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diff --git a/examples/data/pen_digit_train.pkl b/examples/data/pen_digit_train.pkl
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diff --git a/examples/example.ipynb b/examples/example.ipynb
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@@ -1,286 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "da33c65c-dabe-4ce4-8725-7b2cea275c9c",
-   "metadata": {},
-   "source": [
-    "### Installation instruction:\n",
-    "- pip install -i https://test.pypi.org/simple/ signature-mahalanobis-knn==0.1.1\n",
-    "- Install sktime (modified to fix a bug, see issue 1591), esig, iisignature for signature computations: \n",
-    "    - pip install git+https://github.com/sz85512678/sktime.git\n",
-    "    - pip install esig iisignature\n",
-    "- (Optional) Obtain test data from https://github.com/sz85512678/signature_mahalanobis_knn/tree/main/data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "98f9253d-105b-4591-b74d-2cb93f803dfd",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import importlib\n",
-    "\n",
-    "import pandas as pd\n",
-    "\n",
-    "from sig_anomaly import SigMahaKNN"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "90d069f1-b480-4196-a292-0b7ff487a469",
-   "metadata": {},
-   "source": [
-    "### Using anomaly detection on streams"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "b07723b1-2896-4222-9ca1-ae3240ecdb63",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "DATA_DIR = \"./data/\"\n",
-    "digit = 1\n",
-    "\n",
-    "train_df = pd.read_pickle(DATA_DIR + \"pen_digit_train.pkl\")\n",
-    "test_df = pd.read_pickle(DATA_DIR + \"pen_digit_test.pkl\")\n",
-    "corpus = train_df[train_df[\"Digit\"] == digit][\"Stream\"].values\n",
-    "test_inlier = test_df[test_df[\"Digit\"] == digit][\"Stream\"].values\n",
-    "test_outlier = test_df[test_df[\"Digit\"] != digit][\"Stream\"].values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "b23f5fd7-405b-4405-91ca-411456e81728",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sig_maha_knn = SigMahaKNN.SignatureMahalanobisKNN()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cdf60db6-8479-4326-8970-f4475dab2cc3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sig_maha_knn.fit(corpus)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4bc6f3f0-36e8-446d-943d-d7c0b7583c5c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%time\n",
-    "inlier_dists = sig_maha_knn.conformance(test_inlier)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e3ab80da-ed49-4e6e-b669-7f1946c1e636",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%time\n",
-    "outlier_dists = sig_maha_knn.conformance(test_outlier)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c958f03f-1818-4c01-800f-78c4bbbb368f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%time\n",
-    "auc = sig_maha_knn.compute_auc_given_dists(inlier_dists, outlier_dists)\n",
-    "print(\"Auc is\", auc)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "24bc63f8-874c-4d1e-9255-397f632478c8",
-   "metadata": {},
-   "source": [
-    "### Using the variance norm as a standalong object"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b826afcc-b66e-4b74-b132-3063015d9a4e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sktime.transformations.panel.signature_based import SignatureTransformer\n",
-    "from joblib import Parallel, delayed"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "8117ca13-7ca2-4204-a294-a3a07a9eca68",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "mahalanobis = Distance.Mahalanobis()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "ec7a5154-9bb9-431b-84bb-7f44bfabcbc7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "signature_transform = SignatureTransformer(\n",
-    "    augmentation_list=None,\n",
-    "    window_name=\"global\",\n",
-    "    window_depth=None,\n",
-    "    window_length=None,\n",
-    "    window_step=None,\n",
-    "    rescaling=None,\n",
-    "    sig_tfm=\"signature\",\n",
-    "    depth=2,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "06fded8c-0576-413c-840d-ea897988fc39",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sigs = Parallel(n_jobs=-2)(\n",
-    "    delayed(signature_transform.fit_transform)(corpus[i]) for i in range(len(corpus))\n",
-    ")\n",
-    "sigs = pd.concat(sigs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "id": "e88c72bb-fb28-4bd0-ac51-ea4250c60664",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "mahalanobis.fit(sigs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "92267731-855b-40fa-ba99-c2a4a409cb7a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "y1 = test_inlier[0]\n",
-    "sig_y1 = signature_transform.fit_transform(y1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "id": "af911415-63d9-43f1-9610-6a82f3a121a4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "y2 = corpus[0]\n",
-    "sig_y2 = signature_transform.fit_transform(y2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "id": "9e8089b4-0f34-46ea-b1a3-9c9e57979d4d",
-   "metadata": {},
-   "outputs": [
-    {
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-     "execution_count": 57,
-     "metadata": {},
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-   ],
-   "source": [
-    "mahalanobis.distance(sig_y1, sig_y2)"
-   ]
-  },
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-   "cell_type": "code",
-   "execution_count": null,
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