# PyWavelets - Wavelet Transforms in Python¶

PyWavelets is open source wavelet transform software for Python. It combines a simple high level interface with low level C and Cython performance.

PyWavelets is very easy to use and get started with. Just install the package, open the Python interactive shell and type:

>>> import pywt >>> cA, cD = pywt.dwt([1, 2, 3, 4], 'db1')

Voilà! Computing wavelet transforms has never been so simple :)

Here is a slightly more involved example of applying a digital wavelet transform to an image:

```
import numpy as np
import matplotlib.pyplot as plt
import pywt
import pywt.data
# Load image
original = pywt.data.camera()
# Wavelet transform of image, and plot approximation and details
titles = ['Approximation', ' Horizontal detail',
'Vertical detail', 'Diagonal detail']
coeffs2 = pywt.dwt2(original, 'bior1.3')
LL, (LH, HL, HH) = coeffs2
fig = plt.figure(figsize=(12, 3))
for i, a in enumerate([LL, LH, HL, HH]):
ax = fig.add_subplot(1, 4, i + 1)
ax.imshow(a, interpolation="nearest", cmap=plt.cm.gray)
ax.set_title(titles[i], fontsize=10)
ax.set_xticks([])
ax.set_yticks([])
fig.tight_layout()
plt.show()
```

## Main features¶

The main features of PyWavelets are:

- 1D, 2D and nD Forward and Inverse Discrete Wavelet Transform (DWT and IDWT)
- 1D, 2D and nD Multilevel DWT and IDWT
- 1D, 2D and nD Stationary Wavelet Transform (Undecimated Wavelet Transform)
- 1D and 2D Wavelet Packet decomposition and reconstruction
- 1D Continuous Wavelet Transform
- Computing Approximations of wavelet and scaling functions
- Over 100 built-in wavelet filters and support for custom wavelets
- Single and double precision calculations
- Real and complex calculations
- Results compatible with Matlab Wavelet Toolbox (TM)

## Getting help¶

Use GitHub Issues, StackOverflow, or the PyWavelets discussions group to post your comments or questions.

## License¶

PyWavelets is a free Open Source software released under the MIT license.

## Citing¶

If you use PyWavelets in a scientific publication, we would appreciate citations of the project:

Lee G, Gommers R, Wasilewski F, Wohlfahrt K, O’Leary A, Nahrstaedt H, and Contributors, “PyWavelets - Wavelet Transforms in Python”, 2006-, https://github.com/PyWavelets/pywt [Online; accessed 2018-MM-DD].