{ "cells": [ { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "backend = widget\n" ] } ], "source": [ "import time\n", "\n", "#%matplotlib notebook\n", "%matplotlib widget\n", "\n", "\n", "import matplotlib.pyplot as plt\n", "print(\"backend = \",plt.get_backend()) #prints \"widget\"\n", "\n", "from matplotlib.animation import FuncAnimation\n", "from datetime import datetime\n", "import matplotlib.dates as mdates\n", "from collections import deque\n", "import numpy as np\n", "import os\n", "import serial\n", "import socket\n", "import re\n", "\n", "PORT = \"COM43\"\n", "PORT = \"/dev/ttytDAN\"\n", "#PORT = \"/tmp/ttyJupyter\"\n", "\n", "# How many sensor samples we want to store\n", "HISTORY_SIZE = 2500\n", "\n", "# Pause re-sampling the sensor and drawing for INTERVAL seconds\n", "INTERVAL = 0.01\n", "\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sample time: 2026-04-28 13:48:11\n", "Opened /dev/ttytDAN\n", "[0.0, 0.0, 8192.0, 0.0, 0.0, 0.0, -176.0, 312.0, 424.0]\n", "[0.0, 0.0, 8192.0, 0.0, 0.0, 0.0, -180.0, 298.0, 441.0]\n", "[0.0, 0.0, 8192.0, 0.0, 0.0, 0.0, -175.0, 299.0, 437.0]\n", "[0.0, 0.0, 8192.0, 0.0, 0.0, 0.0, -180.0, 304.0, 458.0]\n", "[0.0, 0.0, 8192.0, 0.0, 0.0, 0.0, -182.0, 300.0, 427.0]\n" ] } ], "source": [ "now = datetime.now()\n", "serialport = None\n", "\n", "def get_imu_data():\n", " global serialport\n", " if not serialport:\n", " # open serial port\n", " serialport = serial.Serial(PORT, 115200, timeout=0.1)\n", " # check which port was really used\n", " print(\"Opened\", serialport.name)\n", " # Flush input\n", " time.sleep(3)\n", " serialport.readline()\n", "\n", " # Poll the serial port\n", " line = str(serialport.readline(), 'utf-8')\n", " if not line:\n", " return None\n", " #print(line)\n", " #if not \"Uni:\" in line:\n", " # return None\n", " if not \"Raw:\" in line:\n", " return None\n", " #vals = line.replace(\"Uni:\", \"\").strip().split(',')\n", " vals = line.replace(\"Raw:\", \"\").strip().split(',')\n", " #print(vals)\n", " if len(vals) != 9:\n", " return None\n", " try:\n", " vals = [float(i) for i in vals]\n", " except ValueError:\n", " return None\n", " #print(vals)\n", " return vals\n", "# demonstrate capture works with a sample of 20 lines\n", "print(\"Sample time: \",now.strftime(\"%Y-%m-%d %H:%M:%S\"))\n", "for _ in range(5):\n", " print(get_imu_data())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Magnetometer data capture" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "After closing port and before starting.\n", "HOSTNAME: eos , PORT: /dev/ttytDAN\n", "Plotting time start: 2026-04-28 13:48:19\n", "Before show()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "18d570ab556e4834892b65fe6d786a64", "version_major": 2, "version_minor": 0 }, "image/png": 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/PebNmze8NjQ0FBER48ePj5dffjkuvPDCo86rrq6O6urq93h6AKAc3AE8w1VVVcWsWbOio6NjeG1oaCg6OjqiqanpqOMvvvjiePHFF6Orq2v48alPfSquueaa6Orq8tYuACTgDuAY0NraGosXL47Zs2fHnDlzYs2aNXH48OFYsmRJREQsWrQopk2bFu3t7VFTUxOXXHLJiPPPO++8iIij1gGAsUkAjgELFiyI/fv3x8qVK6O7uztmzpwZW7ZsGf7BkL1790ZFhZu9AMDvjSuKoij3EJx5+vr6oq6uLnp7e6O2trbc4wBwglzHc3NbCAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBOAYsXbt2pg+fXrU1NREY2NjbNu27ZjHrl+/PubOnRsTJkyICRMmRHNz8zseDwCMLQJwDNi4cWO0trZGW1tb7NixI2bMmBEtLS3xxhtvjHr81q1b4/rrr48f/ehH0dnZGQ0NDfHJT34yfvnLX5Z4cgCgHMYVRVGUewjencbGxrjiiivioYceioiIoaGhaGhoiFtvvTWWL1/+R88fHByMCRMmxEMPPRSLFi06rufs6+uLurq66O3tjdra2nc1PwCl5zqemzuAZ7iBgYHYvn17NDc3D69VVFREc3NzdHZ2Htff8eabb8Zbb70V73//+495TH9/f/T19Y14AABnJgF4hjtw4EAMDg5GfX39iPX6+vro7u4+rr/j9ttvj6lTp46IyD/U3t4edXV1w4+GhoZ3NTcAUD4CMLnVq1fHhg0b4umnn46amppjHrdixYro7e0dfuzbt6+EUwIA76Xx5R6Ad2fixIlRWVkZPT09I9Z7enpi8uTJ73ju/fffH6tXr44f/vCHcdlll73jsdXV1VFdXf2u5wUAys8dwDNcVVVVzJo1Kzo6OobXhoaGoqOjI5qamo553n333Rf33ntvbNmyJWbPnl2KUQGA04Q7gGNAa2trLF68OGbPnh1z5syJNWvWxOHDh2PJkiUREbFo0aKYNm1atLe3R0TEP/3TP8XKlSvjiSeeiOnTpw9/r+D73ve+eN/73le21wEAlIYAHAMWLFgQ+/fvj5UrV0Z3d3fMnDkztmzZMvyDIXv37o2Kiv+72fvNb34zBgYG4jOf+cyIv6etrS2+/OUvl3J0AKAMfA4gJ8XnRwGc2VzHc/M9gAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwDHiLVr18b06dOjpqYmGhsbY9u2be94/Pe+9724+OKLo6amJi699NLYvHlziSYFAMpNAI4BGzdujNbW1mhra4sdO3bEjBkzoqWlJd54441Rj3/hhRfi+uuvjxtvvDF27twZ8+fPj/nz58fPfvazEk8OAJTDuKIoinIPwbvT2NgYV1xxRTz00EMRETE0NBQNDQ1x6623xvLly486fsGCBXH48OH4wQ9+MLz28Y9/PGbOnBnr1q07rufs6+uLurq66O3tjdra2vfmhQBQMq7juY0v9wC8OwMDA7F9+/ZYsWLF8FpFRUU0NzdHZ2fnqOd0dnZGa2vriLWWlpZ45plnjvk8/f390d/fP/zn3t7eiPj9BQSAM8/b12/3gXISgGe4AwcOxODgYNTX149Yr6+vj927d496Tnd396jHd3d3H/N52tvb45577jlqvaGh4SSmBuB08T//8z9RV1dX7jEoMQHIcVmxYsWIu4YHDx6MD3zgA7F3714XjnfQ19cXDQ0NsW/fPm+xvAP7dHzs0/GxT8ent7c3zj///Hj/+99f7lEoAwF4hps4cWJUVlZGT0/PiPWenp6YPHnyqOdMnjz5hI6PiKiuro7q6uqj1uvq6lxgj0Ntba19Og726fjYp+Njn45PRYWfB83Iv/UzXFVVVcyaNSs6OjqG14aGhqKjoyOamppGPaepqWnE8RERzz333DGPBwDGFncAx4DW1tZYvHhxzJ49O+bMmRNr1qyJw4cPx5IlSyIiYtGiRTFt2rRob2+PiIjbbrstrr766njggQfiuuuuiw0bNsRPf/rTeOSRR8r5MgCAEhGAY8CCBQti//79sXLlyuju7o6ZM2fGli1bhn/QY+/evSNu8V955ZXxxBNPxF133RV33HFH/MVf/EU888wzcckllxz3c1ZXV0dbW9uobwvzf+zT8bFPx8c+HR/7dHzsU24+BxAAIBnfAwgAkIwABABIRgACACQjAAEAkhGAHNPatWtj+vTpUVNTE42NjbFt27Z3PP573/teXHzxxVFTUxOXXnppbN68uUSTlteJ7NP69etj7ty5MWHChJgwYUI0Nzf/0X0dK0706+ltGzZsiHHjxsX8+fNP7YCniRPdp4MHD8bSpUtjypQpUV1dHRdddFGK//ZOdJ/WrFkTH/rQh+Lss8+OhoaGWLZsWfzud78r0bSl9+Mf/zjmzZsXU6dOjXHjxr3j73p/29atW+NjH/tYVFdXxwc/+MF4/PHHT/mclFEBo9iwYUNRVVVVPPbYY8V//dd/FTfddFNx3nnnFT09PaMe/5Of/KSorKws7rvvvuKll14q7rrrruKss84qXnzxxRJPXlonuk833HBDsXbt2mLnzp3Frl27ir/5m78p6urqiv/+7/8u8eSldaL79LbXXnutmDZtWjF37tzi05/+dGmGLaMT3af+/v5i9uzZxbXXXls8//zzxWuvvVZs3bq16OrqKvHkpXWi+/Sd73ynqK6uLr7zne8Ur732WvHss88WU6ZMKZYtW1biyUtn8+bNxZ133lk89dRTRUQUTz/99Dsev2fPnuKcc84pWltbi5deeqn4xje+UVRWVhZbtmwpzcCUnABkVHPmzCmWLl06/OfBwcFi6tSpRXt7+6jHf/azny2uu+66EWuNjY3F3/7t357SOcvtRPfpDx05cqQ499xzi29/+9unasTTwsns05EjR4orr7yy+Na3vlUsXrw4RQCe6D5985vfLC644IJiYGCgVCOeFk50n5YuXVr85V/+5Yi11tbW4qqrrjqlc54ujicAv/SlLxUf/ehHR6wtWLCgaGlpOYWTUU7eAuYoAwMDsX379mhubh5eq6ioiObm5ujs7Bz1nM7OzhHHR0S0tLQc8/ix4GT26Q+9+eab8dZbb43pX8Z+svv0la98JSZNmhQ33nhjKcYsu5PZp+9///vR1NQUS5cujfr6+rjkkkti1apVMTg4WKqxS+5k9unKK6+M7du3D79NvGfPnti8eXNce+21JZn5TJDxGp6d3wTCUQ4cOBCDg4PDv0nkbfX19bF79+5Rz+nu7h71+O7u7lM2Z7mdzD79odtvvz2mTp161IV3LDmZfXr++efj0Ucfja6urhJMeHo4mX3as2dP/Md//Ed87nOfi82bN8err74aX/ziF+Ott96Ktra2UoxdciezTzfccEMcOHAgPvGJT0RRFHHkyJG45ZZb4o477ijFyGeEY13D+/r64re//W2cffbZZZqMU8UdQCiT1atXx4YNG+Lpp5+Ompqaco9z2jh06FAsXLgw1q9fHxMnTiz3OKe1oaGhmDRpUjzyyCMxa9asWLBgQdx5552xbt26co92Wtm6dWusWrUqHn744dixY0c89dRTsWnTprj33nvLPRqUjTuAHGXixIlRWVkZPT09I9Z7enpi8uTJo54zefLkEzp+LDiZfXrb/fffH6tXr44f/vCHcdlll53KMcvuRPfp5z//ebz++usxb9684bWhoaGIiBg/fny8/PLLceGFF57aocvgZL6epkyZEmeddVZUVlYOr334wx+O7u7uGBgYiKqqqlM6czmczD7dfffdsXDhwvj85z8fERGXXnppHD58OG6++ea48847R/yu9KyOdQ2vra1192+M8lXPUaqqqmLWrFnR0dExvDY0NBQdHR3R1NQ06jlNTU0jjo+IeO655455/FhwMvsUEXHffffFvffeG1u2bInZs2eXYtSyOtF9uvjii+PFF1+Mrq6u4cenPvWpuOaaa6KrqysaGhpKOX7JnMzX01VXXRWvvvrqcCBHRLzyyisxZcqUMRl/ESe3T2+++eZRkfd2NBdFceqGPYNkvIanV+6fQuH0tGHDhqK6urp4/PHHi5deeqm4+eabi/POO6/o7u4uiqIoFi5cWCxfvnz4+J/85CfF+PHji/vvv7/YtWtX0dbWluZjYE5kn1avXl1UVVUVTz75ZPGrX/1q+HHo0KFyvYSSONF9+kNZfgr4RPdp7969xbnnnlv83d/9XfHyyy8XP/jBD4pJkyYVX/3qV8v1EkriRPepra2tOPfcc4t//dd/Lfbs2VP8+7//e3HhhRcWn/3sZ8v1Ek65Q4cOFTt37ix27txZRETx4IMPFjt37ix+8YtfFEVRFMuXLy8WLlw4fPzbHwPzj//4j8WuXbuKtWvX+hiYMU4Ackzf+MY3ivPPP7+oqqoq5syZU/znf/7n8D+7+uqri8WLF484/rvf/W5x0UUXFVVVVcVHP/rRYtOmTSWeuDxOZJ8+8IEPFBFx1KOtra30g5fYiX49/f+yBGBRnPg+vfDCC0VjY2NRXV1dXHDBBcXXvva14siRIyWeuvROZJ/eeuut4stf/nJx4YUXFjU1NUVDQ0PxxS9+sfjf//3f0g9eIj/60Y9Gvda8vS+LFy8urr766qPOmTlzZlFVVVVccMEFxT//8z+XfG5KZ1xRuP8NAJCJ7wEEAEhGAAIAJCMAAQCSEYAAAMkIQACAZAQgAEAyAhAAIBkBCACQjAAEAEhGAAIAJCMAAQCSEYAAAMkIQACAZAQgAEAyAhAAIBkBCACQjAAEAEhGAAIAJCMAAQCSEYAAAMkIQACAZAQgAEAyAhAAIBkBCACQjAAEAEhGAAIAJCMAAQCSEYAAAMkIQACAZAQgAEAyAhAAIJn/B94+2opdFJXOAAAAAElFTkSuQmCC", "text/html": [ "\n", "
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\n", " Figure\n", "
\n", " \n", "
\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting time stopped (by user click or limit): 2026-04-28 13:48:19\n", "After show()\n", "After for i loop\n" ] } ], "source": [ "\n", "# Deque for axes\n", "mag_x = deque(maxlen=HISTORY_SIZE)\n", "mag_y = deque(maxlen=HISTORY_SIZE)\n", "mag_z = deque(maxlen=HISTORY_SIZE)\n", "\n", "fig, ax = plt.subplots(1, 1)\n", "ax.set_aspect(1)\n", "\n", "# close port in case its open\n", "if serialport:\n", " try:\n", " serialport.close()\n", " except NameError:\n", " pass\n", "print(\"After closing port and before starting.\")\n", "serialport = None\n", "anim = None\n", "\n", "def onClick(event):\n", " if anim:\n", " anim.event_source.stop()\n", "\n", "from datetime import datetime\n", "\n", "\n", "\n", "def animate(i):\n", " print(\"starting animate()\", i)\n", "\n", " for _ in range(i):\n", " ret = get_imu_data()\n", "\n", " if not ret:\n", " continue\n", "\n", " #print(\"MAG:\", ret[6:9])\n", "\n", " x, y, z = ret[6:9]\n", " mag_x.append(x)\n", " mag_y.append(y)\n", " mag_z.append(z)\n", "\n", " ax.cla()\n", " ax.set_aspect(1)\n", "\n", " ax.scatter(mag_x, mag_y, color='r')\n", " ax.scatter(mag_y, mag_z, color='g')\n", " ax.scatter(mag_z, mag_x, color='b')\n", "\n", " ax.set_title(f\"Mag samples: {len(mag_x)}\")\n", "\n", " if len(mag_x) == HISTORY_SIZE:\n", " anim.event_source.stop()\n", "\n", "#animate(0)\n", "\n", "fig.canvas.mpl_connect('button_press_event', onClick) \n", "anim = FuncAnimation(\n", " fig,\n", " animate,\n", " interval=100,\n", " cache_frame_data=False\n", ")\n", "#hostname = os.environ.get(\"HOSTNAME\") # does not work as Jupyter inherit a limited number of ENV variables\n", "hostname = socket.gethostname()\n", "#hostname = \"SUSPENDED\"\n", "print(\"HOSTNAME: \",hostname,\", PORT: \",PORT)\n", "print(\"Plotting time start: \", datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"))\n", "\n", "print(\"Before show()\")\n", "plt.show()\n", "print(\"Plotting time stopped (by user click or limit): \", datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"))\n", "print(\"After show()\")\n", "#anim\n", "#for i in range(2):\n", "# animate(i)\n", "\n", "print(\"After for i loop\")" ] }, { "cell_type": "raw", "metadata": { "scrolled": true }, "source": [ "min_x = min(mag_x)\n", "max_x = max(mag_x)\n", "min_y = min(mag_y)\n", "max_y = max(mag_y)\n", "min_z = min(mag_z)\n", "max_z = max(mag_z)\n", "\n", "print(\"X range: \", min_x, max_x)\n", "print(\"Y range: \", min_y, max_y)\n", "print(\"Z range: \", min_z, max_z)\n", "\n", "mag_calibration = [ (max_x + min_x) / 2, (max_y + min_y) / 2, (max_z + min_z) / 2]\n", "print(\"Final c userlibration in uTesla:\", mag_calibration)\n", "\n", "cal_mag_x = [x - mag_calibration[0] for x in mag_x]\n", "cal_mag_y = [y - mag_calibration[1] for y in mag_y]\n", "cal_mag_z = [z - mag_calibration[2] for z in mag_z]\n", "\n", "fig, ax = plt.subplots(1, 1)\n", "ax.set_aspect(1)\n", "\n", "# Clear all axis\n", "ax.cla()\n", "\n", "# Display the now calibrated data\n", "ax.scatter(cal_mag_x, cal_mag_y, color='r')\n", "ax.scatter(cal_mag_y, cal_mag_z, color='g')\n", "ax.scatter(cal_mag_z, cal_mag_x, color='b')\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Gyroscope offset calibration" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Put down the board and do not touch or move it!\n", "3...2...1...COLLECTING GYRO DATA\n", "Opened /dev/ttytDAN\n", "Gyro X range: 0.0 0.0\n", "Gyro Y range: 0.0 0.0\n", "Gyro Z range: 0.0 0.0\n", "Final calibration in rad/s: [0.0, 0.0, 0.0]\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "90098820a7df42229c092d2851cfdfa4", "version_major": 2, "version_minor": 0 }, 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", 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", 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