adaptive.IntegratorLearner

class adaptive.IntegratorLearner(*args, **kwargs)[source]

Bases: adaptive.learner.base_learner.BaseLearner

add_ival(ival)[source]
property approximating_intervals
ask(n, tell_pending=True)[source]

Choose points for learners.

data: dict
done()[source]
property err
property igral
loss(real=True)[source]

Return the loss for the current state of the learner.

Parameters

real (bool, default: True) – If False, return the “expected” loss, i.e. the loss including the as-yet unevaluated points (possibly by interpolation).

property npoints

Number of evaluated points.

pending_points: set
plot()[source]
pop_from_stack(n)[source]
propagate_removed(ival)[source]
remove_unfinished()[source]

Remove uncomputed data from the learner.

tell(point, value)[source]

Tell the learner about a single value.

Parameters

  • x (A value from the function domain) –

  • y (A value from the function image) –

tell_pending()[source]

Tell the learner that ‘x’ has been requested such that it’s not suggested again.