Moved legends inside of plot.

The %matplotlib notebook back end does not account for things being
drown outside of the plot, and they end up getting partially or
fully cut off.

01-g-h-filter.ipynb

@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
@@ -289,7 +289,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 54,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -411,7 +411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
@@ -420,7 +420,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 164.9833\n"
+      "Average of measurements is 164.9738\n"
      ]
     }
    ],
@@ -444,7 +444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
@@ -453,7 +453,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 165.0324\n"
+      "Average of measurements is 165.0411\n"
      ]
     }
    ],
@@ -593,7 +593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1446,7 +1446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -2256,7 +2256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -3053,7 +3053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -3862,7 +3862,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
@@ -4790,7 +4790,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -4808,7 +4808,7 @@
        "array([1, 2, 3])"
       ]
      },
-     "execution_count": 62,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4829,7 +4829,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
@@ -4840,7 +4840,7 @@
        "array([4, 5, 6])"
       ]
      },
-     "execution_count": 63,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4852,7 +4852,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
@@ -4883,7 +4883,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -4910,7 +4910,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -4939,7 +4939,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
@@ -4950,7 +4950,7 @@
        "array([1, 4])"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4968,7 +4968,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
@@ -4979,7 +4979,7 @@
        "array([4, 5, 6])"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4997,7 +4997,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
@@ -5042,7 +5042,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false
    },
@@ -5075,7 +5075,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
@@ -5125,7 +5125,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -5145,7 +5145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
@@ -5175,7 +5175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
@@ -5230,7 +5230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
@@ -5250,7 +5250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
@@ -6022,7 +6022,7 @@
     {
      "data": {
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -6092,7 +6092,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false
    },
@@ -6110,7 +6110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -6883,7 +6883,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -6915,7 +6915,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
@@ -7687,7 +7687,7 @@
     {
      "data": {
       "text/html": [
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+       "<img 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       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -7699,10 +7699,10 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1d2732f40b8>]"
+       "[<matplotlib.lines.Line2D at 0x1d647bca5f8>]"
       ]
      },
-     "execution_count": 79,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7728,7 +7728,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
@@ -7746,7 +7746,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
@@ -8518,7 +8518,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -8558,7 +8558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
@@ -8576,7 +8576,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
@@ -9348,7 +9348,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -9390,7 +9390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
@@ -9408,7 +9408,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -10180,7 +10180,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -10234,7 +10234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false
    },
@@ -10252,7 +10252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -11025,7 +11025,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -11049,7 +11049,7 @@
     "    book_plots.plot_filter(data1, label='g=0.1', marker='s')\n",
     "    book_plots.plot_filter(data2, label='g=0.4', marker='v')\n",
     "    book_plots.plot_filter(data3, label='g=0.8', lw=2)\n",
-    "    book_plots.show_legend()\n",
+    "    plt.legend(loc=4)\n",
     "    book_plots.set_limits([20,40], [50, 250])"
    ]
   },
@@ -11062,7 +11062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -11834,7 +11834,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -11849,7 +11849,7 @@
        "(6, 20)"
       ]
      },
-     "execution_count": 88,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -11868,7 +11868,7 @@
     "book_plots.plot_filter(data1, label='g=0.1', marker='s')\n",
     "book_plots.plot_filter(data2, label='g=0.5', marker='v')\n",
     "book_plots.plot_filter(data3, label='g=0.9', lw=2)\n",
-    "book_plots.show_legend()\n",
+    "plt.legend(loc=4)\n",
     "plt.ylim([6, 20])"
    ]
   },
@@ -11883,7 +11883,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
@@ -12655,7 +12655,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -12675,7 +12675,7 @@
     "book_plots.plot_measurements(zs)\n",
     "book_plots.plot_filter(data2, label='g=0.546\\nh=0.205', marker='s')\n",
     "book_plots.plot_filter(data1, label='g=0.302\\nh=0.054', marker='v')\n",
-    "book_plots.show_legend()"
+    "plt.legend(loc=4);"
    ]
   },
   {
@@ -12696,7 +12696,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false
    },
@@ -13468,7 +13468,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -13490,7 +13490,7 @@
     "book_plots.plot_filter(data1, label='dx=0, h=0.05')\n",
     "book_plots.plot_filter(data2, label='dx=2, h=0.05', marker='v')\n",
     "book_plots.plot_filter(data3, label='dx=2, h=0.5',  marker='s')\n",
-    "book_plots.show_legend()"
+    "plt.legend(loc=1);"
    ]
   },
   {
@@ -13510,7 +13510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false
    },
@@ -14325,7 +14325,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false
    },
@@ -15097,7 +15097,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -15114,7 +15114,7 @@
     "plt.figure()\n",
     "book_plots.plot_measurements(zs)\n",
     "book_plots.plot_filter(data, label='filter', lw=2)\n",
-    "book_plots.show_legend()"
+    "plt.legend(loc=1);"
    ]
   },
   {
@@ -15128,7 +15128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -15900,7 +15900,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -15916,7 +15916,7 @@
     "plt.figure()\n",
     "book_plots.plot_measurements(zs)\n",
     "book_plots.plot_filter(data, label='filter', lw=2)\n",
-    "book_plots.show_legend()"
+    "plt.legend(loc=1);"
    ]
   },
   {
@@ -15960,7 +15960,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
@@ -16778,7 +16778,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false
    },
@@ -17550,7 +17550,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -17576,7 +17576,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -18349,7 +18349,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -18377,7 +18377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false
    },
@@ -19149,7 +19149,7 @@
     {
      "data": {
       "text/html": [
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+       "<img 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       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -19177,7 +19177,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false
    },
@@ -19194,7 +19194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
@@ -19966,7 +19966,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img 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truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -19992,7 +19992,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false
    },
@@ -20764,7 +20764,7 @@
     {
      "data": {
       "text/html": [
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truncated
+       "<img src=\"data:image/png;base64,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 truncated
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -20814,7 +20814,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 48,
    "metadata": {
     "collapsed": true
    },
@@ -20835,7 +20835,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false
    },
@@ -20846,7 +20846,7 @@
        "(0.96, 0.24)"
       ]
      },
-     "execution_count": 102,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -20864,7 +20864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false
    },
@@ -20890,7 +20890,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
@@ -20916,7 +20916,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 52,
    "metadata": {
     "collapsed": false
    },
@@ -20945,7 +20945,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 53,
    "metadata": {
     "collapsed": false
    },

code/gh_internal.py

@@ -79,7 +79,7 @@ def plot_g_h_results(measurements, filtered_data,
 
     book_plots.plot_filter(filtered_data, **kwargs)
     book_plots.plot_measurements(measurements, label=z_label)
-    book_plots.show_legend()
+    plt.legend(loc=4)
     plt.title(title)
     plt.gca().set_xlim(left=0,right=len(measurements))