# SSM\_chorma

> SSM\_chorma(wav\_filename:str, anno\_csv: str, hop\_size: int = 4096, Nfft: int = 1024)

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Function description
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To show the self-similarity matrix calculated by chroma

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Parameter
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wav\_filename: .wav filename&#x20;

anno\_csv: segmentation .csv&#x20;

hop\_size: hop size between frames&#x20;

Nfft: numbers of points of FFT

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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 StructureAnalysis

y, sr = librosa.load('Mozart_Turkish_March.wav', duration = 45)
StructureAnalysis.SSM_chorma('./Mozart_Turkish_March.wav', 'anno.csv')
```

<figure><img src="https://3500702469-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fh9wXRXdIQoYFVdZ0YFUo%2Fuploads%2FuZcn0qAAzFm4Rl4J5Y3S%2Fimage.png?alt=media&#x26;token=1ea94ff1-34da-48dd-a61d-94406899a605" alt=""><figcaption></figcaption></figure>
