{ "metadata": { "name": "example_generate_camino_schemefile.ipynb" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "import os\n", "from dmipy.signal_models import g_from_b\n", "from scipy.stats import gamma\n", "gradient_folder = '/user/rfick/home/microstruktur/microstruktur/gradient_tables/'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Generate schemefile" ] }, { "cell_type": "code", "collapsed": false, "input": [ "bvals_hcp = np.loadtxt(gradient_folder + 'bvals_hcp_wu_minn.txt') # in s/mm^2, shape (N)\n", "bvecs_hcp = np.loadtxt(gradient_folder + 'bvecs_hcp_wu_minn.txt').T # Cartesian unit vectors, shape(N x 3)\n", "delta, Delta = np.loadtxt(gradient_folder + 'delta_Delta_hcp_wu_minn.txt', skiprows=1) # in seconds\n", "G = g_from_b(bvals_hcp * 1e6, delta, Delta) # gradient strength in T/m. bvals input as s/m^2 so x10^6\n", "G[G == 5.] = 0. # set b0 measurements to 0 explicitly\n", "TE = 2 * delta + Delta + 0.001" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "raw", "metadata": {}, "source": [ "Camino schemefiles are formed as:\n", "\n", "VERSION: STEJSKALTANNER\n", "x_1, y_1, z_1, |G_1|, DELTA_1, delta_1, TE_1\n", "x_2 ...\n", "...\n", "\n", "where x, y, z are the orientations of the b-vectors, |G| is the gradient strength, DELTA is the pulse separation, delta is the pulse length and TE is the Echo Time. Everything is in SI units, so a Connectom gradient strength of 300 mT/m is put in as 0.3 T/m for example.\n", "\n", "Reference: http://camino.cs.ucl.ac.uk/index.php?n=Docs.SchemeFiles" ] }, { "cell_type": "code", "collapsed": false, "input": [ "N = len(bvals_hcp) # length of acquisition\n", "scheme = np.concatenate([bvecs_hcp, G[:, None].T,\n", " np.tile(Delta, (1, N)),\n", " np.tile(delta, (1, N)),\n", " np.tile(TE, (1, N))], axis=0).T # camino schemefile of size (N x 7)\n", "header = np.array([['VERSION: STEJSKALTANNER' ,'','','','','','']]) # clumsy way to make an array with text\n", "scheme_with_header = np.concatenate([header, scheme], axis=0) # the to-be-saved schemefile\n", "np.savetxt(gradient_folder + 'schemefile_hcp_wu_minn.scheme1', scheme_with_header, fmt=\"%s\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 10 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Generate parameters for simulation substrate" ] }, { "cell_type": "code", "collapsed": false, "input": [ "lattices, alpha, beta = np.loadtxt(gradient_folder + 'camino_substrate_parameters_alexander2010.txt',\n", " skiprows=1, usecols=(0, 1, 2)).T\n", "x = np.linspace(0, 4e-6, 200)\n", "for alpha_, beta_ in zip(alpha[::2], beta[::2]):\n", " gamma_dist = gamma(alpha_, scale=beta_)\n", " plt.plot(x * 2e6, gamma_dist.pdf(x))\n", "xlabel('Axon Diameter ($\\mu$m)', fontsize=15)\n", "ylabel('Probability Density', fontsize=15)\n", "title('Simulated Gamma Distributions', fontsize=17)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 77, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAaUAAAEmCAYAAADC9o/YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\njf8PvJkRtVHH810AAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 77 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.hist(alpha[::2] * beta[::2] * 2e6, bins=15)\n", "xlabel('Mean Axon Diameter ($\\mu$m)', fontsize=15)\n", "ylabel('Frequency', fontsize=15)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 78, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAEYCAYAAACgDKohAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text": [ "" ] } ], "prompt_number": 78 }, { "cell_type": "raw", "metadata": {}, "source": [ "The latices were selected by alexander et al (2010) to maximize the packing of the cylinders for the given gamma distribrution to an intra-axonal volume fraction of around (0.7)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "latices_onesize = lattices[::2]\n", "latice_surfaces = latices_onesize ** 2\n", "original_surface_intra = latice_surfaces * 0.7 # volume fraction of maximum packing\n", "largest_latice_surface = original_surface_intra * 5 # to make the intra-axonal surface fraction 0.2" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 90 }, { "cell_type": "code", "collapsed": false, "input": [ "latice_steps = 10\n", "output = []\n", "fnames = []\n", "for i in np.arange(latices_onesize.shape[0]):\n", " latices_ = np.sqrt(np.linspace(latice_surfaces[i], largest_latice_surface[i], latice_steps))\n", " alphas_ = np.tile(alpha[::2][i], latice_steps)\n", " betas_ = np.tile(beta[::2][i], latice_steps)\n", " for latnum_ in np.arange(10):\n", " fnames.append('gamma'+str(i)+'lat'+str(latnum_)+'.Bfloat') \n", " output.append(np.c_[latices_, alphas_, betas_])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 130 }, { "cell_type": "code", "collapsed": false, "input": [ "parameter_list = np.c_[np.concatenate(output), np.array(fnames)]\n", "savetxt(gradient_folder + 'camino_substrate_parameters_review_fick2017.txt', parameter_list, fmt=\"%s\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 132 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Camino command to start simulation" ] }, { "cell_type": "raw", "metadata": {}, "source": [ "The Camino command to run one simulation:\n", "\n", "SCHEMEFILES=\"schemefile_hcp_wu_minn\"\n", "\n", "WALKERS=80000\n", "TIMESTEPS=5000\n", "\n", "DIFF=1.7E-9;\n", "\n", "BASEDIR=/home/rfick/simulations/journal_review\n", "OUTPUTDIR=$BASEDIR/data\n", "mkdir ${OUTPUTDIR}\n", "\n", "for scheme in $SCHEMEFILES\n", "do\n", " mkdir ${OUTPUTDIR}/${scheme} \n", " while read -r LATSIZE GAMA GAMB FNAME; do\n", " datasynth -walkers ${WALKERS} -tmax ${TIMESTEPS} -geometry inflammation -numcylinders 100 -p 0.0 -initial uniform -voxels 1 -increments 1 -separateruns -latticesize ${LATSIZE} -schemefile $BASEDIR/schemes/$scheme.scheme1 -gamma ${GAMA} ${GAMB} -diffusivity ${DIFF} 1> ${OUTPUTDIR}/${scheme}/${FNAME} 2> ${OUTPUTDIR}/${scheme}/${FNAME}_log.txt && cat ${OUTPUTDIR}/${scheme}/${FNAME}_log.txt | grep fraction | awk '{print $5}' > ${OUTPUTDIR}/${scheme}/${FNAME}_fraction.txt\"\n", " done