moved chapters 11 and 12 for reorg.

11_Ensemble_Kalman_Filter/README.md

@@ -1,3 +0,0 @@
-You may read this book online via nbviewer by using this link:
-[*Read Online Now*](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)
-z

11_Ensemble_Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:117157ef61273ba2130924efba98e19d14240ed7d99a785a7b9319d86ac83680"
+  "signature": "sha256:5346f4c3acd322f6b0d64eb36febeafe9c3d7e392f241c7bdd3b7950924dbe44"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -32,7 +32,7 @@
       "from __future__ import division, print_function\n",
       "import matplotlib.pyplot as plt\n",
       "import sys\n",
-      "sys.path.insert(0,'../code') # allow us to format the book\n",
+      "sys.path.insert(0,'./code') # allow us to format the book\n",
       "import book_format\n",
       "book_format.load_style()"
      ],
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7f92d3e98128>"
+        "<IPython.core.display.HTML at 0x7f970a241400>"
        ]
       }
      ],
@@ -312,9 +312,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f92b6f5a5f8>"
+        "<matplotlib.figure.Figure at 0x7f96f0d98940>"
        ]
       }
      ],
@@ -351,8 +351,7 @@
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "$$\\boldsymbol\\chi \\sim \\mathcal{N}(\\mathbf{x}_0, \\mathbf{P}_0)\n",
-      "$$\n",
+      "$$\\boldsymbol\\chi \\sim \\mathcal{N}(\\mathbf{x}_0, \\mathbf{P}_0)$$\n",
       "\n",
       "This just says to select the sigma points from the filter's initial mean and covariance. In code this might look like\n",
       "\n",
@@ -635,7 +634,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f92b365a908>"
+        "<matplotlib.figure.Figure at 0x7f96e5a34a58>"
        ]
       }
      ],

12_Designing_Nonlinear_Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:791761b5754db825adff7c53fa4f7ad4db30eca96fd08a08c78aa79f84242d39"
+  "signature": "sha256:b5fb5804ede73bfa10fc7023f5c5db78201332729c4ab675b5f971ed71273b41"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -32,7 +32,7 @@
       "from __future__ import division, print_function\n",
       "import matplotlib.pyplot as plt\n",
       "import sys\n",
-      "sys.path.insert(0, '../code') # allow us to format the book\n",
+      "sys.path.insert(0, './code') # allow us to format the book\n",
       "import book_format\n",
       "book_format.load_style()"
      ],
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fbcef879128>"
+        "<IPython.core.display.HTML at 0x7f1ee7140438>"
        ]
       }
      ],
@@ -406,7 +406,7 @@
        "output_type": "display_data",
        "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fbcd33ea7b8>"
+        "<matplotlib.figure.Figure at 0x7f1eca2736a0>"
        ]
       }
      ],
@@ -825,9 +825,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fbcd2103320>"
+        "<matplotlib.figure.Figure at 0x7f1ec92b03c8>"
        ]
       }
      ],

12_Designing_Nonlinear_Kalman_Filters/README.md

@@ -1,2 +0,0 @@
-You may read this book online via nbviewer by using this link:
-[*Read Online Now*](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)