FIX: move check function to avoid circular import

Author: thibaultcordier

mapie/classification.py

@@ -15,7 +15,7 @@
 
 from mapie._machine_precision import EPSILON
 from mapie._typing import ArrayLike, NDArray
-from mapie.estimator import EnsembleClassifier
+from mapie.estimator.classifier import EnsembleClassifier
 from mapie.metrics import classification_mean_width_score
 from mapie.utils import (check_alpha, check_alpha_and_n_samples, check_cv,
                          check_estimator_classification, check_n_features_in,

mapie/conformity_scores/check.py

@@ -0,0 +1,38 @@
+from typing import Optional
+
+from .conformity_scores import ConformityScore
+from .residual_conformity_scores import AbsoluteConformityScore
+
+
+def check_conformity_score(
+    conformity_score: Optional[ConformityScore],
+    sym: bool = True,
+) -> ConformityScore:
+    """
+    Check parameter ``conformity_score``.
+
+    Raises
+    ------
+    ValueError
+        If parameter is not valid.
+
+    Examples
+    --------
+    >>> from mapie.utils import check_conformity_score
+    >>> try:
+    ...     check_conformity_score(1)
+    ... except Exception as exception:
+    ...     print(exception)
+    ...
+    Invalid conformity_score argument.
+    Must be None or a ConformityScore instance.
+    """
+    if conformity_score is None:
+        return AbsoluteConformityScore(sym=sym)
+    elif isinstance(conformity_score, ConformityScore):
+        return conformity_score
+    else:
+        raise ValueError(
+            "Invalid conformity_score argument.\n"
+            "Must be None or a ConformityScore instance."
+        )

mapie/conformity_scores/conformity_scores.py

@@ -5,7 +5,7 @@
 
 from mapie._compatibility import np_nanquantile
 from mapie._typing import ArrayLike, NDArray
-from mapie.estimator import EnsembleRegressor
+from mapie.estimator.regressor import EnsembleRegressor
 
 
 class ConformityScore(metaclass=ABCMeta):
@@ -326,14 +326,14 @@ def get_bounds(
     ) -> Tuple[NDArray, NDArray, NDArray]:
         """
         Compute bounds of the prediction intervals from the observed values,
-        the estimator of type ``EnsembleEstimator`` and the conformity scores.
+        the estimator of type ``EnsembleRegressor`` and the conformity scores.
 
         Parameters
         ----------
         X: ArrayLike of shape (n_samples, n_features)
             Observed feature values.
 
-        estimator: EnsembleEstimator
+        estimator: EnsembleRegressor
             Estimator that is fitted to predict y from X.
 
         conformity_scores: ArrayLike of shape (n_samples,)

mapie/estimator/classifier.py

@@ -11,11 +11,7 @@
 
 from mapie._typing import ArrayLike, NDArray
 from mapie.estimator.interface import EnsembleEstimator
-from mapie.utils import (
-    check_no_agg_cv,
-    fit_estimator,
-    fix_number_of_classes,
-)
+from mapie.utils import check_no_agg_cv, fit_estimator, fix_number_of_classes
 
 
 class EnsembleClassifier(EnsembleEstimator):

mapie/regression/regression.py

@@ -13,11 +13,12 @@
 
 from mapie._typing import ArrayLike, NDArray
 from mapie.conformity_scores import ConformityScore, ResidualNormalisedScore
-from mapie.estimator import EnsembleRegressor
+from mapie.estimator.regressor import EnsembleRegressor
 from mapie.utils import (check_alpha, check_alpha_and_n_samples,
-                         check_conformity_score, check_cv,
-                         check_estimator_fit_predict, check_n_features_in,
-                         check_n_jobs, check_null_weight, check_verbose)
+                         check_cv, check_estimator_fit_predict,
+                         check_n_features_in, check_n_jobs, check_null_weight,
+                         check_verbose)
+from mapie.conformity_scores.check import check_conformity_score
 
 
 class MapieRegressor(BaseEstimator, RegressorMixin):

mapie/tests/test_regression.py

@@ -25,7 +25,7 @@
 from mapie.conformity_scores import (AbsoluteConformityScore, ConformityScore,
                                      GammaConformityScore,
                                      ResidualNormalisedScore)
-from mapie.estimator import EnsembleRegressor
+from mapie.estimator.regressor import EnsembleRegressor
 from mapie.metrics import regression_coverage_score
 from mapie.regression import MapieRegressor
 from mapie.subsample import Subsample

mapie/utils.py

@@ -16,7 +16,6 @@
 
 from ._compatibility import np_quantile
 from ._typing import ArrayLike, NDArray
-from .conformity_scores import AbsoluteConformityScore, ConformityScore
 
 SPLIT_STRATEGIES = ["uniform", "quantile", "array split"]
 
@@ -600,40 +599,6 @@ def check_lower_upper_bounds(
         )
 
 
-def check_conformity_score(
-    conformity_score: Optional[ConformityScore],
-    sym: bool = True,
-) -> ConformityScore:
-    """
-    Check parameter ``conformity_score``.
-
-    Raises
-    ------
-    ValueError
-        If parameter is not valid.
-
-    Examples
-    --------
-    >>> from mapie.utils import check_conformity_score
-    >>> try:
-    ...     check_conformity_score(1)
-    ... except Exception as exception:
-    ...     print(exception)
-    ...
-    Invalid conformity_score argument.
-    Must be None or a ConformityScore instance.
-    """
-    if conformity_score is None:
-        return AbsoluteConformityScore(sym=sym)
-    elif isinstance(conformity_score, ConformityScore):
-        return conformity_score
-    else:
-        raise ValueError(
-            "Invalid conformity_score argument.\n"
-            "Must be None or a ConformityScore instance."
-        )
-
-
 def check_defined_variables_predict_cqr(
     ensemble: bool,
     alpha: Union[float, Iterable[float], None],