def exportVtk(self, filename):
"""Method for exporting fem calculation output to VTK-compatible format"""
print("Exporting results to '%s'..." % filename)
# --- Create points and polygon definitions from our node network
points = self.outputData.coords.tolist()
# --- Make sure topology is VTK-compatible; i.e.: 0-based
#polygons = (self.outputData.edof-1).tolist()
topo = np.zeros([self.outputData.edof.shape[0], 3], dtype=int)
for i in range(self.outputData.edof.shape[0]):
topo[i, 0] = self.outputData.edof[i, 1] / 2 - 1
topo[i, 1] = self.outputData.edof[i, 3] / 2 - 1
topo[i, 2] = self.outputData.edof[i, 5] / 2 - 1
polygons = (topo).tolist()
# --- Specify both vector and scalar data for each element
#pointData = vtk.PointData(vtk.Scalars(self.outputData.a.tolist(), name="Displacement"))
#cellData = vtk.CellData(vtk.Scalars(max(self.outputData.stress), name="maxvmstress"),\
# vtk.Vectors(self.outputData.stress, "stress"))
cellData = vtk.CellData(
vtk.Scalars(self.outputData.stress, name="Von Mises"))
# --- Create the structure of the element network
structure = vtk.PolyData(points=points, polygons=polygons)
# --- Store everything in a vtk instance
#vtkData = vtk.VtkData(structure, pointData, cellData)
vtkData = vtk.VtkData(structure, cellData)
# --- Save the data to the specified file
vtkData.tofile(filename, "ascii")
def test_tet_mesh(visualize=False):
pytest.importorskip("meshpy")
from math import pi, cos, sin
from meshpy.tet import MeshInfo, build
from meshpy.geometry import \
GeometryBuilder, generate_surface_of_revolution, EXT_CLOSED_IN_RZ
pytest.importorskip("meshpy")
big_r = 3
little_r = 1.5
points = 50
dphi = 2 * pi / points
rz = np.array(
[[big_r + little_r * cos(i * dphi), little_r * sin(i * dphi)]
for i in range(points)])
geo = GeometryBuilder()
geo.add_geometry(*generate_surface_of_revolution(
rz, closure=EXT_CLOSED_IN_RZ, radial_subdiv=20))
mesh_info = MeshInfo()
geo.set(mesh_info)
mesh = build(mesh_info)
def tet_face_vertices(vertices):
return [
(vertices[0], vertices[1], vertices[2]),
(vertices[0], vertices[1], vertices[3]),
(vertices[0], vertices[2], vertices[3]),
(vertices[1], vertices[2], vertices[3]),
]
face_map = {}
for el_id, el in enumerate(mesh.elements):
for fid, face_vertices in enumerate(tet_face_vertices(el)):
face_map.setdefault(frozenset(face_vertices), []).append(
(el_id, fid))
adjacency = {}
for face_vertices, els_faces in face_map.items():
if len(els_faces) == 2:
(e1, f1), (e2, f2) = els_faces
adjacency.setdefault(e1, []).append(e2)
adjacency.setdefault(e2, []).append(e1)
cuts, part_vert = pymetis.part_graph(17, adjacency)
if visualize:
import pyvtk
vtkelements = pyvtk.VtkData(
pyvtk.UnstructuredGrid(mesh.points, tetra=mesh.elements), "Mesh",
pyvtk.CellData(pyvtk.Scalars(part_vert, name="partition")))
vtkelements.tofile('split.vtk')
def field2VTKData (self,name=None,lookupTable=None):
"""
Creates VTK representation of the receiver. Useful for visualization. Requires pyvtk module.
:param str name: human-readable name of the field
:param pyvtk.LookupTable lookupTable: color lookup table
:return: Instance of pyvtk
:rtype: pyvtk
"""
import pyvtk
if name is None:
name=self.getFieldIDName()
if lookupTable and not isinstance(lookupTable,pyvtk.LookupTable):
log.info('ignoring lookupTable which is not a pyvtk.LookupTable instance.')
lookupTable=None
if lookupTable is None:
lookupTable=pyvtk.LookupTable([(0,.231,.298,1.0),(.4,.865,.865,1.0),(.8,.706,.016,1.0)],name='coolwarm')
#Scalars use different name than 'coolwarm'. Then Paraview uses its own color mapping instead of taking 'coolwarm' from *.vtk file. This prevents setting Paraview's color mapping.
scalarsKw=dict(name=name,lookup_table='default')
else:
scalarsKw=dict(name=name,lookup_table=lookupTable.name)
# see http://cens.ioc.ee/cgi-bin/cvsweb/python/pyvtk/examples/example1.py?rev=1.3 for an example
vectorsKw=dict(name=name) # vectors don't have a lookup_table
if (self.fieldType == FieldType.FT_vertexBased):
if (self.getValueType() == ValueType.Scalar):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.PointData(pyvtk.Scalars([val[0] for val in self.value],**scalarsKw),lookupTable), 'Unstructured Grid Example')
elif (self.getValueType() == ValueType.Vector):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.PointData(pyvtk.Vectors(self.value,**vectorsKw),lookupTable), 'Unstructured Grid Example')
elif (self.getValueType() == ValueType.Tensor):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.PointData(pyvtk.Tensors(self.getMartixForTensor(self.value),**vectorsKw),lookupTable),'Unstructured Grid Example')
else:
if (self.getValueType() == ValueType.Scalar):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.CellData(pyvtk.Scalars([val[0] for val in self.value],**scalarsKw),lookupTable), 'Unstructured Grid Example')
elif (self.getValueType() == ValueType.Vector):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.CellData(pyvtk.Vectors(self.value,**vectorsKw),lookupTable), 'Unstructured Grid Example')
elif (self.getValueType() == ValueType.Tensor):
return pyvtk.VtkData(self.mesh.getVTKRepresentation(), pyvtk.CellData(pyvtk.Tensors(self.getMartixForTensor(self.value),**vectorsKw),lookupTable),'Unstructured Grid Example')
def make_vtk(**kwargs):
args = []
if 'grid' in kwargs:
args.append(kwargs.get('grid'))
if 'point_data' in kwargs:
data = kwargs['point_data']
args.append(pyvtk.PointData(*data))
if 'cell_data' in kwargs:
data = kwargs['cell_data']
args.append(pyvtk.CellData(*data))
if 'header' in kwargs:
args.append(kwargs.get('header'))
return pyvtk.VtkData(*args)
def exportVtk(self, filename):
"""Export results to VTK"""
print("Exporting results to %s." % filename)
# --- Skapa punkter och polygon definitioner från vårt nät
points = self.outputData.coords.tolist()
# --- Tänk på att topologin i VTK är 0-baserad varför vi måste minskar **edof** med 1.
#polygons = (self.outputData.edof-1).tolist()
# --- För spänningsproblemet användas, se också nästa stycke:
polygons = (self.outputData.topo - 1).tolist()
# --- Resultat från beräkningen skapas i separata objekt. Punkter i vtk.PointData och
# --- elementdata i vtk.CellData. Nedan anger vi både vektor data och skalärvärden för elementen.
# --- Tänk på att vektorerna måste ha 3 komponenter, så lägg till detta i beräkningsdelen.
#pointData = vtk.PointData(vtk.Scalars(self.outputData.a.tolist(), name="Nodal Properties"))
#ellData = vtk.CellData(vtk.Scalars(self.outputData.vonMises, name="Von Mises"), vtk.Vectors(self.outputData.flow, "flow"))
# --- För spänningsproblemet blir det istället (ingen pointData)
#HÄR BLIR DET KNAS#
cellData = vtk.CellData(
vtk.Scalars(self.outputData.vonMises, name="mises"),
vtk.Vectors(self.outputData.stresses1, "principal stress 1"),
vtk.Vectors(self.outputData.stresses2, "principal stress 2"))
# --- Skapa strukturen för elementnätet.
structure = vtk.PolyData(points=points, polygons=polygons)
# --- Lagra allting i en vtk.VtkData instans
# vtkData = vtk.VtkData(structure, pointData, cellData)
# --- För spänningsfallet
vtkData = vtk.VtkData(structure, cellData)
# --- Spara allt till filen
vtkData.tofile(filename, "ascii")
xTmp = list(zip(x, y))
tri = Delaunay(xTmp)
# Generate Cell Data
nCells = tri.nsimplex
cellTemp = np.random.rand(nCells)
# Zip the point co-ordinates for the VtkData input
points = list(zip(x, y, z))
vtk = pyvtk.VtkData(\
pyvtk.UnstructuredGrid(points,
triangle=tri.simplices
),
pyvtk.PointData(pyvtk.Scalars(pointPressure,name='Pressure')),
pyvtk.CellData(pyvtk.Scalars(cellTemp,name='Temperature')),
'2D Delaunay Example'
)
vtk.tofile('Delaunay2D')
vtk.tofile('Delaunay2Db', 'binary')
# Compute the 3D Delaunay triangulation in the x-y plane
xTmp = list(zip(x, y, z))
tri = Delaunay(xTmp)
# Generate Cell Data
nCells = tri.nsimplex
cellTemp = np.random.rand(nCells)
# Zip the point co-ordinates for the VtkData input
points = list(zip(x, y, z))
def export_vtk_stress(filename,
coords,
topo,
a=None,
el_scalar=None,
el_vec1=None,
el_vec2=None):
"""
Export mesh and results for a 2D stress problem.
Parameters:
filename Filename of vtk-file
coords Element coordinates (np.array)
topo Element topology (not dof topology). mesh.topo. (np.array)
a Element displacements 2-dof (np.array)
el_scalar Scalar values for each element (list)
el_vec1 Vector value for each element (list)
el_vec2 Vector value for each element (list)
"""
points = coords.tolist()
polygons = (topo - 1).tolist()
displ = []
point_data = None
scalars = None
vectors1 = None
vectors2 = None
cell_data = None
if a is not None:
for i in range(0, len(a), 2):
displ.append([np.asscalar(a[i]), np.asscalar(a[i + 1]), 0.0])
point_data = vtk.PointData(vtk.Vectors(displ, name="displacements"))
if el_scalar is not None:
scalars = vtk.Scalars(el_scalar, name="scalar")
if el_vec1 is not None:
vectors1 = vtk.Vectors(el_vec1, name="principal1")
if el_vec2 is not None:
vectors2 = vtk.Vectors(el_vec2, name="principal2")
if el_scalar is not None and el_vec1 is None and el_vec2 is None:
cell_data = vtk.CellData(scalars)
if el_scalar is not None and el_vec1 is None and el_vec2 is not None:
cell_data = vtk.CellData(scalars, vectors2)
if el_scalar is not None and el_vec1 is not None and el_vec2 is None:
cell_data = vtk.CellData(scalars, vectors1)
if el_scalar is not None and el_vec1 is not None and el_vec2 is None:
cell_data = vtk.CellData(scalars, vectors1, vectors2)
if el_scalar is None and el_vec1 is None and el_vec2 is not None:
cell_data = vtk.CellData(vectors2)
if el_scalar is None and el_vec1 is not None and el_vec2 is None:
cell_data = vtk.CellData(vectors1)
if el_scalar is None and el_vec1 is not None and el_vec2 is None:
cell_data = vtk.CellData(vectors1, vectors2)
structure = vtk.PolyData(points=points, polygons=polygons)
if cell_data is not None and point_data is not None:
vtk_data = vtk.VtkData(structure, cell_data, point_data)
if cell_data is None and point_data is not None:
vtk_data = vtk.VtkData(structure, point_data)
if cell_data is None and point_data is None:
vtk_data = vtk.VtkData(structure)
vtk_data.tofile("exm6.vtk", "ascii")
#for inc in range(11):
#print inc
#fid = open('SkullPO_'+AA[inc]+'stress.log')
#SS = fid.read()
#SS = SS.split(strSplit)
#SS1 = SS[0]
#SS2 = SS[1]
#SS1 = SS1.split('\n')
#SS2 = SS2.split('\n')
#SS1 = SS1[0:1687791]
#SS2 = SS2[0:1687791]
#for i in range(1687791):
#SS1[i] = SS1[i].split(' ')
#SS2[i] = SS2[i].split(' ')
#ST1 = np.array(SS1,float)
#ST2 = np.array(SS2,float)
#Stress = np.c_[ST1[:,1:],ST2[:,1:]]
#vonMisses = np.sqrt(Stress[:,0]*Stress[:,0]+Stress[:,1]*Stress[:,1]+Stress[:,2]*Stress[:,2]-Stress[:,1]*Stress[:,2]-Stress[:,0]*Stress[:,2]-Stress[:,0]*Stress[:,1]+3*(Stress[:,3]*Stress[:,3]+Stress[:,4]*Stress[:,4]+Stress[:,5]*Stress[:,5]))
#Stress = np.c_[Stress,vonMisses]
#np.ma.dump(Stress,'Skull'+AA[inc]+'Stress')
Tet = np.ma.load('SkullPO_TetUse')
NC = np.ma.load('SkullPO_NC050')
for inc in range(11):
print 'Skull ' + AA[inc] + ' on Average Shape'
Stress = np.ma.load('Skull' + AA[inc] + 'Stress')
print Stress[:, 6]
skvtk = pv.VtkData(pv.UnstructuredGrid(points=NC, tetra=Tet),
'skull ' + AA[inc] + ' vM stress',
pv.CellData(pv.Scalars(Stress[:, 6], 'von Misses')))
skvtk.tofile('SkullAver_' + AA[inc] + 'vM.vtk')
sys.path = ['..'] + sys.path
#from pyvtk import *
import pyvtk as vtk
structure = vtk.PolyData(points=[[0, 0, 0], [1, 0, 0], [1, 1, 0], [0, 1, 0],
[0, 0, 1], [1, 0, 1], [1, 1, 1], [0, 1, 1]],
polygons=[[0, 1, 2, 3], [4, 5, 6, 7], [0, 1, 5, 4],
[2, 3, 7, 6], [0, 4, 7, 3], [1, 2, 6, 5]])
pointdata = vtk.PointData(
vtk.Scalars([0, 1, 2, 3, 4, 5, 6, 7],
name='sample_scalars',
lookup_table='my_table'),
vtk.LookupTable([[0, 0, 0, 1], [1, 0, 0, 1], [0, 1, 0, 1], [1, 1, 0, 1],
[0, 0, 1, 1], [1, 0, 1, 1], [0, 1, 1, 1], [1, 1, 1, 1]],
name='my_table'))
celldata = vtk.CellData(
vtk.Scalars([0, 1, 2, 3, 4, 5], name='cell_scalars'),
vtk.Normals(
[[0, 0, -1], [0, 0, 1], [0, -1, 0], [0, 1, 0], [-1, 0, 0], [1, 0, 0]],
name='cell_normals'),
vtk.Field('FieldData',
cellIds=[[0], [1], [2], [3], [4], [5]],
faceAttributes=[[0, 1], [1, 2], [2, 3], [3, 4], [4, 5], [5, 6]]))
vtkdata = vtk.VtkData(structure, pointdata, celldata)
vtkdata.tofile('example1ascii', 'ascii')
#vtkdata.tofile('example1binary','binary')
#vtk2 = VtkData('example1')t
import numpy as np
import pyvtk as pv
### Von Mises of average stress tensor of P and O skulls
fname = 'SkullPO_AveragePO'
S = (np.ma.load('Skull100Stress')[:, 0:6] +
np.ma.load('Skull000Stress')[:, 0:6]) / 2
NCS = (np.ma.load('SkullPO_NC100') + np.ma.load('SkullPO_NC000')) / 2
TetT = np.ma.load('SkullPO_TetUse')
VonM = np.sqrt(
(np.power(S[:, 0] - S[:, 1], 2) + np.power(S[:, 1] - S[:, 2], 2) +
np.power(S[:, 0] - S[:, 2], 2) + 6 *
(S[:, 3] * S[:, 3] + S[:, 4] * S[:, 4] + S[:, 5] * S[:, 5])) / 2)
skvtk = pv.VtkData(pv.UnstructuredGrid(points=NCS, tetra=TetT),
'skull unique mesh',
pv.CellData(pv.Scalars(VonM, 'VonMises')))
skvtk.tofile(fname + '.vtk')
np.ma.dump(VonM, fname + 'VonMises')
### Von Mises of Difference in stress tensor for Average and Average between P and O
fname = 'SkullPO_AvPOminAverage'
S = S - np.ma.load('Skull050Stress')[:, 0:6]
NCS = np.ma.load('SkullPO_NC050')
TetT = np.ma.load('SkullPO_TetUse')
VonM = np.sqrt(
(np.power(S[:, 0] - S[:, 1], 2) + np.power(S[:, 1] - S[:, 2], 2) +
np.power(S[:, 0] - S[:, 2], 2) + 6 *
(S[:, 3] * S[:, 3] + S[:, 4] * S[:, 4] + S[:, 5] * S[:, 5])) / 2)
skvtk = pv.VtkData(pv.UnstructuredGrid(points=NCS, tetra=TetT),
'skull unique mesh',
pv.CellData(pv.Scalars(VonM, 'VonMises')))