def __init__(self, v0=[0, 40], v1=[40, 40], v2=[10, 0]):
if (self.__checkPoint(v0) or self.__checkPoint(v1)
or self.__checkPoint(v2)):
print("input point error")
return 0
self.v = [v0, v1, v2]
self.x_min = min(v0[0], v1[0], v2[0])
self.x_max = max(v0[0], v1[0], v2[0])
self.y_min = min(v0[1], v1[1], v2[1])
self.y_max = max(v0[1], v1[1], v2[1])
self.edge = [
edge.edge(self.v[1], self.v[2]),
edge.edge(self.v[0], self.v[2]),
edge.edge(self.v[0], self.v[1])
]
if (self.edge[0].len >= max(self.edge[1].len, self.edge[2].len)):
self.longEdge = self.edge[0]
self.longVtx = [self.v[0], self.v[1], self.v[2]]
elif (self.edge[1].len >= self.edge[2].len):
self.longEdge = self.edge[1]
self.longVtx = [self.v[1], self.v[2], self.v[0]]
else:
self.longEdge = self.edge[2]
self.longVtx = [self.v[2], self.v[0], self.v[1]]
return
def triangle_triangle_intersect(self,triangle,includeboundary=True,errtol=1e-12):
#This method returns whether an inputted triangle intersects the triangle object or not.
#Distinction is made whether to include the boundaries of the triangle objects or not.
if len(self.edges)==0:
self.edges=[edge(self.points[0],self.points[1]),edge(self.points[0],self.points[2]),edge(self.points[1],self.points[2])]
if len(triangle.edges)==0:
triangle.edges=[edge(triangle.points[0],triangle.points[1]),edge(triangle.points[0],triangle.points[2]),edge(triangle.points[1],triangle.points[2])]
return any([triangle.edge_triangle_intersect(e,includeboundary=includeboundary,errtol=errtol) for e in self.edges]) or any([self.edge_triangle_intersect(e,includeboundary=includeboundary,errtol=errtol) for e in triangle.edges])
def edge_triangle_intersect(self,edgeVar,includeboundary=True,errtol=1e-12):
#This method returns whether an edge intersects the triangle object or not.
#Distinction is made whether to include the boundaries of the triangle and edge objects or not.
if len(self.edges)==0:
self.edges=[edge(self.points[0],self.points[1]),edge(self.points[0],self.points[2]),edge(self.points[1],self.points[2])]
if includeboundary:
if any([self.point_triangle_intersect(p,errtol=errtol) for p in edgeVar.points]):
return True
else:
if any([edgeVar.edge_edge_intersect(e,errtol=errtol) for e in self.edges]):
return True
return False
else:
if any([self.point_triangle_intersect(p,includeboundary=False,errtol=errtol) for p in edgeVar.points]):
return True
else:
p1bool1=any([e.point_edge_intersect(edgeVar.points[0],errtol=errtol) for e in self.edges])
p1bool2=any([p.is_point(edgeVar.points[0]) for p in self.points])
if p1bool1 and not p1bool2:
state1=1
elif p1bool2:
state1=2
else:
state1=3
p2bool1=any([e.point_edge_intersect(edgeVar.points[1],errtol=errtol) for e in self.edges])
p2bool2=any([p.is_point(edgeVar.points[1]) for p in self.points])
if p2bool1 and not p2bool2:
state2=1
elif p2bool2:
state2=2
else:
state2=3
state=state1*state2
if state==1 or state==2:
if any([e.point_edge_intersect(edgeVar.points[0],errtol=errtol) and e.point_edge_intersect(edgeVar.points[1],errtol=errtol) for e in self.edges]):
return False
else:
return True
elif state==3:
if any([self.edges[0].point_edge_intersect(p,errtol=errtol) for p in edgeVar.points]):
return self.edges[1].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol) or self.edges[2].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol)
elif any([self.edges[1].point_edge_intersect(p,errtol=errtol) for p in edgeVar.points]):
return self.edges[0].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol) or self.edges[2].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol)
else:
return self.edges[0].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol) or self.edges[1].edge_edge_intersect(edgeVar,includeboundary=False,errtol=errtol)
elif state==6:
return any([edgeVar.edge_edge_intersect(e,includeboundary=False,errtol=errtol) for e in self.edges])
elif state==9:
if any([edgeVar.edge_edge_intersect(e,includeboundary=False,errtol=errtol) for e in self.edges]):
return True
return False
def generateKeywordGraph(self, searchResult, kw):
art = ArticleNode()
dummyThiccGraph = {'nodes': [], 'edges': []}
nodeList = []
edgelist = []
xie = 0
yie = 0
#print("graphGenerator: " + str(searchResult))
for x in searchResult:
xie += 1
yie += 1
randColor = "#{:06x}".format(random.randint(0, 0xFFFFFF))
testNode = node(str(x), str(x), 2, random.randint(-100, 100),
random.randint(-100, 100), randColor)
nodeList.append(testNode)
for z in searchResult[x]:
if (x == "Undefined"):
articleNode = node(str(z), str(z), 1,
random.randint(-100, 100),
random.randint(-100, 100), randColor)
nodeList.append(articleNode)
articleEdge = edge(str(z), str(x))
edgelist.append(articleEdge)
print("Category: " + str(x) + " article: " + str(z))
else:
label = "Title: " + str(
z.getTitle()) + " ArticleID: " + str(
z.getInfo()) + " SubCategory: " + str(
z.getSubCat())
articleNode = node(str(z.getInfo()), label, 1,
random.randint(-100, 100),
random.randint(-100, 100), randColor)
nodeList.append(articleNode)
articleEdge = edge(str(z.getInfo()), str(x))
edgelist.append(articleEdge)
print("Category: " + str(x) + " article: " +
str(z.getInfo()))
randColor0 = "#{:06x}".format(random.randint(0, 0xFFFFFF))
nodObj = node(kw, kw, 3, 0, 0, randColor0)
nodeList.insert(0, nodObj)
for x in searchResult:
testEdge = edge(str(x), kw)
edgelist.append(testEdge)
dummyThiccGraph['nodes'] = [node.__dict__ for node in nodeList]
dummyThiccGraph['edges'] = [edge.__dict__ for edge in edgelist]
output = dummyThiccGraph
print(dummyThiccGraph['nodes'])
with open(os.path.join('static', 'testjson.json'), 'w') as outfile:
outfile.write(json.dumps(output, indent=4))
return output
def addEdge(self, ed, w = 1.0, d = False):
if not ed:
return
if self.isEdgePresent(ed):
return
if type(ed) == str:
e = ed.split()
h = self.getNode(e[0])
t = self.getNode(e[1])
if not h:
self.addNode(e[0])
h = self.getNode(e[0])
if not t:
self.addNode(e[1])
t = self.getNode(e[1])
ed = edge.edge(e[0], e[1], w, d)
h.addEdge(ed)
t.addEdge(ed)
else:
h = self.getNode(ed.head)
t = self.getNode(ed.tail)
if not h:
self.addNode(ed.head)
h = self.getNode(ed.head)
if not t:
self.addNode(ed.tail)
t = self.getNode(ed.tail)
h.addEdge(ed)
t.addEdge(ed)
self.edges.append(ed)
self.numedges += 1
return
def createEdgeObjects(verticeList):
edgeList =[]
for u in verticeList:
neighborList = u.get_neighbors()
for n in neighborList:
newEdge = edge(u, n[0], n[1])
edgeList.append(newEdge)
return edgeList
def reverseEdge(self, ed):
h = ed.tail
t = ed.head
d = ed.directed
w = ed.weight
self.removeEdge(ed)
self.addEdge(edge.edge(h, t, w, d))
return
def generate(branch):
pushMatrix()
x = branch.x
y = branch.y
sz = branch.sz
cnt = branch.cnt
a = branch.a
translate(x, y)
line(0, 0, 0, -sz)
if cnt < total:
translate(0, -sz)
rotate(a)
e1 = Edge.edge(0, 0, sz * (0.67), cnt + 1, a, total)
generate(e1)
rotate(2 * -a)
e2 = Edge.edge(0, 0, sz + (0.67), cnt + 1, a, total)
generate(e1)
popMatrix()
def add_edge(self, u, v, w=0):
if u == v:
raise ValueError("u == v")
self.e += 1
#define two edges u->v and v->u
e = edge(u,v,w)
re = edge(v,u,0)
#adding reverse edge
e.re = re
re.re = e
#add edges
self.adj_list[u].append(e)
self.adj_list[v].append(re)
#setting default flows
self.flow[e]=0
self.flow[re]=0
def create_edge (self, label=""):
'''
Convenience routine for creating an edge between the last two added nodes.
'''
if not len(self.history) == 2:
return
e = edge(self.history[0].id, self.history[1].id, label)
self.add_edge(e)
return e
def create_edge(self, label=""):
'''
Convenience routine for creating an edge between the last two added nodes.
'''
if not len(self.history) == 2:
return
e = edge(self.history[0].id, self.history[1].id, label)
self.add_edge(e)
return e
def createGraph(self, edgelist, numnodes = -1):
if not numnodes == -1:
for i in range(1, numnodes + 1):
self.addNode(str(i))
for i in edgelist:
if not i:
break
ed = i.split()
#if self.isEdgePresent(ed[0] + " " + ed[1]):
# continue
#if not self.getNode(ed[0]):
# self.addNode(node.node(ed[0]))
#if not self.getNode(ed[1]):
# self.addNode(node.node(ed[1]))
if self.weighted:
e = edge.edge(ed[0], ed[1], float(ed[2]), self.directed)
else:
e = edge.edge(ed[0], ed[1], directed = self.directed)
self.addEdge(e)
return
def getEdgeList(self, prov_json_file):
edgeJsonList = []
edgeLabel = []
loopCounter = 0
edgeList = []
json_data = open(prov_json_file).read()
provJsonData = json.loads(json_data)
#finds edge labes with names wasAssociatedWith,
#wasGeneratedBy, and used...
edge_label = ['wasAssociatedWith', 'wasGeneratedBy', 'used']
# edgeJsonList.append(provJsonData['wasAssociatedWith'])
# edgeJsonList.append(provJsonData['wasGeneratedBy'])
# edgeJsonList.append(provJsonData['used'])
for label in edge_label:
if label in provJsonData:
edgeJsonList.append(provJsonData[label])
#list of edge label values
edgeLabel.append('wasAssociatedWith')
edgeLabel.append('wasGeneratedBy')
edgeLabel.append('used')
#print(edgeLabel)
#creates an edge object with the source and destionation nodes
#from the prov json graph and stores the edge object in a list.
for i in range(len(edgeJsonList)):
for data, value in edgeJsonList[i].items():
key_list = list(value.keys())
destination_node = value[key_list[0]]
source_node = value[key_list[1]]
#creates edge objects
edgeVal = edge(source_node, destination_node, edgeLabel[i])
#print(edgeVal.toString())
#adds edge to a list
#print(loopCounter)
edgeList.append(edgeVal)
#loopCounter += 1
return edgeList
def set_weight_undirect_graph(graph):
e1 = edge(0,1,0.1)
e2 = edge(0,2,0.5)
e3 = edge(0,3,0.2)
e4 = edge(1,2,0.1)
e5 = edge(1,3,1.1)
e6 = edge(2,3,0.1)
e7 = edge(2,4,1.5)
e8 = edge(3,4,0.3)
graph.add_edge(e1)
graph.add_edge(e2)
graph.add_edge(e3)
graph.add_edge(e4)
graph.add_edge(e5)
graph.add_edge(e6)
graph.add_edge(e7)
graph.add_edge(e8)
def draw_line():
global node_set, eid
A = simpledialog.askinteger("Input Node A", "Input Node A ID")
B = simpledialog.askinteger("Input Node B", "Input Node B ID")
weight = simpledialog.askinteger("Weight", "Input Weight")
nodeA = search_node(A, node_set)
nodeB = search_node(B, node_set)
if (nodeA and nodeB):
new_edge = edge(eid, nodeA, nodeB, weight)
eid += 1
new_edge.draw(canvas)
if(cycle_detect(nodeA, nodeB)):
messagebox.showinfo("Cycle", "Oops, a Cycle")
nodeA.connect(nodeB)
append_tree(nodeA.getTree())
nodeA.getTree().add_edge(new_edge)
def edge_list_create(self, vectorlist):
# This is a helper function to run the Kruskal algorithm. It creates edge objects from the adjacency
# matrix of the graph. These edge objects hold the weight of each edge, along with pointer to their start
# and ending vector objects.
#
# Since the graph is undirected, the actual order of these vectors is not important. However,
# if one wanted to apply another algorithmic approach to finding a minimum spanning tree within a graph
# this could be useful.
# Initialize an empty list
edgelist = []
# Create a copy of the adjacency matrix dimensions with a False boolean in all positions.
# This matrix will be used to ensure that duplicate edges are not added to our edgelist. This is
# useful for the Kruskal algorithm as we can override the standard compare function (cmp) to
# sort the edgelist, and since it will have no duplicates, we can sort it without having to do
# any additional steps
edge_check = [[False for x in range(self.max_vert)]
for y in range(self.max_vert)]
# Initialize integer for looping
i = 0
# For each vertex in the simple graph do the following:
while i < self.max_vert:
# Get a list of adjacent vertices
for x in self.get_adjacent(i):
# Check to see if the edge has already been added
if edge_check[i][x] == False:
# If it has not, create a new edge and add it to the edge list
new_edge = edge(self.ad_matrix[i][x], vectorlist[i],
vectorlist[x])
edgelist.append(new_edge)
# Mark both edges in the matrix as true, so a duplicate will not be added
edge_check[i][x] == True
edge_check[x][i] == True
# Increase constant i to move onto the next position in the main adjacency matrix
i += 1
# Return the created edgelist that has no duplicate edge objects
return edgelist
def __createEdgesDictionary(self, v1, v2, create=True):
newEdge = False
v1Id = v1.getId()
v2Id = v2.getId()
if v2Id not in self.__edges[v1Id]:
self.__edges[v1Id] = {}
self.__edges[v1Id][v2Id] = {}
newEdge = True
if v1Id not in self.__edges[v2Id]:
newEdge = True
if create == False:
self.__edges[v1Id][v2Id] = {}
if newEdge and create:
a = edge.edge(v1, v2)
self.__edges[v1Id][v2Id] = a
self.__edges[v2Id][v1Id] = a
v1.addEdge(a)
v2.addEdge(a)
self.__edgeslist.append(a)
return self.__edges[v1Id][v2Id]
def drawSpin(self, color='b', linewidth=1.0, lineratio=1.0):
currT = self.origT
width = linewidth
for i in range(self.iter):
ratioX = abs(currT.v[1][0] - currT.v[2][0])*self.ratio
ratioY = abs(currT.v[1][1] - currT.v[2][1])*self.ratio
if(currT.v[1][0] > currT.v[2][0]):
newX = currT.v[1][0] - ratioX
else:
newX = currT.v[1][0] + ratioX
if(currT.v[1][1] > currT.v[2][1]):
newY = currT.v[1][1] - ratioY
else:
newY = currT.v[1][1] + ratioY
newPoint = [newX, newY]
newEdge = edge.edge(currT.v[0], newPoint)
newEdge.draw(color, width)
width = width*lineratio
newT = triangle.triangle(newPoint, currT.v[2], currT.v[0])
currT = newT
return
def getEdgeList(self, prov_json_file):
"""Converts a provenance graph file into an edge list.
Creates a list of labeled, directed edges.
"""
edgeList = []
json_data = None
with open(prov_json_file) as json_file:
json_data = json_file.read()
provJsonData = json.loads(json_data)
# For edge labels given (wAW, wGB, u), create an edge object with
# the source and destination nodes from the prov json graph and
# store the edges in a list.
edge_label = ['wasAssociatedWith', 'wasGeneratedBy', 'used']
for label in edge_label:
for data, value in provJsonData[label].items():
keys = value.keys()
destination_node = value[keys[0]]
source_node = value[keys[1]]
edgeVal = edge(source_node, destination_node, label)
edgeList.append(edgeVal)
return edgeList
def _insert_Vertex_Delaunay_(point, P, E, T):
#This method inserts a vertex into already Delaunay triangulation so that the triangulation remains Delaunay.
#The method first checks if the point has not been added before.
matchbool = False
for p in P:
if p.is_point(point):
matchbool = True
break
if not matchbool:
polyedges = []
staredges = []
constraintpolypoints = []
#The method sees if the new point would fall into the circumcircle of any of the already-existing triangles.
#The method then deletes those triangles.
for i in range(len(T) - 1, -1, -1):
if T[i].inCircumcircle(point, includeboundary=True):
#Distinction is made whether the new point falls inside a triangle (in which case constraint edges are mostly ignored)...
if T[i].point_triangle_intersect(point):
for j in range(len(T[i].edges)):
if T[i].edges[j].point_edge_intersect(
point, includeboundary=False):
if T[i].edges[j].constraint:
constraintpolypoints += T[i].edges[j].points
break
for e in T[i].edges:
if e not in polyedges:
polyedges.append(e)
for p in T[i].points:
starE = edge(point, p)
if all([not starE.is_edge(elem)
for elem in staredges]):
staredges.append(starE)
for p in T[i].points:
p.triangles.remove(T[i])
for e in T[i].edges:
e.triangles.remove(T[i])
del T[i]
else:
#...or falls outside of a triangle, in which case the triangle is only deleted if the new edges that will be made by the insertion of the new point
#do not intersect any constrained edges.
intersectbool = False
for j, e in enumerate(T[i].edges):
for p in T[i].points:
if not p.is_point(e.points[0]) and not p.is_point(
e.points[1]):
starE = edge(point, p)
if starE.edge_edge_intersect(
e, includeboundary=False):
if all([
not starE.edge_edge_intersect(
elem, includeboundary=False)
for elem in E if elem.constraint
]):
for k in range(j):
if T[i].edges[k] not in polyedges:
polyedges.append(T[i].edges[k])
for k in range(j + 1, 3):
if T[i].edges[k] not in polyedges:
polyedges.append(T[i].edges[k])
for elemP in T[i].points:
starE = edge(point, elemP)
if all([
not starE.is_edge(elem)
for elem in staredges
]):
staredges.append(starE)
intersectbool = True
for elemP in T[i].points:
elemP.triangles.remove(T[i])
for elemE in T[i].edges:
elemE.triangles.remove(T[i])
del T[i]
break
if intersectbool:
break
#When all the necessary triangles have been removed and after some structural clean up...
for i in range(len(polyedges) - 1, -1, -1):
if any([
polyedges[i].edge_edge_intersect(starE,
includeboundary=False)
for starE in staredges
]):
polyedges[i].points[0].edges.remove(polyedges[i])
polyedges[i].points[1].edges.remove(polyedges[i])
E.remove(polyedges[i])
del polyedges[i]
#... a new set of edges is made that connects the new point
#to the rest of the triangulation and a new set of triangles is added
#to the triangulation over the framework of the new connective edges.
for e in polyedges:
e1 = edge(e.points[0], point)
e2 = edge(e.points[1], point)
t = triangle(e.points[0], e.points[1], point)
t.edges = [e]
matchbool = False
for elem in E:
if e1.is_edge(elem):
matchbool = True
t.edges.append(elem)
break
if not matchbool:
if e.points[0] in constraintpolypoints:
e1.constraint = True
E.append(e1)
t.edges.append(e1)
e1.update()
e1.enclosed = True
matchbool = False
for elem in E:
if e2.is_edge(elem):
matchbool = True
t.edges.append(elem)
break
if not matchbool:
if e.points[1] in constraintpolypoints:
e2.constraint = True
E.append(e2)
t.edges.append(e2)
e2.update()
e2.enclosed = True
t.update()
T.append(t)
P.append(point)
del self.edgelist[:]
del self.neighbours[:]
del self.inedgelist[:]
del self.outedgelist[:]
self.degree = self.indegree = self.outdegree = 0
self.colour = "white"
self.visited = "False"
return
if __name__ == "__main__":
print node.__doc__
n1 = node('1')
n2 = node('2')
print "node names", n1.name, n2.name
e = edge.edge('1', '2')
n1.addEdge(e)
e = edge.edge('2', '1')
n2.addEdge(e)
n1.addEdge(edge.edge('5', '1'))
print "degrees", n1.degree, n2.degree
e = edge.edge('4', '1', directed = True)
n1.addEdge(e)
e = edge.edge('1', '7', directed = True)
n1.addEdge(e)
print 'neighbourhood:', n1.getNeighbourhood()
for e in n1.getEdgeList():
print e
n1.removeEdge(edge.edge('1', '7', directed = True))
print 'neighbourhood:', n1.getNeighbourhood()
for e in n1.getEdgeList():
## for i in ops.nodes:
## print i.name, i.degree
## print ops.isNodePresent('1')
## print ops.isNodePresent(node.node('7'))
## print ops.isNodePresent(node.node('3'))
print '****'
#ops.removeNode(node.node('5'))
ops.createGraph(['7 8', '9 10'])
#e1 = edge.edge('1', '2')
#ops.addEdge(e1)
ops.addEdge('4 6')
#ops.addEdge(edge.edge('4', '6'))
print "numedges", ops.numedges
print "numnodes", ops.numnodes
for i in ops.nodes:
print i.name, i.degree
for e in ops.edges:
print e.head, e.tail
print '****'
print "ed: ", ops.isEdgePresent(edge.edge('1', '2'))
ops.removeEdge(edge.edge('1', '2'))
print "numedges", ops.numedges
ops.removeNode(node.node('5'))
for i in ops.edges:
print i.head, i.tail, i.directed, i.weight
for i in ops.nodes:
print i.name, i.degree
ops.resetGraph()
for nd in ops.getNodes():
print 'nd', nd.name
def create_edge( self): return edge()
dc_length=968)
dcc_15_layout = dcc_15.Layout()
dcc_20 = my_dc(gap_inc_vec=[420.0, 430.0, 440.0, 450.0, 460.0],
length_inc_vec=[110, 120, 130],
name="ring6",
width=20.0,
dc_length=988)
dcc_20_layout = dcc_20.Layout()
marker = dicingMarker()
marker_layout = marker.Layout()
marker2 = label()
marker2_layout = marker2.Layout()
marker3 = edge()
marker3_layout = marker3.Layout()
pr = PlaceComponents(
child_cells={
"comp1": dc_10,
"comp2": dc_15,
"comp3": dc_20,
"comp4": dcc_10,
"comp5": dcc_15,
"comp6": dcc_20,
"marker1": marker,
"marker2": marker2,
"marker3": marker3,
})
pr_layout = pr.Layout(
import thirdparty.morphsnakes.morphsnakes as mh
from matplotlib import pyplot as ppl
def circle_levelset(shape, center, sqradius, scalerow=1.0):
"""Build a binary function with a circle as the 0.5-levelset."""
grid = np.mgrid[list(map(slice, shape))].T - center
phi = sqradius - np.sqrt(np.sum((grid.T)**2, 0))
u = np.float_(phi > 0)
return u
img = cv2.imread('../data/interim/spim2/c397.jpg', 0)
filtered = cv2.bilateralFilter(img, 9, 350, 350)
edgeShape = edge.edge(filtered)
k, dst = cv2.threshold(edgeShape, 4, 255, cv2.THRESH_BINARY)
dilate = cv2.erode(dst,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2)),
iterations=1)
closing = cv2.morphologyEx(dilate,
cv2.MORPH_CLOSE,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(11, 11)),
iterations=1)
final = cv2.dilate(closing,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)),
iterations=1)
_, contours, _ = cv2.findContours(final, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
def set_negative_weight_direct_graph(graph):
e1 = edge(0,1,0.1)
e2 = edge(0,2,0.5)
e3 = edge(0,3,-0.2)
e4 = edge(1,2,0.1)
e5 = edge(1,3,1.1)
e6 = edge(2,3,0.1)
e7 = edge(2,4,-1.5)
e8 = edge(3,4,0.3)
e9 = edge(4,3,0.2)
e10 = edge(3,1,10.0)
e11 = edge(2,1,1.1)
graph.add_edge(e1)
graph.add_edge(e2)
graph.add_edge(e3)
graph.add_edge(e4)
graph.add_edge(e5)
graph.add_edge(e6)
graph.add_edge(e7)
graph.add_edge(e8)
graph.add_edge(e9)
graph.add_edge(e10)
graph.add_edge(e11)
def scan_triangulate(P, errtol=1e-12):
#This method executes the scan triangulation algorithm that triangulates points by simply connecting them haphazardly.
N = len(P)
P.sort(key=lambda p: p.x)
E = []
T = []
if N < 2:
return E, T
elif N == 2:
e = edge(P[0], P[1])
e.index = 0
e.update()
E.append(e)
return E, T
else:
#Checks if set of points is colinear
e0 = edge(P[0], P[1])
colinearbool = True
for i in range(2, N):
if abs(e0.cross(edge(P[0], P[i]))) > abs(errtol):
colinearbool = False
break
if colinearbool:
print("Error: point set is colinear, unable to make convex hull")
E = [edge(P[i], P[i + 1]) for i in range(N - 1)]
for i in range(N - 1):
E[i].index = i
return P, E, T
#Makes the first triangle.
startindex = -1
for i in range(2, N):
t0 = triangle(P[0], P[1], P[i])
t0.index = 0
if t0.area() > abs(errtol):
T.append(t0)
e1 = edge(P[0], P[1])
e1.index = 0
e1.update()
e2 = edge(P[0], P[i])
e2.index = 1
e2.update()
e3 = edge(P[1], P[i])
e3.index = 2
e3.update()
t0.edges = [e1, e2, e3]
t0.update()
E = [e1, e2, e3]
startindex = i
P[0].index = 0
P[1].index = 1
P[i].index = 2
break
if startindex == -1:
print("All points are colinear")
else:
point_index = 3
edge_index = 3
tri_index = 1
#Adds more triangles to the triangulation whenever possible.
for i in range(2, N):
if i != startindex:
#Every point is added incrementally to the triangulation.
P[i].index = point_index
point_index += 1
newE = []
newEbool = []
for e in E:
if not e.enclosed:
#An edge is made to the added point and tested to be unique and not crossing any other edge.
e1 = edge(e.points[0], P[i])
match1bool = False
for j in range(len(newE)):
if e1.is_edge(newE[j]):
e1 = newE[j]
e1bool = newEbool[j]
match1bool = True
break
if not match1bool:
e1bool = any([
elem.edge_edge_intersect(e1,
includeboundary=False)
for elem in E
])
#An edge is made to the added point and tested to be uniue and not crossing any other edge.
e2 = edge(e.points[1], P[i])
match2bool = False
for j in range(len(newE)):
if e2.is_edge(newE[j]):
e2 = newE[j]
e2bool = newEbool[j]
match2bool = True
break
if not match2bool:
e2bool = any([
elem.edge_edge_intersect(e2,
includeboundary=False)
for elem in E
])
#If both edges are viable, a new triangle is made.
if not e1bool and not e2bool:
t = triangle(e.points[0], e.points[1], P[i])
t.edges = [e, e1, e2]
if all([
not t.triangle_triangle_intersect(
tri, includeboundary=False)
for tri in T
]):
t.index = tri_index
tri_index += 1
e.enclosed = True
if not match1bool:
e1.update()
newE.append(e1)
newEbool.append(e1bool)
e1.index = edge_index
edge_index += 1
else:
e1.enclosed = True
if not match2bool:
e2.update()
newE.append(e2)
newEbool.append(e2bool)
e2.index = edge_index
edge_index += 1
else:
e2.enclosed = True
t.update()
T.append(t)
E = E + newE
return P, E, T
def addEdge(graph, from_node:int, to_node:int, cost:int):
graph[from_node].append(edge( from_node, to_node, cost))
@author: aldo
"""
#%%
import agent
import edge
from simulGivenRoutes import execute
from getRoutes import getRoutes
from itertools import product
from copy import deepcopy
from ARoptimization import ARoptim
from ExpOptim import updatePosterior
from ExpOptim import generateDraws
#network creation
network=[ [None] * 4 for i in range(4)]
network[0][1]=edge.edge('x')
network[1][2]=edge.edge('x')
network[1][3]=edge.edge('x')
network[3][2]=edge.edge('x')
#agent creation
agents=list()
agents.append(agent.agent(0,2,1))
agents.append(agent.agent(1,2,2))
agents.append(agent.agent(1,2,3))
agents.append(agent.agent(1,2,1))
#%%
#Experience
#sensitivity to New information
delta=0.1
#getting routes and costs
routesAndCosts=getRoutes(network, agents, 10, cost=True)
def convex_hull(P, errtol=1e-12):
#This method executes the quickhull algorithm that computes the convex hull of a number of points.
N = len(P)
if N <= 1:
print(
"Error: Unable to make a convex hull due to lack of sufficient points"
)
return []
elif N == 2:
return [edge(P[0], P[1])]
else:
#Checks if set of points is colinear
e0 = edge(P[0], P[1])
colinearbool = True
for i in range(2, N):
if abs(e0.cross(edge(P[0], P[i]))) > abs(errtol):
colinearbool = False
break
if colinearbool:
print("Error: point set is colinear, unable to make convex hull")
return []
#Finds the left_most and down_most point of the set.
left_anchor = P[0]
for i in range(1, N):
if P[i].x < left_anchor.x:
left_anchor = P[i]
elif P[i].x == left_anchor.x and P[i].y < left_anchor.y:
left_anchor = P[i]
#Finds the right_most and up_most point of the set.
right_anchor = P[0]
for i in range(1, N):
if P[i].x > right_anchor.x:
right_anchor = P[i]
elif P[i].x == right_anchor.x and P[i].y > right_anchor.y:
right_anchor = P[i]
#Finds the farthest points above the line between left_anchor and right_anchor.
farthest_anchor = left_anchor
height = 0
for p in P:
res = -(right_anchor.y - left_anchor.y) * p.x + (
right_anchor.x - left_anchor.x
) * p.y - right_anchor.x * left_anchor.y + right_anchor.y * left_anchor.x
if (right_anchor.x - left_anchor.x) * res > abs(
errtol) and res > height + abs(errtol):
farthest_anchor = p
height = res
#Sorting points that into an upper half, but only focussing on those that dont yet fall into the contructed convex hull.
e0 = edge(left_anchor, right_anchor)
upper_hull = [
edge(left_anchor, farthest_anchor),
edge(farthest_anchor, right_anchor)
]
exterior = []
tri = triangle(left_anchor, farthest_anchor, right_anchor)
tri.edges = [e0] + upper_hull
for p in P:
if not p.is_point(left_anchor) and not p.is_point(
farthest_anchor) and not p.is_point(right_anchor):
res = -(right_anchor.y - left_anchor.y) * p.x + (
right_anchor.x - left_anchor.x
) * p.y - right_anchor.x * left_anchor.y + right_anchor.y * left_anchor.x
if (right_anchor.x - left_anchor.x) * res > abs(
errtol) and not tri.point_triangle_intersect(
p, includeboundary=False):
exterior.append(p)
#Fully constructing the upper convex hull iteratively.
counter = 0
while len(exterior) > 0 and counter < N:
for i in range(len(upper_hull)):
res1 = upper_hull[i].points[1].x - upper_hull[i].points[0].x
if res1 != 0:
#Again finds the farthest points below line between two connected points in the convex hull.
farthest_anchor = upper_hull[i].points[0]
height = 0
for p in exterior:
res2 = -(upper_hull[i].points[1].y -
upper_hull[i].points[0].y) * p.x + (
upper_hull[i].points[1].x -
upper_hull[i].points[0].x
) * p.y - upper_hull[i].points[1].x * upper_hull[
i].points[0].y + upper_hull[i].points[
1].y * upper_hull[i].points[0].x
if res1 * res2 > abs(
errtol) and res2 > height + abs(errtol):
farthest_anchor = p
height = res2
#If there exists a point outside the convex hull, change the hull to include it.
if height > abs(errtol) or not farthest_anchor.is_point(
upper_hull[i].points[0]):
e1 = edge(upper_hull[i].points[0], farthest_anchor)
e2 = edge(farthest_anchor, upper_hull[i].points[1])
upper_hull += [e1, e2]
if height > abs(errtol):
tri = triangle(upper_hull[i].points[0],
upper_hull[i].points[1],
farthest_anchor)
for j in range(len(exterior) - 1, -1, -1):
if tri.point_triangle_intersect(
exterior[j], includeboundary=False):
del exterior[j]
exterior.remove(farthest_anchor)
del upper_hull[i]
break
counter += 1
#Finds the farthest points below the line between left_anchor and right_anchor.
farthest_anchor = right_anchor
height = 0
for p in P:
res = -(right_anchor.y - left_anchor.y) * p.x + (
right_anchor.x - left_anchor.x
) * p.y - right_anchor.x * left_anchor.y + right_anchor.y * left_anchor.x
if (right_anchor.x - left_anchor.x
) * res < -abs(errtol) and res + abs(errtol) < height:
farthest_anchor = p
height = res
#Sorting points that into a lower half, but only focussing on those that dont yet fall into the contructed convex hull.
lower_hull = [
edge(left_anchor, farthest_anchor),
edge(farthest_anchor, right_anchor)
]
exterior = []
tri = triangle(left_anchor, farthest_anchor, right_anchor)
tri.edges = [e0] + lower_hull
for p in P:
if not p.is_point(left_anchor) and not p.is_point(
farthest_anchor) and not p.is_point(right_anchor):
res = -(right_anchor.y - left_anchor.y) * p.x + (
right_anchor.x - left_anchor.x
) * p.y - right_anchor.x * left_anchor.y + right_anchor.y * left_anchor.x
if (right_anchor.x - left_anchor.x
) * res < -abs(errtol) and not tri.point_triangle_intersect(
p, includeboundary=False):
exterior.append(p)
#Fully constructing the lower convex hull iteratively.
counter = 0
while len(exterior) > 0 and counter < N:
for i in range(len(lower_hull)):
res1 = lower_hull[i].points[1].x - lower_hull[i].points[0].x
if res1 != 0:
#Again finds the farthest points below line between two connected points in the convex hull
farthest_anchor = lower_hull[i].points[0]
height = 0
for p in exterior:
res2 = -(lower_hull[i].points[1].y -
lower_hull[i].points[0].y) * p.x + (
lower_hull[i].points[1].x -
lower_hull[i].points[0].x
) * p.y - lower_hull[i].points[1].x * lower_hull[
i].points[0].y + lower_hull[i].points[
1].y * lower_hull[i].points[0].x
if res1 * res2 < -abs(errtol) and res2 + abs(
errtol) < height:
farthest_anchor = p
height = res2
#If there exists a point outside the convex hull, change the hull to include it.
if height < -abs(errtol) or not farthest_anchor.is_point(
lower_hull[i].points[0]):
e1 = edge(lower_hull[i].points[0], farthest_anchor)
e2 = edge(farthest_anchor, lower_hull[i].points[1])
lower_hull += [e1, e2]
if height < -abs(errtol):
tri = triangle(lower_hull[i].points[0],
lower_hull[i].points[1],
farthest_anchor)
for j in range(len(exterior) - 1, -1, -1):
if tri.point_triangle_intersect(
exterior[j], includeboundary=False):
del exterior[j]
exterior.remove(farthest_anchor)
del lower_hull[i]
break
counter += 1
return upper_hull + lower_hull
def delaunize(P, E, T, errtol=1e-12):
#This method takes a triangulation and executes the Lawson Flip algorithm on it to make the triangulation Delaunay.
delaunaybool = False
counter = 0
N = len(E)
while not delaunaybool and counter < N * (N - 1) / 2 + 1:
#While the triangulation it not yet Delaunay...
delaunaybool = True
for e in E:
#...the algorithm finds an edge that is part of two triangles, and sees if the two enclosing triangles need to be flipped.
if e.enclosed:
p1 = e.triangles[0].points[0]
if p1 in e.points:
p1 = e.triangles[0].points[1]
if p1 in e.points:
p1 = e.triangles[0].points[2]
p2 = e.triangles[1].points[0]
if p2 in e.points:
p2 = e.triangles[1].points[1]
if p2 in e.points:
p2 = e.triangles[1].points[2]
#If the two triangles need to be Lawson flipped, the method reworks the triangulation so that the infastructure is maintained
#and the two triangles are now flipped (and therefore are Delaunay).
if e.triangles[0].inCircumcircle(p2):
if all([
abs(
edge(p1, e.points[i]).cross(
edge(p2, e.points[i]))) > abs(errtol)
for i in range(2)
]):
t1 = e.triangles[0]
t2 = e.triangles[1]
for elem in t1.edges:
elem.triangles.remove(t1)
for elem in t1.points:
elem.triangles.remove(t1)
for elem in t2.edges:
elem.triangles.remove(t2)
for elem in t2.points:
elem.triangles.remove(t2)
for elem in e.points:
elem.edges.remove(e)
temppoints = [elem for elem in e.points]
e.points = [p1, p2]
tempt1edges = [
elem for elem in t1.edges if not e.is_edge(elem)
]
tempt2edges = [
elem for elem in t2.edges if not e.is_edge(elem)
]
if tempt1edges[0].edge_edge_intersect(
tempt2edges[0], includeboundary=True):
t1.edges = [tempt1edges[0], tempt2edges[0], e]
t2.edges = [tempt1edges[1], tempt2edges[1], e]
else:
t1.edges = [tempt1edges[0], tempt2edges[1], e]
t2.edges = [tempt1edges[1], tempt2edges[0], e]
if temppoints[0] in tempt1edges[0].points:
t1.points = [p1, p2, temppoints[0]]
t2.points = [p1, p2, temppoints[1]]
else:
t1.points = [p1, p2, temppoints[1]]
t2.points = [p1, p2, temppoints[0]]
t1.update()
t2.update()
e.update()
t1.triagarea = None
t2.triagarea = None
e.edgelength = None
delaunaybool = False
counter += 1
import cv2
import edge
import numpy as np
import scipy.ndimage as nd
from thirdparty.chanvese.chanvese import chanvese
img = nd.imread('../data/interim/spim2/c97.jpg', flatten=True)
edgeShape = edge.edge(
cv2.bilateralFilter(cv2.imread('../data/interim/spim2/c97.jpg', 0), 9, 350,
350))
k, dst = cv2.threshold(edgeShape, 4, 255, cv2.THRESH_BINARY)
dilate = cv2.erode(dst,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2)),
iterations=1)
closing = cv2.morphologyEx(dilate,
cv2.MORPH_CLOSE,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(11, 11)),
iterations=1)
final = cv2.dilate(closing,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)),
iterations=1)
# cv2.imshow("final",final)
# cv2.waitKey(0)
_, contours, _ = cv2.findContours(final, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
mask = np.zeros(img.shape, np.uint8)
cv2.drawContours(mask, contours, -1, (255), -1)
cv2.imshow("final", mask)
mask[mask > 0] = 1
cv2.waitKey(0)
def _patch_(P, E, T, constr, anchor, cavityPoints, involvedE):
#This method patches an pseudo-Delaunay triangulation over a hole left by removing all the triangles that intersect a constrained edge.
while not anchor.points[1].is_point(constr.points[0]):
paths = []
for e in anchor.points[1].edges:
if not e.enclosed and not e.is_edge(anchor):
if e.points[1].is_point(anchor.points[1]):
e.swap()
paths.append(e)
if len(paths) == 0:
anchor.swap()
cavityPoints.append(anchor.points[1])
elif len(paths) == 1:
anchor = paths[0]
cavityPoints.append(anchor.points[1])
else:
cwIndex = 0
thetaprime = math.atan2(anchor.points[0].y - anchor.points[1].y,
anchor.points[0].x - anchor.points[1].x)
if thetaprime < 0:
thetaprime += 2 * math.pi
minAngle = math.atan2(
paths[0].points[1].y - paths[0].points[0].y,
paths[0].points[1].x - paths[0].points[0].x) - thetaprime
while minAngle <= 0:
minAngle += 2 * math.pi
for i in range(1, len(paths)):
res = math.atan2(
paths[i].points[1].y - paths[i].points[0].y,
paths[i].points[1].x - paths[i].points[0].x) - thetaprime
while res <= 0:
res += 2 * math.pi
if res < minAngle:
minAngle = res
cwIndex = i
anchor = paths[cwIndex]
cavityPoints.append(anchor.points[1])
segments = [cavityPoints]
segmentE = [constr]
while len(segments) > 0:
for i in range(len(segments) - 1, -1, -1):
if len(segments[i]) == 3:
e1 = segments[i][1].edges[0]
e2 = segments[i][1].edges[1]
ref1 = edge(segments[i][0], segments[i][1])
ref2 = edge(segments[i][-1], segments[i][1])
for j in range(len(segments[i][1].edges)):
if segments[i][1].edges[j].is_edge(ref1):
e1 = segments[i][1].edges[j]
elif segments[i][1].edges[j].is_edge(ref2):
e2 = segments[i][1].edges[j]
involvedE += [e1, e2]
tri = triangle(segments[i][0], segments[i][1], segments[i][-1])
tri.edges = [e1, e2, segmentE[i]]
tri.update()
T.append(tri)
del segments[i]
del segmentE[i]
else:
for j in range(1, len(segments[i]) - 1):
tri = triangle(segments[i][0], segments[i][j],
segments[i][-1])
validbool = True
for k in range(1, len(segments[i]) - 1):
if k != j and tri.inCircumcircle(
segments[i][k], includeboundary=False):
validbool = False
break
if validbool:
if j == 1:
e1 = segments[i][1].edges[0]
ref1 = edge(segments[i][0], segments[i][1])
for k in range(1, len(segments[i][1].edges)):
if segments[i][1].edges[k].is_edge(ref1):
e1 = segments[i][1].edges[k]
break
e2 = edge(segments[i][1], segments[i][-1])
e2.update()
E.append(e2)
involvedE += [e1, e2]
tri.edges = [e1, e2, segmentE[i]]
tri.update()
T.append(tri)
segments[i] = segments[i][1:]
segmentE[i] = e2
elif j == len(segments[i]) - 2:
e1 = edge(segments[i][0], segments[i][-2])
e1.update()
e2 = segments[i][-2].edges[0]
ref2 = edge(segments[i][-2], segments[i][-1])
for k in range(1, len(segments[i][-2].edges)):
if segments[i][-2].edges[k].is_edge(ref2):
e2 = segments[i][-2].edges[k]
break
E.append(e1)
involvedE += [e1, e2]
tri.edges = [e1, e2, segmentE[i]]
tri.update()
T.append(tri)
segments[i] = segments[i][0:-1]
segmentE[i] = e1
else:
e1 = edge(segments[i][0], segments[i][j])
e1.update()
e2 = edge(segments[i][j], segments[i][-1])
e2.update()
E += [e1, e2]
involvedE += [e1, e2]
tri.edges = [segmentE[i], e1, e2]
tri.update()
T.append(tri)
segments.append(segments[i][j:])
segmentE.append(e2)
segments[i] = segments[i][0:j + 1]
segmentE[i] = e1
break
def delaunay_triangulate(P, constraints=[]):
#This method uses the Bowyer-Watson Algorithm to iteratively insert points into an already Delaunay triangulation.
maxX = P[0].x
minX = P[0].x
maxY = P[0].y
minY = P[0].y
for i in range(1, len(P)):
if P[i].x > maxX:
maxX = P[i].x
elif P[i].x < minX:
minX = P[i].x
if P[i].y > maxY:
maxY = P[i].y
elif P[i].y < minY:
minY = P[i].y
cx = (maxX + minX) / 2
cy = (maxY + minY) / 2
r = math.sqrt((maxX - minX)**2 + (maxY - minY)**2) / 2 + 1
p01 = point(cx, cy + 2 * r)
p02 = point(cx + math.sqrt(3) * r, cy - r)
p03 = point(cx - math.sqrt(3) * r, cy - r)
P.insert(0, p03)
P.insert(0, p02)
P.insert(0, p01)
e01 = edge(p01, p02)
e01.update()
e02 = edge(p01, p03)
e02.update()
e03 = edge(p02, p03)
e03.update()
E = [e01, e02, e03]
t0 = triangle(p01, p02, p03)
t0.edges = [e01, e02, e03]
t0.update()
T = [t0]
for p in P[3:]:
_insert_Vertex_Delaunay_(p, P, E, T)
for i in range(len(T) - 1, -1, -1):
if (p01 in T[i].points) or (p02 in T[i].points) or (p03
in T[i].points):
for elem in T[i].points:
elem.triangles.remove(T[i])
for elem in T[i].edges:
elem.triangles.remove(T[i])
elem.enclosed = False
del T[i]
for i in range(len(E) - 1, -1, -1):
if (p01 in E[i].points) or (p02 in E[i].points) or (p03
in E[i].points):
for elem in E[i].points:
elem.edges.remove(E[i])
del E[i]
del P[0]
del P[0]
del P[0]
if constraints is not None:
#constraintIndex=[]
if isinstance(constraints, list) or isinstance(
constraints, tuple) or isinstance(constraints, np.ndarray):
if all([isinstance(constr, edge) for constr in constraints]):
for i in range(len(constraints) - 1, -1, -1):
matchbool = False
for j in range(len(E)):
if constraints[i].is_edge(E[j]):
matchbool = True
E[j].constraint = True
#constraintIndex.append(j)
break
if matchbool:
#print("Constraint "+constraints[i].to_string()+" is already included in the triangulation")
del constraints[i]
for i in range(len(constraints) - 1):
for j in range(len(constraints) - 1, i, -1):
if constraints[i].is_edge(constraints[j]):
print("Constraint " + constraints[j].to_string() +
" is already included in constraints set")
del constraints[j]
elif constraints[i].edge_edge_intersect(
constraints[j], includeboundary=False):
print("Constraint " + constraints[j].to_string() +
" intersects with constraint " +
constraints[i].to_string() +
"; the former has been deleted")
del constraints[j]
for i in range(len(constraints) - 1, -1, -1):
p1bool = False
p2bool = False
for p in P:
if constraints[i].points[0].is_point(p):
p1bool = True
elif constraints[i].points[1].is_point(p):
p2bool = True
if p1bool and p2bool:
break
if not p1bool or not p2bool:
print("One of the points in Constraint " +
constraints[i].to_string() +
" is not included in the triangulation")
del constraints[i]
for constr in constraints:
constr.constraint = True
#_constrained_(P,E,T,constraints,constraintIndex)
_constrained_(P, E, T, constraints)
return P, E, T
def makeMST():
wgraph = adjacencyListW.makeAdjListW()
disj = [] #represents list of disjoint sets
edgesList = []#stores list of edges
mst=[] #stores mst
#print('printing the disjoint set')
for ver in wgraph: #making disjoint sets and sorting edges of each vertex
discurr = [] #creating each disjoint set
discurr.append(disjoint.disjVer(ver.name, discurr))
#print(str(discurr[0].name) + ' ', end='')
disj.append(discurr)
quickSort.sortQuicklyAtt(ver.adj, 0, len(ver.adj)-1)#sorting edges adj to each vertex
#print()
#print('done printing disjoint sets')
for ver in wgraph: #making list of edges
for i in ver.adj: #just for printing edges of vertices
edgesList.append(edge.edge(disj[int(ver.name)-1][0], disj[int(i.name)-1][0], i.dist))
#print('printing in disj')#check again
#for i in disj:
# print(str(i[0].name) + ' ', end='')
#print('done printing disjoint sets')
'''
for i in edgesList:
print(str(i.frm.name)+' '+str(i.to.name)+' '+str(i.dist)+' ,',end='')
print()
'''
quickSort.sortQuicklyAttr(wgraph, 0, len(wgraph)-1)#sorts all the vertices in adjacency list
'''
print('after quick sort')
for ver in wgraph:
print(str(ver.name) + ' ', end='')
for i in ver.adj: #just for printing edges of vertices
print(str(i.name) + ' ' + str(i.dist) + ' ', end='')
print()
print('done printing after quick sort')
for i in wgraph: #just for printing
print(str(i.name) + ' ', end='')
for j in i.adj: #just for printing
print(str(j.dist) + ' ', end='')
print()
'''
quickSort.sortQuicklyAtt(edgesList, 0, len(edgesList)-1)
print('printing sorted edges')
for i in edgesList:
print(str(i.frm.name)+' '+str(i.to.name)+' '+str(i.dist)+' ,',end='')
print()
print('done printing sorted edges')
print('here comes the mst')
for i in edgesList:
if(i.frm.list != i.to.list):
mst.append(i)
toList = i.to.list
#print('tolist '+str(toList))
for j in toList:
j.list = i.frm.list
i.frm.list.append(j)
for i in mst:
print(str(i.frm.name)+' '+str(i.to.name)+' '+str(i.dist)+' ,',end='')
print()
dt = distance(pts[n], pts[n + 1])
except IndexError:
dt = distance(pts[0], pts[-1])
coefs += dt * exp(complex(0, -k * t * 2 * pi / T)) * complex(pts[n][0], pts[n][1])
n += 1
t += dt
return coefs / T
if __name__ == '__main__':
nb_cercles = 50
rayon_minimal = 0
path = 'ens.png'
print("Détection d'un bord et des coordonnés de la courbe.")
pts = curve(edge(path))
print("Séparation des x et y.")
ptsx = [pt[0] for pt in pts]
ptsy = [pt[1] for pt in pts]
print("Calcul de la période.")
T = periode(pts)
print("Échantillonage des ts.")
p = 1 # précision
ts = [t / p for t in range(ceil(T * p) + 1)]
print("Calcul des affixes des pts de la série de fourier complexe de la courbe.")
zs = fourier_iter(ts, pts, T, N=nb_cercles, p=rayon_minimal)
