complex_num=np.array([1+2j,3-4j])# 获取实部real_part=np.real(complex_num)print("numpyarray.com - Real part:",real_part)# 获取虚部imag_part=np.imag(complex_num)print("numpyarray.com - Imaginary part:",imag_part)# 计算模
When we use a 2D NumPy array as the input, the np.sqrt function simply calculates the square root of every element of the array. The output of the function is simply an array of those calculated square roots, arranged in exactly the same shape as the input array. So if the input array...
importnumpyasnp array_2d=np.array([[1,4,9],[16,25,36]])result_2d=np.sqrt(array_2d)print(f"The square roots of the 2D array are:\n{result_2d}.") 1. 2. 3. 4. 5. 6. 在这个示例中,我们定义了一个二维数组并计算其所有元素的平方根。运行结果将是一个同样维度的数组,每个元素都是...
arr = np.array([1, 2, 3]) print("Array with Rank 1: \n",arr) # 创建 rank 2 数组 arr = np.array([[1, 2, 3], [4, 5, 6]]) print("Array with Rank 2: \n", arr) # 从元组创建数组 arr = np.array((1, 3, 2)) print("\nArray created using " "passed tuple:\n",...
运行上述代码后,将输出: text The square root of 16 is 4.0 The square roots of the array [16 25 36 49] are [4. 5. 6. 7.] 这样,就成功地使用NumPy对数值和数组进行了开方操作。
(x, y))#Elementwise product; both produce the array#[[ 5.0 12.0]#[21.0 32.0]]print(x *y)print(np.multiply(x, y))#Elementwise division; both produce the array#[[ 0.2 0.33333333]#[ 0.42857143 0.5 ]]print(x /y)print(np.divide(x, y))#Elementwise square root; produces the array#...
#Sum of all the elements in an array sum=np.sum(arr1) print("Sum of all elements \n",sum) #Square of an array squareroot=np.sqrt(arr1) print("Square of arr1 \n", squareroot) #Square of an array square=np.square(arr1) ...
>>> from numpy import * >>> zeros( (12), dtype=int8 ) array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int8) >>> zeros( (2,6), dtype=int16 ) array([[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]], dtype=int16) >>> ones( (6,2), dtype=int...
square-root of an array1 : [ 1. 2. 3. 4.] square-root of an array2 : [ 2.44948974 3.16227766 4.24264069] 代码2: #Pythonprogram explaining # numpy.sqrt() method # importing numpy import numpy as geek # applying sqrt() method on complex numbers ...
本篇我们看看NumPy中最为基本的Array操作 >>> from numpy import * 创建一个矩阵 >>> a=array([[1,2,3],[4,5,6]])>>> a.shape(2, 3) >>> b=arange(15);print b[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]>>> b.reshape(3,5)array([[ 0, 1, 2, 3, 4],[ 5, 6, 7,...