([d1,d2,d3,d4,d5]) C.convertArrays2File(r, 'out.plt')
#  TFIStar (pyTree) import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D P0 = (0,0,0); P1 = (5,0,0); P2 = (7,3,0); P3 = (4,5,0); P4 = (2,2,0) # 5 curves (dont need to be lines) d1 = D.line(P0, P1, N=11) d2 = D.line(P1, P2, N=11) d3 = D.line(P2, P3, N=11) d4 = D.line(P3, P4, N=11) d5 = D.line(P4, P0, N=11) r = G.TFIStar([d1,d2,d3,d4,d5]) C.convertPyTree2File(r, 'out.cgns')

Generator.
hyper2D
(line, distrib, "C") Generate an hyperbolic mesh (2D) of “C” or “O” type from a from a line defined by line and from a distribution defined by distrib. The resulting mesh is nearly orthogonal.
 Parameters
line (array) – starting line of the hyperbolic mesh
distrib (array) – distribution orthogonal to the line
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  hyper2D (array)  import Geom as D import Generator as G import Converter as C msh = D.naca(12., 5001) # Distribution Ni = 300; Nj = 50 distrib = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) a = G.hyper2D(msh, distrib, "C") C.convertArrays2File([a], 'out.plt')
#  hyper2D (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C line = D.naca(12., 5001) # Distribution Ni = 300; Nj = 50 distrib = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) a = G.hyper2D(line, distrib, "C") C.convertPyTree2File(a, 'out.cgns')

Generator.PolyLine.
polyLineMesher
(a, h, hf, density) Generate a 2D mesh around a 2D polyline where a is the input polyline (BARarray), h is the height of the mesh, hf is the height of the first cell and density is the number of points per unity of length. In the ‘array’ version, it returns a list where B[0] is the list of generated meshes, B[1] is the list of wall boundaries, B[2] is the list of overlap boundaries, B[3] is h, B[4] is density (eventually modified by the mesher). In the pyTree version, it returns a list [zones,hs,densities], where zones is a list of zones of a CGNS python tree, containing the blocks, wall boundaries, match and overlap boundaries; hs is the list of heights (modified if necessary), and densities the list of densities (also modified if necessary).
 Parameters
a (BARarray) – input polyline
h (float) – height of the mesh
hf (float) – first cell size
density (integer) – number of points per unity of length
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  polyLineMesher (array)  import Converter as C import Generator.PolyLine as GP import Generator as G import Transform as T # Read a 2D geometry created with tecplot a = C.convertFile2Arrays('fusee.plt') a = G.close(a,1e2); a = T.reorder(a,(1,2,3)) C.convertArrays2File(a, 'input.plt') # Data h = 0.02; hf = 0.0001; density = 500 # Per families coords = []; walls = [] for i in a: b = GP.polyLineMesher(i, h, hf, density) coords.append(b[0]) walls.append(b[1]) # Flat meshes = [] for i in coords: meshes = meshes + i C.convertArrays2File(meshes, 'out.plt')
#  polyLineMesher (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Transform.PyTree as T tb = C.convertFile2PyTree('fusee.plt') tb = G.close(tb,1e2); tb = T.reorder(tb,(1,2,3)) h = 0.02; hf = 0.0001; density = 500 res = G.polyLineMesher(tb[2][1][2][0], h, hf, density) zones = res[0]; h = res[1]; density = res[2] t = C.newPyTree(['PolyC1']); t[2][1][2] += zones C.convertPyTree2File(t, 'out.cgns')

Generator.PolyC1.
polyC1Mesher
(A, h, hf, density, splitCrit=10.) Generate a 2D mesh around a 2D polyC1 curve where A is a list of iarrays each representing a C1 curve. All iarrays put together must represent a polyC1 curve. SplitCrit is a curvature radius triggering split. Other arguments are similar to polyLineMesher. The function return is also similar to polyLineMesher.
 Parameters
A (list of arrays) – list of 1D curves
h (float) – height of the mesh
hf (float) – first cell size
density (integer) – number of points per unity of length
splitCrit (float) – threshold curvature radius below which the initial curve is split
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  polyC1Mesher (array)  import Converter as C import Generator.PolyC1 as GP import Generator as G import Transform as T # Read geometry from svg file a = C.convertFile2Arrays('Data/curve.svg', density=1)[0] a = T.homothety(a,(0,0,0),0.01) a = T.reorder(a, (1,2,3)) h = 0.2; hp = 0.001; density = 10.; splitCrit = 2. m = GP.polyC1Mesher(a, h, hp, density, splitCrit) for i in m[0]: v = G.getVolumeMap(i) min = C.getMinValue(v, 'vol') if min <= 0: print('negative volume detected.') C.convertArrays2File(m[0], 'out.plt')
#  polyC1Mesher (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Transform.PyTree as T tb = C.convertFile2PyTree('curve1.svg', nptsCurve=100, nptsLine=400) z = T.homothety(tb[2][1][2][0], (0.,0.,0.), 0.01) z = T.reorder(z, (1,2,3)) h = 0.1; hf = 0.001; density = 100; splitCrit = 10. res = G.polyC1Mesher(z, h, hf, density, splitCrit) zones = res[0]; h = res[1]; density = res[2] t = C.newPyTree(['Base']); t[2][1][2] += zones C.convertPyTree2File(t, 'out.cgns')

Generator.
pointedHat
(a, (x, y, z)) Create a structured mesh from a curve defined by a iarray and a point. For the pyTree version: if a contains a solution, it is not taken into account in b.
 Parameters
a (array) – closed 1D curve
(x,y,z) (3tuple of floats) – coordinates of point
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  pointedHat (array)  import Geom as D import Generator as G import Converter as C c = D.circle( (0,0,0), 1., 360., 0., 100) surf = G.pointedHat(c,(0.,0.,1.)) C.convertArrays2File([surf], 'out.plt')
#  pointedHat (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C c = D.circle( (0,0,0), 1., 360., 0., 100) surf = G.pointedHat(c,(0.,0.,1.)) t = C.newPyTree(['Base']); t[2][1][2].append(surf) C.convertPyTree2File(t, 'out.cgns')

Generator.
stitchedHat
(a, (offx, offy, offz), tol=1.e6, tol2=1.e5) Create a stitched mesh from a curve defined by a iarray. The surface is stitched in the middle. Tol is the accuracy of the search, tol2 is a merging tolerance and offx, offy, off z an optional offset. For the pyTree version: if a contains a solution, it is not taken into account in b.
 Parameters
a (array) – closed 1D curve
(offx,offy,offz) (3tuple of floats) – coordinates of offset vector
tol (float) – accuracy of search
tol2 (float) – merging tolerance
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  stitchedHat (array)  import Geom as D import Generator as G import Transform as T import Converter as C c = D.circle( (0,0,0), 1., 360., 0., 100) c = T.contract(c, (0,0,0), (0,1,0), (0,0,1), 0.1) c = G.stitchedHat(c, (0,0,0), 1.e3) C.convertArrays2File([c], 'out.plt')
#  stitchedHat (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Transform.PyTree as T import Converter.PyTree as C c = D.circle((0,0,0), 1., 360., 0., 100) c = T.contract(c, (0,0,0), (0,1,0), (0,0,1), 0.1) c = G.stitchedHat(c, (0,0,0), 1.e4) C.convertPyTree2File(c, 'out.cgns')

Generator.
surfaceWalk
(surfaces, c, dj, constraints=[], niter=0, alphaRef=180., check=0, toldist=1.e6) Surface extrusion starting from a curve, resulting into a surface mesh. dj is the distribution of points in the extrusion direction starting from c, niter the number of smoothing iterations. check=1 means that the extrusion stops at the layer before cells intersect alphaRef is the deviation angle wrt 180 degrees enabling to stop the extrusion before it crosses a sharp edge on the surface. toldist is a tolerance below which points are considered matching. Constraints can be set as 1D zones.
 Parameters
surfaces (list of arrays) – list of surfaces
c (array or pyTree) – starting curve for the extrusion
dj (1Darray) – distribution of points for the extrusion
constraints (list of arrays) – 1D curves constraining the extrusion
niter (integer) – number of smoothing iterations
alphaRef (float) – deviation angle (in degrees) stopping the extrusion
check (integer) – activation key for stopping the extrusion (0 or 1)
toldist (float) – merging points tolerance
 Returns
2D structured mesh
 Return type
array or pyTree
Example of use:
#  surfaceWalk (array) import Converter as C import Geom as D import Transform as T import Generator as G # User definition of parametric curve def f(t,u): x = t+u; y = t*t+1+u*u; z = u return (x,y,z) # Array definition of geometry a = D.surface(f) c = D.circle((1.2,1.7,0.6), 0.1,N=100) c = T.rotate(c, (1.2,1.7,0.6), (0,1,0), 90.) c = T.reorder(c,(1,2,3)) c = T.projectOrtho(c,[a]) h = G.cart((0.,0.,0.),(0.01,1,1),(30,1,1)) r = G.surfaceWalk([a], c, h, niter=100) C.convertArrays2File([a,c,r], "out.plt")
#  surfaceWalk (pyTree) import Converter.PyTree as C import Geom.PyTree as D import Transform.PyTree as T import Generator.PyTree as G # User definition of parametric curve def f(t,u): x = t+u; y = t*t+1+u*u; z = u return (x,y,z) # Array definition of geometry a = D.surface(f) c = D.circle((1.2,1.7,0.6), 0.1) c = T.rotate(c, (1.2,1.7,0.6), (0,1,0), 90.) c = T.reorder(c,(1,2,3)) c = T.projectOrtho(c,[a]) h = G.cart((0.,0.,0.),(0.01,1,1),(15,1,1)) r = G.surfaceWalk([a], c, h, niter=100) C.convertPyTree2File(r, "out.cgns")

Generator.
collarMesh
(s1, s2, dj, dk, niterj=100, niterk=100, ext=5, alphaRef=30., type='union', contour=[], constraints1=[], constraints2=[], toldist=1.e10, topology='overset') Create a collar mesh at junction(s) between two surfaces s1 and s2 in union or difference assembly, using a distribution along the surface dj and a distribution in the normal direction to the wall dk. niterj and niterk are the number of smoothing iterations for j and k directions. ext is the extension of the collar mesh for difference assembly. type is the assembly type, and can be ‘union’ or ‘difference’. alphaRef is the deviation angle wrt 180 degrees above which the walk is stopped. contour is the starting contour to create the collar grids, constraints1 and constraints2 are 1D zones defining the curves the collar grid must follow on surfaces s1 and s2 respectively. toldist is the matching point tolerance. Parameter ‘topology’ can be ‘overset’ or ‘extruded’, only useful in case of difference. Topology set to ‘overset’ results in two overlapping collar grids, whereas it results in a collar grid extruded from the surface grid in the other case.
 Parameters
s1 (array or pyTree) – surface
s2 (array or pyTree) – surface
dj (1Darray) – distribution of points along surfaces
dk (1Darray) – distribution of points in the normal direction
niterj (integer) – number of smoothing iterations in j direction
niterk (integer) – number of smoothing iterations in k direction
ext (integer) – extension of collar for difference assembly
alphaRef (float) – deviation angle (in degrees) stopping the extrusion
type (string) – type of the assembly (union or difference)
contour (list of arrays) – starting curve for the collar creation
constraints1 (list of arrays) – 1D curves constraining the collar on s1 surface
constraints2 (list of arrays) – 1D curves constraining the collar on s2 surface
toldist (float) – merging points tolerance
topology (string) – choice of collar mesh topology (overset or extruded) in case of difference assembly
 Returns
3D structured mesh
 Return type
array or pyTree
Example of use:
#  collarMesh (array)  import Converter as C import Geom as D import Transform as T import Generator as G s1 = D.sphere((0.,0.,0.),1,20) s2 = T.translate(s1,(1.2,0.,0.)); s2 = T.homothety(s2,(0,0,0),0.5) dhj = G.cart((0.,0.,0.),(1.e2,1,1),(21,1,1)) dhk = G.cart((0.,0.,0.),(1.e2,1,1),(11,1,1)) a = G.collarMesh(s1,s2, dhj,dhk,niterj=100,niterk=100,type='union') C.convertArrays2File(a,"out.plt")
#  collarMesh (pyTree) import Converter.PyTree as C import Geom.PyTree as D import Transform.PyTree as T import Generator.PyTree as G s1 = D.sphere((0.,0.,0.),1,20) s2 = T.translate(s1,(1.2,0.,0.)); s2 = T.homothety(s2,(0,0,0),0.5) dhj = G.cart((0.,0.,0.),(1.e2,1,1),(21,1,1)) dhk = G.cart((0.,0.,0.),(1.e2,1,1),(11,1,1)) a = G.collarMesh(s1,s2, dhj,dhk,niterj=100,niterk=100,type='union') C.convertPyTree2File(a,"out.cgns")
Cartesian grid generators

Generator.
gencartmb
(A, h, Dfar, nlvl) Simple Cartesian generator. Create a set of Cartesian grids (B) around a list of body grids (A). Those grids are patched with a ratio of 2. The user controls the number of levels, and the number of points for each level of grid. h is the spatial step on the finest level. Dfar is the maximal distance to the body. nlvl is a list that provides the number of points per level (nlvl[0]: finest grid), except for the finest level.
 Parameters
A (array/list of arrays or pyTree/list of pyTrees) – body grids
h (float) – spatial step in the finest level
Dfar (float) – maximal distance to the body A
nlvl (list of integers) – list of number of points per level (except the finest one)
 Returns
2D/3D structured mesh
 Return type
array or pyTree
Example of use:
#  gencartmb (array)  import Generator as G import Converter as C # body grid a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,30)) h = 1.e1# Step of finest Cartesian grid Dfar = 10.# Extension of far boundaries nlvl = [5,5,5] # Nb of points per level, except the 4th level (automatic) cartGrids = G.gencartmb([a], h, Dfar, nlvl) C.convertArrays2File(cartGrids, 'out.plt')
#  gencartmb (pyTree)  import Generator.PyTree as G import Converter.PyTree as C # body mesh a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,30)) h = 1.e1 # Step of finest Cartesian grid Dfar = 20. # Distance to far boundaries # Nb of points per level: # Here 4 levels, but last one is computed automatically nlvl = [10,10,5] # nlvl[0]: coarse grid t = C.newPyTree(['Bodies', 'CARTESIAN']); t[2][1][2].append(a) zones = G.gencartmb(t[2][1], h, Dfar, nlvl) t[2][2][2] += zones C.convertPyTree2File(t, 'out.cgns')

Generator.
octree
(surfs, snearList=[], dfarList=[], dfar=1., balancing=0, levelMax=1000, ratio=2, octant=None) Create a QUAD quadtree mesh in 2D or an HEXA octree mesh in 3D starting from a list of bodies and snears. Each parameter snear is the required spatial step of the octree near the corresponding body; the extension of the domaine can be provided by dfar, starting from the global bounding box of all surfaces defined by surfs. A list of extensions can be provided in dfarList, in order not to take into account a surface in the computation of the bounding box. It must be set to 1 for the surface that must not be taken into account. Parameter balancing=1 means that the octree is balanced, i.e. adjacent elements are at worst twice as big/small; levelMax is the maximum number of levels required. If ratio=2, then a classical octree mesh is built. If ratio=3, a 27tree mesh is built, in which case the spacing ratio is 3 (and not 2) between two adjacent elements. Parameter balancing enables to balance the octree; balancing=0 means no balancing; balancing=1 means a classical balancing, whereas balancing=2 takes also into account elements sharing a common vertex.
 Parameters
surfs (list of arrays/pyTrees) – body grids
snears (list of floats) – list of spatial step near the corresponding body
dfar (float) – maximal distance to the body grids
balancing (integer) – activation key for balanced octree (0, 1 or 2)
levelMax (integer) – maximum number of levels
ratio (integer) – spacing ratio between two adjacent elements
 Returns
2D/3D unstructured mesh
 Return type
array or pyTree
Example of use:
#  octree (array)  import Generator as G import Converter as C import Geom as D s = D.circle((0,0,0), 1., N=100); snear = 0.01 res = G.octree([s], [snear], dfar=5., balancing=2) C.convertArrays2File([res], 'out.plt')
#  octree (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D s = D.circle((0,0,0), 1., N=100); snear = 0.1 res = G.octree([s], [snear], dfar=5.) C.convertPyTree2File(res, 'out.cgns')

Generator.
octree2Struct
(octree, vmin=15, ext=0, optimized=1, merged=1, AMR=0, sizeMax=1000000) Convert an octree or a quadtree mesh into a set of Cartesian grids. Parameter ext is the extension of Cartesian grids in all the directions; vmin can be an integer defining the number of points in each Cartesian grid, or a list of integers, defining the number of points per refinement level. In that case, the first element of the list of vmin defines the finest level. Specifying all the levels is not mandatory. If optimized=1, the ext value is reduced by 1 at overlap borders for the coarsest grid for minimum overlapping. If merged=1, Cartesian grids are merged in order to reduce the number of created grids. If AMR=1, a set of AMR zones are generated. Parameter sizeMax can be used when merging is applied: in that case, the number of points per grid does not exceed sizeMax. Warning: to obtain multigrid blocks, optimized must be set to 0.
 Parameters
octree (array or pyTree) – input unstructured octree grid
vmin (integer or list of integers) – number of points in all Cartesian grids or list of number of points for each octree level
ext (integer) – extension of Cartesian grids (0 = no extension, N = extension of N cells in all direction)
optimized (integer) – activation key for optimization of coarsest grid (0 or 1)
merged (integer) – activation key for automatic merging of Cartesian grids
AMR (integer) – activation key for AMR generation (0 or 1)
sizeMax (integer) – maximum number of points in Cartesian grids after merging
 Returns
2D/3D structured mesh
 Return type
array or pyTree
Example of use:
#  octree2Struct (array)  import Generator as G import Converter as C import Geom as D s = D.circle((0,0,0), 1., N=100); snear = 0.1 res = G.octree([s],[snear], dfar=5., balancing=1) res = G.octree2Struct(res, vmin=5, ext=2, optimized=1) C.convertArrays2File([s]+res, "out.plt")
#  octree2Struct (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D s = D.circle((0,0,0), 1., N=100); snear = 0.1 res = G.octree([s],[snear], dfar=5., balancing=1) res = G.octree2Struct(res, vmin=5, ext=2,merged=1) C.convertPyTree2File(res, 'out.cgns')

Generator.
adaptOctree
(octree, indicator, balancing=1, ratio=2) Adapt an unstructured octree with respect to an indicator field located at element centers. If ‘indicator’ is strictly positive for an element, then the element must be refined as many times as required by the indicator number. If ‘indicator’ is strictly negative, the element is coarsened if possible as many times as required by the indicator number. If ‘indicator’ is 0., the element remains unchanged. balancing=1 means that the octree is balanced after adaptation. If ratio=2, then a classical octree mesh is built. If ratio=3, a 27tree mesh is built, in which case the spacing ratio is 3 (and not 2) between two adjacent elements. For array interface indicator is an array, for pyTree version, indicator is the name of field stored as a solution located at centers. Exists also as in place version (_adaptOctree) that modifies a and returns None.
 Parameters
octree (array or pyTree) – input unstructured octree grid
indicator (array or variable name in the pyTree) – field of values to indicate where to refine, coarsen or maintain the octree grid
balancing (integer) – activation key for balanced octree (0, 1 or 2, see the definition of octree function for the meaning)
ratio (integer) – spacing ratio between two adjacent elements
 Returns
modified reference copy of t
 Return type
same as input
Example of use:
#  adaptOctree (array)  import Generator as G import Converter as C import Geom as D s = D.circle((0,0,0), 1., N=100); snear = 0.1 o = G.octree([s], [snear], dfar=5., balancing=1) indic = C.node2Center(o) indic = C.initVars(indic, 'indicator', 1.) res = G.adaptOctree(o, indic) C.convertArrays2File([o,res], "out.plt")
#  adaptOctree (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D s = D.circle((0,0,0), 1., N=100); snear = 0.1 o = G.octree([s], [snear], dfar=5.,balancing=1) o = C.initVars(o, 'centers:indicator', 1.) res = G.adaptOctree(o) C.convertPyTree2File(res, 'out.cgns')

Generator.
expandLayer
(octree, level=0, corners=0, balancing=0) Expand the layer of given level for an octree unstructured mesh. If corners=1, expand also in corners directions. Exists also as in place version (_expandLayer) that modifies a and returns None.
 Parameters
octree (array or pyTree) – input unstructured octree grid
level (integer) – level to be expanded (level=0 is the finest)
corners (integer) – activation key for expansion in corners (0 or 1)
balancing (integer) – activation key for balanced octree (0, 1 or 2, see the definition of octree function for the meaning)
 Returns
modified reference copy of t
 Return type
same as input
Example of use:
#  expandLayer (array)  import Generator as G import Converter as C import Geom as D s = D.circle((0.,0.,0.), 1., N=100) o = G.octree([s], [0.1], dfar=1., balancing=1) o2 = G.expandLayer(o, level=0) C.convertArrays2File([o, o2], "out.plt")
#  expandLayer (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D s = D.circle((0.,0.,0.),1.,N=100) o = G.octree([s], [0.1], dfar=1., balancing=1) o2 = G.expandLayer(o, level=0) C.convertPyTree2File(o2, 'out.cgns')

Generator.PyTree.
cartRx
(X0, H, N, Nb, depth=0, addCellN=False, addBCMatch=False, rank=None, size=None) Create a set of regular cartesian grids. If depth > 0, an overlap of depth cells is added between grids. When used in parallel, the set of grids is distributed.
 Parameters
X0 (tuple of 3 floats) – first point coordinates
H (tuple of 3 floats) – steps of grids
N (tuple of 3 integers) – number of points in each direction for each block
Nb (tuple of 3 floats) – number of blocks in each direction
depth (integer) – number of overlap cells between cartesian grids
addCellN (boolean) – if True and depth > 0, add cellN field
addBCMatch (boolean) – if True and depth=0, create BCMatch
rank (integer) – current rank when running in parallel
size (integer) – current number of procs when running in parallel
 Returns
regular cartesian set of grids
 Return type
list of zones
Example of use:
#  cartRx (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartRx((0,0,0), (1,1,1), (30,30,30), (5,5,5), depth=0, addCellN=False) C.convertPyTree2File(a, 'out.cgns')

Generator.PyTree.
cartRx3
(XC0, XC1, HC, XF0, XF1, R, dim=3, rank=None, size=None) Create a set of regular and geometric cartesian grids with double steps. The mesh is made of a regular cartesian core and border grids are geometric cartesian grids. When used in parallel, the set of grids is distributed.
 Parameters
XC0 (tuple of 3 floats) – first point of cartesian core
XC1 (tuple of 3 floats) – last of of cartesian core
HC (tuple of 3 floats) – core cartesian steps
XF0 (tuple of 3 floats) – first point of geometric region
XF1 (tuple of 3 floats) – last point of geometric region
R (tuple of 3 floats) – geometric factor in each direction
dim (2 or 3) – space dimension
rank (integer) – current rank when running in parallel
size (integer) – current number of procs when running in parallel
 Returns
cartesian set of grids
 Return type
list of zones
Example of use:
#  cartRx3 (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cartRx3((0,0,0), (10,10,10), (0.1,0.1,0.1), (10,10,10), (30,20,20), (1.1,1.1,1.1)) C.convertPyTree2File(a, 'out.cgns')
Operations on meshes

Generator.
close
(a, tol=1.e12) Close a mesh defined by array a. Points that are distant of tol maximum to one another are merged.
Exists also as in place version (_close) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
tol (float) – merging points tolerance
 Returns
modified reference copy of t
 Return type
array or pyTree
Example of use:
#  close (array)  import Converter as C import Generator as G a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0.01, 10., (20,20,10)) a = C.convertArray2Tetra(a) a = G.close(a, 1.e3) C.convertArrays2File(a, 'out.plt')
#  close (pyTree)  import Converter.PyTree as C import Generator.PyTree as G a1 = G.cart((0,0,0), (1,1,1), (10,10,1)) a2 = G.cart((9+1.e2,0,0), (1,1,1), (10,10,1)) a3 = G.cart((0,5.01,0),(1,1,1),(19,6,1)) a4 = G.cart((0,9.0001,0),(1,1,1),(10,6,1)) a5 = G.cart((9.01,9.0002,0),(1,1,1),(10,6,1)) t = C.newPyTree(['Base',2,a1,a2,a3,a4,a5]) t = G.close(t, 1.e1) C.convertPyTree2File(t, 'out.cgns')

Generator.
selectInsideElts
(a, curves) Select elements of a TRIarray, whose centers are inside the given list of curves, defined by BARarrays.
 Parameters
a (array or pyTree) – input triangle 2D mesh
curves (array or list of arrays) – list of curves
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  selectInsideElts (array)  import Converter as C import Generator as G import Geom as D a = G.cart( (0,0,0), (1,1,1), (10,10,1)); a = C.convertArray2Tetra(a) b = D.circle( (5,5,0), 3.); b = C.convertArray2Tetra(b) a = G.selectInsideElts(a, [b]) C.convertArrays2File([a,b], 'out.plt')
#  selectInsideElts (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D a = G.cart((0,0,0), (1,1,1), (10,10,1)) a = C.convertArray2Tetra(a) b = D.circle((5,5,0), 3.) b = C.convertArray2Tetra(b) a = G.selectInsideElts(a, b) C.convertPyTree2File(a, 'out.cgns')

Generator.
map
(a, distrib, dir) Map a distribution on a curve or on a structured surface. Map a iarray distribution in a direction (dir=1,2,3) in a surface or volume mesh.
 Parameters
a (array or pyTree) – 1D/2D/3D structured mesh
distrib (array) – distribution of points
dir (integer) – direction i/j/k for the distribution (dir=1,2,3)
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  map (array)  import Geom as D import Generator as G import Converter as C # Map on a curve l = D.line( (0,0,0), (1,1,0) ) Ni = 10 d = G.cart( (0,0,0), (1./(Ni1),1.,1.), (Ni,1,1) ) m = G.map(l, d) C.convertArrays2File([m], "out1.plt") # Map on a structured surface ni = 2; nj = 3 a = G.cart((0,0,0), (1,1,1), (ni,nj,1)) C.setValue(a, (1,1,1), [1.,1.,2.]) C.setValue(a, (1,2,1), [1.,2.,5.]) C.setValue(a, (1,3,1), [1.,3.,2.]) C.setValue(a, (2,1,1), [2.,1.,2.]) C.setValue(a, (2,2,1), [2.,2.,5.]) C.setValue(a, (2,3,1), [2.,3.,2.]) b = D.bezier(a, 10, 10) Ni = 50; Nj = 30 d = G.cart( (0,0,0), (1./(Ni1),1./(Nj1),1.), (Ni,Nj,1) ) d = G.enforceX(d, 0.5, 0.01, (10,20)) d = G.enforceY(d, 0.5, 0.01, (10,20)) b = G.map(b, d) C.convertArrays2File(b, "out2.plt") # Map in a direction a = G.cylinder((0,0,0), 0.5, 2., 0, 60, 1., (20,20,1)) Ni = 10 d = G.cart( (0,0,0), (1./(Ni1),1.,1.), (Ni,1,1) ) d = G.enforcePlusX(d, 0.01, (10,20)) a = G.map(a, d, 2) C.convertArrays2File(a, "out3.plt")
#  map (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C l = D.line( (0,0,0), (1,1,0) ) Ni = 11; dist = G.cart( (0,0,0), (1./(Ni1),1.,1.), (Ni,1,1) ) l = G.map(l, dist) t = C.newPyTree(['Base',1,l]) C.convertPyTree2File(t, 'out.cgns')

Generator.
mapSplit
(a, distrib, splitCrit=100.) Split a iarray and map a distribution on the splitted iarray. SplitCrit is the curvature radius triggering split.
 Parameters
a (array or pyTree) – 1D/2D/3D structured mesh
distrib (array) – distribution of points
splitCrit (float) – curvature radius for array splitting
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  mapSplit (array)  import Generator as G import Converter as C import Geom as D # polyline a = D.polyline([(0,0,0),(1,0,0),(1,1,0),(2,3,0),(1.5,3,0),(1,1.5,0),(0,0,0)]) # distribution Ni = 41 dist = G.cart((0,0,0),(1./(Ni1),1,1),(Ni,1,1)) dist = G.enforceX(dist, 15.5/(Ni1), 0.005, 2,5) dist = G.enforceX(dist, 27.5/(Ni1), 0.005, 2,5) a = G.mapSplit(a,dist,0.25) C.convertArrays2File(a, 'out.plt')
#  mapSplit (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D # polyline a = D.polyline([(0,0,0),(1,0,0),(1,1,0),(2,3,0),(1.5,3,0),(1,1.5,0),(0,0,0)]) # distribution Ni = 41 dist = G.cart((0,0,0),(1./(Ni1),1,1),(Ni,1,1)) dist = G.enforceX(dist, 15.5/(Ni1), 0.005, 2,5) dist = G.enforceX(dist, 27.5/(Ni1), 0.005, 2,5) zones = G.mapSplit(a,dist,0.25) t = C.newPyTree(['Base',1]); t[2][1][2] += zones C.convertPyTree2File(t, 'out.cgns')

Generator.
refine
(a, power, dir) Refine a structured array. The original distribution is kept but the number of points is multiplied by power. Dir is the direction of refinement (1, 2, 3). If dir=0, refine in all directions.
Exists also as in place version (_refine) that modifies a and returns None.
 Parameters
a ([array] or [zone]) – 1D/2D/3D structured mesh
power (float) – multiplication factor of number of points
dir (integer) – direction i/j/k for the distribution (dir=0,1,2,3)
 Return type
Identical to a
Example of use:
#  refine (array)  import Generator as G import Converter as C a = G.cart( (0,0,0), (0.1,0.1,0.1), (20,20,1) ) a = G.refine(a, 1.5, 1) C.convertArrays2File([a], 'out.plt')
#  refine (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart( (0,0,0), (0.1,0.1,0.1), (20,20,1) ) a = G.refine(a, 1.5, 1) C.convertPyTree2File(a, 'out.cgns')

Generator.
mapCurvature
(a, N, power, dir) Map a structured array following the curvature. N is the final number of points. Dir is the direction of remeshing (1, 2, 3).
 Parameters
a ([array] or [zone]) – 1D/2D structured mesh
N (integer) – number of points after new distribution
power (float) – refinement factor
dir (integer) – direction i/j/k for the distribution (dir=1,2,3)
 Return type
Identical to a
Example of use:
#  mapCurvature (array)  import Generator as G import Converter as C import Geom as D ni = 2; nj = 3 a = G.cart((0,0,0), (1,1,1), (ni,nj,1)) C.setValue(a, (1,1,1), [1.,1.,2.]) C.setValue(a, (1,2,1), [1.,2.,4.]) C.setValue(a, (1,3,1), [1.,3.,2.]) C.setValue(a, (2,1,1), [2.,1.,2.]) C.setValue(a, (2,2,1), [2.,2.,5.]) C.setValue(a, (2,3,1), [2.,3.,2.]) b = D.bezier(a, density=10.) b = G.mapCurvature(b, N=100, power=0.5, dir=1) C.convertArrays2File([b], 'out.plt')
#  mapCurvature (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D ni = 2; nj = 3 a = G.cart((0,0,0), (1,1,1), (ni,nj,1)) C.setValue(a,'GridCoordinates', (1,1,1), [1.,1.,2.]) C.setValue(a,'GridCoordinates', (1,2,1), [1.,2.,5.]) C.setValue(a,'GridCoordinates', (1,3,1), [1.,3.,2.]) C.setValue(a,'GridCoordinates', (2,1,1), [2.,1.,2.]) C.setValue(a,'GridCoordinates', (2,2,1), [2.,2.,5.]) C.setValue(a,'GridCoordinates', (2,3,1), [2.,3.,2.]) b = D.bezier(a, density=10.) b = G.mapCurvature(b, N=100, power=0.5, dir=1) C.convertPyTree2File(b, 'out.cgns')

Generator.
densify
(a, h) Densify a iarray or a BARarray with a new discretization step h. Discretization points from the original array are kept.
Exists also as in place version (_densify) that modifies a and returns None.
 Parameters
a ([array] or [zone]) – 1D structured mesh
h (float) – new cell size step for the points densification
 Return type
Identical to a
Example of use:
#  densify (array)  import Generator as G import Converter as C import Geom as D a = D.circle((0,0,0), 1., 10) b = G.densify(a, 0.01) C.convertArrays2File(b, 'out.plt')
#  densify (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D a = D.circle((0,0,0), 1., 10) b = G.densify(a, 0.01) C.convertPyTree2File(b, 'out.cgns')

Generator.
grow
(a, vector) Grow a surface array of one layer. Vector is the node displacement. For the array version, vector is defined by an array. For the PyTree version, vector = [‘v1’,’v2’,’v3’] where variables ‘v1’, ‘v2’, ‘v3’ are defined as solutions in a, located at nodes.
 Parameters
a (array or Zone) – 2D surface mesh
vector (array or list of 3 variables contained in the solution) – vector of node displacement
 Returns
new 3D structured mesh
 Return type
array or Zone
Example of use:
#  grow (array)  import Converter as C import Generator as G import Geom as D a = D.sphere( (0,0,0), 1., 50 ) n = G.getNormalMap(a) n = C.center2Node(n); n[1] = n[1]*100. b = G.grow(a, n) C.convertArrays2File([b], 'out.plt')
#  grow (pyTree) import Converter.PyTree as C import Converter.Internal as Internal import Generator.PyTree as G import Geom.PyTree as D a = D.sphere((0,0,0), 1., 50) a = G.getNormalMap(a) a = C.center2Node(a, Internal.__FlowSolutionCenters__) a = C.rmVars(a, Internal.__FlowSolutionCenters__) b = G.grow(a, ['sx','sy','sz']) t = C.newPyTree(['Base1',2,'Base2',3]) t[2][1][2].append(a); t[2][2][2].append(b) C.convertPyTree2File(t, 'out.cgns')

Generator.
stack
(a, b=None) Stack two 2D structured meshes or a list of structured meshes (with the same nixnj) into a single 3D mesh.
 Parameters
a (array, Zone or list of arrays, zones) – a 2D structured mesh or a list of structured meshes
b (array or Zone) – 2D structured mesh or None
 Returns
new 3D structured mesh
 Return type
array or Zone
Example of use:
#  stack (array)  import Generator as G import Converter as C import Transform as T import Geom as D # Concatenate 2 structured grids a = G.cylinder((0,0,0), 1, 1.3, 360, 0, 1., (50,10,1)) b = T.rotate(a, (0,0,0), (1,0,0), 5.) b = T.translate(b, (0,0,0.5)) c = G.stack(a, b) # Concatenate a list of structured grids a = [] for i in range(10): a.append(D.circle((0,0,i), 1.)) c = G.stack(a) C.convertArrays2File(c, 'out.plt')
#  stack (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Transform.PyTree as T a = G.cylinder((0,0,0), 1, 1.3, 360, 0, 1., (50,10,1)) b = T.rotate(a, (0,0,0), (1,0,0), 5.) b = T.translate(b, (0,0,0.5)) c = G.stack(a, b) C.convertPyTree2File(c, 'out.cgns')

Generator.
addNormalLayers
(a, d, check=0, niter=0) Normal extrusion from a surface mesh. d is a 1D distribution providing the height of each layer. If check=1, the extrusion stops before negative volume cells are created. Niter specifies the number of iterations for normals smoothing.
 Parameters
a (array or pyTree) – 2D surface mesh
d (1D array) – distribution of normal extrusion
check (integer) – activation key for negative volume criteria (0 or 1)
niter (integer) – number of iterations for normals smoothing
 Returns
new 3D structured mesh
 Return type
array or pyTree
Example of use:
#  addNormalLayers (array)  import Generator as G import Converter as C import Geom as D d = C.array('d', 3, 1, 1) d[1][0,0] = 0.1; d[1][0,1] = 0.2; d[1][0,2] = 0.3 a = D.sphere( (0,0,0), 1, 50 ) a = G.addNormalLayers(a, d) C.convertArrays2File([a], 'out.plt')
#  addNormalLayers (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D d = G.cart((0.,0.,0.), (0.1,1,1),(3,1,1)) a = D.sphere((0,0,0), 1, 50) b = G.addNormalLayers(a, d) C.convertPyTree2File(b, 'out.cgns')

Generator.
TTM
(a, niter=100) Smooth a mesh using elliptic generator.
 Parameters
a (array or pyTree) – 2D structured mesh
niter (integer) – number of smoothing iterations
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  TTM (array)  import Converter as C import Generator as G import Geom as D P0 = (0,0,0); P1 = (5,0,0); P2 = (0,7,0); P3 = (5,7,0) # Geometry d1 = D.line(P0, P1); d2 = D.line(P2, P3) pts = C.array('x,y,z', 5, 1, 1) x = pts[1][0]; y = pts[1][1]; z = pts[1][2] x[0] = 0. ; y[0] = 0.; z[0] = 0. x[1] =2. ; y[ 1 ] = 2.; z[1] = 0. x[2] =3. ; y[ 2 ] = 3.; z[2] = 0. x[3] = 2. ; y[ 3 ] = 5.; z[3] = 0. x[4] = 0. ; y[ 4 ] = 7.; z[4] = 0. b1 = D.bezier(pts) x[0] = 5.; y[ 0 ] = 0.; z[ 0 ] = 0. x[1] = 3.; y[ 1 ] = 2.; z[ 1 ] = 0. x[2] = 2.; y[ 2 ] = 3.; z[ 2 ] = 0. x[3] = 6.; y[ 3 ] = 5.; z[ 3 ] = 0. x[4] = 5.; y[ 4 ] = 7.; z[ 4 ] = 0. b2 = D.bezier( pts ) C.convertArrays2File([d1, d2, b1, b2], 'geom.plt') # Regular discretision of each line Ni = 20; Nj = 10 r = G.cart((0,0,0), (1./(Ni1),1,1), (Ni,1,1)) q = G.cart((0,0,0), (1./(Nj1),1,1), (Nj,1,1)) r1 = G.map(d1, r) r2 = G.map(d2, r) r3 = G.map(b1, q) r4 = G.map(b2, q) # TTM m = G.TFI([r1, r2, r3, r4]) m2 = G.TTM(m, 2000) C.convertArrays2File([m,m2], 'out.plt')
#  TTM (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D P0 = (0,0,0); P1 = (5,0,0); P2 = (0,7,0); P3 = (5,7,0) # Geometry d1 = D.line(P0,P1); d2 = D.line(P2,P3) d3 = D.line(P0,P2); d4 = D.line(P1,P3) # Regular discretisation of each line Ni = 20; Nj = 10 r = G.cart((0,0,0), (1./(Ni1),1,1), (Ni,1,1)) q = G.cart((0,0,0), (1./(Nj1),1,1), (Nj,1,1)) r1 = G.map(d1, r); r2 = G.map(d2, r) r3 = G.map(d3, q); r4 = G.map(d4, q) # TTM m = G.TFI([r1, r2, r3, r4]) m = G.TTM(m) t = C.newPyTree(['Base',2]); t[2][1][2].append(m) C.convertPyTree2File(t, 'out.cgns')

Generator.
snapFront
(a, S, optimized=1) Snap a mesh to a surface S. A front must be defined in a by a cellN field. Points of this front are snapped to the surface. If optimized=0, the exterior front cellN=1 is snapped, else if optimized=1 optimized front cellN=1 is snapped, else if optimized=2, front cellN=0 is snapped.
Exists also as in place version (_snapFront) that modifies a and returns None.
 Parameters
a (array or pyTree) – 3D mesh
S (list of zones) – surface mesh
optimized (integer) – optimization key (0,1,2)
 Returns
new unstructured mesh
 Return type
array or pyTree
Example of use:
#  snapFront (array)  import Generator as G import Converter as C import Geom as D import Connector as X import Transform as T s = D.circle((0,0,0), 1., N=100) s = T.addkplane(s) # Grille cartesienne (reguliere) BB = G.bbox([s]) ni = 100; nj = 100; nk = 3 xmin = BB[0]; ymin = BB[1]; zmin = BB[2]0.5 xmax = BB[3]; ymax = BB[4]; zmax = BB[5]+0.5 hi = (xmaxxmin)/(ni1); hj = (ymaxymin)/(nj1) h = min(hi, hj) ni = int((xmaxxmin)/h)+7; nj = int((ymaxymin)/h)+7 b = G.cart((xmin3*h, ymin3*h, zmin), (h, h, 1.), (ni,nj,nk)) celln = C.array('cellN', ni, nj, nk) celln = C.initVars(celln, 'cellN', 1.) # Masquage cellno = X.blankCells([b], [celln], [s], blankingType=0, delta=0., dim=2) a = C.initVars(s, 'cellN', 1) b = C.addVars([b, cellno[0]]) # Adapte le front de la grille a la surface b = T.subzone(b, (1,1,2), (b[2],b[3],2)) b = G.snapFront(b, [s]) C.convertArrays2File([a,b], 'out.plt')
#  snapFront (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D import Connector.PyTree as X import Transform.PyTree as T import Converter.Internal as Internal s = D.circle((0,0,0), 1., N=100) s2 = T.addkplane(s) # Grille cartesienne (reguliere) BB = G.bbox([s]) ni = 100; nj = 100; nk = 3 xmin = BB[0]; ymin = BB[1]; zmin = BB[2]0.5 xmax = BB[3]; ymax = BB[4]; zmax = BB[5]+0.5 hi = (xmaxxmin)/(ni1); hj = (ymaxymin)/(nj1) h = min(hi, hj) ni = int((xmaxxmin)/h)+7; nj = int((ymaxymin)/h)+7 b = G.cart( (xmin3*h, ymin3*h, zmin), (h, h, 1.), (ni,nj,nk) ) t = C.newPyTree(['Cart']) t[2][1][2].append(b) # Masquage t = C.initVars(t,'cellN',1) import numpy BM = numpy.array([[1]]) t = X.blankCells(t,[[s2]],BM,blankingType='node_in',dim=2) # Adapte le front de la grille a la surface dim = Internal.getZoneDim(b) t = T.subzone(t, (1,1,2), (dim[1],dim[2],2)) t = G.snapFront(t, [s2]) t = C.addBase2PyTree(t, 'Surface', cellDim=2) s2 = C.initVars(s2,'cellN',1) t[2][2][2].append(s2) C.convertPyTree2File(t, 'out.cgns')

Generator.
snapSharpEdges
(a, S, step=None, angle=30.) Snap a mesh to a surface S, constrained by sharp edges and corners. if step != None, sharp edges are refined with this step. Sharp Edges are calculated depending on angle.
Exists also as in place version (_snapSharpEdges) that modifies a and returns None.
 Parameters
a (array or pyTree) – mesh to be deformed
S (list of zones) – surface mesh
step (float) – step for sharp edges refinement
angle (float) – angle (in degrees) for sharp edges detection
 Returns
new unstructured mesh
 Return type
array or pyTree
Example of use:
#  snapSharpEdges (array)  import Generator as G import Converter as C import Post as P import Geom as D # Enforce polyline define by s in b s = D.polyline([(0.2,0,0),(1,1,0),(2.5,1,0),(0.2,0,0)]) s = C.initVars(s, 'indic', 0) h = 0.1 ni = 30; nj = 20; nk=1 b = G.cartHexa((0.5, 0.5, 0), (h, h, 1.), (ni,nj,nk)) b = C.initVars(b, 'indic', 0) b = G.snapSharpEdges(b, [s], h) c = C.converter.convertQuad2Tri(b) C.convertArrays2File([b,c, s], 'out.plt') # Same with smooth #c = T.smooth(c, eps=0.5, niter=5, # fixedConstraints=s) # #projConstraints=s)C # Enforce all constraints (must be overrefined) s = D.circle((0,0,0), R=1, N=400) s = C.initVars(s, 'indic', 0) h = 0.3 ni = 10; nj = 20; nk=1 b = G.cartHexa((1.5, 1.5, 0), (h, h, 1.), (ni,nj,nk)) b = C.initVars(b, 'indic', 0) b = G.snapSharpEdges(b, [s], 0.1*h) c = C.converter.convertQuad2Tri(b) C.convertArrays2File([b,c,s], 'out.plt') import sys; sys.exit() # Idem external h = 0.3 ni = 10; nj = 10; nk=1 s = G.cartHexa((1.6,1.6,0), (h/2,h/2,1.), (2*ni+2,2*nj+2,nk)) s = P.exteriorFaces(s) s = C.initVars(s, 'indic', 0) b = G.cartHexa((1.5, 1.5, 0), (h, h, 1.), (ni,nj,nk)) b = C.initVars(b, 'indic', 0) b = G.snapSharpEdges(b, [s], h*0.1) C.convertArrays2File([b,s], 'out.plt')
#  snapSharpEdges (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D # polylignes avec angles vifs s = D.polyline([(0.02,0,0),(1,1,0),(2,1,0),(0.02,0,0)]) # Grille cartesienne (reguliere) h = 0.1 ni = 30; nj = 20; nk=1 b = G.cart((0.5, 0.5, 0), (h, h, 1.), (ni,nj,nk)) b = G.snapSharpEdges(b, [s], h) t = C.newPyTree(['Cart','Surface']) t[2][1][2].append(b); t[2][2][2].append(s) C.convertPyTree2File(t, 'out.cgns')
Operation on surface meshes

Generator.
fittingPlaster
(a, bumpFactor=0.) Fit a surface structured patch to a curve a. BumpFactor controls the curvature of the patch.
 Parameters
a (array) – curve to deform the structured patch
bumpFactor (float) – amplitude of the bump
 Returns
new structured mesh
 Return type
array or pyTree
Example of use:
#  fittingPlaster (array)  import Generator as G import Converter as C import Geom as D a = D.circle( (0,0,0), 1, N=50 ) a = C.convertArray2Tetra(a) a = G.close(a) b = G.fittingPlaster(a, bumpFactor=0.5) C.convertArrays2File([a,b], 'out.plt')
#  fittingPlaster (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D a = D.circle( (0,0,0), 1, N=50 ) a = C.convertArray2Tetra(a) a = G.close(a) b = G.fittingPlaster(a, bumpFactor=0.5) C.convertPyTree2File(b, 'out.cgns')

Generator.
gapfixer
(a, c, hardPoints=None, refine=1) Fill a gap defined by a BAR contour a drawn on a surface c. You can force the generated mesh to pass through hardPoints (NODES). If refine=0, no inside points are added.
 Parameters
a (BAR array) – contour of the gap
c (array) – surface to be filled
hardPoints (array or list of arrays) – mesh containing nodes to be enforced
refine (integer) – activation key for including points in the gap mesh (0 or 1)
 Returns
new surface mesh
 Return type
array or pyTree
Example of use:
#  gapfixer (array)  import Generator as G import Converter as C import Geom as D # Fix the gap inside a circle drawn on a plane a = D.circle((0,0,0), 1, N=100) a = C.convertArray2Tetra(a); a = G.close(a) b = G.cart((2.,2.,0.), (0.1,0.1,1.), (50,50,1)) a1 = G.gapfixer(a, b) C.convertArrays2File(a1, 'out.plt') # Fill the gap in the circle, using one defined point hp = D.point((0.5, 0.5, 0.)) a2 = G.gapfixer(a, b, hp, refine=0) C.convertArrays2File(a2, 'outHP.plt')
#  gapfixer (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D # Fix the gap inside a circle drawn on a plane a = D.circle((0,0,0), 1, N=100) a = C.convertArray2Tetra(a); a = G.close(a) b = G.cart((2.,2.,0.), (0.1,0.1,1.), (50,50,1)) a1 = G.gapfixer(a, b) C.convertPyTree2File(a1, 'out.cgns') # Fill the gap in the circle, using one defined point hp = D.point((0.5, 0.5, 0.)) a2 = G.gapfixer(a, b, hp, refine=0) C.convertPyTree2File(a2, 'outHP.cgns')

Generator.
gapsmanager
(A, mode=0, coplanar=0) Fill multiple gaps in a set of surface components A. Also, eliminate overlap regions between components if any. Normals for all patches must be pointed outwards. Set mode=0 for nodal mesh, 1 for center mesh, and 2 otherwise. Set coplanar=1 if all components are lying on a same plane.
 Parameters
A (array or pyTree) – surface mesh with gaps
mode (integer) – key for grid location (0 = nodes, 1 = centers, 2 = others)
coplanar (integer) – activation key for coplanar components of A (0 or 1)
 Returns
new surface mesh
 Return type
array or pyTree
Example of use:
#  gapsmanager (array)  import Geom as D import Converter as C import Generator as G a = D.sphere6((0,0,0), 1, N=10) a = C.node2Center(a) a = C.convertArray2Tetra(a) b = G.gapsmanager(a, mode=2) C.convertArrays2File(b, 'out.plt')
#  gapsmanager (pyTree)  import Geom.PyTree as D import Converter.PyTree as C import Generator.PyTree as G a = D.sphere6((0,0,0), 1, N=10) a = C.node2Center(a) a = C.convertArray2Tetra(a) b = G.gapsmanager(a, mode=2) C.convertPyTree2File(b, 'out.cgns')

Generator.
mmgs
(A, ridgeAngle=45., hmin=0., hmax=0., hausd=0.01, grow=1.1, anisotropy=0, optim=0, fixedConstraints=[], sizeConstraints=[]) Refine a TRI surface mesh using MMGs.
 Parameters
A ([array, list of arrays] or [zone, pyTree]) – surface TRI mesh
ridgeAngle (double) – Angle between adjacent cells that MMGs consider to be a ridge (degrees)
hmin (double) – the minimum mesh step in final mesh
hmax (double) – the maximum mesh step in final mesh
hausd (double) – the maximum chordal deviation in final mesh from initial mesh
grow (double) – the maximum difference of steps between two adjacent cells
optim (int) – if 1, only optimize mesh keeping the same number of points
fixedConstraints ([list of arrays] or [list of zones]) – curves or surface identifying points that must be in output mesh
sizeConstraints ([list of arrays] or [list of zones]) – curves or surface defining sizemap
 Returns
remeshed surface
 Return type
identical to input
Example of use:
#  mmgs (array)  import Geom as D import Generator as G import Converter as C a = D.sphere6( (0,0,0), 1., N=20, ntype='TRI' ) # Optimisation b = G.mmgs(a, optim=1) C.convertArrays2File(b, 'out.plt') # Remaillage avec parametres b = G.mmgs(a, hausd=0.01, hmax=0.1) C.convertArrays2File(b, 'out.plt') # Raffinement avec sizemap a = C.initVars(a, 'sizemap=0.2*abs({x})+0.05') b = G.mmgs(a, hausd=10.) C.convertArrays2File(b, 'out.plt')
#  mmgs (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C a = D.sphere6( (0,0,0), 1., N=20, ntype='TRI' ) # Optimisation b = G.mmgs(a, optim=1) C.convertPyTree2File(b, 'out1.cgns') # Remaillage avec parametres b = G.mmgs(a, hausd=0.01, hmax=0.1) C.convertPyTree2File(b, 'out2.cgns') # Raffinement avec sizemap a = C.initVars(a, '{sizemap}=0.2*abs({CoordinateX})+0.05') b = G.mmgs(a, hausd=10.) C.convertPyTree2File(b, 'out3.cgns')
Information on generated meshes

Generator.
barycenter
(a, weight=None) Return the barycenter of a, with optional weight.
 Parameters
a (array or pyTree) – input mesh
weight (string) – name of the weight variable in a
 Returns
coordinates of the barycenter
 Return type
3list of floats
Example of use:
#  barycenter (array)  import Generator as G import Converter as C a = G.cart((0.,0.,0.), (0.1,0.1,1.), (20,20,20)) print(G.barycenter(a)) #>> [0.9500000000000001, 0.9500000000000005, 9.5] w = C.initVars(a, 'weight', 1.); w = C.extractVars(w,['weight']) print(G.barycenter(a, w)) #>> [0.9500000000000001, 0.9500000000000005, 9.5]
#  barycenter (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0.,0.,0.), (0.1,0.1,1.), (20,20,20)) print(G.barycenter(a)) #>> [0.9500000000000001, 0.9500000000000005, 9.5] a = C.initVars(a, 'weight', 1.) print(G.barycenter(a, 'weight')) #>> [0.9500000000000001, 0.9500000000000005, 9.5]

Generator.
bbox
(a) Return the bounding box [xmin, ymin, zmin, xmax, ymax, zmax] of a.
 Parameters
a (array or pyTree) – input mesh
 Returns
coordinates of the bounding box
 Return type
6list of floats
Example of use:
#  bbox (array)  import Generator as G a = G.cart((0.,0.,0.),(0.1,0.1,1.),(20,20,20)) b = G.cart((12.,0.,0.),(0.1,0.1,1.),(20,20,20)) print(G.bbox(a)) print(G.bbox([a, b]))
#  bbox (pyTree)  import Generator.PyTree as G a = G.cart((0.,0.,0.),(0.1,0.1,1.),(20,20,20)) print(G.bbox(a))

Generator.
bboxOfCells
(a) Return the bounding box of each cell of a. The bounding box field is located at centers of cells.
Exists also as in place version (_bboxOfCells) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  bboxOfCells (array)  import Generator as G a = G.cart((0.,0.,0.),(0.1,0.1,1.),(20,20,20)) b = G.bboxOfCells(a) print(b)
#  bboxOfCells (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0.,0.,0.),(0.1,0.1,1.),(20,20,20)) a = G.bboxOfCells(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
BB
(a, method='AABB', weighting=0, tol=0.) Return the bounding box of a as an array or a zone. If method is ‘AABB’, then it computes the AxisAligned BoundingBox, if method is ‘OBB’ then it computes the Oriented BoundingBox. The argument weighting may be 0, and the OBB is computed using a CloudPoint approach, or 1, and it is computed using a SurfaceWeighting approach. If weighting=1, then the provided array must be a surface composed of triangles.
Exists also as in place version (_BB) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
method (string) – choice between axisaligned or oriented bounding box
weighting (integer) – activation key for surface weighting approach
tol (float) – extension of bounding box in all the directions
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  BB (array)  import Generator as G import Converter as C import Geom as D s = D.circle((0,0,0), 1., N=100) a = G.BB(s) C.convertArrays2File([a,s], 'out.plt')
#  BB (pyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D s = D.circle((0,0,0), 1., N=100) a = G.BB(s); a[0] = 'bbox' C.convertPyTree2File([s,a], 'out.cgns')

Generator.
CEBBIntersection
(a1, a2, tol=1.e10) Test the Cartesian Elements Bounding Box (CEBB) intersection between a1 and a2. Tolerance is a float given by tol. Return 0 if no intersection, 1 otherwise.
 Parameters
a1 (array or pyTree) – input mesh
a2 (array or pyTree) – input mesh
tol (float) – tolerance of intersection
 Returns
0 if no intersection, 1 otherwise
 Return type
integer
Example of use:
#  CEBBIntersection (array)  import Generator as G import Transform as T ni = 11; nj = 3; nk = 11 a1 = G.cart((0.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = G.cart((1.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = T.rotate(a2, (0,0,0), (0,0,1), 12.) print(G.CEBBIntersection(a1, a2))
#  CEBBIntersection (pyTree) import Generator.PyTree as G import Transform.PyTree as T ni = 11; nj = 3; nk = 11 a1 = G.cart((0.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = G.cart((1.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = T.rotate(a2, (0,0,0), (0,0,1), 12.) print(G.CEBBIntersection(a1, a2))

Generator.
bboxIntersection
(a1, a2, tol=1.e6, isBB=False, method='AABB') Test if a1 and a2 intersects. Three options are available: method=’AABB’ (intersection between two AxisAligned Bounding Boxes, by default); method=’OBB’ (intersection between two Oriented Bounding Boxes, the most general case); method=’AABBOBB’ (intersection between an AABB a1 and an OBB a2).; If a1 and a2 are directly the corresponding bounding boxes, the user may switch isBB=True in order to avoid recalculating them. Return 0 if no intersection, 1 otherwise.
Exists also as in place version (_bboxIntersection) that modifies a1 and returns None.
 Parameters
a1 (array or pyTree) – input mesh
a2 (array or pyTree) – input mesh
tol (float) – tolerance of intersection
isBB (boolean) – activation key if meshes already are bounding boxes
method (string) – intersection method
 Returns
0 if no intersection, 1 otherwise
 Return type
integer
Example of use:
#  bboxIntersection (array)  import Generator as G ni = 11; nj = 3; nk = 11 a1 = G.cart((0.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = G.cart((0.5,0.05,0.01), (0.1,0.1,0.2),(ni, nj,nk)) intersect = G.bboxIntersection(a1,a2); print(intersect)
#  bboxIntersection (pyTree)  import Generator.PyTree as G ni = 11; nj = 3; nk = 11 a1 = G.cart((0.,0.,0.), (0.1,0.1,0.2),(ni, nj,nk)) a2 = G.cart((0.5,0.05,0.01), (0.1,0.1,0.2),(ni, nj,nk)) intersect = G.bboxIntersection(a1, a2); print(intersect)

Generator.
checkPointInCEBB
(a, (x, y, z)) Test if a given point is in the CEBB of a.
 Parameters
a (array or pyTree) – input mesh
(x,y,z) (3tuple of floats) – coordinates of point
 Returns
0 if point is not in the CEBB of a, 1 otherwise
 Return type
integer
Example of use:
#  checkPointInCEBB (array)  import Generator as G import Transform as T Ni = 20; Nj = 20 a1 = G.cart((0,0,0),(1./Ni,0.5/Nj,1),(Ni,Nj,2)) a2 = G.cart((0.1,0,0),(0.5/Ni, 0.5/Nj, 1), (Ni,Nj,2)) a2 = T.rotate(a2, (0.1,0,0), (0,0,1), 0.22) # Check if point is in CEBB of mesh2 val = G.checkPointInCEBB(a2, (0.04839, 0.03873, 0.5)); print(val)
#  checkPointInCEBB (pyTree)  import Generator.PyTree as G import Transform.PyTree as T Ni = 20; Nj = 20 a2 = G.cart((0.1,0,0),(0.5/Ni, 0.5/Nj, 1), (Ni,Nj,2)) a2 = T.rotate(a2, (0.1,0,0), (0,0,1), 0.22) # Check if point is in CEBB of a2 val = G.checkPointInCEBB(a2, (0.04839, 0.03873, 0.5)); print(val)

Generator.
getVolumeMap
(a) Return the volume field of an array. Volume is located at centers of cells.
Exists also as in place version (_getVolumeMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input volume or surface mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getVolumeMap (array)  import Generator as G import Converter as C a = G.cart((0.,0.,0.), (0.1,0.1,0.2), (10,10,3)) vol = G.getVolumeMap(a) vol = C.center2Node(vol); vol = C.addVars([a, vol]) C.convertArrays2File(vol, "out.plt")
#  getVolumeMap (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0.,0.,0.), (0.1,0.1,0.2), (10,10,3)) a = G.getVolumeMap(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
getNormalMap
(a) Return the surface normals field of a surface array. It is located at centers of cells.
Exists also as in place version (_getNormalMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getNormalMap (array)  import Geom as D import Generator as G import Converter as C # 2D structured a = D.sphere((0,0,0), 1, 50) n = G.getNormalMap(a) n = C.center2Node(n);n = C.addVars([a, n]) C.convertArrays2File([n], 'out1.plt') # 2D unstructured a = D.sphere((0,0,0), 1, 50) a = C.convertArray2Tetra(a) n = G.getNormalMap(a) n = C.center2Node(n);n = C.addVars([a, n]) C.convertArrays2File([n], 'out2.plt')
#  getNormalMap (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C a = D.sphere((0,0,0), 1, 50) a = G.getNormalMap(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
getSmoothNormalMap
(a, niter=2, eps=0.4) Return the smoothed surface normals field of a surface array, located at nodes. niter is the number of smoothing operations, and eps is a smoothing weight.
Exists also as in place version (_getSmoothNormalMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface mesh
niter (integer) – smoothing iterations number
eps (float) – smoothing weight
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getSmoothNormalMap (array)  import Converter as C import Generator as G import Transform as T a = G.cart((0.,0.,0.),(1.,1.,1.),(10,10,1)) b = G.cart((0.,0.,0.),(1.,1.,1.),(1,10,10)) b = T.rotate(b,(0.,0.,0.),(0.,1.,0.),45.) c = C.convertArray2Hexa([a,b]) c = T.join(c); c = T.reorder(c,(1,)) c = T.rotate(c,(0.,0.,0.),(0.,1.,0.),15.) s = G.getSmoothNormalMap(c, niter=4) c = C.addVars([c,s]) C.convertArrays2File(c, "out.plt")
#  getSmoothNormalMap (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Transform.PyTree as T a = G.cart((0.,0.,0.),(1.,1.,1.),(10,10,1)) b = G.cart((0.,0.,0.),(1.,1.,1.),(1,10,10)) b = T.rotate(b,(0.,0.,0.),(0.,1.,0.),45.) c = C.convertArray2Hexa([a,b]) c = T.join(c); c = T.reorder(c,(1,)) c = T.rotate(c,(0.,0.,0.),(0.,1.,0.),15.) c = G.getSmoothNormalMap(c,niter=4) C.convertPyTree2File(c, "out.cgns")

Generator.
getOrthogonalityMap
(a) Return the orthogonality map of an array. The orthogonality map corresponds to the maximum deviation of all dihedral angles of an element. The orthogonality map is expressed in degree and located at centers.
Exists also as in place version (_getOrthogonalityMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getOrthogonalityMap (array)  import Generator as G import Converter as C a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,10)) ac = C.node2Center(a) ortho = G.getOrthogonalityMap(a) ortho = C.addVars([ac, ortho]) C.convertArrays2File([ortho], "out.plt")
#  getOrthogonalityMap (pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,10)) a = G.getOrthogonalityMap(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
getRegularityMap
(a) Return the regularity map of an array. The regularity map corresponds to the maximum deviation of the volume ratio of an element and all its neigbouring cells. The regularity map is located at centers.
Exists also as in place version (_getRegularityMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getRegularityMap (array)  import Generator as G import Converter as C a = G.cart( (0,0,0), (1,1,1), (50,50,1)) a = G.enforceX(a, 25, 0.1, 10, 10) ac = C.node2Center(a) reg = G.getRegularityMap(a) reg = C.addVars([ac, reg]) C.convertArrays2File([reg], "out.plt")
#  getRegularityMapPT (array)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0,0,0), (1,1,1), (50,50,1)) a = G.enforceX(a, 25, 0.1, 10, 10) a = G.getRegularityMap(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
getTriQualityMap
(a) Return the quality map of a TRI array. The triangle quality is a value between 0. (degenerated triangle) and 1. (equilateral triangle). The quality map is located at centers.
Exists also as in place version (_getTriQualityMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface TRI mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getTriQualitylityMap (array)  import Generator as G import Converter as C import Geom as D a = D.sphere( (0,0,0), 1, N=10 ) a = C.convertArray2Tetra(a); a = G.close(a) n = G.getTriQualityMap(a) n = C.center2Node(n); n = C.addVars([a, n]) C.convertArrays2File([n], "out.plt")
#  getTriQualitylityMap (PyTree)  import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D a = D.sphere((0,0,0), 1, N=10) a = C.convertArray2Tetra(a) a = G.close(a) t = C.newPyTree(['Base',2,a]) t = G.getTriQualityMap(t) C.convertPyTree2File(t, 'out.cgns')

Generator.
getCellPlanarity
(a) Return a measure of cell planarity for each cell. It is located at centers of cells.
Exists also as in place version (_getCellPlanarity) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getCellPlanarity (array)  import Converter as C import Generator as G import Geom as D a = D.sphere( (0,0,0), 1., 10) p = G.getCellPlanarity(a) p = C.center2Node(p); a = C.addVars([a, p]) C.convertArrays2File([a], 'out.plt')
#  getCellPlanarity (pyTree)  import Converter.PyTree as C import Generator.PyTree as G import Geom.PyTree as D a = D.sphere((0,0,0), 1., 10) a = G.getCellPlanarity(a) C.convertPyTree2File(a, 'out.cgns')

Generator.
getCircumCircleMap
(a) Return the map of circum circle radius of any cell of a ‘TRI’ array.
Exists also as in place version (_getCircumCircleMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getCircumCircleMap (array)  import Geom as D import Generator as G import Converter as C a = D.sphere((0,0,0), 1, 50) a = C.convertArray2Tetra(a) n = G.getCircumCircleMap(a) n = C.center2Node(n); n = C.addVars([a, n]) C.convertArrays2File([n], "out.plt")
#  getCircumCircleMap (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C a = D.sphere((0,0,0), 1, 50) a = C.convertArray2Tetra(a) t = C.newPyTree(['Base',2,a]) t = G.getCircumCircleMap(t) C.convertPyTree2File(t, 'out.cgns')

Generator.
getInCircleMap
(a) Return the map of inscribed circle radius of any cell of a ‘TRI’ array.
Exists also as in place version (_getInCircleMap) that modifies a and returns None.
 Parameters
a (array or pyTree) – input surface mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getInCircleMap (array)  import Geom as D import Generator as G import Converter as C a = D.sphere((0,0,0), 1, 50) a = C.convertArray2Tetra(a) n = G.getInCircleMap(a) n = C.center2Node(n); n = C.addVars([a, n]) C.convertArrays2File([n], "out.plt")
#  getInCircleMap (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C a = D.sphere((0,0,0), 1, 50) a = C.convertArray2Tetra(a) t = C.newPyTree(['Base',2,a]) t = G.getInCircleMap(t) C.convertPyTree2File(t, 'out.cgns')

Generator.
getEdgeRatio
(a) Return the ratio between the longest and the smallest edges of a cell.
Exists also as in place version (_getEdgeRatio) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getEdgeRatio(array)  import Generator as G import Converter as C a = G.cart((0.,0.,0.), (0.1,0.1,0.1), (11,11,11)) a = G.enforcePlusX(a,1e6,(5,50)) r = G.getEdgeRatio(a) r = C.center2Node(r); r = C.addVars([a,r]) C.convertArrays2File([r], "out.plt")
#  getEdgeRatio(pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0.,0.,0.), (0.1,0.1,0.1), (11,11,11)) a = G.enforcePlusX(a,1e6,(5,50)) a = G.getEdgeRatio(a) C.convertPyTree2File(a, "out.cgns")

Generator.
getMaxLength
(a) Return the length of the longer edge of each cell.
Exists also as in place version (_getMaxLength) that modifies a and returns None.
 Parameters
a (array or pyTree) – input mesh
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  getMaxLength(array)  import Generator as G import Converter as C a = G.cart((0.,0.,0.), (0.1,0.1,0.1), (11,11,11)) a = G.enforcePlusX(a,1e6,(5,50)) r = G.getMaxLength(a) r = C.center2Node(r); r = C.addVars([a,r]) C.convertArrays2File([r], "out.plt")
#  getMaxLength(pyTree)  import Generator.PyTree as G import Converter.PyTree as C a = G.cart((0.,0.,0.), (0.1,0.1,0.1), (11,11,11)) a = G.enforcePlusX(a,1e6,(5,50)) a = G.getMaxLength(a) C.convertPyTree2File(a, "out.cgns")
Operations on distributions

Generator.
enforceX
(a, x0, enforcedh, (supp, add)) Enforce a region around a line x=x0. The size of the cell around the line is enforcedh. “supp” points are suppressed from the starting distribution on the left and right side. “add” points are added on the left and add points are added on the right. Add exactely add points. Adjust add in order to have a monotonic distribution with: Generator.enforceX(a, x0, enforcedh, supp, add). Exists also for Y and Z directions: Generator.enforceY, Generator.enforceZ.
 Parameters
a (array or pyTree) – input structured mesh
x0 (float) – Xcoordinate for refinement
enforcedh (float) – cell size near refinement
supp (integer) – number of suppressed points
add (integer) – number of added points
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforceX (array)  import Generator as G import Converter as C Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) # Monotonic distribution b = G.enforceX(a, 0.3, 0.001, (13,25)) C.convertArrays2File([b], "out.plt")
#  enforceX (pyTree)  import Generator.PyTree as G import Converter.PyTree as C Ni = 50; Nj = 50; Nk = 2 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,Nk)) a = G.enforceX(a, 0.3, 0.001, (13,25)) C.convertPyTree2File(a, 'out.cgns')

Generator.
enforceMoinsX
(a, enforcedh, (supp, add)) Same as before but with a one sided distribution (left). This can be usefull to create a boundary layer distribution in an Euler mesh. Adjust add in order to have a monotonic distribution with: Generator.enforceMoinsX(a, enforcedh, supp, add). Exists also for Y and Z directions: Generator.enforceMoinsY, Generator.enforceMoinsZ.
 Parameters
a (array or pyTree) – input structured mesh
enforcedh (float) – cell size near refinement
supp (integer) – number of suppressed points
add (integer) – number of added points
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforceMoinsX (array)  import Generator as G import Converter as C Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = G.enforceMoinsX(a, 1.e3, (10,15)) C.convertArrays2File([b], "out.plt")
#  enforceMoinsX (pyTree)  import Converter.PyTree as C import Generator.PyTree as G Ni = 50; Nj = 50; Nk = 1 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,Nk)) b = G.enforceMoinsX(a, 1.e3, (10,15)) C.convertPyTree2File(b, 'out.cgns')

Generator.
enforcePlusX
(a, enforcedh, (supp, add)) Same as before but with a one sided distribution (right). Adjust add in order to have a monotonic distribution with: Generator.enforcePlusX(a, x0, enforcedh, supp, add). Exists also for Y and Z directions: Generator.enforceMoinsY, Generator.enforcePlusZ.
 Parameters
a (array or pyTree) – input structured mesh
enforcedh (float) – cell size near refinement
supp (integer) – number of suppressed points
add (integer) – number of added points
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforcePlusX (array)  import Generator as G import Converter as C # Distribution Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = G.enforcePlusX(a, 1.e3, (10,20)) C.convertArrays2File([b], "out.plt")
#  enforcePlusX (pyTree)  import Converter.PyTree as C import Generator.PyTree as G # Distribution Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = G.enforcePlusX(a, 1.e3, (10,20)) C.convertPyTree2File(b, 'out.cgns')

Generator.
enforceLine
(a, line, enforcedh, (supp, add)) Enforce a curvilinear line defined by the array line in a distribution defined by the array a.
 Parameters
a (array or pyTree) – input 2D distribution
line (array) – line
enforcedh (float) – cell size near refinement
supp (integer) – number of suppressed points
add (integer) – number of added points
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforceLine (array)  import Generator as G import Converter as C import Geom as D Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = D.line((0.,0.2,0.), (1.,0.2,0.), 20) c = G.enforceLine(a, b, 0.01, (5,3)) C.convertArrays2File([c], 'out.plt')
#  enforceLine (pyTree) import Generator.PyTree as G import Converter.PyTree as C import Geom.PyTree as D Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = D.line((0.,0.2,0.), (1.,0.2,0.), 20) a = G.enforceLine(a, b, 0.01, (5,3)) C.convertPyTree2File(a, 'out.cgns')

Generator.
enforcePoint
(a, x0) Enforce a point in the distribution. The index of enforced point is returned.
 Parameters
a (array or pyTree) – input 2D distribution
x0 (float) – Ilocation of the refinement point
 Returns
index of enforced point
 Return type
integer
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforcePoint (array)  import Converter as C import Generator as G # distribution Ni = 20; Nj = 20 a = G.cart((0,0,0), (1./(Ni1),5./(Nj1),1), (Ni,Nj,1)) b = G.enforcePoint(a, 0.5) C.convertArrays2File([b], "out.plt")
#  enforcePoint (pyTree)  import Converter.PyTree as C import Generator.PyTree as G Ni = 20; Nj = 20 a = G.cart((0,0,0), (1./(Ni1),5./(Nj1),1), (Ni,Nj,1)) b = G.enforcePoint(a, 0.5) C.convertPyTree2File(b, 'out.cgns')

Generator.
enforceCurvature
(a, curve, power=0.5) Enforce the curvature of an icurve in a distribution defined by a. Power reflects the power of stretching.
 Parameters
a (array or pyTree) – input 2D distribution
curve (array) – reference curve for curvature
power (float) – stretching ratio
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  enforceCurvature (array)  import Geom as D import Generator as G import Converter as C import Transform as T # Naca profile with lines a = D.naca(12., 501) l1 = D.getLength(a) a2 = D.line((1.,0.,0.),(2.,0.,0.), 500) l2 = D.getLength(a2) b = T.join(a, a2) c = D.line((2.,0.,0.),(1.,0.,0.), 500) res = T.join(c, b) # Distribution on the profile l = l1+2*l2 Ni = 100; Nj = 100 p1 = l2/l; p2 = (l2+l1)/l h = (p2p1)/(Ni1) distrib = G.cart((p1,0,0), (h, 0.25/Nj,1), (Ni,Nj,1)) distrib = G.enforceCurvature(distrib, res, 0.6) C.convertArrays2File([distrib], "out.plt")
#  enforceCurvature (pyTree)  import Geom.PyTree as D import Generator.PyTree as G import Converter.PyTree as C a = D.naca(12., 501) # Distribution on the profile Ni = 20; Nj = 20; Nk = 1; h = 1./(Ni1) b = G.cart((0,0,0), (h, 0.25/Nj,1), (Ni,Nj,Nk)) b = G.enforceCurvature(b, a, 0.6) C.convertPyTree2File(b, 'out.cgns')

Generator.
addPointInDistribution
(a, ind) Add a point in a distribution at index ind.
 Parameters
a (array or pyTree) – input distribution
ind (integer) – Iindex of inserted point
 Returns
modified reference copy of a
 Return type
array or pyTree
Example of use:
#  addPointInDistribution (array)  import Generator as G import Converter as C # Distribution Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,1)) b = G.addPointInDistribution( a, Ni ) C.convertArrays2File([b], 'out.plt')
#  addPointInDistribution (pyTree) import Generator.PyTree as G import Converter.PyTree as C # Distribution Ni = 50; Nj = 50 a = G.cart((0,0,0), (1./(Ni1), 0.5/(Nj1),1), (Ni,Nj,2)) b = G.addPointInDistribution(a, Ni) C.convertPyTree2File(b, 'out.cgns')