# PySDKit: signal decomposition in Python
[](https://pypi.org/project/PySDKit/)  [](https://codecov.io/gh/wwhenxuan/PySDKit) [](https://arxiv.org/abs/1234.56789) [](https://pepy.tech/project/pysdkit)  
A Python library for signal decomposition algorithms
## Installation
You can install `PySDKit` through pip.
~~~
pip install pysdkit
~~~
We only used [`NumPy`](https://numpy.org/), [`Scipy`](https://scipy.org/) and [`matplotlib`](https://matplotlib.org/) when developing the project.
## Example script
This project integrates simple signal processing methods, signal decomposition and visualization, and builds a general interface similar to [`Scikit-learn`](https://scikit-learn.org/stable/). It is mainly divided into three steps:
1. Import the signal decomposition method;
2. Create an instance for signal decomposition;
3. Use the `fit_transform` method to implement signal decomposition;
4. Visualize and analyze the original signal and the intrinsic mode functions IMFs obtained by decomposition.
~~~python
from pysdkit import EMD
from pysdkit.data import test_emd
from pysdkit.plot import plot_IMFs
t, signal = test_emd()
# create an instance for signal decomposition
emd = EMD()
# implement signal decomposition
IMFs = emd.fit_transform(signal, max_imf=2)
plot_IMFs(signal, IMFs)
~~~
The EMD in the above example is the most classic `empirical mode decomposition` algorithm in signal decomposition. For more complex signals, you can try other algorithms such as variational mode decomposition ([`VMD`](https://ieeexplore.ieee.org/abstract/document/6655981)).
~~~python
from pysdkit import VMD
# load new signal
signal = np.load("example.npy")
# use variational mode decomposition
vmd = VMD(alpha=500, K=3, tau=0.0, tol=1e-9)
IMFs = vmd.fit_transform(signal=signal)
print(IMFs.shape)
vmd.plot_IMFs(save_figure=True)
~~~
Better observe the characteristics of the decomposed intrinsic mode function in the frequency domain.
~~~python
from pysdkit.plot import plot_IMFs_amplitude_spectra
# frequency domain visualization
plot_IMFs_amplitude_spectra(IMFs, smooth="exp") # use exp smooth
~~~
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