def test_remove_range(self):
t = Vector()
t.copyFrom([0, 1, 2, 3, 4, 5, 6], 0, 7)
t.remove_range(3, 5)
self.assertEqual(t[:], [0, 1, 2, 5, 6])
t.remove(0)
self.assertEqual(t[:], [1, 2, 5, 6])
def test_insert(self):
t = Vector()
t.insert(0, 1)
t.insert(0, 3)
t.insert(1, 5)
t.insert(5, 10)
self.assertEqual(t[:], [3, 5, 1, 10])
def insertV(self, vertex: Vertex): # 插入顶点
for j in range(self.n):
self.__E[j].insert(None) # 各顶点增加一个边记录位置
self.n += 1
self.__E.insert(self.n, Vector().copyFrom([None] * self.n, 0,
self.n)) # 增加新的顶点向量
return self.__V.insert(self.n, vertex) # 增加新顶点
def test_bin_search(self):
t = Vector()
t.copyFrom([0, 1, 2, 3, 4, 5, 6], 0, 7)
self.assertEqual(t.binSearch(0), 0)
self.assertEqual(t.binSearch(3), 3)
self.assertEqual(t.binSearch(6), 6)
self.assertEqual(t.binSearch_A(0), 0)
self.assertEqual(t.binSearch_A(4), 4)
self.assertEqual(t.binSearch_A(6), 6)
def __init__(self):
self.n = 0 # 顶点数
self.e = 0 # 边数
self.__V = Vector() # 顶点集合
self.__E = Vector() # 边集合
class GraphMatrix: # 基于向量，邻接矩阵实现图
def __init__(self):
self.n = 0 # 顶点数
self.e = 0 # 边数
self.__V = Vector() # 顶点集合
self.__E = Vector() # 边集合
def reset(self):
for i in range(self.n):
self.vertex(i).status = VStatus.UNDISCOVERED
self.vertex(i).dTime = -1
self.vertex(i).fTime = -1
self.vertex(i).parent = -1
self.vertex(i).priority = float('inf')
for j in range(self.n):
if self.exists(i, j):
self.__E[i][j].type = EType.UNDETERMINED
def vertex(self, i):
return self.__V[i]
def vertex_data(self, i):
return self.__V[i].data
def inDegree(self, i):
return self.__V[i].InDegree
def outDegree(self, i):
return self.__V[i].outDegree
def firstNbr(self, i):
return self.nextNbr(i, self.n)
def nextNbr(self, i, j):
for j in range(j - 1, 0, -1):
if self.exists(i, j):
return j
return -1
def exists(self, i, j): # i到j的边是否存在
return 0 <= i <= self.n and 0 <= j <= self.n and self.__E[i][
j] is not None
def status(self, i):
return self.__V[i].status
def dTime(self, i):
return self.__V[i].dTime
def fTime(self, i):
return self.__V[i].fTime
def parent(self, i):
return self.__V[i].parent
def priority(self, i):
return self.__V[i].priority
def insertV(self, vertex: Vertex): # 插入顶点
for j in range(self.n):
self.__E[j].insert(None) # 各顶点增加一个边记录位置
self.n += 1
self.__E.insert(self.n, Vector().copyFrom([None] * self.n, 0,
self.n)) # 增加新的顶点向量
return self.__V.insert(self.n, vertex) # 增加新顶点
def removeV(self, i): # 删除第i个顶点及其关联的边
for j in range(self.n): # 所有出边
if self.exists(i, j): # 存在
self.__E[i][j] = None # 删除出边，可选，后续删除整条边
self.__V[j].inDegree -= 1 # 顶点J入度-1
self.__E.remove(i) # 删除i的边数据
self.n -= 1
vBak = self.vertex(i) # 需要删除的顶点备份
self.__V.remove(i) # 删除顶点
for j in range(self.n):
if not self.__E[j][i] is None: # 判断第j的顶点是否有到i的边
self.__E[j][i] = None # 有边时删除
self.__V[j].outDegree -= 1 # 出度减1
return vBak
def type(self, i, j):
return self.__E[i][j].etype
def edge(self, i, j): # 方便后续程序修改值，将边对象直接返回
return self.__E[i][j]
def edge_data(self, i, j):
return self.__E[i][j].data
def weight(self, i, j):
return self.__E[i][j].weight
def insertE(self, edge: Edge, i, j): # 插入i到j的边
if self.exists(i, j): return # 边存在则不做任何处理）
self.__E[i][j] = edge
self.e += 1
self.__V[i].outDegree += 1
self.__V[j].inDegree += 1
def removeE(self, i, j): # 移除i到j的边
eBak = self.edge(i, j)
self.__E[i][j] = None
self.e -= 1
self.__V[i].outDegree -= 1
self.__V[j].inDegree -= 1
return eBak
def __getitem__(self, item: int):
return self.__V[item]
def test_find(self):
t = Vector()
t.copyFrom([5, 4, 3, 2, 1, 5], 0, 6)
self.assertEqual(t.find(5), 0)
self.assertEqual(t.find(10), -1)
self.assertEqual(t.find(5, 1, t.size()), 5)
def test_sort(self):
t = Vector()
t.copyFrom([0, 1, 2, 3, 4, 5, 6], 0, 7)
t.permute()
t._bubbleSort() # 冒泡排序
self.assertEqual(t[:], list(range(7)))
t.permute()
t._selectSort() # 选择排序
self.assertEqual(t[:], list(range(7)))
t.permute()
t._mergeSort() # 归并排序
self.assertEqual(t[:], list(range(7)))
t.permute()
t.quickSort() # 快速排序
self.assertEqual(t[:], list(range(7)))
def test_uniquify(self):
t = Vector()
t.copyFrom([0, 1, 1, 2, 3, 4, 5, 5], 0, 8)
s = t.uniquify()
self.assertEqual(t[:], [0, 1, 2, 3, 4, 5])
self.assertEqual(s, 2)
def test_deduplicate(self):
t = Vector()
t.copyFrom([0, 1, 1, 3, 1, 3, 6], 0, 7)
s = t.deduplicate()
self.assertEqual(set(t[:]), {0, 1, 3, 6})
self.assertEqual(s, 3)
def test_disordered(self):
t = Vector()
t.copyFrom([5, 4, 3, 2, 1], 0, 5)
self.assertEqual(t.disordered(), 4)