{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summary\n",
    "\n",
    "<p class='lead'>\n",
    "Compute the optical crosstalk in two 48-pixel SPAD arrays from the 48-spot smFRET-PAX setup.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Find the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'data/2017-10-16_00_DCR.hdf5'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fname = 'data/2017-10-16_00_DCR.hdf5'\n",
    "fname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "assert Path(fname).is_file(), 'File not found.'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2017-10-16_00_DCR'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlabel = Path(fname).stem\n",
    "mlabel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load software"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from itertools import combinations\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.rcParams['font.sans-serif'].insert(0, 'Arial')\n",
    "plt.rcParams['font.size'] = 14\n",
    "from tqdm import tnrange, tqdm_notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " - Optimized (cython) burst search loaded.\n",
      " - Optimized (cython) photon counting loaded.\n",
      "--------------------------------------------------------------\n",
      " You are running FRETBursts (version 0.6.5).\n",
      "\n",
      " If you use this software please cite the following paper:\n",
      "\n",
      "   FRETBursts: An Open Source Toolkit for Analysis of Freely-Diffusing Single-Molecule FRET\n",
      "   Ingargiola et al. (2016). http://dx.doi.org/10.1371/journal.pone.0160716 \n",
      "\n",
      "--------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from fretbursts import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mon Oct 30 16:50:38 2017'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import time\n",
    "time.ctime()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def coincidence_py(timestamps1, timestamps2):\n",
    "    coinc = 0\n",
    "    i1, i2 = 0, 0\n",
    "    while (i1 < timestamps1.size) and (i2 < timestamps2.size):\n",
    "        if timestamps1[i1] == timestamps2[i2]:\n",
    "            coinc += 1\n",
    "            i1 += 1\n",
    "            i2 += 1\n",
    "        elif timestamps1[i1] > timestamps2[i2]:\n",
    "            i2 += 1\n",
    "        elif timestamps1[i1] < timestamps2[i2]:\n",
    "            i1 += 1\n",
    "    return coinc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%cython\n",
    "cimport numpy as np\n",
    "\n",
    "def coincidence(np.int64_t[:] timestamps1, np.int64_t[:] timestamps2):\n",
    "    cdef np.int64_t coinc, i1, i2, size1, size2\n",
    "    size1 = timestamps1.size\n",
    "    size2 = timestamps2.size\n",
    "    coinc = 0\n",
    "    i1, i2 = 0, 0\n",
    "    while i1 < size1 and i2 < size2:\n",
    "        if timestamps1[i1] == timestamps2[i2]:\n",
    "            coinc += 1\n",
    "            i1 += 1\n",
    "            i2 += 1\n",
    "        elif timestamps1[i1] > timestamps2[i2]:\n",
    "            i2 += 1\n",
    "        elif timestamps1[i1] < timestamps2[i2]:\n",
    "            i1 += 1\n",
    "    return coinc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def crosstalk_probability(t1, t2, tol=1e-6, max_iter=100):\n",
    "    \"\"\"Estimate crosstalk probability between two pixels in a SPAD array.\n",
    "    \n",
    "    Given two input arrays of timestamps `t1` and `t2`, estimate \n",
    "    the crosstalk probability using Poisson statistics without \n",
    "    approximations.\n",
    "    \n",
    "    Arguments:\n",
    "        t1, t2 (array of ints): arrays of timestamps from DCR measurements\n",
    "            for the two pixels to be measured. Timestamps need to be \n",
    "            integers and coincidences are detected when values in the two \n",
    "            arrays are equal. These arrays need to be rescaled, if \n",
    "            coincidence need to be computed on a delta t larger than \\\n",
    "            a single timestamp unit.\n",
    "        tol (float): tollerance for iterative equasion solution\n",
    "        max_iter (int): max iterations used to solve the equation\n",
    "        \n",
    "    Returns:\n",
    "        A 3-element tuple:\n",
    "        - crosstalk probability\n",
    "        - crosstalk probability standard deviation\n",
    "        - number of iterations used for the estimation.\n",
    "    \"\"\"\n",
    "    T = (max((t1.max(), t2.max())) - min((t1.min(), t2.min())))\n",
    "    C = coincidence(t1, t2)\n",
    "    \n",
    "    # Find C_c by solving eq. (1) iteratively\n",
    "    C_c, C_u_prev = 0, 0\n",
    "    for i in range(max_iter):\n",
    "        C_u = ((1 - np.exp(-(t1.size - C_c)/T)) * \n",
    "               (1 - np.exp(-(t2.size - C_c)/T)) * T)\n",
    "        C_c = C - C_u\n",
    "        if np.abs(C_u - C_u_prev) < tol:\n",
    "            break\n",
    "        C_u_prev = C_u\n",
    "    \n",
    "    P_c = C_c / (t1.size + t2.size - C_c)\n",
    "    if C_c <= 0:\n",
    "        sigma = np.nan\n",
    "    else:\n",
    "        sigma = np.sqrt(C_c) / (t1.size + t2.size - C_c)\n",
    "    return P_c, sigma, i\n",
    "\n",
    "def crosstalk(dx, spot1, spot2, divide=1, det=0):\n",
    "    \"\"\"\n",
    "    Calculate the crosstalk between two pixels in a SPAD array for data object, dx. \n",
    "    \n",
    "    Arguments:\n",
    "        spot1, spot2 (ints): pixel pair for\n",
    "            combinations possible in 48 spots. The pixel pair \n",
    "            tuple needs to be intergers. The optical crosstalk \n",
    "            across pixels is computed for a pair of pixels. \n",
    "        divide (int): integer division of timestamps by `divide` are the\n",
    "            timestamps used for coincidence counting.\n",
    "            `divide` rescales the timestamps so that adjacent timestamps\n",
    "            become the same timestamp after division.\n",
    "        det (int): 0, 1 for D, A SPADs respectively. \n",
    "        \n",
    "    Returns:\n",
    "        A 3-element tuple:\n",
    "        - A float corresponding to optical crosstalk between the\n",
    "          selected pixels in the D/A SPAD array.\n",
    "        - A float corresponding to the standard deviation of optical crosstalk\n",
    "          between the selected pixels in the D/A SPAD array.\n",
    "        - A float indicating the probability of optical crosstalk between\n",
    "          selected pixels.\n",
    "    \"\"\"\n",
    "    ph1 = dx.ph_times_m[spot1][dx.detectors[spot1] == det] // divide\n",
    "    ph2 = dx.ph_times_m[spot2][dx.detectors[spot2] == det] // divide\n",
    "    delta_t = d.clk_p*divide\n",
    "    if ph1.size == 0 or ph2.size == 0:\n",
    "        return np.nan, np.nan, 0\n",
    "    ct, sigma, i = crosstalk_probability(ph1, ph2)\n",
    "    return ct, sigma, i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def dist(manta_shape, ich1, ich2):\n",
    "    \"\"\"Compute distance between two pixels on the SPAD array.\n",
    "    \"\"\"\n",
    "    row1, col1 = np.where(manta_shape == ich1)\n",
    "    row2, col2 = np.where(manta_shape == ich2)\n",
    "    del_x = abs(col2 - col1) \n",
    "    del_y = abs(row2 - row1)\n",
    "    dist = float(np.sqrt((del_x)**2 + (del_y)**2)) #multipy by 500 to convert to microns\n",
    "    return(dist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def savefig(fname, **kwargs):\n",
    "    \"\"\"Save figure with default arguments.\"\"\"\n",
    "    import os\n",
    "    basename = os.path.basename(fname)\n",
    "    dir_ = f'figures/{mlabel}_'\n",
    "    kwargs_ = dict(dpi=180, bbox_inches='tight', \n",
    "                   frameon=True, facecolor='white', transparent=False)\n",
    "    kwargs_.update(kwargs)\n",
    "    plt.savefig(dir_ + basename, **kwargs_)\n",
    "    print('Saved: ', dir_ + basename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d = loader.photon_hdf5(fname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DCR timetrace for spot 31 of D-SPAD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1+EcUxGOBrlpDJ+niKs5uZppJp+8ArVaauQnaSNKquHxfj3/kdjxfwkdvXYrv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\nIiIiIiIiGUDBXBEREREREREREZEM8P8B2Zy+g/TM4pAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xce7d0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "spot = 31\n",
    "det = 0\n",
    "ph = d.ph_times_m[spot][d.detectors[spot] == det] * d.clk_p\n",
    "counts, bins = np.histogram(ph, bins=np.arange(0, d.time_max, 5))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(24, 4))\n",
    "ax.plot(bins[1:], counts, label='Det %d, spot %d' % (det, spot))\n",
    "plt.legend()\n",
    "display(fig)\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6846745,)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.detectors[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6846745,)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.ph_times_m[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[47, 35, 23, 11],\n",
       "       [46, 34, 22, 10],\n",
       "       [45, 33, 21,  9],\n",
       "       [44, 32, 20,  8],\n",
       "       [43, 31, 19,  7],\n",
       "       [42, 30, 18,  6],\n",
       "       [41, 29, 17,  5],\n",
       "       [40, 28, 16,  4],\n",
       "       [39, 27, 15,  3],\n",
       "       [38, 26, 14,  2],\n",
       "       [37, 25, 13,  1],\n",
       "       [36, 24, 12,  0]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "manta_shape = np.arange(48).reshape(4, 12)[::-1].T[::-1]\n",
    "manta_shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compute crosstalk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **NOTE**: With `combinations(range(48), 2)` we generate all the **unique** combinations (i.e. no permutations) of 48 pixel IDs. \n",
    "> See [itertools.combinations](https://docs.python.org/3.6/library/itertools.html#itertools.combinations) for more info.\n",
    "\n",
    "We start by computing all paris of pixels (`pix_pairs`) and all the distances for all the pairs of pixels (`distances`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pix_pairs = []\n",
    "distances = []\n",
    "for ich1, ich2 in combinations(range(48), 2):\n",
    "    pix_pairs.append((ich1, ich2))\n",
    "    distances.append(dist(manta_shape, ich1, ich2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we compute the crosstalk for all pairs of pixes on both arrays.\n",
    "Results are stored in two DataFrame (i.e. tables) called `pairdata0` and `pairdata1` \n",
    "for donor and acceptor detector respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def compute_crosstalk_detector(det):\n",
    "    xtalk_err_list = []\n",
    "    for ich1, ich2 in tqdm_notebook(combinations(range(48), 2), total=len(distances), \n",
    "                                    desc=f'Det. {det}', leave=True):\n",
    "        res = crosstalk(d, ich1, ich2, divide=4, det=det)\n",
    "        xtalk_err_list.append(res)\n",
    "        if res[2] > 50:\n",
    "            print('i', ich1, ich2, flush=True)\n",
    "        if np.isnan(res[1]):\n",
    "            print(f'  W: Crosstalk for detector {det} pair {ich1}, {ich2} is NaN.', flush=True)\n",
    "\n",
    "    xtalk_err_array = np.array(xtalk_err_list)\n",
    "    pairdata =  pd.DataFrame(columns=['crosstalk', 'distance', 'error'])\n",
    "    pairdata['crosstalk'] = xtalk_err_array[:, 0]        \n",
    "    pairdata['error'] = xtalk_err_array[:, 1]\n",
    "    pairdata['distance'] = distances\n",
    "    pairdata['pix1'] = np.array(pix_pairs)[:,0]\n",
    "    pairdata['pix2'] = np.array(pix_pairs)[:,1]\n",
    "    return pairdata\n",
    "\n",
    "def compute_crosstalk_both_dectectors(recompute=False):\n",
    "    res = []\n",
    "    for det in (0, 1):\n",
    "        fname_crosstalk = f'results/{mlabel}_crosstalk_data_detector{det}.csv'\n",
    "        if Path(fname_crosstalk).exists():\n",
    "            print(f'- Loading crosstalk for detector {det} from cache', flush=True)\n",
    "            pairdata = pd.read_csv(fname_crosstalk, index_col=0)\n",
    "        else:\n",
    "            print(f'- Computing crosstalk for detector {det}', flush=True)\n",
    "            pairdata = compute_crosstalk_detector(det)  \n",
    "            pairdata.to_csv(fname_crosstalk)\n",
    "        res.append(pairdata)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Loading crosstalk for detector 0 from cache\n",
      "- Loading crosstalk for detector 1 from cache\n"
     ]
    }
   ],
   "source": [
    "pairdata0, pairdata1 = compute_crosstalk_both_dectectors(recompute=False)\n",
    "pairdata = pairdata1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crosstalk</th>\n",
       "      <th>distance</th>\n",
       "      <th>error</th>\n",
       "      <th>pix1</th>\n",
       "      <th>pix2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000772</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.481646e-05</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000014</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.193197e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000007</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.729624e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000002</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.092910e-07</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000010</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.699850e-06</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   crosstalk  distance         error  pix1  pix2\n",
       "0   0.000772       1.0  1.481646e-05     0     1\n",
       "1   0.000014       2.0  2.193197e-06     0     2\n",
       "2   0.000007       3.0  2.729624e-06     0     3\n",
       "3   0.000002       4.0  8.092910e-07     0     4\n",
       "4   0.000010       5.0  3.699850e-06     0     5"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pairdata.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Crosstalk vs distance')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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s4fVNEUqDwWBoMxdL5n0MKNS0lbcjrbrI+ZbNjwXqtyfWdEydwWAwtIeLRbDkWSxAytu1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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xce7d438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pairdata.plot(x='distance', y='crosstalk', kind='scatter', alpha=0.3, marker='H', s=30,\n",
    "               logy=True, ylim=(2e-8, 10e-3));\n",
    "plt.ylabel(u'crosstalk prob.')\n",
    "plt.xlabel(u'Distance (unit = 500 μm)')\n",
    "plt.title('Crosstalk vs distance')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Optical crosstalk between pixels is maximal at shorter distances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0011385712427402512, 0.001042788265769392)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pairdata0.crosstalk.max(), pairdata1.crosstalk.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Optical crosstalk along the x,y axes is determined by selecting a pair of neighboring pixels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Probability $\\\\times \\\\; 10^{-3}$')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RG5I6rbInSWx3WadpZSiPer22iujVldfFQrf2CipXK6CXjn+znzOv45Il3/Xj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\nzrlceEBxzjmXCw8ozjnncvH/MEbUyCt6BYYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18e55898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist = 1\n",
    "mask = pairdata['distance'] == dist\n",
    "plt.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H')\n",
    "plt.title('Crosstalk ($\\pm 3\\sigma$), pair distance = %.1f pixels' % dist);\n",
    "plt.ylabel(r'Probability $\\times \\; 10^{-3}$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Optical crosstalk along the diagonal is determined by selecting a pair of cater-cornered pixels and calculating the distance along the diagonal with the Pythagorian Theorem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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S1o5WAxO+eNqGQ05QeeStgbR6PPHkieOHPIfl6L235eJfPjAk6IzVJp/G59OM\n9LTNUw6YwTdvmz9k39WC+vEX3/7cND+1M79mv63ayMP1aoWkDx78so623+6xaVxu6crV7Pvp60ft\nYKR578PZUtI5km6QdFP2+oWk20n35Yx5veyy2NijKY9uaiDtlIiq0FwwqFx76b1mv61xggkNBbmy\nC0mjvSk6by+1rwEHAbcAewO/JF3LeQXw0WKSZu30aMqr1xed2z1pdtNk2O9rYM0Ulaax3rW415r9\nttYE69wPVXYhabQ3RecNOK8C3hkRHwHuBr4fEW8jBZtDi0rcWNdOj6a8yqiBjHTSbHUd6abfL1on\nCPUyuLj79tjT6rf15t226mvNslW6Npw0oXKFqzzyBhwBD2f/30eq2QB8C9gj1walSZIulPSkpEcl\nfaiNdWZJmt9k+u8lRcNr1zzp6qd2ejRBvhNmGTWQZuoDR7Pmg6UrV3Pi12d3fSd+u4q6898GS6vf\n1qfe8pd9rVm2+5sfVHkDzhzSqAIAdwEHZ/+/uIu0nA3sS2qqOxk4XdJRrRaW9HLgKhq+Q9ZpYQfg\nlcCWda97ukhbX7TTo6mbrpzNaiD1Aea935jDCZeue/Iv6l6aZs0HK1YHK1YPnVbUdStov2dSUZ9n\n1VTV62TN0vW+A3fkgceXDCn0DWqtvJNHTNf7MPB9SUuBS4EPSvot8GfAZZ1uTNIU4ETgsIiYA8yR\ndBZwCnBFk+VPBj4H3A80FkFeSupsckdENBsNYaCM1Nul1UXGj1z9a+Y+9iwAH7jiTo7a80UjflZj\nz53rfvPoOssUeQGzWU+2ZmrXrbbZbIOuPq+TnklFfF67aicPeP5Y+ZpN71W1l199us48/OXr9Fq7\n4XePEYin2+jJ1thDst9y1XAi4hZgW+AbEbEYmAmcQxpH7b05NrkLMAm4uW7azcAekpoFxdeSalhf\nbDJvJ+D+0RBs2tHqIuM1dy7ouJmoWfBqVOQFzGbNB5MmiPV7dN2qk55JRXxeO6o8IkMrVeys0Uv9\n/L7N8uwzy1ezZMXqIdOaFQSrWAvK26RGRDwbEQslbQ48ExHnRsQVETF8cbW5LUnP1FleN20hMJHn\nnzJa/9lvjYirW2xrJ2CNpB9m14J+LmmvHGkaCM0uMo4X69yns2TFau5d8PSwma9Z8GrU655sFx4z\nk/V71IbdSc+kstrMB60bbBVPYqNRbUy0Vnl2dUOebSwIVrUgU5Xn4WwANPb1rb3vtKj558CmwHnA\nG0idGq6XtF2zhSWdJGm2pNmLFi1qtkilNaslrG2SIVeuCZatWjts5msWvBr1uifba166xYjXrfLq\npGdS4+f16kTbz26wnQ70WNXqQcrWAAAPHElEQVST2GjWqkA50v1CVS3IVOV5OMtZN7DU3i/tcFvv\nAF4aEddFxK+A9wB/5PlODkNExIURMTMiZk6btk5lqjC9OmE1qyW8adetRgwczTJfs+C14aTxbLZB\nMRdW290H3dyDMlzzR96eSe2eaHs5Nl3e7RepqiexQTdc4G+WZ1+w/gSmTBp6paGxIFjV+3mq8jyc\nh4FNJU2smzadVMt5opMNRcSqiPhT3fsA/pfUoaEvet31tvEE/anDX75OJm3ULPM1C15fPW4Pdnxh\n/m6itR9TFUrHeXsmtXOi7fXYdFXovl30SazdayODcM2ozALlBcfM5MIR8nFVRxOvyvNw7srW27du\n2ixgTkSsbr5Kc5Jul/ThuvfjgL8kBZ2+KHKImnYydmMmfckWU5g4vr3M16s73LspHRf5Y87z/do5\n0XY7Nt1IQbDbPFTESbuqJ7F29SpwlV2g3GuHzUfMx1UdWqoSz8OJiFr36vMk7SnpjaTmui9lnz1d\nUrtXcb9P6qb9BkkvJT0uYTPScDx9UdQQNZ2Uousz5DWnzGKDif3NfHlLx1WoGbVzou312HS9HOZo\nOPUn6W5PYnlO+P1uRmxHL8c8rOn0eltV7zMq4nk4j5I6DnT7PJxTgTuA64HzgTMi4sps3iPAkW1u\n50zg3GwbdwEvAQ6MiKdzpqtrRQ1R0+tSdC/lLR1X4bpBOyfaXpf+eznMUbuKzEftBJIqFDba0a/C\nwEiqOB5ft8/D2ZU0lM3epHtxcj8PJyKWRsRxEbFhRGwVEZ+vm6eIuKTJOpdExNYN09ZExMcj4kUR\nMTki9o+I3+RJU1GKGq6i16XoXspbOm71nS/+5bx1TlhltqM3nmh73YTRTR7Ku1+arZc3H+UZwaIK\nhY12VKEw0EqzmlE/r4m1HXAi4sHai1TjOA2YDdxOGjX6VuCMbJ7VaWeImpoiHl1bRXlLx82+86QJ\nYs3aGHLCOvmy2ZxUcjt6Ed+vXZ3koXp5awnDrddtd+rrfvMoz7Zx42JVe1o1Gu3jnxUpb6eBzwOH\nAIcBm5CGl3kz6aL/p4pJ2mAoo6tvzXCl6E5PAv2QZx80+84AajjPtrr7uswx0Xpdi8yz/by1hCJr\nF3lHsOi2gFVWST5vYaAf+n1NLG/AOQo4ISJ+FBHPRMRTEfFfpPHQji4uedXWTRtzL0d4Hk2afefx\n48axvM27r5u1ow9CcC5K3lpCkbWLvCNYVLWnVTP9brJuRxWuieUNOOOAx5tMXwxsmD85g2WkgTNb\nBZOiR3ge7Rq/8/H7btf23ddVaEfvp7y1hCKbb/OOYDHaClj9rl1U4ZpY3oDzM+CzkjauTZC0CfBp\nUi+zMaGTgTPrg0kVDvwg6+Tu67Hejp63llBk7aKbESyK6KRQhe7UVahdVOGaWN6A8wFSd+OHJd0l\n6S7gIWAr0iMFxoR2B85sDCZVOPBFK/MH3snd171uR6/6XfB5awlF1i56MYLFcKowKkOjXhQyO20a\nrkKno1zPw4mIhyXtTOo48DLSWGi/BX6aDSUzJpxywAy+edv8IcFjbUDjLqgFkz/fciOg+XNgagd+\n9rwny0l8gZo9Z6bV8zmKunbS6lkmVXy+Sb/lfe5Lkc+L6WZbneaZ4W7ELOIZR3meXzRcIfODB7+s\n6zS1o9n5qlZrLauZMlfAkXQR8JmI+B7wvWKTNDhqJbf3fONXALx6x6kE8KN7Hx02mLQ68HttvzlX\n3P5/wGA9iGu40ltZPyYbXt5AX+R6jdN61XFjuBsxe/EQv1rhajjDFTLL0ux8ddSeLyr1mljeJrXD\ngWrd7tsn7Qyc2dj23ayJ4d+O3JX3/eedlb+rupnR2ESYV2MzR9nXEqp27aIfirwRs91Hko/UNFaV\nHnf97nTUzeMJzpd0iKSd6sdZy8ZaG7PabftuPPC3PfDEwHYkqELbcBWVfaG4Chemq6CoGzGb7c9r\n71qQq3BVpR53/bwtIG/AOYP0mOcfAPfw/BhrtfHWxrRejUhcVVUpvUG17rEpuzeiez8mRd2I2ckj\nydspXPW7dlEFeQPO9g2v+jHWxnQNJ69BriVUqfRWJWUXIga50FK0xpM70HFTYyePJK/izahV1FGn\nAUl/A/w16cFo10bEFT1J1Rg0XA+S4y++Pdc2e1nSb9x2kT2a2vm8QVB2b8QqXJiuklqeKfpC/yF/\nMZ2bfp/ue+/HhfdB1snzcD4MXAJMJo0mcKmkMTVuWi+5ljB4RrpAX3ZTY5WaNqskb1Nj3keSW2ud\nNKmdRBo/7ZCIOAx4O/D3UuMwipaX23iroahntZRdiHChpbm8TY3en8XrpEltG9KQNjXfA6YAWwIL\nikyUWb+02/zS7r1HrZoae9VE2OumzUHUTdOm92exOqnhTABW1d5ExGpgGbB+0Yky65d2m1/KuEBf\npR53g8xNjdWRt5ea2ajUbiAZ5F6FY42bxqqj06Ft3i7pmbr344EjJC2qXygivtZ1ykYhl1aL1Yv9\n2W7zy3C9Cq23aoOldnL83TRWDZ0EnPnA+xumLQTe1TAtAAcca1uVAnG73dOrMC4VVGvfmY2k7YAT\nEdv1MB2W8QmkvzoJJC41V4d/N4Mh12jRZqOZA0l15Xk0gFWHA46Nai75jh6dPHfJqsm91MxsIHhw\n0sHnGo5Zm1xb6q8qPDXTuuOAY+vwidWqyIOTDj4HnB7xSXtsKOo4O7+MzPc+DT5fwzGzgeARAwaf\nazh9VIVSbRXSYO0b68erjC7rY30f95IDzgDwD8Bs8Ph3uy43qZmZWSlcwzGzgVJkzcG1kHI54Fhh\n/OO10cj5ujgOOGY2Jjhw9J+v4ZiZWSkccMzMrBRuUrNKKrv5w80tZr3ngGMj8sm4O95/o4+PaT4O\nOGZmJRnrgcrXcMzMrBSu4QygsV5KMrPB5IAzhjhQmfWOf18jq0yTmqRJki6U9KSkRyV9qI11Zkma\n32T6/pJ+LWmppBslzehNqs3MrF2VCTjA2cC+wEHAycDpko5qtbCklwNX0fAdJG0DfA+4HJgJPApc\nK6lK39XMbMypxElY0hTgROD9ETEnIq4FzgJOabH8ycD/AAubzD4RuDsizoqI+4C/BbYBDuhJ4s3M\nrC2VCDjALsAk4Oa6aTcDe0hqdp3ptcCxwBebzNsbuKn2JiKWAr8C3MBqZtZHVQk4WwJPRMTyumkL\ngYnAtMaFI+KtEXH1MNta0DBtIbB1EQk1M7N8qhJwNgBWNEyrvZ9U0LaabkfSSZJmS5q9aNGiDj/K\nzMzaVZWAs5x1A0Lt/dKCttV0OxFxYUTMjIiZ06atU5kyM7OCVOU+nIeBTSVNjIiV2bTppJrJEzm2\nNb1h2nTgnu6S2Jr735uZjawqNZy7gJWkbtE1s4A5EbG6w23dmq0LgKQNgN2y6WZm1ieVCDhZT7JL\ngfMk7SnpjcBpwJcAJE2XNLnNzX0N2EvSRyXtBHwVmA/8rAdJNzOzNlUi4GROBe4ArgfOB86IiCuz\neY8AR7azkYiYBxwOHAPMBl4IvCki1hadYDMza19VruHUajnHZa/GeWqxziXAJU2m/xD4YbEpNDOz\nblQm4JhZMdyJxaqqSk1qZmY2ijngmJlZKRxwzMysFA44ZmZWCgccMzMrhXupmTXhnl5mxXMNx8zM\nSuGAY2ZmpXDAMTOzUjjgmJlZKRxwzMysFA44ZmZWCgccMzMrhQOOmZmVwgHHzMxKoYjodxoqQ9Ii\n4MGcq08FHi8wOdYe7/f+8H4vX5X3+bYRMW2khRxwCiJpdkTM7Hc6xhrv9/7wfi/faNjnblIzM7NS\nOOCYmVkpHHCKc2G/EzBGeb/3h/d7+QZ+n/sajpmZlcI1HDMzK4UDjpmZlcIBp0uSJkm6UNKTkh6V\n9KF+p2k0kvRiSddl+/khSZ+XtH42b1tJP5a0RNJvJR3S7/SONpIuknRj3ftdJN0iaamkOZL26GPy\nRhVJ60n6gqTHJS2W9GVJk7J5A53XHXC6dzawL3AQcDJwuqSj+puk0UXSROA6YAVpX/8N8GbgTEkC\nrgUWA3sAlwLfkbR9n5I76kg6EDih7v0U4IfArcDuwC+AH0h6QX9SOOqcDRwOvAk4DDgE+NhoyOvu\nNNCF7If3OHBYRPw0m3Y68PqImNXXxI0ikmYB1wObRcSz2bR3AF8A3gH8ANgiIp7J5v0UuDUiTu9T\nkkeNLI//GngEWB0R+0n6W+DjwPYRsTY7Ef4e+GxEXNTH5A48SZsAC4FDI+In2bTjgSNJgWig87pr\nON3ZBZgE3Fw37WZgD0kT+pOkUel3wBtqwSYTpH2/N3Bn7QeYuRnYp8T0jWZnAjdmr5q9gV9GxFqA\nSKXWX+J9XoRZwDLgp7UJEXFJRBzCKMjrDjjd2RJ4IiKW101bCEwERhxXyNoTEYtqNUgASeOAU0hN\nOVsCCxpWWQhsXV4KRydJ+wBHAKc1zPI+750XA/OAt0u6V9KDkj6XNSsP/H53Kbw7G5CuK9SrvZ9U\nclrGki8Au5HasU+l+THw/u9CdpH6q8D7I+LJ1Gr2nFb53vu8ey8AtgfeS7om/ALgy6Rz9cDvdwec\n7ixn3YNde7+05LSMetm1gn8D3gO8NSLulbQc2Lhh0Ul4/3fr/wF/iIhvN5nXKt97n3dvNbARcHRE\n/BFA0mnAZcAlDHhed8DpzsPAppImRsTKbNp0Uqnjif4la/TJmtG+SuqhdmREXJvNeph0La3edNJF\nbsvvHcCWkmrXzSYC47P33yTt43re58VYQOqc8ce6ab8D1gceBV7esPxA7Xdfw+nOXcBKUlfdmlnA\nnIhY3Z8kjVqfJ50ED4+I79ZNvxXYNetNVTMrm2757Qf8BbBr9voKMDv7/1Zg36zGWat57ov3eRFu\nASZIqg8sOwHPZPMGOq+7W3SXJJ0PvBo4nlTauAw4KSKu7Ge6RhNJe5N+bP9Malaot4jUbfc+4BPA\noaTmoJ0jYl5piRzlJH0SmJV1i94ImAt8CzgPOJFUGJjR0IPKcpB0DakjwMmk6zZfB74LfIgBz+uu\n4XTvVOAO0n0i5wNnONgU7q3Z30+Tmg/qXyLdILcFMAc4FnjLoPwAB1FE/An4K1Kt5lfAK0nd1h1s\ninEMKbBcD1wDXA38U0SsYcDzums4ZmZWCtdwzMysFA44ZmZWCgccMzMrhQOOmZmVwgHHzMxK4YBj\nZmalcMAxM7NSOOCYmVkp/j+SSoFOeWqWEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b46c358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist = np.sqrt(2)\n",
    "mask = pairdata['distance'] == dist\n",
    "plt.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H')\n",
    "plt.title('Crosstalk ($\\pm 3\\sigma$), pair distance = %.1f pixels' % dist);\n",
    "plt.ylabel(r'Probability $\\times \\; 10^{-3}$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, optical crosstalk along the x,y axes is calculated for a pair of pixels separated by a distance equal to two pixels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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q+otKyg/INBtWPGjUrD71jsPZTtJ5km6W9Pvs8QdJfyKNyzEbtjxo1Kw+9XaL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\nHDMza4n/D2cw7yWpQpivAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11923d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist = 2\n",
    "mask = pairdata['distance'] == dist\n",
    "plt.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H')\n",
    "plt.title('Crosstalk ($\\pm 3\\sigma$), pair distance = %.1f pixels' % dist);\n",
    "plt.ylabel(r'Probability $\\times \\; 10^{-3}$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Crosstalk vs chip position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def pixel_rowcol_to_ch(d, row, col):\n",
    "    detectors = d.setup['detectors']\n",
    "    i = np.where((detectors['position'] == (row, col)).sum(axis=1) == 2)[0][0]\n",
    "    ich = detectors['spot'][i]\n",
    "    return ich\n",
    "\n",
    "def pixel_ch_to_rowcol(d, ich):\n",
    "    detectors = d.setup['detectors']\n",
    "    ich = np.where(detectors['spot'] == ich)\n",
    "    pix_pos = detectors['position'][ich][0]\n",
    "    return pix_pos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def pair_coord(pix1, pix2):\n",
    "    \"\"\"\n",
    "    Returns (i, j) position in the expanded `a` array used to generate \n",
    "    heatmap of optical crosstalk for a pair of pixels \n",
    "    `pix1` and `pix2` (pixel ids, [0, 47]).\n",
    "    \"\"\"\n",
    "    v1 = pixel_ch_to_rowcol(d, pix1)\n",
    "    v2 = pixel_ch_to_rowcol(d, pix2)\n",
    "    return (v1[0] + v2[0]), (v1[1] + v2[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7, 23)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nshape = len(manta_shape[0,:])*2 - 1, len(manta_shape[:,1])*2 - 1\n",
    "nshape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXsAAACMCAYAAACd3gkeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nL0kNMOwlqQGGvSQ1wLCXpAb8H70hW8hjvfLZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b553c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a = np.zeros(nshape)\n",
    "a[1::2, 1::2] = np.nan\n",
    "a[0::2, 0::2] = np.nan\n",
    "plt.imshow(a, interpolation='none', cmap='YlGnBu')\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Opitcal crosstalk calculated for pixels of distance  $d=1$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crosstalk</th>\n",
       "      <th>distance</th>\n",
       "      <th>error</th>\n",
       "      <th>pix1</th>\n",
       "      <th>pix2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000772</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.000893</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.000892</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.000913</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.000958</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    crosstalk  distance     error  pix1  pix2\n",
       "0    0.000772       1.0  0.000015     0     1\n",
       "11   0.000893       1.0  0.000036     0    12\n",
       "47   0.000892       1.0  0.000013     1     2\n",
       "58   0.000913       1.0  0.000016     1    13\n",
       "93   0.000958       1.0  0.000018     2     3"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist = 1\n",
    "\n",
    "mask = pairdata['distance'] == dist\n",
    "pairdata_d1 = pairdata.loc[mask]\n",
    "pairdata_d1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for p, pair in pairdata_d1.iterrows():\n",
    "    i, j = pair_coord(pair.pix1, pair.pix2)\n",
    "    a[j, i] = pair.crosstalk\n",
    "    #print(i, j, pair.pix1, pair.pix2, pair.crosstalk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Opitcal crosstalk calculated for cater-corner pixels of distance $d=2^{1/2}$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crosstalk</th>\n",
       "      <th>distance</th>\n",
       "      <th>error</th>\n",
       "      <th>pix1</th>\n",
       "      <th>pix2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.000140</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.000138</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.000146</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>0.000139</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.000134</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1033</th>\n",
       "      <td>0.000151</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>33</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>0.000195</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>33</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1047</th>\n",
       "      <td>0.000148</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>34</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1049</th>\n",
       "      <td>0.000139</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>34</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
       "      <td>0.000163</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>35</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      crosstalk  distance     error  pix1  pix2\n",
       "12     0.000140  1.414214  0.000014     0    13\n",
       "57     0.000138  1.414214  0.000006     1    12\n",
       "59     0.000146  1.414214  0.000006     1    14\n",
       "103    0.000139  1.414214  0.000007     2    13\n",
       "105    0.000134  1.414214  0.000003     2    15\n",
       "...         ...       ...       ...   ...   ...\n",
       "1033   0.000151  1.414214  0.000004    33    44\n",
       "1035   0.000195  1.414214  0.000011    33    46\n",
       "1047   0.000148  1.414214  0.000002    34    45\n",
       "1049   0.000139  1.414214  0.000001    34    47\n",
       "1060   0.000163  1.414214  0.000008    35    46\n",
       "\n",
       "[66 rows x 5 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist = np.sqrt(2)\n",
    "\n",
    "mask = pairdata['distance'] == dist\n",
    "pairdata_diag = pairdata.loc[mask]\n",
    "pairdata_diag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for p, pair in pairdata_diag.iterrows():\n",
    "    i = pair_coord(pair.pix1, pair.pix2)[0]\n",
    "    j = pair_coord(pair.pix1, pair.pix2)[1]\n",
    "    a[j, i] = pair.crosstalk\n",
    "    #print(i, j, pair.pix1, pair.pix2, pair.crosstalk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[11, 10,  9,  8,  7,  6,  5,  4,  3,  2,  1,  0],\n",
       "       [23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12],\n",
       "       [35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24],\n",
       "       [47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = manta_shape.T[::-1]\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PP3bvxLJ+/Xqvr6Xt6HXp0iUmTJhAeno62dnZzJ49mz59+njUZSUvMOb2ww8/cPXqVfeN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\nNxgMBoPBYDAYXMD/B1y+vZlz6AwTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1bc32cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 3.5))\n",
    "xs = np.arange(12)\n",
    "ys = np.repeat(np.arange(4)[np.newaxis,:].T, xs.size, axis=1)\n",
    "plt.plot(xs, ys.T, 'o', ms=20, mew=1, mec='k', color='white')\n",
    "im = plt.imshow(a*1e2, interpolation='none', cmap='Blues', vmin=0, vmax=0.15,\n",
    "                extent=(-0.25, 11.25, -0.25, 3.25))\n",
    "for row in range(4):\n",
    "    for col in range(12):\n",
    "        ax.text(col+0.01, row-0.01, str(m[row,col]), va='center', ha='center', fontsize=12)\n",
    "im.cmap.set_under(alpha=0)\n",
    "plt.colorbar()\n",
    "plt.xticks(range(12))\n",
    "plt.yticks(range(4))\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Crosstalk figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def reflection_distance(dist, thickness=1):\n",
    "    return np.sqrt((dist/2)**2 + thickness*2)*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved:  figures/2017-10-16_00_DCR_crosstalk_both_detectors\n"
     ]
    },
    {
     "data": {
      "image/png": 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Qutp1J1QqDTKz0wo6l7uvdvfe7n6Mu3d29zdLJejIoGfmsnTd1lxpS9dtZdAz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OwsF110EUePHiUUCtXNpkqn01iWRSgU0vlTlmXt6Ujncrl0NlU2m9WZWOqYXC6X7kLn8XiQUuqS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\n1XXPA41iKrujUgz7jddczh98/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ym6jSm/B9wlhPh94GnK34RrpJRPdrjd36EcWvtyYBm4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\niIiISMP8/0DxvOOGJIBjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1be6df60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, AX = plt.subplots(2, 3, figsize=(20, 10), sharex='col', sharey='col')\n",
    "ax1a = AX[0, 0]\n",
    "ax2a = AX[0, 1]\n",
    "ax3a = AX[0, 2]\n",
    "ax1d = AX[1, 0]\n",
    "ax2d = AX[1, 1]\n",
    "ax3d = AX[1, 2]\n",
    "plt.subplots_adjust(hspace=0.1, wspace=0.3)\n",
    "\n",
    "xtext, ytext = 0.95, 0.95\n",
    "font_kw = dict(fontsize=26, va='top', ha='right')\n",
    "\n",
    "pairdata = pairdata1\n",
    "ax1a.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance == 1], alpha=0.3, s=30, c='C0')\n",
    "ax1a.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance == np.sqrt(2)], alpha=0.3, s=30, c='C1')\n",
    "ax1a.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance > np.sqrt(2)], alpha=0.2, s=30, c='grey')\n",
    "ax1a.set_yscale('log')\n",
    "ax1a.set_ylim(2e-7, 2e-3)\n",
    "ax1a.set_ylabel(r'Crosstalk Probability')\n",
    "#ax1a.set_xlabel(u'Distance (unit = 500 μm)')\n",
    "ax1a.set_title('Crosstalk vs distance')\n",
    "ax1a.text(xtext, ytext, 'A', transform=ax1a.transAxes, **font_kw)\n",
    "x = np.unique(pairdata.distance)\n",
    "A = pairdata.loc[pairdata.distance == 1, 'crosstalk'].mean()\n",
    "y = A / x**2\n",
    "ax1a.plot(x, y, ls='--', color='k')\n",
    "ax1a.text(0.5, 0.58, r'$\\propto R^{-2}$', transform=ax1a.transAxes, fontsize=24)\n",
    "# A = pairdata.loc[pairdata.distance == np.sqrt(2), 'crosstalk'].mean() * 2\n",
    "# y = A / x**2\n",
    "# ax1a.plot(x, y, ls='--', color='k')\n",
    "# A = 3e-3\n",
    "# y = A / reflection_distance(x)**2\n",
    "# ax1a.plot(x, y, ls='-', color='k')\n",
    "\n",
    "dist = 1\n",
    "mask = pairdata['distance'] == dist\n",
    "ax2a.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H', color='C0')\n",
    "ax2a.set_title('Horizontal/vertical pairs');\n",
    "ax2a.set_ylabel(r'Crosstalk Probability $\\times \\; 10^{-3}$')\n",
    "#ax2a.set_xlabel('Pixel pair')\n",
    "ax2a.text(xtext, ytext, 'B', transform=ax2a.transAxes, **font_kw)\n",
    "\n",
    "dist = np.sqrt(2)\n",
    "mask = pairdata['distance'] == dist\n",
    "ax3a.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H', color='C1')\n",
    "ax3a.set_title('Diagonal pairs');\n",
    "ax3a.set_ylabel(r'Crosstalk Probability $\\times \\; 10^{-3}$')\n",
    "#ax3a.set_xlabel('Pixel pair')\n",
    "ax3a.text(xtext, ytext, 'C', transform=ax3a.transAxes, **font_kw)\n",
    "\n",
    "pairdata = pairdata0\n",
    "ax1d.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance == 1], alpha=0.3, s=30, c='C0')\n",
    "ax1d.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance == np.sqrt(2)], alpha=0.3, s=30, c='C1')\n",
    "ax1d.scatter('distance', 'crosstalk', data=pairdata.loc[pairdata.distance > np.sqrt(2)], alpha=0.2, s=30, c='grey')\n",
    "ax1d.set_yscale('log')\n",
    "ax1d.set_ylim(2e-7, 2e-3)\n",
    "ax1d.set_ylabel(r'Crosstalk Probability')\n",
    "ax1d.set_xlabel(u'Distance (unit = 500 μm)')\n",
    "#ax1d.set_title('Crosstalk vs distance')\n",
    "ax1d.text(xtext, ytext, 'D', transform=ax1d.transAxes, **font_kw)\n",
    "x = np.unique(pairdata.distance)\n",
    "A = pairdata.loc[pairdata.distance == 1, 'crosstalk'].mean()\n",
    "y = A / x**2\n",
    "ax1d.plot(x, y, ls='--', color='k')\n",
    "ax1d.text(0.5, 0.58, r'$\\propto R^{-2}$', transform=ax1d.transAxes, fontsize=24)\n",
    "\n",
    "dist = 1\n",
    "mask = pairdata['distance'] == dist\n",
    "ax2d.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H', color='C0')\n",
    "#ax2d.set_title('Horizontal/vertical pairs');\n",
    "ax2d.set_ylabel(r'Crosstalk Probability $\\times \\; 10^{-3}$')\n",
    "ax2d.set_xlabel('Pixel pair')\n",
    "ax2d.text(xtext, ytext, 'E', transform=ax2d.transAxes, **font_kw)\n",
    "\n",
    "dist = np.sqrt(2)\n",
    "mask = pairdata['distance'] == dist\n",
    "ax3d.errorbar(x=np.arange(mask.sum()), y=pairdata['crosstalk'][mask]*1e3, yerr=3*pairdata['error'][mask]*1e3, fmt='H', color='C1')\n",
    "#ax3d.set_title('Diagonal pairs');\n",
    "ax3d.set_ylabel(r'Crosstalk Probability $\\times \\; 10^{-3}$')\n",
    "ax3d.set_xlabel('Pixel pair')\n",
    "ax3d.text(xtext, ytext, 'F', transform=ax3d.transAxes, **font_kw);\n",
    "savefig('crosstalk_both_detectors')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\\frac{A}{R^2} = \\langle P_c \\rangle$$\n",
    "\n",
    "$$A = \\langle P_c \\rangle {R^2}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heatmaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_heatmap(pairdata):\n",
    "    a = np.zeros(nshape)*np.nan\n",
    "    dist = 1\n",
    "    mask = pairdata['distance'] == dist\n",
    "    pairdata_d1 = pairdata.loc[mask]\n",
    "    for p, pair in pairdata_d1.iterrows():\n",
    "        i, j = pair_coord(pair.pix1, pair.pix2)\n",
    "        a[j, i] = pair.crosstalk\n",
    "        #print(i, j, pair.pix1, pair.pix2, pair.crosstalk)\n",
    "\n",
    "    dist = np.sqrt(2)\n",
    "    mask = pairdata['distance'] == dist\n",
    "    pairdata_diag = pairdata.loc[mask]\n",
    "    for p, pair in pairdata_diag.iterrows():\n",
    "        i, j = pair_coord(pair.pix1, pair.pix2)\n",
    "        a[j, i] = pair.crosstalk\n",
    "    #print(i, j, pair.pix1, pair.pix2, pair.crosstalk)\n",
    "    return a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_crosstalk_heatmap(a, ax, title='Spatial distribution of crosstalk', cmap='Blues', vmin=0, vmax=1.5):\n",
    "    m = manta_shape.T[::-1]\n",
    "    xs = np.arange(12)\n",
    "    ys = np.repeat(np.arange(4)[np.newaxis,:].T, xs.size, axis=1)\n",
    "    ax.plot(xs, ys.T, 'o', ms=20, mew=1, mec='k', color='white')\n",
    "    im = ax.imshow(a*1e3, interpolation='none',  cmap=cmap, vmin=vmin, vmax=vmax,\n",
    "                    extent=(-0.25, 11.25, -0.25, 3.25))\n",
    "    for row in range(4):\n",
    "        for col in range(12):\n",
    "            ax.text(col+0.01, row-0.01, str(m[row,col]), va='center', ha='center', fontsize=12)\n",
    "    ax.set_xticks(range(12))\n",
    "    ax.set_yticks(range(4));\n",
    "    ax.set_title(title)\n",
    "    ax.text(1.14, 0.5, r'Crosstalk Probability $\\times \\; 10^{-3}$', rotation=90, va='center', transform=ax.transAxes)\n",
    "    return im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a0 = compute_heatmap(pairdata0)\n",
    "a1 = compute_heatmap(pairdata1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved:  figures/2017-10-16_00_DCR_crosstalk_heatmaps_both_detectors\n"
     ]
    },
    {
     "data": {
      "image/png": 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DhkXMNXvwwQf9+h+VKlWiU6dOgLu9AF5//XXq16/PbbfdRo8ePbhw4QLgPC9bCHZj9q8W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\naWlpPPTQQ6xcuZKkpCTuuusunnzyyXzrs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      "text/plain": [
       "<matplotlib.figure.Figure at 0x15f36ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(14, 8))\n",
    "im1 = plot_crosstalk_heatmap(a1, ax1, title='Acceptor SPAD array', cmap='Oranges')\n",
    "fig.colorbar(im1, ax=ax1)\n",
    "im0 = plot_crosstalk_heatmap(a0, ax0, title='Donor SPAD array', cmap='Blues')\n",
    "fig.colorbar(im0, ax=ax0)\n",
    "savefig('crosstalk_heatmaps_both_detectors')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.6 (py36)",
   "language": "python",
   "name": "py36"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "nav_menu": {},
  "toc": {
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
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   "toc_position": {},
   "toc_section_display": "block",
   "toc_window_display": true
  },
  "toc_position": {
   "height": "810px",
   "left": "0px",
   "right": "1549px",
   "top": "106px",
   "width": "212px"
  }
 },
 "nbformat": 4,
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}