NK_X_corr_ns56.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import gps_particle_data\n",
    "import wget\n",
    "import os\n",
    "import numpy as np \n",
    "import time\n",
    "import json\n",
    "import sys\n",
    "import math\n",
    "from datetime import datetime, timedelta, date\n",
    "from itertools import compress\n",
    "from random import randint\n",
    "import urllib2\n",
    "import aacgmv2\n",
    "import scipy\n",
    "import matplotlib\n",
    "from matplotlib import gridspec\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150111_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150118_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.83313736  0.45018999  0.38545666]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150215_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150222_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.83313736  0.45018999  0.38545666  0.38897183]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150315_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150322_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150412_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150419_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150510_v1.03.ascii\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150517_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.91488337]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150614_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150621_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.91488337  0.96660334]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150712_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150719_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
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      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150816_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150823_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
      "[ 0.97854368  0.8835162   0.99349624  0.94882216  0.97777851  0.98278968\n",
      "  0.99058162  0.95517383  0.98254292  0.99367197  0.97833369  0.73211791\n",
      "  0.98846154  0.93278599  0.83860094  0.76514504  0.98171126  0.76828397\n",
      "  0.96313413  0.78153234  0.99383795  0.92221715  0.91186213  0.96722383\n",
      "  0.95381895  0.97783047  0.96239474  0.97027749  0.98207367  0.95539556\n",
      "  0.9860617   0.88539406  0.93451272  0.81539652  0.78750044  0.95144984\n",
      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935  0.90605889]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150913_v1.03.ascii\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_150920_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
      "[ 0.97854368  0.8835162   0.99349624  0.94882216  0.97777851  0.98278968\n",
      "  0.99058162  0.95517383  0.98254292  0.99367197  0.97833369  0.73211791\n",
      "  0.98846154  0.93278599  0.83860094  0.76514504  0.98171126  0.76828397\n",
      "  0.96313413  0.78153234  0.99383795  0.92221715  0.91186213  0.96722383\n",
      "  0.95381895  0.97783047  0.96239474  0.97027749  0.98207367  0.95539556\n",
      "  0.9860617   0.88539406  0.93451272  0.81539652  0.78750044  0.95144984\n",
      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935  0.90605889  0.96422838]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151011_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151018_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
      "[ 0.97854368  0.8835162   0.99349624  0.94882216  0.97777851  0.98278968\n",
      "  0.99058162  0.95517383  0.98254292  0.99367197  0.97833369  0.73211791\n",
      "  0.98846154  0.93278599  0.83860094  0.76514504  0.98171126  0.76828397\n",
      "  0.96313413  0.78153234  0.99383795  0.92221715  0.91186213  0.96722383\n",
      "  0.95381895  0.97783047  0.96239474  0.97027749  0.98207367  0.95539556\n",
      "  0.9860617   0.88539406  0.93451272  0.81539652  0.78750044  0.95144984\n",
      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935  0.90605889  0.96422838  0.98749033]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151115_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151122_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
      "[ 0.97854368  0.8835162   0.99349624  0.94882216  0.97777851  0.98278968\n",
      "  0.99058162  0.95517383  0.98254292  0.99367197  0.97833369  0.73211791\n",
      "  0.98846154  0.93278599  0.83860094  0.76514504  0.98171126  0.76828397\n",
      "  0.96313413  0.78153234  0.99383795  0.92221715  0.91186213  0.96722383\n",
      "  0.95381895  0.97783047  0.96239474  0.97027749  0.98207367  0.95539556\n",
      "  0.9860617   0.88539406  0.93451272  0.81539652  0.78750044  0.95144984\n",
      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935  0.90605889  0.96422838  0.98749033\n",
      "  0.58142526]\n",
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151213_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_151220_v1.03.ascii\n",
      "channel: 2 X-cor  --->    1.0\n",
      "[ 0.97854368  0.8835162   0.99349624  0.94882216  0.97777851  0.98278968\n",
      "  0.99058162  0.95517383  0.98254292  0.99367197  0.97833369  0.73211791\n",
      "  0.98846154  0.93278599  0.83860094  0.76514504  0.98171126  0.76828397\n",
      "  0.96313413  0.78153234  0.99383795  0.92221715  0.91186213  0.96722383\n",
      "  0.95381895  0.97783047  0.96239474  0.97027749  0.98207367  0.95539556\n",
      "  0.9860617   0.88539406  0.93451272  0.81539652  0.78750044  0.95144984\n",
      "  0.82367394  0.99552461  0.95751114  0.93614664  0.92632404  0.94082678\n",
      "  0.90253054  0.9721097   0.80540339  0.80256397  0.93822639  0.80142115\n",
      "  0.98351181  0.94075231  0.88373807  0.96562909  0.88573976  0.8821351\n",
      "  0.95788464  0.87148166  0.94433686  0.85095882  0.95675541  0.95384947\n",
      "  0.88066325  0.87559151  0.91330843  0.80168467  0.81242905  0.93657261\n",
      "  0.60409734  0.33414591  0.73253036  0.54668013  0.8828114   0.91699607\n",
      "  0.30098167  0.64257719  0.82714853  0.2961717   0.79681272  0.36267908\n",
      "  0.31719357  0.73334215  0.9865746   0.80658102  0.8844696   0.88232343\n",
      "  0.93001496  0.80880389  0.82227669  0.33623406  0.77377911  0.81480038\n",
      "  0.34465579  0.94087111  0.85250124  0.47329241  0.86155606  0.85042929\n",
      "  0.76880297  0.94359233  0.83114723  0.72176416  0.74471408  0.84632554\n",
      "  0.77978325  0.95393941  0.94289647  0.92653769  0.90946998  0.98836635\n",
      "  0.75427162  0.39832467  0.99422487  0.95206534  0.62544371  0.66658526\n",
      "  0.79684375  0.88212369  0.90854251  0.68045234  0.367137    0.49615456\n",
      "  0.80836372  0.37495263  0.27887203  0.6953543   0.35179453  0.30509821\n",
      "  0.8190818   0.3226507   0.5085209   0.3998893   0.45937266  0.88280559\n",
      "  0.83313736  0.45018999  0.38545666  0.38897183  0.47414288  0.96544728\n",
      "  0.91488337  0.96660334  0.66130935  0.90605889  0.96422838  0.98749033\n",
      "  0.58142526  0.8969896 ]\n"
     ]
    }
   ],
   "source": [
    "for j in range(12):\n",
    "    #if j == 0 or j == 1 or j == 2:\n",
    "        #continue\n",
    "    start_date = datetime(2015,j+1,10,0,0,0);\n",
    "    end_date = datetime(2015,j+1,23,0,0,0);\n",
    "    ms = gps_particle_data.meta_search();\n",
    "    ms.load_data(start_date,end_date);\n",
    "    \n",
    "    output_data = ms.get_all_data_by_satellite()\n",
    "    signal = 'rate_electron_measured'\n",
    "    for i in range(11):\n",
    "        a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "        ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "        #Normalised cross-correlation between channel 2 and all other channels for a given time period.\n",
    "        cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "        fname = 'ch2_'+str(i)+ '_ns56' +'.ascii'\n",
    "        with open(fname, 'a') as f:\n",
    "            np.savetxt(f, cor)\n",
    "        if i == 2 :\n",
    "            print 'channel:', i, 'X-cor  --->   ', cor[0]\n",
    "    \n",
    "    cont = np.loadtxt('ch2_0_ns56.ascii')\n",
    "    print cont"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8LslPVNWZSfYmubS7H5bk0ulrAAA4bqwZw919sLv/ZLr9hSTXJnlQkqcnuXi628VJnrGo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\nEsMAAAxLDAMAMCwxDADAsP4/k3W3BW6FiSsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5795a8f910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f57975d1cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5795d37dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f579761a890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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JYQAAxhLDAACMJYYBABhLDAMAMJYYBgBgLDEMAMBYG8ZwVb2iqm6oqivX3feCqvpIVV2+\nfDx2Z8cEAIDtt8qR4V9J8ujj3P+z3X3u8nHp9o4FAAA7b8MY7u43J/nELswCAAC7aivnDD+rqq5Y\nTqM4fdsmAgCAXXKyMfzSJPdPcm6S65K86EQ7VtUFVXW0qo4eO3bsJJ8OAAC230nFcHd/tLtv7u5b\nkrwsyXm3s+9F3X24uw8fPHjwZOcEAIBtd1IxXFVnrfvySUmuPNG+AACwXx3YaIeqemWSRyU5o6o+\nnOT5SR5VVecm6STXJvnuHZwRAAB2xIYx3N1PO87dL9+BWQAAYFe5Ah0AAGOJYQAAxhLDAACMJYYB\nABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHEMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAwlhgGAGAsMQwA\nwFhiGACAscQwAABjiWEAAMYSwwAAjCWGAQAYSwwDADCWGAYAYCwxDADAWGIYAICxxDAAAGOJYQAA\nxhLDAACMJYYBABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHEMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAw\nlhgGAGAsMQwAwFhiGACAscQwAABjiWEAAMYSwwAAjHVgrwcA4NR06Mglez0CwJY5MgwAwFhiGACA\nscQwAABjiWEAAMYSwwAAjCWGAQAYSwwDADCWGAYAYCwxDADAWGIYAICxxDAAAGOJYQAAxhLDAACM\nJYYBABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHEMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAwlhgGAGAs\nMQwAwFhiGACAscQwAABjiWEAAMbaMIar6hVVdUNVXbnuvntV1Zuq6r3L59N3dkwAANh+qxwZ/pUk\nj77NfUeSXNbdD0hy2fI1AACcUjaM4e5+c5JP3ObuJyS5eLl9cZInbvNcAACw4072nOEzu/u65fb1\nSc480Y5VdUFVHa2qo8eOHTvJpwMAgO235R+g6+5O0rez/aLuPtzdhw8ePLjVpwMAgG1zsjH80ao6\nK0mWzzds30gAALA7TjaGX5/kGcvtZyR53faMAwAAu2eVt1Z7ZZK3JnlQVX24qp6Z5MIk31BV703y\n9cvXAABwSjmw0Q7d/bQTbDp/m2cBAIBd5Qp0AACMJYYBABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHE\nMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAwlhgGAGAsMQwAwFhiGACAscQwAABjiWEAAMYSwwAAjCWG\nAQAYSwwDADCWGAYAYCwxDADAWGIYAICxxDAAAGOJYQAAxhLDAACMJYYBABjrwF4PALBfHDpyyV6P\nAOxz+/XPiWsvfNxej3DKcmQYAICxxDAAAGOJYQAAxhLDAACMJYYBABhLDAMAMJYYBgBgLDEMAMBY\nYhgAgLHEMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAwlhgGAGAsMQwAwFhiGACAscQwAABjiWEAAMYS\nwwAAjCWGAQAYSwwDADCWGAYAYCwxDADAWGIYAICxxDAAAGOJYQAAxhLDAACMJYYBABhLDAMAMJYY\nBgBgrAN7PQAwz6Ejl+z1CACQxJFhAAAGE8MAAIwlhgEAGEsMAwAwlhgGAGAsMQwAwFhiGACAscQw\nAABjiWEAAMYSwwAAjCWGAQAYSwwDADDWga08uKquTfKpJDcnuam7D2/HUAAAsBu2FMOLf9rdH9uG\n7wMAALvKaRIAAIy11SPDneR/VtXNSX65uy+67Q5VdUGSC5Lk7LPP3uLTwf506Mglez3CcV174eP2\negQA2Ne2emT4kd19bpLHJPm+qvqa2+7Q3Rd19+HuPnzw4MEtPh0AAGyfLcVwd39k+XxDktcmOW87\nhgIAgN1w0jFcVZ9TVXe/9XaSb0xy5XYNBgAAO20r5wyfmeS1VXXr9/n17v7NbZkKAAB2wUnHcHe/\nP8lDt3EWAADYVd5aDQCAscQwAABjiWEAAMYSwwAAjCWGAQAYSwwDADCWGAYAYCwxDADAWGIYAICx\nxDAAAGOJYQAAxhLDAACMJYYBABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHEMAAAY4lhAADGEsMAAIwl\nhgEAGEsMAwAwlhgGAGAsMQwAwFhiGACAscQwAABjiWEAAMY6sNcD7IZDRy7Z6xGO69oLH7fXIwAA\njObIMAAAY4lhAADGEsMAAIwlhgEAGEsMAwAwlhgGAGAsMQwAwFhiGACAscQwAABjiWEAAMYSwwAA\njCWGAQAYSwwDADCWGAYAYCwxDADAWAf2egD2n0NHLtnrEU7o2gsft9cjnFL2839LANgPHBkGAGAs\nMQwAwFhiGACAscQwAABjiWEAAMYSwwAAjCWGAQAYSwwDADCWGAYAYCwxDADAWGIYAICxxDAAAGOJ\nYQAAxhLDAACMJYYBABjrwF4PAJtx6Mglez0CAHAH4sgwAABjiWEAAMYSwwAAjCWGAQAYSwwDADCW\nGAYAYCwxDADAWGIYAICxxDAAAGOJYQAAxhLDAACMtaUYrqpHV9V7quqaqjqyXUMBAMBuOOkYrqrT\nkvxCksckOSfJ06rqnO0aDAAAdtpWjgyfl+Sa7n5/d/9NklclecL2jAUAADtvKzF83yR/uu7rDy/3\nAQDAKeHATj9BVV2Q5ILly09X1Xt2+jl3yRlJPraVb1A/vU2TnBq2vF7DWK/Ns2abY702x3ptjvXa\nHE2xOauu1xes8s22EsMfSXK/dV9//nLf39PdFyW5aAvPsy9V1dHuPrzXc5wqrNfmWK/Ns2abY702\nx3ptjvXaHOu1Odu9Xls5TeIPkjygqr6wqu6c5KlJXr89YwEAwM476SPD3X1TVX1/kt9KclqSV3T3\nVds2GQAA7LAtnTPc3ZcmuXSbZjnV3OFO/dhh1mtzrNfmWbPNsV6bY702x3ptjvXanG1dr+ru7fx+\nAABwynA5ZgAAxhLDG9joktNV9YSquqKqLq+qo1X1yL2Yc79Y9RLdVfXwqrqpqp68m/PtNyu8vh5V\nVZ9cXl+XV9W/3Ys594tVXl/Lml1eVVdV1f/a7Rn3kxVeX89d99q6sqpurqp77cWs+8EK6/W5VfXf\nq+qdy+vrO/Zizv1ihfU6vapeu/w/8u1V9ZC9mHO/qKpXVNUNVXXlCbZXVf3csp5XVNWX7vaM+8kK\n6/XgqnprVf11Vf3Qlp6su32c4CNrPxj4viT3T3LnJO9Mcs5t9rlb/v/pJl+S5N17Pfd+Xq91+/12\n1s43f/Jez72f1yvJo5K8Ya9n3Q8fK67XPZP8cZKzl6/vvddz7+f1us3+j0/y23s9935eryTPS/LT\ny+2DST6R5M57Pfs+Xq+fSfL85faDk1y213Pv8Zp9TZIvTXLlCbY/Nskbk1SSRyR5217PvM/X695J\nHp7kJ5P80Faey5Hh27fhJae7+9O9/FdJ8jlJJp+Eveolup+V5DeS3LCbw+1DLmm+Oaus17cmeU13\nfyhJunvya2yzr6+nJXnlrky2P62yXp3k7lVVWTsQ8okkN+3umPvGKut1TtYOfKS7353kUFWdubtj\n7h/d/easvWZO5AlJfrXX/H6Se1bVWbsz3f6z0Xp19w3d/QdJ/narzyWGb99Kl5yuqidV1buTXJLk\nO3dptv1ow/WqqvsmeVKSl+7iXPvVqpc0/8rln8zeWFX/ZHdG25dWWa8HJjm9qn63qt5RVU/ften2\nn1VfX6mqf5Tk0Vn7S+pUq6zXS5J8cZL/m+RdSZ7d3bfsznj7zirr9c4k/zxJquq8rF0N7PN3ZbpT\n08q/Z9leYngbdPdru/vBSZ6Y5Cf2ep597j8k+eHB/wPZrD/M2j/5f0mSn0/y3/Z4nv3uQJIvS/K4\nJN+U5Eer6oF7O9Ip4fFJ/k93395RK9ZeU5cnuU+Sc5O8pKrusbcj7WsXZu3o5uVZ+xfBP0py896O\nBP/Qlt5neICVLjl9q+5+c1Xdv6rO6O6J12RfZb0OJ3nV2r8y5owkj62qm7p7YuRtuF7dfeO625dW\n1S96ff2d472+Ppzk4939mSSfqao3J3lokj/ZnRH3lc38+fXUzD5FIlltvb4jyYXLqXHXVNUHsnYu\n7Nt3Z8R9ZdU/v74jWfvhsCQfSPL+3RrwFLSp5mD7ODJ8+za85HRVfdHymzzLT37eJcnHd33S/WHD\n9eruL+zuQ919KMl/TfK9Q0M4We319XnrXl/nZe33rNfXiS8B/7okj6yqA8s//X95kqt3ec79YpX1\nSlV9bpKvzdraTbbKen0oyflJspz7+qDMjbtV/vy657ItSb4ryZvX/wWff+D1SZ6+vKvEI5J8sruv\n2+uhJnBk+Hb0CS45XVX/ctn+S0m+OWsv3r9N8pdJvmXdD9SNsuJ6sVhxvZ6c5Huq6qasvb6e6vV1\n4vXq7qur6jeTXJHkliT/sbuP+7Y8d3Sb+P34pCT/YzmaPtaK6/UTSX6lqt6VtZ/4/+Gh/0qz6np9\ncZKLq6qTXJXkmXs28D5QVa/M2jsEnVFVH07y/CR3Sv5uvS7N2jtKXJPkL7IcVZ9qo/Wqqs9LcjTJ\nPZLcUlXPydo7mmz6L1yuQAcAwFhOkwAAYCwxDADAWGIYAICxxDAAAGOJYQAAxhLDAACMJYYBABhL\nDAMAMNb/A9ExXUklt3QxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5795a8f050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2PVBV11XVNVW1by0nDgAA62GWK8wvSXLeUcvemORh3f0tSd6X5JcG+z+mu8/p7l2rmyIA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\nAAAD/xfqXgpg01MD7wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f57974da0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5797d57150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5796be0210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CGQAABgQzAAAMLBnMVXVRVd1ZVdfPW/a7VfXhqrq2qi6tqkcssu8tVXVdVV1TVVeu5sQB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\nzwMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f579758cbd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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DAACMJYYBABhLDAMAMJYYBgBgLDEMAMBYYhgAgLHEMAAAY4lhAADGEsMAAIwlhgEAGEsM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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f579685efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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uRQ8AYDl7D1y26CGwCbbrf8cbLzpv0UMAjiHOMAMAwIBgBgCAAcEMAAADghkAAAYEMwAA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\nBgCAAcEMAAADghkAAAYEMwAADPx/r7FJwgfM4WwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5796ba6050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(11):\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    fig = plt.figure(figsize=(12, 9))\n",
    "    cor = np.loadtxt(fname)\n",
    "    plt.hist(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    plt.title(fname)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_061008_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Test 9th Oct 2006\n",
    "\n",
    "start_date = datetime(2006,10,8,0,0,0);\n",
    "end_date = datetime(2006,10,9,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: array([ 0.91266148]), 1: array([ 0.94975399]), 2: array([ 1.]), 3: array([ 0.81392439]), 4: array([ 0.57846106]), 5: array([ 0.47957602]), 6: array([ 0.43324751]), 7: array([ 0.44509568]), 8: array([ 0.57868584]), 9: array([ 0.52165241]), 10: array([ 0.48848895])}\n"
     ]
    }
   ],
   "source": [
    "dcor = {}\n",
    "signal = 'rate_electron_measured'\n",
    "output_data = ms.get_all_data_by_satellite()\n",
    "for i in range(11):\n",
    "    a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "    ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "    cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "    dcor.update({i:cor})\n",
    "print dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ch2_0_ns56.ascii [ 0.91266148] 0.64\n",
      "ch2_1_ns56.ascii [ 0.94975399] 0.76\n",
      "ch2_2_ns56.ascii [ 1.] 1.00\n",
      "ch2_3_ns56.ascii [ 0.81392439] 0.10\n",
      "ch2_4_ns56.ascii [ 0.57846106] 0.13\n",
      "ch2_5_ns56.ascii [ 0.47957602] 0.18\n",
      "ch2_6_ns56.ascii [ 0.43324751] 0.19\n",
      "ch2_7_ns56.ascii [ 0.44509568] 0.14\n",
      "ch2_8_ns56.ascii [ 0.57868584] 0.28\n",
      "ch2_9_ns56.ascii [ 0.52165241] 0.17\n",
      "ch2_10_ns56.ascii [ 0.48848895] 0.22\n"
     ]
    }
   ],
   "source": [
    "xv = dcor.values()\n",
    "for i in range(len(xv)):\n",
    "    sum_bins_up_to = []\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    cor = np.loadtxt(fname)\n",
    "    sort = np.histogram(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    for j in range(len(sort[1])):\n",
    "        if sort[1][j] <= xv[i] <= sort[1][j+1]:\n",
    "            for k in np.arange(j+1):\n",
    "                sum_bins_up_to.append(sort[0][k])\n",
    "            tot_sum_up_to = np.sum(sum_bins_up_to)\n",
    "            pvalue = float(tot_sum_up_to)/float(np.sum(sort[0]))\n",
    "            print fname, xv[i], '%.2f' % (pvalue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_090524_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Test 25th May 2009\n",
    "\n",
    "start_date = datetime(2009,5,20,0,0,0);\n",
    "end_date = datetime(2009,5,26,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: array([ 0.23554187]), 1: array([ 0.74258099]), 2: array([ 1.]), 3: array([ 0.94603438]), 4: array([ 0.90324178]), 5: array([ 0.8012095]), 6: array([ 0.8139127]), 7: array([ 0.85653208]), 8: array([ 0.84547122]), 9: array([ 0.85168144]), 10: array([ 0.85263454])}\n"
     ]
    }
   ],
   "source": [
    "dcor = {}\n",
    "signal = 'rate_electron_measured'\n",
    "output_data = ms.get_all_data_by_satellite()\n",
    "for i in range(11):\n",
    "    a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "    ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "    cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "    dcor.update({i:cor})\n",
    "print dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ch2_2_ns56.ascii [ 1.] 1.00\n",
      "ch2_3_ns56.ascii [ 0.94603438] 0.96\n",
      "ch2_4_ns56.ascii [ 0.90324178] 0.75\n",
      "ch2_5_ns56.ascii [ 0.8012095] 0.63\n",
      "ch2_6_ns56.ascii [ 0.8139127] 0.78\n",
      "ch2_7_ns56.ascii [ 0.85653208] 0.86\n",
      "ch2_8_ns56.ascii [ 0.84547122] 0.83\n",
      "ch2_9_ns56.ascii [ 0.85168144] 0.84\n",
      "ch2_10_ns56.ascii [ 0.85263454] 0.84\n"
     ]
    }
   ],
   "source": [
    "xv = dcor.values()\n",
    "for i in range(len(xv)):\n",
    "    sum_bins_up_to = []\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    cor = np.loadtxt(fname)\n",
    "    sort = np.histogram(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    for j in range(len(sort[1])):\n",
    "        if sort[1][j] <= xv[i] <= sort[1][j+1]:\n",
    "            for k in np.arange(j+1):\n",
    "                sum_bins_up_to.append(sort[0][k])\n",
    "            tot_sum_up_to = np.sum(sum_bins_up_to)\n",
    "            pvalue = float(tot_sum_up_to)/float(np.sum(sort[0]))\n",
    "            print fname, xv[i], '%.2f' % (pvalue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_130210_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Test 12th Feb 2013\n",
    "\n",
    "start_date = datetime(2013,2,9,0,0,0);\n",
    "end_date = datetime(2013,2,13,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: array([ 0.44425641]), 1: array([ 0.84510738]), 2: array([ 1.]), 3: array([ 0.94944766]), 4: array([ 0.58362166]), 5: array([ 0.34096039]), 6: array([ 0.24985921]), 7: array([ 0.21219473]), 8: array([ 0.27366882]), 9: array([ 0.36621976]), 10: array([ 0.40079952])}\n"
     ]
    }
   ],
   "source": [
    "dcor = {}\n",
    "signal = 'rate_electron_measured'\n",
    "output_data = ms.get_all_data_by_satellite()\n",
    "for i in range(11):\n",
    "    a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "    ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "    cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "    dcor.update({i:cor})\n",
    "print dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ch2_0_ns56.ascii [ 0.44425641] 0.14\n",
      "ch2_1_ns56.ascii [ 0.84510738] 0.08\n",
      "ch2_2_ns56.ascii [ 1.] 1.00\n",
      "ch2_3_ns56.ascii [ 0.94944766] 0.96\n",
      "ch2_4_ns56.ascii [ 0.58362166] 0.13\n",
      "ch2_5_ns56.ascii [ 0.34096039] 0.08\n",
      "ch2_6_ns56.ascii [ 0.24985921] 0.03\n",
      "ch2_7_ns56.ascii [ 0.21219473] 0.01\n",
      "ch2_8_ns56.ascii [ 0.27366882] 0.01\n",
      "ch2_9_ns56.ascii [ 0.36621976] 0.03\n",
      "ch2_10_ns56.ascii [ 0.40079952] 0.08\n"
     ]
    }
   ],
   "source": [
    "xv = dcor.values()\n",
    "for i in range(len(xv)):\n",
    "    sum_bins_up_to = []\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    cor = np.loadtxt(fname)\n",
    "    sort = np.histogram(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    for j in range(len(sort[1])):\n",
    "        if sort[1][j] <= xv[i] <= sort[1][j+1]:\n",
    "            for k in np.arange(j+1):\n",
    "                sum_bins_up_to.append(sort[0][k])\n",
    "            tot_sum_up_to = np.sum(sum_bins_up_to)\n",
    "            pvalue = float(tot_sum_up_to)/float(np.sum(sort[0]))\n",
    "            print fname, xv[i], '%.2f' % (pvalue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_160103_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Test 6th Jan 2016\n",
    "\n",
    "start_date = datetime(2016,1,2,0,0,0);\n",
    "end_date = datetime(2016,1,7,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: array([ 0.61118363]), 1: array([ 0.98627214]), 2: array([ 1.]), 3: array([ 0.98665615]), 4: array([ 0.96080355]), 5: array([ 0.9389024]), 6: array([ 0.919697]), 7: array([ 0.90039252]), 8: array([ 0.91574764]), 9: array([ 0.93251445]), 10: array([ 0.93534256])}\n"
     ]
    }
   ],
   "source": [
    "dcor = {}\n",
    "signal = 'rate_electron_measured'\n",
    "output_data = ms.get_all_data_by_satellite()\n",
    "for i in range(11):\n",
    "    a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "    ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "    cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "    dcor.update({i:cor})\n",
    "print dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ch2_0_ns56.ascii [ 0.61118363] 0.18\n",
      "ch2_1_ns56.ascii [ 0.98627214] 0.76\n",
      "ch2_2_ns56.ascii [ 1.] 1.00\n",
      "ch2_3_ns56.ascii [ 0.98665615] 0.96\n",
      "ch2_4_ns56.ascii [ 0.96080355] 0.95\n",
      "ch2_5_ns56.ascii [ 0.9389024] 0.98\n",
      "ch2_6_ns56.ascii [ 0.919697] 0.97\n",
      "ch2_7_ns56.ascii [ 0.90039252] 0.95\n",
      "ch2_8_ns56.ascii [ 0.91574764] 0.99\n",
      "ch2_9_ns56.ascii [ 0.93251445] 0.97\n",
      "ch2_10_ns56.ascii [ 0.93534256] 0.97\n"
     ]
    }
   ],
   "source": [
    "xv = dcor.values()\n",
    "for i in range(len(xv)):\n",
    "    sum_bins_up_to = []\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    cor = np.loadtxt(fname)\n",
    "    sort = np.histogram(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    for j in range(len(sort[1])):\n",
    "        if sort[1][j] <= xv[i] <= sort[1][j+1]:\n",
    "            for k in np.arange(j+1):\n",
    "                sum_bins_up_to.append(sort[0][k])\n",
    "            tot_sum_up_to = np.sum(sum_bins_up_to)\n",
    "            pvalue = float(tot_sum_up_to)/float(np.sum(sort[0]))\n",
    "            print fname, xv[i], '%.2f' % (pvalue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  56\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns56/ns56_160904_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Test 9th Sept 2016\n",
    "\n",
    "start_date = datetime(2016,9,4,0,0,0);\n",
    "end_date = datetime(2016,9,10,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: array([ 0.99544243]), 1: array([ 0.99867596]), 2: array([ 1.]), 3: array([ 0.99523229]), 4: array([ 0.973753]), 5: array([ 0.9456183]), 6: array([ 0.91940475]), 7: array([ 0.88566425]), 8: array([ 0.88723489]), 9: array([ 0.92252189]), 10: array([ 0.91851611])}\n"
     ]
    }
   ],
   "source": [
    "dcor = {}\n",
    "signal = 'rate_electron_measured'\n",
    "output_data = ms.get_all_data_by_satellite()\n",
    "for i in range(11):\n",
    "    a0 = np.asarray(output_data[56][signal])[:,2]\n",
    "    ar2 = np.asarray(output_data[56][signal])[:,i]\n",
    "    cor = np.correlate(a0, ar2)/(math.sqrt(np.sum(a0**2)*np.sum(ar2**2)))\n",
    "    dcor.update({i:cor})\n",
    "print dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ch2_0_ns56.ascii [ 0.99544243] 1.00\n",
      "ch2_1_ns56.ascii [ 0.99867596] 1.00\n",
      "ch2_2_ns56.ascii [ 1.] 1.00\n",
      "ch2_3_ns56.ascii [ 0.99523229] 1.00\n",
      "ch2_4_ns56.ascii [ 0.973753] 1.00\n",
      "ch2_5_ns56.ascii [ 0.9456183] 0.98\n",
      "ch2_6_ns56.ascii [ 0.91940475] 0.97\n",
      "ch2_7_ns56.ascii [ 0.88566425] 0.95\n",
      "ch2_8_ns56.ascii [ 0.88723489] 0.96\n",
      "ch2_9_ns56.ascii [ 0.92252189] 0.97\n",
      "ch2_10_ns56.ascii [ 0.91851611] 0.97\n"
     ]
    }
   ],
   "source": [
    "xv = dcor.values()\n",
    "for i in range(len(xv)):\n",
    "    sum_bins_up_to = []\n",
    "    fname = 'ch2_'+str(i)+'_ns56.ascii'\n",
    "    cor = np.loadtxt(fname)\n",
    "    sort = np.histogram(cor, bins = np.arange(min(cor), max(cor)+0.1, 0.05))\n",
    "    for j in range(len(sort[1])):\n",
    "        if sort[1][j] <= xv[i] <= sort[1][j+1]:\n",
    "            for k in np.arange(j+1):\n",
    "                sum_bins_up_to.append(sort[0][k])\n",
    "            tot_sum_up_to = np.sum(sum_bins_up_to)\n",
    "            pvalue = float(tot_sum_up_to)/float(np.sum(sort[0]))\n",
    "            print fname, xv[i], '%.2f' % (pvalue)"
   ]
  }
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