play_with_dev_model.ipynb 331 KB
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{
 "cells": [
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modelling developmental trajectories of white matter in newborns \n",
    "\n"
   ]
  },
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
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    "# Setup \n",
    "\n",
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    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import sys\n",
    "sys.path.append('/Users/saad/python-modules')\n",
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    "from mh import MH, plot_samples, gauss_logpr\n",
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    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import sys, os, glob\n",
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    "import scipy as sp\n",
    "sns.set()\n",
    "sns.set_context('talk')\n"
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 128,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "26"
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      ]
     },
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     "execution_count": 128,
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in design matrix\n",
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    "df = pd.read_csv('/Users/saad/Desktop/tmp_matteo/input_vars/input_vars_design_mat.csv')\n",
    "df['csf_vol'] = df['csf_vol']+df['ven_vol']  # define CSF = Ventricles+CorticalCSF\n",
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    "\n",
    "\n",
    "# Read in the tracts volumes\n",
    "\n",
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    "tracts_dir = '/Users/saad/Desktop/tmp_matteo/input_vars'\n",
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    "tracts_files = sorted(glob.glob(os.path.join(tracts_dir,'*_resorted.txt')))\n",
    "\n",
    "tracts_names = []\n",
    "tracts_vols  = []\n",
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    "exclude      = ['mcp','ml_l','ml_r']\n",
    "indluce_mask = []\n",
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    "for i in range(len(tracts_files)):\n",
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    "    tract = os.path.splitext(os.path.split(tracts_files[i])[-1])[-2].split(\"_\", 2)\n",
    "    if tract[1] in ['l','r']:\n",
    "        tract = tract[0]+\"_\"+tract[1]        \n",
    "    else:\n",
    "        tract = tract[0]\n",
    "    if tract not in exclude:\n",
    "        tracts_names.append(tract)\n",
    "        tracts_vols.append(np.loadtxt(tracts_files[i])[:,1])\n",
    "        indluce_mask.append(True)\n",
    "    else:\n",
    "        indluce_mask.append(False)\n",
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    "\n",
    "tracts_vols = np.asarray(tracts_vols).T\n",
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    "num_tracts  = tracts_vols.shape[1]\n",
    "\n",
    "len(tracts_names)\n"
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   ]
  },
  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
    "----------------------------------\n",
    "### Modelling code here\n",
    "----------------------------------"
   ]
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  },
  {
   "cell_type": "code",
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   "execution_count": 17,
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   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare data\n",
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    "def prepare(df,name=None,Y=None,deconfound=False,normalise=True):\n",
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    "    # Data and regressors\n",
    "    if name is not None:\n",
    "        Y = np.array(df[name])\n",
    "    b = np.array(df['age_birth'])\n",
    "    s = np.array(df['age_scan'])\n",
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    "    if deconfound:\n",
    "        # Confounds\n",
    "        #df['brain_vol'] = np.array(df['gm_vol'])+np.array(df['wm_vol'])+np.array(df['ven_vol'])\n",
    "        conf = np.array(df[['qc_snr','qc_cnr400','qc_cnr1000','qc_cnr2600']])\n",
    "        # Regress out confounds from data\n",
    "        from sklearn.linear_model import LinearRegression\n",
    "        reg = LinearRegression(fit_intercept=True, normalize=False).fit(conf, Y)\n",
    "        Y = Y - reg.predict(conf) + reg.intercept_    \n",
    "    if normalise:\n",
    "        # Normalise to 95th percentile\n",
    "        Y = Y/np.quantile(Y,.95,axis=0)*100  \n",
    "\n",
    "    return Y,b,s\n",
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    "             \n",
    "   \n",
    "# Various forward models\n",
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    "prem_thresh = 37 # prematurity threshold\n",
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    "# Only one slope (beta1=beta2)\n",
    "def forward_0(p,s,b):\n",
    "    return p[0]*s-p[0]*p[1]\n",
    "\n",
    "# Same post-birth slopes for term and prem\n",
    "def forward_1(p,s,b):\n",
    "    pred = p[0]*b + p[1]*(s-b)- p[0]*p[2]    \n",
    "    return pred\n",
    "# Post-birth slope is different\n",
    "def forward_2(p,s,b):\n",
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    "    term = b>=prem_thresh\n",
    "    prem = b<prem_thresh\n",
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    "    \n",
    "    pred = p[0]*b - p[0]*p[3]\n",
    "    pred[term] += p[1]*(s[term]-b[term])\n",
    "    pred[prem] += p[2]*(s[prem]-b[prem])\n",
    "    return pred\n",
    "# All slopes different - same onset\n",
    "def forward_3(p,s,b):\n",
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    "    term = b>=prem_thresh\n",
    "    prem = b<prem_thresh\n",
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    "    \n",
    "    pred = np.zeros(s.size)\n",
    "    pred[term] = p[0]*b[term] + p[1]*(s[term]-b[term])- p[0]*p[4]\n",
    "    pred[prem] = p[2]*b[prem] + p[3]*(s[prem]-b[prem])- p[2]*p[4]\n",
    "    \n",
    "    return pred\n",
    "\n",
    "\n",
    "class ForwardModel:\n",
    "    def __init__(self,modelid):\n",
    "        self.modelid = modelid\n",
    "        if modelid == 0:\n",
    "            self.forward = forward_0\n",
    "            self.nparams = 2\n",
    "            self.labels = ['beta1','onset']\n",
    "        elif modelid == 1:\n",
    "            self.forward = forward_1\n",
    "            self.nparams = 3\n",
    "            self.labels = ['beta1','beta2','onset']\n",
    "        elif modelid == 2:\n",
    "            self.forward = forward_2\n",
    "            self.nparams = 4\n",
    "            self.labels = ['beta1','beta2-term','beta2-prem','onset']\n",
    "        elif modelid == 3:\n",
    "            self.forward = forward_3\n",
    "            self.nparams = 5\n",
    "            self.labels = ['beta1-term','beta2-term','beta1-prem','beta2-prem','onset']\n",
    "        else:\n",
    "            raise Exception('Unknown model id.')\n",
    "    def bounds(self):        \n",
    "        if self.modelid == 0:\n",
    "            LB = np.array([-np.inf,0])\n",
    "            UB = np.array([ np.inf,40])\n",
    "            return LB,UB\n",
    "        elif self.modelid == 1:\n",
    "            LB = np.array([-np.inf,-np.inf,0])\n",
    "            UB = np.array([ np.inf, np.inf,40])\n",
    "            return LB,UB\n",
    "        elif self.modelid == 2:\n",
    "            LB = np.array([-np.inf,-np.inf,-np.inf,0])\n",
    "            UB = np.array([ np.inf, np.inf,np.inf,40])\n",
    "            return LB,UB\n",
    "        elif self.modelid == 3:\n",
    "            LB = np.array([-np.inf,-np.inf,-np.inf,-np.inf,0])\n",
    "            UB = np.array([ np.inf, np.inf, np.inf, np.inf,40])\n",
    "            return LB,UB\n",
    "        else:\n",
    "            raise Exception('Unknown model id.')\n",
    "    def init(self):       \n",
    "        if self.modelid == 0:\n",
    "            return np.array([0,0.00001])\n",
    "        elif self.modelid == 1:\n",
    "            return np.array([0,0,0.00001])\n",
    "        elif self.modelid == 2:\n",
    "            return np.array([0,0,0,0.00001])\n",
    "        elif self.modelid == 3:\n",
    "            return np.array([0,0,0,0,0.00001])\n",
    "        else:\n",
    "            raise Exception('Unknown model id.')\n",
    "        \n",
    "        \n",
    "# Fit model to data\n",
    "def do_fit(Y,b,s,forward_model):\n",
    "    loglik  = lambda p : np.log(np.linalg.norm(Y-forward_model.forward(p,s,b)))*Y.size/2\n",
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    "    logpr   = lambda p : np.sum(gauss_logpr(p[:-1],loc=0,scale=40))\n",
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    "    # Bounds\n",
    "    LB,UB = forward_model.bounds()\n",
    "    # Initialise\n",
    "    p0   = forward_model.init()\n",
    "\n",
    "    mh = MH(loglik,logpr,njumps=10000)\n",
    "    import time\n",
    "    start = time.time()\n",
    "    samples = mh.fit(p0,LB=LB,UB=UB)\n",
    "    ML      = mh.marglik_Laplace(samples)\n",
    "    \n",
    "    return samples, ML\n",
    "\n",
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    "# SVD the data prior to fitting (for vertex-wise data)\n",
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    "def do_pca_fit(Y,b,s,forward_model,keep=10):\n",
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    "    \n",
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    "    if Y.shape[0]>Y.shape[1]:\n",
    "        raise Exception(\"Data must be transposed\")\n",
    "    import scipy as sp\n",
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    "    #U,S,V = sp.sparse.linalg.svds(Y-Y.mean(axis=0),k=keep)\n",
    "    U,S,V = sp.sparse.linalg.svds(Y,k=keep)\n",
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    "    \n",
    "    all_betas = np.zeros((fm.nparams,keep))\n",
    "    for i in range(keep):\n",
    "        samples, _ = do_fit(Y@V[i,:].T,b,s,forward_model)\n",
    "        betas = samples[:,:-1].mean(axis=0)\n",
    "        betas = np.append(betas,-samples[:,-1].mean(axis=0)*betas[0])\n",
    "        all_betas[:,i] = betas\n",
    "    all_betas = all_betas@V\n",
    "    grot1 = all_betas[:-1,:]\n",
    "    grot2 = -all_betas[-1,:]/all_betas[0,:]\n",
    "    all_betas = np.concatenate((grot1,grot2[None,:]))\n",
    "    return all_betas\n"
   ]
  },
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------\n",
    "### End of model code\n",
    "-------\n",
    "\n",
    "#### Quick fit "
   ]
  },
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  {
   "cell_type": "code",
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   "execution_count": 18,
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   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
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     ]
    },
    {
     "data": {
      "text/plain": [
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       "<matplotlib.figure.Figure at 0x123f7edd8>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<matplotlib.figure.Figure at 0x121b77c18>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
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       "<matplotlib.figure.Figure at 0x123f7ebe0>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<matplotlib.figure.Figure at 0x124737a90>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Quick fit a model and look at the resuts\n",
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    "model = 2\n",
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    "fm    = ForwardModel(model)\n",
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    "name  = 'csf_vol'\n",
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    "data,birth,scan = prepare(df,name=name)\n",
    "samples, ML = do_fit(data,birth,scan,fm)\n",
    "\n",
    "plot_samples(samples,labels=fm.labels,plot_type='vector')\n",
    "plot_samples(samples,labels=fm.labels,plot_type='matrix')\n"
   ]
  },
  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
    "### ANALYSIS 1: Gross volumetric changes"
   ]
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  },
  {
   "cell_type": "code",
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   "execution_count": 19,
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   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<matplotlib.figure.Figure at 0x1214aa438>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# COMPARE CSF,GM,WM \n",
    "\n",
    "fm = ForwardModel(2)\n",
    "param_list = [0,1,2]\n",
    "\n",
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    "plt.style.use('seaborn-white')\n",
    "plt.figure(figsize=(20,5))\n",
    "for idx,name in enumerate(['csf_vol','gm_vol','wm_vol']):\n",
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    "    Y,b,s = prepare(df,name)\n",
    "    samples,_ = do_fit(Y,b,s,fm)    \n",
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    "    \n",
    "    plt.subplot(1, 3, idx+1)\n",
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    "    [plt.hist(samples[:,i],histtype='step') for i in param_list]\n",
    "    plt.legend([ fm.labels[i] for i in param_list ])\n",
    "    plt.title(name)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 20,
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   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "[[1.000e+00 0.000e+00 0.000e+00]\n",
      " [2.330e+02 1.000e+00 0.000e+00]\n",
      " [4.343e+03 1.900e+01 1.000e+00]]\n"
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     ]
    }
   ],
   "source": [
    "# BAYESIAN MODEL COMPARISON\n",
    "# WITH APPROX MARGINAL LIKELIHOOD\n",
    "\n",
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    "name    = 'gm_vol'\n",
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    "nmodels = 3\n",
    "\n",
    "MLs  = np.zeros(nmodels)\n",
    "for modelid in [1,2,3]: \n",
    "    fm = ForwardModel(modelid)\n",
    "    Y,b,s = prepare(df,name)\n",
    "    samples, ML = do_fit(Y,b,s,fm)\n",
    "    MLs[modelid-1] = ML\n",
    " \n",
    "# Bayes factor\n",
    "BF = np.zeros([nmodels,nmodels])\n",
    "for i in range(nmodels):\n",
    "    for j in range(nmodels):\n",
    "        BF[i,j] = np.exp(MLs[i]-MLs[j])\n",
    "        \n",
    "\n",
    "print(\"{}\".format(np.round(BF)))\n",
    "\n"
   ]
  },
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ANALYSIS 2 : Tract volumes"
   ]
  },
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  {
   "cell_type": "code",
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   "execution_count": 21,
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   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n",
      "10\n",
      "11\n",
      "12\n",
      "13\n",
      "14\n",
      "15\n",
      "16\n",
      "17\n",
      "18\n",
      "19\n",
      "20\n",
      "21\n",
      "22\n",
      "23\n",
      "24\n",
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      "25\n"
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     ]
    }
   ],
   "source": [
    "# Loop through the tracts \n",
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    "model         = 2\n",
    "fm            = ForwardModel(model)\n",
    "res_tract_vol = np.zeros((1000,fm.nparams,num_tracts))\n",
    "for i in range(num_tracts):\n",
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    "    print(i)\n",
    "    data,birth,scan = prepare(df,Y=tracts_vols[:,i])\n",
    "    samples, ML = do_fit(data,birth,scan,fm)\n",
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    "    res_tract_vol[:,:,i] = samples\n",
    "\n"
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 22,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "(4, 26)"
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      ]
     },
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     "execution_count": 22,
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     "metadata": {},
     "output_type": "execute_result"
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    }
   ],
   "source": [
    "mean = res_tract_vol.mean(axis=0)\n",
    "std  = res_tract_vol.std(axis=0)\n",
    "\n",
    "mean.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
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    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<matplotlib.figure.Figure at 0x13050cc88>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
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       "<matplotlib.figure.Figure at 0x132875400>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#fm = ForwardModel(2)\n",
    "#param_list = [0,1,2]\n",
    "\n",
    "#for name in ['csf_vol']:\n",
    "#    Y,b,s = prepare(df,name)\n",
    "#    samples,_ = do_fit(Y,b,s,fm)    \n",
    "    \n",
    "#grot=samples.mean(axis=0)\n",
    "\n",
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    "def quick_plot_bars(x):\n",
    "    p = 0\n",
    "    l = 1\n",
    "    c = 2\n",
    "    a = 3\n",
    "    tracts_type = np.asarray([p,p,p,p,l,l,l,l,p,p,c,c,l,l,a,a,a,a,p,p,a,a,p,p,a,a])\n",
    "    idx         = np.argsort(tracts_type)\n",
    "    tracts_names_sorted = [tracts_names[idx[i]] for i in range(num_tracts)]\n",
    "\n",
    "    fig, ax = plt.subplots(1,1,figsize=(5,8))\n",
    "\n",
    "    sns.set_context('talk')\n",
    "    sns.barplot(x=x,y=tracts_names_sorted,hue=tracts_type[idx],palette=['r','g','b','k'],dodge=False)\n",
    "    plt.figure(figsize=(5,8))\n",
    "    sns.set_context('talk')\n",
    "\n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    ax.legend(handles[:0], labels[:0])\n",
    "\n",
    "    \n",
    "quick_plot_bars(mean[0,:])    \n",
    "#sns.scatterplot(x=beta1,y=beta2_prem)\n",
    "#sns.scatterplot(x=beta1,y=beta2_term,color='r')\n",
    "#[plt.text(x=T1[i],y=T2[i],s=tracts_names[i],fontsize=16) for i in range(len(tracts_names))]\n",
    "#plt.xlabel('beta1')\n",
    "#plt.ylabel('beta2')\n",
    "#\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model entropy\n",
    "\n",
    "- Get entropy data\n",
    "- Run model=2 using PCA dim reduction trick\n",
    "- Save all betas into a cifti file\n",
    "- View in workbench :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading data\n",
    "dirname = '/Users/saad/Desktop/tmp_matteo'\n",
    "df = pd.read_csv(os.path.join(dirname,'input_vars','input_vars_design_mat.csv'))\n",
    "\n",
    "tmp = np.load(os.path.join(dirname,'input_vars','entropy.npz'))\n",
    "en  = tmp['arr_0']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fitting the model\n",
    "fm    = ForwardModel(2)\n",
    "Y,b,s = prepare(df,Y=en.T,deconfound=False,normalise=True)\n",
    "betas = do_pca_fit(Y,b,s,fm,keep=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cifti, nibabel\n",
    "\n",
    "left_mask  = nibabel.load(os.path.join(dirname,'input_vars','week40.L.atlasroi.10k.shape.gii')).darrays[0].data\n",
    "right_mask = nibabel.load(os.path.join(dirname,'input_vars','week40.R.atlasroi.10k.shape.gii')).darrays[0].data\n",
    "\n",
    "bm = cifti.BrainModel.from_mask(left_mask, name='CortexLeft') + cifti.BrainModel.from_mask(right_mask, name='CortexRight')\n",
    "\n",
    "sc = cifti.Scalar.from_names(['beta1', 'beta2-term','beta2-prem','onset'])   \n",
    "cifti.write(os.path.join(dirname,'entropy_model2_coefs.dscalar.nii'), betas, (sc, bm))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model cortical morphology\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading data\n",
    "dirname = '/Users/saad/Desktop/tmp_matteo'\n",
    "df = pd.read_csv(os.path.join(dirname,'input_vars','input_vars_design_mat.csv'))\n",
    "\n",
    "var = 'corr_thickness'\n",
    "tmp = np.load(os.path.join(dirname,'input_vars',var+'.npz'))['arr_0']\n",
    "\n",
    "# Fitting the model\n",
    "fm    = ForwardModel(2)\n",
    "Y,b,s = prepare(df,Y=tmp.T,deconfound=False,normalise=False)\n",
    "betas = do_pca_fit(Y,b,s,fm,keep=10)\n",
    "\n",
    "left_mask  = nibabel.load(os.path.join(dirname,'input_vars','week40.L.atlasroi.32k.inv.func.gii')).darrays[0].data\n",
    "right_mask = nibabel.load(os.path.join(dirname,'input_vars','week40.R.atlasroi.32k.inv.func.gii')).darrays[0].data\n",
    "\n",
    "bm = cifti.BrainModel.from_mask(left_mask, name='CortexLeft') + cifti.BrainModel.from_mask(right_mask, name='CortexRight')\n",
    "\n",
    "sc = cifti.Scalar.from_names(['beta1', 'beta2-term','beta2-prem','onset'])   \n",
    "cifti.write(os.path.join(dirname,var+'_model2_coefs.dscalar.nii'), betas, (sc, bm))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model blueprints\n",
    "- Load blueprints\n",
    "- For each tract \n",
    "    - Run model and save betas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirname = '/Users/saad/Desktop/tmp_matteo'\n",
    "df = pd.read_csv(os.path.join(dirname,'input_vars','input_vars_design_mat.csv'))\n",
    "\n",
    "var = 'blueprints'\n",
    "bp  = np.load(os.path.join(dirname,'input_vars',var+'.npz'))['arr_0']\n",
    "bp  = bp[:,indluce_mask,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save all mean BPs\n",
    "sc = cifti.Scalar.from_names(tracts_names)   \n",
    "cifti.write(os.path.join(dirname,'BluePrints.dscalar.nii'), np.log(bp.mean(axis=2).T), (sc, bm))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n",
      "10\n",
      "11\n",
      "12\n",
      "13\n",
      "14\n",
      "15\n",
      "16\n",
      "17\n",
      "18\n",
      "19\n",
      "20\n",
      "21\n",
      "22\n",
      "23\n",
      "24\n",
      "25\n"
     ]
    }
   ],
   "source": [
    "# Model tract area\n",
    "thresh = 50\n",
    "tracts_areas = np.sum(bp>thresh,axis=0)\n",
    "\n",
    "# Loop through the tracts \n",
    "model = 2\n",
    "fm    = ForwardModel(model)\n",
    "results_tracts_area = np.zeros((1000,4,num_tracts))\n",
    "for i in range(num_tracts):\n",
    "    print(i)\n",
    "    data,birth,scan = prepare(df,Y=tracts_areas[i,:].T,normalise=True)\n",
    "    samples, ML = do_fit(data,birth,scan,fm)\n",
    "    results_tracts_area[:,:,i] = samples\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1327a16d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1327a1dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x132912d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1327af940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "quick_plot_bars(res_tract_vol.mean(axis=0)[2,:])\n",
    "quick_plot_bars(results_tracts_area.mean(axis=0)[2,:])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "tracts_areas = np.sum(bp>thresh,axis=0)\n",
    "tracts_areas_perc = np.mean(bp>thresh,axis=0)*100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta1      = []\n",
    "beta2_term = []\n",
    "beta2_prem = []\n",
    "for i in range(len(results)):\n",
    "    beta1.append(results[i][:,0].mean())\n",
    "    beta2_term.append(results[i][:,1].mean())\n",
    "    beta2_prem.append(results[i][:,2].mean())\n",
    "    \n",
    "beta1      = np.asarray(beta1)\n",
    "beta2_term = np.asarray(beta2_term)\n",
    "beta2_prem = np.asarray(beta2_prem)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
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    "plt.figure(figsize=(5,8))\n",
    "sns.set_context('talk')\n",
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    "sns.barplot(x=beta2_prem,y=tracts_names)\n",
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    "plt.figure(figsize=(5,8))\n",
    "sns.set_context('talk')\n",
    "\n",
    "sns.scatterplot(x=beta1,y=beta2_prem)\n",
    "sns.scatterplot(x=beta1,y=beta2_term,color='r')\n",
    "#[plt.text(x=T1[i],y=T2[i],s=tracts_names[i],fontsize=16) for i in range(len(tracts_names))]\n",
    "plt.xlabel('beta1')\n",
    "plt.ylabel('beta2')\n",
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    "plt.legend(['prem','term'])\n"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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