Merge branch 'release/v0.1.6'

Author: MischaPanch

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.5
+current_version = 0.1.6
 commit = False
 tag = False
 allow_dirty = False

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/psf/black
-    rev: 20.8b1
+    rev: 22.1.0
     hooks:
-      - id: black
-        language_version: python3
+      - id: black-jupyter
+        language_version: python3

docs/kyle/calibration.rst

@@ -60,16 +60,16 @@
    "outputs": [],
    "source": [
     "X, y = datasets.make_classification(\n",
-    "        n_samples=n_samples,\n",
-    "        n_features=20,\n",
-    "        n_informative=7,\n",
-    "        n_redundant=10,\n",
-    "        n_classes=n_classes,\n",
-    "        random_state=42,\n",
-    "    )\n",
+    "    n_samples=n_samples,\n",
+    "    n_features=20,\n",
+    "    n_informative=7,\n",
+    "    n_redundant=10,\n",
+    "    n_classes=n_classes,\n",
+    "    random_state=42,\n",
+    ")\n",
     "X_train, X_test, y_train, y_test = train_test_split(\n",
-    "        X, y, test_size=0.2, random_state=42\n",
-    "    )"
+    "    X, y, test_size=0.2, random_state=42\n",
+    ")"
    ]
   },
   {
@@ -270,10 +270,9 @@
    "outputs": [],
    "source": [
     "# Create model calibrator and calibrate model\n",
-    "calibrator = ModelCalibrator(X_calibrate=X_test, \n",
-    "                             y_calibrate=y_test, \n",
-    "                             X_fit=X_train, \n",
-    "                             y_fit=y_train)"
+    "calibrator = ModelCalibrator(\n",
+    "    X_calibrate=X_test, y_calibrate=y_test, X_fit=X_train, y_fit=y_train\n",
+    ")"
    ]
   },
   {
@@ -305,7 +304,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Passing X_test instead of X_calibrate in predict_proba() to make comparison with pre-calib model clear, \n",
+    "# Passing X_test instead of X_calibrate in predict_proba() to make comparison with pre-calib model clear,\n",
     "# same reasong for y_test in ece.compute()\n",
     "calibrated_confidences = calibratable_model.predict_proba(X_test)\n",
     "\n",
@@ -428,10 +427,11 @@
    "source": [
     "def overestimating_max(x: np.ndarray):\n",
     "    x = x.copy()\n",
-    "    mask = x > 1/2\n",
-    "    x[mask] = x[mask] - (1/4 - (1-x[mask])**2)\n",
+    "    mask = x > 1 / 2\n",
+    "    x[mask] = x[mask] - (1 / 4 - (1 - x[mask]) ** 2)\n",
     "    return x\n",
     "\n",
+    "\n",
     "automorphism = MaxComponentSimplexAut(overestimating_max)\n",
     "shifted_sampler = DirichletFC(num_classes=2, simplex_automorphism=automorphism)\n",
     "\n",