archive.tar

./Untitled.ipynb0000644000175000017500000000011013451743752013113 0ustar  pipi00000000000000{
 "cells": [],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 2
}
./Triple Basic.ipynb0000644000175000017500000023621113451737174013602 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from picamera.array import PiYUVArray\n",
    "from picamera import PiCamera\n",
    "\n",
    "from scipy.signal import find_peaks, butter, filtfilt\n",
    "from pwm import PWM\n",
    "import tools\n",
    "import threading\n",
    "import ipywidgets as ipw\n",
    "import time\n",
    "#import matplotlib.pyplot as plt\n",
    "import skimage as ski\n",
    "\n",
    "WIDTH_  = 224\n",
    "HEIGHT_ = 160\n",
    "MEDIAN_ = WIDTH_ // 2\n",
    "\n",
    "# Camera resolution\n",
    "res = (WIDTH_, HEIGHT_)\n",
    "\n",
    "# Run a track detection algorithm on a single horizontal line.\n",
    "# Uses YUV420 image format as the Y component corresponds to image intensity (gray image)\n",
    "# and thus there is no need to convert from RGB to BW\n",
    "\n",
    "camera = PiCamera()\n",
    "        \n",
    "# Check the link below for the combinations between mode and resolution\n",
    "# https://picamera.readthedocs.io/en/release-1.13/fov.html#sensor-modes\n",
    "camera.sensor_mode = 7\n",
    "camera.resolution = res\n",
    "camera.framerate = 120\n",
    "\n",
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "\n",
    "# Wn = 0.02, the cut-off frequency, acceptable values are from 0 to 1\n",
    "b, a = butter(3, 0.02)\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "pwm1 = PWM(1)\n",
    "\n",
    "pwm0.period = 20000000\n",
    "pwm1.period = 20000000\n",
    "\n",
    "pwm0.enable = True\n",
    "pwm1.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000\n",
    "pwm1.duty_cycle = 1600000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 1100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 2100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 1600000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e5454301403640948355600f4a5f13a3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "IntRangeSlider(value=(1138, 1275), description='Speed Ranges', max=1500, min=1000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3a1f88ab4c6b421dba7f2ca4f5f118b6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "ToggleButton(value=False, description='Shut it down')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#max speed that this algo works\n",
    "#ucla = 1120000\n",
    "#sonic = 1250000\n",
    "\n",
    "UCLA_              =  1138500\n",
    "USC_               =  1275000\n",
    "SONIC_             =  1275000\n",
    "\n",
    "CENTER_LINE_       =  HEIGHT_ // 2\n",
    "INTERVAL_          =  0.0\n",
    "CENTER_THRESHOLD_  =  WIDTH_ // 10\n",
    "\n",
    "STRAIGHT_     =  1600000\n",
    "RIGHT_        =  1100000\n",
    "LEFT_         =  2100000\n",
    "NUM_PREV_VAL_ =  8\n",
    "\n",
    "killSwitch = ipw.ToggleButton(value=False, description='Shut it down')\n",
    "#minMaxSlider = ipw.IntRangeSlider(value=[UCLA_/1000,SONIC_/1000], min = 1000, max = 1500,step = 1, description = 'Speed Ranges')\n",
    "\n",
    "#display(minMaxSlider)\n",
    "display(killSwitch)\n",
    "\n",
    "def main_loop():\n",
    "    rawCapture = PiYUVArray(camera, size=res)\n",
    "    stream = camera.capture_continuous(rawCapture, format=\"yuv\", use_video_port=True)\n",
    "\n",
    "    #for pwm1\n",
    "    #duty_cycle\n",
    "\n",
    "    #      (array([482, 542], dtype=int32), {'peak_heights': array([186.831036  , 185.01286929])})\n",
    "\n",
    "    numFrames = 0\n",
    "\n",
    "    #if linePos is 1 then the line is to the right of the car\n",
    "    #if linePos is -1 then the line is to the left of the car\n",
    "    #if linePos is 0 either uhoh we're doomed\n",
    "    #if lost is true then the line is lost\n",
    "    linePos = 0\n",
    "    lost = False\n",
    "    prevSteerDC = pwm1.duty_cycle\n",
    "    prevSteerDiffArr = []\n",
    "    prevPeakAvgArr = []\n",
    "    for i in range(NUM_PREV_VAL_):\n",
    "        prevSteerDiffArr.append(-1)\n",
    "        prevPeakAvgArr.append(-1)\n",
    "    \n",
    "    for f in stream:\n",
    "        t = time.time()\n",
    "        #speeds = update_speeds()\n",
    "        \n",
    "        #UCLA_ = speeds[0]\n",
    "        #SONIC_ = speeds[1]\n",
    "        \n",
    "        if killSwitch.value:\n",
    "            break\n",
    "\n",
    "        numFrames += 1\n",
    "        # Get the intensity component of the image (a trick to get black and white images)\n",
    "        I = f.array[:, :, 0]\n",
    "        # Reset the buffer for the next image\n",
    "        rawCapture.truncate(0)\n",
    "        # Select a horizontal line in the middle of the image\n",
    "        L = I[CENTER_LINE_, :]\n",
    "        # Smooth the transitions so we can detect the peaks \n",
    "        Lf = filtfilt(b, a, L)\n",
    "        # Find peaks which are higher than 0.5\n",
    "        p = find_peaks(Lf, height=128)\n",
    "\n",
    "        totalPeakAmt = 0\n",
    "        avgPeakLoc = -520\n",
    "        numPeaks = 0\n",
    "\n",
    "        for peak in p[0]:\n",
    "            numPeaks += 1\n",
    "            totalPeakAmt += peak\n",
    "\n",
    "        if numPeaks != 0:\n",
    "            avgPeakLoc = totalPeakAmt / numPeaks\n",
    "            if numPeaks == 3:\n",
    "                print(\"THIS IS THE BEGINNING OF THE END\")\n",
    "\n",
    "        if avgPeakLoc != -520 :\n",
    "            if avgPeakLoc < MEDIAN_:\n",
    "                if lost and linePos == 1:\n",
    "                    #pwm1.duty_cycle = RIGHT_\n",
    "                    #continue\n",
    "                    break\n",
    "                linePos = -1\n",
    "            else:\n",
    "                if lost and linePos == -1:\n",
    "                    #pwm1.duty_cycle = LEFT_\n",
    "                    #continue\n",
    "                    break\n",
    "                linePos = 1\n",
    "\n",
    "            pwm1.duty_cycle = int(STRAIGHT_ - ((avgPeakLoc - MEDIAN_)/MEDIAN_)*500000)\n",
    "            lost = False\n",
    "        else:\n",
    "            if linePos == -1:\n",
    "                pwm1.duty_cycle = LEFT_\n",
    "            elif linePos == 1:\n",
    "                pwm1.duty_cycle = RIGHT_\n",
    "            else:\n",
    "                pwm1.duty_cycle = STRAIGHT_\n",
    "\n",
    "            lost = True\n",
    "            #pwm0.duty_cycle = SONIC_\n",
    "\n",
    "        if abs(prevSteerDC - STRAIGHT_) < abs(pwm1.duty_cycle - STRAIGHT_) and prevSteerDiffArr[0] > 0 and prevSteerDiffArr[1] > 0 and abs(pwm1.duty_cycle - STRAIGHT_) > 400000:\n",
    "            pwm0.duty_cycle = SONIC_\n",
    "        elif abs(avgPeakLoc - MEDIAN_) <= CENTER_THRESHOLD_:\n",
    "            i = 0\n",
    "            while i < NUM_PREV_VAL_:\n",
    "                if abs(prevPeakAvgArr[i] - MEDIAN_) > CENTER_THRESHOLD_:\n",
    "                    break\n",
    "                i += 1\n",
    "            #print(\"STRAIGHT\")\n",
    "            if i == NUM_PREV_VAL_:\n",
    "                pwm0.duty_cycle = USC_\n",
    "        else:\n",
    "            pwm0.duty_cycle = UCLA_\n",
    "            if abs(pwm1.duty_cycle - STRAIGHT_) > 300000:\n",
    "                pwm0.duty_cycle = UCLA_ + 4000\n",
    "\n",
    "        i = NUM_PREV_VAL_ - 1\n",
    "        while i > 0:\n",
    "            prevSteerDiffArr[i] = prevSteerDiffArr[i - 1]\n",
    "            prevPeakAvgArr[i] = prevPeakAvgArr[i - 1]\n",
    "            i -= 1\n",
    "        \n",
    "        prevSteerDiffArr[0] = abs(pwm1.duty_cycle - STRAIGHT_) - abs(prevSteerDC - STRAIGHT_)\n",
    "        prevPeakAvgArr[0] = avgPeakLoc\n",
    "\n",
    "        prevSteerDC = pwm1.duty_cycle\n",
    "\n",
    "        time_elapsed = time.time() - t\n",
    "        \n",
    "        print(prevPeakAvgArr)\n",
    "        print(prevSteerDiffArr)\n",
    "        print(sum(prevSteerDiffArr))\n",
    "        print(sum(prevSteerDiffArr) / len(prevSteerDiffArr))\n",
    "        print(pwm1.duty_cycle)\n",
    "        print(\"Elapsed {:0.4f} seconds, estimated FPS {:0.2f}\".format(time_elapsed, 1 / time_elapsed))\n",
    "        time.sleep(INTERVAL_)\n",
    "        \n",
    "    pwm0.duty_cycle = 1000000\n",
    "\n",
    "    # Release resources\n",
    "    stream.close()\n",
    "    rawCapture.close()\n",
    "    camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "def update_speeds():\n",
    "    UCLA_ = minMaxSlider.value[0] * 1000\n",
    "    SONIC_ = minMaxSlider.value[1] * 1000\n",
    "    return [UCLA_, SONIC_]\n",
    "minMaxSlider.observe(update_speeds)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = threading.Thread(target=main_loop)\n",
    "t.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-520, -1, -1, -1, -1, -1, -1, -1]\n",
      "[0, -1, -1, -1, -1, -1, -1, -1]\n",
      "-7\n",
      "-0.875\n",
      "1600000\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.55\n",
      "[-520, -520, -1, -1, -1, -1, -1, -1]\n",
      "[0, 0, -1, -1, -1, -1, -1, -1]\n",
      "-6\n",
      "-0.75\n",
      "1600000\n",
      "Elapsed 0.0055 seconds, estimated FPS 183.18\n",
      "[-520, -520, -520, -1, -1, -1, -1, -1]\n",
      "[0, 0, 0, -1, -1, -1, -1, -1]\n",
      "-5\n",
      "-0.625\n",
      "1600000\n",
      "Elapsed 0.0063 seconds, estimated FPS 157.87\n",
      "[-520, -520, -520, -520, -1, -1, -1, -1]\n",
      "[0, 0, 0, 0, -1, -1, -1, -1]\n",
      "-4\n",
      "-0.5\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.59\n",
      "[-520, -520, -520, -520, -520, -1, -1, -1]\n",
      "[0, 0, 0, 0, 0, -1, -1, -1]\n",
      "-3\n",
      "-0.375\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.25\n",
      "[-520, -520, -520, -520, -520, -520, -1, -1]\n",
      "[0, 0, 0, 0, 0, 0, -1, -1]\n",
      "-2\n",
      "-0.25\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -1]\n",
      "[0, 0, 0, 0, 0, 0, 0, -1]\n",
      "-1\n",
      "-0.125\n",
      "1600000\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.78\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.09\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.49\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.07\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.97\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.78\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.69\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.24\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.14\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0062 seconds, estimated FPS 161.40\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.09\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.76\n",
      "[181.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[308036, 0, 0, 0, 0, 0, 0, 0]\n",
      "308036\n",
      "38504.5\n",
      "1291964\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.55\n",
      "[124.0, 181.0, -520, -520, -520, -520, -520, -520]\n",
      "[-254464, 308036, 0, 0, 0, 0, 0, 0]\n",
      "53572\n",
      "6696.5\n",
      "1546428\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.84\n",
      "[79.0, 124.0, 181.0, -520, -520, -520, -520, -520]\n",
      "[93749, -254464, 308036, 0, 0, 0, 0, 0]\n",
      "147321\n",
      "18415.125\n",
      "1747321\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.17\n",
      "[15.0, 79.0, 124.0, 181.0, -520, -520, -520, -520]\n",
      "[285714, 93749, -254464, 308036, 0, 0, 0, 0]\n",
      "433035\n",
      "54129.375\n",
      "2033035\n",
      "Elapsed 0.0065 seconds, estimated FPS 152.74\n",
      "[-520, 15.0, 79.0, 124.0, 181.0, -520, -520, -520]\n",
      "[66965, 285714, 93749, -254464, 308036, 0, 0, 0]\n",
      "500000\n",
      "62500.0\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 182.64\n",
      "[13.0, -520, 15.0, 79.0, 124.0, 181.0, -520, -520]\n",
      "[-58036, 66965, 285714, 93749, -254464, 308036, 0, 0]\n",
      "441964\n",
      "55245.5\n",
      "2041964\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.67\n",
      "[58.0, 13.0, -520, 15.0, 79.0, 124.0, 181.0, -520]\n",
      "[-200893, -58036, 66965, 285714, 93749, -254464, 308036, 0]\n",
      "241071\n",
      "30133.875\n",
      "1841071\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.66\n",
      "[97.0, 58.0, 13.0, -520, 15.0, 79.0, 124.0, 181.0]\n",
      "[-174107, -200893, -58036, 66965, 285714, 93749, -254464, 308036]\n",
      "66964\n",
      "8370.5\n",
      "1666964\n",
      "Elapsed 0.0092 seconds, estimated FPS 109.28\n",
      "[145.0, 97.0, 58.0, 13.0, -520, 15.0, 79.0, 124.0]\n",
      "[80358, -174107, -200893, -58036, 66965, 285714, 93749, -254464]\n",
      "-160714\n",
      "-20089.25\n",
      "1452678\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.81\n",
      "[-520, 145.0, 97.0, 58.0, 13.0, -520, 15.0, 79.0]\n",
      "[352678, 80358, -174107, -200893, -58036, 66965, 285714, 93749]\n",
      "446428\n",
      "55803.5\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.38\n",
      "[-520, -520, 145.0, 97.0, 58.0, 13.0, -520, 15.0]\n",
      "[0, 352678, 80358, -174107, -200893, -58036, 66965, 285714]\n",
      "352679\n",
      "44084.875\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.50\n",
      "[-520, -520, -520, 145.0, 97.0, 58.0, 13.0, -520]\n",
      "[0, 0, 352678, 80358, -174107, -200893, -58036, 66965]\n",
      "66965\n",
      "8370.625\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.14\n",
      "[-520, -520, -520, -520, 145.0, 97.0, 58.0, 13.0]\n",
      "[0, 0, 0, 352678, 80358, -174107, -200893, -58036]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0098 seconds, estimated FPS 101.74\n",
      "[-520, -520, -520, -520, -520, 145.0, 97.0, 58.0]\n",
      "[0, 0, 0, 0, 352678, 80358, -174107, -200893]\n",
      "58036\n",
      "7254.5\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.09\n",
      "[-520, -520, -520, -520, -520, -520, 145.0, 97.0]\n",
      "[0, 0, 0, 0, 0, 352678, 80358, -174107]\n",
      "258929\n",
      "32366.125\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.57\n",
      "[-520, -520, -520, -520, -520, -520, -520, 145.0]\n",
      "[0, 0, 0, 0, 0, 0, 352678, 80358]\n",
      "433036\n",
      "54129.5\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 352678]\n",
      "352678\n",
      "44084.75\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.52\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0099 seconds, estimated FPS 101.38\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.85\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.91\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.83\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0101 seconds, estimated FPS 98.80\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.55\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.32\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.26\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.53\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.77\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.18\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.14\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.30\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.65\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.34\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.96\n",
      "[158.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-294642, 0, 0, 0, 0, 0, 0, 0]\n",
      "-294642\n",
      "-36830.25\n",
      "1394642\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.79\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[119.0, 158.0, -520, -520, -520, -520, -520, -520]\n",
      "[-174108, -294642, 0, 0, 0, 0, 0, 0]\n",
      "-468750\n",
      "-58593.75\n",
      "1568750\n",
      "Elapsed 0.0053 seconds, estimated FPS 189.20\n",
      "[66.0, 119.0, 158.0, -520, -520, -520, -520, -520]\n",
      "[174107, -174108, -294642, 0, 0, 0, 0, 0]\n",
      "-294643\n",
      "-36830.375\n",
      "1805357\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.16\n",
      "[6.0, 66.0, 119.0, 158.0, -520, -520, -520, -520]\n",
      "[267857, 174107, -174108, -294642, 0, 0, 0, 0]\n",
      "-26786\n",
      "-3348.25\n",
      "2073214\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.21\n",
      "[5.0, 6.0, 66.0, 119.0, 158.0, -520, -520, -520]\n",
      "[4464, 267857, 174107, -174108, -294642, 0, 0, 0]\n",
      "-22322\n",
      "-2790.25\n",
      "2077678\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.11\n",
      "[-520, 5.0, 6.0, 66.0, 119.0, 158.0, -520, -520]\n",
      "[22322, 4464, 267857, 174107, -174108, -294642, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 182.35\n",
      "[-520, -520, 5.0, 6.0, 66.0, 119.0, 158.0, -520]\n",
      "[0, 22322, 4464, 267857, 174107, -174108, -294642, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.81\n",
      "[-520, -520, -520, 5.0, 6.0, 66.0, 119.0, 158.0]\n",
      "[0, 0, 22322, 4464, 267857, 174107, -174108, -294642]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.10\n",
      "[-520, -520, -520, -520, 5.0, 6.0, 66.0, 119.0]\n",
      "[0, 0, 0, 22322, 4464, 267857, 174107, -174108]\n",
      "294642\n",
      "36830.25\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.95\n",
      "[-520, -520, -520, -520, -520, 5.0, 6.0, 66.0]\n",
      "[0, 0, 0, 0, 22322, 4464, 267857, 174107]\n",
      "468750\n",
      "58593.75\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.46\n",
      "[-520, -520, -520, -520, -520, -520, 5.0, 6.0]\n",
      "[0, 0, 0, 0, 0, 22322, 4464, 267857]\n",
      "294643\n",
      "36830.375\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.14\n",
      "[46.0, -520, -520, -520, -520, -520, -520, 5.0]\n",
      "[-205358, 0, 0, 0, 0, 0, 22322, 4464]\n",
      "-178572\n",
      "-22321.5\n",
      "1894642\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.35\n",
      "[135.0, 46.0, -520, -520, -520, -520, -520, -520]\n",
      "[-191963, -205358, 0, 0, 0, 0, 0, 22322]\n",
      "-374999\n",
      "-46874.875\n",
      "1497321\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.43\n",
      "[-520, 135.0, 46.0, -520, -520, -520, -520, -520]\n",
      "[397321, -191963, -205358, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.57\n",
      "[-520, -520, 135.0, 46.0, -520, -520, -520, -520]\n",
      "[0, 397321, -191963, -205358, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.23\n",
      "[-520, -520, -520, 135.0, 46.0, -520, -520, -520]\n",
      "[0, 0, 397321, -191963, -205358, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.70\n",
      "[-520, -520, -520, -520, 135.0, 46.0, -520, -520]\n",
      "[0, 0, 0, 397321, -191963, -205358, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.27\n",
      "[-520, -520, -520, -520, -520, 135.0, 46.0, -520]\n",
      "[0, 0, 0, 0, 397321, -191963, -205358, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.98\n",
      "[-520, -520, -520, -520, -520, -520, 135.0, 46.0]\n",
      "[0, 0, 0, 0, 0, 397321, -191963, -205358]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.33\n",
      "[-520, -520, -520, -520, -520, -520, -520, 135.0]\n",
      "[0, 0, 0, 0, 0, 0, 397321, -191963]\n",
      "205358\n",
      "25669.75\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.73\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 397321]\n",
      "397321\n",
      "49665.125\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.95\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.30\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.20\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0100 seconds, estimated FPS 99.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.67\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 168.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.32\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.07\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.33\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.46\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.86\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.01\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.89\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.79\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.28\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.52\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.15\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.16\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.53\n",
      "[217.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-31250, 0, 0, 0, 0, 0, 0, 0]\n",
      "-31250\n",
      "-3906.25\n",
      "1131250\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.97\n",
      "[145.0, 217.0, -520, -520, -520, -520, -520, -520]\n",
      "[-321428, -31250, 0, 0, 0, 0, 0, 0]\n",
      "-352678\n",
      "-44084.75\n",
      "1452678\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.96\n",
      "[92.0, 145.0, 217.0, -520, -520, -520, -520, -520]\n",
      "[-58037, -321428, -31250, 0, 0, 0, 0, 0]\n",
      "-410715\n",
      "-51339.375\n",
      "1689285\n",
      "Elapsed 0.0053 seconds, estimated FPS 187.99\n",
      "[19.0, 92.0, 145.0, 217.0, -520, -520, -520, -520]\n",
      "[325893, -58037, -321428, -31250, 0, 0, 0, 0]\n",
      "-84822\n",
      "-10602.75\n",
      "2015178\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.50\n",
      "[-520, 19.0, 92.0, 145.0, 217.0, -520, -520, -520]\n",
      "[84822, 325893, -58037, -321428, -31250, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.46\n",
      "[-520, -520, 19.0, 92.0, 145.0, 217.0, -520, -520]\n",
      "[0, 84822, 325893, -58037, -321428, -31250, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.31\n",
      "[-520, -520, -520, 19.0, 92.0, 145.0, 217.0, -520]\n",
      "[0, 0, 84822, 325893, -58037, -321428, -31250, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 170.96\n",
      "[-520, -520, -520, -520, 19.0, 92.0, 145.0, 217.0]\n",
      "[0, 0, 0, 84822, 325893, -58037, -321428, -31250]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0102 seconds, estimated FPS 98.49\n",
      "[-520, -520, -520, -520, -520, 19.0, 92.0, 145.0]\n",
      "[0, 0, 0, 0, 84822, 325893, -58037, -321428]\n",
      "31250\n",
      "3906.25\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.49\n",
      "[-520, -520, -520, -520, -520, -520, 19.0, 92.0]\n",
      "[0, 0, 0, 0, 0, 84822, 325893, -58037]\n",
      "352678\n",
      "44084.75\n",
      "2100000\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.27\n",
      "[-520, -520, -520, -520, -520, -520, -520, 19.0]\n",
      "[0, 0, 0, 0, 0, 0, 84822, 325893]\n",
      "410715\n",
      "51339.375\n",
      "2100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 84822]\n",
      "84822\n",
      "10602.75\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.24\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.46\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.48\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.20\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.10\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.26\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.85\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.38\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.69\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.48\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.54\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.23\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.80\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.27\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.82\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.73\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.92\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.35\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.91\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.37\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.16\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.04\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.82\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.45\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.15\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.06\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.98\n",
      "[8.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-35715, 0, 0, 0, 0, 0, 0, 0]\n",
      "-35715\n",
      "-4464.375\n",
      "2064285\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.50\n",
      "[41.0, 8.0, -520, -520, -520, -520, -520, -520]\n",
      "[-147321, -35715, 0, 0, 0, 0, 0, 0]\n",
      "-183036\n",
      "-22879.5\n",
      "1916964\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.92\n",
      "[62.0, 41.0, 8.0, -520, -520, -520, -520, -520]\n",
      "[-93750, -147321, -35715, 0, 0, 0, 0, 0]\n",
      "-276786\n",
      "-34598.25\n",
      "1823214\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.03\n",
      "[80.0, 62.0, 41.0, 8.0, -520, -520, -520, -520]\n",
      "[-80357, -93750, -147321, -35715, 0, 0, 0, 0]\n",
      "-357143\n",
      "-44642.875\n",
      "1742857\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.19\n",
      "[93.0, 80.0, 62.0, 41.0, 8.0, -520, -520, -520]\n",
      "[-58036, -80357, -93750, -147321, -35715, 0, 0, 0]\n",
      "-415179\n",
      "-51897.375\n",
      "1684821\n",
      "Elapsed 0.0051 seconds, estimated FPS 197.76\n",
      "[109.0, 93.0, 80.0, 62.0, 41.0, 8.0, -520, -520]\n",
      "[-71429, -58036, -80357, -93750, -147321, -35715, 0, 0]\n",
      "-486608\n",
      "-60826.0\n",
      "1613392\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.34\n",
      "[119.0, 109.0, 93.0, 80.0, 62.0, 41.0, 8.0, -520]\n",
      "[17858, -71429, -58036, -80357, -93750, -147321, -35715, 0]\n",
      "-468750\n",
      "-58593.75\n",
      "1568750\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.77\n",
      "[120.0, 119.0, 109.0, 93.0, 80.0, 62.0, 41.0, 8.0]\n",
      "[4465, 17858, -71429, -58036, -80357, -93750, -147321, -35715]\n",
      "-464285\n",
      "-58035.625\n",
      "1564285\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.80\n",
      "[112.0, 120.0, 119.0, 109.0, 93.0, 80.0, 62.0, 41.0]\n",
      "[-35715, 4465, 17858, -71429, -58036, -80357, -93750, -147321]\n",
      "-464285\n",
      "-58035.625\n",
      "1600000\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.23\n",
      "[99.0, 112.0, 120.0, 119.0, 109.0, 93.0, 80.0, 62.0]\n",
      "[58035, -35715, 4465, 17858, -71429, -58036, -80357, -93750]\n",
      "-258929\n",
      "-32366.125\n",
      "1658035\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.23\n",
      "[85.0, 99.0, 112.0, 120.0, 119.0, 109.0, 93.0, 80.0]\n",
      "[62500, 58035, -35715, 4465, 17858, -71429, -58036, -80357]\n",
      "-102679\n",
      "-12834.875\n",
      "1720535\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.00\n",
      "[72.0, 85.0, 99.0, 112.0, 120.0, 119.0, 109.0, 93.0]\n",
      "[58036, 62500, 58035, -35715, 4465, 17858, -71429, -58036]\n",
      "35714\n",
      "4464.25\n",
      "1778571\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.97\n",
      "[59.0, 72.0, 85.0, 99.0, 112.0, 120.0, 119.0, 109.0]\n",
      "[58036, 58036, 62500, 58035, -35715, 4465, 17858, -71429]\n",
      "151786\n",
      "18973.25\n",
      "1836607\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.95\n",
      "[50.0, 59.0, 72.0, 85.0, 99.0, 112.0, 120.0, 119.0]\n",
      "[40178, 58036, 58036, 62500, 58035, -35715, 4465, 17858]\n",
      "263393\n",
      "32924.125\n",
      "1876785\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.77\n",
      "[46.0, 50.0, 59.0, 72.0, 85.0, 99.0, 112.0, 120.0]\n",
      "[17857, 40178, 58036, 58036, 62500, 58035, -35715, 4465]\n",
      "263392\n",
      "32924.0\n",
      "1894642\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.95\n",
      "[41.0, 46.0, 50.0, 59.0, 72.0, 85.0, 99.0, 112.0]\n",
      "[22322, 17857, 40178, 58036, 58036, 62500, 58035, -35715]\n",
      "281249\n",
      "35156.125\n",
      "1916964\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.44\n",
      "[42.0, 41.0, 46.0, 50.0, 59.0, 72.0, 85.0, 99.0]\n",
      "[-4464, 22322, 17857, 40178, 58036, 58036, 62500, 58035]\n",
      "312500\n",
      "39062.5\n",
      "1912500\n",
      "Elapsed 0.0104 seconds, estimated FPS 96.14\n",
      "[46.0, 42.0, 41.0, 46.0, 50.0, 59.0, 72.0, 85.0]\n",
      "[-17858, -4464, 22322, 17857, 40178, 58036, 58036, 62500]\n",
      "236607\n",
      "29575.875\n",
      "1894642\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.33\n",
      "[51.0, 46.0, 42.0, 41.0, 46.0, 50.0, 59.0, 72.0]\n",
      "[-22321, -17858, -4464, 22322, 17857, 40178, 58036, 58036]\n",
      "151786\n",
      "18973.25\n",
      "1872321\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.74\n",
      "[56.0, 51.0, 46.0, 42.0, 41.0, 46.0, 50.0, 59.0]\n",
      "[-22321, -22321, -17858, -4464, 22322, 17857, 40178, 58036]\n",
      "71429\n",
      "8928.625\n",
      "1850000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.02\n",
      "[58.0, 56.0, 51.0, 46.0, 42.0, 41.0, 46.0, 50.0]\n",
      "[-8929, -22321, -22321, -17858, -4464, 22322, 17857, 40178]\n",
      "4464\n",
      "558.0\n",
      "1841071\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.60\n",
      "[63.0, 58.0, 56.0, 51.0, 46.0, 42.0, 41.0, 46.0]\n",
      "[-22321, -8929, -22321, -22321, -17858, -4464, 22322, 17857]\n",
      "-58035\n",
      "-7254.375\n",
      "1818750\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.06\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[65.0, 63.0, 58.0, 56.0, 51.0, 46.0, 42.0, 41.0]\n",
      "[-8929, -22321, -8929, -22321, -22321, -17858, -4464, 22322]\n",
      "-84821\n",
      "-10602.625\n",
      "1809821\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.59\n",
      "[64.0, 65.0, 63.0, 58.0, 56.0, 51.0, 46.0, 42.0]\n",
      "[4464, -8929, -22321, -8929, -22321, -22321, -17858, -4464]\n",
      "-102679\n",
      "-12834.875\n",
      "1814285\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.33\n",
      "[64.0, 64.0, 65.0, 63.0, 58.0, 56.0, 51.0, 46.0]\n",
      "[0, 4464, -8929, -22321, -8929, -22321, -22321, -17858]\n",
      "-98215\n",
      "-12276.875\n",
      "1814285\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.04\n",
      "[64.0, 64.0, 64.0, 65.0, 63.0, 58.0, 56.0, 51.0]\n",
      "[0, 0, 4464, -8929, -22321, -8929, -22321, -22321]\n",
      "-80357\n",
      "-10044.625\n",
      "1814285\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.61\n",
      "[63.0, 64.0, 64.0, 64.0, 65.0, 63.0, 58.0, 56.0]\n",
      "[4465, 0, 0, 4464, -8929, -22321, -8929, -22321]\n",
      "-53571\n",
      "-6696.375\n",
      "1818750\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.12\n",
      "[58.0, 63.0, 64.0, 64.0, 64.0, 65.0, 63.0, 58.0]\n",
      "[22321, 4465, 0, 0, 4464, -8929, -22321, -8929]\n",
      "-8929\n",
      "-1116.125\n",
      "1841071\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.76\n",
      "[53.0, 58.0, 63.0, 64.0, 64.0, 64.0, 65.0, 63.0]\n",
      "[22321, 22321, 4465, 0, 0, 4464, -8929, -22321]\n",
      "22321\n",
      "2790.125\n",
      "1863392\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.20\n",
      "[49.0, 53.0, 58.0, 63.0, 64.0, 64.0, 64.0, 65.0]\n",
      "[17858, 22321, 22321, 4465, 0, 0, 4464, -8929]\n",
      "62500\n",
      "7812.5\n",
      "1881250\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.54\n",
      "[46.0, 49.0, 53.0, 58.0, 63.0, 64.0, 64.0, 64.0]\n",
      "[13392, 17858, 22321, 22321, 4465, 0, 0, 4464]\n",
      "84821\n",
      "10602.625\n",
      "1894642\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.94\n",
      "[41.0, 46.0, 49.0, 53.0, 58.0, 63.0, 64.0, 64.0]\n",
      "[22322, 13392, 17858, 22321, 22321, 4465, 0, 0]\n",
      "102679\n",
      "12834.875\n",
      "1916964\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.45\n",
      "[36.0, 41.0, 46.0, 49.0, 53.0, 58.0, 63.0, 64.0]\n",
      "[22321, 22322, 13392, 17858, 22321, 22321, 4465, 0]\n",
      "125000\n",
      "15625.0\n",
      "1939285\n",
      "Elapsed 0.0064 seconds, estimated FPS 156.66\n",
      "[34.0, 36.0, 41.0, 46.0, 49.0, 53.0, 58.0, 63.0]\n",
      "[8929, 22321, 22322, 13392, 17858, 22321, 22321, 4465]\n",
      "133929\n",
      "16741.125\n",
      "1948214\n",
      "Elapsed 0.0106 seconds, estimated FPS 94.77\n",
      "[-520, 34.0, 36.0, 41.0, 46.0, 49.0, 53.0, 58.0]\n",
      "[151786, 8929, 22321, 22322, 13392, 17858, 22321, 22321]\n",
      "281250\n",
      "35156.25\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.81\n",
      "[29.0, -520, 34.0, 36.0, 41.0, 46.0, 49.0, 53.0]\n",
      "[-129465, 151786, 8929, 22321, 22322, 13392, 17858, 22321]\n",
      "129464\n",
      "16183.0\n",
      "1970535\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.48\n",
      "[35.0, 29.0, -520, 34.0, 36.0, 41.0, 46.0, 49.0]\n",
      "[-26785, -129465, 151786, 8929, 22321, 22322, 13392, 17858]\n",
      "80358\n",
      "10044.75\n",
      "1943750\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.83\n",
      "[48.0, 35.0, 29.0, -520, 34.0, 36.0, 41.0, 46.0]\n",
      "[-58036, -26785, -129465, 151786, 8929, 22321, 22322, 13392]\n",
      "4464\n",
      "558.0\n",
      "1885714\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.22\n",
      "[62.0, 48.0, 35.0, 29.0, -520, 34.0, 36.0, 41.0]\n",
      "[-62500, -58036, -26785, -129465, 151786, 8929, 22321, 22322]\n",
      "-71428\n",
      "-8928.5\n",
      "1823214\n",
      "Elapsed 0.0101 seconds, estimated FPS 99.20\n",
      "[80.0, 62.0, 48.0, 35.0, 29.0, -520, 34.0, 36.0]\n",
      "[-80357, -62500, -58036, -26785, -129465, 151786, 8929, 22321]\n",
      "-174107\n",
      "-21763.375\n",
      "1742857\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.34\n",
      "[97.0, 80.0, 62.0, 48.0, 35.0, 29.0, -520, 34.0]\n",
      "[-75893, -80357, -62500, -58036, -26785, -129465, 151786, 8929]\n",
      "-272321\n",
      "-34040.125\n",
      "1666964\n",
      "Elapsed 0.0052 seconds, estimated FPS 193.13\n",
      "[116.0, 97.0, 80.0, 62.0, 48.0, 35.0, 29.0, -520]\n",
      "[-49106, -75893, -80357, -62500, -58036, -26785, -129465, 151786]\n",
      "-330356\n",
      "-41294.5\n",
      "1582142\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.88\n",
      "[125.0, 116.0, 97.0, 80.0, 62.0, 48.0, 35.0, 29.0]\n",
      "[40178, -49106, -75893, -80357, -62500, -58036, -26785, -129465]\n",
      "-441964\n",
      "-55245.5\n",
      "1541964\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.93\n",
      "[126.0, 125.0, 116.0, 97.0, 80.0, 62.0, 48.0, 35.0]\n",
      "[4464, 40178, -49106, -75893, -80357, -62500, -58036, -26785]\n",
      "-308035\n",
      "-38504.375\n",
      "1537500\n",
      "Elapsed 0.0093 seconds, estimated FPS 108.03\n",
      "[116.0, 126.0, 125.0, 116.0, 97.0, 80.0, 62.0, 48.0]\n",
      "[-44642, 4464, 40178, -49106, -75893, -80357, -62500, -58036]\n",
      "-325892\n",
      "-40736.5\n",
      "1582142\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.67\n",
      "[95.0, 116.0, 126.0, 125.0, 116.0, 97.0, 80.0, 62.0]\n",
      "[58034, -44642, 4464, 40178, -49106, -75893, -80357, -62500]\n",
      "-209822\n",
      "-26227.75\n",
      "1675892\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.60\n",
      "[65.0, 95.0, 116.0, 126.0, 125.0, 116.0, 97.0, 80.0]\n",
      "[133929, 58034, -44642, 4464, 40178, -49106, -75893, -80357]\n",
      "-13393\n",
      "-1674.125\n",
      "1809821\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.74\n",
      "[37.0, 65.0, 95.0, 116.0, 126.0, 125.0, 116.0, 97.0]\n",
      "[125000, 133929, 58034, -44642, 4464, 40178, -49106, -75893]\n",
      "191964\n",
      "23995.5\n",
      "1934821\n",
      "Elapsed 0.0064 seconds, estimated FPS 157.22\n",
      "[7.0, 37.0, 65.0, 95.0, 116.0, 126.0, 125.0, 116.0]\n",
      "[133929, 125000, 133929, 58034, -44642, 4464, 40178, -49106]\n",
      "401786\n",
      "50223.25\n",
      "2068750\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.19\n",
      "[-520, 7.0, 37.0, 65.0, 95.0, 116.0, 126.0, 125.0]\n",
      "[31250, 133929, 125000, 133929, 58034, -44642, 4464, 40178]\n",
      "482142\n",
      "60267.75\n",
      "2100000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.80\n",
      "[-520, -520, 7.0, 37.0, 65.0, 95.0, 116.0, 126.0]\n",
      "[0, 31250, 133929, 125000, 133929, 58034, -44642, 4464]\n",
      "441964\n",
      "55245.5\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.56\n",
      "[2.0, -520, -520, 7.0, 37.0, 65.0, 95.0, 116.0]\n",
      "[-8929, 0, 31250, 133929, 125000, 133929, 58034, -44642]\n",
      "428571\n",
      "53571.375\n",
      "2091071\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.14\n",
      "[35.0, 2.0, -520, -520, 7.0, 37.0, 65.0, 95.0]\n",
      "[-147321, -8929, 0, 31250, 133929, 125000, 133929, 58034]\n",
      "325892\n",
      "40736.5\n",
      "1943750\n",
      "Elapsed 0.0061 seconds, estimated FPS 165.01\n",
      "[62.0, 35.0, 2.0, -520, -520, 7.0, 37.0, 65.0]\n",
      "[-120536, -147321, -8929, 0, 31250, 133929, 125000, 133929]\n",
      "147322\n",
      "18415.25\n",
      "1823214\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.08\n",
      "[90.0, 62.0, 35.0, 2.0, -520, -520, 7.0, 37.0]\n",
      "[-125000, -120536, -147321, -8929, 0, 31250, 133929, 125000]\n",
      "-111607\n",
      "-13950.875\n",
      "1698214\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.19\n",
      "[119.0, 90.0, 62.0, 35.0, 2.0, -520, -520, 7.0]\n",
      "[-66964, -125000, -120536, -147321, -8929, 0, 31250, 133929]\n",
      "-303571\n",
      "-37946.375\n",
      "1568750\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.15\n",
      "[145.0, 119.0, 90.0, 62.0, 35.0, 2.0, -520, -520]\n",
      "[116072, -66964, -125000, -120536, -147321, -8929, 0, 31250]\n",
      "-321428\n",
      "-40178.5\n",
      "1452678\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.41\n",
      "[157.0, 145.0, 119.0, 90.0, 62.0, 35.0, 2.0, -520]\n",
      "[53571, 116072, -66964, -125000, -120536, -147321, -8929, 0]\n",
      "-299107\n",
      "-37388.375\n",
      "1399107\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.86\n",
      "[165.0, 157.0, 145.0, 119.0, 90.0, 62.0, 35.0, 2.0]\n",
      "[35715, 53571, 116072, -66964, -125000, -120536, -147321, -8929]\n",
      "-263392\n",
      "-32924.0\n",
      "1363392\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.94\n",
      "[162.0, 165.0, 157.0, 145.0, 119.0, 90.0, 62.0, 35.0]\n",
      "[-13393, 35715, 53571, 116072, -66964, -125000, -120536, -147321]\n",
      "-267856\n",
      "-33482.0\n",
      "1376785\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.29\n",
      "[149.0, 162.0, 165.0, 157.0, 145.0, 119.0, 90.0, 62.0]\n",
      "[-58036, -13393, 35715, 53571, 116072, -66964, -125000, -120536]\n",
      "-178571\n",
      "-22321.375\n",
      "1434821\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.35\n",
      "[129.0, 149.0, 162.0, 165.0, 157.0, 145.0, 119.0, 90.0]\n",
      "[-89286, -58036, -13393, 35715, 53571, 116072, -66964, -125000]\n",
      "-147321\n",
      "-18415.125\n",
      "1524107\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.94\n",
      "[109.0, 129.0, 149.0, 162.0, 165.0, 157.0, 145.0, 119.0]\n",
      "[-62501, -89286, -58036, -13393, 35715, 53571, 116072, -66964]\n",
      "-84822\n",
      "-10602.75\n",
      "1613392\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.49\n",
      "[83.0, 109.0, 129.0, 149.0, 162.0, 165.0, 157.0, 145.0]\n",
      "[116072, -62501, -89286, -58036, -13393, 35715, 53571, 116072]\n",
      "98214\n",
      "12276.75\n",
      "1729464\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.83\n",
      "[65.0, 83.0, 109.0, 129.0, 149.0, 162.0, 165.0, 157.0]\n",
      "[80357, 116072, -62501, -89286, -58036, -13393, 35715, 53571]\n",
      "62499\n",
      "7812.375\n",
      "1809821\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.18\n",
      "[53.0, 65.0, 83.0, 109.0, 129.0, 149.0, 162.0, 165.0]\n",
      "[53571, 80357, 116072, -62501, -89286, -58036, -13393, 35715]\n",
      "62499\n",
      "7812.375\n",
      "1863392\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.22\n",
      "[51.0, 53.0, 65.0, 83.0, 109.0, 129.0, 149.0, 162.0]\n",
      "[8929, 53571, 80357, 116072, -62501, -89286, -58036, -13393]\n",
      "35713\n",
      "4464.125\n",
      "1872321\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.49\n",
      "[61.0, 51.0, 53.0, 65.0, 83.0, 109.0, 129.0, 149.0]\n",
      "[-44643, 8929, 53571, 80357, 116072, -62501, -89286, -58036]\n",
      "4463\n",
      "557.875\n",
      "1827678\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.05\n",
      "[77.0, 61.0, 51.0, 53.0, 65.0, 83.0, 109.0, 129.0]\n",
      "[-71428, -44643, 8929, 53571, 80357, 116072, -62501, -89286]\n",
      "-8929\n",
      "-1116.125\n",
      "1756250\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[95.0, 77.0, 61.0, 51.0, 53.0, 65.0, 83.0, 109.0]\n",
      "[-80358, -71428, -44643, 8929, 53571, 80357, 116072, -62501]\n",
      "-1\n",
      "-0.125\n",
      "1675892\n",
      "Elapsed 0.0062 seconds, estimated FPS 162.11\n",
      "[108.0, 95.0, 77.0, 61.0, 51.0, 53.0, 65.0, 83.0]\n",
      "[-58035, -80358, -71428, -44643, 8929, 53571, 80357, 116072]\n",
      "4465\n",
      "558.125\n",
      "1617857\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.47\n",
      "[119.0, 108.0, 95.0, 77.0, 61.0, 51.0, 53.0, 65.0]\n",
      "[13393, -58035, -80358, -71428, -44643, 8929, 53571, 80357]\n",
      "-98214\n",
      "-12276.75\n",
      "1568750\n",
      "Elapsed 0.0052 seconds, estimated FPS 191.32\n",
      "[129.0, 119.0, 108.0, 95.0, 77.0, 61.0, 51.0, 53.0]\n",
      "[44643, 13393, -58035, -80358, -71428, -44643, 8929, 53571]\n",
      "-133928\n",
      "-16741.0\n",
      "1524107\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.21\n",
      "[128.0, 129.0, 119.0, 108.0, 95.0, 77.0, 61.0, 51.0]\n",
      "[-4464, 44643, 13393, -58035, -80358, -71428, -44643, 8929]\n",
      "-191963\n",
      "-23995.375\n",
      "1528571\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.07\n",
      "[127.0, 128.0, 129.0, 119.0, 108.0, 95.0, 77.0, 61.0]\n",
      "[-4464, -4464, 44643, 13393, -58035, -80358, -71428, -44643]\n",
      "-205356\n",
      "-25669.5\n",
      "1533035\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.36\n",
      "[119.0, 127.0, 128.0, 129.0, 119.0, 108.0, 95.0, 77.0]\n",
      "[-35715, -4464, -4464, 44643, 13393, -58035, -80358, -71428]\n",
      "-196428\n",
      "-24553.5\n",
      "1568750\n",
      "Elapsed 0.0052 seconds, estimated FPS 192.43\n",
      "[112.0, 119.0, 127.0, 128.0, 129.0, 119.0, 108.0, 95.0]\n",
      "[-31250, -35715, -4464, -4464, 44643, 13393, -58035, -80358]\n",
      "-156250\n",
      "-19531.25\n",
      "1600000\n",
      "Elapsed 0.0052 seconds, estimated FPS 191.42\n",
      "[104.0, 112.0, 119.0, 127.0, 128.0, 129.0, 119.0, 108.0]\n",
      "[35714, -31250, -35715, -4464, -4464, 44643, 13393, -58035]\n",
      "-40178\n",
      "-5022.25\n",
      "1635714\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.93\n",
      "[97.0, 104.0, 112.0, 119.0, 127.0, 128.0, 129.0, 119.0]\n",
      "[31250, 35714, -31250, -35715, -4464, -4464, 44643, 13393]\n",
      "49107\n",
      "6138.375\n",
      "1666964\n",
      "Elapsed 0.0054 seconds, estimated FPS 184.89\n",
      "[90.0, 97.0, 104.0, 112.0, 119.0, 127.0, 128.0, 129.0]\n",
      "[31250, 31250, 35714, -31250, -35715, -4464, -4464, 44643]\n",
      "66964\n",
      "8370.5\n",
      "1698214\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.94\n",
      "[88.0, 90.0, 97.0, 104.0, 112.0, 119.0, 127.0, 128.0]\n",
      "[8928, 31250, 31250, 35714, -31250, -35715, -4464, -4464]\n",
      "31249\n",
      "3906.125\n",
      "1707142\n",
      "Elapsed 0.0102 seconds, estimated FPS 98.33\n",
      "[87.0, 88.0, 90.0, 97.0, 104.0, 112.0, 119.0, 127.0]\n",
      "[4465, 8928, 31250, 31250, 35714, -31250, -35715, -4464]\n",
      "40178\n",
      "5022.25\n",
      "1711607\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.44\n",
      "[89.0, 87.0, 88.0, 90.0, 97.0, 104.0, 112.0, 119.0]\n",
      "[-8929, 4465, 8928, 31250, 31250, 35714, -31250, -35715]\n",
      "35713\n",
      "4464.125\n",
      "1702678\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.41\n",
      "[93.0, 89.0, 87.0, 88.0, 90.0, 97.0, 104.0, 112.0]\n",
      "[-17857, -8929, 4465, 8928, 31250, 31250, 35714, -31250]\n",
      "53571\n",
      "6696.375\n",
      "1684821\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.23\n",
      "[100.0, 93.0, 89.0, 87.0, 88.0, 90.0, 97.0, 104.0]\n",
      "[-31250, -17857, -8929, 4465, 8928, 31250, 31250, 35714]\n",
      "53571\n",
      "6696.375\n",
      "1653571\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.19\n",
      "[108.0, 100.0, 93.0, 89.0, 87.0, 88.0, 90.0, 97.0]\n",
      "[-35714, -31250, -17857, -8929, 4465, 8928, 31250, 31250]\n",
      "-17857\n",
      "-2232.125\n",
      "1617857\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.77\n",
      "[116.0, 108.0, 100.0, 93.0, 89.0, 87.0, 88.0, 90.0]\n",
      "[1, -35714, -31250, -17857, -8929, 4465, 8928, 31250]\n",
      "-49106\n",
      "-6138.25\n",
      "1582142\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.71\n",
      "[121.0, 116.0, 108.0, 100.0, 93.0, 89.0, 87.0, 88.0]\n",
      "[22321, 1, -35714, -31250, -17857, -8929, 4465, 8928]\n",
      "-58035\n",
      "-7254.375\n",
      "1559821\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.97\n",
      "[122.0, 121.0, 116.0, 108.0, 100.0, 93.0, 89.0, 87.0]\n",
      "[4464, 22321, 1, -35714, -31250, -17857, -8929, 4465]\n",
      "-62499\n",
      "-7812.375\n",
      "1555357\n",
      "Elapsed 0.0054 seconds, estimated FPS 185.57\n",
      "[117.0, 122.0, 121.0, 116.0, 108.0, 100.0, 93.0, 89.0]\n",
      "[-22321, 4464, 22321, 1, -35714, -31250, -17857, -8929]\n",
      "-89285\n",
      "-11160.625\n",
      "1577678\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.58\n",
      "[105.0, 117.0, 122.0, 121.0, 116.0, 108.0, 100.0, 93.0]\n",
      "[8928, -22321, 4464, 22321, 1, -35714, -31250, -17857]\n",
      "-71428\n",
      "-8928.5\n",
      "1631250\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.20\n",
      "[100.0, 105.0, 117.0, 122.0, 121.0, 116.0, 108.0, 100.0]\n",
      "[22321, 8928, -22321, 4464, 22321, 1, -35714, -31250]\n",
      "-31250\n",
      "-3906.25\n",
      "1653571\n",
      "Elapsed 0.0091 seconds, estimated FPS 110.31\n",
      "[95.0, 100.0, 105.0, 117.0, 122.0, 121.0, 116.0, 108.0]\n",
      "[22321, 22321, 8928, -22321, 4464, 22321, 1, -35714]\n",
      "22321\n",
      "2790.125\n",
      "1675892\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.61\n",
      "[91.0, 95.0, 100.0, 105.0, 117.0, 122.0, 121.0, 116.0]\n",
      "[17858, 22321, 22321, 8928, -22321, 4464, 22321, 1]\n",
      "75893\n",
      "9486.625\n",
      "1693750\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.77\n",
      "[84.0, 91.0, 95.0, 100.0, 105.0, 117.0, 122.0, 121.0]\n",
      "[31250, 17858, 22321, 22321, 8928, -22321, 4464, 22321]\n",
      "107142\n",
      "13392.75\n",
      "1725000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.24\n",
      "[79.0, 84.0, 91.0, 95.0, 100.0, 105.0, 117.0, 122.0]\n",
      "[22321, 31250, 17858, 22321, 22321, 8928, -22321, 4464]\n",
      "107142\n",
      "13392.75\n",
      "1747321\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.46\n",
      "[78.0, 79.0, 84.0, 91.0, 95.0, 100.0, 105.0, 117.0]\n",
      "[4464, 22321, 31250, 17858, 22321, 22321, 8928, -22321]\n",
      "107142\n",
      "13392.75\n",
      "1751785\n",
      "Elapsed 0.0096 seconds, estimated FPS 103.65\n",
      "[82.0, 78.0, 79.0, 84.0, 91.0, 95.0, 100.0, 105.0]\n",
      "[-17857, 4464, 22321, 31250, 17858, 22321, 22321, 8928]\n",
      "111606\n",
      "13950.75\n",
      "1733928\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.14\n",
      "[91.0, 82.0, 78.0, 79.0, 84.0, 91.0, 95.0, 100.0]\n",
      "[-40178, -17857, 4464, 22321, 31250, 17858, 22321, 22321]\n",
      "62500\n",
      "7812.5\n",
      "1693750\n",
      "Elapsed 0.0051 seconds, estimated FPS 196.07\n",
      "[106.0, 91.0, 82.0, 78.0, 79.0, 84.0, 91.0, 95.0]\n",
      "[-66965, -40178, -17857, 4464, 22321, 31250, 17858, 22321]\n",
      "-26786\n",
      "-3348.25\n",
      "1626785\n",
      "Elapsed 0.0051 seconds, estimated FPS 197.05\n",
      "[117.0, 106.0, 91.0, 82.0, 78.0, 79.0, 84.0, 91.0]\n",
      "[-4463, -66965, -40178, -17857, 4464, 22321, 31250, 17858]\n",
      "-53570\n",
      "-6696.25\n",
      "1577678\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.92\n",
      "[126.0, 117.0, 106.0, 91.0, 82.0, 78.0, 79.0, 84.0]\n",
      "[40178, -4463, -66965, -40178, -17857, 4464, 22321, 31250]\n",
      "-31250\n",
      "-3906.25\n",
      "1537500\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.28\n",
      "[130.0, 126.0, 117.0, 106.0, 91.0, 82.0, 78.0, 79.0]\n",
      "[17858, 40178, -4463, -66965, -40178, -17857, 4464, 22321]\n",
      "-44642\n",
      "-5580.25\n",
      "1519642\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.18\n",
      "[126.0, 130.0, 126.0, 117.0, 106.0, 91.0, 82.0, 78.0]\n",
      "[-17858, 17858, 40178, -4463, -66965, -40178, -17857, 4464]\n",
      "-84821\n",
      "-10602.625\n",
      "1537500\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.03\n",
      "[123.0, 126.0, 130.0, 126.0, 117.0, 106.0, 91.0, 82.0]\n",
      "[-13392, -17858, 17858, 40178, -4463, -66965, -40178, -17857]\n",
      "-102677\n",
      "-12834.625\n",
      "1550892\n",
      "Elapsed 0.0052 seconds, estimated FPS 192.79\n",
      "[110.0, 123.0, 126.0, 130.0, 126.0, 117.0, 106.0, 91.0]\n",
      "[-40180, -13392, -17858, 17858, 40178, -4463, -66965, -40178]\n",
      "-125000\n",
      "-15625.0\n",
      "1608928\n",
      "Elapsed 0.0051 seconds, estimated FPS 196.73\n",
      "[94.0, 110.0, 123.0, 126.0, 130.0, 126.0, 117.0, 106.0]\n",
      "[71429, -40180, -13392, -17858, 17858, 40178, -4463, -66965]\n",
      "-13393\n",
      "-1674.125\n",
      "1680357\n",
      "Elapsed 0.0055 seconds, estimated FPS 180.52\n",
      "[83.0, 94.0, 110.0, 123.0, 126.0, 130.0, 126.0, 117.0]\n",
      "[49107, 71429, -40180, -13392, -17858, 17858, 40178, -4463]\n",
      "102679\n",
      "12834.875\n",
      "1729464\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.01\n",
      "[67.0, 83.0, 94.0, 110.0, 123.0, 126.0, 130.0, 126.0]\n",
      "[71428, 49107, 71429, -40180, -13392, -17858, 17858, 40178]\n",
      "178570\n",
      "22321.25\n",
      "1800892\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.28\n",
      "[55.0, 67.0, 83.0, 94.0, 110.0, 123.0, 126.0, 130.0]\n",
      "[53572, 71428, 49107, 71429, -40180, -13392, -17858, 17858]\n",
      "191964\n",
      "23995.5\n",
      "1854464\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.01\n",
      "[48.0, 55.0, 67.0, 83.0, 94.0, 110.0, 123.0, 126.0]\n",
      "[31250, 53572, 71428, 49107, 71429, -40180, -13392, -17858]\n",
      "205356\n",
      "25669.5\n",
      "1885714\n",
      "Elapsed 0.0062 seconds, estimated FPS 161.77\n",
      "[43.0, 48.0, 55.0, 67.0, 83.0, 94.0, 110.0, 123.0]\n",
      "[22321, 31250, 53572, 71428, 49107, 71429, -40180, -13392]\n",
      "245535\n",
      "30691.875\n",
      "1908035\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.80\n",
      "[38.0, 43.0, 48.0, 55.0, 67.0, 83.0, 94.0, 110.0]\n",
      "[22322, 22321, 31250, 53572, 71428, 49107, 71429, -40180]\n",
      "281249\n",
      "35156.125\n",
      "1930357\n",
      "Elapsed 0.0063 seconds, estimated FPS 158.28\n",
      "[39.0, 38.0, 43.0, 48.0, 55.0, 67.0, 83.0, 94.0]\n",
      "[-4465, 22322, 22321, 31250, 53572, 71428, 49107, 71429]\n",
      "316964\n",
      "39620.5\n",
      "1925892\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.30\n",
      "[50.0, 39.0, 38.0, 43.0, 48.0, 55.0, 67.0, 83.0]\n",
      "[-49107, -4465, 22322, 22321, 31250, 53572, 71428, 49107]\n",
      "196428\n",
      "24553.5\n",
      "1876785\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.88\n",
      "[56.0, 50.0, 39.0, 38.0, 43.0, 48.0, 55.0, 67.0]\n",
      "[-26785, -49107, -4465, 22322, 22321, 31250, 53572, 71428]\n",
      "120536\n",
      "15067.0\n",
      "1850000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.10\n",
      "[59.0, 56.0, 50.0, 39.0, 38.0, 43.0, 48.0, 55.0]\n",
      "[-13393, -26785, -49107, -4465, 22322, 22321, 31250, 53572]\n",
      "35715\n",
      "4464.375\n",
      "1836607\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.54\n",
      "[69.0, 59.0, 56.0, 50.0, 39.0, 38.0, 43.0, 48.0]\n",
      "[-44643, -13393, -26785, -49107, -4465, 22322, 22321, 31250]\n",
      "-62500\n",
      "-7812.5\n",
      "1791964\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.17\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[74.0, 69.0, 59.0, 56.0, 50.0, 39.0, 38.0, 43.0]\n",
      "[-22322, -44643, -13393, -26785, -49107, -4465, 22322, 22321]\n",
      "-116072\n",
      "-14509.0\n",
      "1769642\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.18\n",
      "[79.0, 74.0, 69.0, 59.0, 56.0, 50.0, 39.0, 38.0]\n",
      "[-22321, -22322, -44643, -13393, -26785, -49107, -4465, 22322]\n",
      "-160714\n",
      "-20089.25\n",
      "1747321\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.31\n",
      "[74.0, 79.0, 74.0, 69.0, 59.0, 56.0, 50.0, 39.0]\n",
      "[22321, -22321, -22322, -44643, -13393, -26785, -49107, -4465]\n",
      "-160715\n",
      "-20089.375\n",
      "1769642\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.29\n",
      "[71.0, 74.0, 79.0, 74.0, 69.0, 59.0, 56.0, 50.0]\n",
      "[13393, 22321, -22321, -22322, -44643, -13393, -26785, -49107]\n",
      "-142857\n",
      "-17857.125\n",
      "1783035\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.71\n",
      "[69.0, 71.0, 74.0, 79.0, 74.0, 69.0, 59.0, 56.0]\n",
      "[8929, 13393, 22321, -22321, -22322, -44643, -13393, -26785]\n",
      "-84821\n",
      "-10602.625\n",
      "1791964\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.44\n",
      "[60.0, 69.0, 71.0, 74.0, 79.0, 74.0, 69.0, 59.0]\n",
      "[40178, 8929, 13393, 22321, -22321, -22322, -44643, -13393]\n",
      "-17858\n",
      "-2232.25\n",
      "1832142\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.08\n",
      "[52.0, 60.0, 69.0, 71.0, 74.0, 79.0, 74.0, 69.0]\n",
      "[35715, 40178, 8929, 13393, 22321, -22321, -22322, -44643]\n",
      "31250\n",
      "3906.25\n",
      "1867857\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.85\n",
      "[43.0, 52.0, 60.0, 69.0, 71.0, 74.0, 79.0, 74.0]\n",
      "[40178, 35715, 40178, 8929, 13393, 22321, -22321, -22322]\n",
      "116071\n",
      "14508.875\n",
      "1908035\n",
      "Elapsed 0.0064 seconds, estimated FPS 155.40\n",
      "[40.0, 43.0, 52.0, 60.0, 69.0, 71.0, 74.0, 79.0]\n",
      "[13393, 40178, 35715, 40178, 8929, 13393, 22321, -22321]\n",
      "151786\n",
      "18973.25\n",
      "1921428\n",
      "Elapsed 0.0064 seconds, estimated FPS 155.75\n",
      "[32.0, 40.0, 43.0, 52.0, 60.0, 69.0, 71.0, 74.0]\n",
      "[35714, 13393, 40178, 35715, 40178, 8929, 13393, 22321]\n",
      "209821\n",
      "26227.625\n",
      "1957142\n",
      "Elapsed 0.0064 seconds, estimated FPS 156.88\n",
      "[37.0, 32.0, 40.0, 43.0, 52.0, 60.0, 69.0, 71.0]\n",
      "[-22321, 35714, 13393, 40178, 35715, 40178, 8929, 13393]\n",
      "165179\n",
      "20647.375\n",
      "1934821\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.44\n",
      "[31.0, 37.0, 32.0, 40.0, 43.0, 52.0, 60.0, 69.0]\n",
      "[26786, -22321, 35714, 13393, 40178, 35715, 40178, 8929]\n",
      "178572\n",
      "22321.5\n",
      "1961607\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.63\n",
      "[42.0, 31.0, 37.0, 32.0, 40.0, 43.0, 52.0, 60.0]\n",
      "[-49107, 26786, -22321, 35714, 13393, 40178, 35715, 40178]\n",
      "120536\n",
      "15067.0\n",
      "1912500\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.11\n",
      "[49.0, 42.0, 31.0, 37.0, 32.0, 40.0, 43.0, 52.0]\n",
      "[-31250, -49107, 26786, -22321, 35714, 13393, 40178, 35715]\n",
      "49108\n",
      "6138.5\n",
      "1881250\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.26\n",
      "[51.0, 49.0, 42.0, 31.0, 37.0, 32.0, 40.0, 43.0]\n",
      "[-8929, -31250, -49107, 26786, -22321, 35714, 13393, 40178]\n",
      "4464\n",
      "558.0\n",
      "1872321\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.83\n",
      "[59.0, 51.0, 49.0, 42.0, 31.0, 37.0, 32.0, 40.0]\n",
      "[-35714, -8929, -31250, -49107, 26786, -22321, 35714, 13393]\n",
      "-71428\n",
      "-8928.5\n",
      "1836607\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.68\n",
      "[64.0, 59.0, 51.0, 49.0, 42.0, 31.0, 37.0, 32.0]\n",
      "[-22322, -35714, -8929, -31250, -49107, 26786, -22321, 35714]\n",
      "-107143\n",
      "-13392.875\n",
      "1814285\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.47\n",
      "[65.0, 64.0, 59.0, 51.0, 49.0, 42.0, 31.0, 37.0]\n",
      "[-4464, -22322, -35714, -8929, -31250, -49107, 26786, -22321]\n",
      "-147321\n",
      "-18415.125\n",
      "1809821\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.88\n",
      "[64.0, 65.0, 64.0, 59.0, 51.0, 49.0, 42.0, 31.0]\n",
      "[4464, -4464, -22322, -35714, -8929, -31250, -49107, 26786]\n",
      "-120536\n",
      "-15067.0\n",
      "1814285\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.33\n",
      "[61.0, 64.0, 65.0, 64.0, 59.0, 51.0, 49.0, 42.0]\n",
      "[13393, 4464, -4464, -22322, -35714, -8929, -31250, -49107]\n",
      "-133929\n",
      "-16741.125\n",
      "1827678\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.90\n",
      "[58.0, 61.0, 64.0, 65.0, 64.0, 59.0, 51.0, 49.0]\n",
      "[13393, 13393, 4464, -4464, -22322, -35714, -8929, -31250]\n",
      "-71429\n",
      "-8928.625\n",
      "1841071\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.52\n",
      "[52.0, 58.0, 61.0, 64.0, 65.0, 64.0, 59.0, 51.0]\n",
      "[26786, 13393, 13393, 4464, -4464, -22322, -35714, -8929]\n",
      "-13393\n",
      "-1674.125\n",
      "1867857\n",
      "Elapsed 0.0104 seconds, estimated FPS 96.59\n",
      "[49.0, 52.0, 58.0, 61.0, 64.0, 65.0, 64.0, 59.0]\n",
      "[13393, 26786, 13393, 13393, 4464, -4464, -22322, -35714]\n",
      "8929\n",
      "1116.125\n",
      "1881250\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.42\n",
      "[43.0, 49.0, 52.0, 58.0, 61.0, 64.0, 65.0, 64.0]\n",
      "[26785, 13393, 26786, 13393, 13393, 4464, -4464, -22322]\n",
      "71428\n",
      "8928.5\n",
      "1908035\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.99\n",
      "[38.0, 43.0, 49.0, 52.0, 58.0, 61.0, 64.0, 65.0]\n",
      "[22322, 26785, 13393, 26786, 13393, 13393, 4464, -4464]\n",
      "116072\n",
      "14509.0\n",
      "1930357\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.34\n",
      "[-520, 38.0, 43.0, 49.0, 52.0, 58.0, 61.0, 64.0]\n",
      "[169643, 22322, 26785, 13393, 26786, 13393, 13393, 4464]\n",
      "290179\n",
      "36272.375\n",
      "2100000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.03\n",
      "[23.0, -520, 38.0, 43.0, 49.0, 52.0, 58.0, 61.0]\n",
      "[-102679, 169643, 22322, 26785, 13393, 26786, 13393, 13393]\n",
      "183036\n",
      "22879.5\n",
      "1997321\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.95\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''plt.imshow(I)'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-2bb2f3d52ec1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mL\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"raw\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"filtered\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m300\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "'''plt.plot(L, label=\"raw\")\n",
    "plt.plot(Lf, label=\"filtered\")\n",
    "plt.ylim([0, 300])\n",
    "plt.legend()'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'camera' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-2935dfd9e3ee>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcamera\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'camera' is not defined"
     ]
    }
   ],
   "source": [
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pwm import PWM\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "\n",
    "pwm0.duty_cycle = 1000000\n",
    "\n",
    "pwm0.period = 20000000\n",
    "\n",
    "pwm0.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./CameraInterface.ipynb0000644000175000017500000052151713446024104014342 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from picamera.array import PiYUVArray, PiRGBArray\n",
    "from picamera import PiCamera\n",
    "\n",
    "from scipy.signal import find_peaks, butter, filtfilt\n",
    "\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import skimage as ski\n",
    "import tools\n",
    "\n",
    "# Camera resolution\n",
    "res = (128, 96)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Interface the camera capturing RGB images\n",
    "\n",
    "camera = PiCamera()\n",
    "        \n",
    "# Check the link below for the combinations between mode and resolution\n",
    "# https://picamera.readthedocs.io/en/release-1.13/fov.html#sensor-modes\n",
    "camera.sensor_mode = 7\n",
    "camera.resolution = res\n",
    "camera.framerate = 120\n",
    "\n",
    "# Initialize the buffer and start capturing\n",
    "rawCapture = PiRGBArray(camera, size=res)\n",
    "stream = camera.capture_continuous(rawCapture, format=\"rgb\", use_video_port=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pi/.virtualenvs/raceon/lib/python3.5/site-packages/picamera/encoders.py:544: PiCameraResolutionRounded: frame size rounded up from 120x90 to 128x96\n",
      "  width, height, fwidth, fheight)))\n"
     ]
    }
   ],
   "source": [
    "# Get next frame from the stream\n",
    "\n",
    "rawCapture.truncate(0)\n",
    "frame = next(stream)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%timeit\n",
    "\n",
    "# Bigger the image, more it takes for the conversion\n",
    "#I = ski.color.rgb2gray(frame.array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%timeit\n",
    "\n",
    "# Arlgorithms operate faster on smaller images\n",
    "#I = ski.color.rgb2gray(frame.array[0:320, 0:240, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x6c4e3850>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the captured image\n",
    "plt.imshow(frame.array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Release resources\n",
    "stream.close()\n",
    "rawCapture.close()\n",
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "\n",
    "# Wn = 0.02, the cut-off frequency, acceptable values are from 0 to 1\n",
    "b, a = butter(3, 0.02)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed 11.89 seconds, estimated FPS 25.23\n"
     ]
    }
   ],
   "source": [
    "# Run a track detection algorithm on a single horizontal line.\n",
    "# Uses YUV420 image format as the Y component corresponds to image intensity (gray image)\n",
    "# and thus there is no need to convert from RGB to BW\n",
    "\n",
    "camera = PiCamera()\n",
    "        \n",
    "# Check the link below for the combinations between mode and resolution\n",
    "# https://picamera.readthedocs.io/en/release-1.13/fov.html#sensor-modes\n",
    "camera.sensor_mode = 7\n",
    "camera.resolution = res\n",
    "camera.framerate = 120\n",
    "\n",
    "# Initialize the buffer and start capturing\n",
    "rawCapture = PiYUVArray(camera, size=res)\n",
    "stream = camera.capture_continuous(rawCapture, format=\"yuv\", use_video_port=True)\n",
    "\n",
    "# Measure the time needed to process 300 images to estimate the FPS\n",
    "N = 300\n",
    "k = 0\n",
    "t = time.time()\n",
    "\n",
    "for f in stream:\n",
    "    # Get the intensity component of the image (a trick to get black and white images)\n",
    "    I = f.array[:, :, 0]\n",
    "    \n",
    "    # Reset the buffer for the next image\n",
    "    rawCapture.truncate(0)\n",
    "    \n",
    "    # Select a horizontal line in the middle of the image\n",
    "    L = I[180, :]\n",
    "\n",
    "    # Smooth the transitions so we can detect the peaks \n",
    "    Lf = filtfilt(b, a, L)\n",
    "\n",
    "    # Find peaks which are higher than 0.5\n",
    "    p = find_peaks(Lf, height=128)\n",
    "    \n",
    "    # Increment the number of processed frames\n",
    "    k += 1\n",
    "    if k > N:\n",
    "        break\n",
    "        \n",
    "time_elapsed = time.time() - t\n",
    "print(\"Elapsed {:0.2f} seconds, estimated FPS {:0.2f}\".format(time_elapsed, N / time_elapsed))\n",
    "\n",
    "# Release resources\n",
    "stream.close()\n",
    "rawCapture.close()\n",
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this section if you get the Error: Out of resources\n",
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x67883e50>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the last image\n",
    "plt.imshow(I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x678a2fd0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the pixel intensities along the selected line\n",
    "plt.plot(L, label=\"raw\")\n",
    "plt.plot(Lf, label=\"filtered\")\n",
    "plt.ylim([0, 300])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([347, 452], dtype=int32),\n",
       " {'peak_heights': array([217.37741025, 206.4504596 ])})"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./TestSliders.ipynb0000644000175000017500000000642513451555634013607 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6e08207313004d9f9bdfb6506d1593a6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=10, description='x', max=30, min=-10), Output()), _dom_classes=('widget-…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.f(x)>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ipywidgets import interact\n",
    "\n",
    "\n",
    "# Function that will be called for each slider movement\n",
    "\n",
    "def f(x):\n",
    "\n",
    "    print(x)\n",
    "\n",
    "    \n",
    "\n",
    "# Create a slider and set its default position to 10\n",
    "\n",
    "interact(f, x=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets as ipw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "sl = ipw.ToggleButton(value=False, description='Shut it down')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e7f6ff67ce3f466286220ee955c43ec8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "ToggleButton(value=False, description='Shut it down')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(sl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import threading\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_float():\n",
    "    while True:\n",
    "        print(sl.value)\n",
    "        time.sleep(1)\n",
    "        if sl.value < 2:\n",
    "            break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8.1\n",
      "8.1\n",
      "8.1\n",
      "8.1\n"
     ]
    }
   ],
   "source": [
    "t = threading.Thread(target=print_float)\n",
    "t.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sl.observe(print, names=\"value\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./pwm.py0000644000175000017500000000772513432076367011460 0ustar  pipi00000000000000"""Linux PWM driver sysfs interface"""

import os

__author__ = 'Scott Ellis'
__version__ = '1.0'
__license__ = 'New BSD'
__copyright__ = 'Copyright (c) 2016 Scott Ellis'

class PWM(object):
    """
    A class to work with the Linux PWM driver sysfs interface
    """

    def __init__(self, channel=0, chip=0):
        """ Specify channel and chip when creating an instance

        The Linux kernel driver exports a sysfs interface like this

            /sys/class/pwm/pwmchip<chip>/pwm<channel>

        A <chip> can have multiple <channels>.

        The channel and chip are determined by the kernel driver.

        For example the two PWM timers from the RPi kernel driver
        show up like this

            /sys/class/pwm/pwmchip0/pwm0
            /sys/class/pwm/pwmchip0/pwm1

        To use the RPi timers create instances this way

            pwm0 = PWM(0) or PWM(0,0)
            pwm1 = PWM(1) or PWM(1,0)

        """
        self._channel = channel
        self._chip = chip
        self.base = '/sys/class/pwm/pwmchip{:d}'.format(self._chip)
        self.path = self.base + '/pwm{:d}'.format(self._channel)

        if not os.path.isdir(self.base):
            raise FileNotFoundError('Directory not found: ' + self.base)

    # enable class as a context manager
    def __enter__(self):
        self.export()
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        self.enable = False
        self.inversed = False
        self.unexport()
        return

    def export(self):
        """Export the channel for use through the sysfs interface.
        Required before first use.
        """
        if not os.path.isdir(self.path):
            with open(self.base + '/export', 'w') as f:
                f.write('{:d}'.format(self._channel))

    def unexport(self):
        """Unexport the channel.
        The sysfs interface is no longer usable until it is exported again.
        """
        if os.path.isdir(self.path):
            with open(self.base + '/unexport', 'w') as f:
                f.write('{:d}'.format(self._channel))

    @property
    def channel(self):
        """The channel used by this instance.
        Read-only, set in the constructor.
        """
        return self._channel

    @property
    def chip(self):
        """The chip used by this instance.
        Read-only, set in the constructor.
        """
        return self._chip

    @property
    def period(self):
        """The period of the pwm timer in nanoseconds."""
        with open(self.path + '/period', 'r') as f:
            value = f.readline().strip()

        return int(value)

    @period.setter
    def period(self, value):
        with open(self.path + '/period', 'w') as f:
            f.write('{:d}'.format(value))

    @property
    def duty_cycle(self):
        """The duty_cycle (the ON pulse) of the timer in nanoseconds."""
        with open(self.path + '/duty_cycle', 'r') as f:
            value = f.readline().strip()

        return int(value)

    @duty_cycle.setter
    def duty_cycle(self, value):
        with open(self.path + '/duty_cycle', 'w') as f:
            f.write('{:d}'.format(value))

    @property
    def enable(self):
        """Enable or disable the timer, boolean"""
        with open(self.path + '/enable', 'r') as f:
            value = f.readline().strip()

        return True if value == '1' else False

    @enable.setter
    def enable(self, value):
        with open(self.path + '/enable', 'w') as f:
            if value:
                f.write('1')
            else:
                f.write('0')

    @property
    def inversed(self):
        """normal polarity or inversed, boolean"""
        with open(self.path + '/polarity', 'r') as f:
            value = f.readline().strip()

        return True if value == 'inversed' else False

    @inversed.setter
    def inversed(self, value):
        with open(self.path + '/polarity', 'w') as f:
            if value:
                f.write('inversed')
            else:
                f.write('normal')

./Stream.ipynb0000644000175000017500000001210113444623424012554 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import io\n",
    "import picamera\n",
    "import logging\n",
    "import socketserver\n",
    "from threading import Condition\n",
    "from http import server\n",
    "\n",
    "PAGE=\"\"\"\\\n",
    "<html>\n",
    "<head>\n",
    "<title>picamera MJPEG streaming demo</title>\n",
    "</head>\n",
    "<body>\n",
    "<h1>PiCamera MJPEG Streaming Demo</h1>\n",
    "<img src=\"stream.mjpg\" width=\"640\" height=\"480\" />\n",
    "</body>\n",
    "</html>\n",
    "\"\"\"\n",
    "\n",
    "class StreamingOutput(object):\n",
    "    def __init__(self):\n",
    "        self.frame = None\n",
    "        self.buffer = io.BytesIO()\n",
    "        self.condition = Condition()\n",
    "\n",
    "    def write(self, buf):\n",
    "        if buf.startswith(b'\\xff\\xd8'):\n",
    "            # New frame, copy the existing buffer's content and notify all\n",
    "            # clients it's available\n",
    "            self.buffer.truncate()\n",
    "            with self.condition:\n",
    "                self.frame = self.buffer.getvalue()\n",
    "                self.condition.notify_all()\n",
    "            self.buffer.seek(0)\n",
    "        return self.buffer.write(buf)\n",
    "\n",
    "class StreamingHandler(server.BaseHTTPRequestHandler):\n",
    "    def do_GET(self):\n",
    "        if self.path == '/':\n",
    "            self.send_response(301)\n",
    "            self.send_header('Location', '/index.html')\n",
    "            self.end_headers()\n",
    "        elif self.path == '/index.html':\n",
    "            content = PAGE.encode('utf-8')\n",
    "            self.send_response(200)\n",
    "            self.send_header('Content-Type', 'text/html')\n",
    "            self.send_header('Content-Length', len(content))\n",
    "            self.end_headers()\n",
    "            self.wfile.write(content)\n",
    "        elif self.path == '/stream.mjpg':\n",
    "            self.send_response(200)\n",
    "            self.send_header('Age', 0)\n",
    "            self.send_header('Cache-Control', 'no-cache, private')\n",
    "            self.send_header('Pragma', 'no-cache')\n",
    "            self.send_header('Content-Type', 'multipart/x-mixed-replace; boundary=FRAME')\n",
    "            self.end_headers()\n",
    "            try:\n",
    "                while True:\n",
    "                    with output.condition:\n",
    "                        output.condition.wait()\n",
    "                        frame = output.frame\n",
    "                    self.wfile.write(b'--FRAME\\r\\n')\n",
    "                    self.send_header('Content-Type', 'image/jpeg')\n",
    "                    self.send_header('Content-Length', len(frame))\n",
    "                    self.end_headers()\n",
    "                    self.wfile.write(frame)\n",
    "                    self.wfile.write(b'\\r\\n')\n",
    "            except Exception as e:\n",
    "                logging.warning(\n",
    "                    'Removed streaming client %s: %s',\n",
    "                    self.client_address, str(e))\n",
    "        else:\n",
    "            self.send_error(404)\n",
    "            self.end_headers()\n",
    "\n",
    "class StreamingServer(socketserver.ThreadingMixIn, server.HTTPServer):\n",
    "    allow_reuse_address = True\n",
    "    daemon_threads = True\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "192.168.43.233 - - [21/Mar/2019 05:48:41] \"GET / HTTP/1.1\" 301 -\n",
      "192.168.43.233 - - [21/Mar/2019 05:48:41] \"GET /index.html HTTP/1.1\" 200 -\n",
      "192.168.43.233 - - [21/Mar/2019 05:48:41] \"GET /stream.mjpg HTTP/1.1\" 200 -\n",
      "192.168.43.233 - - [21/Mar/2019 05:48:41] code 404, message Not Found\n",
      "192.168.43.233 - - [21/Mar/2019 05:48:41] \"GET /favicon.ico HTTP/1.1\" 404 -\n",
      "WARNING:root:Removed streaming client ('192.168.43.233', 59349): [Errno 32] Broken pipe\n"
     ]
    }
   ],
   "source": [
    "with picamera.PiCamera(resolution='640x480', framerate=24) as camera:\n",
    "    output = StreamingOutput()\n",
    "    camera.start_recording(output, format='mjpeg')\n",
    "    try:\n",
    "        address = ('', 8000)\n",
    "        server = StreamingServer(address, StreamingHandler)\n",
    "        server.serve_forever()\n",
    "    finally:\n",
    "        camera.stop_recording()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./Alignment.ipynb0000644000175000017500000001276313445347601013256 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CENTER is 1600000\n",
    "#RIGHT is  1100000\n",
    "#LEFT is   2100000\n",
    "#for pwm1\n",
    "#duty_cycle\n",
    "\n",
    "from pwm import PWM\n",
    "\n",
    "import time\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "pwm1 = PWM(1)\n",
    "\n",
    "pwm0.export()\n",
    "pwm1.export()\n",
    "\n",
    "pwm0.period = 20000000\n",
    "pwm1.period = 20000000\n",
    "\n",
    "pwm0.duty_cycle = 1000000\n",
    "pwm1.duty_cycle = 1600000\n",
    "\n",
    "pwm0.enable = True\n",
    "pwm1.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1789062\n",
      "2068750\n"
     ]
    }
   ],
   "source": [
    "pwm1.duty_cycle = 1789062\n",
    "print(pwm1.duty_cycle)\n",
    "time.sleep(3)\n",
    "pwm1.duty_cycle = 2068750\n",
    "print(pwm1.duty_cycle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1150000\n",
    "time.sleep(1)\n",
    "pwm0.duty_cycle = 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pwm import PWM\n",
    "\n",
    "import time\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "pwm1 = PWM(1)\n",
    "\n",
    "pwm0.export()\n",
    "pwm1.export()\n",
    "\n",
    "pwm0.period = 20000000\n",
    "pwm1.period = 20000000\n",
    "\n",
    "pwm0.duty_cycle = 1000000\n",
    "pwm1.duty_cycle = 1600000\n",
    "\n",
    "pwm0.enable = True\n",
    "pwm1.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "OSError",
     "evalue": "[Errno 22] Invalid argument",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;31mOSError\u001b[0m: [Errno 22] Invalid argument",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-16511d4263d2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpwm0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mduty_cycle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1100000\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/pwm.py\u001b[0m in \u001b[0;36mduty_cycle\u001b[0;34m(self, value)\u001b[0m\n\u001b[1;32m    109\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mduty_cycle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    110\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'/duty_cycle'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'w'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 111\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'{:d}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    112\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    113\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mOSError\u001b[0m: [Errno 22] Invalid argument"
     ]
    }
   ],
   "source": [
    "pwm0.duty_cycle = 1100000\n",
    "\n",
    "i = 0\n",
    "\n",
    "time.sleep(5)\n",
    "\n",
    "pwm1.duty_cycle = 1135000\n",
    "\n",
    "while i < 700000:\n",
    "    time.sleep(.1)\n",
    "    pwm1.duty_cycle += 10000\n",
    "    i += 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm1.duty_cycle = 1600000\n",
    "pwm0.duty_cycle = 1120000\n",
    "time.sleep(2)\n",
    "pwm0.duty_cycle = 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./tools.py0000644000175000017500000000021013445470324011766 0ustar  pipi00000000000000from scipy.signal import find_peaks, butter, filtfilt


def printFrame(frame, subdivisions):
    b, a = butter(3, 0.02)
    return frame./BasicSingle.ipynb0000644000175000017500000046312713445473516013534 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from picamera.array import PiYUVArray\n",
    "from picamera import PiCamera\n",
    "\n",
    "from scipy.signal import find_peaks, butter, filtfilt\n",
    "from pwm import PWM\n",
    "\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import skimage as ski\n",
    "\n",
    "# Camera resolution\n",
    "res = (640, 480)\n",
    "\n",
    "# Run a track detection algorithm on a single horizontal line.\n",
    "# Uses YUV420 image format as the Y component corresponds to image intensity (gray image)\n",
    "# and thus there is no need to convert from RGB to BW\n",
    "\n",
    "camera = PiCamera()\n",
    "        \n",
    "# Check the link below for the combinations between mode and resolution\n",
    "# https://picamera.readthedocs.io/en/release-1.13/fov.html#sensor-modes\n",
    "camera.sensor_mode = 7\n",
    "camera.resolution = res\n",
    "camera.framerate = 120\n",
    "\n",
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "\n",
    "# Wn = 0.02, the cut-off frequency, acceptable values are from 0 to 1\n",
    "b, a = butter(3, 0.02)\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "pwm1 = PWM(1)\n",
    "\n",
    "pwm0.export()\n",
    "pwm1.export()\n",
    "\n",
    "pwm0.period = 20000000\n",
    "pwm1.period = 20000000\n",
    "\n",
    "pwm0.enable = True\n",
    "pwm1.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000\n",
    "pwm1.duty_cycle = 1100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 2100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 1600000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "440.5\n",
      "1411718\n",
      "False\n",
      "1\n",
      "416.5\n",
      "1449218\n",
      "False\n",
      "1\n",
      "319.5\n",
      "1600781\n",
      "False\n",
      "-1\n",
      "235.0\n",
      "1732812\n",
      "False\n",
      "-1\n",
      "259.5\n",
      "1694531\n",
      "False\n",
      "-1\n",
      "355.5\n",
      "1544531\n",
      "False\n",
      "1\n",
      "381.5\n",
      "1503906\n",
      "False\n",
      "1\n",
      "291.0\n",
      "1645312\n",
      "False\n",
      "-1\n",
      "202.5\n",
      "1783593\n",
      "False\n",
      "-1\n",
      "283.0\n",
      "1657812\n",
      "False\n",
      "-1\n",
      "432.0\n",
      "1425000\n",
      "False\n",
      "1\n",
      "386.5\n",
      "1496093\n",
      "False\n",
      "1\n",
      "153.5\n",
      "1860156\n",
      "False\n",
      "-1\n",
      "106.5\n",
      "1933593\n",
      "False\n",
      "-1\n",
      "440.5\n",
      "1411718\n",
      "False\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "514.0\n",
      "1296875\n",
      "False\n",
      "1\n",
      "93.0\n",
      "1954687\n",
      "False\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "483.0\n",
      "1345312\n",
      "False\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "7.0\n",
      "2089062\n",
      "False\n",
      "-1\n",
      "10.0\n",
      "2084375\n",
      "False\n",
      "-1\n",
      "333.25\n",
      "1579296\n",
      "False\n",
      "1\n",
      "377.5\n",
      "1510156\n",
      "False\n",
      "1\n",
      "321.4\n",
      "1597812\n",
      "False\n",
      "1\n",
      "383.5\n",
      "1500781\n",
      "False\n",
      "1\n",
      "507.5\n",
      "1307031\n",
      "False\n",
      "1\n",
      "-1\n",
      "1100000\n",
      "True\n",
      "1\n",
      "57.0\n",
      "2010937\n",
      "False\n",
      "-1\n",
      "59.0\n",
      "2007812\n",
      "False\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n",
      "-1\n",
      "2100000\n",
      "True\n",
      "-1\n"
     ]
    }
   ],
   "source": [
    "rawCapture = PiYUVArray(camera, size=res)\n",
    "stream = camera.capture_continuous(rawCapture, format=\"yuv\", use_video_port=True)\n",
    "\n",
    "#CENTER is 1600000\n",
    "#RIGHT is  1100000\n",
    "#LEFT is   2100000\n",
    "#for pwm1\n",
    "#duty_cycle\n",
    "\n",
    "#      (array([482, 542], dtype=int32), {'peak_heights': array([186.831036  , 185.01286929])})\n",
    "\n",
    "numFrames = 0\n",
    "\n",
    "#if linePos is 1 then the line is to the right of the car\n",
    "#if linePos is -1 then the line is to the left of the car\n",
    "#if linePos is 0 either uhoh we're doomed\n",
    "#if lost is true then the line is lost\n",
    "\n",
    "linePos = 0\n",
    "lost = False\n",
    "\n",
    "pwm0.duty_cycle = 1120000\n",
    "\n",
    "for f in stream:\n",
    "    if pwm0.duty_cycle == 1000000:\n",
    "        break\n",
    "    \n",
    "    numFrames += 1\n",
    "    # Get the intensity component of the image (a trick to get black and white images)\n",
    "    I = f.array[:, :, 0]\n",
    "    \n",
    "    # Reset the buffer for the next image\n",
    "    rawCapture.truncate(0)\n",
    "    \n",
    "    # Select a horizontal line in the middle of the image\n",
    "    L = I[240, :]\n",
    "\n",
    "    # Smooth the transitions so we can detect the peaks \n",
    "    Lf = filtfilt(b, a, L)\n",
    "\n",
    "    # Find peaks which are higher than 0.5\n",
    "    p = find_peaks(Lf, height=128)\n",
    "    \n",
    "    totalPeakAmt = 0\n",
    "    avgPeakLoc = -1\n",
    "    numPeaks = 0\n",
    "    \n",
    "    for peak in p[0]:\n",
    "        numPeaks += 1\n",
    "        totalPeakAmt += peak\n",
    "        \n",
    "    if numPeaks != 0:\n",
    "        avgPeakLoc = totalPeakAmt / numPeaks\n",
    "    \n",
    "    if avgPeakLoc != -1 :\n",
    "        lost = False\n",
    "        \n",
    "        if avgPeakLoc < 320:\n",
    "            linePos = -1\n",
    "        else:\n",
    "            linePos = 1\n",
    "            \n",
    "        pwm1.duty_cycle = int(1600000 - ((avgPeakLoc - 320)/320)*500000)\n",
    "    else:\n",
    "        lost = True\n",
    "        \n",
    "        if linePos == -1:\n",
    "            pwm1.duty_cycle = 2100000\n",
    "        elif linePos == 1:\n",
    "            pwm1.duty_cycle = 1100000\n",
    "        else:\n",
    "            pwm1.duty_cycle = 1600000\n",
    "    \n",
    "    print(avgPeakLoc)\n",
    "    print(pwm1.duty_cycle)\n",
    "    print(lost)\n",
    "    print(linePos)\n",
    "    \n",
    "        \n",
    "    #plt.imshow(I)\n",
    "    \n",
    "    time.sleep(0.2)\n",
    "    \n",
    "# Release resources\n",
    "stream.close()\n",
    "rawCapture.close()\n",
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x692ca4b0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x692a8a10>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(L, label=\"raw\")\n",
    "plt.plot(Lf, label=\"filtered\")\n",
    "plt.ylim([0, 300])\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pwm import PWM\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "\n",
    "pwm0.export()\n",
    "\n",
    "pwm0.duty_cycle = 1000000\n",
    "\n",
    "pwm0.period = 20000000\n",
    "\n",
    "pwm0.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./UpgradedSingle.ipynb0000644000175000017500000024074513451613166014237 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from picamera.array import PiYUVArray\n",
    "from picamera import PiCamera\n",
    "\n",
    "from scipy.signal import find_peaks, butter, filtfilt\n",
    "from pwm import PWM\n",
    "import tools\n",
    "import threading\n",
    "import ipywidgets as ipw\n",
    "import time\n",
    "#import matplotlib.pyplot as plt\n",
    "#import skimage as ski\n",
    "\n",
    "WIDTH_  = 224\n",
    "HEIGHT_ = 160\n",
    "CENTER_ = WIDTH_ // 2\n",
    "\n",
    "# Camera resolution\n",
    "res = (WIDTH_, HEIGHT_)\n",
    "\n",
    "# Run a track detection algorithm on a single horizontal line.\n",
    "# Uses YUV420 image format as the Y component corresponds to image intensity (gray image)\n",
    "# and thus there is no need to convert from RGB to BW\n",
    "\n",
    "camera = PiCamera()\n",
    "        \n",
    "# Check the link below for the combinations between mode and resolution\n",
    "# https://picamera.readthedocs.io/en/release-1.13/fov.html#sensor-modes\n",
    "camera.sensor_mode = 7\n",
    "camera.resolution = res\n",
    "camera.framerate = 120\n",
    "\n",
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "\n",
    "# Wn = 0.02, the cut-off frequency, acceptable values are from 0 to 1\n",
    "b, a = butter(3, 0.02)\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "pwm1 = PWM(1)\n",
    "\n",
    "pwm0.period = 20000000\n",
    "pwm1.period = 20000000\n",
    "\n",
    "pwm0.enable = True\n",
    "pwm1.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000\n",
    "pwm1.duty_cycle = 1600000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 1100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 2100000\n",
    "time.sleep(1)\n",
    "pwm1.duty_cycle = 1600000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b6d0444a8b2d452b86fbd0394a62caef",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "IntRangeSlider(value=(1138, 1275), description='Speed Ranges', max=1500, min=1000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4c44e98c29f549ccbac716c71a24ca5a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "ToggleButton(value=False, description='Shut it down')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[28.0, 23.0, -520, 38.0, 43.0, 49.0, 52.0, 58.0]\n",
      "[-22321, -102679, 169643, 22322, 26785, 13393, 26786, 13393]\n",
      "147322\n",
      "18415.25\n",
      "1975000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.42\n",
      "[41.0, 28.0, 23.0, -520, 38.0, 43.0, 49.0, 52.0]\n",
      "[-58036, -22321, -102679, 169643, 22322, 26785, 13393, 26786]\n",
      "75893\n",
      "9486.625\n",
      "1916964\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.13\n",
      "[54.0, 41.0, 28.0, 23.0, -520, 38.0, 43.0, 49.0]\n",
      "[-58036, -58036, -22321, -102679, 169643, 22322, 26785, 13393]\n",
      "-8929\n",
      "-1116.125\n",
      "1858928\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.26\n",
      "[63.0, 54.0, 41.0, 28.0, 23.0, -520, 38.0, 43.0]\n",
      "[-40178, -58036, -58036, -22321, -102679, 169643, 22322, 26785]\n",
      "-62500\n",
      "-7812.5\n",
      "1818750\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.13\n",
      "[68.0, 63.0, 54.0, 41.0, 28.0, 23.0, -520, 38.0]\n",
      "[-22322, -40178, -58036, -58036, -22321, -102679, 169643, 22322]\n",
      "-111607\n",
      "-13950.875\n",
      "1796428\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.09\n"
     ]
    }
   ],
   "source": [
    "#max speed that this algo works\n",
    "#ucla = 1120000\n",
    "#sonic = 1250000\n",
    "\n",
    "UCLA_         =  1138500\n",
    "USC_          =  1275000\n",
    "SONIC_        =  1275000\n",
    "LINE_         =  HEIGHT_ // 2\n",
    "INTERVAL_     =  0.0\n",
    "CENTER_THRESHOLD_ = WIDTH_ // 10\n",
    "\n",
    "STRAIGHT_     =  1600000\n",
    "RIGHT_        =  1100000\n",
    "LEFT_         =  2100000\n",
    "NUM_PREV_VAL_ =  8\n",
    "\n",
    "killSwitch = ipw.ToggleButton(value=False, description='Shut it down')\n",
    "minMaxSlider = ipw.IntRangeSlider(value=[UCLA_/1000,SONIC_/1000], min = 1000, max = 1500,step = 1, description = 'Speed Ranges')\n",
    "\n",
    "display(minMaxSlider)\n",
    "display(killSwitch)\n",
    "\n",
    "def main_loop():\n",
    "    rawCapture = PiYUVArray(camera, size=res)\n",
    "    stream = camera.capture_continuous(rawCapture, format=\"yuv\", use_video_port=True)\n",
    "\n",
    "    #for pwm1\n",
    "    #duty_cycle\n",
    "\n",
    "    #      (array([482, 542], dtype=int32), {'peak_heights': array([186.831036  , 185.01286929])})\n",
    "\n",
    "    numFrames = 0\n",
    "\n",
    "    #if linePos is 1 then the line is to the right of the car\n",
    "    #if linePos is -1 then the line is to the left of the car\n",
    "    #if linePos is 0 either uhoh we're doomed\n",
    "    #if lost is true then the line is lost\n",
    "    linePos = 0\n",
    "    lost = False\n",
    "    prevSteerDC = pwm1.duty_cycle\n",
    "    prevSteerDiffArr = []\n",
    "    prevPeakAvgArr = []\n",
    "    for i in range(NUM_PREV_VAL_):\n",
    "        prevSteerDiffArr.append(-1)\n",
    "        prevPeakAvgArr.append(-1)\n",
    "    \n",
    "    for f in stream:\n",
    "        t = time.time()\n",
    "        #speeds = update_speeds()\n",
    "        \n",
    "        #UCLA_ = speeds[0]\n",
    "        #SONIC_ = speeds[1]\n",
    "        \n",
    "        if killSwitch.value:\n",
    "            break\n",
    "\n",
    "        numFrames += 1\n",
    "        # Get the intensity component of the image (a trick to get black and white images)\n",
    "        I = f.array[:, :, 0]\n",
    "        # Reset the buffer for the next image\n",
    "        rawCapture.truncate(0)\n",
    "        # Select a horizontal line in the middle of the image\n",
    "        L = I[LINE_, :]\n",
    "        # Smooth the transitions so we can detect the peaks \n",
    "        Lf = filtfilt(b, a, L)\n",
    "        # Find peaks which are higher than 0.5\n",
    "        p = find_peaks(Lf, height=128)\n",
    "\n",
    "        totalPeakAmt = 0\n",
    "        avgPeakLoc = -520\n",
    "        numPeaks = 0\n",
    "\n",
    "        for peak in p[0]:\n",
    "            numPeaks += 1\n",
    "            totalPeakAmt += peak\n",
    "\n",
    "        if numPeaks != 0:\n",
    "            avgPeakLoc = totalPeakAmt / numPeaks\n",
    "            if numPeaks == 3:\n",
    "                print(\"THIS IS THE BEGINNING OF THE END\")\n",
    "\n",
    "        if avgPeakLoc != -520 :\n",
    "            if avgPeakLoc < CENTER_:\n",
    "                if lost and linePos == 1:\n",
    "                    #pwm1.duty_cycle = RIGHT_\n",
    "                    #continue\n",
    "                    break\n",
    "                linePos = -1\n",
    "            else:\n",
    "                if lost and linePos == -1:\n",
    "                    #pwm1.duty_cycle = LEFT_\n",
    "                    #continue\n",
    "                    break\n",
    "                linePos = 1\n",
    "\n",
    "            pwm1.duty_cycle = int(STRAIGHT_ - ((avgPeakLoc - CENTER_)/CENTER_)*500000)\n",
    "            lost = False\n",
    "        else:\n",
    "            if linePos == -1:\n",
    "                pwm1.duty_cycle = LEFT_\n",
    "            elif linePos == 1:\n",
    "                pwm1.duty_cycle = RIGHT_\n",
    "            else:\n",
    "                pwm1.duty_cycle = STRAIGHT_\n",
    "\n",
    "            lost = True\n",
    "            #pwm0.duty_cycle = SONIC_\n",
    "\n",
    "        if abs(prevSteerDC - STRAIGHT_) < abs(pwm1.duty_cycle - STRAIGHT_) and prevSteerDiffArr[0] > 0 and prevSteerDiffArr[1] > 0 and abs(pwm1.duty_cycle - STRAIGHT_) > 400000:\n",
    "            pwm0.duty_cycle = SONIC_\n",
    "            #prevSteerDiffArr[0] = -1\n",
    "            '''+ (500000 - abs(pwm1.duty_cycle - STRAIGHT_)))'''\n",
    "        elif abs(avgPeakLoc - CENTER_) <= CENTER_THRESHOLD_:\n",
    "            i = 0\n",
    "            while i < NUM_PREV_VAL_:\n",
    "                if abs(prevPeakAvgArr[i] - CENTER_) > CENTER_THRESHOLD_:\n",
    "                    break\n",
    "                i += 1\n",
    "            #print(\"STRAIGHT\")\n",
    "            if i == NUM_PREV_VAL_:\n",
    "                pwm0.duty_cycle = USC_\n",
    "        else:\n",
    "            pwm0.duty_cycle = UCLA_\n",
    "            if abs(pwm1.duty_cycle - STRAIGHT_) > 300000:\n",
    "                pwm0.duty_cycle = UCLA_ + 4000\n",
    "\n",
    "        i = NUM_PREV_VAL_ - 1\n",
    "        while i > 0:\n",
    "            prevSteerDiffArr[i] = prevSteerDiffArr[i - 1]\n",
    "            prevPeakAvgArr[i] = prevPeakAvgArr[i - 1]\n",
    "            i -= 1\n",
    "        \n",
    "        prevSteerDiffArr[0] = abs(pwm1.duty_cycle - STRAIGHT_) - abs(prevSteerDC - STRAIGHT_)\n",
    "        prevPeakAvgArr[0] = avgPeakLoc\n",
    "\n",
    "        prevSteerDC = pwm1.duty_cycle\n",
    "\n",
    "        time_elapsed = time.time() - t\n",
    "        \n",
    "        print(prevPeakAvgArr)\n",
    "        print(prevSteerDiffArr)\n",
    "        print(sum(prevSteerDiffArr))\n",
    "        print(sum(prevSteerDiffArr) / len(prevSteerDiffArr))\n",
    "        print(pwm1.duty_cycle)\n",
    "        print(\"Elapsed {:0.4f} seconds, estimated FPS {:0.2f}\".format(time_elapsed, 1 / time_elapsed))\n",
    "        time.sleep(INTERVAL_)\n",
    "        \n",
    "    pwm0.duty_cycle = 1000000\n",
    "\n",
    "    # Release resources\n",
    "    stream.close()\n",
    "    rawCapture.close()\n",
    "    camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_speeds():\n",
    "    UCLA_ = minMaxSlider.value[0] * 1000\n",
    "    SONIC_ = minMaxSlider.value[1] * 1000\n",
    "    return [UCLA_, SONIC_]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#minMaxSlider.observe(update_speeds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-520, -1, -1, -1, -1, -1, -1, -1]\n",
      "[0, -1, -1, -1, -1, -1, -1, -1]\n",
      "-7\n",
      "-0.875\n",
      "1600000\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.55\n",
      "[-520, -520, -1, -1, -1, -1, -1, -1]\n",
      "[0, 0, -1, -1, -1, -1, -1, -1]\n",
      "-6\n",
      "-0.75\n",
      "1600000\n",
      "Elapsed 0.0055 seconds, estimated FPS 183.18\n",
      "[-520, -520, -520, -1, -1, -1, -1, -1]\n",
      "[0, 0, 0, -1, -1, -1, -1, -1]\n",
      "-5\n",
      "-0.625\n",
      "1600000\n",
      "Elapsed 0.0063 seconds, estimated FPS 157.87\n",
      "[-520, -520, -520, -520, -1, -1, -1, -1]\n",
      "[0, 0, 0, 0, -1, -1, -1, -1]\n",
      "-4\n",
      "-0.5\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.59\n",
      "[-520, -520, -520, -520, -520, -1, -1, -1]\n",
      "[0, 0, 0, 0, 0, -1, -1, -1]\n",
      "-3\n",
      "-0.375\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.25\n",
      "[-520, -520, -520, -520, -520, -520, -1, -1]\n",
      "[0, 0, 0, 0, 0, 0, -1, -1]\n",
      "-2\n",
      "-0.25\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -1]\n",
      "[0, 0, 0, 0, 0, 0, 0, -1]\n",
      "-1\n",
      "-0.125\n",
      "1600000\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.78\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.09\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.49\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.07\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.97\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.78\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.69\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.24\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.14\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0062 seconds, estimated FPS 161.40\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.09\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1600000\n",
      "Elapsed 0.0054 seconds, estimated FPS 183.76\n",
      "[181.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[308036, 0, 0, 0, 0, 0, 0, 0]\n",
      "308036\n",
      "38504.5\n",
      "1291964\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.55\n",
      "[124.0, 181.0, -520, -520, -520, -520, -520, -520]\n",
      "[-254464, 308036, 0, 0, 0, 0, 0, 0]\n",
      "53572\n",
      "6696.5\n",
      "1546428\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.84\n",
      "[79.0, 124.0, 181.0, -520, -520, -520, -520, -520]\n",
      "[93749, -254464, 308036, 0, 0, 0, 0, 0]\n",
      "147321\n",
      "18415.125\n",
      "1747321\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.17\n",
      "[15.0, 79.0, 124.0, 181.0, -520, -520, -520, -520]\n",
      "[285714, 93749, -254464, 308036, 0, 0, 0, 0]\n",
      "433035\n",
      "54129.375\n",
      "2033035\n",
      "Elapsed 0.0065 seconds, estimated FPS 152.74\n",
      "[-520, 15.0, 79.0, 124.0, 181.0, -520, -520, -520]\n",
      "[66965, 285714, 93749, -254464, 308036, 0, 0, 0]\n",
      "500000\n",
      "62500.0\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 182.64\n",
      "[13.0, -520, 15.0, 79.0, 124.0, 181.0, -520, -520]\n",
      "[-58036, 66965, 285714, 93749, -254464, 308036, 0, 0]\n",
      "441964\n",
      "55245.5\n",
      "2041964\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.67\n",
      "[58.0, 13.0, -520, 15.0, 79.0, 124.0, 181.0, -520]\n",
      "[-200893, -58036, 66965, 285714, 93749, -254464, 308036, 0]\n",
      "241071\n",
      "30133.875\n",
      "1841071\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.66\n",
      "[97.0, 58.0, 13.0, -520, 15.0, 79.0, 124.0, 181.0]\n",
      "[-174107, -200893, -58036, 66965, 285714, 93749, -254464, 308036]\n",
      "66964\n",
      "8370.5\n",
      "1666964\n",
      "Elapsed 0.0092 seconds, estimated FPS 109.28\n",
      "[145.0, 97.0, 58.0, 13.0, -520, 15.0, 79.0, 124.0]\n",
      "[80358, -174107, -200893, -58036, 66965, 285714, 93749, -254464]\n",
      "-160714\n",
      "-20089.25\n",
      "1452678\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.81\n",
      "[-520, 145.0, 97.0, 58.0, 13.0, -520, 15.0, 79.0]\n",
      "[352678, 80358, -174107, -200893, -58036, 66965, 285714, 93749]\n",
      "446428\n",
      "55803.5\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.38\n",
      "[-520, -520, 145.0, 97.0, 58.0, 13.0, -520, 15.0]\n",
      "[0, 352678, 80358, -174107, -200893, -58036, 66965, 285714]\n",
      "352679\n",
      "44084.875\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.50\n",
      "[-520, -520, -520, 145.0, 97.0, 58.0, 13.0, -520]\n",
      "[0, 0, 352678, 80358, -174107, -200893, -58036, 66965]\n",
      "66965\n",
      "8370.625\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.14\n",
      "[-520, -520, -520, -520, 145.0, 97.0, 58.0, 13.0]\n",
      "[0, 0, 0, 352678, 80358, -174107, -200893, -58036]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0098 seconds, estimated FPS 101.74\n",
      "[-520, -520, -520, -520, -520, 145.0, 97.0, 58.0]\n",
      "[0, 0, 0, 0, 352678, 80358, -174107, -200893]\n",
      "58036\n",
      "7254.5\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.09\n",
      "[-520, -520, -520, -520, -520, -520, 145.0, 97.0]\n",
      "[0, 0, 0, 0, 0, 352678, 80358, -174107]\n",
      "258929\n",
      "32366.125\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.57\n",
      "[-520, -520, -520, -520, -520, -520, -520, 145.0]\n",
      "[0, 0, 0, 0, 0, 0, 352678, 80358]\n",
      "433036\n",
      "54129.5\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 352678]\n",
      "352678\n",
      "44084.75\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.52\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0099 seconds, estimated FPS 101.38\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.85\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.91\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.83\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0101 seconds, estimated FPS 98.80\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.55\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.32\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.26\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.53\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.77\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.18\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.14\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.30\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.65\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.34\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.96\n",
      "[158.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-294642, 0, 0, 0, 0, 0, 0, 0]\n",
      "-294642\n",
      "-36830.25\n",
      "1394642\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.79\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[119.0, 158.0, -520, -520, -520, -520, -520, -520]\n",
      "[-174108, -294642, 0, 0, 0, 0, 0, 0]\n",
      "-468750\n",
      "-58593.75\n",
      "1568750\n",
      "Elapsed 0.0053 seconds, estimated FPS 189.20\n",
      "[66.0, 119.0, 158.0, -520, -520, -520, -520, -520]\n",
      "[174107, -174108, -294642, 0, 0, 0, 0, 0]\n",
      "-294643\n",
      "-36830.375\n",
      "1805357\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.16\n",
      "[6.0, 66.0, 119.0, 158.0, -520, -520, -520, -520]\n",
      "[267857, 174107, -174108, -294642, 0, 0, 0, 0]\n",
      "-26786\n",
      "-3348.25\n",
      "2073214\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.21\n",
      "[5.0, 6.0, 66.0, 119.0, 158.0, -520, -520, -520]\n",
      "[4464, 267857, 174107, -174108, -294642, 0, 0, 0]\n",
      "-22322\n",
      "-2790.25\n",
      "2077678\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.11\n",
      "[-520, 5.0, 6.0, 66.0, 119.0, 158.0, -520, -520]\n",
      "[22322, 4464, 267857, 174107, -174108, -294642, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 182.35\n",
      "[-520, -520, 5.0, 6.0, 66.0, 119.0, 158.0, -520]\n",
      "[0, 22322, 4464, 267857, 174107, -174108, -294642, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.81\n",
      "[-520, -520, -520, 5.0, 6.0, 66.0, 119.0, 158.0]\n",
      "[0, 0, 22322, 4464, 267857, 174107, -174108, -294642]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.10\n",
      "[-520, -520, -520, -520, 5.0, 6.0, 66.0, 119.0]\n",
      "[0, 0, 0, 22322, 4464, 267857, 174107, -174108]\n",
      "294642\n",
      "36830.25\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.95\n",
      "[-520, -520, -520, -520, -520, 5.0, 6.0, 66.0]\n",
      "[0, 0, 0, 0, 22322, 4464, 267857, 174107]\n",
      "468750\n",
      "58593.75\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.46\n",
      "[-520, -520, -520, -520, -520, -520, 5.0, 6.0]\n",
      "[0, 0, 0, 0, 0, 22322, 4464, 267857]\n",
      "294643\n",
      "36830.375\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.14\n",
      "[46.0, -520, -520, -520, -520, -520, -520, 5.0]\n",
      "[-205358, 0, 0, 0, 0, 0, 22322, 4464]\n",
      "-178572\n",
      "-22321.5\n",
      "1894642\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.35\n",
      "[135.0, 46.0, -520, -520, -520, -520, -520, -520]\n",
      "[-191963, -205358, 0, 0, 0, 0, 0, 22322]\n",
      "-374999\n",
      "-46874.875\n",
      "1497321\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.43\n",
      "[-520, 135.0, 46.0, -520, -520, -520, -520, -520]\n",
      "[397321, -191963, -205358, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.57\n",
      "[-520, -520, 135.0, 46.0, -520, -520, -520, -520]\n",
      "[0, 397321, -191963, -205358, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.23\n",
      "[-520, -520, -520, 135.0, 46.0, -520, -520, -520]\n",
      "[0, 0, 397321, -191963, -205358, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.70\n",
      "[-520, -520, -520, -520, 135.0, 46.0, -520, -520]\n",
      "[0, 0, 0, 397321, -191963, -205358, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.27\n",
      "[-520, -520, -520, -520, -520, 135.0, 46.0, -520]\n",
      "[0, 0, 0, 0, 397321, -191963, -205358, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.98\n",
      "[-520, -520, -520, -520, -520, -520, 135.0, 46.0]\n",
      "[0, 0, 0, 0, 0, 397321, -191963, -205358]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.33\n",
      "[-520, -520, -520, -520, -520, -520, -520, 135.0]\n",
      "[0, 0, 0, 0, 0, 0, 397321, -191963]\n",
      "205358\n",
      "25669.75\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.73\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 397321]\n",
      "397321\n",
      "49665.125\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.95\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.30\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.20\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0100 seconds, estimated FPS 99.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.67\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 168.03\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.32\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.07\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.33\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.46\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.86\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.01\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.89\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.79\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.28\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.52\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.15\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.76\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.16\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "1100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.53\n",
      "[217.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-31250, 0, 0, 0, 0, 0, 0, 0]\n",
      "-31250\n",
      "-3906.25\n",
      "1131250\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.97\n",
      "[145.0, 217.0, -520, -520, -520, -520, -520, -520]\n",
      "[-321428, -31250, 0, 0, 0, 0, 0, 0]\n",
      "-352678\n",
      "-44084.75\n",
      "1452678\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.96\n",
      "[92.0, 145.0, 217.0, -520, -520, -520, -520, -520]\n",
      "[-58037, -321428, -31250, 0, 0, 0, 0, 0]\n",
      "-410715\n",
      "-51339.375\n",
      "1689285\n",
      "Elapsed 0.0053 seconds, estimated FPS 187.99\n",
      "[19.0, 92.0, 145.0, 217.0, -520, -520, -520, -520]\n",
      "[325893, -58037, -321428, -31250, 0, 0, 0, 0]\n",
      "-84822\n",
      "-10602.75\n",
      "2015178\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.50\n",
      "[-520, 19.0, 92.0, 145.0, 217.0, -520, -520, -520]\n",
      "[84822, 325893, -58037, -321428, -31250, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.46\n",
      "[-520, -520, 19.0, 92.0, 145.0, 217.0, -520, -520]\n",
      "[0, 84822, 325893, -58037, -321428, -31250, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.31\n",
      "[-520, -520, -520, 19.0, 92.0, 145.0, 217.0, -520]\n",
      "[0, 0, 84822, 325893, -58037, -321428, -31250, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 170.96\n",
      "[-520, -520, -520, -520, 19.0, 92.0, 145.0, 217.0]\n",
      "[0, 0, 0, 84822, 325893, -58037, -321428, -31250]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0102 seconds, estimated FPS 98.49\n",
      "[-520, -520, -520, -520, -520, 19.0, 92.0, 145.0]\n",
      "[0, 0, 0, 0, 84822, 325893, -58037, -321428]\n",
      "31250\n",
      "3906.25\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.49\n",
      "[-520, -520, -520, -520, -520, -520, 19.0, 92.0]\n",
      "[0, 0, 0, 0, 0, 84822, 325893, -58037]\n",
      "352678\n",
      "44084.75\n",
      "2100000\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.27\n",
      "[-520, -520, -520, -520, -520, -520, -520, 19.0]\n",
      "[0, 0, 0, 0, 0, 0, 84822, 325893]\n",
      "410715\n",
      "51339.375\n",
      "2100000\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.08\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 84822]\n",
      "84822\n",
      "10602.75\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.24\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.46\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.48\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.20\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.10\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.26\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.85\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.38\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.84\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.70\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.69\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.48\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.54\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.23\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.80\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.27\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.82\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.73\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.92\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.35\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.91\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.68\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.81\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.66\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.37\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.16\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.71\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.04\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.82\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.45\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.15\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.06\n",
      "[-520, -520, -520, -520, -520, -520, -520, -520]\n",
      "[0, 0, 0, 0, 0, 0, 0, 0]\n",
      "0\n",
      "0.0\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.98\n",
      "[8.0, -520, -520, -520, -520, -520, -520, -520]\n",
      "[-35715, 0, 0, 0, 0, 0, 0, 0]\n",
      "-35715\n",
      "-4464.375\n",
      "2064285\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.50\n",
      "[41.0, 8.0, -520, -520, -520, -520, -520, -520]\n",
      "[-147321, -35715, 0, 0, 0, 0, 0, 0]\n",
      "-183036\n",
      "-22879.5\n",
      "1916964\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.92\n",
      "[62.0, 41.0, 8.0, -520, -520, -520, -520, -520]\n",
      "[-93750, -147321, -35715, 0, 0, 0, 0, 0]\n",
      "-276786\n",
      "-34598.25\n",
      "1823214\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.03\n",
      "[80.0, 62.0, 41.0, 8.0, -520, -520, -520, -520]\n",
      "[-80357, -93750, -147321, -35715, 0, 0, 0, 0]\n",
      "-357143\n",
      "-44642.875\n",
      "1742857\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.19\n",
      "[93.0, 80.0, 62.0, 41.0, 8.0, -520, -520, -520]\n",
      "[-58036, -80357, -93750, -147321, -35715, 0, 0, 0]\n",
      "-415179\n",
      "-51897.375\n",
      "1684821\n",
      "Elapsed 0.0051 seconds, estimated FPS 197.76\n",
      "[109.0, 93.0, 80.0, 62.0, 41.0, 8.0, -520, -520]\n",
      "[-71429, -58036, -80357, -93750, -147321, -35715, 0, 0]\n",
      "-486608\n",
      "-60826.0\n",
      "1613392\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.34\n",
      "[119.0, 109.0, 93.0, 80.0, 62.0, 41.0, 8.0, -520]\n",
      "[17858, -71429, -58036, -80357, -93750, -147321, -35715, 0]\n",
      "-468750\n",
      "-58593.75\n",
      "1568750\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.77\n",
      "[120.0, 119.0, 109.0, 93.0, 80.0, 62.0, 41.0, 8.0]\n",
      "[4465, 17858, -71429, -58036, -80357, -93750, -147321, -35715]\n",
      "-464285\n",
      "-58035.625\n",
      "1564285\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.80\n",
      "[112.0, 120.0, 119.0, 109.0, 93.0, 80.0, 62.0, 41.0]\n",
      "[-35715, 4465, 17858, -71429, -58036, -80357, -93750, -147321]\n",
      "-464285\n",
      "-58035.625\n",
      "1600000\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.23\n",
      "[99.0, 112.0, 120.0, 119.0, 109.0, 93.0, 80.0, 62.0]\n",
      "[58035, -35715, 4465, 17858, -71429, -58036, -80357, -93750]\n",
      "-258929\n",
      "-32366.125\n",
      "1658035\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.23\n",
      "[85.0, 99.0, 112.0, 120.0, 119.0, 109.0, 93.0, 80.0]\n",
      "[62500, 58035, -35715, 4465, 17858, -71429, -58036, -80357]\n",
      "-102679\n",
      "-12834.875\n",
      "1720535\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.00\n",
      "[72.0, 85.0, 99.0, 112.0, 120.0, 119.0, 109.0, 93.0]\n",
      "[58036, 62500, 58035, -35715, 4465, 17858, -71429, -58036]\n",
      "35714\n",
      "4464.25\n",
      "1778571\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.97\n",
      "[59.0, 72.0, 85.0, 99.0, 112.0, 120.0, 119.0, 109.0]\n",
      "[58036, 58036, 62500, 58035, -35715, 4465, 17858, -71429]\n",
      "151786\n",
      "18973.25\n",
      "1836607\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.95\n",
      "[50.0, 59.0, 72.0, 85.0, 99.0, 112.0, 120.0, 119.0]\n",
      "[40178, 58036, 58036, 62500, 58035, -35715, 4465, 17858]\n",
      "263393\n",
      "32924.125\n",
      "1876785\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.77\n",
      "[46.0, 50.0, 59.0, 72.0, 85.0, 99.0, 112.0, 120.0]\n",
      "[17857, 40178, 58036, 58036, 62500, 58035, -35715, 4465]\n",
      "263392\n",
      "32924.0\n",
      "1894642\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.95\n",
      "[41.0, 46.0, 50.0, 59.0, 72.0, 85.0, 99.0, 112.0]\n",
      "[22322, 17857, 40178, 58036, 58036, 62500, 58035, -35715]\n",
      "281249\n",
      "35156.125\n",
      "1916964\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.44\n",
      "[42.0, 41.0, 46.0, 50.0, 59.0, 72.0, 85.0, 99.0]\n",
      "[-4464, 22322, 17857, 40178, 58036, 58036, 62500, 58035]\n",
      "312500\n",
      "39062.5\n",
      "1912500\n",
      "Elapsed 0.0104 seconds, estimated FPS 96.14\n",
      "[46.0, 42.0, 41.0, 46.0, 50.0, 59.0, 72.0, 85.0]\n",
      "[-17858, -4464, 22322, 17857, 40178, 58036, 58036, 62500]\n",
      "236607\n",
      "29575.875\n",
      "1894642\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.33\n",
      "[51.0, 46.0, 42.0, 41.0, 46.0, 50.0, 59.0, 72.0]\n",
      "[-22321, -17858, -4464, 22322, 17857, 40178, 58036, 58036]\n",
      "151786\n",
      "18973.25\n",
      "1872321\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.74\n",
      "[56.0, 51.0, 46.0, 42.0, 41.0, 46.0, 50.0, 59.0]\n",
      "[-22321, -22321, -17858, -4464, 22322, 17857, 40178, 58036]\n",
      "71429\n",
      "8928.625\n",
      "1850000\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.02\n",
      "[58.0, 56.0, 51.0, 46.0, 42.0, 41.0, 46.0, 50.0]\n",
      "[-8929, -22321, -22321, -17858, -4464, 22322, 17857, 40178]\n",
      "4464\n",
      "558.0\n",
      "1841071\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.60\n",
      "[63.0, 58.0, 56.0, 51.0, 46.0, 42.0, 41.0, 46.0]\n",
      "[-22321, -8929, -22321, -22321, -17858, -4464, 22322, 17857]\n",
      "-58035\n",
      "-7254.375\n",
      "1818750\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.06\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[65.0, 63.0, 58.0, 56.0, 51.0, 46.0, 42.0, 41.0]\n",
      "[-8929, -22321, -8929, -22321, -22321, -17858, -4464, 22322]\n",
      "-84821\n",
      "-10602.625\n",
      "1809821\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.59\n",
      "[64.0, 65.0, 63.0, 58.0, 56.0, 51.0, 46.0, 42.0]\n",
      "[4464, -8929, -22321, -8929, -22321, -22321, -17858, -4464]\n",
      "-102679\n",
      "-12834.875\n",
      "1814285\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.33\n",
      "[64.0, 64.0, 65.0, 63.0, 58.0, 56.0, 51.0, 46.0]\n",
      "[0, 4464, -8929, -22321, -8929, -22321, -22321, -17858]\n",
      "-98215\n",
      "-12276.875\n",
      "1814285\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.04\n",
      "[64.0, 64.0, 64.0, 65.0, 63.0, 58.0, 56.0, 51.0]\n",
      "[0, 0, 4464, -8929, -22321, -8929, -22321, -22321]\n",
      "-80357\n",
      "-10044.625\n",
      "1814285\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.61\n",
      "[63.0, 64.0, 64.0, 64.0, 65.0, 63.0, 58.0, 56.0]\n",
      "[4465, 0, 0, 4464, -8929, -22321, -8929, -22321]\n",
      "-53571\n",
      "-6696.375\n",
      "1818750\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.12\n",
      "[58.0, 63.0, 64.0, 64.0, 64.0, 65.0, 63.0, 58.0]\n",
      "[22321, 4465, 0, 0, 4464, -8929, -22321, -8929]\n",
      "-8929\n",
      "-1116.125\n",
      "1841071\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.76\n",
      "[53.0, 58.0, 63.0, 64.0, 64.0, 64.0, 65.0, 63.0]\n",
      "[22321, 22321, 4465, 0, 0, 4464, -8929, -22321]\n",
      "22321\n",
      "2790.125\n",
      "1863392\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.20\n",
      "[49.0, 53.0, 58.0, 63.0, 64.0, 64.0, 64.0, 65.0]\n",
      "[17858, 22321, 22321, 4465, 0, 0, 4464, -8929]\n",
      "62500\n",
      "7812.5\n",
      "1881250\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.54\n",
      "[46.0, 49.0, 53.0, 58.0, 63.0, 64.0, 64.0, 64.0]\n",
      "[13392, 17858, 22321, 22321, 4465, 0, 0, 4464]\n",
      "84821\n",
      "10602.625\n",
      "1894642\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.94\n",
      "[41.0, 46.0, 49.0, 53.0, 58.0, 63.0, 64.0, 64.0]\n",
      "[22322, 13392, 17858, 22321, 22321, 4465, 0, 0]\n",
      "102679\n",
      "12834.875\n",
      "1916964\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.45\n",
      "[36.0, 41.0, 46.0, 49.0, 53.0, 58.0, 63.0, 64.0]\n",
      "[22321, 22322, 13392, 17858, 22321, 22321, 4465, 0]\n",
      "125000\n",
      "15625.0\n",
      "1939285\n",
      "Elapsed 0.0064 seconds, estimated FPS 156.66\n",
      "[34.0, 36.0, 41.0, 46.0, 49.0, 53.0, 58.0, 63.0]\n",
      "[8929, 22321, 22322, 13392, 17858, 22321, 22321, 4465]\n",
      "133929\n",
      "16741.125\n",
      "1948214\n",
      "Elapsed 0.0106 seconds, estimated FPS 94.77\n",
      "[-520, 34.0, 36.0, 41.0, 46.0, 49.0, 53.0, 58.0]\n",
      "[151786, 8929, 22321, 22322, 13392, 17858, 22321, 22321]\n",
      "281250\n",
      "35156.25\n",
      "2100000\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.81\n",
      "[29.0, -520, 34.0, 36.0, 41.0, 46.0, 49.0, 53.0]\n",
      "[-129465, 151786, 8929, 22321, 22322, 13392, 17858, 22321]\n",
      "129464\n",
      "16183.0\n",
      "1970535\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.48\n",
      "[35.0, 29.0, -520, 34.0, 36.0, 41.0, 46.0, 49.0]\n",
      "[-26785, -129465, 151786, 8929, 22321, 22322, 13392, 17858]\n",
      "80358\n",
      "10044.75\n",
      "1943750\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.83\n",
      "[48.0, 35.0, 29.0, -520, 34.0, 36.0, 41.0, 46.0]\n",
      "[-58036, -26785, -129465, 151786, 8929, 22321, 22322, 13392]\n",
      "4464\n",
      "558.0\n",
      "1885714\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.22\n",
      "[62.0, 48.0, 35.0, 29.0, -520, 34.0, 36.0, 41.0]\n",
      "[-62500, -58036, -26785, -129465, 151786, 8929, 22321, 22322]\n",
      "-71428\n",
      "-8928.5\n",
      "1823214\n",
      "Elapsed 0.0101 seconds, estimated FPS 99.20\n",
      "[80.0, 62.0, 48.0, 35.0, 29.0, -520, 34.0, 36.0]\n",
      "[-80357, -62500, -58036, -26785, -129465, 151786, 8929, 22321]\n",
      "-174107\n",
      "-21763.375\n",
      "1742857\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.34\n",
      "[97.0, 80.0, 62.0, 48.0, 35.0, 29.0, -520, 34.0]\n",
      "[-75893, -80357, -62500, -58036, -26785, -129465, 151786, 8929]\n",
      "-272321\n",
      "-34040.125\n",
      "1666964\n",
      "Elapsed 0.0052 seconds, estimated FPS 193.13\n",
      "[116.0, 97.0, 80.0, 62.0, 48.0, 35.0, 29.0, -520]\n",
      "[-49106, -75893, -80357, -62500, -58036, -26785, -129465, 151786]\n",
      "-330356\n",
      "-41294.5\n",
      "1582142\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.88\n",
      "[125.0, 116.0, 97.0, 80.0, 62.0, 48.0, 35.0, 29.0]\n",
      "[40178, -49106, -75893, -80357, -62500, -58036, -26785, -129465]\n",
      "-441964\n",
      "-55245.5\n",
      "1541964\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.93\n",
      "[126.0, 125.0, 116.0, 97.0, 80.0, 62.0, 48.0, 35.0]\n",
      "[4464, 40178, -49106, -75893, -80357, -62500, -58036, -26785]\n",
      "-308035\n",
      "-38504.375\n",
      "1537500\n",
      "Elapsed 0.0093 seconds, estimated FPS 108.03\n",
      "[116.0, 126.0, 125.0, 116.0, 97.0, 80.0, 62.0, 48.0]\n",
      "[-44642, 4464, 40178, -49106, -75893, -80357, -62500, -58036]\n",
      "-325892\n",
      "-40736.5\n",
      "1582142\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.67\n",
      "[95.0, 116.0, 126.0, 125.0, 116.0, 97.0, 80.0, 62.0]\n",
      "[58034, -44642, 4464, 40178, -49106, -75893, -80357, -62500]\n",
      "-209822\n",
      "-26227.75\n",
      "1675892\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.60\n",
      "[65.0, 95.0, 116.0, 126.0, 125.0, 116.0, 97.0, 80.0]\n",
      "[133929, 58034, -44642, 4464, 40178, -49106, -75893, -80357]\n",
      "-13393\n",
      "-1674.125\n",
      "1809821\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.74\n",
      "[37.0, 65.0, 95.0, 116.0, 126.0, 125.0, 116.0, 97.0]\n",
      "[125000, 133929, 58034, -44642, 4464, 40178, -49106, -75893]\n",
      "191964\n",
      "23995.5\n",
      "1934821\n",
      "Elapsed 0.0064 seconds, estimated FPS 157.22\n",
      "[7.0, 37.0, 65.0, 95.0, 116.0, 126.0, 125.0, 116.0]\n",
      "[133929, 125000, 133929, 58034, -44642, 4464, 40178, -49106]\n",
      "401786\n",
      "50223.25\n",
      "2068750\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.19\n",
      "[-520, 7.0, 37.0, 65.0, 95.0, 116.0, 126.0, 125.0]\n",
      "[31250, 133929, 125000, 133929, 58034, -44642, 4464, 40178]\n",
      "482142\n",
      "60267.75\n",
      "2100000\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.80\n",
      "[-520, -520, 7.0, 37.0, 65.0, 95.0, 116.0, 126.0]\n",
      "[0, 31250, 133929, 125000, 133929, 58034, -44642, 4464]\n",
      "441964\n",
      "55245.5\n",
      "2100000\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.56\n",
      "[2.0, -520, -520, 7.0, 37.0, 65.0, 95.0, 116.0]\n",
      "[-8929, 0, 31250, 133929, 125000, 133929, 58034, -44642]\n",
      "428571\n",
      "53571.375\n",
      "2091071\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.14\n",
      "[35.0, 2.0, -520, -520, 7.0, 37.0, 65.0, 95.0]\n",
      "[-147321, -8929, 0, 31250, 133929, 125000, 133929, 58034]\n",
      "325892\n",
      "40736.5\n",
      "1943750\n",
      "Elapsed 0.0061 seconds, estimated FPS 165.01\n",
      "[62.0, 35.0, 2.0, -520, -520, 7.0, 37.0, 65.0]\n",
      "[-120536, -147321, -8929, 0, 31250, 133929, 125000, 133929]\n",
      "147322\n",
      "18415.25\n",
      "1823214\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.08\n",
      "[90.0, 62.0, 35.0, 2.0, -520, -520, 7.0, 37.0]\n",
      "[-125000, -120536, -147321, -8929, 0, 31250, 133929, 125000]\n",
      "-111607\n",
      "-13950.875\n",
      "1698214\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.19\n",
      "[119.0, 90.0, 62.0, 35.0, 2.0, -520, -520, 7.0]\n",
      "[-66964, -125000, -120536, -147321, -8929, 0, 31250, 133929]\n",
      "-303571\n",
      "-37946.375\n",
      "1568750\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.15\n",
      "[145.0, 119.0, 90.0, 62.0, 35.0, 2.0, -520, -520]\n",
      "[116072, -66964, -125000, -120536, -147321, -8929, 0, 31250]\n",
      "-321428\n",
      "-40178.5\n",
      "1452678\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.41\n",
      "[157.0, 145.0, 119.0, 90.0, 62.0, 35.0, 2.0, -520]\n",
      "[53571, 116072, -66964, -125000, -120536, -147321, -8929, 0]\n",
      "-299107\n",
      "-37388.375\n",
      "1399107\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.86\n",
      "[165.0, 157.0, 145.0, 119.0, 90.0, 62.0, 35.0, 2.0]\n",
      "[35715, 53571, 116072, -66964, -125000, -120536, -147321, -8929]\n",
      "-263392\n",
      "-32924.0\n",
      "1363392\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.94\n",
      "[162.0, 165.0, 157.0, 145.0, 119.0, 90.0, 62.0, 35.0]\n",
      "[-13393, 35715, 53571, 116072, -66964, -125000, -120536, -147321]\n",
      "-267856\n",
      "-33482.0\n",
      "1376785\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.29\n",
      "[149.0, 162.0, 165.0, 157.0, 145.0, 119.0, 90.0, 62.0]\n",
      "[-58036, -13393, 35715, 53571, 116072, -66964, -125000, -120536]\n",
      "-178571\n",
      "-22321.375\n",
      "1434821\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.35\n",
      "[129.0, 149.0, 162.0, 165.0, 157.0, 145.0, 119.0, 90.0]\n",
      "[-89286, -58036, -13393, 35715, 53571, 116072, -66964, -125000]\n",
      "-147321\n",
      "-18415.125\n",
      "1524107\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.94\n",
      "[109.0, 129.0, 149.0, 162.0, 165.0, 157.0, 145.0, 119.0]\n",
      "[-62501, -89286, -58036, -13393, 35715, 53571, 116072, -66964]\n",
      "-84822\n",
      "-10602.75\n",
      "1613392\n",
      "Elapsed 0.0050 seconds, estimated FPS 201.49\n",
      "[83.0, 109.0, 129.0, 149.0, 162.0, 165.0, 157.0, 145.0]\n",
      "[116072, -62501, -89286, -58036, -13393, 35715, 53571, 116072]\n",
      "98214\n",
      "12276.75\n",
      "1729464\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.83\n",
      "[65.0, 83.0, 109.0, 129.0, 149.0, 162.0, 165.0, 157.0]\n",
      "[80357, 116072, -62501, -89286, -58036, -13393, 35715, 53571]\n",
      "62499\n",
      "7812.375\n",
      "1809821\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.18\n",
      "[53.0, 65.0, 83.0, 109.0, 129.0, 149.0, 162.0, 165.0]\n",
      "[53571, 80357, 116072, -62501, -89286, -58036, -13393, 35715]\n",
      "62499\n",
      "7812.375\n",
      "1863392\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.22\n",
      "[51.0, 53.0, 65.0, 83.0, 109.0, 129.0, 149.0, 162.0]\n",
      "[8929, 53571, 80357, 116072, -62501, -89286, -58036, -13393]\n",
      "35713\n",
      "4464.125\n",
      "1872321\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.49\n",
      "[61.0, 51.0, 53.0, 65.0, 83.0, 109.0, 129.0, 149.0]\n",
      "[-44643, 8929, 53571, 80357, 116072, -62501, -89286, -58036]\n",
      "4463\n",
      "557.875\n",
      "1827678\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.05\n",
      "[77.0, 61.0, 51.0, 53.0, 65.0, 83.0, 109.0, 129.0]\n",
      "[-71428, -44643, 8929, 53571, 80357, 116072, -62501, -89286]\n",
      "-8929\n",
      "-1116.125\n",
      "1756250\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[95.0, 77.0, 61.0, 51.0, 53.0, 65.0, 83.0, 109.0]\n",
      "[-80358, -71428, -44643, 8929, 53571, 80357, 116072, -62501]\n",
      "-1\n",
      "-0.125\n",
      "1675892\n",
      "Elapsed 0.0062 seconds, estimated FPS 162.11\n",
      "[108.0, 95.0, 77.0, 61.0, 51.0, 53.0, 65.0, 83.0]\n",
      "[-58035, -80358, -71428, -44643, 8929, 53571, 80357, 116072]\n",
      "4465\n",
      "558.125\n",
      "1617857\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.47\n",
      "[119.0, 108.0, 95.0, 77.0, 61.0, 51.0, 53.0, 65.0]\n",
      "[13393, -58035, -80358, -71428, -44643, 8929, 53571, 80357]\n",
      "-98214\n",
      "-12276.75\n",
      "1568750\n",
      "Elapsed 0.0052 seconds, estimated FPS 191.32\n",
      "[129.0, 119.0, 108.0, 95.0, 77.0, 61.0, 51.0, 53.0]\n",
      "[44643, 13393, -58035, -80358, -71428, -44643, 8929, 53571]\n",
      "-133928\n",
      "-16741.0\n",
      "1524107\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.21\n",
      "[128.0, 129.0, 119.0, 108.0, 95.0, 77.0, 61.0, 51.0]\n",
      "[-4464, 44643, 13393, -58035, -80358, -71428, -44643, 8929]\n",
      "-191963\n",
      "-23995.375\n",
      "1528571\n",
      "Elapsed 0.0051 seconds, estimated FPS 195.07\n",
      "[127.0, 128.0, 129.0, 119.0, 108.0, 95.0, 77.0, 61.0]\n",
      "[-4464, -4464, 44643, 13393, -58035, -80358, -71428, -44643]\n",
      "-205356\n",
      "-25669.5\n",
      "1533035\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.36\n",
      "[119.0, 127.0, 128.0, 129.0, 119.0, 108.0, 95.0, 77.0]\n",
      "[-35715, -4464, -4464, 44643, 13393, -58035, -80358, -71428]\n",
      "-196428\n",
      "-24553.5\n",
      "1568750\n",
      "Elapsed 0.0052 seconds, estimated FPS 192.43\n",
      "[112.0, 119.0, 127.0, 128.0, 129.0, 119.0, 108.0, 95.0]\n",
      "[-31250, -35715, -4464, -4464, 44643, 13393, -58035, -80358]\n",
      "-156250\n",
      "-19531.25\n",
      "1600000\n",
      "Elapsed 0.0052 seconds, estimated FPS 191.42\n",
      "[104.0, 112.0, 119.0, 127.0, 128.0, 129.0, 119.0, 108.0]\n",
      "[35714, -31250, -35715, -4464, -4464, 44643, 13393, -58035]\n",
      "-40178\n",
      "-5022.25\n",
      "1635714\n",
      "Elapsed 0.0055 seconds, estimated FPS 181.93\n",
      "[97.0, 104.0, 112.0, 119.0, 127.0, 128.0, 129.0, 119.0]\n",
      "[31250, 35714, -31250, -35715, -4464, -4464, 44643, 13393]\n",
      "49107\n",
      "6138.375\n",
      "1666964\n",
      "Elapsed 0.0054 seconds, estimated FPS 184.89\n",
      "[90.0, 97.0, 104.0, 112.0, 119.0, 127.0, 128.0, 129.0]\n",
      "[31250, 31250, 35714, -31250, -35715, -4464, -4464, 44643]\n",
      "66964\n",
      "8370.5\n",
      "1698214\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.94\n",
      "[88.0, 90.0, 97.0, 104.0, 112.0, 119.0, 127.0, 128.0]\n",
      "[8928, 31250, 31250, 35714, -31250, -35715, -4464, -4464]\n",
      "31249\n",
      "3906.125\n",
      "1707142\n",
      "Elapsed 0.0102 seconds, estimated FPS 98.33\n",
      "[87.0, 88.0, 90.0, 97.0, 104.0, 112.0, 119.0, 127.0]\n",
      "[4465, 8928, 31250, 31250, 35714, -31250, -35715, -4464]\n",
      "40178\n",
      "5022.25\n",
      "1711607\n",
      "Elapsed 0.0061 seconds, estimated FPS 164.44\n",
      "[89.0, 87.0, 88.0, 90.0, 97.0, 104.0, 112.0, 119.0]\n",
      "[-8929, 4465, 8928, 31250, 31250, 35714, -31250, -35715]\n",
      "35713\n",
      "4464.125\n",
      "1702678\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.41\n",
      "[93.0, 89.0, 87.0, 88.0, 90.0, 97.0, 104.0, 112.0]\n",
      "[-17857, -8929, 4465, 8928, 31250, 31250, 35714, -31250]\n",
      "53571\n",
      "6696.375\n",
      "1684821\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.23\n",
      "[100.0, 93.0, 89.0, 87.0, 88.0, 90.0, 97.0, 104.0]\n",
      "[-31250, -17857, -8929, 4465, 8928, 31250, 31250, 35714]\n",
      "53571\n",
      "6696.375\n",
      "1653571\n",
      "Elapsed 0.0049 seconds, estimated FPS 202.19\n",
      "[108.0, 100.0, 93.0, 89.0, 87.0, 88.0, 90.0, 97.0]\n",
      "[-35714, -31250, -17857, -8929, 4465, 8928, 31250, 31250]\n",
      "-17857\n",
      "-2232.125\n",
      "1617857\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.77\n",
      "[116.0, 108.0, 100.0, 93.0, 89.0, 87.0, 88.0, 90.0]\n",
      "[1, -35714, -31250, -17857, -8929, 4465, 8928, 31250]\n",
      "-49106\n",
      "-6138.25\n",
      "1582142\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.71\n",
      "[121.0, 116.0, 108.0, 100.0, 93.0, 89.0, 87.0, 88.0]\n",
      "[22321, 1, -35714, -31250, -17857, -8929, 4465, 8928]\n",
      "-58035\n",
      "-7254.375\n",
      "1559821\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.97\n",
      "[122.0, 121.0, 116.0, 108.0, 100.0, 93.0, 89.0, 87.0]\n",
      "[4464, 22321, 1, -35714, -31250, -17857, -8929, 4465]\n",
      "-62499\n",
      "-7812.375\n",
      "1555357\n",
      "Elapsed 0.0054 seconds, estimated FPS 185.57\n",
      "[117.0, 122.0, 121.0, 116.0, 108.0, 100.0, 93.0, 89.0]\n",
      "[-22321, 4464, 22321, 1, -35714, -31250, -17857, -8929]\n",
      "-89285\n",
      "-11160.625\n",
      "1577678\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.58\n",
      "[105.0, 117.0, 122.0, 121.0, 116.0, 108.0, 100.0, 93.0]\n",
      "[8928, -22321, 4464, 22321, 1, -35714, -31250, -17857]\n",
      "-71428\n",
      "-8928.5\n",
      "1631250\n",
      "Elapsed 0.0051 seconds, estimated FPS 194.20\n",
      "[100.0, 105.0, 117.0, 122.0, 121.0, 116.0, 108.0, 100.0]\n",
      "[22321, 8928, -22321, 4464, 22321, 1, -35714, -31250]\n",
      "-31250\n",
      "-3906.25\n",
      "1653571\n",
      "Elapsed 0.0091 seconds, estimated FPS 110.31\n",
      "[95.0, 100.0, 105.0, 117.0, 122.0, 121.0, 116.0, 108.0]\n",
      "[22321, 22321, 8928, -22321, 4464, 22321, 1, -35714]\n",
      "22321\n",
      "2790.125\n",
      "1675892\n",
      "Elapsed 0.0058 seconds, estimated FPS 173.61\n",
      "[91.0, 95.0, 100.0, 105.0, 117.0, 122.0, 121.0, 116.0]\n",
      "[17858, 22321, 22321, 8928, -22321, 4464, 22321, 1]\n",
      "75893\n",
      "9486.625\n",
      "1693750\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.77\n",
      "[84.0, 91.0, 95.0, 100.0, 105.0, 117.0, 122.0, 121.0]\n",
      "[31250, 17858, 22321, 22321, 8928, -22321, 4464, 22321]\n",
      "107142\n",
      "13392.75\n",
      "1725000\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.24\n",
      "[79.0, 84.0, 91.0, 95.0, 100.0, 105.0, 117.0, 122.0]\n",
      "[22321, 31250, 17858, 22321, 22321, 8928, -22321, 4464]\n",
      "107142\n",
      "13392.75\n",
      "1747321\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.46\n",
      "[78.0, 79.0, 84.0, 91.0, 95.0, 100.0, 105.0, 117.0]\n",
      "[4464, 22321, 31250, 17858, 22321, 22321, 8928, -22321]\n",
      "107142\n",
      "13392.75\n",
      "1751785\n",
      "Elapsed 0.0096 seconds, estimated FPS 103.65\n",
      "[82.0, 78.0, 79.0, 84.0, 91.0, 95.0, 100.0, 105.0]\n",
      "[-17857, 4464, 22321, 31250, 17858, 22321, 22321, 8928]\n",
      "111606\n",
      "13950.75\n",
      "1733928\n",
      "Elapsed 0.0058 seconds, estimated FPS 171.14\n",
      "[91.0, 82.0, 78.0, 79.0, 84.0, 91.0, 95.0, 100.0]\n",
      "[-40178, -17857, 4464, 22321, 31250, 17858, 22321, 22321]\n",
      "62500\n",
      "7812.5\n",
      "1693750\n",
      "Elapsed 0.0051 seconds, estimated FPS 196.07\n",
      "[106.0, 91.0, 82.0, 78.0, 79.0, 84.0, 91.0, 95.0]\n",
      "[-66965, -40178, -17857, 4464, 22321, 31250, 17858, 22321]\n",
      "-26786\n",
      "-3348.25\n",
      "1626785\n",
      "Elapsed 0.0051 seconds, estimated FPS 197.05\n",
      "[117.0, 106.0, 91.0, 82.0, 78.0, 79.0, 84.0, 91.0]\n",
      "[-4463, -66965, -40178, -17857, 4464, 22321, 31250, 17858]\n",
      "-53570\n",
      "-6696.25\n",
      "1577678\n",
      "Elapsed 0.0050 seconds, estimated FPS 200.92\n",
      "[126.0, 117.0, 106.0, 91.0, 82.0, 78.0, 79.0, 84.0]\n",
      "[40178, -4463, -66965, -40178, -17857, 4464, 22321, 31250]\n",
      "-31250\n",
      "-3906.25\n",
      "1537500\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.28\n",
      "[130.0, 126.0, 117.0, 106.0, 91.0, 82.0, 78.0, 79.0]\n",
      "[17858, 40178, -4463, -66965, -40178, -17857, 4464, 22321]\n",
      "-44642\n",
      "-5580.25\n",
      "1519642\n",
      "Elapsed 0.0050 seconds, estimated FPS 199.18\n",
      "[126.0, 130.0, 126.0, 117.0, 106.0, 91.0, 82.0, 78.0]\n",
      "[-17858, 17858, 40178, -4463, -66965, -40178, -17857, 4464]\n",
      "-84821\n",
      "-10602.625\n",
      "1537500\n",
      "Elapsed 0.0050 seconds, estimated FPS 198.03\n",
      "[123.0, 126.0, 130.0, 126.0, 117.0, 106.0, 91.0, 82.0]\n",
      "[-13392, -17858, 17858, 40178, -4463, -66965, -40178, -17857]\n",
      "-102677\n",
      "-12834.625\n",
      "1550892\n",
      "Elapsed 0.0052 seconds, estimated FPS 192.79\n",
      "[110.0, 123.0, 126.0, 130.0, 126.0, 117.0, 106.0, 91.0]\n",
      "[-40180, -13392, -17858, 17858, 40178, -4463, -66965, -40178]\n",
      "-125000\n",
      "-15625.0\n",
      "1608928\n",
      "Elapsed 0.0051 seconds, estimated FPS 196.73\n",
      "[94.0, 110.0, 123.0, 126.0, 130.0, 126.0, 117.0, 106.0]\n",
      "[71429, -40180, -13392, -17858, 17858, 40178, -4463, -66965]\n",
      "-13393\n",
      "-1674.125\n",
      "1680357\n",
      "Elapsed 0.0055 seconds, estimated FPS 180.52\n",
      "[83.0, 94.0, 110.0, 123.0, 126.0, 130.0, 126.0, 117.0]\n",
      "[49107, 71429, -40180, -13392, -17858, 17858, 40178, -4463]\n",
      "102679\n",
      "12834.875\n",
      "1729464\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.01\n",
      "[67.0, 83.0, 94.0, 110.0, 123.0, 126.0, 130.0, 126.0]\n",
      "[71428, 49107, 71429, -40180, -13392, -17858, 17858, 40178]\n",
      "178570\n",
      "22321.25\n",
      "1800892\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.28\n",
      "[55.0, 67.0, 83.0, 94.0, 110.0, 123.0, 126.0, 130.0]\n",
      "[53572, 71428, 49107, 71429, -40180, -13392, -17858, 17858]\n",
      "191964\n",
      "23995.5\n",
      "1854464\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.01\n",
      "[48.0, 55.0, 67.0, 83.0, 94.0, 110.0, 123.0, 126.0]\n",
      "[31250, 53572, 71428, 49107, 71429, -40180, -13392, -17858]\n",
      "205356\n",
      "25669.5\n",
      "1885714\n",
      "Elapsed 0.0062 seconds, estimated FPS 161.77\n",
      "[43.0, 48.0, 55.0, 67.0, 83.0, 94.0, 110.0, 123.0]\n",
      "[22321, 31250, 53572, 71428, 49107, 71429, -40180, -13392]\n",
      "245535\n",
      "30691.875\n",
      "1908035\n",
      "Elapsed 0.0065 seconds, estimated FPS 154.80\n",
      "[38.0, 43.0, 48.0, 55.0, 67.0, 83.0, 94.0, 110.0]\n",
      "[22322, 22321, 31250, 53572, 71428, 49107, 71429, -40180]\n",
      "281249\n",
      "35156.125\n",
      "1930357\n",
      "Elapsed 0.0063 seconds, estimated FPS 158.28\n",
      "[39.0, 38.0, 43.0, 48.0, 55.0, 67.0, 83.0, 94.0]\n",
      "[-4465, 22322, 22321, 31250, 53572, 71428, 49107, 71429]\n",
      "316964\n",
      "39620.5\n",
      "1925892\n",
      "Elapsed 0.0059 seconds, estimated FPS 169.30\n",
      "[50.0, 39.0, 38.0, 43.0, 48.0, 55.0, 67.0, 83.0]\n",
      "[-49107, -4465, 22322, 22321, 31250, 53572, 71428, 49107]\n",
      "196428\n",
      "24553.5\n",
      "1876785\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.88\n",
      "[56.0, 50.0, 39.0, 38.0, 43.0, 48.0, 55.0, 67.0]\n",
      "[-26785, -49107, -4465, 22322, 22321, 31250, 53572, 71428]\n",
      "120536\n",
      "15067.0\n",
      "1850000\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.10\n",
      "[59.0, 56.0, 50.0, 39.0, 38.0, 43.0, 48.0, 55.0]\n",
      "[-13393, -26785, -49107, -4465, 22322, 22321, 31250, 53572]\n",
      "35715\n",
      "4464.375\n",
      "1836607\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.54\n",
      "[69.0, 59.0, 56.0, 50.0, 39.0, 38.0, 43.0, 48.0]\n",
      "[-44643, -13393, -26785, -49107, -4465, 22322, 22321, 31250]\n",
      "-62500\n",
      "-7812.5\n",
      "1791964\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.17\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[74.0, 69.0, 59.0, 56.0, 50.0, 39.0, 38.0, 43.0]\n",
      "[-22322, -44643, -13393, -26785, -49107, -4465, 22322, 22321]\n",
      "-116072\n",
      "-14509.0\n",
      "1769642\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.18\n",
      "[79.0, 74.0, 69.0, 59.0, 56.0, 50.0, 39.0, 38.0]\n",
      "[-22321, -22322, -44643, -13393, -26785, -49107, -4465, 22322]\n",
      "-160714\n",
      "-20089.25\n",
      "1747321\n",
      "Elapsed 0.0057 seconds, estimated FPS 176.31\n",
      "[74.0, 79.0, 74.0, 69.0, 59.0, 56.0, 50.0, 39.0]\n",
      "[22321, -22321, -22322, -44643, -13393, -26785, -49107, -4465]\n",
      "-160715\n",
      "-20089.375\n",
      "1769642\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.29\n",
      "[71.0, 74.0, 79.0, 74.0, 69.0, 59.0, 56.0, 50.0]\n",
      "[13393, 22321, -22321, -22322, -44643, -13393, -26785, -49107]\n",
      "-142857\n",
      "-17857.125\n",
      "1783035\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.71\n",
      "[69.0, 71.0, 74.0, 79.0, 74.0, 69.0, 59.0, 56.0]\n",
      "[8929, 13393, 22321, -22321, -22322, -44643, -13393, -26785]\n",
      "-84821\n",
      "-10602.625\n",
      "1791964\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.44\n",
      "[60.0, 69.0, 71.0, 74.0, 79.0, 74.0, 69.0, 59.0]\n",
      "[40178, 8929, 13393, 22321, -22321, -22322, -44643, -13393]\n",
      "-17858\n",
      "-2232.25\n",
      "1832142\n",
      "Elapsed 0.0059 seconds, estimated FPS 168.08\n",
      "[52.0, 60.0, 69.0, 71.0, 74.0, 79.0, 74.0, 69.0]\n",
      "[35715, 40178, 8929, 13393, 22321, -22321, -22322, -44643]\n",
      "31250\n",
      "3906.25\n",
      "1867857\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.85\n",
      "[43.0, 52.0, 60.0, 69.0, 71.0, 74.0, 79.0, 74.0]\n",
      "[40178, 35715, 40178, 8929, 13393, 22321, -22321, -22322]\n",
      "116071\n",
      "14508.875\n",
      "1908035\n",
      "Elapsed 0.0064 seconds, estimated FPS 155.40\n",
      "[40.0, 43.0, 52.0, 60.0, 69.0, 71.0, 74.0, 79.0]\n",
      "[13393, 40178, 35715, 40178, 8929, 13393, 22321, -22321]\n",
      "151786\n",
      "18973.25\n",
      "1921428\n",
      "Elapsed 0.0064 seconds, estimated FPS 155.75\n",
      "[32.0, 40.0, 43.0, 52.0, 60.0, 69.0, 71.0, 74.0]\n",
      "[35714, 13393, 40178, 35715, 40178, 8929, 13393, 22321]\n",
      "209821\n",
      "26227.625\n",
      "1957142\n",
      "Elapsed 0.0064 seconds, estimated FPS 156.88\n",
      "[37.0, 32.0, 40.0, 43.0, 52.0, 60.0, 69.0, 71.0]\n",
      "[-22321, 35714, 13393, 40178, 35715, 40178, 8929, 13393]\n",
      "165179\n",
      "20647.375\n",
      "1934821\n",
      "Elapsed 0.0060 seconds, estimated FPS 166.44\n",
      "[31.0, 37.0, 32.0, 40.0, 43.0, 52.0, 60.0, 69.0]\n",
      "[26786, -22321, 35714, 13393, 40178, 35715, 40178, 8929]\n",
      "178572\n",
      "22321.5\n",
      "1961607\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.63\n",
      "[42.0, 31.0, 37.0, 32.0, 40.0, 43.0, 52.0, 60.0]\n",
      "[-49107, 26786, -22321, 35714, 13393, 40178, 35715, 40178]\n",
      "120536\n",
      "15067.0\n",
      "1912500\n",
      "Elapsed 0.0059 seconds, estimated FPS 170.11\n",
      "[49.0, 42.0, 31.0, 37.0, 32.0, 40.0, 43.0, 52.0]\n",
      "[-31250, -49107, 26786, -22321, 35714, 13393, 40178, 35715]\n",
      "49108\n",
      "6138.5\n",
      "1881250\n",
      "Elapsed 0.0056 seconds, estimated FPS 178.26\n",
      "[51.0, 49.0, 42.0, 31.0, 37.0, 32.0, 40.0, 43.0]\n",
      "[-8929, -31250, -49107, 26786, -22321, 35714, 13393, 40178]\n",
      "4464\n",
      "558.0\n",
      "1872321\n",
      "Elapsed 0.0058 seconds, estimated FPS 172.83\n",
      "[59.0, 51.0, 49.0, 42.0, 31.0, 37.0, 32.0, 40.0]\n",
      "[-35714, -8929, -31250, -49107, 26786, -22321, 35714, 13393]\n",
      "-71428\n",
      "-8928.5\n",
      "1836607\n",
      "Elapsed 0.0057 seconds, estimated FPS 174.68\n",
      "[64.0, 59.0, 51.0, 49.0, 42.0, 31.0, 37.0, 32.0]\n",
      "[-22322, -35714, -8929, -31250, -49107, 26786, -22321, 35714]\n",
      "-107143\n",
      "-13392.875\n",
      "1814285\n",
      "Elapsed 0.0066 seconds, estimated FPS 152.47\n",
      "[65.0, 64.0, 59.0, 51.0, 49.0, 42.0, 31.0, 37.0]\n",
      "[-4464, -22322, -35714, -8929, -31250, -49107, 26786, -22321]\n",
      "-147321\n",
      "-18415.125\n",
      "1809821\n",
      "Elapsed 0.0056 seconds, estimated FPS 177.88\n",
      "[64.0, 65.0, 64.0, 59.0, 51.0, 49.0, 42.0, 31.0]\n",
      "[4464, -4464, -22322, -35714, -8929, -31250, -49107, 26786]\n",
      "-120536\n",
      "-15067.0\n",
      "1814285\n",
      "Elapsed 0.0057 seconds, estimated FPS 175.33\n",
      "[61.0, 64.0, 65.0, 64.0, 59.0, 51.0, 49.0, 42.0]\n",
      "[13393, 4464, -4464, -22322, -35714, -8929, -31250, -49107]\n",
      "-133929\n",
      "-16741.125\n",
      "1827678\n",
      "Elapsed 0.0056 seconds, estimated FPS 179.90\n",
      "[58.0, 61.0, 64.0, 65.0, 64.0, 59.0, 51.0, 49.0]\n",
      "[13393, 13393, 4464, -4464, -22322, -35714, -8929, -31250]\n",
      "-71429\n",
      "-8928.625\n",
      "1841071\n",
      "Elapsed 0.0061 seconds, estimated FPS 163.52\n",
      "[52.0, 58.0, 61.0, 64.0, 65.0, 64.0, 59.0, 51.0]\n",
      "[26786, 13393, 13393, 4464, -4464, -22322, -35714, -8929]\n",
      "-13393\n",
      "-1674.125\n",
      "1867857\n",
      "Elapsed 0.0104 seconds, estimated FPS 96.59\n",
      "[49.0, 52.0, 58.0, 61.0, 64.0, 65.0, 64.0, 59.0]\n",
      "[13393, 26786, 13393, 13393, 4464, -4464, -22322, -35714]\n",
      "8929\n",
      "1116.125\n",
      "1881250\n",
      "Elapsed 0.0060 seconds, estimated FPS 167.42\n",
      "[43.0, 49.0, 52.0, 58.0, 61.0, 64.0, 65.0, 64.0]\n",
      "[26785, 13393, 26786, 13393, 13393, 4464, -4464, -22322]\n",
      "71428\n",
      "8928.5\n",
      "1908035\n",
      "Elapsed 0.0065 seconds, estimated FPS 153.99\n",
      "[38.0, 43.0, 49.0, 52.0, 58.0, 61.0, 64.0, 65.0]\n",
      "[22322, 26785, 13393, 26786, 13393, 13393, 4464, -4464]\n",
      "116072\n",
      "14509.0\n",
      "1930357\n",
      "Elapsed 0.0062 seconds, estimated FPS 160.34\n",
      "[-520, 38.0, 43.0, 49.0, 52.0, 58.0, 61.0, 64.0]\n",
      "[169643, 22322, 26785, 13393, 26786, 13393, 13393, 4464]\n",
      "290179\n",
      "36272.375\n",
      "2100000\n",
      "Elapsed 0.0056 seconds, estimated FPS 180.03\n",
      "[23.0, -520, 38.0, 43.0, 49.0, 52.0, 58.0, 61.0]\n",
      "[-102679, 169643, 22322, 26785, 13393, 26786, 13393, 13393]\n",
      "183036\n",
      "22879.5\n",
      "1997321\n",
      "Elapsed 0.0060 seconds, estimated FPS 165.95\n"
     ]
    }
   ],
   "source": [
    "t = threading.Thread(target=main_loop)\n",
    "t.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''plt.imshow(I)'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-2bb2f3d52ec1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mL\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"raw\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"filtered\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m300\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "'''plt.plot(L, label=\"raw\")\n",
    "plt.plot(Lf, label=\"filtered\")\n",
    "plt.ylim([0, 300])\n",
    "plt.legend()'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'camera' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-2935dfd9e3ee>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcamera\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'camera' is not defined"
     ]
    }
   ],
   "source": [
    "camera.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pwm0.duty_cycle = 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pwm import PWM\n",
    "\n",
    "pwm0 = PWM(0)\n",
    "\n",
    "pwm0.duty_cycle = 1000000\n",
    "\n",
    "pwm0.period = 20000000\n",
    "\n",
    "pwm0.enable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
./TrackDetection.ipynb0000644000175000017500000101174713437642702014246 0ustar  pipi00000000000000{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import skimage as ski\n",
    "\n",
    "from scipy.signal import find_peaks, butter, filtfilt\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the sample image\n",
    "\n",
    "I = ski.io.imread(\"track.jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x6ce43d50>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2464, 3280, 3)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the image dimensions in pixels\n",
    "\n",
    "I.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Conversion to gray\n",
    "Ibw = ski.color.rgb2gray(I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Since the image has a black line on a white background \n",
    "# we invert the image by substracting it from its maximum value.\n",
    "# We also select a smaller region of interest\n",
    "\n",
    "ROI = Ibw.max() - Ibw[1350:1400, 1000:3000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.20534235294117642, 1.0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the minimum and the maximum values\n",
    "\n",
    "ROI.min(), ROI.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x6b68bff0>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select the 25th row in the image for line detection\n",
    "L = ROI[25]\n",
    "\n",
    "# Plot the intensities across this row\n",
    "plt.plot(L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([   4,    8,   10,   16,   24,   30,   36,   44,   46,   56,   64,\n",
       "          69,   73,   77,   81,   85,   88,   90,   97,   99,  102,  108,\n",
       "         111,  120,  123,  127,  137,  141,  148,  150,  152,  155,  164,\n",
       "         166,  172,  176,  180,  182,  184,  187,  190,  199,  209,  212,\n",
       "         224,  229,  232,  238,  243,  246,  250,  252,  256,  264,  267,\n",
       "         272,  279,  286,  291,  306,  309,  312,  315,  318,  320,  323,\n",
       "         326,  332,  335,  338,  341,  352,  355,  357,  365,  370,  376,\n",
       "         380,  392,  396,  400,  406,  408,  414,  417,  420,  425,  442,\n",
       "         449,  465,  475,  478,  484,  489,  492,  494,  498,  504,  507,\n",
       "         522,  530,  536,  538,  545,  556,  559,  567,  572,  579,  583,\n",
       "         586,  589,  595,  601,  605,  610,  616,  623,  626,  641,  647,\n",
       "         652,  654,  657,  660,  664,  666,  669,  672,  683,  688,  693,\n",
       "         711,  721,  734,  737,  739,  745,  747,  751,  754,  761,  764,\n",
       "         769,  772,  778,  783,  786,  794,  806,  816,  819,  828,  830,\n",
       "         834,  837,  844,  850,  853,  860,  877,  894,  896,  899,  903,\n",
       "         907,  912,  919,  934,  938,  941,  962,  978,  982,  987,  990,\n",
       "         994,  999, 1002, 1005, 1008, 1017, 1023, 1027, 1040, 1048, 1063,\n",
       "        1066, 1072, 1076, 1085, 1087, 1092, 1096, 1111, 1125, 1134, 1138,\n",
       "        1148, 1151, 1156, 1161, 1166, 1172, 1180, 1184, 1186, 1192, 1196,\n",
       "        1200, 1203, 1206, 1215, 1217, 1223, 1225, 1233, 1237, 1241, 1244,\n",
       "        1250, 1261, 1264, 1270, 1273, 1279, 1283, 1287, 1290, 1293, 1296,\n",
       "        1301, 1304, 1308, 1310, 1313, 1315, 1317, 1323, 1327, 1330, 1334,\n",
       "        1338, 1341, 1346, 1350, 1355, 1358, 1365, 1369, 1371, 1374, 1378,\n",
       "        1381, 1394, 1401, 1404, 1407, 1410, 1418, 1422, 1426, 1431, 1433,\n",
       "        1438, 1440, 1444, 1449, 1453, 1460, 1464, 1467, 1471, 1473, 1477,\n",
       "        1485, 1491, 1493, 1498, 1500, 1504, 1511, 1519, 1525, 1528, 1531,\n",
       "        1535, 1538, 1544, 1549, 1555, 1558, 1564, 1568, 1577, 1581, 1589,\n",
       "        1593, 1596, 1601, 1606, 1610, 1616, 1620, 1623, 1626, 1634, 1639,\n",
       "        1644, 1646, 1652, 1658, 1662, 1665, 1668, 1673, 1677, 1682, 1686,\n",
       "        1690, 1696, 1699, 1705, 1707, 1710, 1714, 1717, 1721, 1723, 1728,\n",
       "        1732, 1735, 1738, 1740, 1746, 1753, 1755, 1758, 1762, 1765, 1769,\n",
       "        1774, 1779, 1784, 1787, 1790, 1794, 1799, 1807, 1810, 1816, 1819,\n",
       "        1824, 1827, 1833, 1836, 1840, 1848, 1856, 1858, 1861, 1865, 1868,\n",
       "        1884, 1886, 1891, 1902, 1905, 1907, 1909, 1913, 1916, 1921, 1924,\n",
       "        1930, 1933, 1936, 1942, 1948, 1955, 1958, 1967, 1971, 1976, 1978,\n",
       "        1982, 1985, 1989, 1992, 1995], dtype=int32),\n",
       " {'peak_heights': array([0.91350235, 0.90427529, 0.90289137, 0.86258941, 0.87827569,\n",
       "         0.86120549, 0.80071529, 0.79933137, 0.79933137, 0.80071529,\n",
       "         0.76542118, 0.91937333, 0.92578784, 0.93783529, 0.93783529,\n",
       "         0.95352157, 0.97312941, 0.97115725, 0.95352157, 0.95352157,\n",
       "         0.96136471, 0.95547098, 0.96528627, 0.95716039, 0.95744314,\n",
       "         0.95352157, 0.9496    , 0.94401176, 0.94654941, 0.94849882,\n",
       "         0.95242039, 0.94065569, 0.71071961, 0.70819686, 0.71856275,\n",
       "         0.72918863, 0.70819686, 0.71464118, 0.71464118, 0.71856275,\n",
       "         0.72780471, 0.99583333, 0.94544824, 0.94990549, 0.97566706,\n",
       "         0.96559176, 0.96754118, 0.95969804, 0.9641851 , 0.96222078,\n",
       "         0.95744314, 0.95969804, 0.97538431, 0.87931725, 0.86755255,\n",
       "         0.91517686, 0.70339725, 0.66165882, 0.64596471, 0.94654941,\n",
       "         0.94206235, 0.96222078, 0.95577647, 0.96557686, 0.97342   ,\n",
       "         0.96222078, 0.96949843, 0.96557686, 0.96557686, 0.95829922,\n",
       "         0.96222078, 0.91320471, 0.91712627, 0.93224706, 0.73167373,\n",
       "         0.69302353, 0.71263137, 0.68518039, 0.93084824, 0.97006392,\n",
       "         0.96949843, 0.96614235, 0.96614235, 0.96614235, 0.96614235,\n",
       "         0.97398549, 0.97398549, 0.95439255, 0.74430941, 0.78435843,\n",
       "         0.91517686, 0.94598392, 0.9616702 , 0.97315216, 0.96559176,\n",
       "         0.96222078, 0.97006392, 0.97342   , 0.9518549 , 0.94654941,\n",
       "         0.77735647, 0.70814431, 0.69809882, 0.83956588, 0.87878157,\n",
       "         0.89838941, 0.93029765, 0.95047098, 0.9616702 , 0.95382706,\n",
       "         0.9616702 , 0.95382706, 0.78162039, 0.8871902 , 0.90623255,\n",
       "         0.83956588, 0.7952898 , 0.83115725, 0.81547098, 0.88859686,\n",
       "         0.92164392, 0.94320118, 0.94712275, 0.94881216, 0.96138745,\n",
       "         0.96280902, 0.96138745, 0.94570118, 0.96559176, 0.90509373,\n",
       "         0.91407569, 0.84013137, 0.78130784, 0.86366078, 0.95888745,\n",
       "         0.96280902, 0.96280902, 0.97457373, 0.97065216, 0.96056902,\n",
       "         0.9616702 , 0.8219302 , 0.87037294, 0.93478471, 0.93311804,\n",
       "         0.80370627, 0.76951333, 0.75607412, 0.81995804, 0.89838941,\n",
       "         0.94096118, 0.94488275, 0.96223569, 0.96056902, 0.95439255,\n",
       "         0.94880431, 0.7255498 , 0.91269176, 0.91604784, 0.74879647,\n",
       "         0.79921137, 0.9275149 , 0.93535804, 0.94712275, 0.95496588,\n",
       "         0.95076157, 0.95860471, 0.96280902, 0.9135102 , 0.91743176,\n",
       "         0.85525216, 0.76252549, 0.93870627, 0.95047098, 0.95047098,\n",
       "         0.95439255, 0.94990549, 0.94849882, 0.94598392, 0.94654941,\n",
       "         0.95439255, 0.77937333, 0.89308392, 0.83956588, 0.71015412,\n",
       "         0.72640588, 0.92584039, 0.93870627, 0.94488275, 0.96223569,\n",
       "         0.94262784, 0.95047098, 0.94880431, 0.94544824, 0.89308392,\n",
       "         0.67093765, 0.6852251 , 0.6152102 , 0.93311804, 0.91853294,\n",
       "         0.95831412, 0.96951333, 0.98127804, 0.99219451, 0.89054627,\n",
       "         0.89614235, 0.89390235, 0.90006392, 0.89222078, 0.8989251 ,\n",
       "         0.89222078, 0.90284667, 0.91853294, 0.92302   , 0.91656078,\n",
       "         0.91263922, 0.92694157, 0.91656078, 0.91656078, 0.91598745,\n",
       "         0.92496941, 0.9137702 , 0.90030118, 0.90814431, 0.90814431,\n",
       "         0.9087098 , 0.90814431, 0.89245804, 0.90030118, 0.90030118,\n",
       "         0.9137702 , 0.90030118, 0.90200549, 0.90928314, 0.89808392,\n",
       "         0.89416235, 0.89416235, 0.90030118, 0.89469804, 0.90814431,\n",
       "         0.91206588, 0.91990902, 0.91430588, 0.90646275, 0.91430588,\n",
       "         0.91430588, 0.91822745, 0.89861961, 0.91263922, 0.90087451,\n",
       "         0.90144   , 0.92048235, 0.91656078, 0.90087451, 0.91516196,\n",
       "         0.89833686, 0.90479608, 0.89861961, 0.90479608, 0.91656078,\n",
       "         0.91038431, 0.90087451, 0.90087451, 0.90087451, 0.91263922,\n",
       "         0.91656078, 0.90871765, 0.90087451, 0.89695294, 0.90871765,\n",
       "         0.90871765, 0.90479608, 0.91038431, 0.90928314, 0.92496941,\n",
       "         0.94065569, 0.92889098, 0.93281255, 0.92496941, 0.92496941,\n",
       "         0.94849882, 0.92889098, 0.93281255, 0.93337804, 0.93281255,\n",
       "         0.93281255, 0.93673412, 0.93673412, 0.92889098, 0.92889098,\n",
       "         0.94401176, 0.9518549 , 0.94793333, 0.94401176, 0.93616863,\n",
       "         0.93616863, 0.9518549 , 0.94793333, 0.95969804, 0.95577647,\n",
       "         0.95969804, 0.97146275, 0.96361961, 0.96361961, 0.95354431,\n",
       "         0.96361961, 0.96222078, 0.97006392, 0.9857502 , 0.9806898 ,\n",
       "         0.97676824, 0.9806898 , 0.98012431, 0.97734157, 0.98012431,\n",
       "         0.98404588, 0.98095765, 0.97703608, 0.97647059, 0.98431373,\n",
       "         0.98431373, 0.97647059, 0.99272235, 0.99551294, 0.99607843,\n",
       "         0.98823529, 0.97707373, 0.79379647, 0.79939961, 0.8265302 ,\n",
       "         0.83907569, 0.81048588, 0.83065922, 0.82617216, 0.81524078,\n",
       "         0.74715255, 0.74938471, 0.75722784, 0.74210706, 0.73034235,\n",
       "         0.71857765, 0.70681294, 0.70376235, 0.63854706, 0.67552275,\n",
       "         0.63603216, 0.6198102 , 0.57950824, 0.72033451, 0.66935412,\n",
       "         0.93597608, 0.90233373, 0.92948706, 0.9350902 , 0.94096118,\n",
       "         0.95301647, 0.94490549, 0.83771373, 0.96507882, 0.94882706,\n",
       "         0.92194157, 0.93457725, 0.9055349 , 0.57443294, 0.5788902 ,\n",
       "         0.57945569, 0.97647059, 0.96835961, 0.96527137, 0.96722078,\n",
       "         0.98823529, 0.98039216, 0.96862745, 0.97647059, 0.98431373,\n",
       "         0.96862745, 0.97647059, 0.97311451, 0.98095765, 0.98095765,\n",
       "         0.98095765, 0.97871765, 0.97479608, 0.97087451, 0.97284667,\n",
       "         0.98627804, 0.97087451, 0.97871765, 0.9689251 , 0.97284667])})"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Due to the noise in the image the algorithm finds many peaks heigher than 0.5\n",
    "find_peaks(L, height=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "\n",
    "# Wn = 0.02, the cut-off frequency, acceptable values are from 0 to 1\n",
    "b, a = butter(3, 0.02)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter the selected row in the image using the above filter coefficients a, b\n",
    "Lf = filtfilt(b, a, L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x6b703470>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the pixel intensities along the selected row\n",
    "plt.plot(L, label=\"raw\")\n",
    "plt.plot(Lf, label=\"filtered\")\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 111,  238,  334,  414,  501,  584,  660,  749,  824,  912,  997,\n",
       "        1083, 1204, 1351, 1676, 1839, 1956], dtype=int32),\n",
       " {'peak_heights': array([0.97083364, 0.90064222, 0.87884636, 0.88175569, 0.86997416,\n",
       "         0.86942543, 0.8707533 , 0.88413459, 0.85499108, 0.86793307,\n",
       "         0.86475288, 0.86481753, 0.9093664 , 0.90302439, 0.98459633,\n",
       "         0.85515233, 0.9922581 ])})"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the two peaks in the filtered data\n",
    "find_peaks(Lf, height=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6.08 ms ± 15.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "## Estimate the run time of the line detection algorithm\n",
    "\n",
    "# Select the 25th row in the image for line detection\n",
    "L = ROI[25]\n",
    "\n",
    "# To filter the noise in the image we use a 3rd order Butterworth filter\n",
    "b, a = butter(3, 0.02)\n",
    "\n",
    "# Smooth the transitions so we can detect the peaks \n",
    "Lf = filtfilt(b, a, L)\n",
    "\n",
    "# Find peaks which are higher than 0.5\n",
    "p = find_peaks(Lf, height=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}