diff --git a/docs/algorithms/Adjusted.md b/docs/algorithms/Adjusted.md
index 899876bc43a07605182cdc4978ad9e338be3a698..7f13dd5462ebc8ec1c6d7583fb5b3ffc27e87f24 100644
--- a/docs/algorithms/Adjusted.md
+++ b/docs/algorithms/Adjusted.md
@@ -123,6 +123,10 @@ observatories are shown in this
 [Adjusted Example](AdjustedPhaseOneFunction2.ipynb) IPython
 notebook.
 
+There's a [Generation Tool](AdjustedPhase1GenerationTool.ipynb) notebook, for
+generating the tranformation matrices in an automated fashion, with tools for
+adjusting manually and previewing the effect on delta F,  etc.
+
 
 ## References
 
diff --git a/docs/algorithms/AdjustedPhase1GenerationTool.ipynb b/docs/algorithms/AdjustedPhase1GenerationTool.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b3aa93083852bff18cd9701dab254f8dcfebe1bc
--- /dev/null
+++ b/docs/algorithms/AdjustedPhase1GenerationTool.ipynb
@@ -0,0 +1,802 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Adjusted Phase 1  Generation Tool\n",
+    "Below are packages imported during development, most of which are used below\n",
+    "Read through the worksheet, and enter any values in the cells headed 'Enter' below.  Then click 'Cell' in the menu above, and 'Run All.'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "\n",
+    "import matplotlib as mp\n",
+    "\n",
+    "import pandas as pd\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "import scipy as sp\n",
+    "\n",
+    "import scipy.linalg as spl\n",
+    "\n",
+    "import glob\n",
+    "\n",
+    "import json\n",
+    "\n",
+    "import urllib2\n",
+    "\n",
+    "from datetime import datetime \n",
+    "\n",
+    "import matplotlib.pyplot as pl\n",
+    "\n",
+    "import re\n",
+    "\n",
+    "import obspy\n",
+    "\n",
+    "from obspy.core import UTCDateTime\n",
+    "\n",
+    "import geomagio\n",
+    "\n",
+    "from geomagio.edge import EdgeFactory\n",
+    "\n",
+    "#from geomagio.Algorithm import DeltaFAlgorithm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example url for baseline web service"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "https://geohazards.usgs.gov/baselines/observation.json.php?observatory=BOU&starttime=2016-01-01&endtime=2016-10-07"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Enter the Observatory in the cell below as a string, similar to the following example:\n",
+    "\n",
+    "```python\n",
+    "obs_code = 'BOU'\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "obs_code = 'BOU'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Enter the start date and end date for which you'd like to request baseline measurements\n",
+    "If you choose a year's worth, that will result in the mean delta F for adjusted data being closest to 0, but will amplify the daily variation.  If you choose a shorter time period closer to the present, the daily variation will remain small, but the mean delta F will be biased by seasonal variation.  If the baseline service is called without dates, it will return the last one month's baseline measurements."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "start_date = '2015-10-10'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "end_date = '2016-10-09'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "baseline_url = 'https://geohazards.usgs.gov/baselines/observation.json.php'\n",
+    "full_url = baseline_url + '?observatory=' + obs_code + '&starttime=' + start_date + '&endtime=' + end_date\n",
+    "response = urllib2.urlopen(full_url)\n",
+    "parsed_response = json.load(response)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-22.0"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_abs = []\n",
+    "d_abs = []\n",
+    "z_abs = []\n",
+    "h_ord = []\n",
+    "d_ord = []\n",
+    "z_ord = []\n",
+    "h_t = []\n",
+    "d_t = []\n",
+    "z_t = []\n",
+    "\n",
+    "for datum in parsed_response['data']:\n",
+    "    for reading in datum['readings']:\n",
+    "        if (reading['H']['absolute'] is not None\n",
+    "           and reading['D']['absolute'] is not None\n",
+    "           and reading['Z']['absolute'] is not None\n",
+    "           and reading['H']['baseline'] is not None\n",
+    "           and reading['D']['baseline'] is not None\n",
+    "           and reading['Z']['baseline'] is not None\n",
+    "           and reading['H']['valid'] is True\n",
+    "           and reading['D']['valid'] is True\n",
+    "           and reading['Z']['valid'] is True):\n",
+    "            h_abs.append(reading['H']['absolute'])\n",
+    "            d_abs.append(reading['D']['absolute'])\n",
+    "            z_abs.append(reading['Z']['absolute'])\n",
+    "            h_ord.append(reading['H']['absolute'] - reading['H']['baseline'])\n",
+    "            d_ord.append(reading['D']['absolute'] - reading['D']['baseline'])\n",
+    "            z_ord.append(reading['Z']['absolute'] - reading['Z']['baseline'])\n",
+    "            h_t.append(reading['H']['end'])\n",
+    "            d_t.append(reading['D']['end'])\n",
+    "            z_t.append(reading['Z']['end'])\n",
+    "            \n",
+    "last_datum = parsed_response['data'][1]\n",
+    "pier_correction = float(last_datum['pier']['correction'])\n",
+    "pier_correction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot of H absolutes, ordinates, baselines\n",
+    "Absolutes are in the top plot below, in blue.  These represent the field, as measured by the overhauser (with the pier correction applied), with direction measured by the theodolite.  Ordinates are also in the top plot, in green.  They represent the variometer's reading of the field corresponding to the times absolute measurements are taken.  Baselines, or the difference between the two are in the bottom plot, in blue.  Vertical axis units are nanoteslas.  Horizontal axis units are unix timestamp (seconds since Jan 1, 1970)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x4126b240>]"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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EXIkRuxzV1qsislj0UmB/5zpnJToxIhRIjGgpL/nWTS8HflP+MMbGzh2dI1mI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\nNbBkSbTOfO1aPdsZHISGBnjoITjuuPz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RSulXKQnuCl0jqNw4kzGGqaNNIZ4czP9h7B1j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\nQJvwAKDtBxep0jqhjxjVAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x3e099438>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.subplot(2,1,1)\n",
+    "pl.plot(h_t,h_abs,'.',h_t,h_ord,'.')\n",
+    "pl.subplot(2,1,2)\n",
+    "pl.plot(h_t,np.asarray(h_abs) - np.asarray(h_ord),'.')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot of D absolutes, ordinates, baselines\n",
+    "Absolutes are in the top plot below, in blue.  These represent the declination angle of the field, as measured by the overhauser (with the pier correction applied), with direction measured by the theodolite.  Ordinates are also in the top plot, in green.  They represent the declination (from the sensor's H axis) calculated from the variometer's reading of the field corresponding to the times absolute measurements are taken.  Baselines, or the difference between the two are in the bottom plot, in blue.  Vertical axis units are degrees.  Horizontal axis units are unix timestamp (seconds since Jan 1, 1970)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x42a48dd8>]"
+      ]
+     },
+     "execution_count": 116,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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islhEXhWRTd52dmlvzTCS09kJ06bBqae6387OSktkGOmj3N5q8517o7rV4VNV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\nGIaRCDMYhmEYRiLMYBiGYRiJ+P+ixjOXIsDsWQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x429a2668>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.subplot(2,1,1)\n",
+    "pl.plot(d_t,d_abs,'.',d_t,d_ord,'.')\n",
+    "pl.subplot(2,1,2)\n",
+    "pl.plot(d_t,np.asarray(d_abs) - np.asarray(d_ord),'.')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot of Z absolutes, ordinates, baselines\n",
+    "Absolutes are in the top plot below, in blue. These represent the field, as measured by the overhauser (with the pier correction applied), with direction measured by the theodolite. Ordinates are also in the top plot, in green. They represent the variometer's reading of the field corresponding to the times absolute measurements are taken. Baselines, or the difference between the two are in the bottom plot, in blue. Vertical axis units are nanoteslas. Horizontal axis units are unix timestamp (seconds since Jan 1, 1970)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x42e27c50>]"
+      ]
+     },
+     "execution_count": 117,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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RPQXptjIMwzCMMOY8DMMwjKwx52EYhmFkTcbOQ0RKROR1Ean2zqeLyBJve1dElnjpZ3r5\nlnj7ZhHZ17s2VETeFJE6EbkzUHa5V94qEVkoIj1z/aCGYRhG7sim5XE5TugQAFU9XVWHqOoQ4Elg\nhpf+Z1U9wEsfD6xW1Te92+4FzlfVSqBSRI720s8H1qtqP+BO4JateirDMAwjr2TkPERkT2As8ECK\nLN8nMWQX3Ozz6V4ZuwEVqvqqd+1h4ETv+ATgj97xEzhpE8MwDCOiZNry+C3wEyAhTtbTtvpQVd9J\ncl9wHsgewPuBa+97af619wBUtRn4TES6Z2ibYRiGsY1p1XkEta1wmlOtaVv59w0H/qOqy9tgV07j\nkQ3DMIzckskM84OA40VkLJ62lYg8HNC2Ohm3yFOY04l3KvXAXoHzPb204LUGr8ztw4q6PiaMaBiG\nkZ5ICCPGZRY5jIAku4iMAa5R1cND+QTXDXWwqq4JpL8CXAa8CjwLTFbVWSIyAahS1QmeYOKJqpog\nUWIzzA3DMLKnIJLsrZBM2wrgUGBd0HF4mLaVYRhGO8C0rQzDMNo5pm1lGIZhRAJzHoZhGEbWmPMw\nDMMwssach2EYhpE1ORdG9K7tKyILRGSpiPxLRMq99CEmjGgYhlH85FwY0Zvk9whwkapWAaOBr73b\n7sOEEQ3DMIqefAgjfhf4l6ouBVDVDaqqJoxoGIbRfsiHMGKllz5LRF4TkZ946SaMaBiG0U5odYZ5\nUBhRREbTujBiGU4PaxjwFfAPEXkNaMzCrpSTWUzbyjAMIz2R0LYSkV8BZwOb8YQRgRkBYcR6YIiq\nNnj5TwPGqOoPvPPrgP8FpgFzVXWgl346cJiqXiIis4BJqrrIK/MDVd01iS02w9wwDCNLCjLDXFWv\nVdWeqtoXpzn1gqqe410+CljhOw6P2cC3RaSLiJQBhwHLVPVD4HMRGe4JJ54DPO3dUw2c6x2fCryw\n1U9mGIZh5I2cCyOq6mcicgfwGrAFeDYggGjCiIZhGO0AE0Y0DMNo55gwomEYhhEJzHkYhmEYWWPO\nwzAMw8gacx6GYRhG1uRcGFFEeonIl4Fr9wbKMGFEwzCMdkA2obq+MOL24IQR/QsichvwWSDv255g\nYhhfGPFVEZkpIker6mwCwojeJMNbsHBdwzCMyJIPYURIIi9iwoiGYRjth3wIIwL09rqs5orIwV6a\nCSMahmG0E/IhjNgA9FTVDSIyBPiriAzK0i4TRjQMw2gjRSmMmOT+ucBVOKdiwoiGYRjbmKIQRhSR\nXUSkxDvuC+wDrDZhRMMwjPZDzoURgUOBm0RkE04Y8WJV9SOxTBjRMAyjHWDCiIZhGO0cE0Y0DMMw\nIoE5D8MwDCNrzHkYhmEYWZNzbatA/p4i0iQiPw6kmbaVYRhGOyCbloevbQU4bStVHeJpWD0JzAjl\nvx2YGUrzta0qgUoROdpLb9G2Au7EaVsZhmEYESUv2lYicgKwmoCzMW0rwzCM9kPOta1EZDvgauBG\n4mVGTNvKMAyjndCq8whqW+GcQWvaVjcAv1XVL7fCrpzGIxuGYRi5JZMZ5gcBx4vIWDxtKxF5OKBt\ndTIQXLtjBDBORG4BdgKaReQr3JjIXoF8e+J0sfD2ewENXpnbq+r6ZMZEWRixobGBZ1Y9w3H9jqPH\n9j0KbY5hGB2USAgjxmUWOQy4SlWP987HANeo6uEp8k8CmlT1Du/8FeAy4FXgWWCyqs4SkQlAlapO\n8AQTTwwuNhUoL7IzzGevms3Yv4xli26hc2lnVl+2usWBLGlYwh2v3MGPR/6YIT2SrZFlGIaRP6I4\nwzyZtlU6LsXpWNUBq0LaVrt42lZXABO30q5typKGJYz58xi26BYANjZv5MkVTwLOqQydMpRpb01j\n6JShLGlYkrKcuk/quGbONdR9Upc2zTAMo9CYtlUOOHvG2Ux7a1pcWvXp1exRsQdDpwyNSx83cBxT\nT5jKovpFAIzYYwQAz656ljOfPBNFEYSVl64EoP89/VvunX/ufFZ8uoJhuw/jtQ9e47h+xwEkdJXV\nfVLHg288yPn7n0/lLpX5eWjDMIqGfLQ8zHnkgCUNS+KcRJ8d+zDrrFkMvm8wm7dsjsv7k//zE/7+\n9t9Z+vFSAAbuPJDSklKWfbwMDQSzTTx4IvWN9Tzy5iMtaSVS0tK6ASgvKQdg05ZNlJeU8/ipj7Pn\n9nsybMqwlrJuGn0T5x9wPl9s+iJjh1L3SR13LrqT3bvtzvkHnG/jN4ZR5JjziKjzAOdAbl1wK2P2\nHsPJg07mL0v/wsXPXByXp5RSZpw2g5MfO5lmbXZpUoqIxDkZv+Xxf5//v/yt7m8Z2yAIO3bekQ0b\nN8Sld5JObNbNca2asAPxWyvf6fUdxvx5TEt6ePxma2ja2MTSj5ZStWsVFZ0rtro8wzAyw5xHhJ1H\nmIbGBva+e2++2vwVJZRw7cHXcsmBl1DRuYJRD45KaHnUflpLnx37cGzlsfz30P+mcpfKhBZNeWk5\nm5o3tZyXSRmbdXPCZ7fGxIMn8usjft1yXvdJHQPuGRDX8gky5XtTOLTnoQmtkWSBAH6rpXuX7gzf\nYziH9zmcis4VNG1sYuQDI1n56UoG7DyAVy54xRyIYWwjzHkUkfMA50Bmvj2TsfuMjfvl3rSxicX1\niwEYvsdwAJZ9vIzB3xyc8EJd0rCEOxfdyRUjrmC3brsx8+2ZDNltCEs+XMKhPQ/lpEdPYvkny+Pu\n2aXrLnzy5ScIgqKttjyumXMNt7ycXBGmc2lnnj/7eQ7946FxaU+f9nRcC6Xmwhq6lXeLG6MB6N+9\nP69e9Cpz353LCY+e0JI+fdx0eu7Qk86lnXl0+aNx3WmZRqdFuSUTZduMjkdBnYe3tGwN8J6qHi8i\n0wH/DbQTsEFVh4jIgcD9gVtvVNW/emUMIX4lwSu89HKcXMlQ4BPgNFVdl8SGonIe24KmjU3MWzOP\nUx47hU1bNtG5tDNv/vebrP9qPd27dGf+uvmM3WcsX2z6gqn/msoP9vtB0i4rv+UhCH8/8+/8bdXf\n2G273fivA/6LuxbfleBcRvQYwaKGRS3n4/cdz+4Vuyd1QnPGz2HZx8u4fNblLWm7brcrH/3no5Zz\n36l9semLuNZWzYU1DOkxJG4ODcATK55g8qLJvLvhXSp3ruTp059m3tp5cYED2c67ydUL31pZRtQo\ntPO4Evdy396f5xG4dhvwmar+QkS6AJtUdYunZ/UvYHfvfBHwQ1V9VURmAnep6mwRuQT4tjfP4zTg\npGKb51FoUrVyMqXuk7q0ziXYosim5QHOeQzcZSB9J/dlY/NGSimlmeaEfBMPnsh7n78XF7k2ft/x\n/OaI37R0AZaXlCMibGzeGHdvWUkZm7dsppRSThhwAhcNuYgTHj2Bjc0b48Zt/FbNuAHjeKXhlZYW\nT9PGJkZMGUHtp7X037k/c86Zw9rP1yY4kkwi2apXVse1sqpPr+Z7/b+Xquq3GmvlGK1RMOfhCSNO\nBX4J/DiJ81gHHO7rWwXS+wALcNpVuwIvqOog79rpwGGqeomIzAImqeoib4b5h6r6zSR2mPMoEHWf\n1DF58eSW1oj/Iva71IJjHrctvI2nVz7N+q/WM2DnASw4fwEVnStaHNyi9xfxwOvxGpupWh7TTpzG\nXYvvYnHD4q2y/+5j7mbUnqMSQqf9ltbva37PU7VPtaTvUbEHHzR9QOXOlUw7eRqPLn+U7/T6Dsf8\n+ZiWsaFTB57KL77zixYn4r/E57wzh+tfvL6lrFuOvIWfHPSTpHYlax09tfwpfjb3Z/zy8F9y0qCT\n0j5X08YmRj04qqWV8+T3n0xogRlGIZ3H4zjHsQOBGebetUOA21V1eCBtOPAQ0BMYr6pPi8hQ4Neq\n+l0vz8HA1V4X2FvA0ara4F1bBYwIS5SY8ygemjY2pRzHCbdkLjrgIq4adVXcmMedi+5kTN8xnPXX\ns+LuTdXyaI1xA8axacumrKLXMuWm0Tdx2uDTOOnRk1j56Up6dOvB+00xDVC/5eE7l52/sTPz1s5j\n2O7DGPXQqLjW0aL3F3Hy4ye33Dvj1BlpHcic1XM46pGjWs7LS8rZtGUTXcq68M6P3mnVgQRbLR80\nfZDQqrJWTfsgH86jVW2roDCiiIymdWFEVHUxUCUi/YGHReTvWdqV8iGjrG1lxKjoXMHIPUcmvVa5\nSyW1l9am7CYb0mMID5/0MGfPODsufeQeI3ny+27m/sy3Z9K/e39mvjOTsXuP5chHjmTTlk1x+fvs\n2Id3P3sXgCdXPpmx7X6gQaZcP+96bnrxppbIt/eb3mfP7fekobGB3jv25oV3X2CPij0Y/9R4ln+y\nvKX8YPfdxuaNnPPUOazesDqu7AnPTmDEniP48IsP44II/BbL9uXbx+X36+CrzV8x8+2ZXDDkgpR2\nB7vqeu/Ym3c/exdFueXlW7jggAu4ZNglnD3j7JauvEUXLkrrQLKZnGpOKb9EQttKRH4FnA1sxhNG\nBGYEhBHrgSF+qyHJ/f/Aybk3AHNVdaCXnq7b6gNV3TVJWdby6ECEQ5X9wfNk+F1ie1XsxbSl07hi\nxBX027kfE56dwJ/e+lNLvnP3O5ctuoWT+p/E4g8WM7rn6LiuqJ+P/jmH9TosLrrMf9kLwpRjp3DB\ns6lfyD63HnUre22/F2c8eUZWjigZZZSxmVhI9qwzZ3HiYyfy1eav6Fzamd479ObtDW+z9057s/bz\ntWxs3kgn6cSFQy/k8hGXpx6bqa3mhOknJL2WNH+oBdVrh14t40JvfPBGXJ3VXlqb8nP9rrYVn6xg\n4C4DmX327KTjS0buKHiobibCiCLSGxeR1SwivYCXgX1VdX17FkY08kOycZVsCEeSpZogGW4FBdOA\nuOtPLX8qrmsJ4mf7+11QyaLUwuy5/Z683/h+XNr2nban8evGlPcM2mVQXHj23cfczbAewxj8zcE0\nbWzioTce4vq516d9ZoDLZ17O5Fcnp7UvyOQxkzlv//MYdv8w6tbX0Uk60azN9N2pL+9seCfOSZ5Z\ndSbTxrnAh3Dodbirref2PXm/8f2krZvwmFDTxqY4aR9zNpkRRecxFVioqvcH8pyNEzbcBGzBher+\nzbs2lPhQ3cu99M7AI8ABwKfA6aq6Jsnnm/MwsiZdJFlb8Z3aWVVn8V7Te4zdZyxAXMRbePKlPx4B\nUEJJS1TXS+teammhCMJrF75GfVM9pz5+KhubNya0PCDWGko2tnHlrCu5c9GdsfORV3LH0Xe01MWD\nbzzIft/cL248qVNJJ/4x/h888tYjPLDkgZjN3sRU3yHOXzefM548I6M6qrmwBiCh9fh+4/tx0WhB\nxg0Yx6+O+BWVu1TS0NjQEqHnh6CfOP1EVny6AoDK7pW8dtFrgNOGW/T+Ii4ZdomN1ySh4M6j0Jjz\nMIqNoOPqVt6NmW/P5NCeh7L+q/VxwQTJHFww/PrDLz7kqueuYt7aeS1lX3rgpVx78LUJg+LTl06P\ne8FPHzed06pOS6skMLrXaOaeNzelzb5DDDsmn1IpbZHc8Tm+3/Gs2rCKFZ+saEk7ffDpvP7B69Su\nr01bb7WX1jLrnVlxc4MuPfBS7nn1nvhnHTeda/9xLas/c2NFfktr94rdGXb/MFatX0W/7v144HsP\n8Pslv08I0U5FMscTbEF1K+/WMr7Trbwbz6x6hl7b9+KRtx6J5NIL5jzMeRgdmMmLJse9TO8+5m5+\nOPyHCfmaNjYx7P5hvL3+bfbpvg+vXfQaFZ0r0ioJzD93Pof0PqRVG1I5oKnHT2X5x8u5deGtae+/\n46g7+PHzP271c87d71waNzby1MpY+PRNo2/i+nnXx+W78IALmfL6lIR7x+wzptUWkj8uEx7oD8/5\nWXThIlZ9uiohzNunc2nnhOi/aSdOY+Y7MyPjSMx5mPMwOjDhbpx0gpXJQqXD4z9/OvFPPPLWI1x7\n8LUZOQ6fuk/q+J+a/6G6tpo1n62hsntly1iF351XQgl/fPOPLfcM/uZgHj7xYf753j/jHKDPMfsc\nw9/fTh6UWSIlDNh5AM+Pf57D/3g4devd2jadSzvzs0N+luBQAM4cfCZ/XvbntM9x6YGXctnwyxLG\nxFZ+ujIukGDq8VO577X72jzXKF2gx7bCnIc5D6ODk08lgWxpbS5PskCFoAMEpwwwYOcBzD57Nkc8\nfAR16+v2HIwpAAAgAElEQVTYsXxH1m+MTfEav+947hl7T4vA5rw181jz2RrGDRwHEFeez/H9judv\nq/6WNtLt56N/TtPXTXGtsYkHT2T3brvHOThfvSAVyVoeQcbvO56HT3o45fVtgTkPcx6GUTSkclS+\nAwyP/fjOqLykvGVNmnTRYsHy7nvtPn7x0i9a0ny5HP/zv9j0Bb966VdU11Xz9ZavW1puX2z6IsHJ\ndSvvFpPSCY3ljNxjJPeMvSeubH9cyA8TD09uba8tD1Q1ow23ZO3rQLV3Ph1Y4m3vAku89COB13Ca\nVq/iZEv8MoYAb+KWob0zkF7ulbcKWAj0TGGDFgNz584ttAkZYXbmjmKwUbV47Hz4rw/rxDkTtfbj\n2ozvqamv0fEzxmtNfU3KPPWf1+uUmila/3l9S1rtx7UJn+Xnq6mv0S6/6KLcgHb5RZe4+1RT12cm\ntmxLvHdnxu/7TLZsnMeVwJ985xG6dhtwnXe8H7CbdzwYeD+QbxFwoHc8EydJAnAJcK93fBowPYUN\neajW3DNp0qRCm5ARZmfuKAYbVc3OtpDM4fhEyc505MN5lGTSOvGEEccCD6TI8n08iRJV/Zeqfugd\nLwO6iEgnT2G3QlVf9e55GDjROz4B8EfXngCOyMQuwzCMfNNj+x5cMOQCE5oMkZHzAH6LkxhJGHDw\nhBE/1JCirnftFFx31tc4Zd3gVNr3vTS8/XsAqtoMfCYi3TN9CMMwDGMb01rTBDgW+J13PBr4W+j6\nvcCVSe4bjBvD6O2dDwWeC1w/mNj4yVtAj8C1t4HuScpU22yzzTbbst9y3W3VqqoucBBwvIiMxRNG\nFJGHNSaMeDJuILwFr5trBk6OfY2XXA/sFci2p5cWvNbglbm9huTYcU+f22gBwzAMo0202m2lqteq\nak9V7QucjlvQ6Rzv8lHACg0o6orIDsAzOMHEVwLlfAh8LiLDRUSAc4CnvcvVwLne8anAC1v5XIZh\nGEYeyXTMIxWnEVrLA/ghsDdwvYi8LiJLRGQX79qlwIO4UN1VqjrLS38Q2MVbBOoKnLCiYRiGEVGK\napKgYRiGEQ22tuXRZkTkQRH5t4i82Uq+A0XkaxE5OZRe4rVqqgNpO4nIcyJSKyKzvS60KNo5SUTe\n99KXeOuiFMxOEVkjIv/yWoqLA+k5rc882Ri1utxBRB4XkRUiskxERnjpkfpuprEzMvUpIpWB3ovX\nReRzEbnMuxaZ+mzFzsjUp5d2pYgsFZE3RWSaiJR76VnXZ8GcBzAVODpdBhEpAX4DzE5y+XJgeSht\nIjBHVfvjxk1+GlE7Ae5Q1SHeNivJ9WzZGju3AKNV9QANrEVP7uszHzZCtOryLtxaNQNxE2Z9PfKo\nfTdT2QkRqU9VrfP+3kNw0Zr/wQXiQITqsxU7ISL1KSI9gB/hVn7dF7cMub/oXtb1WTDnoar/BDa0\nku1HuEmDHwUTJfWkxeBkwz8Sm4QYNTshzTrtbWFr7PRsSfZdyGl95slG/1rOaKudIrI9cIiqTvXK\n2ayq/pKAkflutmInRKQ+QxwJvKOq/lyxyNRnK3ZCtOqzFNhORMqArsQiXrOuz0K2PNLieckTVfU+\nEis/1aTFXVX139AS3ZWwDnpE7AT4oYi8ISIP5KLJvZV2KvC8iLwqIhcG0rdpfbbRRohOXfYBPhGR\nqV4Xxf0i8g3vWpS+m+nshOjUZ5BwcE6U6jNI0iCiKNSnFxV7O7AO5zQ+U9V/eJezrs/IOg/gTuCa\ncKKIHAv8W1XfwFVMOq++LaIB2mLnvUBfVd0f+BC4owB2Bu05yGtyjwUuFZGDU5SR7/psi41RqEuf\nMtycp3s8W78kFjmYzBnmm7bYGYX6jKsrEekEHA88nqaMQtRnJnZGpj5FZEdcC6MX0APoJiJnpiij\n9frM9azDbDbvId5McW21t70LNOEq/njgVzjPuRr4APgCeNi7ZwXwLe94N9wclMjZmWnZ28LOJPkm\nAT/OV33m2sYo1SXwLWB1IN/BeIoMEftuprQzSvUZuH48MCt0T2TqM52dUapP4BRgSiDfeGLqIVnX\nZ6FbHilbDqra19v64PruJqhqtaaftFgNnOcdn0tsEmKk7BQnEulzMrC0UHaKSFcR6ebZtR3w3YA9\n+ajPnNoYpbpU1+x/T0T8xSeOIBYsEaXvZko7o1SfgSxnkNgVFJn6TGdnxOpzHTBSRLqIiOD+7n6g\nRNb1mYk8SV4QkT/jtLJ2FpF1uF+T5TgNlvtD2TNtkt4MPCYi/wWsxan9RtHOW0Rkf1wE0Rrg4gLa\n+S3gKRFR3Pdhmqo+513LaX3mycYo1SXAZcA0rwtjNfADLz1q381UdkaqPkWkK24Q+qJQvkjVZxo7\nI1OfqrpYRJ7Arcv0tbf382ddnzZJ0DAMw8iaQndbGYZhGEWIOQ/DMAwja/LmPCSJnISI7CciC7z0\npwODoEeKyGte+qsicni+7DIMwzC2nryNeYjIamCoqm4IpC3GhVj+U0TOw8U/Xy8i++HmRHwoIoOB\n2aq6Z14MMwzDMLaafHZbJZOT6Kduaj3AHGAcgKZY9zyPthmGYUQeyVAE0cvbU0TmeD04L3gzzfNG\nPp1HUE7iAi9tmYgc7x1/H7eaYBwSv+65YRhGR6ZVEcQAtwF/UNX9gJtwwoh5I5/dVrur6gci8k3g\nedwiUR8BdwPdcZNSLlPVbwbuGQz8FThKY8vXBsu0uGLDMIw2oDlexjtvLQ9V/cDbfww8BQxXJ118\ntKoeCEwH3vHzS/J1z5OVG/lt0qRJBbfB7DQbzU6z09/yQV6cRyo5Ca8V4mvNXwf8j3e+I0nWPTcM\nwzCiSb5aHt8C/ikirwOv4ETXngPOEJFanI5Ovar+wct/KanXPTcMwzAiRl60rVT1XWD/JOmTgclJ\n0n8J/DIfthSC0aNHF9qEjDA7c0cx2AhmZ64pFjvzQVFpW4mIFpO9hmEYUUBE0GIZMDcMwzDaL+Y8\nDMMwjKwx52HklKYmWLjQ7Q3DaL+Y8zByRlMTHHIIHHqo25sDMYz2S1RUdbt7WixNIpIQjWUUB0uX\nwrJlsHkzLF/ujg3DaJ/ks+WxBRitqgeo6nAvbQpwtTrtlaeAq730r3CTBq/Koz1GnunVC8q84O/S\nUujZs7D2GIaRP6Kiqvulqi4ANubRHiPPrF0LX3tylps3w7p1hbXHMIz8ETlVXaN4qapyW6dOMHiw\n2wzDaJ/kZYa5x0EaUNUVkZXAfwF3i8j/w6nqbsrj5xvbmIoKmDkTnn0Wjj3WnRuG0T7Jm/PQgKqu\niPiqunfgadOLSD/g2GzLveGGG1qOR48e3aHlAQpNU5MbJK+qco6iqQnGjnUD5YMHw0svmQMxjEIw\nb9485s2bl9fPyIs8iYh0BUpU9QtPVfc54Ebgdc+ZlOAWOZkbEEdERM4Fhqnqj1KUa/IkEcEPyw06\niqVLXZju5s2u62r+fBg5stCWGoZRTPIk2arqIiLvArcD54rIOhEZkCfbjByQLCy3qso5krIyF3ll\n0VaG0X4xYUSjTTQ0wN57w1dfQZcu8M470KOHSz/sMHj3XejTB1580aVDYjfX1pLr8gyjvVJMLQ+j\nnZMqLHftWuc4mpvh7bedI2lqSj37PJmcSSYSJ01NMGqUK2vUKJvNbhjbGnMeRptIFZZbVeW6rHzW\nrnVdWsm6uXwHcOihMQeQqcTJokWuzOZmt1+8OP/PbBhGjHyG6hrtmIoKN0juD5gHu43KAt+qkhI3\n9lFRAQMGwIoV0L+/u8d3ABBzAF27JjoZG3Q3jOhhLQ+jzTQ1wZtvxrcOli514x8+wS6t5ub4fTIy\nlTgZMcK1csrK3H748OT5DMPID+Y8jIwJjkX4A+YXX+z2DQ0uT1UVDBwYu2fgwFgrY8UK5zhWrAA/\nBH3gQOckfAeQqcRJRQUsWOBaPwsWuDSTgjeMbYc5DyMjwmMRTzzhIq3A7WfOdMf+S33OHLctWJA8\nEuqyy+CYY9zx7NmxfNmIK1ZUxLq0fNtGjXKfa07EMPJLJCTZvWs/FZFVIrJCRL6bL7uMthEe8O7T\nx4XogtuPHRvLW1EBRxzhNt9xBLuZevWCNWtcWStWxO4BV/ZGTx5z48bY9SDhaKylS922ebPbH3OM\nrSdiGPkmEpLsIjIIJ5Q4EDgGuFdEchqTbGROQwPcf3+sKwoSWwRDh7qxjSlTYnM80hHsZvrNb+Kv\nLVmS+Ys+2ALyWxmdO8OWLbE8tp6IYeSfvE0S9GaMD1PVTwNpG1R1J+94T2C2qg4WkYmAqurN3rW/\nAzeo6qJQmTZJMM+kmvy3cKF7aTc3Oyfy0kttj4KaMweOOip27o95vPSSOx81ClaudNFZs2e7cZBe\nvdz+P/9xLYvNm2P3futb8Y6upAQGDUrdZWYYHY1imySYjST7HsB7gXvrvTSjDbRlHfG6OrjmGnjw\nweRjGbmUWx80yLUWfJqbYy2FYAtl9mw4/HA46CDo29e1Nq680jmVkpLYvUHHESwzW2z9dcPInKKT\nZDdV3fQkEyxs7dd3XZ17IfuNOpHYcf/+bp9uXke2rF0b/3IvK3MOxXdI/kD49OnONoiNg6xcCbNm\nOWdz2WWxMkpLY2Vu2eLGShYvduMurcmYNDW5aLAf/tDNiq+sdOfWajGKlW2hqouq5n0DJgE/DqX1\nA17xjicC1wSuzQJGJClHjfQsWKBaWqoKqmVlqgsXtn7P1Ve7/Mm28nLV+vrc2tjYqLrffqqdOqlW\nVanOmePSwlxxRaI9Xbqo1taqPv+86qBB7hkHDnTllJTE562ujn1WWZnbhz/Hvy6SeK9htBe8d2dO\n3+t56bYSka5+JJUnyf5dYKnXCsGTZL8O+B/vlmrgdBEpF5E+wD6ACU60gVShrum6ZM4/37U2fHbb\nLXa8aZPruspll47fipk/33VRBaOyglxySbxd4MY6jj3WjXuUlLhWyKJFrpw774zP27VrclmUIP71\n8FDamjVb/ZiG0a6JhCS7qi4HHvPSZwITPG9pZEmyUNfW9KIqK1130MSJUFvrlHDLy921Ll1i97Wm\nN5UNftdUuq4h3y5/nKNTJ+jdOxbmW1sL223nyqiogPPOS5x1XlXl7i0ri8miBPGvlwT+Ezp3hqOP\ntvEPw0hLrpsy+dywbqtWefrpxO6XBQtctw24rqJMurLq61WnTHH7ttyfaxob3efW18e6vFJ1Qy1c\n6PaNja57a+BA15VXVZU8v399n31UJ0923WLpuroMo9ggD91Wtp5HkRMeDA6Hwc6Z436BB8Nfsw1h\n9dVv23p/rmlqan3g3rfZl0QB1/qYMQM++ACOO86FICerr65dbUVEo32Rj1BdU9UtYpJFVvkzuVes\ncLpRvmBgc7OLQmpLCKtPVPx2UJYkFUHFXp+SEjj1VNed17kzrF6d/F6/K2vlyuRdXYZhmLZVURMc\nDF62zIW2gmsZ/POfbp7E0qUwd65zJsEQ1mw/Z+VK53hqa4t35vbXX8ePB912mwsRrqqKF2f08zY3\nx0QaDcOIx5xHEROMrGpuhgkTXEsE3K/lsWNjE+ty9TmtiRVGBb8FVlLiWhmdOsUvUgVw111uYHz2\nbOds/e64uXOdk1R1+3yHyxtGMWLdVkXM2rUulBbciy4Yjqoaa5WsW+dmaK9b57pjsl37IplMemta\nVoWmosI5hWefdUvhrl8P3bvDt78dq7MtW1yrasUKFy7sEw7TXbt2m5ltGEXDtlbV3V9EFvppIjLM\nS+8kIg+JyJvetcPyZVd7olevWEitiPt17c/Urqpye19O5KWXYmtfZDvYnUtpkm1FU5NreU2YAN//\nvrP500+Tj/l8+WX8+SmnxORTOneGk0/Ov72GUWzks+Xhq+puCKTdDExS1edE5BjgVuBw4EJcKNm+\n3kTCvwPD8mhb0ZBOWmPt2phAYEkJXHUV/OhHsXxhOZG2thZyKU2yrUg2OdB3gv7a5z5du8bf26OH\nG0yfOdM5oKi3sgyjEORzzEOSlL8F2ME73hEngAgwCHgBQFU/Bj7zWyUdmaYm13d/yCFuH56w5rcu\nysrcduutrg/fz5fJRLxMyWVZ24Jgy8tvjflOcPZsl5ZuCdsePeCCC8xxGEYq8inJvhr4DGgG7lfV\nKSIyAJiNcywCjFLV90TkQuBI4EygJ7AE+C9VfSpUZoea51FdDSecEDufPt0NVgdbIU1N8Ic/xIsE\nzpmTmSBgeyfdfJBM5oqkK7cj16tRfBTbPI+gqu5znqruKcDlqvpXETkFeAg4ytsPBF4F1gIv45xO\nhyY8cHvFFfDxx27+hj92UVERv2a4T1vUddsb6eaDZDJXJBlRmzBpGIVim8wwF5FJwBfAdeotBuWl\nf66qOyTJ/zJwvqquDKXrpEmTWs7buyR7Q4OLktq40XWx+OMbAJMnOy2niorkL7SlS22WdD4Iz0if\nOtX9HQwjSoQl2W+88cactzzy4jxEpCtQoqpfeKq6zwE3Ar/FiR6+KCJHAL9R1QNF5BueLV+KyFHA\nz1R1dJJyO1S3VUODWyt806b49SogfvU934EEu2H8lsfy5a5/vyO2PHJFsJtq0aJ45wFuLkhlZWFs\nM4xMKKaVBFOp6l4E3O6l/8I7B9gVWCIiy4CfAOPzZFdR8cwzsTkJzc1u8La0NHYelBgPD2gHZc/N\ncbSdsCLxoEGw007xeX7/+8LYZkSXjrAqZV7GPFT1XWD/JOkvkyQEV1XXAgPyYUsU8VeuAxdFlerF\nftxxbp6Br8U0dy68954b+6itjV99Lxlt7dc3YoRDflescKG9GwIB6NlOujTaNx1lvNHkSbYx/vjE\nUUe5bdSo1L9OKipct1VJidvvvruLopo9G+65x81DaI9fyigRXg/kP/+B+vr4PP36FcY2I5osXeo2\nX3OuWLXgWsOcxzbGl8PwWbky9uUKN3UXLXLXt2xx+8WL42dOjx3bvpvFUcFXJN60Ca6+OvH6449v\n/Wd0hG6OjkKvXi5IBdyPjmLQgmsL5jy2MVVV8aG1Awa4pq3fIjn00PStkdaWVTVyy6JFMUXiujrX\nXRhEBH7wg637jNZWejSKi6Dyg68F1x4x57GNqahwobRz5rjNnyfgrz+xebPbL14cU4YNyoUnmzlt\nFIZx41yLMNNIq1StC/tB0L7YeedYZGRzsxPkbI+Y8ygAFRVu7OKII9KPWfiOJigXblFU2xbfgZeV\nJUq6X3JJdo4jVeuiV69YFF1JiRO7vP9+F6ptFA/+j4NZs2ILp6m6/9X2iC1DGxGCy6YGZ5Abhcef\nQ9Ozp9MOa8vs8oULndNobnaO6KWXYpFw4YmH5eVufKVLF3jnHdPXKgaCEVb9+jlhzY0bo/M3LKZ5\nHplKsh/opZeJyB88SfZlIjIxX3ZFlWStDCMa+CHPPXq4v01Q2j7YFZVu0DubBbX8uT1ffeUi6ozo\nE+x6fPttF0QxZUo0HEe+KLQk+y04SfZTgXJPkv0bwHIR+bOqttOhpnj8Gcy9ekVnnXAjOcG5M8Ff\nmwO8WUorVyaP7V++PH4J3BUrYi8Vv2ts5UrYc894TbP+/fP+SEYO8McifUWH0aPb/w/AqEiyK7Cd\niJQCXYGNQGMebYsM/gvokENg770t4qaYCP7aXLHCbf6g97x5mY9b+K3Ol16CI4+Mv/boo3kx3cgx\nHXEsMp/OQ4HnReRVT3Id4ErgNhFZh2t1/NRLfwL4EvgAWAPcpqqf5dG2yOC/gJqbXTeFRdwUD8HI\nt8rKWLcUwKmnwsUXO2HLhob4yLnKSvf3DToWv0UT7s761re2zbMY2ZGsi7LY1rzZWvK5nsfuQUl2\n4DKcJPvcgCT7xap6lIgcBPw3cC6wM/ASMEZV14TKLEpV3XTrPwS7PsrKnBMxIcPiwR9M/+ij+LVX\nglx5Jdx4ozueN885Fl9yZvXq+D7xhgbo3dutGd+pk+vCaq995sVKWH5k5kw3t2Pnnd3f97jjCv83\n2xaquqhq3jdgEnAVsCGU/pm3/x1wViD9QeCUJOVosdHYqFpVpVpW5vaNjcnzLFyoWl/v9snyGNHm\n+edV3YhV4lZaqrrffu7vetdd8dcmT44vp7FRdeBAd8/AgfZdiCILFrj/Z3D7ffZRLSlRFXFpnTu7\n/+Uo4b07c/pez0u3lYh0FZFu3vF2wHeBt4AGETnMSz8CWOXdsg74TiD/SGBluNxiZO7cxMl/YYLR\nPB2p2dueCHZLDRzoBrpLvP+uoAJy797x91VUxI+NLF0Kq1a5e95+O7V0jVE4gpMAN292rcMtW2LB\nLhs3wpNPFsy8bUa+oq2+BTwlIup9xjR1EVYXAXd5A+NfEZNkvweYKiJLvfMHVXVpQqlFRlMTXH55\nfNqXXxbGFiM/BLskFyyIdWU0NbkXyD33OCfQv79LHzzYOZe6Oid2efHFLjTX78IKR+34ZYVVWsGW\nwi0U8+bFR0Xutptz/lu2xNLCPxLaJbluyuRzo8i6rZ5/PtaU9bc5cwptlZErGhtdd1RZWaxbKphe\nWqpaXu66NIJdUH435c03x3837r47/rqff8ECV5bfTTJnTvLPNXJHY6Or92R1W1+v2qWL+3t06aJa\nW+v+Jv37R7e7kWLptjLcr8XLLov/hSICe+1VOJuM3JJKkyoYQbdpk/tFumJFrMvS76YcEFrBxpc/\nCUfthCcY/uc/HUPyu1C0JlTZo4eb/OdPAqysdFJDr77qJvkuWtQxWoPmPPLE0qWuayKItmOdm45I\nKpFKP93Xq0rF4Ye7+0pLYxPLkhGeYPi//9sxJL8LRSZClT16wAUXuL0/HgUda8zSnEeeCEuvg2t5\nHHpoYewxck+qiWF++uzZzimUlcVUkcP3v/KK+7X6yiuZv3Q++igm+d3c3H4lvwtFWKgynXPuyHL6\n5jzyREWFe3lceWUs6qasDNavL6xdRm5JNTHMV05+5ZV4LaxM74fYL9qePd2AOrj90UebLH8m1NXB\nNdfE9wA0NLQ+8z+ZlEwqOrKcfj61rTo0/op/S5c6lVR/8p/9o3cs2rqOfDDCqnfv+MWFXnzRTUxb\nt859n1I5nmKJxsqHrXV1bkxJFW691emGdevmJIC++qptarfJ7EwWHddhyPUIvL/hZEb+BbwOLPbS\n9gcW+mnAMC/9TC9tibdvBvZNUmbOoxDyRXgi0ZQp0YvAMKJLsoloZWVuAlppafoJp88/H5uYGvVo\nrFQRa1vL1VfHR7JNnKj6+9/Hp02Zktqm8MTedJM3w9FxUYQ8RFvl03msBnYKpc0GvusdH4OTKgnf\nVwWsSlFmzioz14RD+/x/ik6dov8PbESP8Penvt7NRk8X9h0MEfbzdOrkXmxRJegk22prsrDampr4\nuqqpcXXYubNmNAs86BAaGxPDqqurs7ezkOTDeURFVTfIGcD0PNqVc5KtP94RVTaN3FFR4bqm7rnH\n7Xv0SFzJMDzhNBgiDG6srV+/aHal+OM5vXpt3fhNqgHrjRtjg95lZS5kuqLCdQGKuH1rq3j63Y2H\nHOLGToKsbBf6F1tJrr2Rv+FaHkuAV4ELvbQBwFqcHMl7wF5J7nsbGJSizJx641wR1jUqtl8lRvRI\n1p0T/p5l0vKIos5S+Nlqa1Xvv79tdgZbLqWlsTpJ1vJvrf5aK7+Y/8cpsm6r3b39N3HjGIcAdwEn\neumnAM+H7hkO/CtNmbmsz5wR/lL27m3dVMbWkaw7J1ORzWuuif8+purb31bU1roxiNpadx4ez+nb\nN/GZ0s3wDuKPRfjPGi4jOBbRFucRdHT+eNOgQcX3/50P57FN1jAXkUnAF8B1qrpTIP1zVd0hcH4H\n8JGq/iZFOZGUZG9qcs3t996Lpc2Z40I1DaMt+N0xfhSP3/XpS8CnirKC+EgjEdfFUlm5be1PZ0u3\nbu7Z1q51KyeuXRvLP2eOmw8T1vJK9axNTbD//k4XDFxX1ezZif97TU1u5vell8a0xvyZ4K1FewXX\nsE8X4RYlilaSHbcaYDfveDvgZZyy7jLgMC/9CODVwD0CvA/0TlNurhxxTmlsVN1jj+Ju1hrRo61R\nPFs7CJ3pr/5MCEc9XXmlax345z17JrYGsrE/qPuVrPXhP09VlcsXjlYLXkvXmstVfRQKiqXbCugD\nvIHrrnoLmOilHwS85qUvBA4I3HMYsKCVcnNbozki2VoOJoBoFIpMI/2SvRRzHTpbWxsTBxVRnT49\n/mVfWuq6rYIv77DwYHAsJFlUY9AZ+V1hQYeT7P/Td0qZjiMVQ9hzOorGeeRrKxbnYWMeRqFprdWS\n6qWYya/+bH+J19Sojh/v9uGXfVVV4iJowdZESYkbw6mvT23z008nOgd/fCXZ9WyCEHIRShwFzHlE\n1HkEm759+0YvusUwwqR6Kab71a+aWTdPOH/4hd/Y6F7Sc+ak7iaqqopfna9LF+cEkkVWJXMewSCB\nsIOYPDn2ua3N/Wgv87Xy4TxM2yoHVFQ47aJ//hPeeKPw6xcbHYu2rDKYShF47Vo3JwLcOuph0cVF\ni9zgcnNz6pUxgyTTfmpqctIgAwfGDzyHn8N/3YOTFFm3LiZj39wMV1zhNKp+9rP4z+zc2UkD+YwY\n4T6rpMTtzzsv9rlr18bmxWzZkvi8Nl8rNeY8ckQ6gTvDyBdtVXWtqICHHoLTTnP74Noh5eXuuFMn\n6N5965a/DTup7t2dvtTFF7u9L1AYfI7DDnNRWb7jAKdFdfLJ8NvfxtY2qa2FZ5+Nn7AnAn37Jv4f\nlpY65xGWyU/lRMN1Zf/bSch1UyafGxHttjKMQhHufvKjlVobJK+piR/ITjUHo3fv+JUQs5H4CH6m\nP6YR1peaODFmU1jLq1Mn97mTJ8c+p74+ds2XbWlNkqW1cYti0KbaWrAxD3MehhEkOAYxcGB6QcRg\n3l12SXyJ+3n8Pv7evePzVFe3baJdkOCYikjM1rAzq6lJfKEHZ9Dvs0/MofhjKFVVyccm2su4xdaQ\nD+dh3VaG0Q4QcXpOK1emXlsiOF7xySfx9/7gB7HJcjNnuj7+Sy6Jv3/Nmq2301/CdeJE14Xk2/rY\nYxWT21AAAAqXSURBVLFuKlVYsiSmLeV3mwW1u1avhpoad91fO2XBguRjEzZukSdy7Y38jSwk2b1r\n+wILgKXefeVJysy1QzaMoiZVd0+yX9jhVsPUqa7FUVubPCoqWRdVJhIpmRBuDdTWJkZ5hW2qr4+X\nIomibldUoZi6rchCkh0o9RxGlXe+EzjplND9uaxPwyh6kkm3p+q/T/fiTxe6O2VK4kS9XIwR1NfH\nCyLW1sacWSqb7ror3gEWWrerWMiH88ibtpWIvOu1LD4NpP0deEhVHxeRM4BjVfVsETkGOENVz2ml\nTM2XvYZRrGSid+XT0OAilI49Nj6kvKEh+1X2tmYFwOBKiYMHu66ysWPj9awgUd+rqWnrVgPsqIgI\nmmNtq3wuQ6vA8yLSDNyvqlOAK4HZInI7TstqlJe3EkBEZgG7AI+q6q15tM0w2g2ZLnXrL40cfGGv\nXete/mvXunkd4MYh1q1L/1L217BZudLNvUi1RnsqwvM/nn02cT7IyJHOYQQdY0WFcxi+szHHUTjy\n6TwOUtUPROSbwHMishInw365qv5VRE4BHgKO8uw4CBgGfAX8Q0ReU9W54UJvuOGGluOoqOoaRjEQ\nfGEvW+bmU6xZ417Mjz3m5jo0N7t5FD17pi/LH3z3y1282E3Ae+YZOO4491JvaIg/DxJe+/vYY5Ov\nBZ7MMfboARdckJMqabeEVXXzQaEl2T9T1R1F5DRgjKr+wEu/DvhfVb09VI51WxlGGwnKvPfq5RzH\n5s3Oadxzj4uu8p3HSy+lb83MmQNHHRU7nz7dzdz2u5NefhkOOih991K4uy2b7jcjO/LRbZWXUF0R\n6Soi3bzj7XBy7G8BDSJymJd+BLDKu2U28G0R6SIiZTiF3eX5sM0wOirBkNUXX3Qv6bIy50gOO8y1\nBjp1cumtLQc7YoTLX1rq9v/+t3MU4Pa33hp/PnNmcnuCM7dtJndxkZeWh4j0AZ7CjXuUAdNU9Tci\nchBuNcFSXPfUBFV93bvnTOBa3Drnz6rqT5OUay0Pw8gRDQ3xXVczZ2a32FGwpfDBB86J+OMm/fq5\nsjZutIHtKJCPlsc26bbKFeY8DCN3LFzotKT8rqv58zMbeA/jD577YyDgWjQzZrgWiQ1sF55ii7Yy\nDCPC9OrlXvKbN7vup9YGycP4oboffxzvOMCVueOOsMsu1g3VXjHnYRgdlGzDc4ME52mkcjrjxsGG\nDa2vQ24UJ6ZtZRgdlKoqF15bVubmarQ2SB4kGPa7bh3stlting0bUutsGcWPOQ/D6OC0ZRixqso5\nnNJSt//tb+Ov33tv6+tkGMWNOQ/D6KAsXepmiDc3u4WV2tI6EG8I9tBD40N3zz7blGzbO/nUtloD\nfI4Lvf1aVYeLyP7AfUAX4GtcqO5rItILWAH4a4K9oqoTkpRp0VaGkSOCkwZ97ahMX/LJIrUGD7ZJ\nflGlaCYJemwBRqvqAao63Eu7GZikqgcAk4CgftXbqjrE2xIcRzGRb1mAXGF25o5isBHi7dyadS6S\nLd+ay0l+xVifHY18Og9JUv4WYAfveEegPpS/XVAsXyizM3cUg42QaGdbX/j5XmCpWOuzIxEVVV2A\n3iKyBNfV9f9U9Z95tM0wjK0kUzVfo30SFVXdD4CeqrpBRIYAfxWRQar6RR7tMwzDMNpIoVV1P1fV\nHZLknwtcpapLQuk2Wm4YhtEGikKeRES6AiWq+kVAVfdGPFVdVX3RU9Wt8/LvAqxX1S0i0hfYB7eM\nbRy5fnjDMAyjbeSr2+pbwFNeS8FX1X1ORC4C7hIRX1X3Ii//ocBNIrIJN6h+sap+lifbDMMwjK2k\nqFR1DcMwjGhQsBnmIvKgiPxbRN5sJd+BIvK1iJwcSi8RkSUiUh1I20lEnhORWhGZLSIJ4ykRsXOS\niLzvpS8RkTGFtFNE1ojIv0TkdRFZHEjPaX3mycao1eUOIvK4iKwQkWUiMsJLj9R3M42dkalPEan0\n/t5LvP3nInKZdy0y9dmKnZGpTy/tShFZKiJvisg0ESn30rOuz0LKk0wFjk6XQURKgN/gVhoMczmJ\nqw1OBOaoan/gBSBhQamI2AlwR2BS5KytN3Or7Ew2oRNyX5/5sBGiVZd3ATNVdSCwH045AaL33Uxl\nJ0SkPlW1zvt7DwGGAv8BZniXI1OfrdgJEalPEekB/AgYoqr74oYUTvcuZ12fBXMe3jyODa1k+xHw\nBPBRMFFE9gTGAg+E8p8A/NE7/iNwYkTthBxPitwaO0k+oRNyXJ95stG/ljPaaqeIbA8coqpTvXI2\nq2qjdzky381W7ISI1GeII4F3VPV97zwy9dmKnRCt+iwFthO33HdXYhO1s67PyAojel7yRFW9j8TK\n/y3wE9xExCC7quq/AVT1Q2DXiNoJ8EMReUNEHshFk3sr7fQndL4qIhcG0rdpfbbRRohOXfYBPhGR\nqV4Xxf0i8g3vWpS+m+nshOjUZ5DTgL8EzqNUn0HCdkJE6lNVG4DbgXU4p/GZqv7Du5x1fUbWeQB3\nAteEE0XkWODfqvoGrmLSefVtEQ3QFjvvBfqq6v7Ah8AdBbAzaM9BXpN7LHCpiBycoox812dbbIxC\nXfqUAUOAezxbv8R1B0ByZ5hv2mJnFOozrq5EpBNwPPB4mjIKUZ+Z2BmZ+hSRHXEtjF5AD6CbiJyZ\noozW61NVC7Z5D/Fmimurve1doAlX8ccDv8J5ztW4melfAA9796wAvuUd7wasiKKdmZa9LexMkm8S\n8ON81WeubYxSXeJC1FcH8h0M/C2C382UdkapPgPXjwdmhe6JTH2mszNK9YlT+JgSyDce+F1b67PQ\nLY+ULQdV7ettfXB9dxNUtVpVr1XVnqraFzfY84KqnuPdVg2c5x2fCzwdRTtFJLju2snA0sSSt42d\nItJVRLp5dvkTOn178lGfObUxSnWprtn/nohUelmPIBYsEaXvZko7o1SfgSxnkNgVFJn6TGdnxOpz\nHTBSRLqIiOD+7n6gRNb1WbA1zEXkz8BoYGcRWYf7NVkOqKreH8qeaZP0ZuAxEfkvYC3w/YjaeYu4\ntU22AGuAiwtoZ9IJnd61nNZnnmyMUl0CXAZM87owVgM/8NKj9t1MZWek6lOcWsWRxCYU+0SqPtPY\nGZn6VNXFIvIE8DpuPaXXAT9/1vVpkwQNwzCMrCl0t5VhGIZRhJjzMAzDMLLGnIdhGIaRNeY8DMMw\njKwx52EYhhFRMhVB9PL2FJE54gREX/BmmucNcx6GYRjRpVURxAC3AX9Q1f2Am3DCiHnDnIdhGEZE\n0SQiiCLSV0T+7um8vRiY7DkImOvdNw8nRZI3zHkYhmEUF/cDP1TVA3HCq/d56W/gZrEjbg2PbiKy\nU76MKNgMc8MwDCM7PHmeUcDjnsQIQCdv/xPgdyJyHjAfp5zbnC9bzHkYhmEUDyXABnVqyHGo6gfA\nOGhxMuM0fp2WnBtiGIZhRJcWEURVbQLeFZFTWi6K7Ovtdw60Rn4KPJRPo8x5GIZhRBRPBHEBUCki\n60TkB8BZwPneAlNLcXLr4MQSa0VkJW4xp1/m1TYTRjQMwzCyxVoehmEYRtaY8zAMwzCyxpyHYRiG\nkTXmPAzDMIysMedhGIZhZI05D8MwDCNrzHkYhmEYWWPOwzAMw8ia/w8TN5G7yv5hIgAAAABJRU5E\nrkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x42cbd1d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.subplot(2,1,1)\n",
+    "pl.plot(z_t,z_abs,'.',z_t,z_ord,'.')\n",
+    "pl.subplot(2,1,2)\n",
+    "pl.plot(z_t,np.asarray(z_abs) - np.asarray(z_ord),'.')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Note about averaging\n",
+    "The baselines have up to four values, corresponding to the up to four sets measured by the observer.  Pre-averaging these does not improve the transformation matrix calculated by the least squares solver in scipy/numpy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Calculate $(h,e,Z)_{variometer}$ from $(H,D,Z)_{ordinate}$ and $(X,Y,Z)_{absolute}$ from $(H,D,Z)_{absolute}$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "h_abs_n = np.asarray(h_abs)\n",
+    "d_abs_n = np.asarray(d_abs)\n",
+    "z_abs_n = np.asarray(z_abs)\n",
+    "h_ord_n = np.asarray(h_ord)\n",
+    "d_ord_n = np.asarray(d_ord)\n",
+    "z_ord_n = np.asarray(z_ord)\n",
+    "z_t_n = np.asarray(z_t)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "x_a = h_abs_n*np.cos(d_abs_n*np.pi/180)\n",
+    "y_a = h_abs_n*np.sin(d_abs_n*np.pi/180)\n",
+    "z_a = z_abs_n\n",
+    "h_o = h_ord_n*np.cos(d_ord_n*np.pi/180)\n",
+    "e_o = h_ord_n*np.sin(d_ord_n*np.pi/180)\n",
+    "z_o = z_ord_n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Calculate Transform matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[  9.81546858e-01,  -1.89150435e-01,   6.19830586e-03,\n",
+       "         -2.32136980e+02],\n",
+       "       [  1.50583668e-01,   9.94985961e-01,  -2.27063235e-03,\n",
+       "          2.09168024e+02],\n",
+       "       [ -4.30853583e-02,  -2.01141374e-03,   1.02449397e+00,\n",
+       "          3.26623382e+02],\n",
+       "       [ -0.00000000e+00,   0.00000000e+00,  -0.00000000e+00,\n",
+       "          1.00000000e+00]])"
+      ]
+     },
+     "execution_count": 120,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abs_st = np.vstack([x_a,y_a,z_a,np.ones_like(x_a)])\n",
+    "ord_st = np.vstack([h_o,e_o,z_o,np.ones_like(h_o)])\n",
+    "M, res, rank, sigma = spl.lstsq(ord_st.T,abs_st.T)\n",
+    "tol = 1e-9\n",
+    "maskM = np.abs(M) > tol\n",
+    "M = maskM * M\n",
+    "M = M.T\n",
+    "M"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Enter path to save adjusted statefile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "path = '/users/aclaycomb/'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "data = {\n",
+    "            'M11': M[0,0],\n",
+    "            'M12': M[0,1],\n",
+    "            'M13': M[0,2],\n",
+    "            'M14': M[0,3],\n",
+    "            'M21': M[1,0],\n",
+    "            'M22': M[1,1],\n",
+    "            'M23': M[1,2],\n",
+    "            'M24': M[1,3],\n",
+    "            'M31': M[2,0],\n",
+    "            'M32': M[2,1],\n",
+    "            'M33': M[2,2],\n",
+    "            'M34': M[2,3],\n",
+    "            'M41': M[3,0],\n",
+    "            'M42': M[3,1],\n",
+    "            'M43': M[3,2],\n",
+    "            'M44': M[3,3],\n",
+    "            'PC':  pier_correction\n",
+    "        }\n",
+    "with open(path + 'adj' + obs_code + '_state_.json', 'w') as f:\n",
+    "            f.write(json.dumps(data))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "factory = EdgeFactory()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Enter Start and End Times for Test month(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "start2=UTCDateTime('2016-06-09T00:00:00Z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "end2=UTCDateTime('2016-10-08T23:59:59Z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "hezf = factory.get_timeseries(observatory=obs_code,\n",
+    "\n",
+    "        interval='minute',\n",
+    "\n",
+    "        type='variation',\n",
+    "\n",
+    "        channels=('H', 'E', 'Z', 'F'),\n",
+    "\n",
+    "        starttime=start2,\n",
+    "\n",
+    "        endtime=end2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "raw = np.vstack([hezf[0].data,hezf[1].data,hezf[2].data,np.ones_like(hezf[0].data)])\n",
+    "adj = np.dot(M,raw)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "h_pqqm = np.mean(x_a - h_o)\n",
+    "\n",
+    "e_pqqm = np.mean(y_a - e_o)\n",
+    "\n",
+    "z_pqqm = np.mean(z_a - z_o)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot of $\\Delta F$ Over the Test Period\n",
+    "The left plot (black) shows adjusted delta F, the cyan shows adjusted delta F using average baselines over the period (instead of the transformation).  The blue on the right shows raw delta F."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x4340f4e0>"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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O7n6Eu8+Lrevn7hu6e2d339zdp0bL33T3Hdx9a3c/Nzn1YNy40LZdUxNOE3Fj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\nISIiif4/GOVi/Cnq2RsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x3dabe8d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.figure()\n",
+    "\n",
+    "pl.subplot(1,2,1)\n",
+    "\n",
+    "mean_baseline_delta_f = (((hezf[0].data + h_pqqm)**2 + \n",
+    "                          (hezf[1].data + e_pqqm)**2 + \n",
+    "                          (hezf[2].data + z_pqqm)**2)**(0.5) - hezf[3].data - pier_correction)\n",
+    "\n",
+    "mean_baseline_delta_f_mean = np.nanmean(mean_baseline_delta_f)\n",
+    "\n",
+    "pl.plot(mean_baseline_delta_f,'c')\n",
+    "\n",
+    "pl.hold(True)\n",
+    "\n",
+    "adj_delta_f = (adj[0]**2 + adj[1]**2 + adj[2]**2)**(0.5) - hezf[3].data - pier_correction\n",
+    "\n",
+    "adj_delta_f_mean = np.nanmean(adj_delta_f)\n",
+    "\n",
+    "pl.plot(adj_delta_f,'k')\n",
+    "\n",
+    "pl.ylim(adj_delta_f_mean - 30., adj_delta_f_mean + 30.)\n",
+    "\n",
+    "pl.title('adjusted')\n",
+    "\n",
+    "pl.subplot(1,2,2)\n",
+    "\n",
+    "raw_delta_f = (((hezf[0].data)**2 + (hezf[1].data)**2 + \n",
+    "                (hezf[2].data)**2)**(0.5) - hezf[3].data - pier_correction)\n",
+    "\n",
+    "raw_delta_f_mean = np.nanmean(raw_delta_f)\n",
+    "\n",
+    "pl.plot(((hezf[0].data)**2 + (hezf[1].data)**2 + \n",
+    "         (hezf[2].data)**2)**(0.5) - hezf[3].data - pier_correction,'b')\n",
+    "\n",
+    "pl.ylim(raw_delta_f_mean - 30.,raw_delta_f_mean + 30.)\n",
+    "\n",
+    "pl.title('raw')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plots of Raw h + Static Baseline, Adjusted X, and '$\\Delta h$'\n",
+    "This compares the static baseline applied to the raw data with adjusted data.  These should look similar on this scale."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x43902cf8>"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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LSVbKrSgvL68V2lZZWZklaYIzadIkjBw5MttihAYbUgzDMAzDMHWc0aNHZ1uEvMfPWp9m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\nAxnUQeMrZwZFAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x3d808e80>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.figure(figsize=(14,6))\n",
+    "pl.subplot(1,3,1)\n",
+    "pl.plot(hezf[0].data + h_pqqm,'b')\n",
+    "pl.title('static baseline')\n",
+    "pl.subplot(1,3,2)\n",
+    "pl.plot(adj[0],'c')\n",
+    "pl.title('adjusted')\n",
+    "pl.subplot(1,3,3)\n",
+    "pl.plot(adj[0] - hezf[0].data - h_pqqm,'k')\n",
+    "pl.title('$\\Delta h$')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plots of Raw e + Static Baseline, Adjusted Y, and '$\\Delta e$'\n",
+    "This compares the static baseline applied to the raw data with adjusted data.  These should look similar on this scale."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x43e4cb70>"
+      ]
+     },
+     "execution_count": 131,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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BlCENLS1oYVchhkkcIkpbBKaNwAoTwzBtklOmTsUhEyakLQZThnT89FPcs3Bh2mIwDMMw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Te+sc0VVKX4hilMaXgZpKucZTeecP4xaRJOaW+XKhGcPsKmswyu0sS5cMgQTPSsOBUWGsHCFERJ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\nUMOfl28AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x43310780>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.figure(figsize=(14,6))\n",
+    "pl.subplot(1,3,1)\n",
+    "pl.plot(hezf[1].data + e_pqqm,'b')\n",
+    "pl.title('static baseline')\n",
+    "pl.subplot(1,3,2)\n",
+    "pl.plot(adj[1],'c')\n",
+    "pl.title('adjusted')\n",
+    "pl.subplot(1,3,3)\n",
+    "pl.plot(adj[1] - hezf[1].data - e_pqqm,'k')\n",
+    "pl.title('$\\Delta e$')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plots of Raw z + Static Baseline, Adjusted Z, and '$\\Delta z$'\n",
+    "This compares the static baseline applied to the raw data with adjusted data.  These should look similar on this scale."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x445b0e48>"
+      ]
+     },
+     "execution_count": 132,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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JoqMUz0iYipZTQt60kBBVojg6dTKWqnVUDty0agU8/XThfl6KVEMDcOqpjb/D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\nIBpICSGEEEIIIURB/gUajLbZkAcT0gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x4382fef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pl.figure(figsize=(14,6))\n",
+    "pl.subplot(1,3,1)\n",
+    "pl.plot(hezf[2].data + z_pqqm,'b')\n",
+    "pl.title('static baseline')\n",
+    "pl.subplot(1,3,2)\n",
+    "pl.plot(adj[2],'c')\n",
+    "pl.title('adjusted')\n",
+    "pl.subplot(1,3,3)\n",
+    "pl.plot(adj[2] - hezf[2].data - z_pqqm,'k')\n",
+    "pl.title('$\\Delta z$')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}