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¶

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¶

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.