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ci(mypy): fix mypy errors from numpy and attrs libs #129

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Merged
dustalov merged 6 commits into from
Jan 13, 2025
Merged

ci(mypy): fix mypy errors from numpy and attrs libs #129

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c829140
ci(mypy): remove attrs type ignore
shenxiangzhuang Jan 12, 2025
7d09dc0
fix: more mypy errors
shenxiangzhuang Jan 13, 2025
1bd75a0
remove unused import
shenxiangzhuang Jan 13, 2025
9a91c7f
remove unused import and ignore
shenxiangzhuang Jan 13, 2025
4fe2ddb
fix: format error
shenxiangzhuang Jan 13, 2025
d270fa1
fix: unused error
shenxiangzhuang Jan 13, 2025
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4 changes: 3 additions & 1 deletion crowdkit/aggregation/classification/mace.py
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Original file line number Diff line number Diff line change
Expand Up @@ -313,7 +313,9 @@ def _initialize(self, n_workers: int, n_labels: int) -> None:
self.theta_priors_[:, 0] = self.alpha
self.theta_priors_[:, 1] = self.beta

self.strategy_priors_ = np.ones((n_workers, n_labels)) * 10.0
self.strategy_priors_ = np.multiply(
10.0, np.ones((n_workers, n_labels)), dtype=np.float64
)

def _e_step(
self,
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2 changes: 1 addition & 1 deletion crowdkit/aggregation/image_segmentation/segmentation_rasa.py
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Expand Up @@ -105,7 +105,7 @@ def _aggregate_one(self, segmentations: "pd.Series[Any]") -> npt.NDArray[Any]:
for _ in range(self.n_iter):
weighted = self._segmentation_weighted(segmentations_np, weights)
mv = weighted >= 0.5
weights = self._calculate_weights(segmentations_np, mv)
weights = self._calculate_weights(segmentations_np, mv) # type: ignore[assignment,unused-ignore]

if last_aggregated is not None:
delta = weighted - last_aggregated
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2 changes: 1 addition & 1 deletion crowdkit/aggregation/utils.py
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Expand Up @@ -191,7 +191,7 @@ def converter(series: "pd.Series[Any]") -> "pd.Series[Any]":
series.name = name
return series

return attr.ib(init=False, converter=converter, on_setattr=attr.setters.convert) # type: ignore[no-any-return]
return attr.ib(init=False, converter=converter, on_setattr=attr.setters.convert)


def add_skills_to_data(
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6 changes: 2 additions & 4 deletions crowdkit/metrics/data/_classification.py
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Expand Up @@ -4,7 +4,7 @@
"alpha_krippendorff",
]

from typing import Any, Callable, Hashable, List, Optional, Tuple, Union, cast
from typing import Any, Callable, Hashable, List, Optional, Union, cast

import numpy as np
import pandas as pd
Expand Down Expand Up @@ -266,7 +266,5 @@ def alpha_krippendorff(
0.4444444444444444
"""
_check_answers(answers)
data: List[Tuple[Any, Hashable, Hashable]] = answers[
["worker", "task", "label"]
].values.tolist()
data = answers[["worker", "task", "label"]].values.tolist()
return float(AnnotationTask(data, distance).alpha())