def find_leaf_nodes(mesh,radius=0.3, ratio_of_nodes = 0.3): """ marks some areas of the mesh as areas where there is stimulated exitation. radius is the size of the node areas ratio of nodes is the amount of nodes you want, divided by the number of nodes found by the purkinje simulation. """ marks_vector = np.zeros(fenics_ordered_coordinates.shape[0]) E, N, left, distance_lv, terminal_lv = call_tree.get_left() E, N, right, distance_rv, terminal_rv = call_tree.get_right() ratio_of_discarded_nodes = 1-ratio_of_nodes coin_rv = np.random.random(len(terminal_rv)) terminal_rv = terminal_rv*coin_rv terminal_rv = (terminal_rv > ratio_of_discarded_nodes)*1.0 coin_lv = np.random.random(len(terminal_lv)) terminal_lv = terminal_lv*coin_lv terminal_lv = (terminal_lv > ratio_of_discarded_nodes)*1.0 r = radius #some radius rr = r**2 C = fenics_ordered_coordinates # short hand #left ventricle: terminal_idx = np.argwhere(terminal_lv) for i in range(np.size(terminal_idx)): leaf_idx = terminal_idx[i] leaf_coor = N[leaf_idx, :] dist = C-leaf_coor dist = dist**2 dist = np.sum(dist, axis=1) leaf_idx = np.argwhere(dist < rr) marks_vector[leaf_idx] = distance_lv[terminal_idx[i]] #right ventricle: terminal_idx = np.argwhere(terminal_rv) for i in range(np.size(terminal_idx)): leaf_idx = terminal_idx[i] leaf_coor = N[leaf_idx, :] dist = C-leaf_coor dist = dist**2 dist = np.sum(dist, axis=1) leaf_idx = np.argwhere(dist < rr) marks_vector[leaf_idx] = distance_rv[terminal_idx[i]] return marks_vector
def find_leaf_nodes(mesh, radius=0.3, ratio_of_nodes=0.3):
"""
marks some areas of the mesh as areas where there is stimulated exitation.
radius is the size of the node areas
ratio of nodes is the amount of nodes you want, divided by the number of nodes
found by the purkinje simulation.
"""
marks_vector = np.zeros(fenics_ordered_coordinates.shape[0])
E, N, left, distance_lv, terminal_lv = call_tree.get_left()
E, N, right, distance_rv, terminal_rv = call_tree.get_right()
ratio_of_discarded_nodes = 1 - ratio_of_nodes
coin_rv = np.random.random(len(terminal_rv))
terminal_rv = terminal_rv * coin_rv
terminal_rv = (terminal_rv > ratio_of_discarded_nodes) * 1.0
coin_lv = np.random.random(len(terminal_lv))
terminal_lv = terminal_lv * coin_lv
terminal_lv = (terminal_lv > ratio_of_discarded_nodes) * 1.0
r = radius #some radius
rr = r**2
C = fenics_ordered_coordinates # short hand
#left ventricle:
terminal_idx = np.argwhere(terminal_lv)
for i in range(np.size(terminal_idx)):
leaf_idx = terminal_idx[i]
leaf_coor = N[leaf_idx, :]
dist = C - leaf_coor
dist = dist**2
dist = np.sum(dist, axis=1)
leaf_idx = np.argwhere(dist < rr)
marks_vector[leaf_idx] = distance_lv[terminal_idx[i]]
#right ventricle:
terminal_idx = np.argwhere(terminal_rv)
for i in range(np.size(terminal_idx)):
leaf_idx = terminal_idx[i]
leaf_coor = N[leaf_idx, :]
dist = C - leaf_coor
dist = dist**2
dist = np.sum(dist, axis=1)
leaf_idx = np.argwhere(dist < rr)
marks_vector[leaf_idx] = distance_rv[terminal_idx[i]]
return marks_vector
def find_leaf_nodes(radius=0.3, ratio_of_nodes = 0.3): """ marks some areas of the mesh as areas where there is stimulated exitation. radius is the size of the node areas ratio of nodes is the amount of nodes you want, divided by the number of nodes found by the purkinje simulation. """ marks_vector = np.zeros(fenics_ordered_coordinates.shape[0]) E, N, left, distance_lv, terminal_lv = call_tree.get_left() E, N, right, distance_rv, terminal_rv = call_tree.get_right() ratio_of_discarded_nodes = 1-ratio_of_nodes coin_rv = np.random.random(len(terminal_rv)) terminal_rv = terminal_rv*coin_rv terminal_rv = (terminal_rv > ratio_of_discarded_nodes)*1.0 coin_lv = np.random.random(len(terminal_lv)) terminal_lv = terminal_lv*coin_lv terminal_lv = (terminal_lv > ratio_of_discarded_nodes)*1.0 r0=0.05 r1=0.3 C = fenics_ordered_coordinates # short hand #left ventricle: terminals = terminal_lv + terminal_rv terminal_idx = np.argwhere(terminals) terminal_coor = N[terminal_idx] terminal_coor = np.reshape(terminal_coor, (terminal_coor.shape[0], terminal_coor.shape[2])) distvec = np.zeros(terminal_coor.shape) BZ = np.zeros(C.shape[0]) distr = np.zeros(terminal_coor.shape[0]) for i in range(C.shape[0]): distvec = C[i,:] - terminal_coor distr = np.sum(distvec**2,axis=1) dist = np.min(distr) r = np.sqrt(dist) BZ[i] = ((r1-r)/(r1-r0)).clip(-1,1) return BZ
def find_leaf_nodes(radius=0.3, ratio_of_nodes=0.3):
"""
marks some areas of the mesh as areas where there is stimulated exitation.
radius is the size of the node areas
ratio of nodes is the amount of nodes you want, divided by the number of nodes
found by the purkinje simulation.
"""
marks_vector = np.zeros(fenics_ordered_coordinates.shape[0])
E, N, left, distance_lv, terminal_lv = call_tree.get_left()
E, N, right, distance_rv, terminal_rv = call_tree.get_right()
ratio_of_discarded_nodes = 1 - ratio_of_nodes
coin_rv = np.random.random(len(terminal_rv))
terminal_rv = terminal_rv * coin_rv
terminal_rv = (terminal_rv > ratio_of_discarded_nodes) * 1.0
coin_lv = np.random.random(len(terminal_lv))
terminal_lv = terminal_lv * coin_lv
terminal_lv = (terminal_lv > ratio_of_discarded_nodes) * 1.0
r0 = 0.05
r1 = 0.3
C = fenics_ordered_coordinates # short hand
#left ventricle:
terminals = terminal_lv + terminal_rv
terminal_idx = np.argwhere(terminals)
terminal_coor = N[terminal_idx]
terminal_coor = np.reshape(
terminal_coor, (terminal_coor.shape[0], terminal_coor.shape[2]))
distvec = np.zeros(terminal_coor.shape)
BZ = np.zeros(C.shape[0])
distr = np.zeros(terminal_coor.shape[0])
for i in range(C.shape[0]):
distvec = C[i, :] - terminal_coor
distr = np.sum(distvec**2, axis=1)
dist = np.min(distr)
r = np.sqrt(dist)
BZ[i] = ((r1 - r) / (r1 - r0)).clip(-1, 1)
return BZ
from dolfin import *
import sys
import os
import numpy as np
parentdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, parentdir)
from monodomain_solver import *
sys.path.insert(0, '../purkinje/python/')
import call_tree
E, N, left, distance_lv, terminal_lv = call_tree.get_left()
E, N, right, distance_rv, terminal_rv = call_tree.get_right()
mesh = Mesh('heart.xml')
#plot(mesh, axes=True, grid=True)
print terminal_rv.shape, E.shape, N.shape, mesh.coordinates().shape
mesh = Mesh('meshes/reference.xml')
meshfunc = MeshFunction('double', mesh, 'meshes/rv.attr0.xml')
#plot(meshfunc)
#interactive()
radius = 0.1
V = FunctionSpace(mesh, 'CG', 1)
coordinates = mesh.coordinates()
from dolfin import *
import sys
import os
import numpy as np
parentdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0,parentdir)
from monodomain_solver import *
sys.path.insert(0, '../purkinje/python/')
import call_tree
E, N, left, distance_lv, terminal_lv = call_tree.get_left()
E, N, right, distance_rv, terminal_rv = call_tree.get_right()
mesh = Mesh('heart.xml')
#plot(mesh, axes=True, grid=True)
print terminal_rv.shape, E.shape, N.shape, mesh.coordinates().shape
mesh = Mesh('meshes/reference.xml')
meshfunc = MeshFunction('double', mesh, 'meshes/rv.attr0.xml')
#plot(meshfunc)
#interactive()
radius = 0.1
V = FunctionSpace(mesh, 'CG', 1)