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# scipy.odr.polynomial

scipy.odr.polynomial(order)

  Factory function for a general polynomial model.

  Parameters:
    order int or sequence

      If an integer, it becomes the order of the polynomial to fit. If a sequence of numbers, then these are the explicit powers in the polynomial. A constant term (power 0) is always included, so don’t include 0. Thus, polynomial(n) is equivalent to polynomial(range(1, n+1)).

  Returns:
    polynomial Model instance

      Model instance.

  Examples

  We can fit an input data using orthogonal distance regression (ODR) with a polynomial model:

      >>> import numpy as np
      >>> import matplotlib.pyplot as plt
      >>> from scipy import odr
      >>> x = np.linspace(0.0, 5.0)
      >>> y = np.sin(x)
      >>> poly_model = odr.polynomial(3)  # using third order polynomial model
      >>> data = odr.Data(x, y)
      >>> odr_obj = odr.ODR(data, poly_model)
      >>> output = odr_obj.run()  # running ODR fitting
      >>> poly = np.poly1d(output.beta[::-1])
      >>> poly_y = poly(x)
      >>> plt.plot(x, y, label="input data")
      >>> plt.plot(x, poly_y, label="polynomial ODR")
      >>> plt.legend()
      >>> plt.show()