# plot\_tempogram

> plot\_tempogram(y: npt.ArrayLike, sr: int, type: str = 'autocorr', hop\_length: int = 512)

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Function description
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To visualize the result of dynamic tempo estimation

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Parameter
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y: input signal array

sr: sampling rate&#x20;

type: algorithms to use&#x20;

*autocoor: by auto-correlation (default)*&#x20;

*fourier: STFT*&#x20;

hop\_length: hop size between frames

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Return
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None

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Example
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```python
from audioviz import *
import librosa
import numpy as np
from audioviz import BeatAnalysis

y, sr = librosa.load('Mozart_Turkish_March.wav', duration = 45)
BeatAnalysis.plot_tempogram(y = y, sr = sr)
```

<figure><img src="https://3500702469-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fh9wXRXdIQoYFVdZ0YFUo%2Fuploads%2FBRKMkHktwCwA07F3PADq%2Fimage.png?alt=media&#x26;token=8e555420-7896-4803-8117-3abea1bbb94d" alt=""><figcaption></figcaption></figure>
