標籤:python演算法
一.無序表尋找def sequential_search(lis, key): for i in lis: if i == key: return lis.index(i) else: continue else: return Falseif __name__ == '__main__': LIST = [1, 5, 8, 123, 22, 54, 7, 99, 300, 222] result = sequential_search(LIST,1231) print(result) 二.有序表尋找1.二分尋找(Binary Search)def binary_search(lis,key): low = 0 high = len(lis) - 1 time = 0 while low < high: time += 1 mid = int((low + high)/2) if key < lis[mid]: high = mid - 1 elif key > lis[mid]: low = mid + 1 else: print("times: %s" % time) return mid print("times: %s" % time) return Falseif __name__ == '__main__': LIST = [1, 5, 7, 8, 22, 54, 99, 123, 200, 222, 444] result = binary_search(LIST,99) print(result) 2. 插值尋找二分尋找法雖然已經很不錯了,但還有可以最佳化的地方。有的時候,對半過濾還不夠狠,要是每次都排除十分之九的資料豈不是更好?選擇這個值就是關鍵問題,插值的意義就是:以更快的速度進行縮減。插值的核心就是使用公式:value = (key – list[low])/(list[high] – list[low])用這個value來代替二分尋找中的1/2def binary_search(lis, key): low = 0 high = len(lis) - 1 time = 0 while low < high: time += 1 # 計算mid值是插值演算法的核心代碼 mid = low + int((high - low) * (key - lis[low]) / (lis[high] - lis[low])) print("mid=%s, low=%s, high=%s" % (mid, low, high)) if key < lis[mid]: high = mid - 1 elif key > lis[mid]: low = mid + 1 else: # 列印尋找的次數 print("times: %s" % time) return mid print("times: %s" % time) return False
python 基本演算法