Minor formatting change.

Print number with less precision.

06_Multivariate_Kalman_filter/Multivariate_Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:546c300a4167bd8d99ab1fb7e4797514b2e0824b9845eb68a2349e78cf851afa"
+  "signature": "sha256:c78ca01428b83b821d3b3df8db255bd73fb02c8d8953729cd7545e61506fab30"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -259,13 +259,13 @@
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 1,
+       "prompt_number": 13,
        "text": [
-        "<IPython.core.display.HTML at 0x7f4cf2ee74e0>"
+        "<IPython.core.display.HTML at 0x7f4a614e3fd0>"
        ]
       }
      ],
-     "prompt_number": 1
+     "prompt_number": 13
     },
     {
      "cell_type": "heading",
@@ -393,13 +393,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAADtCAYAAAAcNaZ2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4cf2ed6f28>"
+        "<matplotlib.figure.Figure at 0x7f4a44928940>"
        ]
       }
      ],
-     "prompt_number": 2
+     "prompt_number": 14
     },
     {
      "cell_type": "markdown",
@@ -447,7 +447,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 3
+     "prompt_number": 5
     },
     {
      "cell_type": "markdown",
@@ -469,7 +469,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 4
+     "prompt_number": 7
     },
     {
      "cell_type": "markdown",
@@ -487,7 +487,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 5
+     "prompt_number": 8
     },
     {
      "cell_type": "markdown",
@@ -506,7 +506,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 6
+     "prompt_number": 10
     },
     {
      "cell_type": "markdown",
@@ -519,7 +519,7 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "print(multivariate_gaussian(x, mu, P))"
+      "print('{:.4}'.format(multivariate_gaussian(x, mu, P)))"
      ],
      "language": "python",
      "metadata": {},
@@ -528,11 +528,11 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "0.017439537440741816\n"
+        "0.01744\n"
        ]
       }
      ],
-     "prompt_number": 7
+     "prompt_number": 12
     },
     {
      "cell_type": "markdown",
@@ -870,6 +870,13 @@
      ],
      "prompt_number": 14
     },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## A Visualization"
+     ]
+    },
     {
      "cell_type": "heading",
      "level": 2,