h = 0.01 smoothingKernelFunc = 2 speedsound = 1 density = 1 shearmodulus = 1 bulkmodulus = 1 # Create a packer, see packers directory for options cubic = pyck.CubicPacker([10.0, 10.0, 10.0], h) # pack = pyck.Pack(cubic); # do not create the cubic packer in this # function call as it will be destroyed, blame SWIG developers pack = pyck.StructuredPack(cubic) # Create some shapes, see shapes directory for options and reference # First argument is always a tag for these particles # Mapping operations are applied sequentially cube = pyck.Cuboid(1, [2, 2, 2], [6, 6, 6]) sphere = pyck.Sphere(2, [2, 2, 2], 5) # Map the shapes and generate the pack # As with creating the cubic packer, do not create the shapes within the # function call here pack.AddShape(cube) pack.AddShape(sphere) pack.Process() # Create a new model from the pack model = pyck.Model(pack) # Create a new field of n-dimensional integers # Arguments are CreateIntField(label,dimensions) # label - label for this field in the vtp file
import pyck
L = [1, 1, 0]
r = 0.002
dim = 2
smoothingKernelFunc = 1
cubic = pyck.Hcp2dPacker(L, r)
# do not create the cubic packer in this function call as it will be
# destroyed, blame SWIG developers
pack = pyck.StructuredPack(cubic)
cube = pyck.Cuboid(1, [0, 0, 0], [1, 1, 0])
convexh = pyck.ConvexHull2D(2, [[0.1, 0.2, 0], [0.8, 0.2, 0], [0.3, 0.8, 0]])
pack.AddShape(cube)
pack.AddShape(convexh)
# Map the shapes and generate the pack
pack.Process()
# Create a new model from the pack
model = pyck.Model(pack)
# Create a new field of n-dimensional integers
# Arguments are CreateIntField(label,dimensions)
# label - label for this field in the vtp file
# dimensions - dimensionality of this field, doesnt have to correspond to model dimensions
# Create field of doubles in the same way with CreateDoubleField
stateField = model.CreateIntField("State", 1)
# for i in range(1, 17):
import pyck
L = [10.0, 10.0, 0.0]
r = 0.1
# Create a packer, see packers directory for options
cubic = pyck.Hcp2dPacker(L, r)
# Get the periodic extent of the pack
periodicExtent = cubic.GetPeriodicExtent()
# Create a structured pack
pack = pyck.StructuredPack(cubic)
# Create a cube which will pack every particle specified by the packer
cube = pyck.Cuboid(1, [-1, -1, -1], [11, 11, 11])
# Add and process
pack.AddShape(cube)
pack.Process()
# Create a new model from the pack
model = pyck.Model(pack)
# (Over)write the domain size
model.SetParameter("Lx", "%e" % periodicExtent[0])
model.SetParameter("Ly", "%e" % periodicExtent[1])
model.SetParameter("Lz", "%e" % periodicExtent[2])
model.SetParameter("GridSizeX", "%d" % math.floor(periodicExtent[0] / r))
model.SetParameter("GridSizeY", "%d" % math.floor(periodicExtent[1] / r))
model.SetParameter("GridSizeZ", "%d" % math.floor(periodicExtent[2] / r))
pack = pyck.StructuredPack(Hcp)
def pythonShape(x, y, z):
dx = x - 1.0
dy = y - 1.0
dz = z - 1.0
r = 0.3
if (dx * dx + dy * dy + dz * dz < r * r):
return True
return False
pyShape = pyck.PyShape(1, [0.7, 0.7, 0.7], [1.0, 1.0, 1.0], pythonShape)
cube = pyck.Cuboid(2, [0.2, 0.2, 0.2], [0.6, 0.6, 0.6])
# Map the shapes and generate the pack
pack.AddShape(pyShape)
pack.AddShape(cube)
pack.Process()
# Create a new model from the pack
model = pyck.Model(pack)
# Create a new field of n-dimensional integers
# Arguments are CreateIntField(label,dimensions)
# label - label for this field in the vtp file
# dimensions - dimensionality of this field, doesnt have to correspond to model dimensions
# Create field of doubles in the same way with CreateDoubleField
stateField = model.CreateIntField("State", 1)
import pyck
L = [10.0, 10.0, 0.0]
r = 0.1
cubic = pyck.CubicPacker(L, r)
pack = pyck.StructuredPack(cubic)
cube = pyck.Cuboid(1, [2, 2, -1], [6, 6, 1])
sphere = pyck.Sphere(2, [2, 2, 2], 5)
pack.AddShape(cube)
pack.AddShape(sphere)
pack.Process()
model = pyck.Model(pack)
# Create an IntField
stateField = model.CreateIntField("State", 1)
# The IntField may be set in the traditional way:
model.SetIntField(stateField, 1, 10)
# Or we can use a callback to determine the value of the
# field as a function of position
# Note that the callback must always take arguments for X Y and Z
# regardless of the dimensionality of the pack
def fieldCallback(x, y, z):
return x
import pyck L = [10.0, 10.0, 0.0] offset = [100.0, 50.0, 0.0] r = 0.1 # Create a packer, see packers directory for options cubic = pyck.CubicPacker(L, r, offset) # do not create the cubic packer in this function call as it will be # destroyed, blame SWIG developers pack = pyck.StructuredPack(cubic) # Create some shapes, see shapes directory for options and reference # First argument is always a tag for these particles # Mapping operations are applied sequentially cube = pyck.Cuboid(1, [102, 52, -1], [106, 56, 1]) sphere = pyck.Sphere(2, [102, 52, 2], 5) # Map the shapes and generate the pack # As with creating the cubic packer, do not create the shapes within the # function call here pack.AddShape(cube) pack.AddShape(sphere) pack.Process() # Create a new model from the pack model = pyck.Model(pack) # Create a new field of n-dimensional integers # Arguments are CreateIntField(label,dimensions) # label - label for this field in the vtp file