Median and uniform filters in SciPy - Mini Project: Build & Apply

Median and Uniform Filters with SciPy

📖 Scenario: You have a noisy 1D signal from a sensor. You want to clean it up to see the true pattern better.

🎯 Goal: Apply median and uniform filters to smooth the noisy signal and compare the results.

📋 What You'll Learn

Create a noisy signal as a list

Set a filter size variable

Apply median and uniform filters using scipy.ndimage

Print the filtered results

💡 Why This Matters

🌍 Real World

Sensors often produce noisy data. Filters help clean data so we can understand the true signal.

💼 Career

Data scientists use filtering techniques to preprocess data before analysis or machine learning.

1

Create a noisy signal

Create a list called signal with these exact values: [2, 80, 6, 3, 2, 75, 5, 3, 2]

SciPy

# Create the noisy signal list called signal
# Your code here

Need a hint?

Use square brackets and commas to create the list exactly as shown.

2

Set the filter size

Create a variable called filter_size and set it to 3

SciPy

signal = [2, 80, 6, 3, 2, 75, 5, 3, 2]
# Set filter_size to 3
# Your code here

Need a hint?

Just assign the number 3 to the variable filter_size.

3

Apply median and uniform filters

Import median_filter and uniform_filter from scipy.ndimage. Then create two variables: median_filtered and uniform_filtered. Use median_filter on signal with size filter_size for median_filtered. Use uniform_filter on signal with size filter_size for uniform_filtered.

SciPy

signal = [2, 80, 6, 3, 2, 75, 5, 3, 2]
filter_size = 3
# Import median_filter and uniform_filter from scipy.ndimage
# Apply median_filter and uniform_filter to signal
# Your code here

Need a hint?

Use the exact function names and variable names as shown.

4

Print the filtered results

Print median_filtered and uniform_filtered each on its own line.

SciPy

from scipy.ndimage import median_filter, uniform_filter

signal = [2, 80, 6, 3, 2, 75, 5, 3, 2]
filter_size = 3

median_filtered = median_filter(signal, size=filter_size)
uniform_filtered = uniform_filter(signal, size=filter_size)
# Print median_filtered and uniform_filtered
# Your code here

Need a hint?

Use two print statements, one for each filtered array.