Correlation (correlate) in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the correlate function from scipy.signal.

SciPy

from scipy.signal import [1]

result = correlate([1, 2, 3], [0, 1, 0.5])
print(result)

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Acorrelate

Bconvolve

Cfftconvolve

Dcorrelation

Attempts:

3 left

💡 Hint

Common Mistakes

Importing 'convolve' instead of 'correlate'.

Using a non-existent function name.

The correlate function is imported from scipy.signal to compute the correlation between two sequences.

2fill in blank

medium

Complete the code to compute the full correlation of two lists.

SciPy

from scipy.signal import correlate

x = [1, 2, 3]
y = [0, 1, 0.5]
result = correlate(x, y, mode=[1])
print(result)

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A'valid'

B'partial'

C'full'

D'same'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'valid' which returns only points where signals fully overlap.

Using 'same' which returns output of the same size as the first input.

The mode='full' computes the full discrete linear correlation of the inputs.

3fill in blank

hard

Fix the error in the code to correctly compute correlation with 'valid' mode.

SciPy

from scipy.signal import correlate

x = [1, 2, 3, 4]
y = [1, 0, 1]
result = correlate(x, y, mode=[1])
print(result)

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A'valid'

B'full'

C'same'

D'invalid'

Attempts:

3 left

💡 Hint

Common Mistakes

Using an invalid mode string causes an error.

Using 'full' or 'same' when 'valid' is required.

The mode must be set to 'valid' to compute correlation only where the signals fully overlap without zero-padding.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each element in x to its correlation with y using 'same' mode.

SciPy

from scipy.signal import correlate

x = [1, 2, 3]
y = [0, 1, 0.5]
correlations = [1]: correlate([[2]], y, mode='same')[1] for [1] in x}
print(correlations)

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Aval

Bx

Cy

Delem

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inside and outside the comprehension.

Using 'x' or 'y' as variable names inside the comprehension causing confusion.

We use a variable name (e.g., 'elem') to iterate over x. For each element, we create a list with that element and compute correlation with y. The dictionary maps each element to the correlation value at the center index.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word in words to the correlation length with a pattern, only if the correlation peak is greater than 1.

SciPy

from scipy.signal import correlate

words = ['cat', 'dog', 'bird']
pattern = [1, 0, 1]
result = [1]: len([2]) for [1] in words if max(correlate([ord(c) for c in [1]], pattern)) > 1}
print(result)

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Aword

Dpattern

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently.

Using 'pattern' instead of the word variable inside the comprehension.

The comprehension iterates over each word in words. For each word, it converts characters to their ASCII codes, correlates with pattern, and includes the word in the dictionary if the maximum correlation is greater than 1. The dictionary maps the word to its length.