print ("Adding 1 to every element:", a + 1) # 从每个元素中减去 2 print ("\nSubtracting 2 from each element:", b - 2) # 数组元素的总和执行一元运算 print ("\nSum of all array " "elements: ", a.sum()) # 添加两个数组执行二元运算 print ("\nArray sum:\n", a + b) 1. ...
import numpy as np x = np.array([1, 2, 3, 4, 5]) # Obtain array of square of each element in x squarer = lambda t: t ** 2 squares = np.array([squarer(xi) for xi in x]) 但是,这可能效率很低,因为我使用列表推导将新数组构造为 Python 列表,然后再将其转换回 numpy 数组。我们...
(arr * 2)) # Halve element values print(repr(arr / 2)) # Integer division (half) print(repr(arr // 2)) # Square element values print(repr(arr**2)) # Square root element values print(repr(arr**0.5)) array([[2, 3], [4, 5]]) array([[0, 1], [2, 3]]) array([[2,...
NumPy 还允许在数组上执行通用函数,如平方根函数、指数函数和三角函数等。 np.sqrt(arr) #Returns the square root of each element np.exp(arr) #Returns the exponentials of each element np.sin(arr) #Returns the sin of each element np.cos(arr) #Returns the cosine of each element np.log(arr)...
print(element) ... 0 1 2 3 10 11 12 13 20 21 22 23 30 31 32 33 40 41 42 43 参见 ndarrays 的索引、索引例程(参考)、newaxis、ndenumerate、indices ## 形状操作 改变数组的形状 数组的形状由沿每个轴的元素数量确定: 代码语言:javascript 代码运行次数:0 运行 复制 >>> a = np.floor(10 ...
square() Return Value The square() function returns the array containing the element-wise squares of the input array. Example 1: Use of dtype Argument in square() import numpy as np # create an array array1 = np.array([1, 2, 3, 4]) # compute the square of array1 with different...
square Compute the square of each element (equivalent to arr ** 2) exp Compute the exponent ex of each element log, log10, log2, log1p Natural logarithm (base e), log base 10, log base 2, and log(1 + x), respectively sign Compute the sign of each element: 1 (positive), 0 (...
print("Sqrt: ",np.sqrt(arr))#Returns the square root of each element print("Exp: ",np.exp(arr)) #Returns the exponentials of each element print("Sin: ",np.sin(arr)) #Returns the sin of each element print("Cos: ",np.cos(arr)) #Returns the cosine of each element ...
70710678j, 0.00000000+0.70710678j]])) Parameters: square matrix Returns The eigenvalues, each repeated according to its multiplicity. The normalized (unit "length") eigenvectors, such that the column ``v[:,i]`` is the eigenvector corresponding to the eigenvalue ``w[i]`` ....
arr / arr #Divides each element by itself 我们还可以对数组执行标量运算,NumPy 通过广播机制使其成为可能: arr + 50 #This adds 50 to every element in that array NumPy 还允许在数组上执行通用函数,如平方根函数、指数函数和三角函数等。 np.sqrt(arr) #Returns the square root of each element ...