bottle-brush-scaling-theory.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": "true"
   },
   "source": [
    "# Table of Contents\n",
    " <p><div class=\"lev1\"><a href=\"#Bottle-brush-with-RW-angular-loop-orientation\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Bottle brush with RW angular loop orientation</a></div><div class=\"lev2\"><a href=\"#No-drift\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>No drift</a></div><div class=\"lev2\"><a href=\"#With-drift\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>With drift</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-OU-angular-loop-orientation-(approximate)\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Bottle brush with OU angular loop orientation (approximate)</a></div><div class=\"lev1\"><a href=\"#Experimental\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Experimental</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-random-angular-loop-orientation\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Bottle brush with random angular loop orientation</a></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-10T16:23:39.725758Z",
     "start_time": "2019-04-10T16:23:39.363861Z"
    }
   },
   "outputs": [],
   "source": [
    "#import glob, os, sys, shelve, itertools\n",
    "#from collections import OrderedDict\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib notebook\n",
    "%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import numpy as np\n",
    "from ipywidgets.widgets.interaction import interact\n",
    "import ipywidgets.widgets as widgets\n",
    "\n",
    "import scipy\n",
    "import scipy.stats as st\n",
    "\n",
    "# from matplotlib import gridspec\n",
    "# from mirnylib import plotting\n",
    "\n",
    "# import seaborn as sns\n",
    "# sns.set_style('white')\n",
    "# sns.set_palette('deep')\n",
    "# sns.set_context('talk')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-10T16:23:39.899347Z",
     "start_time": "2019-04-10T16:23:39.894867Z"
    }
   },
   "outputs": [],
   "source": [
    "MIN_LOG10_S = -1\n",
    "MAX_LOG10_S = 4\n",
    "GLUE_AT = 2\n",
    "EXP_LOOP_SIZE = 80000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-10T16:43:04.978853Z",
     "start_time": "2019-04-10T16:43:04.974667Z"
    }
   },
   "outputs": [],
   "source": [
    "# import sys\n",
    "# sys.path.append(pathlib.Path('../').resolve().as_posix())\n",
    "# import smcviz\n",
    "# import openmmlib\n",
    "\n",
    "# REFSC_60m = smcviz.scalings['WT-20150609-60m-R1']\n",
    "\n",
    "# REFSC_CAPH1_R1_30m = smcviz.scalings['CAPH1-20160726-30m-R1']\n",
    "# REFSC_CAPH1_R2_30m = smcviz.scalings['CAPH1-20160919-30m-R2']\n",
    "\n",
    "# REFSC_CAPH1_R1_60m = smcviz.scalings['CAPH1-20160726-60m-R1']\n",
    "# REFSC_CAPH1_R2_60m = smcviz.scalings['CAPH1-20160919-60m-R2']\n",
    "\n",
    "# REFSC_CAPH2_R1_30m = smcviz.scalings['CAPH2-20160714-30m-R1']\n",
    "# REFSC_CAPH2_R2_30m = smcviz.scalings['CAPH2-20160830-30m-R2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-13T21:51:38.672636Z",
     "start_time": "2017-07-13T21:51:38.520643Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# REFSC_7m = smcviz.scalings['WT-20151009-7m-R1']\n",
    "\n",
    "REFSC_7m = np.array([[  1.06010000e+03,   1.18810000e+03,   1.33210000e+03,\n",
    "          1.49310000e+03,   1.67360000e+03,   1.87610000e+03,\n",
    "          2.10310000e+03,   2.35760000e+03,   2.64310000e+03,\n",
    "          2.96310000e+03,   3.32160000e+03,   3.72310000e+03,\n",
    "          4.17310000e+03,   4.67810000e+03,   5.24410000e+03,\n",
    "          5.87860000e+03,   6.58960000e+03,   7.38660000e+03,\n",
    "          8.28010000e+03,   9.28160000e+03,   1.04046000e+04,\n",
    "          1.16631000e+04,   1.30736000e+04,   1.46551000e+04,\n",
    "          1.64276000e+04,   1.84146000e+04,   2.06421000e+04,\n",
    "          2.31386000e+04,   2.59371000e+04,   2.90741000e+04,\n",
    "          3.25911000e+04,   3.65331000e+04,   4.09516000e+04,\n",
    "          4.59051000e+04,   5.14576000e+04,   5.76816000e+04,\n",
    "          6.46581000e+04,   7.24786000e+04,   8.12451000e+04,\n",
    "          9.10716000e+04,   1.02087100e+05,   1.14434600e+05,\n",
    "          1.28275600e+05,   1.43791100e+05,   1.61182600e+05,\n",
    "          1.80677600e+05,   2.02531100e+05,   2.27027600e+05,\n",
    "          2.54486600e+05,   2.85267100e+05,   3.19770600e+05,\n",
    "          3.58447600e+05,   4.01802600e+05,   4.50401100e+05,\n",
    "          5.04877600e+05,   5.65943600e+05,   6.34395600e+05,\n",
    "          7.11126600e+05,   7.97138100e+05,   8.93553100e+05,\n",
    "          1.00162960e+06,   1.12277810e+06,   1.25858010e+06,\n",
    "          1.41080710e+06,   1.58144610e+06,   1.77272410e+06,\n",
    "          1.98713760e+06,   2.22748460e+06,   2.49690160e+06,\n",
    "          2.79890560e+06,   3.13743760e+06,   3.51691460e+06,\n",
    "          3.94229010e+06,   4.41911560e+06,   4.95361410e+06,\n",
    "          5.55276110e+06,   6.22437510e+06,   6.97722160e+06,\n",
    "          7.82112610e+06,   8.76710210e+06,   9.82749510e+06,\n",
    "          1.10161446e+07,   1.23485626e+07,   1.38421381e+07,\n",
    "          1.55163641e+07,   1.73930901e+07,   1.94968086e+07,\n",
    "          2.18549741e+07,   2.44983631e+07,   2.74614741e+07,\n",
    "          3.07829776e+07,   3.45062216e+07,   3.86797966e+07,\n",
    "          4.33581716e+07,   4.86024026e+07,   5.44809301e+07,\n",
    "          6.10704741e+07,   6.84570326e+07,   7.67370056e+07,\n",
    "          8.60184526e+07,   9.64225031e+07,   1.08084938e+08,\n",
    "          1.21157961e+08,   1.35812184e+08,   1.52238855e+08,\n",
    "          1.70652355e+08,   1.91292994e+08,   2.14430146e+08,\n",
    "          2.40365768e+08,   2.69438340e+08,   3.02027280e+08,\n",
    "          3.38557897e+08,   3.79506943e+08,   4.25408832e+08,\n",
    "          4.76862619e+08,   5.34539812e+08,   5.99193141e+08,\n",
    "          6.71666379e+08,   7.52905356e+08,   8.43970300e+08,\n",
    "          9.46049675e+08],\n",
    "       [  1.36025607e-05,   1.34046188e-05,   1.36574460e-05,\n",
    "          1.32345444e-05,   1.29639579e-05,   1.25128973e-05,\n",
    "          1.19243258e-05,   1.13629686e-05,   1.05735869e-05,\n",
    "          9.77219368e-06,   8.84240339e-06,   8.06609568e-06,\n",
    "          7.14465216e-06,   6.31499827e-06,   5.51226795e-06,\n",
    "          4.76879398e-06,   4.18247063e-06,   3.59360570e-06,\n",
    "          3.13764287e-06,   2.75338562e-06,   2.45340402e-06,\n",
    "          2.18181840e-06,   1.94339264e-06,   1.77000763e-06,\n",
    "          1.60003804e-06,   1.45911904e-06,   1.34797427e-06,\n",
    "          1.22491760e-06,   1.13661127e-06,   1.05464027e-06,\n",
    "          9.74862144e-07,   9.07692404e-07,   8.52651873e-07,\n",
    "          7.98028535e-07,   7.45706359e-07,   7.00864258e-07,\n",
    "          6.58708816e-07,   6.24673757e-07,   5.86377722e-07,\n",
    "          5.54947671e-07,   5.26503076e-07,   4.98313350e-07,\n",
    "          4.72124666e-07,   4.45941670e-07,   4.24237778e-07,\n",
    "          3.99209011e-07,   3.77865371e-07,   3.54132789e-07,\n",
    "          3.35382423e-07,   3.13948076e-07,   2.94289478e-07,\n",
    "          2.74606656e-07,   2.58023724e-07,   2.39221238e-07,\n",
    "          2.22871782e-07,   2.06780001e-07,   1.91610943e-07,\n",
    "          1.77610080e-07,   1.64602895e-07,   1.52824997e-07,\n",
    "          1.41911209e-07,   1.31598674e-07,   1.21713280e-07,\n",
    "          1.12660971e-07,   1.03716735e-07,   9.49234670e-08,\n",
    "          8.53526672e-08,   7.54735421e-08,   6.50218799e-08,\n",
    "          5.39394069e-08,   4.37518502e-08,   3.52473806e-08,\n",
    "          2.90136753e-08,   2.41306659e-08,   2.01100335e-08,\n",
    "          1.69164445e-08,   1.45610547e-08,   1.27782927e-08,\n",
    "          1.15661752e-08,   1.05925240e-08,   9.75479526e-09,\n",
    "          8.97489348e-09,   8.23350430e-09,   7.44221577e-09,\n",
    "          6.66177792e-09,   5.95105691e-09,   5.34956968e-09,\n",
    "          4.80811488e-09,   4.37376310e-09,   3.93143736e-09,\n",
    "          3.59289091e-09,   3.28204473e-09,   3.05535485e-09,\n",
    "          2.87612295e-09,   2.73886018e-09,   2.63728473e-09,\n",
    "          2.57426311e-09,   2.50288251e-09,   2.38974135e-09,\n",
    "          2.27761691e-09,   2.12083309e-09,   1.95334581e-09,\n",
    "          1.75004353e-09,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-13T21:51:40.225292Z",
     "start_time": "2017-07-13T21:51:40.060807Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# REFSC_10m = smcviz.scalings['WT-92Pphase-10m-R1']\n",
    "\n",
    "REFSC_10m =np.array([[  1.06010000e+03,   1.18810000e+03,   1.33210000e+03,\n",
    "          1.49310000e+03,   1.67360000e+03,   1.87610000e+03,\n",
    "          2.10310000e+03,   2.35760000e+03,   2.64310000e+03,\n",
    "          2.96310000e+03,   3.32160000e+03,   3.72310000e+03,\n",
    "          4.17310000e+03,   4.67810000e+03,   5.24410000e+03,\n",
    "          5.87860000e+03,   6.58960000e+03,   7.38660000e+03,\n",
    "          8.28010000e+03,   9.28160000e+03,   1.04046000e+04,\n",
    "          1.16631000e+04,   1.30736000e+04,   1.46551000e+04,\n",
    "          1.64276000e+04,   1.84146000e+04,   2.06421000e+04,\n",
    "          2.31386000e+04,   2.59371000e+04,   2.90741000e+04,\n",
    "          3.25911000e+04,   3.65331000e+04,   4.09516000e+04,\n",
    "          4.59051000e+04,   5.14576000e+04,   5.76816000e+04,\n",
    "          6.46581000e+04,   7.24786000e+04,   8.12451000e+04,\n",
    "          9.10716000e+04,   1.02087100e+05,   1.14434600e+05,\n",
    "          1.28275600e+05,   1.43791100e+05,   1.61182600e+05,\n",
    "          1.80677600e+05,   2.02531100e+05,   2.27027600e+05,\n",
    "          2.54486600e+05,   2.85267100e+05,   3.19770600e+05,\n",
    "          3.58447600e+05,   4.01802600e+05,   4.50401100e+05,\n",
    "          5.04877600e+05,   5.65943600e+05,   6.34395600e+05,\n",
    "          7.11126600e+05,   7.97138100e+05,   8.93553100e+05,\n",
    "          1.00162960e+06,   1.12277810e+06,   1.25858010e+06,\n",
    "          1.41080710e+06,   1.58144610e+06,   1.77272410e+06,\n",
    "          1.98713760e+06,   2.22748460e+06,   2.49690160e+06,\n",
    "          2.79890560e+06,   3.13743760e+06,   3.51691460e+06,\n",
    "          3.94229010e+06,   4.41911560e+06,   4.95361410e+06,\n",
    "          5.55276110e+06,   6.22437510e+06,   6.97722160e+06,\n",
    "          7.82112610e+06,   8.76710210e+06,   9.82749510e+06,\n",
    "          1.10161446e+07,   1.23485626e+07,   1.38421381e+07,\n",
    "          1.55163641e+07,   1.73930901e+07,   1.94968086e+07,\n",
    "          2.18549741e+07,   2.44983631e+07,   2.74614741e+07,\n",
    "          3.07829776e+07,   3.45062216e+07,   3.86797966e+07,\n",
    "          4.33581716e+07,   4.86024026e+07,   5.44809301e+07,\n",
    "          6.10704741e+07,   6.84570326e+07,   7.67370056e+07,\n",
    "          8.60184526e+07,   9.64225031e+07,   1.08084938e+08,\n",
    "          1.21157961e+08,   1.35812184e+08,   1.52238855e+08,\n",
    "          1.70652355e+08,   1.91292994e+08,   2.14430146e+08,\n",
    "          2.40365768e+08,   2.69438340e+08,   3.02027280e+08,\n",
    "          3.38557897e+08,   3.79506943e+08,   4.25408832e+08,\n",
    "          4.76862619e+08,   5.34539812e+08,   5.99193141e+08,\n",
    "          6.71666379e+08,   7.52905356e+08,   8.43970300e+08,\n",
    "          9.46049675e+08],\n",
    "       [  5.12401928e-06,   5.21053010e-06,   5.43670420e-06,\n",
    "          5.51432327e-06,   5.80338727e-06,   5.74049234e-06,\n",
    "          5.81727055e-06,   5.86260055e-06,   5.73426592e-06,\n",
    "          5.67409064e-06,   5.51083511e-06,   5.34948672e-06,\n",
    "          5.15669658e-06,   4.94856413e-06,   4.69226356e-06,\n",
    "          4.42405745e-06,   4.17199337e-06,   3.90491288e-06,\n",
    "          3.61900127e-06,   3.39410568e-06,   3.12408496e-06,\n",
    "          2.89812736e-06,   2.69193214e-06,   2.45217645e-06,\n",
    "          2.27232962e-06,   2.09816377e-06,   1.93096590e-06,\n",
    "          1.78977445e-06,   1.64921804e-06,   1.52646390e-06,\n",
    "          1.41841330e-06,   1.32360411e-06,   1.22847270e-06,\n",
    "          1.15095084e-06,   1.08174275e-06,   1.01408849e-06,\n",
    "          9.55430430e-07,   8.98691236e-07,   8.58129012e-07,\n",
    "          8.08875083e-07,   7.64637589e-07,   7.31114664e-07,\n",
    "          6.92200849e-07,   6.60665470e-07,   6.31291407e-07,\n",
    "          5.97896042e-07,   5.68835030e-07,   5.42300591e-07,\n",
    "          5.15300288e-07,   4.88965839e-07,   4.61142954e-07,\n",
    "          4.36771896e-07,   4.13572974e-07,   3.90778564e-07,\n",
    "          3.69347980e-07,   3.48814164e-07,   3.28971645e-07,\n",
    "          3.11824481e-07,   2.93789418e-07,   2.76521240e-07,\n",
    "          2.59964798e-07,   2.43863255e-07,   2.27076162e-07,\n",
    "          2.08273698e-07,   1.87344523e-07,   1.63703500e-07,\n",
    "          1.37869309e-07,   1.11120277e-07,   8.64569185e-08,\n",
    "          6.59059683e-08,   4.95332916e-08,   3.70433346e-08,\n",
    "          2.74404981e-08,   2.04434070e-08,   1.54896441e-08,\n",
    "          1.21378868e-08,   9.97291256e-09,   8.51308568e-09,\n",
    "          7.41821013e-09,   6.61411826e-09,   5.95786854e-09,\n",
    "          5.33640193e-09,   4.72705901e-09,   4.18209989e-09,\n",
    "          3.59923398e-09,   3.03972761e-09,   2.54110466e-09,\n",
    "          2.11420249e-09,   1.73818067e-09,   1.44410727e-09,\n",
    "          1.16081550e-09,   9.36761032e-10,   7.76385942e-10,\n",
    "          6.58526750e-10,   5.62581388e-10,   4.95524509e-10,\n",
    "          4.62136925e-10,   4.14579522e-10,   4.02640302e-10,\n",
    "          3.91300897e-10,   3.52900340e-10,   3.59177371e-10,\n",
    "          4.74865558e-10,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan,              np.nan,              np.nan,\n",
    "                     np.nan]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-10T16:43:46.711157Z",
     "start_time": "2019-04-10T16:43:46.689331Z"
    }
   },
   "outputs": [],
   "source": [
    "# REFSC_30m = smcviz.scalings['WT-20150609-30m-R1']\n",
    "\n",
    "REFSC_30m = (\n",
    "    np.array([1060.0999999999999, 1188.0999999999999, 1332.0999999999999, 1493.0999999999999, 1673.5999999999999, 1876.0999999999999, 2103.0999999999999, 2357.5999999999999, 2643.0999999999999, 2963.0999999999999, 3321.5999999999999, 3723.0999999999999, 4173.1000000000004, 4678.1000000000004, 5244.1000000000004, 5878.6000000000004, 6589.6000000000004, 7386.6000000000004, 8280.1000000000004, 9281.6000000000004, 10404.6, 11663.1, 13073.6, 14655.1, 16427.599999999999, 18414.599999999999, 20642.099999999999, 23138.599999999999, 25937.099999999999, 29074.099999999999, 32591.099999999999, 36533.099999999999, 40951.599999999999, 45905.099999999999, 51457.599999999999, 57681.599999999999, 64658.100000000006, 72478.600000000006, 81245.100000000006, 91071.600000000006, 102087.10000000001, 114434.60000000001, 128275.60000000001, 143791.10000000001, 161182.60000000001, 180677.60000000001, 202531.10000000001, 227027.60000000001, 254486.59999999998, 285267.09999999998, 319770.59999999998, 358447.59999999998, 401802.59999999998, 450401.09999999998, 504877.59999999998, 565943.59999999998, 634395.59999999998, 711126.59999999998, 797138.09999999998, 893553.09999999998, 1001629.6000000001, 1122778.1000000001, 1258580.1000000001, 1410807.1000000001, 1581446.1000000001, 1772724.1000000001, 1987137.6000000001, 2227484.6000000001, 2496901.6000000001, 2798905.6000000001, 3137437.6000000001, 3516914.6000000001, 3942290.1000000001, 4419115.5999999996, 4953614.0999999996, 5552761.0999999996, 6224375.0999999996, 6977221.5999999996, 7821126.0999999996, 8767102.0999999996, 9827495.0999999996, 11016144.6, 12348562.6, 13842138.1, 15516364.1, 17393090.100000001, 19496808.600000001, 21854974.100000001, 24498363.100000001, 27461474.100000001, 30782977.600000001, 34506221.600000001, 38679796.600000001, 43358171.600000001, 48602402.600000001, 54480930.100000001, 61070474.100000001, 68457032.599999994, 76737005.599999994, 86018452.599999994, 96422503.099999994, 108084938.09999999, 121157961.09999999, 135812184.09999999, 152238855.09999999, 170652355.09999999, 191292993.59999999, 214430145.59999999, 240365768.09999999, 269438340.10000002, 302027280.10000002, 338557897.10000002, 379506942.60000002, 425408832.10000002, 476862618.60000002, 534539811.60000002, 599193140.60000002, 671666379.10000002, 752905356.10000002, 843970299.60000002, 946049674.60000002]),\n",
    "    np.array([23.675955871271874, 23.236626555421729, 23.066863635884847, 22.154452714571342, 21.467480284981807, 20.487367494245994, 19.160454706435878, 17.949003170166357, 16.415234568857386, 14.890233181524469, 13.327493418288194, 11.976836612759442, 10.512942407898162, 9.1349005029935775, 7.9085956321347277, 6.7569424618369842, 5.8690989848720863, 5.0640546842705909, 4.4052025303940123, 3.8904891247104438, 3.4631642433279706, 3.1253142884925431, 2.8047821378746551, 2.5578439264424477, 2.3630871716158621, 2.1790466537117612, 2.0246085517256325, 1.8838032175167119, 1.76475211641389, 1.6462896440262906, 1.5525393513441721, 1.4588544928495353, 1.3721372555187086, 1.3008301278520282, 1.2287831641991491, 1.1669889062227117, 1.1058944331413405, 1.0500554482960165, 1.0, 0.9626059154858434, 0.91474919296378132, 0.87982050546965485, 0.84226404486894413, 0.8089168077811949, 0.7769503867285813, 0.74647710200195516, 0.71588134711832496, 0.68697410529290193, 0.65871989693983068, 0.62731464238829537, 0.60027613270236702, 0.57514705963705059, 0.54615107057834789, 0.51976930440691971, 0.49090114734707713, 0.46307744679980578, 0.43447665458306117, 0.40687844130045864, 0.37938086283748018, 0.35114034378259634, 0.32291674469674325, 0.29463998972017813, 0.26751258897884228, 0.23995520669188192, 0.21396083423648307, 0.19011344601583471, 0.16718835632995099, 0.14709446687242295, 0.13021253723330545, 0.1160188918882349, 0.10670497929090897, 0.10111587113542761, 0.099641938724001289, 0.10259190796296001, 0.10912502769018932, 0.11637930652079441, 0.11998296048899362, 0.11298928603359318, 0.094577549712040562, 0.069578032765169537, 0.048057204280106222, 0.035223246097696274, 0.029000513382554206, 0.024373415309400931, 0.019243673691066811, 0.01462752889253496, 0.011302196219838108, 0.0091482940278357575, 0.0074610556191346883, 0.0061577877928047694, 0.0052151024960781353, 0.0044258888621608412, 0.0038571980326946318, 0.0033870834338773342, 0.0030387264655687874, 0.002745753811241077, 0.002526358711246568, 0.0023551346707166173, 0.002179804846088893, 0.0019746189904878185, 0.0017948425263511838, 0.0015583471819714605, 0.0012250967415409282, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-10T16:27:15.202108Z",
     "start_time": "2019-04-10T16:27:15.182928Z"
    }
   },
   "outputs": [],
   "source": [
    "REFSC_60m = np.array([\n",
    "    [1.06010000e+03, 1.18810000e+03, 1.33210000e+03, 1.49310000e+03, 1.67360000e+03, 1.87610000e+03, 2.10310000e+03, 2.35760000e+03, 2.64310000e+03, 2.96310000e+03, 3.32160000e+03, 3.72310000e+03, 4.17310000e+03, 4.67810000e+03, 5.24410000e+03, 5.87860000e+03, 6.58960000e+03, 7.38660000e+03, 8.28010000e+03, 9.28160000e+03, 1.04046000e+04, 1.16631000e+04, 1.30736000e+04, 1.46551000e+04, 1.64276000e+04, 1.84146000e+04, 2.06421000e+04, 2.31386000e+04, 2.59371000e+04, 2.90741000e+04, 3.25911000e+04, 3.65331000e+04, 4.09516000e+04, 4.59051000e+04, 5.14576000e+04, 5.76816000e+04, 6.46581000e+04, 7.24786000e+04, 8.12451000e+04, 9.10716000e+04, 1.02087100e+05, 1.14434600e+05, 1.28275600e+05, 1.43791100e+05, 1.61182600e+05, 1.80677600e+05, 2.02531100e+05, 2.27027600e+05, 2.54486600e+05, 2.85267100e+05, 3.19770600e+05, 3.58447600e+05, 4.01802600e+05, 4.50401100e+05, 5.04877600e+05, 5.65943600e+05, 6.34395600e+05, 7.11126600e+05, 7.97138100e+05, 8.93553100e+05, 1.00162960e+06, 1.12277810e+06, 1.25858010e+06, 1.41080710e+06, 1.58144610e+06, 1.77272410e+06, 1.98713760e+06, 2.22748460e+06, 2.49690160e+06, 2.79890560e+06, 3.13743760e+06, 3.51691460e+06, 3.94229010e+06, 4.41911560e+06, 4.95361410e+06, 5.55276110e+06, 6.22437510e+06, 6.97722160e+06, 7.82112610e+06, 8.76710210e+06, 9.82749510e+06, 1.10161446e+07, 1.23485626e+07, 1.38421381e+07, 1.55163641e+07, 1.73930901e+07, 1.94968086e+07, 2.18549741e+07, 2.44983631e+07, 2.74614741e+07, 3.07829776e+07, 3.45062216e+07, 3.86797966e+07, 4.33581716e+07, 4.86024026e+07, 5.44809301e+07, 6.10704741e+07, 6.84570326e+07, 7.67370056e+07, 8.60184526e+07, 9.64225031e+07, 1.08084938e+08, 1.21157961e+08, 1.35812184e+08, 1.52238855e+08, 1.70652355e+08, 1.91292994e+08, 2.14430146e+08, 2.40365768e+08, 2.69438340e+08, 3.02027280e+08, 3.38557897e+08, 3.79506943e+08, 4.25408832e+08, 4.76862619e+08, 5.34539812e+08, 5.99193141e+08, 6.71666379e+08, 7.52905356e+08, 8.43970300e+08, 9.46049675e+08],\n",
    "    [1.11674528e-05, 1.10282684e-05, 1.09980203e-05, 1.06884880e-05, 1.03712325e-05, 9.95821573e-06, 9.47413900e-06, 8.87913543e-06, 8.21672193e-06, 7.45318538e-06, 6.82834626e-06, 6.14048613e-06, 5.37048964e-06, 4.71935343e-06, 4.06989925e-06, 3.51089326e-06, 3.02076909e-06, 2.57435245e-06, 2.21909132e-06, 1.91879215e-06, 1.68308009e-06, 1.46757533e-06, 1.30174005e-06, 1.17126648e-06, 1.04734768e-06, 9.51688382e-07, 8.62266245e-07, 7.93401224e-07, 7.25596116e-07, 6.76413802e-07, 6.24958572e-07, 5.84692670e-07, 5.43564296e-07, 5.05236306e-07, 4.71761588e-07, 4.41920715e-07, 4.15568895e-07, 3.92503100e-07, 3.70347541e-07, 3.50564659e-07, 3.33628688e-07, 3.17393189e-07, 3.03657569e-07, 2.90687400e-07, 2.78146055e-07, 2.66326586e-07, 2.55340097e-07, 2.45048634e-07, 2.35155466e-07, 2.25754918e-07, 2.15531712e-07, 2.06851814e-07, 1.97710816e-07, 1.89624627e-07, 1.80552323e-07, 1.71415055e-07, 1.62620001e-07, 1.53768791e-07, 1.44083593e-07, 1.35276642e-07, 1.26636339e-07, 1.17637592e-07, 1.08375348e-07, 9.94187099e-08, 9.04282429e-08, 8.17490821e-08, 7.35160607e-08, 6.52278835e-08, 5.76475407e-08, 5.06953599e-08, 4.44968908e-08, 3.94321523e-08, 3.47959158e-08, 3.12136029e-08, 2.85296416e-08, 2.67930020e-08, 2.59793418e-08, 2.59996532e-08, 2.65096650e-08, 2.68270629e-08, 2.62755234e-08, 2.43076446e-08, 2.07729648e-08, 1.64369050e-08, 1.22358304e-08, 8.92005709e-09, 6.91674313e-09, 5.68891892e-09, 4.89137781e-09, 4.16687997e-09, 3.59501755e-09, 3.15501512e-09, 2.85019840e-09, 2.60398008e-09, 2.42504006e-09, 2.27515440e-09, 2.16693084e-09, 2.04621298e-09, 1.86925166e-09, 1.73855477e-09, 1.57095274e-09, 1.31108423e-09, 9.11974699e-10,            np.nan, np.nan,            np.nan,            np.nan,            np.nan, np.nan,            np.nan,            np.nan,            np.nan, np.nan,            np.nan,            np.nan,            np.nan, np.nan,            np.nan,            np.nan,            np.nan, np.nan]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-13T21:51:41.612172Z",
     "start_time": "2017-07-13T21:51:41.485286Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def prepare_canvas(refsc = REFSC_10m, exp_loop_size=EXP_LOOP_SIZE):\n",
    "    fig, ax = plt.subplots(1,2, figsize=(8,3.5))\n",
    "    plt.subplots_adjust(bottom=0.15, wspace=0.3)\n",
    "    ln1 = ax[0].plot([], [], label='test')\n",
    "\n",
    "    ax[0].set_xlim(MIN_LOG10_S,MAX_LOG10_S)\n",
    "    ax[0].set_ylim(-3,1)\n",
    "    ax[0].set_xticks(np.arange(MIN_LOG10_S,MAX_LOG10_S+0.01))\n",
    "    ax[0].axvline(0.0, ls='--', c='gray',lw=0.5)\n",
    "    ax[0].set_aspect(1.0)\n",
    "    ax[0].set_xlabel('log10 separation/avg loop length')\n",
    "    ax[0].set_ylabel('log10 contact frequency')\n",
    "\n",
    "    if refsc is not None:\n",
    "        x = refsc[0] / exp_loop_size\n",
    "        y = refsc[1]\n",
    "        y /= y[np.argmin(np.abs(np.log10(x/GLUE_AT)))]\n",
    "\n",
    "        ax[0].plot(\n",
    "            np.log10(x),\n",
    "            np.log10(y)\n",
    "        )\n",
    "    else:\n",
    "        ax[0].plot(\n",
    "            [],\n",
    "            []\n",
    "        )\n",
    "    \n",
    "    \n",
    "    ln2 = ax[1].plot([], [], label='test')\n",
    "    ax[1].set_xlim(MIN_LOG10_S,MAX_LOG10_S)\n",
    "    ax[1].set_ylim(-3,1)\n",
    "    ax[1].set_aspect(1.0)\n",
    "    ax[1].axvline(0.0, ls='--', c='gray',lw=0.5)\n",
    "    ax[1].axhline(0.0, ls='--', c='gray',lw=0.5)\n",
    "    ax[1].axhline(-0.5, ls='--', c='gray',lw=0.5)\n",
    "    ax[1].axhline(-3/2, ls='--', c='gray',lw=0.5)\n",
    "    ax[1].set_xlabel('log10 separation/avg loop length')\n",
    "    ax[1].set_ylabel('log-log derivative')\n",
    "    \n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-27T15:45:29.345598Z",
     "start_time": "2017-07-27T15:45:28.649721Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "118ed68b50c84a09acabe5fecb07d2ef"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = prepare_canvas(REFSC_7m)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    min_log10_s=MIN_LOG10_S, max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "    \n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "    \n",
    "    \n",
    "    between_loop_scaling = between_loop_scaling_z\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "    cp =  np.exp(-s) * in_loop_scaling + (1-np.exp(-s))* between_loop_scaling\n",
    "    \n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio):\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            )\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=1.6,\n",
    "        min=-1, \n",
    "        max=4)\n",
    "    interact(update_scalings, z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio)\n",
    "    \n",
    "plot_interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bottle brush with RW angular loop orientation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## No drift"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-05-26T20:56:05.048759",
     "start_time": "2017-05-26T20:56:05.029247"
    }
   },
   "source": [
    "A bottlebrush with angular correlations of loops.\n",
    "- Below the loop size the scaling is calculated as s^-3/2.\n",
    "- Above the loop size, contact probability is the probability for two particles to have the same z-component and same angle.\n",
    "    - The probability of an overlap in z is calculated as in (1).\n",
    "    - The angular orientations of loops perform a RW, the probability of an overlap == the return probability.\n",
    "    - The 2nd slider sets $log10 (RW\\_step\\_in\\_radians / 2 \\pi ) $\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-06-21T16:52:58.995957Z",
     "start_time": "2017-06-21T16:52:58.986644Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-08-06T00:43:39.620133Z",
     "start_time": "2017-08-06T00:43:39.261856Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "32fa39ab3e2a449f9b1a9a01849e8bde"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =prepare_canvas(REFSC_CAPH2_R1_30m,80000)\n",
    "#fig, ax =prepare_canvas(REFSC_7m,60000)\n",
    "\n",
    "#fig, ax =prepare_canvas(REFSC_CAPH1_R2_60m, 200000)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    ang_rw_step,\n",
    "    ang_loop_spread,\n",
    "    min_log10_s=MIN_LOG10_S, \n",
    "    max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "\n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "    \n",
    "    between_loop_scaling_ang = np.vstack(\n",
    "        st.norm.pdf(x , loc=0, scale=np.sqrt(2*ang_loop_spread**2+s*(ang_rw_step**2)))\n",
    "        for x in 2*np.pi*np.arange(-100,100+0.1)\n",
    "        ).sum(axis=0)\n",
    "\n",
    "    between_loop_scaling = between_loop_scaling_z * between_loop_scaling_ang\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "    cp =  np.exp(-s) * in_loop_scaling + (1-np.exp(-s)) * between_loop_scaling\n",
    "\n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio,ang_rw_step,ang_loop_spread):\n",
    "        ang_rw_step = 2 * np.pi * (10**ang_rw_step)\n",
    "        ang_loop_spread = 2 * np.pi * (10**ang_loop_spread)\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            ang_rw_step,\n",
    "            ang_loop_spread\n",
    "            )\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=1.4, #WT-7m 6kb\n",
    "        #value=1.4,\n",
    "        min=-4, \n",
    "        max=4)\n",
    "    widget_ang_rw_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=-1.1, #WT-7m 6kb\n",
    "        #value=-1.1,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "    widget_ang_loop_spread = widgets.FloatSlider(\n",
    "        description='log10 (ang_loop_spread / 2 Pi)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=-1.7, #WT-7m 60kb\n",
    "        #value=-1.3,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "    interact(\n",
    "        update_scalings, \n",
    "        z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio,\n",
    "        ang_rw_step=widget_ang_rw_step,\n",
    "        ang_loop_spread=widget_ang_loop_spread\n",
    "    )\n",
    "    ax[0].set_ylim(-1.5,1.5)\n",
    "    ax[0].set_xlim(-1,3)\n",
    "    #plt.savefig(f'{FIG_FOLDER}/coarse_grained_RW_scaling_7m_60kb.svg')\n",
    "    \n",
    "plot_interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-05-26T13:24:03.332250",
     "start_time": "2017-05-26T13:24:03.324858"
    }
   },
   "source": [
    "## With drift"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-05-26T21:05:23.418338",
     "start_time": "2017-05-26T21:05:23.408531"
    }
   },
   "source": [
    "A bottlebrush with angular correlations and drift of loops.\n",
    "- Same as (2), but with a drift component.\n",
    "    - The 3rd slider sets $log10 (angular\\_drift\\_per\\_loop\\_in\\_radians / 2 \\pi ) $. The inverse of this number is the period of the spiral in loops.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-27T15:49:49.118205Z",
     "start_time": "2017-07-27T15:49:48.769603Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4c20f51de2fa4f2ea49ae7b5448f6ada"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =prepare_canvas(REFSC_30m)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    ang_rw_step,\n",
    "    ang_drift_step,\n",
    "    min_log10_s=MIN_LOG10_S, \n",
    "    max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "\n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "\n",
    "    between_loop_scaling_ang = np.vstack(\n",
    "        st.norm.pdf(x , loc=ang_drift_step*s, scale=ang_rw_step*np.sqrt(s))\n",
    "        for x in 2*np.pi*np.arange(-100,100+0.1)\n",
    "    ).sum(axis=0)\n",
    "\n",
    "    between_loop_scaling = between_loop_scaling_ang * between_loop_scaling_z\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "\n",
    "    cp =  np.exp(-s) * in_loop_scaling + (1-np.exp(-s)) * between_loop_scaling\n",
    "\n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio,ang_rw_step,ang_drift_step):\n",
    "        ang_rw_step = 2 * np.pi * (10**ang_rw_step)\n",
    "        ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            ang_rw_step,\n",
    "            ang_drift_step,\n",
    "            )\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=1.8,\n",
    "        min=-4, \n",
    "        max=4)\n",
    "    widget_ang_rw_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=-1.4,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "    widget_ang_drift_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_drift_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=-2.0,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "\n",
    "    interact(\n",
    "        update_scalings, \n",
    "        z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio,\n",
    "        ang_rw_step=widget_ang_rw_step,\n",
    "        ang_drift_step=widget_ang_drift_step)\n",
    "    \n",
    "\n",
    "plot_interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bottle brush with OU angular loop orientation (approximate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A bottlebrush with angular correlations of loops.\n",
    "- Below the loop size the scaling is calculated as s^-3/2.\n",
    "- Above the loop size, contact probability is the probability for two particles to have the same z-component and same angle.\n",
    "    - The probability of an overlap in z is calculated as in (1).\n",
    "    - The angular orientations of loops perform a contrained random walk with a drift (trending Ornstein Uhlenbeck process). The probability of an overlap == the return probability.\n",
    "    - The 2nd slider sets log10 standard deviation of angular spread for loops emanating from the same anchor / $2\\pi$.\n",
    "    - The 3nd slider sets log10 characteristic length scale of angular loop correlations (in number of loops)\n",
    "    - The 4th slider sets $log10 (angular\\_drift\\_per\\_loop\\_in\\_radians / 2 \\pi ) $. The inverse of this number is the period of the spiral in loops.\n",
    "\n",
    "\n",
    "References:\n",
    "- trending Ornstein-Uhlenbeck (http://web.mit.edu/wangj/www/pap/LoWang95.pdf, page 35)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-08-06T23:13:11.426964Z",
     "start_time": "2017-08-06T23:13:10.805411Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf1ba9dec27c4581818f887a8cacf9a9"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =prepare_canvas(REFSC_60m, 80000)\n",
    "#fig, ax =prepare_canvas(REFSC_30m, 80000)\n",
    "#fig, ax =prepare_canvas(REFSC_CAPH1_R2_30m, 200000)\n",
    "#fig, ax =prepare_canvas(REFSC_CAPH1_R2_60m, 200000)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    ang_rw_step,\n",
    "    ang_loop_spread,\n",
    "    ang_drift_step,\n",
    "    ang_rw_return_scale,\n",
    "    min_log10_s=MIN_LOG10_S, \n",
    "    max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "\n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "    between_loop_scaling_z /= between_loop_scaling_z[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "          \n",
    "    between_loop_scaling_ang = np.vstack(\n",
    "        st.norm.pdf(x , \n",
    "                    loc=ang_drift_step*s, \n",
    "                    scale=np.sqrt(2*ang_loop_spread**2\n",
    "                                  +\n",
    "                                  (ang_rw_step**2)*(1-np.exp(-s/ang_rw_return_scale)) * ang_rw_return_scale )\n",
    "                   )\n",
    "        for x in 2*np.pi*np.arange(-100,100+0.1)\n",
    "    ).sum(axis=0)\n",
    "    \n",
    "    between_loop_scaling = between_loop_scaling_ang * between_loop_scaling_z\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "    cp = np.exp(-s) * in_loop_scaling + (1-np.exp(-s)) * between_loop_scaling\n",
    "\n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio,ang_rw_stat_std,ang_rw_return_scale,ang_loop_spread,ang_drift_step):\n",
    "        ang_rw_stat_std = 2 * np.pi * (10**ang_rw_stat_std)\n",
    "        ang_rw_return_scale = 10 ** (ang_rw_return_scale)\n",
    "        ang_loop_spread = 2 * np.pi * (10**ang_loop_spread)\n",
    "        ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "        ang_rw_step = ang_rw_stat_std * np.sqrt(ang_rw_return_scale)\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            ang_rw_step,\n",
    "            ang_loop_spread,\n",
    "            ang_drift_step,\n",
    "            ang_rw_return_scale\n",
    "            )\n",
    "\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        #value=1.65, #WT-30m\n",
    "        value=1.75, #WT-60m\n",
    "        #value=1.57, #CAPH1-R2-30m 200kb\n",
    "        #value=1.30, #CAPH1-R2-30m 400kb\n",
    "        min=-4, \n",
    "        step=0.025,\n",
    "        max=4)\n",
    "    widget_ang_rw_stat_std = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_stat_std / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        #value=-1.7, #WT-30m,\n",
    "        value=-1.65, #WT-60m\n",
    "        #value=-1.45, #CAPH2-30m\n",
    "        #value=-1.4, #CAPH2-R2-30m 400kb\n",
    "        min=-2, \n",
    "        step=0.025,\n",
    "\n",
    "        max=0)\n",
    "    widget_ang_loop_spread = widgets.FloatSlider(\n",
    "        description='log10 (ang_loop_spread / 2 Pi)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        #value=-1.4, #WT-30m\n",
    "        value=-1.675, #WT-60m\n",
    "        #value=-1.1, #CAPH1-R2-30m 200kb\n",
    "        #value=-0.9, #CAPH1-R2-30m 400kb\n",
    "        min=-4, \n",
    "        max=0)\n",
    "    widget_ang_rw_return_scale = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_return_scale)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        #value=1.15, #WT-30m\n",
    "        value=1.05, #WT-60m\n",
    "        #value=1.00, #CAPH1-R2-30m 200kb\n",
    "        #value=0.95, #CAPH1-R2-30m 400kb\n",
    "        \n",
    "\n",
    "        step=0.025,\n",
    "        \n",
    "        min=0, \n",
    "        max=4)\n",
    "    widget_ang_drift_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_drift_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        step=0.025,\n",
    "        \n",
    "        #value=-1.975, #WT-30m\n",
    "        value=-2.15, #WT-60m\n",
    "        #value=-1.7, #CAPH1-R2-30m 200kb\n",
    "        #value=-1.425, #CAPH1-R2-30m 400kb\n",
    "        min=-4, \n",
    "        max=0)\n",
    "\n",
    "    interact(\n",
    "        update_scalings, \n",
    "        z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio,\n",
    "        ang_rw_stat_std=widget_ang_rw_stat_std,\n",
    "        ang_loop_spread=widget_ang_loop_spread,\n",
    "        ang_rw_return_scale=widget_ang_rw_return_scale,\n",
    "        ang_drift_step=widget_ang_drift_step)\n",
    "\n",
    "    ax[0].set_ylim(-2,1)\n",
    "    ax[0].set_xlim(-1,3)\n",
    "    #plt.savefig(f'{FIG_FOLDER}/coarse_grained_RW_scaling_WT-30m-80kb.svg')\n",
    "    #plt.savefig(f'{FIG_FOLDER}/coarse_grained_RW_scaling_WT-60m-80kb.svg')\n",
    "    #plt.savefig(f'{FIG_FOLDER}/coarse_grained_RW_scaling_CAPH1-R2-30m-200kb.svg')\n",
    "\n",
    "    \n",
    "\n",
    "plot_interactive()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimental"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-04T03:35:38.072280Z",
     "start_time": "2017-07-04T03:35:38.029228Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-04T03:55:46.332312Z",
     "start_time": "2017-07-04T03:55:46.291926Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def simulate_trending_ou(\n",
    "    N, ang_rw_stat_std,ang_rw_return_scale,ang_loop_spread,ang_drift_step):\n",
    "    \n",
    "    ang_rw_stat_std = 2 * np.pi * (10**ang_rw_stat_std)\n",
    "    ang_rw_return_scale = 10 ** (ang_rw_return_scale)\n",
    "    ang_loop_spread = 2 * np.pi * (10**ang_loop_spread)\n",
    "    ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "    ang_rw_step = ang_rw_stat_std * np.sqrt(ang_rw_return_scale)\n",
    "    \n",
    "    angles = [0]\n",
    "    for i in range(1,N):\n",
    "        new_ang = angles[i-1] + ang_drift_step - (angles[i-1] - ang_drift_step * i) / ang_rw_return_scale + np.random.normal(scale=ang_rw_step)\n",
    "        angles.append(new_ang)\n",
    "        \n",
    "    return angles\n",
    "        \n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-04T03:56:06.866708Z",
     "start_time": "2017-07-04T03:56:06.830419Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0771791515585\n"
     ]
    }
   ],
   "source": [
    "ang_rw_stat_std = -1.675\n",
    "ang_rw_return_scale = 1.125\n",
    "ang_loop_spread = -1.3\n",
    "ang_drift_step = -1.975\n",
    "\n",
    "# ang_rw_stat_std = -1.75\n",
    "# ang_rw_return_scale = 1.38\n",
    "# ang_loop_spread = -0.7\n",
    "# ang_drift_step = -1.77\n",
    "\n",
    "ang_rw_stat_std = 2 * np.pi * (10**ang_rw_stat_std)\n",
    "ang_rw_return_scale = 10 ** (ang_rw_return_scale)\n",
    "ang_loop_spread = 2 * np.pi * (10**ang_loop_spread)\n",
    "ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "\n",
    "ang_rw_step = ang_rw_stat_std * np.sqrt(ang_rw_return_scale)\n",
    "print(ang_rw_step / 2 / np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "ang_rw_stat_std = 2 * np.pi * (10**ang_rw_stat_std)\n",
    "ang_rw_return_scale = 10 ** (ang_rw_return_scale)\n",
    "ang_loop_spread = 2 * np.pi * (10**ang_loop_spread)\n",
    "ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "\n",
    "ang_rw_step = ang_rw_stat_std * np.sqrt(ang_rw_return_scale)\n",
    "print(ang_rw_step / 2 / np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-04T03:55:48.356214Z",
     "start_time": "2017-07-04T03:55:48.062921Z"
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       "   </g>\n",
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       "    <path d=\"M 49.744594 115.92 \n",
       "L 49.744594 7.2 \n",
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       "   </g>\n",
       "   <g id=\"patch_4\">\n",
       "    <path d=\"M 217.144594 115.92 \n",
       "L 217.144594 7.2 \n",
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       "   </g>\n",
       "   <g id=\"patch_5\">\n",
       "    <path d=\"M 49.744594 115.92 \n",
       "L 217.144594 115.92 \n",
       "\" style=\"fill:none;stroke:#262626;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n",
       "   </g>\n",
       "   <g id=\"patch_6\">\n",
       "    <path d=\"M 49.744594 7.2 \n",
       "L 217.144594 7.2 \n",
       "\" style=\"fill:none;stroke:#262626;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n",
       "   </g>\n",
       "  </g>\n",
       " </g>\n",
       " <defs>\n",
       "  <clipPath id=\"p6978e90c3e\">\n",
       "   <rect height=\"108.72\" width=\"167.4\" x=\"49.744594\" y=\"7.2\"/>\n",
       "  </clipPath>\n",
       " </defs>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe8a5828080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize=(3,2))\n",
    "angles = np.array(simulate_trending_ou(\n",
    "    N=200, \n",
    "    ang_rw_stat_std=-1.675,\n",
    "    ang_rw_return_scale=1.125,\n",
    "    ang_loop_spread=-1.3,\n",
    "    ang_drift_step=-1.975,\n",
    "    ))\n",
    "plt.plot(\n",
    "    angles\n",
    ")\n",
    "plt.yticks(np.arange(0,3)*2*np.pi, [('{}π'.format(i) if i>0 else '0') for i in 2*np.arange(0,4) ] )\n",
    "plt.ylabel('loop angle α')\n",
    "plt.xlabel('loop index')\n",
    "\n",
    "    \n",
    "#plt.savefig(f'{FIG_FOLDER}/coarse_grained_OURW_example_loop_angles.pdf',\n",
    "#             bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-06-21T17:00:14.037764Z",
     "start_time": "2017-06-21T17:00:13.808296Z"
    }
   },
   "outputs": [
    {
     "data": {
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Cx4nmvkFW11cAMK8qMprDyv1qd3g41NVPc98gPf3eUIPBRbUl7Gxx8n5TH6fPK2fLdy/i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\nVjSNJgloRdNoksD/B0U3Tstpcj+wAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f341f2874e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "rw_step = 0.1*np.pi\n",
    "plt.figure(figsize=(3,2))\n",
    "angles = np.pi+ np.cumsum(np.random.normal(scale=rw_step,size=200))\n",
    "plt.plot(\n",
    "    angles\n",
    ")\n",
    "plt.yticks(np.arange(0,3)*2*np.pi, [('{}π'.format(i) if i>0 else '0') for i in 2*np.arange(0,4) ] )\n",
    "plt.ylabel('loop angle α')\n",
    "plt.xlabel('loop index')\n",
    "plt.ylim(0,2*np.pi)\n",
    "\n",
    "    \n",
    "#plt.savefig(f'{FIG_FOLDER}/coarse_grained_RW_example_loop_angles.pdf',\n",
    "#             bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-06-21T17:00:41.732765Z",
     "start_time": "2017-06-21T17:00:41.501757Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Pe4joAQCNQojtmdSeMaJsNFNSHclhE4PsfPyM9du7YBC5Xsxb5vkjzaLW0YBg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\nLmg5ctQB/wd2DZkkjKwPQQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f341f396b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize=(3,2))\n",
    "angles = np.array(np.random.random(200)*2*np.pi)\n",
    "plt.plot(\n",
    "    angles\n",
    ")\n",
    "plt.yticks(np.arange(0,2)*2*np.pi, [('{}π'.format(i) if i>0 else '0') for i in 2*np.arange(0,4) ] )\n",
    "plt.ylabel('loop angle α')\n",
    "plt.xlabel('loop index')\n",
    "plt.ylim(0,2*np.pi)\n",
    "\n",
    "    \n",
    "#plt.savefig(f'{FIG_FOLDER}/coarse_grained_random_example_loop_angles.pdf',\n",
    "#             bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize=(4,2))\n",
    "angles = np.array(simulate_trending_ou(200,-1.675, 1.125, -1.3, -1.975))\n",
    "full_circle_points = np.r_[0, 1+np.where(angles[1:] // (2 * np.pi) != angles[:-1] // (2 * np.pi))[0], len(angles)]\n",
    "for i,j in zip(full_circle_points[:-1], full_circle_points[1:]):\n",
    "    plt.plot(\n",
    "        np.arange(i,j), \n",
    "        np.mod(angles[i:j], 2*np.pi)\n",
    "    )\n",
    "plt.yticks(np.arange(0,3)*2*np.pi, [('{}π'.format(i) if i>0 else '0') for i in 2*np.arange(0,4) ] )\n",
    "plt.ylabel('loop angle α')\n",
    "plt.ylim(0,2*np.pi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-06-16T21:31:34.585522Z",
     "start_time": "2017-06-16T21:31:34.579515Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([51])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(i,j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-06-16T21:30:48.391981Z",
     "start_time": "2017-06-16T21:30:48.385697Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  4   7  13  17  30  52  53  55  56  62  64  66  67  69  70  72  80  82\n",
      "  91 102 104 117 118 119 120 135 136 138 146 148 150 157 165 171 182 193\n",
      " 195 196]\n"
     ]
    }
   ],
   "source": [
    "print(full_circle_points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-05-26T17:59:47.925480",
     "start_time": "2017-05-26T17:59:47.909067"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# MIN_LOG10_S = -1\n",
    "# MAX_LOG10_S = 4\n",
    "\n",
    "# Z_LOOP_WIDTH = 50\n",
    "# Z_LOOP_STEP = 1\n",
    "# PERIOD_LOOPS = 100\n",
    "\n",
    "# ANG_RW_STAT_STD = 2 * np.pi / 3\n",
    "# ANG_RW_RETURN_COEFF = 1.0/30\n",
    "\n",
    "# ANG_DRIFT_STEP = 2 * np.pi / PERIOD_LOOPS\n",
    "# ANG_RW_STEP = ANG_RW_STAT_STD * np.sqrt(ANG_RW_RETURN_COEFF)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Bottle brush with random angular loop orientation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple bottlebrush w/o angular correlations of loops.\n",
    "- Below the loop size the scaling is calculated as s^-3/2.\n",
    "- Above the loop size, contact probability is the probability for two particles to have the same z-component.\n",
    "    - The z-coordinates of the particles of a loop are normally distributed around the z-coordinate of its base with $\\sigma$.\n",
    "    - The z-coordinate of a loop base is incremented by $\\delta$.\n",
    "    - The slider sets $log10(\\sigma / \\delta)$\n",
    "\n",
    "References: \n",
    "-- an overlap of two gaussians: http://www.tina-vision.net/docs/memos/2003-003.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-27T15:51:38.387751Z",
     "start_time": "2017-07-27T15:51:37.984140Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2d4cb0250ec5463f999747f06fbff465"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =prepare_canvas(REFSC_CAPH1_R2_30m)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    ang_rw_step,\n",
    "    ang_drift_step,\n",
    "    ang_rw_return_scale,\n",
    "    min_log10_s=MIN_LOG10_S, \n",
    "    max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "\n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "    \n",
    "    \n",
    "    between_loop_scaling_ang = np.vstack(\n",
    "        st.norm.pdf(x , \n",
    "                    loc=ang_drift_step*s, \n",
    "                    scale=np.sqrt(\n",
    "                        ang_loop_spread**2\n",
    "                        +\n",
    "                        (ang_rw_step**2)*(ang_rw_return_scale**2)*(1-np.exp(-s/ang_rw_return_scale)))\n",
    "                   )\n",
    "        for x in 2*np.pi*np.arange(-100,100+0.1)\n",
    "    ).sum(axis=0)\n",
    "    \n",
    "    between_loop_scaling =  between_loop_scaling_ang * between_loop_scaling_z\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "    cp = np.exp(-s) * in_loop_scaling + (1-np.exp(-s)) * between_loop_scaling\n",
    "\n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio,ang_rw_stat_std,ang_rw_return_scale,ang_drift_step):\n",
    "        ang_rw_stat_std = 2 * np.pi * (10**ang_rw_stat_std)\n",
    "        ang_rw_return_scale = 10 ** (ang_rw_return_scale)\n",
    "        ang_drift_step = 2 * np.pi * (10**ang_drift_step)\n",
    "        ang_rw_step = ang_rw_stat_std * np.sqrt(ang_rw_return_scale)\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            ang_rw_step,\n",
    "            ang_drift_step,\n",
    "            ang_rw_return_scale\n",
    "            )\n",
    "\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=1.65,\n",
    "        min=-4, \n",
    "        step=0.025,\n",
    "        max=4)\n",
    "    widget_ang_rw_stat_std = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_stat_std / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=-1.675,\n",
    "        min=-2, \n",
    "        step=0.025,\n",
    "\n",
    "        max=0)\n",
    "    widget_ang_rw_return_scale = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_return_scale)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        value=1.125,\n",
    "        step=0.025,\n",
    "        \n",
    "        min=0, \n",
    "        max=4)\n",
    "    widget_ang_drift_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_drift_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='75%', height='80px'),\n",
    "        step=0.025,\n",
    "        \n",
    "        value=-1.975,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "\n",
    "    interact(\n",
    "        update_scalings, \n",
    "        z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio,\n",
    "        ang_rw_stat_std=widget_ang_rw_stat_std,\n",
    "        ang_rw_return_scale=widget_ang_rw_return_scale,\n",
    "        ang_drift_step=widget_ang_drift_step)\n",
    "    \n",
    "ax[0].plot([0,3],[0.5,-1])\n",
    "plot_interactive()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-07-27T15:46:44.363863Z",
     "start_time": "2017-07-27T15:46:44.055621Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8f4ad1e9eb5e4493a91c6ab2eebc367f"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =prepare_canvas(REFSC_CAPH2_R2_30m, 60000)\n",
    "\n",
    "def get_simple_bb_scaling(\n",
    "    z_loop_width_step_log10_ratio,\n",
    "    ang_rw_step,\n",
    "    min_log10_s=MIN_LOG10_S, \n",
    "    max_log10_s=MAX_LOG10_S):\n",
    "    \n",
    "    s = 10**np.linspace(MIN_LOG10_S,MAX_LOG10_S,1000)\n",
    "\n",
    "    in_loop_scaling = s**(-3/2)\n",
    "\n",
    "    between_loop_scaling_z = (\n",
    "        st.norm.pdf(s, loc=0, scale=np.sqrt(2)*(10**z_loop_width_step_log10_ratio))    )\n",
    "    \n",
    "    between_loop_scaling_ang = np.vstack(\n",
    "        st.norm.pdf(x , loc=0, scale=ang_rw_step*np.sqrt(s))\n",
    "        for x in 2*np.pi*np.arange(-100,100+0.1)\n",
    "        ).sum(axis=0)\n",
    "    \n",
    "    between_loop_scaling = between_loop_scaling_z * between_loop_scaling_ang\n",
    "    \n",
    "    in_loop_scaling /= in_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "    between_loop_scaling /= between_loop_scaling[np.argmin(np.abs(np.log10(s/GLUE_AT)))]\n",
    "\n",
    "    cp =  np.exp(-s) * in_loop_scaling + (1-np.exp(-s))* between_loop_scaling\n",
    "\n",
    "    return s, cp\n",
    "\n",
    "def plot_interactive():\n",
    "    \n",
    "    def update_scalings(z_loop_width_step_log10_ratio,ang_rw_step):\n",
    "        ang_rw_step = 2 * np.pi * (10**ang_rw_step)\n",
    "        s,cp = get_simple_bb_scaling(\n",
    "            z_loop_width_step_log10_ratio,\n",
    "            ang_rw_step,\n",
    "            )\n",
    "        ax[0].lines[0].set_data(np.log10(s), np.log10(cp))\n",
    "\n",
    "        ax[1].lines[0].set_data(\n",
    "            (np.log10(s)[1:] + np.log10(s)[:-1])/2,\n",
    "            np.diff(np.log10(cp)) / np.diff(np.log10(s))\n",
    "        )\n",
    "        \n",
    "        \n",
    "    widget_z_loop_width_step_log10_ratio = widgets.FloatSlider(\n",
    "        description='log10(z_loop_spread/step)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=1.9,\n",
    "        min=-4, \n",
    "        max=4)\n",
    "    widget_ang_rw_step = widgets.FloatSlider(\n",
    "        description='log10 (ang_rw_step / 2 Pi)',\n",
    "        layout=widgets.Layout(width='50%', height='80px'),\n",
    "        value=-2.4,\n",
    "        min=-4, \n",
    "        max=0)\n",
    "    interact(\n",
    "        update_scalings, \n",
    "        z_loop_width_step_log10_ratio=widget_z_loop_width_step_log10_ratio,\n",
    "        ang_rw_step=widget_ang_rw_step)\n",
    "    \n",
    "plot_interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": "true"
   },
   "source": [
    "# Table of Contents\n",
    " <p><div class=\"lev1\"><a href=\"#Bottle-brush-with-RW-angular-loop-orientation\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Bottle brush with RW angular loop orientation</a></div><div class=\"lev2\"><a href=\"#No-drift\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>No drift</a></div><div class=\"lev2\"><a href=\"#With-drift\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>With drift</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-OU-angular-loop-orientation-(approximate)\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Bottle brush with OU angular loop orientation (approximate)</a></div><div class=\"lev1\"><a href=\"#Experimental\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Experimental</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-random-angular-loop-orientation\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Bottle brush with random angular loop orientation</a></div>"
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    " <p><div class=\"lev1\"><a href=\"#Bottle-brush-with-RW-angular-loop-orientation\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Bottle brush with RW angular loop orientation</a></div><div class=\"lev2\"><a href=\"#No-drift\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>No drift</a></div><div class=\"lev2\"><a href=\"#With-drift\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>With drift</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-OU-angular-loop-orientation-(approximate)\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Bottle brush with OU angular loop orientation (approximate)</a></div><div class=\"lev1\"><a href=\"#Experimental\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Experimental</a></div><div class=\"lev1\"><a href=\"#Bottle-brush-with-random-angular-loop-orientation\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Bottle brush with random angular loop orientation</a></div>"
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