np.linalg.solve() for linear systems in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the numpy library with the common alias.

NumPy

import [1] as np

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

Amatplotlib

Bpandas

Cnumpy

Dscipy

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the wrong library like pandas or matplotlib.

Forgetting to use the alias 'np'.

The numpy library is commonly imported as np to use its functions easily.

2fill in blank

medium

Complete the code to define matrix A as a 2x2 numpy array.

NumPy

A = np.array([1])

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

A[3, 1, 1, 2]

B[[3 1], [1 2]]

C[[3, 1, 1], [2]]

D[[3, 1], [1, 2]]

Attempts:

3 left

💡 Hint

Common Mistakes

Using a flat list instead of nested lists.

Missing commas between elements.

Matrix A must be a 2x2 list of lists to create a 2D numpy array.

3fill in blank

hard

Fix the error in the code to solve the system Ax = b using numpy.

NumPy

x = np.linalg.[1](A, b)

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

Asolve

Bdet

Cinv

Ddot

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.linalg.inv() and then multiplying, which is less efficient.

Using np.dot() which only does matrix multiplication.

The function np.linalg.solve() solves the linear system Ax = b directly.

4fill in blank

hard

Fill both blanks to create vector b and solve the system Ax = b.

NumPy

b = np.array([1])
x = np.linalg.solve(A, [2])

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

A[9, 8]

Bb

C[[9], [8]]

DA

Attempts:

3 left

💡 Hint

Common Mistakes

Using a 2D array for b which may cause shape errors.

Passing A instead of b to solve.

Vector b is a 1D numpy array with values [9, 8]. Then we pass b to np.linalg.solve().

5fill in blank

hard

Fill all three blanks to create matrix A, vector b, and solve for x.

NumPy

A = np.array([1])
b = np.array([2])
x = np.linalg.solve([3], b)

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

A[[4, 2], [3, 1]]

B[7, 5]

CA

D[[7], [5]]

Attempts:

3 left

💡 Hint

Common Mistakes

Passing b instead of A as the first argument to solve.

Using 2D array for b which is unnecessary here.

Matrix A and vector b are defined as numpy arrays. Then np.linalg.solve() uses A and b to find x.