Compute labels for fit

bico/_core.cpp

@@ -1,23 +1,12 @@
 #include <Python.h>
 
-#include <iostream>
-#include <sstream>
-#include <fstream>
-#include <random>
-#include <ctime>
-#include <time.h>
-
 #include "point/l2metric.h"
 #include "point/squaredl2metric.h"
 #include "point/point.h"
 #include "point/pointweightmodifier.h"
 #include "clustering/bico.h"
-#include "misc/randomness.h"
-#include "misc/randomgenerator.h"
 #include "datastructure/proxysolution.h"
 #include "point/pointcentroid.h"
-#include "point/pointweightmodifier.h"
-#include "point/realspaceprovider.h"
 
 typedef unsigned int uint;
 

bico/clustering/bico.h

@@ -18,7 +18,6 @@
 #include "../datastructure/proxysolution.h"
 #include "../evaluation/kmeansevaluator.h"
 #include "../exception/invalidruntimeconfigurationexception.h"
-#include "../misc/randomness.h"
 
 namespace CluE
 {
@@ -541,8 +540,7 @@ minDist(std::numeric_limits<double>::infinity()),
 pairwise_different(0),
 numOfRebuilds(0)
 {
-    Randomness::initialize(seed);
-    RandomGenerator rg = Randomness::getRandomGenerator();
+    std::mt19937 rg(seed);
     std::vector<double> rndpoint(dimension);
     rndprojections.resize(L);
     bucket_radius.resize(L);

bico/core.py

@@ -64,8 +64,14 @@ def __init__(
 
     @property
     def labels_(self) -> np.ndarray:
-        if not hasattr(self, "_labels"):
+        if not hasattr(self, "_cluster_centers"):
             raise NotFittedError(self._CORESET_ESTIMATOR_ERROR)
+        elif not hasattr(self, "_labels"):
+            raise ValueError(
+                "The labels have not been computed because the coreset "
+                "was fit using partial_fit. "
+                "Please call predict on your data to obtain the labels."
+            )
         return self._labels
 
     @property
@@ -114,6 +120,7 @@ def partial_fit(
 
     def _fit_coreset(
         self,
+        X: Optional[np.ndarray] = None,
     ) -> None:
         if self.coreset_estimator is None:
             from sklearn.cluster import KMeans
@@ -127,10 +134,13 @@ def _fit_coreset(
             self._coreset_points, sample_weight=self._coreset_weights
         )
         self._cluster_centers: np.ndarray = self.coreset_estimator.cluster_centers_
-        self._labels: np.ndarray = self.coreset_estimator.labels_
+        if X is not None:
+            self._labels: np.ndarray = self.coreset_estimator.predict(X)
         self._inertia: float = self.coreset_estimator.inertia_
 
-    def _compute_coreset(self, fit_coreset: bool = False) -> "BICO":
+    def _compute_coreset(
+        self, X: Optional[np.ndarray] = None, fit_coreset: bool = False
+    ) -> "BICO":
         if not hasattr(self, "bico_obj_"):
             raise NotFittedError(
                 "This BICO instance is not fitted yet. " "Call `fit` or `partial_fit`."
@@ -152,7 +162,7 @@ def _compute_coreset(self, fit_coreset: bool = False) -> "BICO":
         self._n_features_out = n_found_points
 
         if self.fit_coreset or fit_coreset:
-            self._fit_coreset()
+            self._fit_coreset(X)
 
         return self
 
@@ -188,7 +198,9 @@ def _fit(
         _DLL.addData(self.bico_obj_, c_array, c_n)
 
         if not partial or fit_coreset:
-            self._compute_coreset(fit_coreset)
+            self._compute_coreset(
+                X=_X if not partial else None, fit_coreset=fit_coreset
+            )
 
         return self
 
@@ -204,9 +216,9 @@ def fit_predict(
         return self.labels_
 
     def predict(self, X: Sequence[Sequence[float]]) -> Any:
-        self._fit_coreset()
-
         if self.coreset_estimator is None:
             raise NotFittedError(self._CORESET_ESTIMATOR_ERROR)
 
+        self._fit_coreset()
+
         return self.coreset_estimator.predict(X)

build_extension.py

@@ -8,7 +8,6 @@
     name="bico._core",
     sources=[
         "bico/_core.cpp",
-        "bico/misc/randomness.cpp",
         "bico/point/pointcentroid.cpp",
         "bico/point/squaredl2metric.cpp",
         "bico/point/point.cpp",