Applying filters (lfilter, sosfilt) in SciPy - Mini Project: Build & Apply

Applying filters with lfilter and sosfilt in SciPy

📖 Scenario: You are working with a noisy sensor signal collected from a weather station. The signal contains unwanted high-frequency noise that makes it hard to analyze the true temperature trend.Your task is to apply digital filters to clean the signal so it becomes smoother and easier to interpret.

🎯 Goal: Build a Python program that creates a noisy signal, sets up filter coefficients, applies the filters using lfilter and sosfilt from SciPy, and then prints the filtered results.

📋 What You'll Learn

Create a noisy signal as a list of floats called noisy_signal with exact values

Create filter coefficients as a tuple called b_a with exact values

Create second-order sections filter coefficients as a list called sos with exact values

Use lfilter with b_a and noisy_signal to create filtered_lfilter

Use sosfilt with sos and noisy_signal to create filtered_sosfilt

Print filtered_lfilter and filtered_sosfilt exactly as shown

💡 Why This Matters

🌍 Real World

Filtering noisy sensor data is common in weather stations, medical devices, and audio processing to get clearer signals.

💼 Career

Understanding how to apply digital filters is important for data scientists working with time series, signal processing, and sensor data analysis.

1

Create the noisy signal data

Create a list called noisy_signal with these exact float values: [0.0, 0.9, 0.1, 1.2, 0.3, 1.5, 0.2, 1.7, 0.1, 1.8]

SciPy

# Create the noisy_signal list with the exact values
# Your code here

Need a hint?

Use square brackets to create a list and separate values with commas.

2

Set up filter coefficients

Create a tuple called b_a with these exact values: ([0.2, 0.2, 0.2], [1.0, -0.5, 0.25]) and a list called sos with this exact nested list: [[0.2, 0.2, 0.2, 1.0, -0.5, 0.25]]

SciPy

noisy_signal = [0.0, 0.9, 0.1, 1.2, 0.3, 1.5, 0.2, 1.7, 0.1, 1.8]
# Create b_a tuple and sos list with exact values
# Your code here

Need a hint?

Use parentheses for tuples and square brackets for lists. Match the exact values and structure.

3

Apply filters using lfilter and sosfilt

Import lfilter and sosfilt from scipy.signal. Use lfilter with b_a[0], b_a[1], and noisy_signal to create filtered_lfilter. Use sosfilt with sos and noisy_signal to create filtered_sosfilt.

SciPy

noisy_signal = [0.0, 0.9, 0.1, 1.2, 0.3, 1.5, 0.2, 1.7, 0.1, 1.8]
b_a = ([0.2, 0.2, 0.2], [1.0, -0.5, 0.25])
sos = [[0.2, 0.2, 0.2, 1.0, -0.5, 0.25]]
# Import lfilter and sosfilt and apply filters
# Your code here

Need a hint?

Use from scipy.signal import lfilter, sosfilt to import. Then call the functions with the correct arguments.

4

Print the filtered results

Print filtered_lfilter and filtered_sosfilt exactly as shown, each on its own line.

SciPy

from scipy.signal import lfilter, sosfilt

noisy_signal = [0.0, 0.9, 0.1, 1.2, 0.3, 1.5, 0.2, 1.7, 0.1, 1.8]
b_a = ([0.2, 0.2, 0.2], [1.0, -0.5, 0.25])
sos = [[0.2, 0.2, 0.2, 1.0, -0.5, 0.25]]

filtered_lfilter = lfilter(b_a[0], b_a[1], noisy_signal)
filtered_sosfilt = sosfilt(sos, noisy_signal)
# Print filtered_lfilter and filtered_sosfilt
# Your code here

Need a hint?

Use two print() statements, one for each filtered array.