diff --git a/LICENSE b/LICENSE
index 7ac90f881..eb55d7df0 100644
--- a/LICENSE
+++ b/LICENSE
@@ -4,7 +4,8 @@ Copyright (c) Newline Technical Innovations 2014, All rights reserved.
 
 Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
 
-Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 Clarifications on Scope:
-The BSD license applies to all files in this repository except the following directories: CEngine, viewer, lib, cef, and git. Excluded directories each have their own licensing terms.
\ No newline at end of file
+The BSD license applies to all files in this repository except the following directories: CEngine, viewer, lib, and non ADSM files in bin. Excluded directories each have their own licensing terms.
\ No newline at end of file
diff --git a/Requirements.txt b/Requirements.txt
index 34c3840ca..c0a630306 100644
--- a/Requirements.txt
+++ b/Requirements.txt
@@ -17,3 +17,5 @@ pytz==2014.10
 requests==2.7.0
 selenium==2.44.0
 six==1.8.0
+setuptools==5.7
+pip==1.5.6
diff --git a/Running_Server.ipynb b/Running_Server.ipynb
index 0f71de90d..72d2e417f 100644
--- a/Running_Server.ipynb
+++ b/Running_Server.ipynb
@@ -1,16 +1,12 @@
 {
- "metadata": {
-  "name": "",
-  "signature": "sha256:5cfea6e2729c5b537c3e66df606ae6fb2806154ef24a9dc85d54b1f9c316a320"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
  "worksheets": [
   {
    "cells": [
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "import sys;\n",
       "sys.path.extend(['C:\\\\Users\\\\Josiah\\\\Documents\\\\SpreadModel', 'C:\\\\Python33\\\\Lib\\\\site-packages\\\\crispy_forms', 'C:\\\\Program Files\\\\PyCharm 3.1.1\\\\helpers\\\\pycharm', 'C:\\\\Program Files\\\\PyCharm 3.1.1\\\\helpers\\\\pydev'])\n",
@@ -19,17 +15,11 @@
       "django_manage_shell.run(\"C:/Users/Josiah/Documents/SpreadModel\")"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 1
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "from Results.models import DailyReport"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
@@ -51,36 +41,35 @@
        ]
       }
      ],
+     "input": [
+      "from Results.models import DailyReport"
+     ],
+     "language": "python",
      "prompt_number": 2
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "DailyReport.objects.count()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 3,
        "text": [
         "912"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "DailyReport.objects.count()"
+     ],
+     "language": "python",
      "prompt_number": 3
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "%pylab inline\n",
-      "import pandas as pd"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
@@ -91,59 +80,60 @@
        ]
       }
      ],
+     "input": [
+      "%pylab inline\n",
+      "import pandas as pd"
+     ],
+     "language": "python",
      "prompt_number": 4
     },
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "from ScenarioCreator.models import Unit"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 5
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "Unit.objects.count()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 6,
        "text": [
         "3957"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "Unit.objects.count()"
+     ],
+     "language": "python",
      "prompt_number": 6
     },
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "latlong = [(u.latitude, u.longitude) for u in Unit.objects.all()]\n",
       "df = pd.DataFrame.from_records(latlong, )\n",
       "df.columns = ['Latitude', 'Longitude']"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 7
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "fig = df.plot('Longitude', 'Latitude', kind='scatter', color='black', figsize=(6.5,6)).figure"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
@@ -165,60 +155,66 @@
        ]
       },
       {
-       "metadata": {},
        "output_type": "display_data",
        "png": 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7VPbaa68JsS4+Pj6Ijo5GREQEgoOD0aFDB0G1OGfOHOGeOp0OvXv3FtG9fft2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\nBAKBQCAQCASCy8n/A7ddJ00h8J/uAAAAAElFTkSuQmCC\n",
        "text": [
         "<matplotlib.figure.Figure at 0x3bdef98>"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "fig = df.plot('Longitude', 'Latitude', kind='scatter', color='black', figsize=(6.5,6)).figure"
+     ],
+     "language": "python",
      "prompt_number": 8
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "from Results.models import DailyByProductionType\n",
-      "DailyByProductionType.objects.count()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 9,
        "text": [
         "2736"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "from Results.models import DailyByProductionType\n",
+      "DailyByProductionType.objects.count()"
+     ],
+     "language": "python",
      "prompt_number": 9
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "DailyByProductionType.objects.filter(iteration=1).count()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 10,
        "text": [
         "546"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "DailyByProductionType.objects.filter(iteration=1).count()"
+     ],
+     "language": "python",
      "prompt_number": 10
     },
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "#Make the annoying debug messages go away.\n",
       "from django.conf import settings\n",
@@ -228,144 +224,137 @@
       "BaseDatabaseWrapper.make_debug_cursor = lambda self, cursor: CursorWrapper(cursor, self)"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 11
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "DailyByProductionType.objects.filter(iteration=1).count()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 12,
        "text": [
         "546"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "DailyByProductionType.objects.filter(iteration=1).count()"
+     ],
+     "language": "python",
      "prompt_number": 12
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', 'expnUAir')"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 13,
        "text": [
         "[(1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0), (17, 0), (18, 0), (19, 0), (20, 0), '...(remaining elements truncated)...']"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', 'expnUAir')"
+     ],
+     "language": "python",
      "prompt_number": 13
     },
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "import pandas as pd"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 14
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "field_name = 'expnUDir'\n",
-      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
-      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
-      "df = df.set_index('day')\n",
-      "df.plot()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 16,
        "text": [
         "<matplotlib.axes.AxesSubplot at 0x8a33390>"
-       ]
+       ],
+       "metadata": {}
       },
       {
-       "metadata": {},
        "output_type": "display_data",
        "png": 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CN91kJ9G+5hpoabEDpu3ebfPyP/3UphoOHw4PPABXXJHuf4V/aGQvkj2ystif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\ni8LBV1RKAAAAAElFTkSuQmCC\n",
        "text": [
         "<matplotlib.figure.Figure at 0x8a44208>"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "field_name = 'expnUDir'\n",
+      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
+      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
+      "df = df.set_index('day')\n",
+      "df.plot()"
+     ],
+     "language": "python",
      "prompt_number": 16
     },
     {
      "cell_type": "heading",
-     "level": 1,
      "metadata": {},
+     "level": 1,
      "source": [
       "Calculating tstnUAll from tstcUAll"
      ]
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "field_name = 'tstcUAll'\n",
-      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
-      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
-      "df = df.set_index('day')\n",
-      "df.plot()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 19,
        "text": [
         "<matplotlib.axes.AxesSubplot at 0x8abe5f8>"
-       ]
+       ],
+       "metadata": {}
       },
       {
-       "metadata": {},
        "output_type": "display_data",
        "png": 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2NZPEIiJysmgXgp7ARmALcE80PnDzZjMnMHFi/LWE1Id1lvLpHOXSW6JZCOoC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\n+4gr1OP4y5UAAAAASUVORK5CYII=\n",
        "text": [
         "<matplotlib.figure.Figure at 0x8c17f98>"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "field_name = 'tstcUAll'\n",
+      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
+      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
+      "df = df.set_index('day')\n",
+      "df.plot()"
+     ],
+     "language": "python",
      "prompt_number": 19
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 23,
        "text": [
@@ -551,43 +540,31 @@
         " (180, 2800),\n",
         " (181, 2800),\n",
         " (182, 2800)]"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))"
+     ],
+     "language": "python",
      "prompt_number": 23
     },
     {
      "cell_type": "code",
-     "collapsed": false,
+     "execution_count": null,
+     "metadata": {},
+     "outputs": [],
      "input": [
       "from Results.graphing import *\n",
       "from Results.views import *"
      ],
      "language": "python",
-     "metadata": {},
-     "outputs": [],
      "prompt_number": 21
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "field_name = 'tstcUAll'\n",
-      "for pt in list(ProductionType.objects.all()) + [None]:\n",
-      "    for iteration in list_of_iterations():\n",
-      "        print(\"For\", pt)\n",
-      "        tstCUAll = {day: value for day, value in list(DailyByProductionType.objects.filter(iteration=iteration, production_type=pt).order_by('day').values_list('day', field_name))}\n",
-      "        for day in range(1, len(tstCUAll)):\n",
-      "            current = DailyByProductionType.objects.filter(day=day, iteration=iteration, production_type=pt).first()\n",
-      "            previous = 0\n",
-      "            try:  previous = tstCUAll[day-1]\n",
-      "            except: print('Fail')\n",
-      "            current.tstnUAll = current.tstcUAll - previous\n",
-      "            current.save()\n",
-      "            print(current.tstnUAll)\n",
-      "        print('\\n')"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
@@ -6381,42 +6358,65 @@
        ]
       }
      ],
+     "input": [
+      "field_name = 'tstcUAll'\n",
+      "for pt in list(ProductionType.objects.all()) + [None]:\n",
+      "    for iteration in list_of_iterations():\n",
+      "        print(\"For\", pt)\n",
+      "        tstCUAll = {day: value for day, value in list(DailyByProductionType.objects.filter(iteration=iteration, production_type=pt).order_by('day').values_list('day', field_name))}\n",
+      "        for day in range(1, len(tstCUAll)):\n",
+      "            current = DailyByProductionType.objects.filter(day=day, iteration=iteration, production_type=pt).first()\n",
+      "            previous = 0\n",
+      "            try:  previous = tstCUAll[day-1]\n",
+      "            except: print('Fail')\n",
+      "            current.tstnUAll = current.tstcUAll - previous\n",
+      "            current.save()\n",
+      "            print(current.tstnUAll)\n",
+      "        print('\\n')"
+     ],
+     "language": "python",
      "prompt_number": 37
     },
     {
      "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "field_name = 'tstnUAll'\n",
-      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
-      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
-      "df = df.set_index('day')\n",
-      "df.plot()"
-     ],
-     "language": "python",
+     "execution_count": null,
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
        "output_type": "pyout",
        "prompt_number": 38,
        "text": [
         "<matplotlib.axes.AxesSubplot at 0x81d6198>"
-       ]
+       ],
+       "metadata": {}
       },
       {
-       "metadata": {},
        "output_type": "display_data",
        "png": 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aT/fwTdjHzs4Ta5zGRjOzb2+HOXOiz6mvj87s04V9ZWVhKxw3iw37efP8HfYi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\nTkSuQmCC\n",
        "text": [
         "<matplotlib.figure.Figure at 0x926cf98>"
-       ]
+       ],
+       "metadata": {}
       }
      ],
+     "input": [
+      "field_name = 'tstnUAll'\n",
+      "time_series = list(DailyByProductionType.objects.filter(iteration=1, production_type__isnull=True).order_by('day').values_list('day', field_name))\n",
+      "df = pd.DataFrame.from_records(time_series, columns=['day', field_name])\n",
+      "df = df.set_index('day')\n",
+      "df.plot()"
+     ],
+     "language": "python",
      "prompt_number": 38
     }
-   ],
-   "metadata": {}
+   ]
   }
- ]
+ ],
+ "cells": [],
+ "metadata": {
+  "name": "",
+  "signature": "sha256:5cfea6e2729c5b537c3e66df606ae6fb2806154ef24a9dc85d54b1f9c316a320"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0
 }
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 7bb74c880..ffa5d5a44 100644
--- a/setup.py
+++ b/setup.py
@@ -30,6 +30,7 @@ def is_exe(file_path):
     'optimize': 2,
     'excludes': [
         'PyInstaller',
+        'tkinter',
         # CHANGE ME for any python packages in your project that you want excluded
         'development_scripts',
     ],