src.fairreckitlib.model.pipeline.model_pipeline_surprise

 1"""This module contains the model pipelines for the Surprise package.
 2
 3Classes:
 4
 5    PredictionPipelineSurprise: prediction pipeline that uses a surprise matrix.
 6    RecommendationPipelineSurprise: recommendation pipeline that uses a surprise matrix.
 7
 8This program has been developed by students from the bachelor Computer Science at
 9Utrecht University within the Software Project course.
10© Copyright Utrecht University (Department of Information and Computing Sciences)
11"""
12
13from ..algorithms.surprise.surprise_matrix import MatrixSurprise
14from ..algorithms.matrix import Matrix
15from .prediction_pipeline import PredictionPipeline
16from .recommendation_pipeline import RecommendationPipeline
17
18
19class PredictionPipelineSurprise(PredictionPipeline):
20    """Prediction Pipeline implementation for a surprise matrix train set."""
21
22    def on_load_train_set_matrix(self) -> Matrix:
23        """Load the train set matrix that all models can use for training.
24
25        Raises:
26            FileNotFoundError: when the train set file is not found.
27            RuntimeError: when the max of the rating scale is larger than the RATING_TYPE_THRESHOLD.
28
29        Returns:
30            the loaded surprise train set matrix.
31        """
32        return MatrixSurprise(
33            self.data_transition.train_set_path,
34            self.data_transition.rating_scale
35        )
36
37
38class RecommendationPipelineSurprise(RecommendationPipeline):
39    """Recommendation Pipeline implementation for a surprise matrix train set."""
40
41    def on_load_train_set_matrix(self) -> Matrix:
42        """Load the train set matrix that all models can use for training.
43
44        Raises:
45            FileNotFoundError: when the train set file is not found.
46            RuntimeError: when the max of the rating scale is larger than the RATING_TYPE_THRESHOLD.
47
48        Returns:
49            the loaded surprise train set matrix.
50        """
51        return MatrixSurprise(
52            self.data_transition.train_set_path,
53            self.data_transition.rating_scale
54        )