def minor_road(vertex, b):

    #Sammelt Numerische Werte aus Variables-Objekt
    pForward=singleton.minor_roadpForward
    pTurn=singleton.minor_roadpTurn
    lMin=singleton.minor_roadlMin
    lMax=singleton.minor_roadlMax


    suggested_vertices=[]


    #Berechnet den Vektor des letzten Weges zu diesem Punkt

    previous_vector=np.array(vertex.coords-vertex.neighbours[len(vertex.neighbours)-1].coords)
    previous_vector=previous_vector/np.linalg.norm(previous_vector)
    n=np.array([-previous_vector[1], previous_vector[0]])
    #Geradeaus
    v=random.uniform(lMin, lMax)*previous_vector
    random_number=random.randint(0, 100)
    if random_number<pForward*b:
        k=Vertex(vertex.coords+v)
        #k.neighbours.append(vertex)
        k.minor_road=True
        suggested_vertices.append(k)

    #Rechts
    v=random.uniform(lMin, lMax)*previous_vector
    random_number=random.randint(0, 100)
    if random_number<pTurn*b:
        k=Vertex(vertex.coords+n)
        #k.neighbours.append(vertex)
        k.minor_road=True
        suggested_vertices.append(k)

    #Links
    v=random.uniform(lMin, lMax)*previous_vector
    random_number=random.randint(0, 100)
    if random_number<pTurn*b:
        k=Vertex(vertex.coords-n)
        #k.neighbours.append(vertex)
        k.minor_road=True
        suggested_vertices.append(k)

    return suggested_vertices
Exemplo n.º 2
0
def minor_road(vertex, b):

    # Sammelt Numerische Werte aus Variables-Objekt
    pForward = singleton.minor_roadpForward
    pTurn = singleton.minor_roadpTurn
    lMin = singleton.minor_roadlMin
    lMax = singleton.minor_roadlMax

    suggested_vertices = []

    # Berechnet den Vektor des letzten Weges zu diesem Punkt

    previous_vector = np.array(vertex.coords -
                               vertex.neighbours[len(vertex.neighbours) -
                                                 1].coords)
    previous_vector = previous_vector / np.linalg.norm(previous_vector)
    n = np.array([-previous_vector[1], previous_vector[0]])
    # Geradeaus
    v = random.uniform(lMin, lMax) * previous_vector
    random_number = random.randint(0, 100)
    if random_number < pForward * b:
        k = Vertex(vertex.coords + v)
        # k.neighbours.append(vertex)
        k.minor_road = True
        suggested_vertices.append(k)

    # Rechts
    v = random.uniform(lMin, lMax) * previous_vector
    random_number = random.randint(0, 100)
    if random_number < pTurn * b:
        k = Vertex(vertex.coords + n)
        # k.neighbours.append(vertex)
        k.minor_road = True
        suggested_vertices.append(k)

    # Links
    v = random.uniform(lMin, lMax) * previous_vector
    random_number = random.randint(0, 100)
    if random_number < pTurn * b:
        k = Vertex(vertex.coords - n)
        # k.neighbours.append(vertex)
        k.minor_road = True
        suggested_vertices.append(k)

    return suggested_vertices
Exemplo n.º 3
0
def seed(vertex,b):
	
	pSeed=singleton.pSeed
	lMin=singleton.seedlMin
	lMax=singleton.seedlMax
	
	suggested_vertices=[]
	
	l=len(vertex.neighbours)
	v1=rotate(90,vertex.neighbours[0].coords-vertex.coords)
	v2=None
	if l==1:
		v2=v1
	elif l==2:
		v2=rotate(90,vertex.neighbours[1].coords-vertex.coords)*-1
	else:
		return []
	v1=v1/np.linalg.norm(v1)
	v2=v2/np.linalg.norm(v2)
	#Rechts
	if b*b*pSeed>np.random.randint(0,100):
		l=np.random.uniform(lMin,lMax)
		k=np.random.uniform(0,1)
		coords=((1-k)*v1+k*v2)*l
		k=Vertex(vertex.coords+coords)
		k.minor_road=True
		suggested_vertices.append(k)
	
	
	v1=v1*-1
	v2=v2*-1
	
	#Links
	if 	b*b*pSeed>np.random.randint(0,100):
		l=np.random.uniform(lMin,lMax)
		k=np.random.uniform(0,1)
		coords=((1-k)*v1+k*v2)*l
		k=Vertex(vertex.coords+coords)
		k.minor_road=True
		suggested_vertices.append(k)
	
	return suggested_vertices
Exemplo n.º 4
0
def seed(vertex, b):

    pSeed = singleton.pSeed
    lMin = singleton.seedlMin
    lMax = singleton.seedlMax

    suggested_vertices = []

    l = len(vertex.neighbours)
    v1 = rotate(90, vertex.neighbours[0].coords - vertex.coords)
    v2 = None
    if l == 1:
        v2 = v1
    elif l == 2:
        v2 = rotate(90, vertex.neighbours[1].coords - vertex.coords) * -1
    else:
        return []
    v1 = v1 / np.linalg.norm(v1)
    v2 = v2 / np.linalg.norm(v2)
    #Rechts
    if b * b * pSeed > np.random.randint(0, 100):
        l = np.random.uniform(lMin, lMax)
        k = np.random.uniform(0, 1)
        coords = ((1 - k) * v1 + k * v2) * l
        k = Vertex(vertex.coords + coords)
        k.minor_road = True
        suggested_vertices.append(k)

    v1 = v1 * -1
    v2 = v2 * -1

    #Links
    if b * b * pSeed > np.random.randint(0, 100):
        l = np.random.uniform(lMin, lMax)
        k = np.random.uniform(0, 1)
        coords = ((1 - k) * v1 + k * v2) * l
        k = Vertex(vertex.coords + coords)
        k.minor_road = True
        suggested_vertices.append(k)

    return suggested_vertices
def reconstruct(path=None):
	
	if path is None:
		import os
		import procedural_city_generation
		path=os.path.dirname(procedural_city_generation.__file__)+"/outputs/output.json"
		
	import json
	try:
		with open(path,'r') as d:
			data=d.read()
	except IOError:
		print "Input could not be located. Try to run the previous program in the chain first."
		return 0
	data=json.loads(data)
	
	from procedural_city_generation.roadmap.Vertex import Vertex
	import numpy as np
	vertex_list=[]
	
	vertex_list=[0]*len(data)
	
	
	for x in data:
		y=data[x]
		k=Vertex(np.array(y[0]))
		k.minor_road,k.seed,k.neighboursindizes=y[1],y[2],y[3]
		vertex_list[int(x)]=k
	
	
	index=0
	for k in vertex_list:
		for x in k.neighboursindizes:
			k.neighbours.append(vertex_list[x])
		k.selfindex=index
		index+=1
		
			
	setliste=[]
	
	
	return vertex_list
Exemplo n.º 6
0
def reconstruct(path=None):
	
	if path is None:
		import os
		import procedural_city_generation
		path=os.path.dirname(procedural_city_generation.__file__)+"/outputs/output.json"
		
	import json
	try:
		with open(path,'r') as d:
			data=d.read()
	except IOError:
		print "Input could not be located. Try to run the previous program in the chain first."
		return 0
	data=json.loads(data)
	
	from procedural_city_generation.roadmap.Vertex import Vertex
	import numpy as np
	vertex_list=[]
	
	vertex_list=[0]*len(data)
	
	
	for x in data:
		y=data[x]
		k=Vertex(np.array(y[0]))
		k.minor_road,k.seed,k.neighboursindizes=y[1],y[2],y[3]
		vertex_list[int(x)]=k
	
	
	index=0
	for k in vertex_list:
		for x in k.neighboursindizes:
			k.neighbours.append(vertex_list[x])
		k.selfindex=index
		index+=1
		
			
	setliste=[]
	
	
	return vertex_list