Windowing methods (Hamming, Hanning, Blackman) in Signal Processing - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a Hamming window of length 64 using NumPy.

Signal Processing

import numpy as np
window = np.[1](64)
print(window)

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

Ahamming

Bbartlett

Cblackman

Dhanning

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'hanning' instead of 'hamming' for a Hamming window.

Misspelling the function name.

Using a window function not related to Hamming.

The np.hamming function generates a Hamming window of the specified length.

2fill in blank

medium

Complete the code to generate a Blackman window of length 128 using SciPy.

Signal Processing

from scipy import signal
window = signal.[1](128)
print(window)

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Abartlett

Bhanning

Chamming

Dblackman

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'hamming' or 'hanning' instead of 'blackman'.

Confusing NumPy and SciPy window functions.

Incorrect function name casing.

The signal.blackman function from SciPy generates a Blackman window.

3fill in blank

hard

Fix the error in the code to generate a Hanning window of length 50 using NumPy.

Signal Processing

import numpy as np
window = np.[1](50)
print(window)

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Ablackman

Bhamming

Channing

Dhanning_window

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent function name like 'hanning_window'.

Confusing Hamming and Hanning window functions.

Incorrect capitalization.

The correct NumPy function for a Hanning window is np.hanning. There is no function named hanning_window.

4fill in blank

hard

Fill both blanks to create a dictionary with window names as keys and their corresponding NumPy window arrays of length 32 as values.

Signal Processing

import numpy as np
windows = {
    'Hamming': np.[1](32),
    'Blackman': np.[2](32)
}
print(windows)

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Ahamming

Bhanning

Cblackman

Dbartlett

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up window function names.

Using SciPy functions instead of NumPy.

Using the same function for both windows.

Use np.hamming for the Hamming window and np.blackman for the Blackman window.

5fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps window names to their corresponding SciPy window arrays of length 40, but only include windows with names starting with 'B'.

Signal Processing

from scipy import signal
window_names = ['Hamming', 'Blackman', 'Bartlett', 'Hanning']
windows = {name: signal.[1](40) for name in window_names if name.[2]('B')}
print(windows)

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Ahamming

Bstartswith

Cblackman

Dhanning

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong window function for the filtered names.

Using 'startswith' incorrectly or misspelling it.

Not filtering the names properly.

Use signal.blackman for the window function, and startswith to filter names starting with 'B'. The comprehension uses the same function for all included names.