{
 "metadata": {
  "name": "",
  "signature": "sha256:2972c0b3c7481ca5e105417e00e4846665d843be51b375771941bbcd06d594d0"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from scipy.sparse import linalg\n",
      "from scipy.stats import rankdata\n",
      "from brightway2 import *\n",
      "from time import time\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "http://docs.scipy.org/doc/scipy/reference/sparse.linalg.html#module-scipy.sparse.linalg"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "solvers = [\n",
      "    linalg.bicg,\n",
      "    linalg.bicgstab,\n",
      "    linalg.cg,\n",
      "    linalg.cgs,\n",
      "    linalg.gmres,\n",
      "    linalg.lgmres,\n",
      "    # linalg.minres,  # Too slow\n",
      "    linalg.qmr,\n",
      "    linalg.spsolve,\n",
      "]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "s_indices = {s.__name__: i for i, s in enumerate(solvers)}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "results = {s.__name__: [] for s in solvers}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* bicg(A, b[, x0, tol, maxiter, xtype, M, ...])\tUse BIConjugate Gradient iteration to solve A x = b\n",
      "* bicgstab(A, b[, x0, tol, maxiter, xtype, M, ...])\tUse BIConjugate Gradient STABilized iteration to solve A x = b\n",
      "* cg(A, b[, x0, tol, maxiter, xtype, M, callback])\tUse Conjugate Gradient iteration to solve A x = b\n",
      "* cgs(A, b[, x0, tol, maxiter, xtype, M, callback])\tUse Conjugate Gradient Squared iteration to solve A x = b\n",
      "* gmres(A, b[, x0, tol, restart, maxiter, ...])\tUse Generalized Minimal RESidual iteration to solve A x = b.\n",
      "* lgmres(A, b[, x0, tol, maxiter, M, ...])\tSolve a matrix equation using the LGMRES algorithm.\n",
      "* minres(A, b[, x0, shift, tol, maxiter, ...])\tUse MINimum RESidual iteration to solve Ax=b\n",
      "* qmr(A, b[, x0, tol, maxiter, xtype, M1, M2, ...])"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ei = Database(\"ecoinvent 2.2\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "method = methods.random()\n",
      "method"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "(u'ReCiPe Endpoint (H,A) w/o LT',\n",
        " u'ecosystem quality w/o LT',\n",
        " u'climate change, ecosystems w/o LT')"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def test_all_solvers(mc, results):\n",
      "    for solver in solvers:\n",
      "        start = time()\n",
      "        if solver == linalg.spsolve:\n",
      "            solver(\n",
      "                mc.technosphere_matrix,\n",
      "                mc.demand_array,\n",
      "            )\n",
      "        else:\n",
      "            solver(\n",
      "                mc.technosphere_matrix,\n",
      "                mc.demand_array,\n",
      "                x0=mc.guess,\n",
      "                maxiter=1000\n",
      "            )\n",
      "        results[solver.__name__].append(time() - start)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for x in range(100):\n",
      "    mc = MonteCarloLCA({ei.random(): 1}, method)\n",
      "    mc.load_data()\n",
      "    mc.next()\n",
      "    test_all_solvers(mc, results)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "xs = range(len(results.values()[0]))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import seaborn as sns\n",
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.clf()\n",
      "\n",
      "fig = plt.gcf()\n",
      "fig.set_size_inches(6, 4)\n",
      "\n",
      "for key, value in results.items():\n",
      "    plt.semilogy(xs, value, label=key)\n",
      "\n",
      "plt.legend(frameon=True, ncol=2)\n",
      "plt.ylabel(\"Time (seconds, log-scale)\")\n",
      "plt.xlabel(\"Monte Carlo iteration\")\n",
      "plt.savefig(\"speed-iterative.png\", dpi=600)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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DwW7Tu9tJk3IpKXGj2fX35i8bH8PUFOEHS69gYdkcADa1bOf+zx8ipsr8c+fz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\nAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11e304c10>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.clf()\n",
      "\n",
      "fig = plt.gcf()\n",
      "fig.set_size_inches(6, 4)\n",
      "\n",
      "for key, value in results.items():\n",
      "    if key in ('spsolve', 'minres', 'bicg', 'qmr'):\n",
      "        continue\n",
      "    plt.semilogy(xs, value, label=key)\n",
      "\n",
      "plt.legend(frameon=True, loc=\"upper left\")\n",
      "plt.ylabel(\"Time (seconds, log-scale)\")\n",
      "plt.xlabel(\"Monte Carlo iteration\")\n",
      "plt.savefig(\"speed-zoom-in.png\", dpi=600)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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4NXZV9xNxmjtH78DpeyUMhelmZDrJiAsNgqaQ7A0KoTEWNE3H16MRdvgx0Gmo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\nIiIiIiIiIiIiIiIiIiIiIiLT5f8BtjCtzFUvIEsAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11bb34450>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for key, value in results.items():\n",
      "    print key, np.min(value), np.average(value), np.max(value)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "bicgstab 0.00020694732666 0.000227701663971 0.000385999679565\n",
        "spsolve 0.031023979187 0.0355286335945 0.0416750907898\n",
        "lgmres 0.000256776809692 0.00028133392334 0.000576019287109\n",
        "bicg 0.000754117965698 0.0227880167961 0.278461933136\n",
        "qmr 0.000820875167847 0.0101756834984 0.0417850017548\n",
        "cg 0.000200986862183 0.000222446918488 0.000375032424927\n",
        "gmres 0.000254154205322 0.000294797420502 0.000549793243408\n",
        "cgs 0.000198841094971 0.000214467048645 0.000446081161499\n"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l = []\n",
      "for key, value in results.items():\n",
      "    l.append((np.average(value), key))\n",
      "\n",
      "sorted(l)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "[(0.00021446704864501952, 'cgs'),\n",
        " (0.00022244691848754883, 'cg'),\n",
        " (0.00022770166397094725, 'bicgstab'),\n",
        " (0.00028133392333984375, 'lgmres'),\n",
        " (0.00029479742050170899, 'gmres'),\n",
        " (0.010175683498382569, 'qmr'),\n",
        " (0.022788016796112059, 'bicg'),\n",
        " (0.035528633594512943, 'spsolve')]"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "m = [x[1] for x in sorted(l)]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for key in m:\n",
      "    print \"%s\\t%.5f\\t%.5f\\t%.5f\" % (key, np.min(results[key]), np.average(results[key]), np.max(results[key]))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "cgs\t0.00020\t0.00021\t0.00045\n",
        "cg\t0.00020\t0.00022\t0.00038\n",
        "bicgstab\t0.00021\t0.00023\t0.00039\n",
        "lgmres\t0.00026\t0.00028\t0.00058\n",
        "gmres\t0.00025\t0.00029\t0.00055\n",
        "qmr\t0.00082\t0.01018\t0.04179\n",
        "bicg\t0.00075\t0.02279\t0.27846\n",
        "spsolve\t0.03102\t0.03553\t0.04168\n"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}