range函数的定义 range函数实例 random.randint函数的定义 random.randint函数实例 clip函数的定义 clip函数实例 一、range函数的定义 range函数的作用是生成一个起始值为start,终值不超过stop,步长为step的等差数列。range函数的基本调用语法如下: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 range(start, stop...
for i in range(500): forward(i) left(91) """) 4、计算1-100以内的素数 print(' '.join([str(item) for item in filter(lambda x: not [x % i for i in range(2, x) if x % i == 0], range(2, 101))])) 5、输出斐波那契数列 print([x[0] for x in [(a[i][0], a.appe...
train_scaled=scaler.fit_transform(train_prices) #创建训练数据集 X_train=[] y_train=[] timesteps=30#时间步长,可根据需求进行调整 foriinrange(timesteps,len(train_scaled)): X_train.append(train_scaled[i-timesteps:i,0]) y_train.append(train_scaled[i,0]) X_train,y_train=np.array(X_tr...
importpgzrun# 导入游戏库importrandom# 导入随机库WIDTH=600# 设置窗口的宽度HEIGHT=800# 设置窗口的高度playerSpeed=5# 玩家水平移动速度brickSpeed=2# 砖块自动上移速度isLoose=False# 游戏是否失败score=0# 游戏得分alien=Actor('alien')# 导入玩家图片alien.x=WIDTH/2# 设置玩家的x坐标alien.y=HEIGHT/5# 设...
param_space={'max_depth':range(3,10),'min_samples_split':range(20,2000),'min_samples_leaf':range(2,20),'max_features': ["sqrt","log2","auto"],'n_estimators':range(100,500) } 1. 2. 3. 4. 5. 6. 贝叶斯优化使用定义的搜索空间对目标函数中评估的点进行采样。
classParse(object):def__init__(self, n):self.n = nself.heads = [None] * (n-1)self.lefts = []self.rights = []foriinrange(n+1):self.lefts.append(DefaultList(0))self.rights.append(DefaultList(0))defadd_arc(self, head, child):self.heads[child] = headifchild < head:self....
and return RMSEdef evaluate_arima_model(X, arima_order):# prepare training datasetX = X.astype('float32')train_size = int(len(X) * 0.50)train, test = X[0:train_size], X[train_size:]history = [x for x in train]# make predictionspredictions = list()for t in range(...
fromrandomimportrandomfromtimeimportperf_counter# Change the value of COUNT according to the speed of your computer.# The value should enable the benchmark to complete in approximately 2 seconds.COUNT =500000DATA = [(random() -0.5) *3for_inrange(COUNT)] e =2.7182818284590452353602874713527defsinh...
('uint8')return xdef plot_filters(filters):newimage = np.zeros((16*filters.shape[0],8*filters.shape[1]))for i in range(filters.shape[2]):y = i%8x = i//8newimage[x*filters.shape[0]:x*filters.shape[0]+filters.shape[0],y*filters.shape[1]:y*filters.shape[1]+filters.shape[...
import asynciodef fib(n):if n<600:n1 = n2 = 1for _ in range(2,n):n1,n2 = n1+n2,n1return n1t = n//2if n%2:return fib(t+1)**2 + fib(t)**2else:return fib(t+1)**2 - fib(t-1)**2def Fib(n):return fib(n)async def asyncFib(n):res = Fib(n)print(res)async ...