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python/network.py 9.78 KB
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  # -*- coding: utf-8 -*-
  """
  Created on Sat Sep 16 16:34:49 2017
  
  @author: pavel
  """
  
  import struct
  import numpy as np
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  import scipy as sp
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  import networkx as nx
  import matplotlib.pyplot as plt
  import math
  
  '''
      Definition of the Node class
      Duplicate of the node class in network
      Stores the physical position, outgoing edges list and incoming edges list.
  '''
  class Node:
      def __init__(self, point, outgoing, incoming):
          self.p = point
          self.o = outgoing
          self.i = incoming
  
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  #    def p():
  #        return self.p
  
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  '''
      Definition of the Fiber class.
      Duplicate of the Node class in network
      Stores the starting vertex, the ending vertex, the points array and the radius array
  '''
  class Fiber:
      
      def __init__ (self):
          self.v0 = 0
          self.v1 = 0
          self.points = []
          self.radii = []
          
      def __init__ (self, p1, p2, pois, rads):
          self.v0 = p1
          self.v1 = p2
          self.points = pois
          self.radii = rads
      
      '''
          return the length of the fiber.
      '''        
      def length(self):
          length = 0
          for i in range(len(self.points)-1):
              length = length + math.sqrt(pow(self.points[i][0]- self.points[i+1][0],2) + pow(self.points[i][1]- self.points[i+1][1],2) + pow(self.points[i][2]- self.points[i+1][2],2))
  
          return length
          
      '''
          returns the turtuosity of the fiber.
      '''    
      def turtuosity(self):
          turtuosity = 0
          distance = math.sqrt(math.pow(self.points[0][0]- self.points[len(self.points)-1][0],2) + math.pow(self.points[0][1]- self.points[len(self.points)-1][1],2) + math.pow(self.points[0][2]- self.points[len(self.points)-1][2],2))
          turtuosity = self.length()/distance
          #print(turtuosity)
          
          return turtuosity
          
      '''
          returns the volume of the fiber.
      '''
      def volume(self):
          volume = 0
          for i in range(len(self.points)-1):
              volume = volume + 1.0/3.0 * math.pi * (math.pow(self.radii[i],2) + math.pow(self.radii[i+1],2) + self.radii[i]*self.radii[i+1]) * math.sqrt(math.pow(self.points[i][0]- self.points[i+1][0],2) + math.pow(self.points[i][1]- self.points[i+1][1],2) + math.pow(self.points[i][2]- self.points[i+1][2],2))
  
          #print(volume)
          return volume
  '''
      Writes the header given and open file descripion, number of verticies and number of edges.
  '''
  def writeHeader(open_file, numVerts, numEdges):
      txt = "nwtFileFormat fileid(14B), desc(58B), #vertices(4B), #edges(4B): bindata"
      b = bytearray()
      b.extend(txt.encode())
      open_file.write(b)
      open_file.write(struct.pack('i', numVerts))
      open_file.write(struct.pack('i', numEdges))
      
  
  '''
      Writes a single vertex to a file.
  '''
  def writeVertex(open_file, vertex):
      open_file.write(struct.pack('<f',vertex.p[0]))
      open_file.write(struct.pack('<f',vertex.p[1]))
      open_file.write(struct.pack('<f',vertex.p[2]))
      open_file.write(struct.pack('i', len(vertex.o)))
      open_file.write(struct.pack('i', len(vertex.i)))
      for j in range(len(vertex.o)):
          open_file.write(struct.pack('i',vertex.o[j]))
          
      for j in range(len(vertex.i)):
          open_file.write(struct.pack('i', vertex.i[j]))    
          
      return
  
  '''
      Writes a single fiber to a file.
  '''
  def writeFiber(open_file, edge):
      open_file.write(struct.pack('i',edge.v0))
      open_file.write(struct.pack('i',edge.v1))
      open_file.write(struct.pack('i',len(edge.points)))
      for j in range(len(edge.points)):
          open_file.write(struct.pack('<f', edge.points[j][0]))
          open_file.write(struct.pack('<f', edge.points[j][1]))
          open_file.write(struct.pack('<f', edge.points[j][2]))
          open_file.write(struct.pack('<f', edge.radii[j]))
          
      return
  
  '''
      Writes the entire network to a file in str given the vertices array and the edges array.
  '''
  def exportNWT(str, vertices, edges):
      with open(str, "wb") as file:
          writeHeader(file, len(vertices), len(edges))
          for i in range(len(vertices)):
              writeVertex(file, vertices[i])
              
          for i in range(len(edges)):
              writeFiber(file, edges[i])
              
      return
  
  
  '''
      Reads a single vertex from an open file and returns a node Object.
  '''
  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(vtx0, vtx1, pts, rads)
          
      return F
  
  '''
      Imports a NWT file at location str.
      Returns a list of Nodes objects and a list of Fiber objects.
  '''
  def importNWT(str):
      with open(str, "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')
          
          nodeList = []
          fiberList = []
          for i in range(numVertex):
              node = readVertex(file)
              nodeList.append(node)
  
          for i in range(numEdges):
              edge = readFiber(file)
              fiberList.append(edge)
          
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      #exportNWT("/home/pavel/Documents/Python/NetLayout/from_python_seg.nwt", nodeList, fiberList)        
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      print(str)
      return nodeList, fiberList;
      
  '''
  Creates a graph from a list of nodes and a list of edges.
  Uses edge length as weight.
  Returns a NetworkX Object.
  '''
   
  def createLengthGraph(nodeList, edgeList):
      G = nx.Graph()
      for i in range(len(nodeList)):
          G.add_node(i, p=V[i].p)
      for i in range(len(edgeList)):
          G.add_edge(edgeList[i].v0, edgeList[i].v1, weight = E[i].length())
          
      return G
      
  '''
  Creates a graph from a list of nodes and a list of edges.
  Uses edge turtuosity as weight.
  Returns a NetworkX Object.
  '''    
  def createTortuosityGraph(nodeList, edgeList):
      G = nx.Graph()
      for i in range(len(nodeList)):
          G.add_node(i, p=V[i].p)
      for i in range(len(edgeList)):
          G.add_edge(edgeList[i].v0, edgeList[i].v1, weight = E[i].turtuosity())
          
      return G
      
      
  '''
  Creates a graph from a list of nodes and a list of edges.
  Uses edge volume as weight.
  Returns a NetworkX Object.
  '''    
  def createVolumeGraph(nodeList, edgeList):
      G = nx.Graph()
      for i in range(len(nodeList)):
          G.add_node(i, p=V[i].p)
      for i in range(len(edgeList)):
          G.add_edge(edgeList[i].v0, edgeList[i].v1, weight = E[i].volume())
          
      return G
  '''
  Returns the positions dictionary for the Circular layout.
  '''    
  def getCircularLayout(graph, dim, radius):
      return nx.circular_layout(graph, dim, radius)
  
  '''
  Return the positions dictionary for the Spring layout.
  '''    
  def getSpringLayout(graph, pos, iterations, scale):
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      return nx.spring_layout(graph, 2, None, pos, iterations, 'weight', scale, None)
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  '''
  Draws the graph.
  '''        
  def drawGraph(graph, pos):
      nx.draw(graph, pos)
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      return
  
  def aabb(nodeList, edgeList):
  
      lower = nodeList[0].p.copy()
      upper = lower.copy()
      for i in nodeList:
          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
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  #calculate the distance field at a given resolution
  #   R (triple) resolution along each dimension
  def distancefield(nodeList, edgeList, R=(100, 100, 100)):
      
      #get a list of all node positions in the network
      P = []
      for e in edgeList:
          for p in e.points:
              P.append(p)
              
      #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)
      
      plt.scatter(P[:, 0], P[:, 1])
      
      #specify the resolution of the ouput grid
      R = (200, 200, 200)
      
      #generate a meshgrid of the appropriate size and resolution to surround the network
      lower, upper = aabb(nodeList, edgeList)           #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, I = tree.query(Q)
      
      return D