Removed temporary files and test code.

I made some changes while testing the plotting change in the last checkin,
and it inadvertantly got checked in.

Untitled1.ipynb

@@ -1,62 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAEKCAYAAAD3tSVSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1df7a30c860>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "plt.plot([1,3,2], [5,3,6])\n",
-    "plt.title('fuck you')\n",
-    "plt.show()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python [default]",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.1"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}

pdf/merge_book.py

@@ -41,10 +41,10 @@ def merge_notebooks(outfile, filenames):
 
 if __name__ == '__main__':
     with open('book.ipynb', 'w', encoding='utf-8') as f:
-        merge_notebooks(f,
-            ['../14-Adaptive-Filtering.ipynb'])
-
         '''merge_notebooks(f,
+            ['../14-Adaptive-Filtering.ipynb'])'''
+
+        merge_notebooks(f,
             ['../00-Preface.ipynb',
              '../01-g-h-filter.ipynb',
              '../02-Discrete-Bayes.ipynb',
@@ -63,7 +63,7 @@ if __name__ == '__main__':
              '../Appendix-A-Installation.ipynb',
              '../Appendix-B-Symbols-and-Notations.ipynb',
              '../Appendix-D-HInfinity-Filters.ipynb',
-             '../Appendix-E-Ensemble-Kalman-Filters.ipynb'])'''
+             '../Appendix-E-Ensemble-Kalman-Filters.ipynb'])
 
 
     #remove text printed for matplotlib charts