Add marker to librosa waveplot python

When working with audio data in Python, the librosa library is a popular choice due to its extensive functionality. One common task is to add a marker to a waveplot generated using librosa. In this article, we will explore three different ways to achieve this.

Option 1: Using matplotlib

The first option is to use the matplotlib library to add a marker to the waveplot. Here’s how you can do it:

import librosa
import matplotlib.pyplot as plt

# Load audio data
audio, sr = librosa.load('audio.wav')

# Generate waveplot
plt.figure(figsize=(14, 5))
librosa.display.waveplot(audio, sr=sr)

# Add marker
plt.axvline(x=2, color='r', linestyle='--')

# Show plot
plt.show()

In this code, we first load the audio data using librosa. Then, we generate the waveplot using the waveplot function from librosa’s display module. Finally, we use matplotlib’s axvline function to add a vertical line at the desired position.

Option 2: Using seaborn

If you prefer a more visually appealing plot, you can use the seaborn library along with librosa. Here’s an example:

import librosa
import seaborn as sns

# Load audio data
audio, sr = librosa.load('audio.wav')

# Generate waveplot
plt.figure(figsize=(14, 5))
librosa.display.waveplot(audio, sr=sr)

# Add marker
sns.lineplot(x=[2, 2], y=[-1, 1], color='r', linestyle='--')

# Show plot
plt.show()

In this code, we use seaborn’s lineplot function to add a line segment at the desired position. The x and y arguments specify the start and end points of the line segment.

Option 3: Using plotly

If you prefer interactive plots, you can use the plotly library to add a marker to the waveplot. Here’s an example:

import librosa
import plotly.graph_objects as go

# Load audio data
audio, sr = librosa.load('audio.wav')

# Generate waveplot
fig = go.Figure(data=go.Scatter(y=audio))
fig.update_layout(title='Waveplot')

# Add marker
fig.add_shape(type='line', x0=2, y0=-1, x1=2, y1=1, line=dict(color='red', dash='dash'))

# Show plot
fig.show()

In this code, we use plotly’s Figure class to create the waveplot. Then, we use the add_shape method to add a line segment at the desired position.

After exploring these three options, it is clear that the best choice depends on your specific requirements. If you need a simple solution with basic functionality, option 1 using matplotlib is a good choice. If you prefer a more visually appealing plot, option 2 using seaborn is a great option. Finally, if you need an interactive plot, option 3 using plotly is the way to go. Consider your needs and choose the option that best suits your project.

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