Switched to ggplot style plotting.

01_gh_filter/g-h_filter.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:59d697bb03f25b3d85c02ebd74747fc150ea9b244db398c0be39d839a761ca74"
+  "signature": "sha256:9a9b36cd7ddaddea122ea8a28f164ea9dd83caabcf16ae22f4a6e58f7a9d8c82"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fc76a0444e0>"
+        "<IPython.core.display.HTML at 0x7f8a3abce6d8>"
        ]
       }
      ],
@@ -354,9 +354,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAtwAAAGGCAYAAABIVFZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3WlgVNXBxvH/uZkkQMgQgyBECggIhrihssiiBhWKIApq\n0IpU61Kpy6vSWpVaXIoiSomW4q4VpQoiIm4UpSgiKCJgTYgLKGsMSFgSEpKQuef9MJhKIRogM3du\n8vw+JXcmc5/xmPDk5txzjLXWIiIiIiIiEeF4HUBEREREpC5T4RYRERERiSAVbhERERGRCFLhFhER\nERGJIBVuEREREZEIUuEWEREREYmgQDROMnnyZJYvX04wGGTChAkAZGdnk5+fD0BJSQlJSUmMHz++\n6mu2bNnCzTffTFZWFueee240YoqIiIiI1LqoXOHOzMzkjjvu2OvYTTfdxPjx4xk/fjzdu3ene/fu\nez3+3HPPcdJJJx3QeXJzcw85q3hDY+dvGj//0tj5m8bP3zR+/nWgYxeVwp2enk5SUtJ+H7PWsnjx\nYnr16lV1bMmSJRxxxBG0atXqgM6j/3H9S2Pnbxo//9LY+ZvGz980fv4Vk4X7p+Tl5ZGSkkKLFi0A\nKCsrY/bs2Vx00UUeJxMREREROXSeF+4PP/xwr6vb06dPZ+DAgSQmJqJd50VERETE74yNUqvdvHkz\nDzzwQNVNkwChUIhrr72WBx54gNTUVADGjBnDli1bACgtLcUYw7Bhw+jfv/8+r5mbm7vXJf2srKwI\nvwsRERERkfBF4h9kZGSQkZFR7XOjskpJdT7//HNatWpVVbYB7r777qqPX375ZRo2bLjfsg37f3M/\nrHwi/pKcnExxcbHXMeQgafz8S2Pnbxo/f9P4+VdaWtoBXeiNSuHOzs4mLy+P4uJiRo4cSVZWFpmZ\nmSxatGiv6SQiIiIiInVN1KaURIuucPuTfsv3N42ff2ns/E3j528aP/9KS0s7oOd7ftOkiIiIiEhd\npsItIiIiIhJBKtwiIiIiIhGkwi0iIiIiEkEq3CIiIiIiEaTCLSIiIiISQSrcIiIiIiIRpMItIiIi\nIhJBKtwiIiIiIhGkwi0iIiIiEkEq3CIiIiIiEaTCLSIiIiISQSrcIiIiIiIRpMItIiIiIhJBKtwi\nIiIiIhGkwi0iIiIiEkEq3CIiIiIiEaTCLSIiIiISQSrcIiIiIiIRpMItIiIiIhJBKtwiIiIiIhGk\nwi0iIiIiEkEq3CIiIiIiEaTCLSIiIiK1ylrrdYSYosItIiIiIrXChkK4H76Le+fvsIXfex0nZgS8\nDiAiIiIi/mathWWLcGdNhYIN4WML/oUZMtzjZLFBhVtEREREDoq1FnKX4856AdauCh9s1gIz+FeY\nbn28DRdDVLhFRERE5IDZVStxX30evsoNH2iSihk0DNP7LEwg3ttwMUaFW0RERERqzK7/Nly0P18a\nPpCUjBlwAeaMgZjERG/DxSgVbhERERH5WXZTPva1qdhPPggfSGyAOfs8zNnnYxoleRsuxqlwi4iI\niEi17NbvsW9Mw374LrguBOIxZ5wTvqodTPE6ni+ocIuIiIjIPmzxDuxbM7DvvQWVu8FxMH36hedp\npzbzOp6vqHCLiIiISBW7qxQ7dxb2ndegfBcApmsfzOBLMC1aeZzOn6JWuCdPnszy5csJBoNMmDAB\ngOzsbPLz8wEoKSkhKSmJ8ePH85///Id//vOfVFZWEggEGD58OMcee2y0ooqIiIjUO7aiHDv/Lezb\nM6CkOHzwuFNwzr8U07q9t+F8LmqFOzMzkwEDBjBp0qSqYzfddFPVx1OmTCEpKTzhPhgMctttt5GS\nksL69esZO3Ysjz32WLSiioiIiNQbtrIS++G72Ddegu1bwweP7owzZATm6M7ehqsjola409PT2bx5\n834fs9ayePFixowZA0Dbtm2rHmvVqhUVFRVVV7tFRERE5NBZ18V+8gH2tanwfUH4YOt2OEMug4yT\nMMZ4G7AOiYkGm5eXR0pKCi1atNjnsY8//ph27dqpbIuIiIjUAmstfLYkvDvkxrXhgy2OxDnvUjip\nJ8ZxvA1YB8VEi/3www/p1avXPsfXr1/P1KlTufPOOz1IJSIiIlK32C/+E9605psvwwdSD8ecewnm\n1L6YuDhvw9VhnhfuUCjEkiVLeOCBB/Y6XlhYyEMPPcQNN9xA8+bN9/u1ubm55ObmVn2elZVFcnJy\nRPNKZCQkJGjsfEzj518aO3/T+PlbNMevcvUXlL30NKE9u0OaYAoNzr+UhLMHY+ITopKhrpk+fXrV\nxxkZGWRkZFT7XM8L9+eff06rVq1ITU2tOlZSUsK4ceO49NJL6dixY7Vfu783V1xcHLGsEjnJycka\nOx/T+PmXxs7fNH7+Fo3xs/nrwlNHln8UPtCwEab/UMyZ51LRoCEVZeVQVh7RDHVRcnIyWVlZNX5+\n1Ap3dnY2eXl5FBcXM3LkSLKyssjMzGTRokX7TCeZM2cOBQUFzJgxgxkzZgDwpz/9iWAwGK24IiIi\nIr5lvy/Avv4i9qP3wbqQkIDpey7ml0MxSfqrSLQZa631OkRt+mFdb/EXXaXxN42ff2ns/E3j52+R\nGD+7Yxv2zWnYBXMhVAlxcZg+/TEDszApqT//AlIjaWlpB/R8z6eUiIiIiMihsSU7sf96BTvvdaio\nAGMwPTLDu0M223cVOIkuFW4RERERn7Jlu7DzXsf+61XYVRI+eGIPnPOHY45s7W04qaLCLSIiIuIz\ndvdu7II52DenQ/GO8MH0E3CGXIY5qvoFJ8QbKtwiIiIiPmFDIexH87GzX4St34cPHtUxXLTTT/A2\nnFRLhVtEREQkxlnXheWLcWdNhYIN4YNprXGGDIcTumsb9hinwi0iIiISo6y1kLs8vDvkutXhg81a\nYAb/CtOtD8bR7pB+oMItIiIiEoPsqpXhov3Vnl21m6RiBg3D9D4LE4j3NpwcEBVuERERkRhi138b\nLtp7tmEnKRkz4ALMGQMxiYnehpODosItIiIiEgPspnzsa1Oxn3wQPpDYAHP2eZizz8c0SvI2nBwS\nFW4RERERD9mt32PfmIb98F1wXQgEMGecgxlwISaY4nU8qQUq3CIiIiIecIu2407/B/a9t6ByNzgO\npk8/zMBhmKbNvI4ntUiFW0RERCSCbEU57CyGkmLYWYTdWQzrv6Fo/ptQtgsA07VPeBv2Fq08TiuR\noMItIiIiUgPWWthVCjuL9pTnYmxJUbhM73Vsz+c7i6GkCCoqqn/R407BOf9STOv20XsjEnUq3CIi\nIlLv2FAoXJD3lOTwlef/lmZKisNXoquOFUHpTgiFDvxkgQAkBaFxMjQOhlcdCTYh6fRfsqvVUbX/\n5iTmqHCLiIiIr1VN2dhTju0PV5b3OfajK8+7Sg7uZIkN9y7OP/qYxsl7jgXDx/Z8TmKD/e4EGUhO\nhuLiQ3z34gcq3CIiIhJz7OZ82PTdnikbRT+aA71nykbxnivPPzdlozrGQFLj/155rirKyVXl2ST9\nT3FOSsbEa8MZOXAq3CIiIhJT7Ko83PG3g3Vr9gU/nrKRFL7ibH5UnEkK7lOmaZSkbdElalS4RURE\nJGZY18V96clw2W7dHtPiyL2KM433vRJNYsP9TtkQiRUq3CIiIhIz7KJ5sHYVpDTFufV+TGIDryOJ\nHDLH6wAiIiIiALa0BDtzCgDmwstVtqXOUOEWERGRmGDfnA7FO6BDOqbbaV7HEak1KtwiIiLiOVuw\nETvvdTAG5+KrNSdb6hQVbhEREfGcO/1pCFViep2FadPB6zgitUqFW0RERDxlP/8UPl8KDRpihgz3\nOo5IrVPhFhEREc/Yyt24058CwAy6GBM8zONEIrVPhVtEREQ8Y+e/BQUboXka5sxBXscRiQgVbhER\nEfGELdqOff0lAJxhV2IC2jZd6iYVbhEREfGEnfUC7CqBY0/GHN/V6zgiEaPCLSIiIlFn163GLnwH\n4uJwsq70Oo5IRKlwi4iISFRZa3FffBKsxWQOwrRs5XUkkYhS4RYREZGosksXwqqVkNwEc+4wr+OI\nRJwKt4iIiESNLS/HzngWAHP+cEyjxh4nEok8FW4RERGJGvuvV2DrFmjdDtP7LK/jiERFIBonmTx5\nMsuXLycYDDJhwgQAsrOzyc/PB6CkpISkpCTGjx8PwKuvvsr8+fNxHIcrrriCE044IRoxRUREJIJs\n4ffYOTMBcIZdjXHiPE4kEh1RKdyZmZkMGDCASZMmVR276aabqj6eMmUKSUlJAGzYsIFFixbx17/+\nla1bt3Lvvffy8MMP4zi6GC8iIuJndsazsLsC07UPpmOG13FEoiYqLTY9Pb2qUP8vay2LFy+mV69e\nAHzyySf06tWLQCBA8+bNadGiBatWrYpGTBEREYkQ+1VO+GbJhATMBZd7HUckqjy/bJyXl0dKSgot\nWrQAYNu2bTRt2rTq8aZNm7J161av4omIiMghsm4I96UnATD9L8A0beZxIpHo8rxwf/jhh1VXt6tj\njIlSGhEREaltduE7sP5bSG2G6T/U6zgiUReVOdzVCYVCLFmyhAceeKDqWGpqKoWFhVWfFxYWkpqa\nut+vz83NJTc3t+rzrKwskpOTIxdYIiYhIUFj52MaP//S2PmbH8bPLdlJ8aypADS6bCQJhx/ucaLY\n4Yfxk+pNnz696uOMjAwyMqq/L8HTwv3555/TqlWrvQr1KaecwsMPP8ygQYPYunUrBQUFdOjQYb9f\nv783V1xcHNHMEhnJyckaOx/T+PmXxs7f/DB+7rSnsMU7oGMGZRknUx7jeaPJD+Mn+5ecnExWVlaN\nnx+Vwp2dnU1eXh7FxcWMHDmSrKwsMjMzWbRo0T7TSVq1asWpp57KzTffTFxcHFdeeaWmlILine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751b90a90>"
+        "<matplotlib.figure.Figure at 0x7f8a2273e3c8>"
        ]
       }
      ],
@@ -390,9 +390,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7518df2b0>"
+        "<matplotlib.figure.Figure at 0x7f8a22495f28>"
        ]
       }
      ],
@@ -426,9 +426,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751596160>"
+        "<matplotlib.figure.Figure at 0x7f8a223fbc18>"
        ]
       }
      ],
@@ -465,9 +465,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7518c8da0>"
+        "<matplotlib.figure.Figure at 0x7f8a3abd36a0>"
        ]
       }
      ],
@@ -492,9 +492,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751770c88>"
+        "<matplotlib.figure.Figure at 0x7f8a22322518>"
        ]
       }
      ],
@@ -527,9 +527,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751841208>"
+        "<matplotlib.figure.Figure at 0x7f8a22148f60>"
        ]
       }
      ],
@@ -595,9 +595,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751547748>"
+        "<matplotlib.figure.Figure at 0x7f8a22161c18>"
        ]
       }
      ],
@@ -624,9 +624,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751574b38>"
+        "<matplotlib.figure.Figure at 0x7f8a22215d30>"
        ]
       }
      ],
@@ -696,9 +696,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7518e43c8>"
+        "<matplotlib.figure.Figure at 0x7f8a224a8400>"
        ]
       }
      ],
@@ -761,9 +761,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751679198>"
+        "<matplotlib.figure.Figure at 0x7f8a2222f358>"
        ]
       }
      ],
@@ -874,9 +874,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75183cb38>"
+        "<matplotlib.figure.Figure at 0x7f8a223f5c50>"
        ]
       }
      ],
@@ -953,9 +953,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7518fd3c8>"
+        "<matplotlib.figure.Figure at 0x7f8a22102ef0>"
        ]
       }
      ],
@@ -1009,9 +1009,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7516167f0>"
+        "<matplotlib.figure.Figure at 0x7f8a221c4d30>"
        ]
       }
      ],
@@ -1072,9 +1072,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75178d9e8>"
+        "<matplotlib.figure.Figure at 0x7f8a2218e908>"
        ]
       }
      ],
@@ -1146,9 +1146,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7518411d0>"
+        "<matplotlib.figure.Figure at 0x7f8a2239ecc0>"
        ]
       }
      ],
@@ -1221,25 +1221,25 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751684438>"
+        "<matplotlib.figure.Figure at 0x7f8a221f1128>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75179e6a0>"
+        "<matplotlib.figure.Figure at 0x7f8a224a8828>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751b83b38>"
+        "<matplotlib.figure.Figure at 0x7f8a2231ae80>"
        ]
       }
      ],
@@ -1276,25 +1276,25 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75161f1d0>"
+        "<matplotlib.figure.Figure at 0x7f8a22334c88>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75175b7b8>"
+        "<matplotlib.figure.Figure at 0x7f8a22349828>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751900eb8>"
+        "<matplotlib.figure.Figure at 0x7f8a22334b38>"
        ]
       }
      ],
@@ -1327,17 +1327,17 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7517fb6d8>"
+        "<matplotlib.figure.Figure at 0x7f8a208d1d68>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc75174fb70>"
+        "<matplotlib.figure.Figure at 0x7f8a223143c8>"
        ]
       }
      ],
@@ -1383,29 +1383,29 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7504ae6d8>"
+        "<matplotlib.figure.Figure at 0x7f8a207b7b00>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc7504436d8>"
+        "<matplotlib.figure.Figure at 0x7f8a20841be0>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fc751658588>"
+        "<matplotlib.figure.Figure at 0x7f8a208c7c18>"
        ]
       }
      ],
-     "prompt_number": 26
+     "prompt_number": 25
     },
     {
      "cell_type": "heading",