68f91f03
 Pavel Govyadinov
added fibernet fo...
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# -*- coding: utf-8 -*-
"""
Created on Sat Jan 19 2018
@author: Jiabing
"""
import struct
import numpy as np
import scipy as sp
import networkx as nx
import matplotlib.pyplot as plt
import math
from mpl_toolkits.mplot3d import Axes3D
from itertools import chain
class Node:
def __init__(self, point, outgoing, incoming):
self.p = point
self.o = outgoing
self.i = incoming
class Fiber:
def __init__ (self, indices):
self.indices = indices
class Point:
def __init__(self, x, y, z, r):
self.x = x
self.y = y
self.z = z
self.r = r
class Edge:
def __init__(self, indices_num, pois, radius):
self.indices_num = indices_num
self.points = pois
self.radius = radius
class NWT:
def readVertex(open_file):
points = np.tile(0., 3)
bytes = open_file.read(4)
points[0] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
points[1] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
points[2] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
numO = int.from_bytes(bytes, byteorder='little')
outgoing = np.tile(0, numO)
bts = open_file.read(4)
numI = int.from_bytes(bts, byteorder='little')
incoming = np.tile(0, numI)
for j in range(numO):
bytes = open_file.read(4)
outgoing[j] = int.from_bytes(bytes, byteorder='little')
for j in range(numI):
bytes = open_file.read(4)
incoming[j] = int.from_bytes(bytes, byteorder='little')
node = Node(points, outgoing, incoming)
return node
'''
Reads a single fiber from an open file and returns a Fiber object .
'''
def readFiber(open_file):
bytes = open_file.read(4)
vtx0 = int.from_bytes(bytes, byteorder = 'little')
bytes = open_file.read(4)
vtx1 = int.from_bytes(bytes, byteorder = 'little')
bytes = open_file.read(4)
numVerts = int.from_bytes(bytes, byteorder = 'little')
pts = []
rads = []
for j in range(numVerts):
point = np.tile(0., 3)
bytes = open_file.read(4)
point[0] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
point[1] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
point[2] = struct.unpack('f', bytes)[0]
bytes = open_file.read(4)
radius = struct.unpack('f', bytes)[0]
pts.append(point)
rads.append(radius)
# F = Fiber(pts)
E = Edge(numVerts, pts, radius)
#E = Edge(pts)
return E
class fibernet:
def __init__(self, filename):
with open(filename, "rb") as file:
header = file.read(72)
bytes = file.read(4)
numVertex = int.from_bytes(bytes, byteorder='little')
bytes = file.read(4)
numEdges = int.from_bytes(bytes, byteorder='little')
#self.P = []
self.F = []
self.N = []
for i in range(numVertex):
node = NWT.readVertex(file)
self.N.append(node)
for i in range( numEdges):
edge = NWT.readFiber(file)
#self.F.append(np.arange(num,num+edge.indices_num,1))
#self.P= chain(self.P, edge.points)
self.F.append(edge.points)
#num += edge.indices_num
def aabb(self):
lower = self.N[0].p.copy()
upper = lower.copy()
for i in self.N:
for c in range(len(lower)):
if lower[c] > i.p[c]:
lower[c] = i.p[c]
if upper[c] < i.p[c]:
upper[c] = i.p[c]
return lower, upper
def distancefield(self, R=(100, 100, 100)):
#generate a meshgrid of the appropriate size and resolution to surround the network
lower, upper = self.aabb() #get the space occupied by the network
x = np.linspace(lower[0], upper[0], R[0]) #get the grid points for uniform sampling of this space
y = np.linspace(lower[1], upper[1], R[1])
z = np.linspace(lower[2], upper[2], R[2])
X, Y, Z = np.meshgrid(x, y, z)
#Z = 150 * numpy.ones(X.shape)
Q = np.stack((X, Y, Z), 3)
d_x = abs(x[1]-x[0]);
d_y = abs(y[1]-y[0]);
d_z = abs(z[1]-z[0]);
dis1 = math.sqrt(pow(d_x,2)+pow(d_y,2)+pow(d_z ,2))
#dx = abs(x[1]-x[0])
#dy = abs(y[1]-y[0])
#dz = abs(z[1]-z[0])
#get a list of all node positions in the network
P = []
for e in self.F[12:13]: #12-17
for p in e:
P.append(p)
for j in range(len(e)-1):
d_t = e[j+1]-e[j]
dis2 = math.sqrt(pow(d_t[0],2)+pow(d_t[1],2)+pow(d_t[2],2))
ins = max(int(d_t[0]/d_x), int(d_t[1]/d_y), int(d_t[2]/d_z))
if( ins>0 ):
ins = ins+1;
for k in range(ins):
p_ins =e[j]+(k+1)*(e[j+1]-e[j])/ins;
P.append(p_ins);
#turn that list into a Numpy array so that we can create a KD tree
P = np.array(P)
#generate a KD-Tree out of the network point array
tree = sp.spatial.cKDTree(P)
#specify the resolution of the ouput grid
# R = (200, 200, 200)
D, I = tree.query(Q)
return D, Q, dis1
'''
##read NWT file
f= fibernet("full_seg.nwt")
#P = tuple(f.P)
plist = f.F
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
xs = []
ys = []
zs = []
for i in range(10):
for j in range(len(F[i])):
xs.append(P[F[i][j]][0])
ys.append(P[F[i][j]][1])
zs.append(P[F[i][j]][2])
#ax.scatter(xs, ys, zs)
#ax = fig.gca(projection='3d')
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
ax.plot(xs, ys, zs, label='center lines')
ax.legend()
plt.savefig('p.png', dpi=100)
plt.show()
'''
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