{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.preprocessing import MaxAbsScaler as skMaxAbsScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MaxAbsScaler():\n",
    "    def fit(self, X):\n",
    "        self.scale_ = np.max(np.abs(X), axis=0)\n",
    "        return self\n",
    "\n",
    "    def transform(self, X):\n",
    "        return X / self.scale_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, _ = load_iris(return_X_y=True)\n",
    "sc1 = MaxAbsScaler().fit(X)\n",
    "sc2 = skMaxAbsScaler().fit(X)\n",
    "assert np.allclose(sc1.scale_, sc2.scale_)\n",
    "Xt1 = sc1.transform(X)\n",
    "Xt2 = sc2.transform(X)\n",
    "assert np.allclose(Xt1, Xt2)"
   ]
  }
 ],
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