{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.covariance import EmpiricalCovariance as skEmpiricalCovariance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class EmpiricalCovariance():\n",
    "    def fit(self, X):\n",
    "        self.covariance_ = np.cov(X.T, bias=True)\n",
    "        return self"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, _ = load_iris(return_X_y=True)\n",
    "est1 = EmpiricalCovariance().fit(X)\n",
    "est2 = skEmpiricalCovariance().fit(X)\n",
    "assert np.allclose(est1.covariance_, est2.covariance_)"
   ]
  }
 ],
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