6. Create a null vector of size 10 but the fifth value which is 1 >>Z = np.zeros(10) Z[4] = 1 print(Z) 7. Create a vector with values ranging from 10 to 49 >>np.arange(10,50) 8. Reverse a vector (first element becomes last) >>Z = np.arange(50) Z = Z[::-1] pri...
For example, if you want to normalize a vector to a range of [a, b], the formula would be: normalized_vector = (max(vector)−min(vector))/(vector−min(vector)) scaled_vector=normalized_vector×(b−a)+a import numpy as np def normalize_vector(vector, range_min, range_max): n...
This function creates a vector of zeros of shape (num_of_features, 1) for W and initializes w_0 to 0. Argument: num_of_features -- size of the W vector, i.e., the number of features, excluding the bias Returns: W -- initialized vector of shape (dim, 1) w_0 -- initialized ...
14. Create a random vector of size 30 and find the mean value (★☆☆) 1arr = np.random.random(30)2print(arr.mean()) 运行结果:0.49710820465862965 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) 1arr = np.ones((10,10))2arr[1:9,1:9] =03print(arr) 运行...
11.Create a checkerboard 8x8 matrix using the tile function (★☆☆) a = np.array([[1,0], [0,1]]) b = np.tile(a,(4,4)) 利用np.tile函数扩张原数组来构造棋盘 12.Normalize a 5x5 random matrix (★☆☆) Z =np.random.random((5,5)) ...
from __future__ import print_function import numpy as np import matplotlib.pyplot as plt x = np.arange(5) print("Exp", np.exp(x)) print("Linspace", np.linspace(-1, 0, 5)) ## Calculate weights N = 5 weights = np.exp(np.linspace(-1., 0., N)) ## Normalize weights weights...
数字组成的数组叫作向量(vector)或一维张量(1D 张量)。一维张量只有一个轴。下面是 一个 Numpy 向量。 >>>x = np.array([1,2,3,4,5])>>>x array([1,2,3,4,5])>>>x.ndim1 这个向量有5 个元素,也被称为5D 向量。 矩阵(2D张量)
Exercise: Implement normalizeRows() to normalize the rows of a matrix. After applying this function to an input matrix x, each row of x should be a vector of unit length (meaning length 1). # GRADED FUNCTION: normalizeRowsdefnormalizeRows(x):""" ...
然后我遇到了这个:https://stackoverflow.com/a/21031303/6209399 也就是说,您可以通过执行以下操作来标准化数组: def normalize_list_numpy(list): normalized_list = list / np.linalg.norm(list) return normalized_list 1. 2. 3. 如果使用我自己的函数和numpy方法对该测试数组test_array = [1, 2, 3,...
The first vector to be added contains the squares of 0 up to n. The second vector contains the cubes of 0 up to n. The program prints the last 2 elements of the sum and the elapsed time. """ def numpysum(n): a = np.arange(n) ** 2 ...