use python 2.7

permanent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from permanent import permanent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def det_and_per(n, k, p):\n",
    "    k_matrices = np.random.randint(-p+1, p+1, size=(k, n, n))\n",
    "    det_list = np.zeros(2*p + 1)\n",
    "    per_list = np.zeros(2*p + 1)\n",
    "    for matrix in np.split(k_matrices, k):\n",
    "        matrix = matrix.reshape(n, n)\n",
    "        det = int(np.linalg.det(matrix)) % (2*p+1)\n",
    "        per = int(permanent(matrix.astype(complex)).real) % (2*p+1)\n",
    "        det_list[det] = det_list[det] + 1\n",
    "        per_list[per] = per_list[per] + 1\n",
    "    print(\"Determinent distribution: {}\".format((det_list / k).tolist()))\n",
    "    print(\"Permanent distribution: {}\".format((per_list / k).tolist()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Determinent distribution: [0.3929, 0.2984, 0.3087]\n",
      "Permanent distribution: [0.3311, 0.3278, 0.3411]\n",
      "CPU times: user 4min 16s, sys: 39.2 ms, total: 4min 16s\n",
      "Wall time: 4min 16s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "det_and_per(15, 10000, 1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (py27)",
   "language": "python",
   "name": "py27"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}