conatus.expert.NLBVPSolution¶

class conatus.expert.NLBVPSolution(coeffs: 'dict[str, np.ndarray]', iterations: 'list[NewtonIteration]', converged: 'bool', plan: 'Plan', settings: 'dict' = <factory>, trivial: 'bool' = False, notes: 'list' = <factory>)[source]¶

Bases: object

Parameters:

coeffs (dict[str, ndarray])
iterations (list[NewtonIteration])
converged (bool)
plan (Plan)
settings (dict)
trivial (bool)
notes (list)

coeffs: dict[str, ndarray]¶

iterations: list[NewtonIteration]¶

converged: bool¶

plan: Plan¶

settings: dict¶

trivial: bool = False¶: the iterate converged to the trivial state (NEWTON_TRIVIAL_FRACTION)

notes: list¶

grid(name)[source]¶

Parameters:: name (str)
Return type:: ndarray

value(name)[source]¶

Value of a constant (scalar) unknown.

Parameters:: name (str)
Return type:: float

property residual: float¶

observed_orders()[source]¶

q_k = log(r_{k+1}/r_k) / log(r_k/r_{k-1}) on the residual sequence (2 = quadratic).

Return type:: list[float]

as_guess()[source]¶

This solution as an initial guess (continuation), by variable, in coefficient layout.

Return type:: dict

explain()[source]¶

Return type:: str