18754124332

Committed 23 Oct 2025 03:48PM UTC coverage: 92.865% (-0.2%) from 93.032%

Build # 18754124332

Build Type

Pull #431

github

Committed by

web-flow

Commit Message

Merge e4a9a83cb into 830c6bc23

Pull Request Pull Request #431: Product kernel explainer

Run Details

186 of 210 new or added lines in 13 files covered. (88.57%)

2 existing lines in 1 file now uncovered.

5375 of 5788 relevant lines covered (92.86%)

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82.61

/src/shapiq/explainer/product_kernel/validation.py

"""Conversion functions for the product kernel explainer implementation."""

from __future__ import annotations

from typing import TYPE_CHECKING

from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.svm import SVC, SVR

from .base import ProductKernelModel
from .conversion import convert_gp_reg, convert_svm

if TYPE_CHECKING:
    from shapiq.typing import Model


SUPPORTED_MODELS = {
    "sklearn.svm.SVR",
    "sklearn.svm.SVC",
    "sklearn.gaussian_process.GaussianProcessRegressor",
}


def validate_pk_model(
    model: Model,  # pyright: ignore[reportInvalidTypeVarUse]
) -> ProductKernelModel:
    """Validate the product kernel model.

    Args:
        model: The model to validate.

    Returns:
        The validated product kernel model.

    Raises:
        TypeError: If the model is not supported.
    """
    # product kernel model already in the correct format
    if isinstance(model, ProductKernelModel):
        return model

    if isinstance(model, SVR):
        return convert_svm(model)

    if isinstance(model, SVC):
        if model.classes_.shape[0] == 2:
            return convert_svm(model)
        msg = "Only binary SVM classification supported."
        raise TypeError(msg)

    if isinstance(model, GaussianProcessRegressor):
        return convert_gp_reg(model)

    msg = f"Unsupported model type.Supported models are: {SUPPORTED_MODELS}"
    raise TypeError(msg)

1	"""Conversion functions for the product kernel explainer implementation."""
2
3	from __future__ import annotations	1✔
4
5	from typing import TYPE_CHECKING	1✔
6
7	from sklearn.gaussian_process import GaussianProcessRegressor	1✔
8	from sklearn.svm import SVC, SVR	1✔
9
10	from .base import ProductKernelModel	1✔
11	from .conversion import convert_gp_reg, convert_svm	1✔
12
13	if TYPE_CHECKING:	1✔
NEW 14	from shapiq.typing import Model	×
15
16
17	SUPPORTED_MODELS = {	1✔
18	"sklearn.svm.SVR",
19	"sklearn.svm.SVC",
20	"sklearn.gaussian_process.GaussianProcessRegressor",
21	}
22
23
24	def validate_pk_model(	1✔
25	model: Model, # pyright: ignore[reportInvalidTypeVarUse]
26	) -> ProductKernelModel:
27	"""Validate the product kernel model.
28
29	Args:
30	model: The model to validate.
31
32	Returns:
33	The validated product kernel model.
34
35	Raises:
36	TypeError: If the model is not supported.
37	"""
38	# product kernel model already in the correct format
39	if isinstance(model, ProductKernelModel):	1✔
NEW 40	return model	×
41
42	if isinstance(model, SVR):	1✔
43	return convert_svm(model)	1✔
44
45	if isinstance(model, SVC):	1✔
46	if model.classes_.shape[0] == 2:	1✔
47	return convert_svm(model)	1✔
NEW 48	msg = "Only binary SVM classification supported."	×
NEW 49	raise TypeError(msg)	×
50
51	if isinstance(model, GaussianProcessRegressor):	1✔
52	return convert_gp_reg(model)	1✔
53
54	msg = f"Unsupported model type.Supported models are: {SUPPORTED_MODELS}"	1✔
55	raise TypeError(msg)	1✔

mmschlk / shapiq / 18754124332

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