Half_Frap_Phi_u.ipynb

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   "cell_type": "markdown",
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   "source": [
    "### FRAP geometries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fem_sol import frap_solver\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "font = {'family' : 'normal',\n",
    "        'weight' : 'normal',\n",
    "        'size'   : 12}\n",
    "import matplotlib\n",
    "matplotlib.rc('font', **font)\n",
    "\n",
    "def make_graph_pretty(xlab, ylab, loc=0, markerfirst=True, handlelength=None):\n",
    "    color1 = 'black'#'darkorange'\n",
    "    color2 = (0, 0, 0)\n",
    "    color2 = (1, 1, 1)\n",
    "    ax = plt.gca()\n",
    "    ax.tick_params(axis='x', colors=color1, which='both')\n",
    "    ax.tick_params(axis='y', colors=color1, which='both')\n",
    "    plt.xlabel(xlab, color=color1)\n",
    "    plt.ylabel(ylab, color=color1)\n",
    "    ax.spines['left'].set_color(color1)\n",
    "    ax.spines['bottom'].set_color(color1)\n",
    "    # Hide the right and top spines\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.set_facecolor(color2)\n",
    "    plt.gcf().subplots_adjust(bottom=0.17, left=0.15)\n",
    "    plt.legend(frameon=False, loc=loc, labelspacing=0.1,\n",
    "               markerfirst=markerfirst, handlelength=handlelength)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = ['Meshes/multi_drop_gauss.xml', 'Meshes/multi_drop_gauss_med.xml',\n",
    "     'Meshes/multi_drop_gauss_far.xml']\n",
    "point_lists = [[[4, 4.5, 0.5], [4, 3.5, 0.5], [3.5, 4, 0.5], [4.5, 4, 0.5]],\n",
    "               [[4, 5, 0.5], [4, 3, 0.5], [3, 4, 0.5], [5, 4, 0.5]],\n",
    "               [[4, 5.5, 0.5], [4, 2.5, 0.5], [2.5, 4, 0.5], [5.5, 4, 0.5]]]\n",
    "f_i = []\n",
    "for j in range(len(m)):\n",
    "    f = frap_solver([4, 4, 0.5], m[j], name=str(j), point_list=point_lists[j],\n",
    "                    T=3)\n",
    "    f.solve_frap()\n",
    "    f_i.append(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(cs[0])):\n",
    "    plt.plot([np.mean(x[1:49])/0.8 for x in cs[0][0:i]], label='dist=0.5')\n",
    "    plt.plot([np.mean(x[1:49])/0.8 for x in cs[1][0:i]], label='dist=1')\n",
    "    plt.plot([np.mean(x[1:49])/0.8 for x in cs[2][0:i]], label='dist=1.5')\n",
    "    plt.plot(range(0, 100), np.ones(100), linestyle='--', color='k')\n",
    "    plt.ylim((0, 1.1))\n",
    "    plt.xlim((0, 100))\n",
    "    make_graph_pretty('t (a.u.)', 'intensity (a.u)', loc=4)\n",
    "#     plt.savefig('img_'+str(i)+'.png', dpi=300)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_coverslip = frap_solver([4, 4, 0.5], 'Meshes/single_drop_coverslip.xml',\n",
    "                          name='FRAP_coverslip', T=300)\n",
    "f_coverslip.solve_frap()\n",
    "f_symmetric = frap_solver([4, 4, 4], 'Meshes/single_drop_symmetric.xml',\n",
    "                          name='FRAP_symmetric', T=300)\n",
    "f_symmetric.solve_frap()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot([np.mean(x[1:49])/0.8 for x in f_coverslip.cs], label='coverslip')\n",
    "plt.plot([np.mean(x[1:49])/0.8 for x in f_symmetric.cs], label='symmetric')\n",
    "plt.plot(range(0, 300), np.ones(300), linestyle='--', color='k')\n",
    "plt.ylim((0, 1.1))\n",
    "plt.xlim((0, 300))\n",
    "make_graph_pretty('t (a.u.)', 'intensity (a.u)', loc=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_coverslip.cs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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