Showcase-Dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import tqdm\n",
    "\n",
    "DATA_PATH = \"./data/\"\n",
    "\n",
    "#import sys\n",
    "#np.set_printoptions(threshold=sys.maxsize)\n",
    "#np.set_printoptions(linewidth=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./data/apriltag-16h5-4mm-ID0-False-Circle-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-False-Eight-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-False-LeftRight-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-False-Random-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-False-Square-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-False-UpDown-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-Circle-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-Eight-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-LeftRight-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-Random-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-Square-1.csv',\n",
       " './data/apriltag-16h5-4mm-ID0-True-UpDown-1.csv',\n",
       " './data/apriltag-36h11-4mm-ID2-True-Random-1.csv',\n",
       " './data/apriltag-36h11-4mm-ID3-True-Random-1.csv',\n",
       " './data/apriltag-36h11-4mm-ID4-True-Random-1.csv',\n",
       " './data/apriltag-36h11-6mm-ID2-True-Random-1.csv',\n",
       " './data/apriltag-36h11-6mm-ID3-True-Random-1.csv',\n",
       " './data/apriltag-36h11-6mm-ID4-True-Random-1.csv',\n",
       " './data/apriltag-36h11-8mm-ID2-True-Random-1.csv',\n",
       " './data/apriltag-36h11-8mm-ID3-True-Random-1.csv',\n",
       " './data/apriltag-36h11-8mm-ID4-True-Random-1.csv',\n",
       " './data/circle-2mm-Circle-1.csv',\n",
       " './data/circle-2mm-Eight-1.csv',\n",
       " './data/circle-2mm-LeftRight-1.csv',\n",
       " './data/circle-2mm-Random-1.csv',\n",
       " './data/circle-2mm-Square-1.csv',\n",
       " './data/circle-2mm-UpDown-1.csv',\n",
       " './data/circle-4mm-Circle-1.csv',\n",
       " './data/circle-4mm-Eight-1.csv',\n",
       " './data/circle-4mm-LeftRight-1.csv',\n",
       " './data/circle-4mm-Random-1.csv',\n",
       " './data/circle-4mm-Square-1.csv',\n",
       " './data/circle-4mm-UpDown-1.csv',\n",
       " './data/circle-6mm-Circle-1.csv',\n",
       " './data/circle-6mm-Eight-1.csv',\n",
       " './data/circle-6mm-LeftRight-1.csv',\n",
       " './data/circle-6mm-Random-1.csv',\n",
       " './data/circle-6mm-Square-1.csv',\n",
       " './data/circle-6mm-UpDown-1.csv',\n",
       " './data/circle-8mm-Circle-1.csv',\n",
       " './data/circle-8mm-Eight-1.csv',\n",
       " './data/circle-8mm-LeftRight-1.csv',\n",
       " './data/circle-8mm-Random-1.csv',\n",
       " './data/circle-8mm-Square-1.csv',\n",
       " './data/circle-8mm-UpDown-1.csv',\n",
       " './data/coinUS-10cent-Circle-1.csv',\n",
       " './data/coinUS-10cent-Eight-1.csv',\n",
       " './data/coinUS-10cent-LeftRight-1.csv',\n",
       " './data/coinUS-10cent-Random-1.csv',\n",
       " './data/coinUS-10cent-Square-1.csv',\n",
       " './data/coinUS-10cent-UpDown-1.csv',\n",
       " './data/coinUS-1cent-Circle-1.csv',\n",
       " './data/coinUS-1cent-Eight-1.csv',\n",
       " './data/coinUS-1cent-LeftRight-1.csv',\n",
       " './data/coinUS-1cent-Random-1.csv',\n",
       " './data/coinUS-1cent-Square-1.csv',\n",
       " './data/coinUS-1cent-UpDown-1.csv',\n",
       " './data/coinUS-25cent-Circle-1.csv',\n",
       " './data/coinUS-25cent-Eight-1.csv',\n",
       " './data/coinUS-25cent-LeftRight-1.csv',\n",
       " './data/coinUS-25cent-Random-1.csv',\n",
       " './data/coinUS-25cent-Square-1.csv',\n",
       " './data/coinUS-25cent-UpDown-1.csv',\n",
       " './data/coinUS-5cent-Circle-1.csv',\n",
       " './data/coinUS-5cent-Eight-1.csv',\n",
       " './data/coinUS-5cent-LeftRight-1.csv',\n",
       " './data/coinUS-5cent-Random-1.csv',\n",
       " './data/coinUS-5cent-Square-1.csv',\n",
       " './data/coinUS-5cent-UpDown-1.csv',\n",
       " './data/fiducial-2mm-False-Circle-1.csv',\n",
       " './data/fiducial-2mm-False-Eight-1.csv',\n",
       " './data/fiducial-2mm-False-LeftRight-1.csv',\n",
       " './data/fiducial-2mm-False-Random-1.csv',\n",
       " './data/fiducial-2mm-False-Square-1.csv',\n",
       " './data/fiducial-2mm-False-UpDown-1.csv',\n",
       " './data/fiducial-2mm-True-Circle-1.csv',\n",
       " './data/fiducial-2mm-True-Eight-1.csv',\n",
       " './data/fiducial-2mm-True-LeftRight-1.csv',\n",
       " './data/fiducial-2mm-True-Random-1.csv',\n",
       " './data/fiducial-2mm-True-Square-1.csv',\n",
       " './data/fiducial-2mm-True-UpDown-1.csv',\n",
       " './data/fiducial-3mm-False-Circle-1.csv',\n",
       " './data/fiducial-3mm-False-Eight-1.csv',\n",
       " './data/fiducial-3mm-False-LeftRight-1.csv',\n",
       " './data/fiducial-3mm-False-Random-1.csv',\n",
       " './data/fiducial-3mm-False-Square-1.csv',\n",
       " './data/fiducial-3mm-False-UpDown-1.csv',\n",
       " './data/fiducial-3mm-True-Circle-1.csv',\n",
       " './data/fiducial-3mm-True-Eight-1.csv',\n",
       " './data/fiducial-3mm-True-LeftRight-1.csv',\n",
       " './data/fiducial-3mm-True-Random-1.csv',\n",
       " './data/fiducial-3mm-True-Square-1.csv',\n",
       " './data/fiducial-3mm-True-UpDown-1.csv',\n",
       " './data/fiducial-4mm-False-Circle-1.csv',\n",
       " './data/fiducial-4mm-False-Eight-1.csv',\n",
       " './data/fiducial-4mm-False-LeftRight-1.csv',\n",
       " './data/fiducial-4mm-False-Random-1.csv',\n",
       " './data/fiducial-4mm-False-Square-1.csv',\n",
       " './data/fiducial-4mm-False-UpDown-1.csv',\n",
       " './data/fiducial-4mm-True-Circle-1.csv',\n",
       " './data/fiducial-4mm-True-Eight-1.csv',\n",
       " './data/fiducial-4mm-True-LeftRight-1.csv',\n",
       " './data/fiducial-4mm-True-Random-1.csv',\n",
       " './data/fiducial-4mm-True-Square-1.csv',\n",
       " './data/fiducial-4mm-True-UpDown-1.csv',\n",
       " './data/fiducial-6mm-False-Circle-1.csv',\n",
       " './data/fiducial-6mm-False-Eight-1.csv',\n",
       " './data/fiducial-6mm-False-LeftRight-1.csv',\n",
       " './data/fiducial-6mm-False-Random-1.csv',\n",
       " './data/fiducial-6mm-False-Square-1.csv',\n",
       " './data/fiducial-6mm-False-UpDown-1.csv',\n",
       " './data/fiducial-6mm-True-Circle-1.csv',\n",
       " './data/fiducial-6mm-True-Eight-1.csv',\n",
       " './data/fiducial-6mm-True-LeftRight-1.csv',\n",
       " './data/fiducial-6mm-True-Random-1.csv',\n",
       " './data/fiducial-6mm-True-Square-1.csv',\n",
       " './data/fiducial-6mm-True-UpDown-1.csv',\n",
       " './data/fiducial-8mm-False-Circle-1.csv',\n",
       " './data/fiducial-8mm-False-Eight-1.csv',\n",
       " './data/fiducial-8mm-False-LeftRight-1.csv',\n",
       " './data/fiducial-8mm-False-Random-1.csv',\n",
       " './data/fiducial-8mm-False-Square-1.csv',\n",
       " './data/fiducial-8mm-False-UpDown-1.csv',\n",
       " './data/fiducial-8mm-True-Circle-1.csv',\n",
       " './data/fiducial-8mm-True-Eight-1.csv',\n",
       " './data/fiducial-8mm-True-LeftRight-1.csv',\n",
       " './data/fiducial-8mm-True-Random-1.csv',\n",
       " './data/fiducial-8mm-True-Square-1.csv',\n",
       " './data/fiducial-8mm-True-UpDown-1.csv',\n",
       " './data/finger-index-L-False-Random-1.csv',\n",
       " './data/finger-index-L-True-Random-1.csv',\n",
       " './data/finger-index-R-False-Random-1.csv',\n",
       " './data/finger-index-R-True-Random-1.csv',\n",
       " './data/finger-little-L-False-Random-1.csv',\n",
       " './data/finger-little-L-True-Random-1.csv',\n",
       " './data/finger-little-R-False-Random-1.csv',\n",
       " './data/finger-little-R-True-Random-1.csv',\n",
       " './data/finger-middle-L-False-Random-1.csv',\n",
       " './data/finger-middle-L-True-Random-1.csv',\n",
       " './data/finger-middle-R-False-Random-1.csv',\n",
       " './data/finger-middle-R-True-Random-1.csv',\n",
       " './data/finger-ring-L-False-Random-1.csv',\n",
       " './data/finger-ring-L-True-Random-1.csv',\n",
       " './data/finger-ring-R-False-Random-1.csv',\n",
       " './data/finger-ring-R-True-Random-1.csv',\n",
       " './data/finger-thumb-L-False-Random-1.csv',\n",
       " './data/finger-thumb-L-True-Random-1.csv',\n",
       " './data/finger-thumb-R-False-Random-1.csv',\n",
       " './data/finger-thumb-R-True-Random-1.csv',\n",
       " './data/hand-L-Circle-1.csv',\n",
       " './data/hand-L-Eight-1.csv',\n",
       " './data/hand-L-LeftRight-1.csv',\n",
       " './data/hand-L-Random-1.csv',\n",
       " './data/hand-L-Square-1.csv',\n",
       " './data/hand-L-UpDown-1.csv',\n",
       " './data/hand-R-Circle-1.csv',\n",
       " './data/hand-R-Eight-1.csv',\n",
       " './data/hand-R-LeftRight-1.csv',\n",
       " './data/hand-R-Random-1.csv',\n",
       " './data/hand-R-Square-1.csv',\n",
       " './data/hand-R-UpDown-1.csv',\n",
       " './data/key-1-False-Circle-1.csv',\n",
       " './data/key-1-False-Eight-1.csv',\n",
       " './data/key-1-False-LeftRight-1.csv',\n",
       " './data/key-1-False-Random-1.csv',\n",
       " './data/key-1-False-Square-1.csv',\n",
       " './data/key-1-False-UpDown-1.csv',\n",
       " './data/key-1-True-Circle-1.csv',\n",
       " './data/key-1-True-Eight-1.csv',\n",
       " './data/key-1-True-LeftRight-1.csv',\n",
       " './data/key-1-True-Random-1.csv',\n",
       " './data/key-1-True-Square-1.csv',\n",
       " './data/key-1-True-UpDown-1.csv',\n",
       " './data/key-2-False-Circle-1.csv',\n",
       " './data/key-2-False-Eight-1.csv',\n",
       " './data/key-2-False-LeftRight-1.csv',\n",
       " './data/key-2-False-Random-1.csv',\n",
       " './data/key-2-False-Square-1.csv',\n",
       " './data/key-2-False-UpDown-1.csv',\n",
       " './data/key-2-True-Circle-1.csv',\n",
       " './data/key-2-True-Eight-1.csv',\n",
       " './data/key-2-True-LeftRight-1.csv',\n",
       " './data/key-2-True-Random-1.csv',\n",
       " './data/key-2-True-Square-1.csv',\n",
       " './data/key-2-True-UpDown-1.csv',\n",
       " './data/key-3-False-Circle-1.csv',\n",
       " './data/key-3-False-Eight-1.csv',\n",
       " './data/key-3-False-LeftRight-1.csv',\n",
       " './data/key-3-False-Random-1.csv',\n",
       " './data/key-3-False-Square-1.csv',\n",
       " './data/key-3-False-UpDown-1.csv',\n",
       " './data/key-3-True-Circle-1.csv',\n",
       " './data/key-3-True-Eight-1.csv',\n",
       " './data/key-3-True-LeftRight-1.csv',\n",
       " './data/key-3-True-Random-1.csv',\n",
       " './data/key-3-True-Square-1.csv',\n",
       " './data/key-3-True-UpDown-1.csv',\n",
       " './data/key-4-False-Circle-1.csv',\n",
       " './data/key-4-False-Eight-1.csv',\n",
       " './data/key-4-False-LeftRight-1.csv',\n",
       " './data/key-4-False-Random-1.csv',\n",
       " './data/key-4-False-Square-1.csv',\n",
       " './data/key-4-False-UpDown-1.csv',\n",
       " './data/key-4-True-Circle-1.csv',\n",
       " './data/key-4-True-Eight-1.csv',\n",
       " './data/key-4-True-LeftRight-1.csv',\n",
       " './data/key-4-True-Random-1.csv',\n",
       " './data/key-4-True-Square-1.csv',\n",
       " './data/key-4-True-UpDown-1.csv',\n",
       " './data/square-10mm-False-Circle-1.csv',\n",
       " './data/square-10mm-False-Eight-1.csv',\n",
       " './data/square-10mm-False-LeftRight-1.csv',\n",
       " './data/square-10mm-False-Random-1.csv',\n",
       " './data/square-10mm-False-Square-1.csv',\n",
       " './data/square-10mm-False-UpDown-1.csv',\n",
       " './data/square-10mm-True-Circle-1.csv',\n",
       " './data/square-10mm-True-Eight-1.csv',\n",
       " './data/square-10mm-True-LeftRight-1.csv',\n",
       " './data/square-10mm-True-Random-1.csv',\n",
       " './data/square-10mm-True-Square-1.csv',\n",
       " './data/square-10mm-True-UpDown-1.csv',\n",
       " './data/square-15mm-False-Circle-1.csv',\n",
       " './data/square-15mm-False-Eight-1.csv',\n",
       " './data/square-15mm-False-LeftRight-1.csv',\n",
       " './data/square-15mm-False-Random-1.csv',\n",
       " './data/square-15mm-False-Square-1.csv',\n",
       " './data/square-15mm-False-UpDown-1.csv',\n",
       " './data/square-15mm-True-Circle-1.csv',\n",
       " './data/square-15mm-True-Eight-1.csv',\n",
       " './data/square-15mm-True-LeftRight-1.csv',\n",
       " './data/square-15mm-True-Random-1.csv',\n",
       " './data/square-15mm-True-Square-1.csv',\n",
       " './data/square-15mm-True-UpDown-1.csv',\n",
       " './data/square-20mm-False-Circle-1.csv',\n",
       " './data/square-20mm-False-Eight-1.csv',\n",
       " './data/square-20mm-False-LeftRight-1.csv',\n",
       " './data/square-20mm-False-Random-1.csv',\n",
       " './data/square-20mm-False-Square-1.csv',\n",
       " './data/square-20mm-False-UpDown-1.csv',\n",
       " './data/square-20mm-True-Circle-1.csv',\n",
       " './data/square-20mm-True-Eight-1.csv',\n",
       " './data/square-20mm-True-LeftRight-1.csv',\n",
       " './data/square-20mm-True-Random-1.csv',\n",
       " './data/square-20mm-True-Square-1.csv',\n",
       " './data/square-20mm-True-UpDown-1.csv',\n",
       " './data/square-25mm-False-Circle-1.csv',\n",
       " './data/square-25mm-False-Eight-1.csv',\n",
       " './data/square-25mm-False-LeftRight-1.csv',\n",
       " './data/square-25mm-False-Random-1.csv',\n",
       " './data/square-25mm-False-Square-1.csv',\n",
       " './data/square-25mm-False-UpDown-1.csv',\n",
       " './data/square-25mm-True-Circle-1.csv',\n",
       " './data/square-25mm-True-Eight-1.csv',\n",
       " './data/square-25mm-True-LeftRight-1.csv',\n",
       " './data/square-25mm-True-Random-1.csv',\n",
       " './data/square-25mm-True-Square-1.csv',\n",
       " './data/square-25mm-True-UpDown-1.csv',\n",
       " './data/square-2mm-False-Circle-1.csv',\n",
       " './data/square-2mm-False-Eight-1.csv',\n",
       " './data/square-2mm-False-LeftRight-1.csv',\n",
       " './data/square-2mm-False-Random-1.csv',\n",
       " './data/square-2mm-False-Square-1.csv',\n",
       " './data/square-2mm-False-UpDown-1.csv',\n",
       " './data/square-2mm-True-Circle-1.csv',\n",
       " './data/square-2mm-True-Eight-1.csv',\n",
       " './data/square-2mm-True-LeftRight-1.csv',\n",
       " './data/square-2mm-True-Random-1.csv',\n",
       " './data/square-2mm-True-Square-1.csv',\n",
       " './data/square-2mm-True-UpDown-1.csv',\n",
       " './data/square-30mm-False-Circle-1.csv',\n",
       " './data/square-30mm-False-Eight-1.csv',\n",
       " './data/square-30mm-False-LeftRight-1.csv',\n",
       " './data/square-30mm-False-Random-1.csv',\n",
       " './data/square-30mm-False-Square-1.csv',\n",
       " './data/square-30mm-False-UpDown-1.csv',\n",
       " './data/square-30mm-True-Circle-1.csv',\n",
       " './data/square-30mm-True-Eight-1.csv',\n",
       " './data/square-30mm-True-LeftRight-1.csv',\n",
       " './data/square-30mm-True-Random-1.csv',\n",
       " './data/square-30mm-True-Square-1.csv',\n",
       " './data/square-30mm-True-UpDown-1.csv',\n",
       " './data/square-4mm-False-Circle-1.csv',\n",
       " './data/square-4mm-False-Eight-1.csv',\n",
       " './data/square-4mm-False-LeftRight-1.csv',\n",
       " './data/square-4mm-False-Random-1.csv',\n",
       " './data/square-4mm-False-Square-1.csv',\n",
       " './data/square-4mm-False-UpDown-1.csv',\n",
       " './data/square-4mm-True-Circle-1.csv',\n",
       " './data/square-4mm-True-Eight-1.csv',\n",
       " './data/square-4mm-True-LeftRight-1.csv',\n",
       " './data/square-4mm-True-Random-1.csv',\n",
       " './data/square-4mm-True-Square-1.csv',\n",
       " './data/square-4mm-True-UpDown-1.csv',\n",
       " './data/square-6mm-False-Circle-1.csv',\n",
       " './data/square-6mm-False-Eight-1.csv',\n",
       " './data/square-6mm-False-LeftRight-1.csv',\n",
       " './data/square-6mm-False-Random-1.csv',\n",
       " './data/square-6mm-False-Square-1.csv',\n",
       " './data/square-6mm-False-UpDown-1.csv',\n",
       " './data/square-6mm-True-Circle-1.csv',\n",
       " './data/square-6mm-True-Eight-1.csv',\n",
       " './data/square-6mm-True-LeftRight-1.csv',\n",
       " './data/square-6mm-True-Random-1.csv',\n",
       " './data/square-6mm-True-Square-1.csv',\n",
       " './data/square-6mm-True-UpDown-1.csv',\n",
       " './data/square-8mm-False-Circle-1.csv',\n",
       " './data/square-8mm-False-Eight-1.csv',\n",
       " './data/square-8mm-False-LeftRight-1.csv',\n",
       " './data/square-8mm-False-Random-1.csv',\n",
       " './data/square-8mm-False-Square-1.csv',\n",
       " './data/square-8mm-False-UpDown-1.csv',\n",
       " './data/square-8mm-True-Circle-1.csv',\n",
       " './data/square-8mm-True-Eight-1.csv',\n",
       " './data/square-8mm-True-LeftRight-1.csv',\n",
       " './data/square-8mm-True-Random-1.csv',\n",
       " './data/square-8mm-True-Square-1.csv',\n",
       " './data/square-8mm-True-UpDown-1.csv']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstFiles = []\n",
    "for filename in os.listdir(DATA_PATH):\n",
    "    if filename.endswith(\".csv\"): \n",
    "         lstFiles.append(os.path.join(DATA_PATH, filename))\n",
    "lstFiles = sorted(lstFiles)\n",
    "lstFiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def from_np_array(array_string):\n",
    "    lst = array_string.replace('[', '').replace(']', '').split()\n",
    "    lst = list(map(int, lst)) \n",
    "    return np.array(lst).reshape(49,37)\n",
    "    \n",
    "def read_csv(filename):\n",
    "    df = pd.read_csv(filename, converters={'Matrix': from_np_array})\n",
    "    del df[\"Index\"]\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 317/317 [00:45<00:00,  6.93it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dataset contains 194101 samples\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "lstSampleCount = []\n",
    "for filename in tqdm.tqdm(lstFiles):\n",
    "    df = read_csv(filename)\n",
    "    lstSampleCount.append(len(df))\n",
    "print(\"The dataset contains %i samples\" % np.sum(lstSampleCount))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Showcase Capactive Marker "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Code</th>\n",
       "      <th>Id</th>\n",
       "      <th>Matrix</th>\n",
       "      <th>Recording</th>\n",
       "      <th>Rotation</th>\n",
       "      <th>Size</th>\n",
       "      <th>TimeStamp</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36h11</td>\n",
       "      <td>4</td>\n",
       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -...</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>Random</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36h11</td>\n",
       "      <td>4</td>\n",
       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -5, -...</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.066</td>\n",
       "      <td>Random</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36h11</td>\n",
       "      <td>4</td>\n",
       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, -4, ...</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.131</td>\n",
       "      <td>Random</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36h11</td>\n",
       "      <td>4</td>\n",
       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -5, -4,...</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.200</td>\n",
       "      <td>Random</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36h11</td>\n",
       "      <td>4</td>\n",
       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -5, -5, -4...</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.266</td>\n",
       "      <td>Random</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Code  Id                                             Matrix  Recording  \\\n",
       "0  36h11   4  [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -...          1   \n",
       "1  36h11   4  [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -5, -...          1   \n",
       "2  36h11   4  [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, -4, ...          1   \n",
       "3  36h11   4  [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -5, -4,...          1   \n",
       "4  36h11   4  [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -5, -5, -4...          1   \n",
       "\n",
       "   Rotation  Size  TimeStamp    Type  \n",
       "0      True   8.0      0.000  Random  \n",
       "1      True   8.0      0.066  Random  \n",
       "2      True   8.0      0.131  Random  \n",
       "3      True   8.0      0.200  Random  \n",
       "4      True   8.0      0.266  Random  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = read_csv(\"%sapriltag-36h11-8mm-ID4-True-Random-1.csv\" % DATA_PATH)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(255-np.fliplr(df.iloc[100].Matrix.clip(0,255)), cmap=\"gray\", vmin=0, vmax=255)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}