import numpy as np
data=np.loadtxt("data",delimiter=",",dtype=float)| Special matrix | Explanation |
| np.asarray(data) | Copy data matrix |
| np.ones(n) np.ones( (M, N) ) np.ones_like( data ) |
Generate a one-dimensional array of length n, all elements are 1 |
| Generate a two-dimensional matrix with M rows and N columns, all elements are 1 | |
| Generate a matrix with the same shape as the matrix data, all elements are 1 | |
| np.zeros(n) np.zeros( (M, N) ) np.zeros_like( data ) |
Generate a one-dimensional array of length n, all elements are 0 |
| Generate a two-dimensional matrix with M rows and N columns, all elements are 0 | |
| Generate a matrix with the same shape as the matrix data, all elements are 0 | |
| np.empty(n) np.empty(n,dtype) np.empty(data) |
Generate an uninitialized one-dimensional array of length n |
| Generate an uninitialized two-dimensional matrix with M rows and N columns | |
| Generate an uninitialized matrix with the same shape as the matrix data | |
| np.eye(n) | Generate an n*n identity matrix (diagonal elements are 1, the rest are 0) |
| np.arange(n) np.arange(begin, end) np.arange(begin, end, step) |
Generate a one-dimensional array from 0 to (n-1), the number of steps is 1 |
| Generate a one-dimensional array from begin to (end-1), the number of steps is 1 | |
| Generate a one-dimensional array from begin to (end-step), the number of steps is step |