### Circular-linear regression example

Source: https://pycircstat.readthedocs.io/en/latest/regression.html

Generates toy data with a circular predictor, trains a CircularLinearRegression model, predicts on the training data, and prints the learned coefficients. The example uses NumPy for data generation and assumes the pycircstat library is installed.

```python
# generate toy data
alpha = np.random.rand(200)*np.pi*2
a0 = np.random.rand()*2*np.pi
A0 = np.abs(np.random.randn())
m0 = np.random.randn()*10
x = m0 + A0*np.cos(alpha - a0)

# generate regressor
reg = CircularLinearRegression()

# train regressor
reg.train(alpha, x)

# predict
x2 = reg(alpha)

# look at coefficients
print(reg[:])
```

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