importnumpyasnpdefrandfloat(num,low,high):'''该函数用于生成指定范围与数量的随机浮点数数组'''iflow>high:print('Low must smaller than high.')returnNoneelse:a=high-lowd=high-aout=np.random.rand(num)out=out*a+dout.tolist()out=np.array(out)returnouta=randfloat(num=20,low=3,high=8)pri...
return 10 * x + y ... >>> b = np.fromfunction(f, (5, 4), dtype=int) >>> b array([[ 0, 1, 2, 3], [10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33], [40, 41, 42, 43]]) >>> b[2, 3] 23 >>> b[0:5, 1] # each row in the second column...
zeros(shape[, dtype, order])Return a matrix of given shape and type, filled with zeros. ones(shape[, dtype, order])Matrix of ones. eye(n[, M, k, dtype, order])Return a matrix with ones on the diagonal and zeros elsewhere.
要获取 NumPy 数组(数组中唯一值的第一个索引位置的数组)中唯一值的索引,只需将return_index 参数np.unique()和数组一起传入即可。 >>> unique_values, indices_list = np.unique(a, return_index=True)>>> print(indices_list)[ 0 2 3 4 5 6 7 12 13 14] 您可以将return_counts参数np.unique()与...
return_index: True表示返回原始数组中的下标。 return_inverse:True表示返回重建原始数组用的下标数组。 下面通过实例介绍unique()的用法。首先用randint()创建含有10个元素、值在0到9范围之内的随机整数数组 >>> a =np.random.randint(0,10,10) >>> a ...
要在NumPy 数组中获取唯一值的索引(数组中唯一值的第一个索引位置数组),只需在np.unique()中传递return_index参数以及你的数组即可。 >>> unique_values, indices_list = np.unique(a, return_index=True)>>> print(indices_list)[ 0 2 3 4 5 6 7 12 13 14] ...
return (data * scaler.std) +scaler.mean # Construct scalers from training set X_scalers = [get_scaler(X_raw_train[row,:]) for row inrange(X_num_row)] X_train = np.array([standardize(X_raw_train[row,:], X_scalers[row]) forrow in range(X_num_row)]) y_scalers = [get_sc...
| ndarray.__ixor__(self, value, /) | Return self^=value. | WarningIn place operations will perform the calculation using the precision decided by the data type of the two operands, but will silently downcast the result (if necessary) so it can fit back into the array. Therefore, for ...
max(a,b) np.maximum(a, b) 逐元素比较a和b,并返回每对中的最大值 norm(v) np.sqrt(v @ v)或np.linalg.norm(v) 向量v的 L2 范数 a & b logical_and(a,b) 逐元素的与运算符(NumPy ufunc)查看逻辑运算符注意事项 a | b np.logical_or(a,b) 逐元素的或运算符(NumPy ufunc)查看逻辑...
find_max(a,n);//调用函数 system("pause"); return 0; } 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35.