import numpy as np array1 = np.array([1, 2, 3]) scalar = 2 # multiply each element in array1 by the scalar value result = np.multiply(array1, scalar) print(result) Run Code Output [2 4 6] In this example, we multiplied each element in array1 by the scalar value of 2. ...
modf Return fractional and integral parts of array as a separate array isnan Return boolean array indicating whether each value is NaN (Not a Number) isfinite, isinf Return boolean array indicating whether each element is finite (non-inf, non-NaN) or infinite, respectively cos, cosh, sin, s...
import numpy as np a = np.array([[1, 2], [3, 4]]) b = np.array([[5, 6], [7, 8]]) path, steps = np.einsum_path('ij,jk->ik', a, b) print(path) print(steps) ['einsum_path', (0, 1)] Complete contraction: ij,jk->ik Naive scaling: 3 Optimized scaling: 3 Naive...
(4)a,b 矩阵:报错;本质上,进行逐元素element-wise运算 a=np.mat(np.arange(6).reshape(2,3))#a=[[0,1,2],[3,4,5]]b=np.mat((np.arage(6)+1).reshape(3,2))#b=[[0,1],[2,3],[4,5]]c=np.multiply(a,b)#wrongTraceback(most recent call last):File"<stdin>",line1,in<modu...
arr[arr<5] | Returns array elements smaller than 5 Scalar Math np.add(arr,1) | Add 1 to each array element np.subtract(arr,2) | Subtract 2 from each array element np.multiply(arr,3) | Multiply each array element by 3 np.divide(arr,4) | Divide each array element by 4 (returns...
array([0, 2, 0, 1]) # Select one element from each row of a using the indices in b print a[np.arange(4), b] # Prints "[ 1 6 7 11]" # Mutate one element from each row of a using the indices in b a[np.arange(4), b] += 10 print a # prints "array([[11, 2, 3...
To give you an idea of the performance differnce(性能差异), consider(演示) a NumPy array one million integers, and the equivalent Python list: importnumpyasnp my_arr = np.arange(1000000) my_list =list(range(1000000)) Now let's multiply each sequence by 2: ...
Now let's multiply each sequence by 2: # %time 测试一行代码执行完所需要的时间 %timefor_inrange(10):my_arr2=my_arr*2 print('*'*50) %timefor_inrange(10):my_list2=[x*2forxinmy_list] 1. 2. 3. 4. 5. 6. 7. Wall time: 35 ms ...
arr=np.array([[ 1,2,3],[4,5,6],[7,8,9]])# 获取(0,1)、(1,2)和( 2,0)位置的元素print(arr[[0,1,2],[1,2,0]])# 输出:[2 6 7] 注意事项 NumPy索引是从0开始的。 切片是原数组的视图,修改切片会影响原数组。如果需要复制,可以使用.copy()方法。
3.Write a NumPy program that creates a 2D NumPy array and a 1D array. Use the np.add ufunc to add the 1D array to each row of the 2D array. Click me to see the sample solution 4.Write a NumPy program that uses the np.multiply ufunc to perform element-wise multiplication of two ...