LeastSquaresSolver.solve() - Code Metrics - davidrpugh/pyCollocation - Measure and Improve Code Quality continuously with Scrutinizer

LeastSquaresSolver.solve() B
last analyzed 2016-07-20 11:19 UTC

↳ Parent: LeastSquaresSolver

Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes	5
Bugs	0	Features	0

Metric	Value
cc	1
c	5
b	0
f	0
dl	0
loc	34
rs	8.8571

"""
Solvers for over-identified systems.

@author : davidrpugh

"""
from scipy import optimize

from . import solvers


class LeastSquaresSolver(solvers.Solver):

    def solve(self, basis_kwargs, boundary_points, coefs_array, nodes, problem,
              **solver_options):
        """
        Solve a boundary value problem using the collocation method.

        Parameters
        ----------
        basis_kwargs : dict
            Dictionary of keyword arguments used to build basis functions.
        coefs_array : numpy.ndarray
            Array of coefficients for basis functions defining the initial
            condition.
        problem : bvp.TwoPointBVPLike
            A two-point boundary value problem (BVP) to solve.
        solver_options : dict
            Dictionary of options to pass to the non-linear equation solver.

        Return
        ------
        solution: solutions.SolutionLike
            An instance of the SolutionLike class representing the solution to
            the two-point boundary value problem (BVP)

        Notes
        -----

        """
        result = optimize.leastsq(self._compute_residuals,
                                  x0=coefs_array,
                                  args=(basis_kwargs, boundary_points, nodes, problem),
                                  **solver_options)
        solution = self._solution_factory(basis_kwargs, result[0], nodes,
                                          problem, result)
        return solution


1			"""
2			Solvers for over-identified systems.
3
4			@author : davidrpugh
5
6			"""
7			from scipy import optimize
8
9			from . import solvers
10
11
12			class LeastSquaresSolver(solvers.Solver):
13
14			def solve(self, basis_kwargs, boundary_points, coefs_array, nodes, problem,
15			**solver_options):
16			"""
17			Solve a boundary value problem using the collocation method.
18
19			Parameters
20			----------
21			basis_kwargs : dict
22			Dictionary of keyword arguments used to build basis functions.
23			coefs_array : numpy.ndarray
24			Array of coefficients for basis functions defining the initial
25			condition.
26			problem : bvp.TwoPointBVPLike
27			A two-point boundary value problem (BVP) to solve.
28			solver_options : dict
29			Dictionary of options to pass to the non-linear equation solver.
30
31			Return
32			------
33			solution: solutions.SolutionLike
34			An instance of the SolutionLike class representing the solution to
35			the two-point boundary value problem (BVP)
36
37			Notes
38			-----
39
40			"""
41			result = optimize.leastsq(self._compute_residuals,
42			x0=coefs_array,
43			args=(basis_kwargs, boundary_points, nodes, problem),
44			**solver_options)
45			solution = self._solution_factory(basis_kwargs, result[0], nodes,
46			problem, result)
47			return solution
48

davidrpugh / pyCollocation

LeastSquaresSolver.solve() B last analyzed 2016-07-20 11:19 UTC

Complexity

Size

Duplication

Importance

Duplication Side-by-Side

Filter issues like

LeastSquaresSolver.solve() B
last analyzed 2016-07-20 11:19 UTC