Legendre2D¶
-
class
astropy.modeling.polynomial.
Legendre2D
(x_degree, y_degree, x_domain=None, x_window=[-1, 1], y_domain=None, y_window=[-1, 1], n_models=None, model_set_axis=None, name=None, meta=None, **params)[source] [edit on github]¶ Bases:
astropy.modeling.polynomial.OrthoPolynomialBase
Bivariate Legendre series.
Defined as:
\[P_{n_m}(x,y) = \sum_{n,m=0}^{n=d,m=d}C_{nm} L_n(x ) L_m(y)\]where
L_n(x)
andL_m(y)
are Legendre polynomials.Parameters: - x_degree : int
degree in x
- y_degree : int
degree in y
- x_domain : list or None, optional
domain of the x independent variable
- y_domain : list or None, optional
domain of the y independent variable
- x_window : list or None, optional
range of the x independent variable
- y_window : list or None, optional
range of the y independent variable
- **params : dict
keyword: value pairs, representing parameter_name: value
Other Parameters: - fixed : a dict, optional
A dictionary
{parameter_name: boolean}
of parameters to not be varied during fitting. True means the parameter is held fixed. Alternatively thefixed
property of a parameter may be used.- tied : dict, optional
A dictionary
{parameter_name: callable}
of parameters which are linked to some other parameter. The dictionary values are callables providing the linking relationship. Alternatively thetied
property of a parameter may be used.- bounds : dict, optional
A dictionary
{parameter_name: value}
of lower and upper bounds of parameters. Keys are parameter names. Values are a list or a tuple of length 2 giving the desired range for the parameter. Alternatively, themin
andmax
properties of a parameter may be used.- eqcons : list, optional
A list of functions of length
n
such thateqcons[j](x0,*args) == 0.0
in a successfully optimized problem.- ineqcons : list, optional
A list of functions of length
n
such thatieqcons[j](x0,*args) >= 0.0
is a successfully optimized problem.
Notes
Model formula:
\[P(x) = \sum_{i=0}^{i=n}C_{i} * L_{i}(x)\]where
L_{i}
is the corresponding Legendre polynomial.This model does not support the use of units/quantities, because each term in the sum of Legendre polynomials is a polynomial in x - since the coefficients within each Legendre polynomial are fixed, we can’t use quantities for x since the units would not be compatible. For example, the third Legendre polynomial (P2) is 1.5x^2-0.5, but if x was specified with units, 1.5x^2 and -0.5 would have incompatible units.
Methods Summary
fit_deriv
(x, y, *params)Derivatives with respect to the coefficients. Methods Documentation
-
fit_deriv
(x, y, *params)[source] [edit on github]¶ Derivatives with respect to the coefficients. This is an array with Legendre polynomials:
Lx0Ly0 Lx1Ly0…LxnLy0…LxnLym
Parameters: - x : ndarray
input
- y : ndarray
input
- params : throw away parameter
parameter list returned by non-linear fitters
Returns: - result : ndarray
The Vandermonde matrix