Merge branch 'master' into fix-gitignore-mondrian-doc

Author: vincentblot28

.gitignore

@@ -86,3 +86,6 @@ target/
 
 # ZIP files
 *.zip
+
+# Pyenv
+.python-version

CONTRIBUTING.rst

@@ -50,11 +50,26 @@ Documenting your change
 
 If you're adding a class or a function, then you'll need to add a docstring with a doctest. We follow the `numpy docstring convention <https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_numpy.html>`_, so please do too.
 Any estimator should follow the [scikit-learn API](https://scikit-learn.org/stable/developers/develop.html), so please follow these guidelines.
-In order to build the documentation locally, run :
+In order to build the documentation locally, you first need to install some dependencies :
+
+Create a dedicated virtual environment via `conda`:
+
+.. code:: sh
+
+    $ conda env create -f environment.doc.yml
+    $ conda activate mapie-doc
+
+Alternatively, using `pip`, create a different virtual environment than the one used for development, and install the dependencies:
+
+.. code:: sh
+
+    $ pip install -r requirements.doc.txt
+    $ pip install -e .
+
+Finally, once dependencies are installed, you can build the documentation locally by running:
 
 .. code:: sh
 
-    $ cd doc
     $ make clean-doc
     $ make doc
 

HISTORY.rst

@@ -2,9 +2,13 @@
 History
 =======
 
-0.9.x (2024-xx-xx)
+0.9.1 (2024-09-13)
 ------------------
+
+* Fix issue 511 to access non-conformity scores with previous path
 * Update gitignore by including the documentation folder generated for Mondrian
+* Fix (partially) the set-up with pip instead of conda for new contributors
+
 
 
 0.9.0 (2024-09-03)

mapie/conformity_scores/conformity_scores.py

@@ -0,0 +1,165 @@
+from abc import ABCMeta, abstractmethod
+
+from sklearn.utils import deprecated
+
+from mapie.conformity_scores.regression import BaseConformityScore
+from mapie._machine_precision import EPSILON
+from mapie._typing import NDArray
+
+
+@deprecated(
+    "WARNING: Deprecated path to import ConformityScore. "
+    "Please prefer the new path: "
+    "[from mapie.conformity_scores import BaseRegressionScore]."
+)
+class ConformityScore(BaseConformityScore, metaclass=ABCMeta):
+    """
+    Base conformity score class for regression task.
+
+    This class should not be used directly. Use derived classes instead.
+
+    Parameters
+    ----------
+    sym: bool
+        Whether to consider the conformity score as symmetrical or not.
+
+    consistency_check: bool, optional
+        Whether to check the consistency between the methods
+        ``get_estimation_distribution`` and ``get_conformity_scores``.
+        If ``True``, the following equality must be verified:
+        ``self.get_estimation_distribution(
+            y_pred, self.get_conformity_scores(y, y_pred, **kwargs), **kwargs
+        ) == y``
+
+        By default ``True``.
+
+    eps: float, optional
+        Threshold to consider when checking the consistency between
+        ``get_estimation_distribution`` and ``get_conformity_scores``.
+        It should be specified if ``consistency_check==True``.
+
+        By default, it is defined by the default precision.
+    """
+
+    def __init__(
+        self,
+        sym: bool,
+        consistency_check: bool = True,
+        eps: float = float(EPSILON),
+    ):
+        super().__init__()
+        self.sym = sym
+        self.consistency_check = consistency_check
+        self.eps = eps
+
+    @abstractmethod
+    def get_signed_conformity_scores(
+        self,
+        y: NDArray,
+        y_pred: NDArray,
+        **kwargs
+    ) -> NDArray:
+        """
+        Placeholder for ``get_conformity_scores``.
+        Subclasses should implement this method!
+
+        Compute the sample conformity scores given the predicted and
+        observed targets.
+
+        Parameters
+        ----------
+        y: NDArray of shape (n_samples,)
+            Observed target values.
+
+        y_pred: NDArray of shape (n_samples,)
+            Predicted target values.
+
+        Returns
+        -------
+        NDArray of shape (n_samples,)
+            Signed conformity scores.
+        """
+
+    @abstractmethod
+    def get_conformity_scores(
+        self,
+        y: NDArray,
+        y_pred: NDArray,
+        **kwargs
+    ) -> NDArray:
+        """
+        Placeholder for ``get_conformity_scores``.
+        Subclasses should implement this method!
+
+        Compute the sample conformity scores given the predicted and
+        observed targets.
+
+        Parameters
+        ----------
+        y: NDArray of shape (n_samples,)
+            Observed target values.
+
+        y_pred: NDArray of shape (n_samples,)
+            Predicted target values.
+
+        Returns
+        -------
+        NDArray of shape (n_samples,)
+            Conformity scores.
+        """
+
+    @abstractmethod
+    def get_estimation_distribution(
+        self,
+        y_pred: NDArray,
+        conformity_scores: NDArray,
+        **kwargs
+    ) -> NDArray:
+        """
+        Placeholder for ``get_estimation_distribution``.
+        Subclasses should implement this method!
+
+        Compute samples of the estimation distribution given the predicted
+        targets and the conformity scores.
+
+        Parameters
+        ----------
+        y_pred: NDArray of shape (n_samples,)
+            Predicted target values.
+
+        conformity_scores: NDArray of shape (n_samples,)
+            Conformity scores.
+
+        Returns
+        -------
+        NDArray of shape (n_samples,)
+            Observed values.
+        """
+
+    @abstractmethod
+    def predict_set(
+        self,
+        X: NDArray,
+        alpha_np: NDArray,
+        **kwargs
+    ):
+        """
+        Compute the prediction sets on new samples based on the uncertainty of
+        the target confidence set.
+
+        Parameters:
+        -----------
+        X: NDArray of shape (n_samples,)
+            The input data or samples for prediction.
+
+        alpha_np: NDArray of shape (n_alpha, )
+            Represents the uncertainty of the confidence set to produce.
+
+        **kwargs: dict
+            Additional keyword arguments.
+
+        Returns:
+        --------
+        The output structure depend on the subclass.
+            The prediction sets for each sample and each alpha level.
+        """

mapie/conformity_scores/residual_conformity_scores.py

@@ -0,0 +1,34 @@
+from sklearn.utils import deprecated
+
+from .bounds import (
+    AbsoluteConformityScore as NewAbsoluteConformityScore,
+    GammaConformityScore as NewGammaConformityScore,
+    ResidualNormalisedScore as NewResidualNormalisedScore
+)
+
+
+@deprecated(
+    "WARNING: Deprecated path to import AbsoluteConformityScore. "
+    "Please prefer the new path: "
+    "[from mapie.conformity_scores.bounds import AbsoluteConformityScore]."
+)
+class AbsoluteConformityScore(NewAbsoluteConformityScore):
+    pass
+
+
+@deprecated(
+    "WARNING: Deprecated path to import GammaConformityScore. "
+    "Please prefer the new path: "
+    "[from mapie.conformity_scores.bounds import GammaConformityScore]."
+)
+class GammaConformityScore(NewGammaConformityScore):
+    pass
+
+
+@deprecated(
+    "WARNING: Deprecated path to import ResidualNormalisedScore. "
+    "Please prefer the new path: "
+    "[from mapie.conformity_scores.bounds import ResidualNormalisedScore]."
+)
+class ResidualNormalisedScore(NewResidualNormalisedScore):
+    pass

mapie/conformity_scores/utils_classification_conformity_scores.py

@@ -0,0 +1,14 @@
+from sklearn.utils import deprecated
+
+from mapie.conformity_scores.sets.utils import (
+    get_true_label_position as get_true_label_position_new_path,
+)
+
+
+@deprecated(
+    "WARNING: Deprecated path to import get_true_label_position. "
+    "Please prefer the new path: "
+    "[from mapie.conformity_scores.sets.utils import get_true_label_position]."
+)
+def get_true_label_position(*args, **kwargs):
+    return get_true_label_position_new_path(*args, **kwargs)

mapie/estimator/estimator.py

@@ -0,0 +1,12 @@
+from sklearn.utils import deprecated
+
+from mapie.estimator.regressor import EnsembleRegressor as NewEnsembleRegressor
+
+
+@deprecated(
+    "WARNING: Deprecated path to import EnsembleRegressor. "
+    "Please prefer the new path: "
+    "[from mapie.estimator.regressor import EnsembleRegressor]."
+)
+class EnsembleRegressor(NewEnsembleRegressor):
+    pass