def Search(input):
ResNodes = {x: 100 for x in range(1, 21)}
SearchRes = []
nodes = load2prog("./data.dat")
for node in nodes:
# 完全匹配搜索
MatchTarget = [node.name, node.desc]
for i in range(len(MatchTarget)):
SelectRes = SelectAlogrithm(str(input), str(MatchTarget[i]))
if SelectRes == 100:
SelectRes = SelectAlogrithm(GetPinYin(input), GetPinYin(MatchTarget[i]))
SelectRes += 1
if i == 1 and SelectRes != 100:
SelectRes += 2
ResNodes[node.id] = min(ResNodes[node.id], SelectRes)
input_word, input_pinyin = CutWord(input)
desc_word, desc_pinyin = CutWord(node.desc)
if (ResNodes[node.id] == 100):
# 部分匹配搜索
for word in input_word:
for i in range(len(MatchTarget)):
ResNodes[node.id] = min(ResNodes[node.id], SelectAlogrithm(word, str(MatchTarget[i])))
if (ResNodes[node.id] == 100):
# 编辑距离搜索
ResNodes[node.id] = max(ResNodes[node.id], Levenshtein(GetPinYin(input), GetPinYin(desc_word[0])) + 5)
for word in desc_word:
ResNodes[node.id] = min(ResNodes[node.id], Levenshtein(GetPinYin(input), GetPinYin(word)) + 5)
ResNodesAftSort = sorted(ResNodes.items(), key=lambda item: item[1], reverse=False)
for i in range(len(ResNodesAftSort)):
SearchRes.append(GetNode(ResNodesAftSort[i][0]))
return SearchRes
from models import load2prog
nodes=load2prog("data.dat")
def DFS(node, AftNodeList):
for Aft_node in node.aft_list:
if(Aft_node not in AftNodeList):
AftNodeList.append(Aft_node)
DFS(Aft_node, AftNodeList)
def FindAft(node):
AftNodeList = []
DFS(node,AftNodeList)
return AftNodeList
from Search.search import Search
from models import load2prog
data = load2prog("./data.dat")
TestInput = ["数组", "书组", "素组", "线信表", "数"]
for input in TestInput:
SearchRes = Search(input)
print("输入内容为:" + input)
print("结果为")
for node in SearchRes:
MatchTarget = [node.name, node.desc]
for line in MatchTarget:
print(line)
from models import load2prog
from FindPreAft.FindPre import FindPre
from FindPreAft.FindAft import FindAft
nodes = load2prog("../data.dat")
AftNodes = FindAft(nodes[0])
PreNodes = FindPre(nodes[-1])
for Nodes in [AftNodes, PreNodes]:
print("-----------------")
for node in Nodes:
print(node.name)
def GetNode(id):
nodes = load2prog("./data.dat")
for node in nodes:
if id == node.id:
return node
def Sort_by_level():
nodes = models.load2prog('data.dat')
sorted_nodes = QuickSort(nodes, cmp1)
return sorted_nodes
def Sort_by_time():
nodes = models.load2prog('data.dat')
sorted_nodes = QuickSort(nodes, cmp2)
return sorted_nodes
def Sort_by_similarity(node):
nodes = models.load2prog('data.dat')
edgs = models.To_Graph()
dis = heap_Dijsktra(edgs, node.id - 1)
sorted_nodes = QuickSort(nodes, cmp3, dis=dis)
return sorted_nodes
