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Plot Filter ​

This demo demonstrates visualizing filter frequency and phase responses to verify filter characteristics before applying them to data.

What is Filter Visualization? ​

Filter response plots show how a filter affects different frequencies:

  • Magnitude response: Attenuation (in dB) at each frequency

  • Phase response: Time delays introduced across frequencies

  • Cutoff characteristics: Transition band steepness and rolloff

Why Visualize Filters? ​

Verify design parameters:

  • Confirm cutoff frequencies are correct

  • Check passband and stopband behavior

  • Ensure appropriate attenuation levels

Identify potential issues:

  • Excessive ripple in passband

  • Slow transition bands

  • Phase distortion effects

Documentation:

  • Include in methods sections

  • Show filter characteristics clearly

  • Support reproducibility

Filter Types Supported ​

High-pass filters:

  • Remove slow drifts and DC offset

  • Typical: 0.1-1 Hz cutoff

  • Preserve task-related activity

Low-pass filters:

  • Remove high-frequency noise

  • Typical: 30-40 Hz cutoff

  • Anti-aliasing before downsampling

Band-pass filters:

  • Isolate specific frequency ranges

  • Combine high-pass and low-pass

  • Focus on frequency bands of interest

Filter Methods ​

IIR (Infinite Impulse Response):

  • Butterworth filters

  • Efficient computation

  • Steeper rolloff with fewer coefficients

  • Can introduce phase distortion

FIR (Finite Impulse Response):

  • Linear phase (no distortion)

  • Requires more coefficients

  • Computationally more expensive

  • Symmetric impulse response

Visualization Features ​

Reference lines:

  • Common attenuation levels (-3dB, -6dB, -12dB)

  • Highlight filter characteristics

  • Customizable positions and styling

Customization:

  • Line colors and widths

  • Title and labels

  • Frequency resolution (n_points)

  • Reference line positions

Workflow Summary ​

This demo shows filter response visualization:

Create Filters ​

  • Lowpass IIR filter (30 Hz)

  • Highpass IIR filter (1 Hz)

  • Lowpass FIR filter (40 Hz)

  • Various cutoff frequencies

Plot Responses ​

  • Basic magnitude response plots

  • Compare IIR vs FIR characteristics

  • Visualize different cutoffs

Customize Appearance ​

  • Custom colors and line widths

  • Reference lines at specific dB levels

  • Titles and styling options

Verify Characteristics ​

  • Check cutoff frequency accuracy

  • Assess transition band steepness

  • Evaluate filter suitability

Code Examples ​

Show Code
julia
# Demo: Filter Visualization
# Shows filter frequency response and impulse response visualization.

using EegFun
using GLMakie

# Create lowpass IIR filter using create_filter
filter_info = EegFun.create_lowpass_filter(30.0, 256.0; filter_method = "iir")

# Plot filter response
EegFun.plot_filter_response(filter_info)

# Test with custom parameters
EegFun.plot_filter_response(
    filter_info,
    title = "Custom Lowpass Filter Plot",
    color = :blue,
    linewidth = 3,
    reference_lines = [-3, -12, -24],
    reference_color = :red,
    n_points = 1000,
)

# Create highpass IIR filter using create_filter
filter_info = EegFun.create_highpass_filter(1.0, 256.0; filter_method = "iir")
EegFun.plot_filter_response(filter_info, title = "High-pass Filter", color = :green)

# Create FIR filter using create_filter
filter_info = EegFun.create_lowpass_filter(40.0, 256.0; filter_method = "fir")
EegFun.plot_filter_response(filter_info, title = "FIR Lowpass Filter", color = :purple)

# Test additional filter with separate plotting
filter_info = EegFun.create_highpass_filter(0.5, 256.0; filter_method = "iir")
EegFun.plot_filter_response(filter_info, title = "High-pass Filter with Plot")

See Also ​