subtract Subtract elements in second array from first array multiply Multiply array elements divide, floor_divide Divide or floor divide (truncating the remainder) power Raise elements in first array to powers indicated in second array maximum, fmax Element-wise maximum; fmax ignores NaN minimum, fmi...
numpy.prod(a[, axis=None, dtype=None, out=None, …]) Return the product of array elements over a given axis. 【例】返回给定轴上数组元素的乘积。 numpy.cumprod 累乘 numpy.cumprod(a, axis=None, dtype=None, out=None) Return the cumulative product of elements along a given axis. 【例】...
>>> # Create an empty array with 2 elements >>> np.empty(2) array([3.14, 42\. ]) # may vary 您可以创建一个具有元素范围的数组: 代码语言:javascript 代码运行次数:0 运行 复制 >>> np.arange(4) array([0, 1, 2, 3]) 甚至可以创建一个包含一系列均匀间隔的区间的数组。为此,您需要...
numpy.exp(x, *args, **kwargs) Calculate the exponential of all elements in the input array. numpy.log(x, *args, **kwargs) Natural logarithm, element-wise. numpy.exp2(x, *args, **kwargs) Calculate 2**p for all p in the input array. numpy.log2(x, *args, **kwargs) Base-2 ...
(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#...
numpy.multiply() numpy.divide() numpy.floor_divide(x1, x2) Return the largest integer smaller or equal to the division of the inputs. x = np.array([[11, 12, 13, 14, 15], [16, 17, 18, 19, 20], [21, 22, 23, 24, 25], [26, 27, 28, 29, 30], [31, 32, 33,...
import numpy as np arr1 = np.array([1, 2, 3]) arr2 = np.array([4, 5, 6]) elementwise_product = np.multiply(arr1, arr2) print(elementwise_product) [ 4 10 18] 练习54: 计算二维数组中每列的标准差。 import numpy as np matrix = np.random.random((4, 3)) column_stddev = ...
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: ...
乘法(* 或np.multiply):数组元素相乘。 除法(/ 或np.divide):第一个数组元素除以第二个数组的元素。 平方根(np.sqrt):数组每个元素的平方根。 幂运算(** 或np.power):第一个数组元素的第二个数组元素次幂。 import numpy as np a = np.array([1, 2, 3, 4]) b = np.array([5, 6, 7, 8]...
For example, we can multiply all elements in an array by 2 by using the following command: arr = np.array([1, 2, 3, 4])new = 2*arrprint(new)# [2, 4, 6, 8] Useful array creation routines To generate arrays of numbers at regular intervals between two given end points, you can...