Sparse direct solvers (spsolve) in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the sparse solver function from scipy.

SciPy

from scipy.sparse.linalg import [1]

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Asolve

Bspsolve

Csparse_solve

Ddirectsolve

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'solve' which is for dense matrices.

Trying to import a non-existent function like 'directsolve'.

The function spsolve is the correct sparse direct solver imported from scipy.sparse.linalg.

2fill in blank

medium

Complete the code to create a sparse matrix using scipy's csr_matrix.

SciPy

from scipy.sparse import [1]
data = [1, 2, 3]
rows = [0, 1, 2]
cols = [0, 1, 2]
sparse_matrix = [1]((data, (rows, cols)), shape=(3, 3))

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Adia_matrix

Bcsc_matrix

Ccoo_matrix

Dcsr_matrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'csc_matrix' which is compressed sparse column format.

Using 'coo_matrix' which is coordinate format.

csr_matrix is a common sparse matrix format used for efficient arithmetic and matrix vector operations.

3fill in blank

hard

Fix the error in the code to solve the sparse linear system Ax = b.

SciPy

from scipy.sparse.linalg import spsolve
from scipy.sparse import csr_matrix

A = csr_matrix([[3, 0], [0, 4]])
b = [6, 8]
x = spsolve(A, [1])

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Ab

BA

C[6, 8]

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the matrix A instead of vector b.

Passing None or a list literal instead of the variable b.

The right-hand side vector b must be passed to spsolve as the second argument.

4fill in blank

hard

Fill both blanks to create a sparse diagonal matrix and solve Ax = b.

SciPy

from scipy.sparse import [1]
from scipy.sparse.linalg import spsolve
import numpy as np

A = [2](np.array([1, 2, 3]))
b = np.array([1, 4, 9])
x = spsolve(A, b)

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Adiags

Bcsr_matrix

Ccsc_matrix

Deye

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'csr_matrix' or 'csc_matrix' directly with a 1D array.

Using 'eye' which creates an identity matrix, not diagonal from array.

diags creates a sparse diagonal matrix from the given array. We use it both to import and to create matrix A.

5fill in blank

hard

Fill all three blanks to solve a sparse system and print the solution.

SciPy

from scipy.sparse import [1]
from scipy.sparse.linalg import [2]
import numpy as np

A = [1]([[4, 1], [1, 3]])
b = np.array([1, 2])
x = [2](A, b)
print(x)

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Acsr_matrix

Bspsolve

Csolve

Dcsc_matrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'solve' instead of 'spsolve' which is for dense matrices.

Using 'csc_matrix' to create A but not importing it.

We import csr_matrix to create the sparse matrix A, and spsolve to solve the system. The matrix A is created using csr_matrix.