Correlation with np.correlate() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the correlation of two arrays using numpy.

NumPy

import numpy as np

x = np.array([1, 2, 3])
y = np.array([0, 1, 0])
result = np.correlate(x, y, [1])
print(result)

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

A"full"

B"valid"

C"same"

D"none"

Attempts:

3 left

💡 Hint

Common Mistakes

Using an invalid mode string causes an error.

Using "valid" or "same" changes the output size.

The mode "full" returns the full discrete linear correlation, which is the default and most complete result.

2fill in blank

medium

Complete the code to compute the correlation of two arrays with mode 'valid'.

NumPy

import numpy as np

a = np.array([1, 2, 3, 4])
b = np.array([0, 1, 0])
correlation = np.correlate(a, b, mode=[1])
print(correlation)

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

A"same"

B"partial"

C"valid"

D"full"

Attempts:

3 left

💡 Hint

Common Mistakes

Using an unsupported mode string causes an error.

Confusing "valid" with "full" changes the output length.

The mode "valid" returns only those parts of the correlation that are computed without zero-padded edges.

3fill in blank

hard

Fix the error in the code to correctly compute correlation with np.correlate.

NumPy

import numpy as np

x = np.array([1, 2, 3])
y = np.array([0, 1, 0])
result = np.correlate(x, y, [1])
print(result)

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

A"valid"

Bfull

Cvalid

D"full"

Attempts:

3 left

💡 Hint

Common Mistakes

Passing mode without quotes causes a TypeError.

Using an invalid mode string causes a ValueError.

The mode argument must be a string, so it needs quotes around it.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each number to its correlation with a fixed array.

NumPy

import numpy as np

fixed = np.array([1, 0, -1])
numbers = [1, 2, 3]
correlations = {num: np.correlate(np.array([num, num, num]), fixed, mode=[1])[[2]] for num in numbers}
print(correlations)

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

A"valid"

B"full"

C0

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using an invalid mode string.

Using an index out of range.

Using mode "full" gives the full correlation array, and index 0 accesses the first correlation value.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word to the correlation of its length with a fixed array.

NumPy

import numpy as np

fixed = np.array([1, 2, 3])
words = ["cat", "dog", "bird"]
correlation_dict = {word: np.correlate(np.array([len(word)] * 3), fixed, mode=[1])[[2]] for word in words if len(word) [3] 3}
print(correlation_dict)

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

A"valid"

B0

C>

D"full"

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect mode strings.

Using wrong index values.

Using wrong comparison operators.

Use mode "full" for full correlation, index 0 for the first value, and filter words with length greater than 3.