{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_conj_grad( grad, Q ):\n",
    "\n",
    "    def conj_grad( x ):\n",
    "\n",
    "        g = grad( x )\n",
    "        if conj_grad.g is None:\n",
    "            d = g\n",
    "        else:\n",
    "            beta = g @ g / ( conj_grad.g @ conj_grad.g )\n",
    "            d = g - beta * conj_grad.d\n",
    "        \n",
    "        step = g @ d / ( d @ Q @ d )\n",
    "        x = x - step * d\n",
    "\n",
    "        conj_grad.g = g\n",
    "        conj_grad.d = d\n",
    "\n",
    "        return x\n",
    "\n",
    "    conj_grad.d = None\n",
    "    conj_grad.g = None\n",
    "\n",
    "    return conj_grad"
   ]
  }
 ],
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