scipy.odr.quadratic¶

scipy.odr.quadratic = <scipy.odr.models._QuadraticModel object>[source]¶

Quadratic model

This model is defined by \(y = \beta_0 x^2 + \beta_1 x + \beta_2\)

Examples

We can calculate orthogonal distance regression with a quadratic model:

>>> from scipy import odr
>>> x = np.linspace(0.0, 5.0)
>>> y = 1.0 * x ** 2 + 2.0 * x + 3.0
>>> data = odr.Data(x, y)
>>> odr_obj = odr.ODR(data, odr.quadratic)
>>> output = odr_obj.run()
>>> print(output.beta)
[1. 2. 3.]

scipy.odr.unilinear Optimization and root finding (scipy.optimize)