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Add type-hints to SKOptLearner #376

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Add type-hints to SKOptLearner #376

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18 changes: 12 additions & 6 deletions adaptive/learner/skopt_learner.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
from __future__ import annotations

import collections
from typing import Callable

import numpy as np
from skopt import Optimizer
Expand All @@ -25,8 +26,8 @@ class SKOptLearner(Optimizer, BaseLearner):
Arguments to pass to ``skopt.Optimizer``.
"""

def __init__(self, function, **kwargs):
self.function = function
def __init__(self, function: Callable, **kwargs) -> None:
self.function = function # type: ignore
self.pending_points = set()
self.data = collections.OrderedDict()
self._kwargs = kwargs
Expand All @@ -36,7 +37,7 @@ def new(self) -> SKOptLearner:
"""Return a new `~adaptive.SKOptLearner` without the data."""
return SKOptLearner(self.function, **self._kwargs)

def tell(self, x, y, fit=True):
def tell(self, x: float | list[float], y: float, fit: bool = True) -> None:
if isinstance(x, collections.abc.Iterable):
self.pending_points.discard(tuple(x))
self.data[tuple(x)] = y
Expand All @@ -55,7 +56,7 @@ def remove_unfinished(self):
pass

@cache_latest
def loss(self, real=True):
def loss(self, real: bool = True) -> float:
if not self.models:
return np.inf
else:
Expand All @@ -65,7 +66,12 @@ def loss(self, real=True):
# estimator of loss, but it is the cheapest.
return 1 - model.score(self.Xi, self.yi)

def ask(self, n, tell_pending=True):
def ask(
self, n: int, tell_pending: bool = True
) -> (
tuple[list[float], list[float]]
| tuple[list[list[float]], list[float]] # XXX: this indicates a bug!
):
if not tell_pending:
raise NotImplementedError(
"Asking points is an irreversible "
Expand All @@ -79,7 +85,7 @@ def ask(self, n, tell_pending=True):
return [p[0] for p in points], [self.loss() / n] * n

@property
def npoints(self):
def npoints(self) -> int:
"""Number of evaluated points."""
return len(self.Xi)

Expand Down