SciPy Learning in Python--random sparse matrices and operations

1. generate a random sparse matrix :

The functions of generating random sparse matrices in scipy are as follows:

scipy.sparse.rand(m,n,density,format,dtype,random_state)

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Parameter description:

Parameters	meaning
M,n	An integer; a row and column that represents a matrix
Density	A real type; the sparsity of a matrix.
Format	STR type; the type of the matrix; such as format= ' COO '
Dtype	Dtype a type that returns a matrix value
Ranom_state	{numpy.random.randomstate,int}; optional random seed; if empty, default Numpy.random

Example

The code is as follows:

Importscipy as Spyn=4m=4density=0.5Matrixformat='COO'B=spy.sparse.rand (m,n,density=density,format=matrixformat,dtype=None)Print(B)>>> (1, 1) 0.0687198939788  (3, 3) 0.141328654998(0,3) 0.944468193258  (2, 3) 0.598652789611(0,2) 0.0629165518906  (2, 0) 0.624087894456  (1, 2) 0.309460820898  (2, 2) 0.731375305002

2. Operation of sparse matrices:

Importscipy as Spyn=4m=4Row=spy.array ([0,0,0,1,1,3,3]) Col=spy.array ([0,0,1,2,3,2,3]) value=spy.array ([1,2,1,8,1,3,5])Print('Customize the sparse matrix to generate a CSC format :')#the ' COO ' format matrix cannot perform some of the following actionsA=spy.sparse.csc_matrix ((Value, (Row,col)), shape=(n,m))Print('non-sparse representation of sparse matrices ...')Print(A.todense ())Print('non-0 element corresponding coordinate of sparse matrix ...') Nonzero=A.nonzero ()Print(nonzero)Print('outputs a non-0 element corresponding to the row and column coordinates ...')Print(nonzero[0])Print(nonzero[1])Print('output line I not 0 value ...') I=2Print(A[i,:])Print('output column J not 0 value ...') J=2Print(A[:,j])Print('the output coordinate is (I,J) the corresponding value ...')Print(A[i,j])

The output results are as follows:

Customize the sparse matrix to generate a CSC format: Non-sparse representation of sparse matrices ... [[3 18 13 51, 1, 3, 3], dtype=int32), array ([0, 1, 2, 3, 2, 3], dtype=1 1 3 3 1 2 3 2 3] Output line I non-0 value ... Output column J not 0 value  ... (1, 0)        8  (3, 0)        3 The output coordinate is (I,J) the corresponding value ... 0

Note: For more information, see docs.scipy.org

SciPy Learning in Python--random sparse matrices and operations