changed path to css styles

Chapter01_gh_filter/g-h_filter.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:a19258e631c2ec61dbe30715e5859eb2e636ae447095dfe15105ade7e1065d91"
+  "signature": "sha256:705f5c9f0ff79f1dc1b20770eaf7af9dc0114b1bb0f86c980cba8f8d3ee135f2"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -23,6 +23,8 @@
       "#format the book\n",
       "%matplotlib inline\n",
       "from __future__ import division, print_function\n",
+      "import sys\n",
+      "sys.path.insert(0,'../') # allow us to import book_format\n",
       "import matplotlib.pyplot as plt\n",
       "import book_format\n",
       "book_format.load_style()"
@@ -250,7 +252,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fd0302db780>"
+        "<IPython.core.display.HTML at 0x7f85601a09e8>"
        ]
       }
      ],
@@ -343,9 +345,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01aa7c048>"
+        "<matplotlib.figure.Figure at 0x7f854a9340b8>"
        ]
       }
      ],
@@ -379,13 +381,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7f3f98>"
+        "<matplotlib.figure.Figure at 0x7f854a919f98>"
        ]
       }
      ],
-     "prompt_number": 36
+     "prompt_number": 3
     },
     {
      "cell_type": "markdown",
@@ -415,13 +417,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a95e978>"
+        "<matplotlib.figure.Figure at 0x7f854a8d4978>"
        ]
       }
      ],
-     "prompt_number": 37
+     "prompt_number": 4
     },
     {
      "cell_type": "markdown",
@@ -452,9 +454,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fd0302db4e0>"
+        "<matplotlib.figure.Figure at 0x7f854a8e0128>"
        ]
       }
      ],
@@ -479,13 +481,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a8635c0>"
+        "<matplotlib.figure.Figure at 0x7f854a94abe0>"
        ]
       }
      ],
-     "prompt_number": 38
+     "prompt_number": 6
     },
     {
      "cell_type": "markdown",
@@ -514,9 +516,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01aa71e80>"
+        "<matplotlib.figure.Figure at 0x7f854a902e10>"
        ]
       }
      ],
@@ -582,13 +584,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a825e10>"
+        "<matplotlib.figure.Figure at 0x7f854a730048>"
        ]
       }
      ],
-     "prompt_number": 40
+     "prompt_number": 8
     },
     {
      "cell_type": "markdown",
@@ -611,13 +613,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a843748>"
+        "<matplotlib.figure.Figure at 0x7f854a957e80>"
        ]
       }
      ],
-     "prompt_number": 41
+     "prompt_number": 9
     },
     {
      "cell_type": "markdown",
@@ -683,13 +685,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7fe048>"
+        "<matplotlib.figure.Figure at 0x7f854a8ddeb8>"
        ]
       }
      ],
-     "prompt_number": 43
+     "prompt_number": 10
     },
     {
      "cell_type": "markdown",
@@ -750,7 +752,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a9d3ac8>"
+        "<matplotlib.figure.Figure at 0x7f854a9197b8>"
        ]
       }
      ],
@@ -861,13 +863,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a8705c0>"
+        "<matplotlib.figure.Figure at 0x7f854a702390>"
        ]
       }
      ],
-     "prompt_number": 47
+     "prompt_number": 12
     },
     {
      "cell_type": "heading",
@@ -940,13 +942,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a974828>"
+        "<matplotlib.figure.Figure at 0x7f854a8dd908>"
        ]
       }
      ],
-     "prompt_number": 48
+     "prompt_number": 14
     },
     {
      "cell_type": "heading",
@@ -996,13 +998,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a815668>"
+        "<matplotlib.figure.Figure at 0x7f854a8dbd30>"
        ]
       }
      ],
-     "prompt_number": 49
+     "prompt_number": 16
     },
     {
      "cell_type": "markdown",
@@ -1059,13 +1061,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd018f74898>"
+        "<matplotlib.figure.Figure at 0x7f854a8fba58>"
        ]
       }
      ],
-     "prompt_number": 50
+     "prompt_number": 18
     },
     {
      "cell_type": "markdown",
@@ -1133,13 +1135,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7b7128>"
+        "<matplotlib.figure.Figure at 0x7f854a6f7d30>"
        ]
       }
      ],
-     "prompt_number": 51
+     "prompt_number": 20
     },
     {
      "cell_type": "markdown",
@@ -1208,29 +1210,29 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a831c18>"
+        "<matplotlib.figure.Figure at 0x7f854a8a99b0>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01aa1e080>"
+        "<matplotlib.figure.Figure at 0x7f854a8d4e80>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a8d47f0>"
+        "<matplotlib.figure.Figure at 0x7f854a7e8f98>"
        ]
       }
      ],
-     "prompt_number": 52
+     "prompt_number": 22
     },
     {
      "cell_type": "markdown",
@@ -1263,29 +1265,29 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01aa2ac88>"
+        "<matplotlib.figure.Figure at 0x7f854a8e0748>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a963780>"
+        "<matplotlib.figure.Figure at 0x7f854a82fdd8>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7d6828>"
+        "<matplotlib.figure.Figure at 0x7f854a806ba8>"
        ]
       }
      ],
-     "prompt_number": 53
+     "prompt_number": 23
     },
     {
      "cell_type": "markdown",
@@ -1314,21 +1316,21 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a838978>"
+        "<matplotlib.figure.Figure at 0x7f854a881908>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7d0908>"
+        "<matplotlib.figure.Figure at 0x7f854a7fc518>"
        ]
       }
      ],
-     "prompt_number": 54
+     "prompt_number": 24
     },
     {
      "cell_type": "heading",
@@ -1370,29 +1372,29 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a8d4860>"
+        "<matplotlib.figure.Figure at 0x7f854a7a4898>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a910dd8>"
+        "<matplotlib.figure.Figure at 0x7f854a801438>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd01a7b3320>"
+        "<matplotlib.figure.Figure at 0x7f854a7b3320>"
        ]
       }
      ],
-     "prompt_number": 55
+     "prompt_number": 25
     },
     {
      "cell_type": "heading",
@@ -1459,7 +1461,7 @@
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "[1] http://nescacademy.nasa.gov/review/downloadfile.php?file=FundamentalsofKalmanFiltering_Presentation.pdf&amp;id=199&amp;distr=Public"
+      "-  [1] [NASA Kalman Filtering Presentation](http://nescacademy.nasa.gov/review/downloadfile.php?file=FundamentalsofKalmanFiltering_Presentation.pdf&amp;id=199&amp;distr=Public)"
      ]
     }
    ],