The `scipy.sparse.linalg` module provides functions for operating on sparse matrices. Assuming `H` and `I` are SciPy sparse matrices:

```python
# Calculate the inverse of a sparse matrix
sparse.linalg.inv(I)

# Calculate the norm of a sparse matrix
sparse.linalg.norm(I)

# Solve the sparse linear system H * x = I
sparse.linalg.spsolve(H, I)
```

Michigan State University

Google

 F = np.eye(3, k=1) #Create a 2X2 identity matrix

G = np.mat(np.identity(2)) #Create a 2x2 identity matrix

C[[C > 0.5]] = 0

H = sparse.csr_matrix(C) #Compressed Sparse Row matrix

I = sparse.csc_matrix(D) #Compressed Sparse Column matrix

J = sparse.dok_matrix(A) #Dictionary Of Keys matrix

E.todense() #Sparse matrix to full matrix

sparse.isspmatrix_csc(A) #Identify sparse matrix

Learn Before

Related