data-visualization v01.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2f1caf40",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\helde\\AppData\\Local\\Temp\\ipykernel_18464\\926342863.py:2: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses\n",
      "  from imp import reload\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "from imp import reload\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import utils as ut\n",
    "\n",
    "plt.set_cmap(cmap=mpl.cm.gray);\n",
    "mpl.rcParams.update({'font.size': 12});\n",
    "#plt.rcParams['figure.dpi'] = 150"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9295b73",
   "metadata": {},
   "source": [
    "# Datasets\n",
    "\n",
    "## PMat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "370e9858",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(62, 2048)\n"
     ]
    }
   ],
   "source": [
    "#indexes_supine = [1, 8, 9, 10, 11, 12, 15, 16, 17]\n",
    "indexes_all = np.arange(1,17)\n",
    "\n",
    "subject = 1\n",
    "index = 1\n",
    "fn = 'Data/PmatData/experiment-i/S{}/{}.txt'.format(subject,index)\n",
    "img_csv = np.genfromtxt(fn)\n",
    "\n",
    "# discart first 10 and last 10\n",
    "img_csv = img_csv[10:-10,:]\n",
    "n_frames,_ = img_csv.shape\n",
    "\n",
    "# to get size of the read file\n",
    "print(img_csv.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "17dd6690",
   "metadata": {},
   "outputs": [],
   "source": [
    "frame_number = 30\n",
    "\n",
    "img_frame, img_bin = ut.get_frame(img_csv, frame_number, dataset='PMat', mask=True, t=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8dda9405",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,8))\n",
    "plt.imshow(img_frame)\n",
    "plt.axis('off')\n",
    "plt.savefig(f'pmat_f{frame_number}_orig.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "95e53a48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,8))\n",
    "plt.imshow(img_bin)\n",
    "plt.axis('off')\n",
    "plt.savefig(f'pmat_f{frame_number}_bin.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9ae7941a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████| 62/62 [00:00<00:00, 196.83it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████████████████████| 62/62 [00:00<00:00, 712.66it/s]\n"
     ]
    }
   ],
   "source": [
    "pts_dict = {}\n",
    "\n",
    "pts_dict['vert'] = ut.frames_medaxis(img_csv, dataset='PMat', axis=0)\n",
    "pts_dict['horiz'] = ut.frames_medaxis(img_csv, dataset='PMat', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "21e367c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts_vert = pts_dict['vert'][frame_number]\n",
    "pts_horiz = pts_dict['horiz'][frame_number]\n",
    "\n",
    "ut.plot_img_marks(img_frame, dots_v=pts_vert, dots_h=pts_horiz)\n",
    "plt.savefig(f'pmat_f{frame_number}_division')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "21954180",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ut.plot_img_marks(img_bin, dots_v=pts_vert, dots_h=pts_horiz)\n",
    "plt.savefig(f'pmat_f{frame_number}_bin_division')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6183bddd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
  },
  "vscode": {
   "interpreter": {
    "hash": "1e8007de8aeda7321e0e80cd63b62a807434cfe811032a53ba64e2c7137c4c7e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}