Sparse matrix factorizations in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the sparse matrix module from scipy.

SciPy

from scipy import [1]

Drag options to blanks, or click blank then click option'

Astats

Boptimize

Cintegrate

Dsparse

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the wrong scipy submodule like optimize or stats.

Trying to import sparse as a function instead of a module.

The scipy.sparse module provides tools for sparse matrix operations.

2fill in blank

medium

Complete the code to create a CSR sparse matrix from data, rows, and columns arrays.

SciPy

from scipy.sparse import csr_matrix

matrix = csr_matrix((data, (rows, [1])))

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Acols

Bvalues

Cindices

Dshape

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'values' instead of column indices.

Confusing 'indices' with 'cols'.

The CSR matrix constructor takes a tuple with data and a tuple of (row indices, column indices).

3fill in blank

hard

Fix the error in the code to perform LU factorization on a sparse matrix.

SciPy

from scipy.sparse.linalg import [1]

lu = [1](matrix)

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Asplu

Bspsolve

Clu_factor

Dfactorize

Attempts:

3 left

💡 Hint

Common Mistakes

Using lu_factor which does not support sparse matrices.

Using spsolve which solves linear systems but does not factorize.

The correct function for LU factorization of sparse matrices is splu.

4fill in blank

hard

Fill both blanks to compute the LU factorization of a sparse matrix and solve a system.

SciPy

from scipy.sparse.linalg import [1]

lu = [1](matrix)
result = lu.[2](b)

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Acholesky

Bsolve

Csplu

Dfactorize

Attempts:

3 left

💡 Hint

Common Mistakes

Using cholesky instead of splu for sparse factorization.

Calling a non-existent method instead of solve.

The splu function computes the LU factorization, and the solve method solves the system.

5fill in blank

hard

Fill all three blanks to create a sparse identity matrix, convert it to CSC format, and perform LU factorization.

SciPy

from scipy.sparse import identity
from scipy.sparse.linalg import [1]

I = identity(5).[2]()
lu = [3](I)

Drag options to blanks, or click blank then click option'

Asplu

Btocsc

Ccsr_matrix

Dcsc_matrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using csr_matrix instead of converting to CSC.

Trying to factorize without converting to CSC format.

We use identity to create the matrix, convert it to CSC format with tocsc(), and factorize with splu.