List to mat
X= [] The data is in list format. Performing matrix transformation requires np. mat() to perform a forced transformation.
Data Generation
Sequence generation: np.arange(0, 10,0.1) generates 0-10 data with an interval of 0.1 between each generated data.
Trigonometric function: np.sin(x).
Basic matrix: np.zeros(9) generates 9 one-dimensional matrices with 0, while np.zeros((1,2)) defaults to generating matrices with1 * 2 elements all 0.
The same goes for np.ones() np.eye().
Data Insertion
X = np.insert(X,0,values=[1],axis=1) inserts value 1 in the first column of the X matrix.
np.row_stack((a, [8,9])) inserts new elements and rows into the matrix.
Insert np.column_stack((a, [8,9])) column.
Copy the np.tile(a) matrix in all directions.
Matrix concatenation:
Column concatenation of two matrices in np.vstack(a,b). Np. hstack (a, b) performs row concatenation on two matrices--- Only two matrices can be concatenated.
np.stack(a,b,axis = 0 ); At 0, it is concatenated in rows, and at 1, it is concatenated in columns.
np.concatenate((a,b), axis = 1) Merge by Row.
Matrix operation:
Matrix multiplication: A * B/ numpy.matmul().
Matrix transpose: np.transpose() / A.T.
Matrix inverse: np.linalg.inv(a) / A.I.
Opening: np.sqrt() .
Multiply each element of the matrix by 2 A**2.
Dot product: np.dot(a,b).
Determinant: numpy.linalg.det().
Solution of linear equation system: numpy.linalg.solve().
Norm:
np.linalg.norm(x, ord=None, axis=None, keepdims=False).
Traversing matrix elements:
A [0,0] obtains the elements in the first row and column of A, and A [0] obtains the elements in the first row.
A [0:3,1:4] Slice operation to obtain elements from the first row to the fourth row, and from the first column to the fourth column.
Logical operations:
np.all(): returns true if all parentheses are true, and false if one of them is false.
np.any() : returns false if all parentheses are false, and true if one of them is true.
Statistical operations:
Statistical indicator functions: min, max, mean, media, var, std.
Np. function name darray. method name axis parameter: axis= 0 represents the column, axis; Index function representing the maximum and minimum values of rows:
Np.argmax (arr, axis=).
Np.argmin (arr, axis=).