Convolution with np.convolve() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform convolution of two arrays using numpy.

NumPy

import numpy as np

result = np.[1](a, b)
print(result)

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

Adot

Bconvolve

Cmultiply

Dadd

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.dot instead of np.convolve

Using np.multiply which does element-wise multiplication

Using np.add which sums arrays element-wise

The np.convolve() function computes the convolution of two arrays.

2fill in blank

medium

Complete the code to specify the convolution mode as 'valid'.

NumPy

import numpy as np

result = np.convolve(a, b, mode=[1])
print(result)

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

A'valid'

B'same'

C'full'

D'extend'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'full' mode which returns the complete convolution

Using 'same' mode which returns output the same size as first array

Using an invalid mode string

The mode='valid' returns output only where the signals fully overlap.

3fill in blank

hard

Fix the error in the code to correctly perform convolution.

NumPy

import numpy as np

a = [1, 2, 3]
b = [0, 1, 0.5]

result = np.convolve([1], b)
print(result)

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

Aa

Bb

Cresult

Dnp

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the order of arrays

Passing the result variable instead of input arrays

Passing the numpy module instead of arrays

The first argument to np.convolve() should be the first array a.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values for words longer than 3 characters.

NumPy

words = ['data', 'science', 'ai', 'ml', 'python']
lengths = { [1]: [2] for word in words if len(word) > 3 }
print(lengths)

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Aword

Blen(word)

Cword.upper()

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using the length as key instead of value

Using word.upper() as key which changes the word

Using len function object instead of calling it

The dictionary comprehension uses the word as key and its length as value.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys, their lengths as values, only for words longer than 3 characters.

NumPy

words = ['data', 'science', 'ai', 'ml', 'python']
lengths = { [1]: [2] for word in words if len(word) [3] 3 }
print(lengths)

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

Aword.upper()

Blen(word)

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase words as keys

Using '<' instead of '>' in condition

Using the function len without parentheses

The dictionary comprehension uses uppercase words as keys, their lengths as values, and filters words longer than 3 characters.