Untitled3.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import nibabel as nib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "np.set_printoptions(threshold='nan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Load a trk file and extract the endpoints \n",
    "path = 'E:/Celine/Ferret_b2n/F01_Adult/'\n",
    "fstreams = path+'tracto_F01_Adult_rot_den_modifiedgtab_final.trk'\n",
    "\n",
    "from nibabel import trackvis\n",
    "streams, hdr = trackvis.read(fstreams)\n",
    "streamlines = [s[0] for s in streams]\n",
    "\n",
    "endpoints1=[]\n",
    "i= 0\n",
    "\n",
    "for i in range(len(streamlines)):\n",
    "    stream = streamlines[i]\n",
    "    \n",
    "    endpoints1.append([stream[0][0],stream[0][1],stream[0][2],stream[stream.shape[0]-1][0],stream[stream.shape[0]-1][1],stream[stream.shape[0]-1][2]])\n",
    "\n",
    "endpoints = np.asarray(endpoints1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fbizley = 'Bizley2009'\n",
    "niigz = '.nii.gz'\n",
    "\n",
    "imgbiz = nib.load(path+fbizley+niigz)\n",
    "labels = imgbiz.get_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fdwi = 'F01_Adult_rot_den_1'\n",
    "\n",
    "img = nib.load(path+fdwi+niigz)\n",
    "dwi = img.get_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -0.23999999,   0.        ,   0.        ,  19.07999957],\n",
       "       [  0.        ,   0.23999999,   0.        , -14.27999968],\n",
       "       [  0.        ,   0.        ,   0.23999999,  -9.47999979],\n",
       "       [  0.        ,   0.        ,   0.        ,   1.        ]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imgbiz.header.get_base_affine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -0.23999999,   0.        ,   0.        ,  19.07999957],\n",
       "       [  0.        ,   0.23999999,   0.        , -14.27999968],\n",
       "       [  0.        ,   0.        ,   0.23999999,  -9.47999979],\n",
       "       [  0.        ,   0.        ,   0.        ,   1.        ]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img.header.get_base_affine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([91, 91, 92, 92, 93, 93, 94, 94, 95, 95, 96, 96, 97, 97, 98], dtype=int64),\n",
       " array([19, 20, 19, 20, 20, 21, 21, 22, 22, 23, 24, 25, 25, 26, 26], dtype=int64))"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[26].nonzero()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[26,91,19]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(160L, 120L, 80L)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(160L, 120L, 80L, 1L)"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dwi.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 19642.4921875], dtype=float32)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dwi[0,0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nbparcels = len(np.unique(labels))-1 # -1 to remove the background"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nbparcels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "        [ 5.87955379,  7.04804325,  6.08737803],\n",
       "        [ 5.90644312,  7.0430398 ,  6.20421934],\n",
       "        [ 5.9321723 ,  7.04544401,  6.32140398],\n",
       "        [ 5.95890284,  7.0591507 ,  6.43758345],\n",
       "        [ 5.98387051,  7.08558035,  6.55194283],\n",
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       "        [ 6.02516937,  7.16734838,  6.77351952],\n",
       "        [ 6.03250504,  7.2152257 ,  6.88331032],\n",
       "        [ 6.03361511,  7.26130486,  6.99410486],\n",
       "        [ 6.03450823,  7.29955769,  7.10784101],\n",
       "        [ 6.03746843,  7.32521057,  7.22502995],\n",
       "        [ 6.03370571,  7.35433817,  7.34138012],\n",
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       "        [ 5.96482086,  7.50213194,  7.6593852 ],\n",
       "        [ 5.94358873,  7.57159853,  7.75490236],\n",
       "        [ 5.92698193,  7.67271328,  7.81735229],\n",
       "        [ 5.91994572,  7.77518797,  7.87939596],\n",
       "        [ 5.92453623,  7.86886787,  7.95424986]], dtype=float32),\n",
       " array([[ 5.24970388,  7.05098963,  4.99992752],\n",
       "        [ 5.29656601,  7.03242731,  5.10882854],\n",
       "        [ 5.33999968,  7.01999998,  5.21999979],\n",
       "        [ 5.38343382,  7.00757265,  5.33117104],\n",
       "        [ 5.42239094,  7.00316048,  5.4445858 ],\n",
       "        [ 5.45628929,  7.00293922,  5.5596981 ],\n",
       "        [ 5.48307276,  7.00650406,  5.67661667],\n",
       "        [ 5.50683403,  7.02084684,  5.79336309],\n",
       "        [ 5.53386736,  7.05683422,  5.90460205],\n",
       "        [ 5.56412458,  7.09811068,  6.01314116],\n",
       "        [ 5.5979414 ,  7.10391808,  6.12813091],\n",
       "        [ 5.62854958,  7.08501291,  6.24261141]], dtype=float32),\n",
       " array([[ 5.26438332,  7.10282326,  4.79040861],\n",
       "        [ 5.31882095,  7.07453203,  4.89354038],\n",
       "        [ 5.36835527,  7.05346727,  5.0007906 ],\n",
       "        [ 5.41573668,  7.0347867 ,  5.10944605],\n",
       "        [ 5.46000004,  7.01999998,  5.21999979],\n",
       "        [ 5.5042634 ,  7.00521326,  5.33055353],\n",
       "        [ 5.54595184,  6.99323082,  5.44243956],\n",
       "        [ 5.58496904,  6.98385239,  5.55553102],\n",
       "        [ 5.62055111,  6.98449183,  5.67013264],\n",
       "        [ 5.65623474,  6.99590683,  5.78413439],\n",
       "        [ 5.69396019,  7.01021004,  5.89714861],\n",
       "        [ 5.7326479 ,  7.02169991,  6.01015854],\n",
       "        [ 5.7685113 ,  7.016397  ,  6.1245513 ],\n",
       "        [ 5.79915237,  7.00047874,  6.2394762 ],\n",
       "        [ 5.82970858,  6.99528694,  6.35540438],\n",
       "        [ 5.85894442,  7.01513529,  6.47008371],\n",
       "        [ 5.88253307,  7.05503035,  6.58077192],\n",
       "        [ 5.90229225,  7.11039066,  6.68538952],\n",
       "        [ 5.911901  ,  7.1785779 ,  6.78366518],\n",
       "        [ 5.90937138,  7.24542236,  6.88329172],\n",
       "        [ 5.90202904,  7.30081463,  6.9894886 ],\n",
       "        [ 5.90170717,  7.33411455,  7.10477543],\n",
       "        [ 5.90677929,  7.35639668,  7.22257948],\n",
       "        [ 5.90459681,  7.38439083,  7.33924818],\n",
       "        [ 5.89552546,  7.41756964,  7.45421267],\n",
       "        [ 5.87372065,  7.45347452,  7.56661987],\n",
       "        [ 5.84771109,  7.47876549,  7.68100452],\n",
       "        [ 5.83095694,  7.54502535,  7.77963972],\n",
       "        [ 5.81170034,  7.64092255,  7.84915924],\n",
       "        [ 5.80105066,  7.74049377,  7.91528177]], dtype=float32),\n",
       " array([[ 5.23713303,  7.17967796,  5.00687265],\n",
       "        [ 5.28932095,  7.15781736,  5.11269569],\n",
       "        [ 5.33999968,  7.13999987,  5.21999979],\n",
       "        [ 5.39067841,  7.12218237,  5.32730389],\n",
       "        [ 5.43799162,  7.11283493,  5.43718624],\n",
       "        [ 5.48176956,  7.10490274,  5.54863405],\n",
       "        [ 5.52114153,  7.09228182,  5.66128635],\n",
       "        [ 5.55762005,  7.08586979,  5.77542734],\n",
       "        [ 5.59452868,  7.10082865,  5.88862658],\n",
       "        [ 5.63357878,  7.11649561,  6.00100803],\n",
       "        [ 5.67088556,  7.10852051,  6.11478233],\n",
       "        [ 5.7013278 ,  7.09254265,  6.22975206],\n",
       "        [ 5.73011971,  7.08450317,  6.34596872]], dtype=float32),\n",
       " array([[ 5.30509472,  7.20097542,  4.90086126],\n",
       "        [ 5.35728264,  7.1791153 ,  5.0066843 ],\n",
       "        [ 5.40932131,  7.15781736,  5.11269569],\n",
       "        [ 5.46000004,  7.13999987,  5.21999979],\n",
       "        [ 5.51067877,  7.12218237,  5.32730389],\n",
       "        [ 5.56012011,  7.1075592 ,  5.43566322],\n",
       "        [ 5.60841179,  7.09305716,  5.54455566],\n",
       "        [ 5.6541996 ,  7.08308554,  5.65502787],\n",
       "        [ 5.69813156,  7.08163881,  5.76668739],\n",
       "        [ 5.7425456 ,  7.07909727,  5.87813663],\n",
       "        [ 5.78582811,  7.07915354,  5.99005938],\n",
       "        [ 5.82086325,  7.0753212 ,  6.10476685],\n",
       "        [ 5.84630632,  7.06983042,  6.22191   ],\n",
       "        [ 5.87229395,  7.07505751,  6.33894539],\n",
       "        [ 5.90089893,  7.09418631,  6.45390558],\n",
       "        [ 5.92689657,  7.12716436,  6.56631804],\n",
       "        [ 5.94754028,  7.16965103,  6.67663002],\n",
       "        [ 5.95779276,  7.21880913,  6.78561783],\n",
       "        [ 5.95765257,  7.26919365,  6.89452791],\n",
       "        [ 5.95428324,  7.31173468,  7.00668383],\n",
       "        [ 5.95683432,  7.33843565,  7.12364769],\n",
       "        [ 5.96066475,  7.36176491,  7.24129581],\n",
       "        [ 5.95775318,  7.39104509,  7.35763216],\n",
       "        [ 5.94724846,  7.42760372,  7.47144413],\n",
       "        [ 5.92444515,  7.46974087,  7.58146429],\n",
       "        [ 5.89919853,  7.50732279,  7.69259596],\n",
       "        [ 5.8825736 ,  7.58088207,  7.78593731],\n",
       "        [ 5.86231756,  7.68664503,  7.83888865],\n",
       "        [ 5.85622787,  7.78943348,  7.9005127 ]], dtype=float32),\n",
       " ...]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "streamlines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  4.91044855,  23.2446785 ,   9.12738037], dtype=float32)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "endpoints[0,0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  5.05153465,  23.12623596,   9.10031223], dtype=float32)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "endpoints[1,0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conMat = np.zeros((nbparcels,nbparcels))\n",
    "\n",
    "start = -1\n",
    "end = -1\n",
    "countCon = 0\n",
    "countNoCon = 0\n",
    "ep = 0\n",
    "\n",
    "for ep in range(len(endpoints)): #for each endpoint\n",
    "        #if \n",
    "        \n",
    "        if (pow(endpoints[ep,0]-points[p,0],2)+pow(endpoints[ep,1]-points[p,1],2)+pow(endpoints[ep,2]-points[p,2],2)<pow(r,2)):\n",
    "            start=p\n",
    "            #if both endpoints of a streamline were localised in one of the spheres then write in the connectivity matrix\n",
    "            if (start!=-1 and end!=-1):\n",
    "                #print endpoints[ep],points[start],points[end]\n",
    "                conMat[start,end]+=1\n",
    "                conMat[end,start]+=1\n",
    "                countCon +=1\n",
    "                \n",
    "        #if the second (pair) endpoint is the sphere of radius r and center the point p        \n",
    "        if (pow(endpoints[ep,3]-points[p,0],2)+pow(endpoints[ep,4]-points[p,1],2)+pow(endpoints[ep,5]-points[p,2],2)<pow(r,2)):\n",
    "            end=p\n",
    "            #if both endpoints of a streamline were localised in one of the spheres then write in the connectivity matrix\n",
    "            if (start!=-1 and end!=-1):\n",
    "                #print endpoints[ep],points[start],points[end]\n",
    "                conMat[start,end]+=1\n",
    "                conMat[end,start]+=1\n",
    "                countCon +=1\n",
    "                \n",
    "    else:\n",
    "        countNoCon +=1\n",
    "    \n",
    "    #reset for the next streamline\n",
    "    start = -1\n",
    "    end = -1\n",
    "\n",
    "print 'nb of streamlines in the matrix',countCon\n",
    "print 'nb of streamlines rejected from the matrix', countNoCon"
   ]
  }
 ],
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