In this example, we calculate the exponentiation value of the float element of the array by using the power function available inside the NumPy library. Code: importnumpyasmynum# defining arrays here .. x1 and x2x1=[1.5,2.3,2.2,5.3,9]x2=[2,2,2,2,1]#array before power functionprint(...
(提示: sum(axis=(-2,-1))) A = np.random.randint(0,10,(3,4,3,4)) # 传递一个元组(numpy 1.7.0) sum = A.sum(axis=(-2,-1)) print(sum) # 将最后两个维度压缩为一个 # (适用于不接受轴元组参数的函数) sum = A.reshape(A.shape[:-2] + (-1,)).sum(axis=-1) print(sum)...
2、numpy.power(one, two) 将第一个输入数组中的元素作为底数,计算它与第二个输入数组中相应元素的幂,即 one^two 3、numpy.mod(x1, x2) 计算输入数组中相应元素的余数,函数 numpy.remainder(x1, x2) 也产生相同的结果 代码语言:javascript 复制 import numpy as np arr = np.array([[1., 2., 3.]...
power Raise elements in first array to powers indicated in second array maximum, fmax Element-wise maximum; fmax ignores NaN minimum, fmin Element-wise minimum; fmin ignores NaN mod Element-wise modulus (remainder of division) copysign Copy sign of values in second argument to values in first ...
array([0., 1., 2., 3., 4.]) Z=np.arange(5)Z<Z>Z# false ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() 28. 下列表达式的结果分别是什么?(★☆☆) np.array(0) / np.array(0) ...
numpy.floor_divide(x1, x2,args, kwargs)Return the largest integer smaller or equal to the division of the inputs. numpy.power numpy.power(x1, x2,args, kwargs)First array elements raised to powers from second array, element-wise.
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add()numpy.subtract()numpy.multiply()numpy.divide()numpy.floor_divide(x1, x2)numpy.power()...
import numpy as np def test_run(): #Generate an array full of random numbers, #uniformly sampled from [0.0, 1.0) print np.random.random((5, 4)) print np.random.rand(5, 4) #以上两条代码效果一样,都是均匀采样 print np.random.normal(size = (2, 3)) #"Standard normal",mean = 0...
# 这里不使用StringIO, 因为Python2 和Python3 在这个地方有兼容性问题Z=np.genfromtxt("example.txt",delimiter=",")print(Z) 55. numpy数组枚举(enumerate)的等价操作? (★★☆) (提示: np.ndenumerate, np.ndindex) 代码语言:javascript 复制