added chapter 6

Chapter06_Multivariate_Kalman_Filter/Multivariate_Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
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  "metadata": {
   "name": "",
-  "signature": "sha256:689fdab3b9385731104bb925d50f2360185797210ca2900cef719d1f11561ea8"
+  "signature": "sha256:1cf32a918b0518a8dbaabb862de993dcbd8cd2de501bc94b1f4be396791bea47"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -24,6 +24,8 @@
       "%matplotlib inline\n",
       "from __future__ import division, print_function\n",
       "import matplotlib.pyplot as plt\n",
+      "import sys\n",
+      "sys.path.insert(0,'../') # allow us to import book_format\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 0x7fad5e7be860>"
+        "<IPython.core.display.HTML at 0x7f45ed9179e8>"
        ]
       }
      ],
@@ -361,7 +363,7 @@
        "output_type": "display_data",
        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad4976dc88>"
+        "<matplotlib.figure.Figure at 0x7f45ed9179b0>"
        ]
       }
      ],
@@ -556,7 +558,7 @@
        "output_type": "display_data",
        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41ad3828>"
+        "<matplotlib.figure.Figure at 0x7f45ccc52eb8>"
        ]
       }
      ],
@@ -603,7 +605,7 @@
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        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d9f8d0>"
+        "<matplotlib.figure.Figure at 0x7f45ccf14898>"
        ]
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@@ -691,7 +693,7 @@
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41c5c470>"
+        "<matplotlib.figure.Figure at 0x7f45ccdb60b8>"
        ]
       }
      ],
@@ -718,7 +720,7 @@
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        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad4196b320>"
+        "<matplotlib.figure.Figure at 0x7f45ccd825c0>"
        ]
       }
      ],
@@ -745,11 +747,11 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41aab0f0>"
+        "<matplotlib.figure.Figure at 0x7f45ccdb60b8>"
        ]
       }
      ],
-     "prompt_number": 44
+     "prompt_number": 13
     },
     {
      "cell_type": "markdown",
@@ -776,7 +778,7 @@
        "output_type": "display_data",
        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41c147f0>"
+        "<matplotlib.figure.Figure at 0x7f45cce35a90>"
        ]
       }
      ],
@@ -843,7 +845,7 @@
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad4196b668>"
+        "<matplotlib.figure.Figure at 0x7f45ccdb67b8>"
        ]
       }
      ],
@@ -1837,9 +1839,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d8e5f8>"
+        "<matplotlib.figure.Figure at 0x7f45cce35278>"
        ]
       },
       {
@@ -1847,7 +1849,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41ce5d30>"
+        "<matplotlib.figure.Figure at 0x7f45cce37a20>"
        ]
       }
      ],
@@ -2009,9 +2011,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d92a20>"
+        "<matplotlib.figure.Figure at 0x7f45ccf11d30>"
        ]
       },
       {
@@ -2019,7 +2021,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41af0be0>"
+        "<matplotlib.figure.Figure at 0x7f45cce73208>"
        ]
       }
      ],
@@ -2251,9 +2253,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41c87828>"
+        "<matplotlib.figure.Figure at 0x7f45cce29be0>"
        ]
       }
      ],
@@ -2311,17 +2313,17 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d686a0>"
+        "<matplotlib.figure.Figure at 0x7f45ccddde48>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d681d0>"
+        "<matplotlib.figure.Figure at 0x7f45cce29a58>"
        ]
       }
      ],
@@ -2434,9 +2436,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d0e2e8>"
+        "<matplotlib.figure.Figure at 0x7f45ccf10470>"
        ]
       }
      ],
@@ -2506,7 +2508,7 @@
        "output_type": "display_data",
        "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad4976dac8>"
+        "<matplotlib.figure.Figure at 0x7f45cce4a780>"
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@@ -2535,7 +2537,7 @@
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41caa940>"
+        "<matplotlib.figure.Figure at 0x7f45ed917978>"
        ]
       }
      ],
@@ -2605,7 +2607,7 @@
        "output_type": "display_data",
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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad5e7be518>"
+        "<matplotlib.figure.Figure at 0x7f45ccddadd8>"
        ]
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      ],
@@ -2634,7 +2636,7 @@
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d73ef0>"
+        "<matplotlib.figure.Figure at 0x7f45cce0e780>"
        ]
       }
      ],
@@ -2668,7 +2670,7 @@
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        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d06ac8>"
+        "<matplotlib.figure.Figure at 0x7f45cceebd30>"
        ]
       }
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@@ -2699,7 +2701,7 @@
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41c8b4a8>"
+        "<matplotlib.figure.Figure at 0x7f45ccd82908>"
        ]
       }
      ],
@@ -2769,17 +2771,17 @@
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41ae30f0>"
+        "<matplotlib.figure.Figure at 0x7f45cced7b00>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41d03cc0>"
+        "<matplotlib.figure.Figure at 0x7f45ccf183c8>"
        ]
       }
      ],
@@ -2846,7 +2848,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fad41c14550>"
+        "<matplotlib.figure.Figure at 0x7f45cce4a198>"
        ]
       }
      ],
@@ -3054,13 +3056,13 @@
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "[1] http://docs.scipy.org/doc/scipy/reference/tutorial/stats.htmly\n",
+      "- [1] http://docs.scipy.org/doc/scipy/reference/tutorial/stats.htmly\n",
       "\n",
-      "[2] https://en.wikipedia.org/wiki/Kalman_filter\n",
+      "- [2] https://en.wikipedia.org/wiki/Kalman_filter\n",
       "\n",
-      "[3] Brown, Robert Grover. *Introduction to Random Signals and Applied Kalman Filtering* John Wiley & Sons, Inc. 2012\n",
+      "- [3] Brown, Robert Grover. *Introduction to Random Signals and Applied Kalman Filtering* John Wiley & Sons, Inc. 2012\n",
       "\n",
-      "[4] `filterpy` library. Roger Labbe.\n",
+      "- [4] `filterpy` library. Roger Labbe.\n",
       "https://github.com/rlabbe/filterpy"
      ]
     }