{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run cSNMF on Trips data using multiplicative update rules\n",
    "\n",
    "**Constraint:** L1 norm of columns of W should be 1\n",
    "\n",
    "Get a copy of the data matrices in your local machine from the following links:\n",
    " - https://uofi.box.com/s/yo60oe084d68obohgraek4weuaqtpgsp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __init__ import *\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import config\n",
    "import cSNMF\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Read Full-Link data and prep for running NMF.\n",
    "D = np.loadtxt('D_trips.txt')\n",
    "logger.info('Full_link data has been read')\n",
    "\n",
    "if config.SEEDED == 1:\n",
    "    seed_W = 0; seed_H = 1\n",
    "elif config.SEEDED == 0:\n",
    "    seed_W = None; seed_H = None\n",
    "else:\n",
    "    logger.critical('Seed value invalid. Needs to be 0 or 1. Check config.py!')\n",
    "    quit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "W, H, results = cSNMF.factorize(D,\n",
    "                                beta = 5000,\n",
    "                                rank = config.RANK,\n",
    "                                max_iter = 600,\n",
    "                                seed_W = seed_W,\n",
    "                                seed_H = seed_H,\n",
    "                                debug = True,\n",
    "                                axing = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#np.savetxt('W_(seed_W = 10,seed_H = 21).txt', W)\n",
    "#np.savetxt('H_(seed_W = 10,seed_H = 21).txt', H)"
   ]
  }
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