Generator: meshes 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 open-source pre- and post-processor for CFD simulations.

For use with the array interface, you have to import Initiator module:

import Generator as G

For use with the pyTree interface:

import Generator.PyTree as G

List of functions

– Basic grid generation

cart(Xo, H, N) Create a cartesian mesh defined by a structured array.
cartHexa(Xo, H, N) Create a cartesian mesh defined by an hexaedrical array.
cartTetra(Xo, H, N) Create a cartesian mesh defined by a tetraedrical array.
cartPenta(Xo, H, N) Create a cartesian mesh defined by a prismatic array.
cartPyra(Xo, H, N) Create a cartesian mesh defined by a pyramidal array.
cartNGon(Xo, H, N) Create a cartesian mesh defined by a NGON array.
cylinder(Xo, R1, R2, tetas, tetae, H, N) Create a portion of regular cylindrical grid.
cylinder2(Xo, R1, R2, tetas, tetae, H, ...) Create a portion of cylindrical grid.
cylinder3(arrayxz, tetas, tetae, arrayteta) Create a portion of cylindrical grid.

– General purpose grid generators

delaunay(array[, tol, keepBB]) Create a delaunay mesh given a set of points defined by array.
constrainedDelaunay(cont0[, tol, keepBB]) Create a constrained-Delaunay mesh starting from a BAR-array defining
checkDelaunay(contour, tri) Check if the Delaunay triangulation defined by tri is inside the contour.
T3mesher2D(a[, triangulateOnly]) Create a delaunay mesh given a set of points defined by a.
tetraMesher(a[, maxh, grading, ...]) Create a TRI/TETRA mesh given a set of BAR or surfaces in a.
TFI(arrays) Generate a transfinite interpolation mesh from boundaries.
TFITri(a1, a2, a3) Generate a transfinite interpolation mesh from 3 input curves.
TFIO(a) Generate a transfinite interpolation mesh for 1 input curve.
TFIHalfO(a1, a2) Generate a transfinite interpolation mesh for 2 input curves.
TFIMono(a1, a2) Generate a transfinite interpolation mesh for 2 input curves.
hyper2D(array, arrayd, type) Generate an hyperbolic mesh.
PolyLine.polyLineMesher(polyLine, h, yplus, ...) Generate a multiple mesh for a polyline.
PolyC1.polyC1Mesher(curve, h, yplus, density) Generate a multiple mesh for a C1 curve (polyC1).
pointedHat(array, x, y) Create a structured surface defined by a contour and a point (x,y,z).
stitchedHat(array, offx, offy[, tol, tol2]) Create a structured surface defined by a contour and an offset (dx,dy,dz).
surfaceWalk(surfaces, c, distrib[, ...]) Generate a surface mesh by a walk on a list of surfaces, starting from a contour c and following constraints.
collarMesh(s1, s2, distribj, distribk[, ...]) 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

gencartmb(bodies, h, Dfar, nlvl)
octree(stlArrays, snearList[, dfar, ...]) Generates an octree (or a quadtree) mesh starting from a list of TRI (or BAR) arrays defining bodies,
octree2Struct(a[, vmin, ext, optimized, ...]) Generates a structured set of regular Cartesian grid starting from
adaptOctree(octreeHexa, indicField[, ...]) Adapt an unstructured octree w.r.t.
expandLayer(octreeHexa[, level, corners, ...]) Expand the layer of octree elements of level l of one additional layer.

– Operations on meshes

close(array[, tol]) Close a mesh defined by an array gathering points closer than tol.
selectInsideElts(array, curvesList) Select elements whose center is in the surface delimited by curves.
map(array, d[, dir]) Map a distribution on a curve or a surface.
mapSplit(array, dist[, splitCrit, densMax]) Split a curve and map a distribution on the set of split curves.
refine(array, power[, dir]) Refine a mesh of power power along all the directions or on a specified one.
mapCurvature(array, N, power, dir)
densify(array, h)
grow(array, vector) Grow a surface array of one layer by deplacing points of vector.
stack(array1[, array2]) Stack two meshes (with same nixnj) into a single mesh.
addNormalLayers(surface, distrib[, check, ...]) Generate N layers to a surface following normals. distrib is the
TTM(array[, niter]) Smooth a mesh with Thompson-Mastin elliptic generator.
snapFront(meshes, surfaces[, optimized]) Adapt meshes to a given surface (cellN defined).
snapSharpEdges(meshes, surfaces[, step, angle]) Adapt meshes to a given surface sharp edges.

– Operations on surface meshes

fittingPlaster(contour[, bumpFactor]) Generate a structured points cloud over a BAR.
gapfixer(contour, cloud[, hardPoints, refine]) Fix a gap defined by a contour bar and a point cloud representing the gap surface.
gapsmanager(components[, mode, refine, coplanar]) Fix a gap between several component surfaces (list of arrays).

– Information on generated meshes

barycenter(array[, weight]) Get the barycenter of an array.
bbox(arrays) Returns the bounding box of a list of arrays.
bboxOfCells(array) Return the bounding box of all cells of an array.
BB(array[, method, weighting]) Return the axis-aligned or oriented bounding box of an array as an array.
CEBBIntersection(array1, array2[, tol]) Get the Cartesian Elements bounding box intersection of 2 arrays.
bboxIntersection(array1, array2[, tol, ...]) Return the intersection of bounding boxes of 2 arrays.
checkPointInCEBB(array, P) Check if point P is in the Cartesian Elements Bounding Box of
getVolumeMap(array) Return the volume map in an array.
getNormalMap(array) Return the map of surface normals in an array.
getSmoothNormalMap(array[, niter, eps]) Return the map of smoothed and non-normalized surface normals in an array.
getOrthogonalityMap(array) Return the orthogonality map in an array.
getRegularityMap(array) Return the regularity map in an array.
getTriQualityMap(array) Return a TRI quality measure map in an array.
getCellPlanarity(array) Return the cell planarity of a surface mesh in an array.
getCircumCircleMap(array) Return the map of circum circle radius of any cell in a TRI array.
getInCircleMap(array) Return the map of inscribed circle radius of any cell in a TRI array.
getEdgeRatio(array[, dim]) Computes the ratio between the max and min lengths of all the edges of cells in an array.
getMaxLength(array[, dim]) Computes the max length of all the edges of cells in an array.

– Operations on distributions

enforceX(array, x0, enforcedh, N[, add]) Enforce a x0-centered line in a distribution defined by an array.
enforceMoinsX(array, enforcedh, N[, add]) Enforce the last X-line in a distribution (one sided, left).
enforcePlusX(array, enforcedh, N[, add]) Enforce the first X-line in a distribution defined by an array.
enforceLine(array, arrayline, enforcedh, N) Enforce a line in a distribution.
enforcePoint(array, x0) Enforce a point in a distribution.
enforceCurvature(arrayD, arrayC[, power]) Enforce curvature of a curve in a distribution.
addPointInDistribution(array, ind) Add a point in a distribution defined by array.

Contents

CFD field initialisations

The input data defines a grid or a set of grids on which the solution has to be initialized.

The created field variables are the variables defined in the input data. If the five conservative variables are not present, then the default output variables are the coordinates and the conservative variables.


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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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.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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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) (3-tuple of floats) – coordinates of the starting point
  • (hi,hj,hk) (3-tuple of floats) – values of advancing step in the three directions
  • (ni,nj,nk) (3-tuple 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
import CPlot

a = G.cartNGon((0.,0.,0.), (0.1,0.1,0.2), (20,20,20))
CPlot.display([a])
# - 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 center-bottom 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) (3-tuple 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) (3-tuple 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 center-bottom 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) (3-tuple 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')

Generator.delaunay(a, tol=1.e-10, 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./(ni-1); hj = 1./(nj-1); 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./(ni-1); hj = 1./(nj-1); 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.e-10, keepBB=0)

Create a constrained Delaunay triangulation of the convex hull of a contour c. Contour must be a BAR-array 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 (BAR-array) – 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('STEPHANIE')
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('STEPHANIE')
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 (BAR-array) – contour in xy plane
  • tri (array or pyTree) – 2D Delaunay triangulation mesh
Returns:

contour

Return type:

BAR-array

Example of use:

# - checkDelaunay (array) -
import Converter as C
import Generator as G
import Transform as T
import Geom as D

A = D.text1D('STEPHANIE')
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('STEPHANIE')
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)

Create 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.

Parameters:
  • c ([array, list of arrays] or [pyTree, base, zone, list of zones]) – BAR-contour
  • triangulateOnly (integer (0 or 1)) – insertion or not of interior points for the triangulation
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)
C.convertArrays2File([a,b], 'out.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)
t = C.newPyTree(['Base',2]); t[2][1][2].append(b)
C.convertPyTree2File(t, 'out.cgns')

Generator.tetraMesher(a, algo=1)

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
  • 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) – I-direction minimum boundary
  • imax (array) – I-direction maximum boundary
  • jmin (array) – J-direction minimum boundary
  • jmax (array) – J-direction maximum boundary
  • kmin (array) – K-direction minimum boundary
  • kmax (array) – K-direction 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 numpy as N
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./(Ni-1),1,1), (Ni,1,1))
q = G.cart((0,0,0), (1./(Nj-1),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./(nx-1); hy = 1./(ny-1); hz = 1./(nz-1)

# 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
import numpy as N

# 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. N3-N2+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 curves a. The number of points of a must be odd.

Parameters:a (array) – curve
Returns:2D structured mesh (butterfly O-H 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 half-O. N1 and N2 must be odd.

Parameters:
  • a1 (array) – first curve
  • a2 (array) – second curve
Returns:

2D structured mesh (half butterfly C-H topology)

Return type:

array or pyTree

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 half-O. N1-N2 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.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./(Ni-1), 0.5/(Nj-1),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./(Ni-1), 0.5/(Nj-1),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 (BAR-array), 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 (BAR-array) – 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 Post as P
import Geom as D
import Transform as T

# Read a 2D geometry created with tecplot
a = C.convertFile2Arrays('fusee.plt')
a = G.close(a,1e-2); 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,1e-2); 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 i-arrays each representing a C1 curve. All i-arrays 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 Post as P
import Geom as D
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 i-array 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) (3-tuple 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.e-6, tol2=1.e-5)

Create a stitched mesh from a curve defined by a i-array. 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) (3-tuple 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.e-3)
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.e-4)
C.convertPyTree2File(c, 'out.cgns')

Generator.surfaceWalk(surfaces, c, dj, constraints=[], niter=0, alphaRef=180., check=0, toldist=1.e-6)

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 (1D-array) – 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.e-10, 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 (1D-array) – distribution of points along surfaces
  • dk (1D-array) – 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.e-2,1,1),(21,1,1))
dhk = G.cart((0.,0.,0.),(1.e-2,1,1),(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.e-2,1,1),(21,1,1))
dhk = G.cart((0.,0.,0.),(1.e-2,1,1),(11,1,1))
a = G.collarMesh(s1,s2, dhj,dhk,niterj=100,niterk=100,type='union')
C.convertPyTree2File(a,"out.cgns")

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.e-1# 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
import Transform.PyTree as T

# body mesh
a = G.cylinder((0.,0.,0.), 0.5, 1., 360., 0., 10., (50,50,30))
h = 1.e-1  # 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, snears, dfar=5., balancing=0, levelMax=1000, ratio=2)

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; dfar is the extension of the octree mesh in all the directions; 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 27-tree mesh is built, in which case the spacing ratio is 3 (and not 2) between two adjacent elements.

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 or 1)
  • 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=1)
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 27-tree 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 or 1)
  • 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 or 1)
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.close(a, tol=1.e-12)

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
import Transform as T

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.e-3)
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.e-2,0,0), (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.e-1)
C.convertPyTree2File(t, 'out.cgns')

Generator.selectInsideElts(a, curves)

Select elements of a TRI-array, whose centers are inside the given list of curves, defined by BAR-arrays.

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 i-array 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./(Ni-1),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./(Ni-1),1./(Nj-1),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./(Ni-1),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./(Ni-1),1.,1.), (Ni,1,1) )
l = G.map(l, dist)
t = C.newPyTree(['Base',1]); t[2][1][2].append(l)
C.convertPyTree2File(t, 'out.cgns')

Generator.mapSplit(a, distrib, splitCrit=100.)

Split a i-array and map a distribution on the splitted i-array. 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 Transform as T
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./(Ni-1),1,1),(Ni,1,1))
dist = G.enforceX(dist, 15.5/(Ni-1), 0.005, 2,5)
dist = G.enforceX(dist, 27.5/(Ni-1), 0.005, 2,5)
a = G.mapSplit(a,dist,0.25)
C.convertArrays2File(a, 'out.plt')
# - mapSplit (pyTree) -
import Generator.PyTree as G
import Transform.PyTree as T
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./(Ni-1),1,1),(Ni,1,1))
dist = G.enforceX(dist, 15.5/(Ni-1), 0.005, 2,5)
dist = G.enforceX(dist, 27.5/(Ni-1), 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 i-array or a BAR-array 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 [pyTree]) – 1D structured mesh
  • h (float) – new cell size step for the points densification
Return type:

Identify 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 pyTree) – 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 pyTree

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)

Stack two 2D structured meshes (with the same nixnj) into a single 3D mesh.

Parameters:
  • a (array or pyTree) – 2D structured mesh
  • b (array or pyTree) – 2D structured mesh
Returns:

new 3D structured mesh

Return type:

array or pyTree

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)

# Conacatenate n structured grids
a = []
for i in xrange(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((0.1,0.,0.), (0.1,1,1),(2,1,1)) 
a = D.sphere((0,0,0), 1, 50)
a = D.line((0,0,0),(1,1,0),3)
b = G.addNormalLayers(a, d)
d = G.cart((0.1,0.,0.), (-0.1,1,1),(2,1,1)) 
c =  G.addNormalLayers(a, d)
import Transform.PyTree as T
a = T.join(b,c)
C.convertPyTree2File(a, '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./(Ni-1),1,1), (Ni,1,1))
q = G.cart((0,0,0), (1./(Nj-1),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./(Ni-1),1,1), (Ni,1,1))
q = G.cart((0,0,0), (1./(Nj-1),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 = (xmax-xmin)/(ni-1); hj = (ymax-ymin)/(nj-1)
h = min(hi, hj)
ni = int((xmax-xmin)/h)+7; nj = int((ymax-ymin)/h)+7
b = G.cart((xmin-3*h, ymin-3*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 = (xmax-xmin)/(ni-1); hj = (ymax-ymin)/(nj-1)
h = min(hi, hj)
ni = int((xmax-xmin)/h)+7; nj = int((ymax-ymin)/h)+7
b = G.cart( (xmin-3*h, ymin-3*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 Geom as D

# polylines with sharp angles
s = D.polyline([(0.2,0,0),(1,1,0),(2.5,1,0),(0.2,0,0)])
# Regular cartesian grid
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)
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')

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) – amplitude of the bump
  • 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
import numpy as np

# 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.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:

3-list 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)
w = C.initVars(a, 'weight', 1.); w = C.extractVars(w,['weight'])
print G.barycenter(a, w)
# - 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)
a = C.initVars(a, 'weight', 1.)
print G.barycenter(a, 'weight')

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:6-list 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)

Return the bounding box of a as an array or a zone. If method is ‘AABB’, then it computes the Axis-Aligned Bounding-Box, if method is ‘OBB’ then it computes the Oriented Bounding-Box. The argument weighting may be 0, and the OBB is computed using a Cloud-Point approach, or 1, and it is computed using a Surface-Weighting 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 axis-aligned or oriented bounding box
  • weighting (integer) – activation key for surface weighting approach
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.e-10)

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 Converter as C
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 Converter.PyTree as C
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.e-6, isBB=False, method='AABB')

Test if a1 and a2 intersects. Three options are available: method=’AABB’ (intersection between two Axis-Aligned 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) (3-tuple 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
import Converter as C

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
import Converter.PyTree as C

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
import Geom as D

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
import Geom.PyTree as D

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,1e-6,(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,1e-6,(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,1e-6,(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,1e-6,(5,50))
a = G.getMaxLength(a)
C.convertPyTree2File(a, "out.cgns")

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) – X-coordinate 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./(Ni-1), 0.5/(Nj-1),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./(Ni-1), 0.5/(Nj-1),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./(Ni-1), 0.5/(Nj-1),1), (Ni,Nj,1))
b = G.enforceMoinsX(a, 1.e-3, (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./(Ni-1), 0.5/(Nj-1),1), (Ni,Nj,Nk))
b = G.enforceMoinsX(a, 1.e-3, (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./(Ni-1), 0.5/(Nj-1),1), (Ni,Nj,1))
b = G.enforcePlusX(a, 1.e-3, (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./(Ni-1), 0.5/(Nj-1),1), (Ni,Nj,1))
b = G.enforcePlusX(a, 1.e-3, (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./(Ni-1), 0.5/(Nj-1),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./(Ni-1), 0.5/(Nj-1),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) – I-location 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./(Ni-1),5./(Nj-1),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./(Ni-1),5./(Nj-1),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 i-curve 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 = (p2-p1)/(Ni-1)
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./(Ni-1)
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) – I-index 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./(Ni-1), 0.5/(Nj-1),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./(Ni-1), 0.5/(Nj-1),1), (Ni,Nj,2))
b = G.addPointInDistribution(a, Ni)
C.convertPyTree2File(b, 'out.cgns')

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