...print("'c' stands for 'cease'") ...break...print(i) ... a b'c'standsfor'cease' continue退出本次循环,继续执行下一个循环 foriina: ...ifi =='c': ...print("'c' stands for 'cease'") ...continue...print(i) ... a b'c'standsfor'cease'd for...else for i in array...
九九乘法表共有九列九行的数据，其展示出来的形式是一个二维平面空间，因此这是一个非常适合使用两层嵌套循环结构来编写的案例：for i in range(1, 10): for j in range(1, 10): if j == 9: print("\t", i*j) # j == 9时，换行 else: print("\t", i*j, end = '') ...
n_gram = [array[i-k:i] for k in range(m,n+1) for i in range(k,n+1)] return n_gram def find_max(array): n_gram = get_ngram(array) sum_n_gram = [sum(i) for i in n_gram] max_sum = sum_n_gram[0] for i in sum_n_gram: if i >= max_sum: max_sum = i retu...
int_arr = array.array('i', [1, 2, 3]) str_arr = array.array('u', 'hello') array的方法和list基本相同,例如append,pop,insert,remove, index等。 也可以遍历元素 for x in int_arr: print(x) python内置模块array不支持二维数组。 使用第三方扩展库numpy numpy 全称为 Numerical Python,是 Pytho...
j=1 i+=1 print() '''在循环体内嵌入其他的循环体,如在while循环中可以嵌入for循环, 反之,你可以在for循环中嵌入while循环''' for循环 for循环可以做到的事情while循环都可以做到!!! 但是for循环语法更加简单使用频率更高 一般情况下涉及到循环取值的时候都会考虑使用for循环而不是while循环 ...
for i in range(1, 10): for j in range(1, 10): if j == 9: print("\t", i*j) # j == 9时,换行 else: print("\t", i*j, end = '') # j < 9时,不换行 执行结果如下: break和continue 循环的结束分为正常的结束和非正常的结束。正常的结束方式是当循环的判断条件不再符合时,循...
array([[5, 3, 0, 1], [4, 0, 0, 0], [0, 5, 3, 0], [0, 4, 5, 5]]) # 计算用户之间的相似度 def similarity(ratings): n = ratings.shape[0] sim = np.zeros((n, n)) for i in range(n): for j in range(n): if i != j: sim[i][j] = np.corrcoef(ratings[i]...
rows_max=1000# 最大造数行数foriinrange(1,rows_max):index+=1forjinrange(cols_max):apply_no=f'XNAB{int(time.time() * 1000000)}'status=random.randint(0,10)create_datetime=datetime.datetime.now().__format__('%Y-%m-%d %H:%M:%S')enable=random.choice(['Y','N'])cell_value={0:...
num_epochs)J = cost_function(x, y, theta)print("Cost:", J)print("Parameters:", theta) #for testing and plotting cost n_epochs = []jplot = []count = 0for i in J_all: jplot.append(i[0][0]) n_epochs.append(count) count += 1jplot = np.array(jplot)n_epochs = np.array(n...
for i in range(0,height): for j in range(0,width-1): grayCurrentPixel = int(gray[i,j]) grayNextPixel = int(gray[i,j+1]) newPixel = grayCurrentPixel - grayNextPixel + 150 if newPixel > 255: newPixel = 255 if newPixel < 0: newPixel = 0 dstImg[i,j] = newPixel #显示...