Regression Models

Example for circular-linear regression

# 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[:])