From 51fb5e0a19e784ed22bd1867db923de845c76e08 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 26 Oct 2022 14:52:10 +0200
Subject: [PATCH 01/10] Progress on adding the mondrian conformal

---
 .gitignore              | 2 +-
 mapie/classification.py | 7 ++++++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index aa0113dd0..ffe64042f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -19,7 +19,7 @@ doc/datasets/generated/
 doc/generated/
 
 # Distribution / packaging
-
+mapieenv
 .Python
 env/
 build/
diff --git a/mapie/classification.py b/mapie/classification.py
index 815f112d7..ccadf41a5 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -1003,7 +1003,11 @@ def fit(
 
         X, y = indexable(X, y)
         y = _check_y(y)
-        assert type_of_target(y) == "multiclass"
+        if type_of_target(y) != "multiclass" and self.method != "mondrian":
+            raise ValueError(
+                "Invalid method. "
+                "Binary classification problems require the mondrian method. "
+            )
         sample_weight, X, y = check_null_weight(sample_weight, X, y)
         y = cast(NDArray, y)
         n_samples = _num_samples(y)
@@ -1352,6 +1356,7 @@ def predict(
                 - y_pred_proba_last,
                 -EPSILON
             )
+        elif self.
         else:
             raise ValueError(
                 "Invalid method. "

From cb84ddf42f89d4231b158af8c5eb901c0a7deb7f Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 26 Oct 2022 15:26:49 +0200
Subject: [PATCH 02/10] v 0.1.0 of mondrian finished

---
 mapie/classification.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

diff --git a/mapie/classification.py b/mapie/classification.py
index ccadf41a5..1ee629998 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -167,7 +167,7 @@ class MapieClassifier(BaseEstimator, ClassifierMixin):
      [False False  True]]
     """
 
-    valid_methods_ = ["naive", "score", "cumulated_score", "top_k", "raps"]
+    valid_methods_ = ["naive", "score", "cumulated_score", "top_k", "raps","mondrian"]
     fit_attributes = [
         "single_estimator_",
         "estimators_",
@@ -1081,6 +1081,9 @@ def fit(
             self.conformity_scores_ = np.take_along_axis(
                 1 - y_pred_proba, y.reshape(-1, 1), axis=1
             )
+        elif self.method == "mondrian":
+            self.conformity_scores_ = 1-y_pred_proba
+
         elif self.method in ["cumulated_score", "raps"]:
             self.conformity_scores_, self.cutoff = (
                 self._get_true_label_cumsum_proba(
@@ -1227,7 +1230,7 @@ def predict(
         check_alpha_and_n_samples(alpha_np, n)
 
         if self.method == "naive":
-            self.quantiles_ = 1 - alpha_np
+            self.quantiles_ = 1 - alpha_np 
         else:
             if (cv == "prefit") or (agg_scores in ["mean"]):
                 if self.method == "raps":
@@ -1356,7 +1359,12 @@ def predict(
                 - y_pred_proba_last,
                 -EPSILON
             )
-        elif self.
+        elif self.method == "mondrian": #TODO:
+            prediction_sets = np.greater_equal(
+                y_pred_proba,self.quantiles_
+            )
+            
+            
         else:
             raise ValueError(
                 "Invalid method. "

From ae8b009eaf54ffb383d7c5f48cad5c43c9405a41 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 2 Nov 2022 09:37:01 +0100
Subject: [PATCH 03/10] Added mondrian

---
 mapie/classification.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/mapie/classification.py b/mapie/classification.py
index 1ee629998..022239454 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -1263,10 +1263,12 @@ def predict(
                         alpha_np
                     )
                 else:
+                    print("1")
                     self.quantiles_ = compute_quantiles(
                         self.conformity_scores_,
                         alpha_np
                     )
+                    print("2")
             else:
                 self.quantiles_ = (n + 1) * (1 - alpha_np)
 

From ae8f4b00d433cbbf9152a514403f192b595692f7 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 2 Nov 2022 10:18:16 +0100
Subject: [PATCH 04/10] Finished implementing the mondrian conformal

---
 mapie/classification.py | 12 ++++++++++--
 mapie/utils.py          | 14 +++++++++++---
 2 files changed, 21 insertions(+), 5 deletions(-)

diff --git a/mapie/classification.py b/mapie/classification.py
index 022239454..cec225c97 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -1262,13 +1262,19 @@ def predict(
                         self.conformity_scores_regularized,
                         alpha_np
                     )
+                elif self.method == "mondrian":
+                    self.quantiles_ = compute_quantiles(
+                        self.conformity_scores_,
+                        alpha_np,
+                        mondrian = True
+                    )
                 else:
-                    print("1")
+                    
                     self.quantiles_ = compute_quantiles(
                         self.conformity_scores_,
                         alpha_np
                     )
-                    print("2")
+                    
             else:
                 self.quantiles_ = (n + 1) * (1 - alpha_np)
 
@@ -1362,6 +1368,8 @@ def predict(
                 -EPSILON
             )
         elif self.method == "mondrian": #TODO:
+            print(y_pred_proba)
+            print(y_pred_proba.shape)
             prediction_sets = np.greater_equal(
                 y_pred_proba,self.quantiles_
             )
diff --git a/mapie/utils.py b/mapie/utils.py
index a19be25c5..e6ed5a8af 100644
--- a/mapie/utils.py
+++ b/mapie/utils.py
@@ -616,7 +616,7 @@ def check_alpha_and_last_axis(vector: NDArray, alpha_np: NDArray):
         return vector, alpha_np
 
 
-def compute_quantiles(vector: NDArray, alpha: NDArray) -> NDArray:
+def compute_quantiles(vector: NDArray, alpha: NDArray,mondrian = False) -> NDArray:
     """Compute the desired quantiles of a vector.
 
     Parameters
@@ -634,15 +634,23 @@ def compute_quantiles(vector: NDArray, alpha: NDArray) -> NDArray:
         Quantiles of the vector.
     """
     n = len(vector)
-    if len(vector.shape) <= 2:
+    if len(vector.shape) <= 2 and not mondrian:
+        quantiles_ = np.stack([
+                    np_quantile(
+                        vector,
+                        ((n + 1) * (1 - _alpha)) / n,
+                        method="higher"
+                    ) for _alpha in alpha
+        ])
+    elif len(vector.shape) <= 2 and mondrian:
         quantiles_ = np.stack([
                     np_quantile(
                         vector,
                         ((n + 1) * (1 - _alpha)) / n,
                         method="higher",
+                        axis=1
                     ) for _alpha in alpha
         ])
-
     else:
         check_alpha_and_last_axis(vector, alpha)
         quantiles_ = np.stack(

From 48f132770e0fd29b94087f2d52a0ce3070a67841 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 2 Nov 2022 11:04:41 +0100
Subject: [PATCH 05/10] 'Pride cometh before the fall' The actual
 implementation of the mondrian conformal now complete

---
 mapie/classification.py | 15 +++++++++++----
 mapie/utils.py          |  2 +-
 2 files changed, 12 insertions(+), 5 deletions(-)

diff --git a/mapie/classification.py b/mapie/classification.py
index cec225c97..c535c9be4 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -1263,6 +1263,7 @@ def predict(
                         alpha_np
                     )
                 elif self.method == "mondrian":
+
                     self.quantiles_ = compute_quantiles(
                         self.conformity_scores_,
                         alpha_np,
@@ -1281,6 +1282,10 @@ def predict(
         # Build prediction sets
         if self.method == "score":
             if (cv == "prefit") or (agg_scores == "mean"):
+                print("y proba shape")
+                print(y_pred_proba.shape)
+                print("quantiles shape")
+                print(self.quantiles_.shape)
                 prediction_sets = np.greater_equal(
                     y_pred_proba - (1 - self.quantiles_), -EPSILON
                 )
@@ -1368,11 +1373,12 @@ def predict(
                 -EPSILON
             )
         elif self.method == "mondrian": #TODO:
-            print(y_pred_proba)
-            print(y_pred_proba.shape)
-            prediction_sets = np.greater_equal(
+            self.quantiles_ = np.transpose(self.quantiles_,[1,0])
+
+            prediction_sets = (np.greater_equal(
                 y_pred_proba,self.quantiles_
-            )
+            ))
+            
             
             
         else:
@@ -1380,4 +1386,5 @@ def predict(
                 "Invalid method. "
                 "Allowed values are 'score' or 'cumulated_score'."
             )
+        print(prediction_sets)
         return y_pred, prediction_sets
diff --git a/mapie/utils.py b/mapie/utils.py
index e6ed5a8af..849b8d52c 100644
--- a/mapie/utils.py
+++ b/mapie/utils.py
@@ -648,7 +648,7 @@ def compute_quantiles(vector: NDArray, alpha: NDArray,mondrian = False) -> NDArr
                         vector,
                         ((n + 1) * (1 - _alpha)) / n,
                         method="higher",
-                        axis=1
+                        axis=0
                     ) for _alpha in alpha
         ])
     else:

From 917c06becdf85ff8b0586577b6db41c3a080d7c1 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 2 Nov 2022 11:09:44 +0100
Subject: [PATCH 06/10] removed spurious prints

---
 mapie/classification.py | 11 +++--------
 1 file changed, 3 insertions(+), 8 deletions(-)

diff --git a/mapie/classification.py b/mapie/classification.py
index c535c9be4..f2f75ae88 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -1282,10 +1282,6 @@ def predict(
         # Build prediction sets
         if self.method == "score":
             if (cv == "prefit") or (agg_scores == "mean"):
-                print("y proba shape")
-                print(y_pred_proba.shape)
-                print("quantiles shape")
-                print(self.quantiles_.shape)
                 prediction_sets = np.greater_equal(
                     y_pred_proba - (1 - self.quantiles_), -EPSILON
                 )
@@ -1375,9 +1371,9 @@ def predict(
         elif self.method == "mondrian": #TODO:
             self.quantiles_ = np.transpose(self.quantiles_,[1,0])
 
-            prediction_sets = (np.greater_equal(
-                y_pred_proba,self.quantiles_
-            ))
+            prediction_sets = np.greater_equal(
+            y_pred_proba - (1 - self.quantiles_), -EPSILON
+            )
             
             
             
@@ -1386,5 +1382,4 @@ def predict(
                 "Invalid method. "
                 "Allowed values are 'score' or 'cumulated_score'."
             )
-        print(prediction_sets)
         return y_pred, prediction_sets

From 53ec51d4d53db5030bcb70366f6deed1eebdb77f Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 16 Nov 2022 09:40:36 +0100
Subject: [PATCH 07/10] Brought changes in line with flake8 formatting

---
 Makefile                           |  2 +-
 mapie/classification.py            | 27 ++++++++++++++++-----------
 mapie/tests/test_classification.py | 13 ++++++++++++-
 3 files changed, 29 insertions(+), 13 deletions(-)

diff --git a/Makefile b/Makefile
index 5cadb8574..4a58860e6 100644
--- a/Makefile
+++ b/Makefile
@@ -1,7 +1,7 @@
 .PHONY: tests doc build
 
 lint:	
-	flake8 . --exclude=doc
+	flake8 . --exclude=doc mapieenv
 
 type-check:
 	mypy mapie
diff --git a/mapie/classification.py b/mapie/classification.py
index f2f75ae88..a14344fcb 100644
--- a/mapie/classification.py
+++ b/mapie/classification.py
@@ -167,7 +167,13 @@ class MapieClassifier(BaseEstimator, ClassifierMixin):
      [False False  True]]
     """
 
-    valid_methods_ = ["naive", "score", "cumulated_score", "top_k", "raps","mondrian"]
+    valid_methods_ = ["naive",
+                      "score",
+                      "cumulated_score",
+                      "top_k",
+                      "raps",
+                      "mondrian"
+                      ]
     fit_attributes = [
         "single_estimator_",
         "estimators_",
@@ -1230,7 +1236,7 @@ def predict(
         check_alpha_and_n_samples(alpha_np, n)
 
         if self.method == "naive":
-            self.quantiles_ = 1 - alpha_np 
+            self.quantiles_ = 1 - alpha_np
         else:
             if (cv == "prefit") or (agg_scores in ["mean"]):
                 if self.method == "raps":
@@ -1267,15 +1273,15 @@ def predict(
                     self.quantiles_ = compute_quantiles(
                         self.conformity_scores_,
                         alpha_np,
-                        mondrian = True
+                        mondrian=True
                     )
                 else:
-                    
+
                     self.quantiles_ = compute_quantiles(
                         self.conformity_scores_,
                         alpha_np
                     )
-                    
+
             else:
                 self.quantiles_ = (n + 1) * (1 - alpha_np)
 
@@ -1368,15 +1374,14 @@ def predict(
                 - y_pred_proba_last,
                 -EPSILON
             )
-        elif self.method == "mondrian": #TODO:
-            self.quantiles_ = np.transpose(self.quantiles_,[1,0])
+        elif self.method == "mondrian":
+            self.quantiles_ = np.transpose(self.quantiles_, [1, 0])
 
             prediction_sets = np.greater_equal(
-            y_pred_proba - (1 - self.quantiles_), -EPSILON
+                y_pred_proba - (1 - self.quantiles_),
+                -EPSILON
             )
-            
-            
-            
+
         else:
             raise ValueError(
                 "Invalid method. "
diff --git a/mapie/tests/test_classification.py b/mapie/tests/test_classification.py
index 510f11010..4cc52fe79 100644
--- a/mapie/tests/test_classification.py
+++ b/mapie/tests/test_classification.py
@@ -22,7 +22,7 @@
 from mapie.metrics import classification_coverage_score
 from mapie.utils import check_alpha
 
-METHODS = ["score", "cumulated_score", "raps"]
+METHODS = ["score", "cumulated_score", "raps","mondrian"]
 WRONG_METHODS = ["scores", "cumulated", "test", "", 1, 2.5, (1, 2)]
 WRONG_INCLUDE_LABELS = ["randomised", "True", "False", "other", 1, 2.5, (1, 2)]
 Y_PRED_PROBA_WRONG = [
@@ -263,6 +263,17 @@
             agg_scores="mean"
         )
     ),
+    "mondrian": (
+        Params(
+            method="mondrian",
+            cv="prefit",
+            random_state=None
+        ),
+        ParamsPredict(
+            include_last_label="randomized",
+            agg_scores="mean"
+        )
+    ),
 }
 
 COVERAGES = {

From 1b0e00deb64062aa60dcd4640883f55f100b6adc Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 16 Nov 2022 11:23:13 +0100
Subject: [PATCH 08/10] adding tests for the mondrian method.

---
 Makefile                           |  2 +-
 mapie/tests/test_classification.py | 17 +++++++++++++++--
 2 files changed, 16 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index 4a58860e6..a3561eef2 100644
--- a/Makefile
+++ b/Makefile
@@ -1,7 +1,7 @@
 .PHONY: tests doc build
 
 lint:	
-	flake8 . --exclude=doc mapieenv
+	flake8 . --exclude=doc,mapieenv
 
 type-check:
 	mypy mapie
diff --git a/mapie/tests/test_classification.py b/mapie/tests/test_classification.py
index 4cc52fe79..ff45ace03 100644
--- a/mapie/tests/test_classification.py
+++ b/mapie/tests/test_classification.py
@@ -292,7 +292,8 @@
     "naive": 5 / 9,
     "top_k": 1,
     "raps": 1,
-    "raps_randomized": 8/9
+    "raps_randomized": 8/9,
+    "mondrian": 1
 }
 
 X_toy = np.arange(9).reshape(-1, 1)
@@ -475,6 +476,17 @@
         [False, True, True],
         [False, False, True],
     ],
+    "mondrian": [
+        [True, False, False],
+        [True, False, False],
+        [True, True, False],
+        [True, True, True],
+        [True, True, True],
+        [True, True, True],
+        [False, True, True],
+        [False, True, True],
+        [False, False, True],
+    ],
 }
 
 REGULARIZATION_PARAMETERS = [
@@ -875,7 +887,8 @@ def test_toy_dataset_predictions(strategy: str) -> None:
         alpha=0.5,
         include_last_label=args_predict["include_last_label"],
         agg_scores=args_predict["agg_scores"]
-    )
+    ) 
+
     np.testing.assert_allclose(y_ps[:, :, 0], y_toy_mapie[strategy])
     np.testing.assert_allclose(
         classification_coverage_score(y_toy, y_ps[:, :, 0]),

From caa9de6d2785499d9557e76bd58c67f280081f6f Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 16 Nov 2022 12:28:26 +0100
Subject: [PATCH 09/10] Now the linting tests pass..

---
 mapie/tests/test_classification.py | 4 ++--
 mapie/utils.py                     | 4 +++-
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/mapie/tests/test_classification.py b/mapie/tests/test_classification.py
index ff45ace03..96faf502f 100644
--- a/mapie/tests/test_classification.py
+++ b/mapie/tests/test_classification.py
@@ -22,7 +22,7 @@
 from mapie.metrics import classification_coverage_score
 from mapie.utils import check_alpha
 
-METHODS = ["score", "cumulated_score", "raps","mondrian"]
+METHODS = ["score", "cumulated_score", "raps", "mondrian"]
 WRONG_METHODS = ["scores", "cumulated", "test", "", 1, 2.5, (1, 2)]
 WRONG_INCLUDE_LABELS = ["randomised", "True", "False", "other", 1, 2.5, (1, 2)]
 Y_PRED_PROBA_WRONG = [
@@ -887,7 +887,7 @@ def test_toy_dataset_predictions(strategy: str) -> None:
         alpha=0.5,
         include_last_label=args_predict["include_last_label"],
         agg_scores=args_predict["agg_scores"]
-    ) 
+    )
 
     np.testing.assert_allclose(y_ps[:, :, 0], y_toy_mapie[strategy])
     np.testing.assert_allclose(
diff --git a/mapie/utils.py b/mapie/utils.py
index 849b8d52c..62549ccbe 100644
--- a/mapie/utils.py
+++ b/mapie/utils.py
@@ -616,7 +616,9 @@ def check_alpha_and_last_axis(vector: NDArray, alpha_np: NDArray):
         return vector, alpha_np
 
 
-def compute_quantiles(vector: NDArray, alpha: NDArray,mondrian = False) -> NDArray:
+def compute_quantiles(vector: NDArray,
+                      alpha: NDArray,
+                      mondrian=False) -> NDArray:
     """Compute the desired quantiles of a vector.
 
     Parameters

From a569c399f5b4a62398ac6d35927655ebaf81f616 Mon Sep 17 00:00:00 2001
From: mata <mata@simcorp.com>
Date: Wed, 25 Jan 2023 10:46:29 +0100
Subject: [PATCH 10/10] Updated the Authors.rst file

---
 AUTHORS.rst | 1 +
 1 file changed, 1 insertion(+)

diff --git a/AUTHORS.rst b/AUTHORS.rst
index 8fc0ca2d5..c23e89db9 100644
--- a/AUTHORS.rst
+++ b/AUTHORS.rst
@@ -24,4 +24,5 @@ Contributors
 * Louis Lacombe <llacombe@quantmetry.com>
 * Arnaud Capitaine <arnaud.gc.capitaine@gmail.com>
 * Tarik Tazi <ttazi@quantmetry.com>
+* Matthias Adamsen <matthiasadamsen@gmail.com>
 To be continued ...