| 14,8 → 14,15 |
|---|
| "Uk\u00e1zka pou\u017eit\u00ed n\u00e1stroje IPython na manipulaci se senzorov\u00fdmi daty modulu IMU01A\n", |
| "=======\n", |
| "\n", |
| "P\u0159\u00edklad vyu\u017e\u00edv\u00e1 modulovou stavebnici MLAB a jej\u00ed knihovnu https://github.com/MLAB-project/MLAB-I2c-modules \n", |
| "P\u0159\u00edklad vyu\u017e\u00edv\u00e1 modulovou stavebnici MLAB a jej\u00ed knihovnu [pymlab](https://github.com/MLAB-project/MLAB-I2c-modules).\n", |
| "Sn\u00edma\u010d je k po\u010d\u00edta\u010di p\u0159ipojen\u00fd p\u0159es rozhradn\u00ed USB a data jsou vy\u010d\u00edt\u00e1na p\u0159es [I\u00b2C](http://wiki.mlab.cz/doku.php?id=cs:i2c)\n", |
| "\n", |
| "Pou\u017eit\u00fd akcelerometr [MMA8451Q](http://www.freescale.com/webapp/sps/site/prod_summary.jsp?code=MMA8451Q) m\u00e1 n\u00e1sleduj\u00edc\u00ed katalogov\u00e9 parametry: \n", |
| "\n", |
| "* \u00b12g/\u00b14g/\u00b18g dynamically selectable full-scale\n", |
| "* Output data rates (ODR) from 1.56 Hz to 800 Hz\n", |
| "* 99 \u03bcg/\u221aHz noise\n", |
| "\n", |
| "Zprovozn\u011bn\u00ed demo k\u00f3du\n", |
| "---------------------\n", |
| "\n", |
| 42,9 → 49,8 |
|---|
| "i2c-3\ti2c \ti915 gmbus dpc \tI2C adapter\r\n", |
| "i2c-4\ti2c \ti915 gmbus dpb \tI2C adapter\r\n", |
| "i2c-5\ti2c \ti915 gmbus dpd \tI2C adapter\r\n", |
| "i2c-6\ti2c \tDPDDC-C \tI2C adapter\r\n", |
| "i2c-7\ti2c \tDPDDC-D \tI2C adapter\r\n", |
| "i2c-8\ti2c \ti2c-tiny-usb at bus 001 device 005\tI2C adapter\r\n" |
| "i2c-6\ti2c \tDPDDC-B \tI2C adapter\r\n", |
| "i2c-7\ti2c \ti2c-tiny-usb at bus 001 device 007\tI2C adapter\r\n" |
| ] |
| } |
| ], |
| 77,7 → 83,7 |
|---|
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "port = 8" |
| "port = 7" |
| ], |
| "language": "python", |
| "metadata": {}, |
| 138,7 → 144,7 |
|---|
| "language": "python", |
| "metadata": {}, |
| "outputs": [], |
| "prompt_number": 8 |
| "prompt_number": 4 |
| }, |
| { |
| "cell_type": "markdown", |
| 166,7 → 172,7 |
|---|
| ] |
| } |
| ], |
| "prompt_number": 9 |
| "prompt_number": 5 |
| }, |
| { |
| "cell_type": "markdown", |
| 179,16 → 185,20 |
|---|
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "import sys\n", |
| "import time\n", |
| "from IPython.display import clear_output\n", |
| "\n", |
| "MEASUREMENTS = 1000\n", |
| "x = np.zeros(MEASUREMENTS)\n", |
| "y = np.zeros(MEASUREMENTS)\n", |
| "z = np.zeros(MEASUREMENTS)\n", |
| "\n", |
| "list_meas = []\n", |
| "# acc.route() V p\u0159\u00edpad\u011b v\u00edce \u010didel je pot\u0159eba ke ka\u017ed\u00e9mu p\u0159ed jeho pou\u017eit\u00edm nechat vyroutovat cesutu na sb\u011brnici.\n", |
| "\n", |
| "for n in range(MEASUREMENTS):\n", |
| " (x[n], y[n], z[n]) = acc.axes()\n", |
| " print( n, x[n], y[n], z[n])" |
| " clear_output()\n", |
| " (x, y, z) = acc.axes()\n", |
| " list_meas.append([x, y, z])\n", |
| " print (n, list_meas[n])\n", |
| " sys.stdout.flush()" |
| ], |
| "language": "python", |
| "metadata": {}, |
| 197,8014 → 207,22 |
|---|
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "(0, -0.81022499999999997, -0.54599999999999993, -0.26715)\n", |
| "(1, -0.83362499999999995, -0.52162500000000001, -0.26032499999999997)" |
| "(999, [0.038024999999999996, -0.00975, 0.966225])\n" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(2, -0.70297500000000002, -0.61327500000000001, -0.39487499999999998)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(3, -0.83996249999999995, -0.58694999999999997, -0.35489999999999999)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(4, -0.74246249999999991, -0.70199999999999996, -0.33052499999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(5, -0.51285000000000003, -0.83947499999999997, -0.30614999999999998)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(6, -0.058987499999999998, -0.95647499999999996, -0.14235)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(7, 0.25447500000000001, -0.84142499999999998, 0.011699999999999999)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(8, 0.70199999999999996, -0.64203749999999993, -0.071175000000000002)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(9, 0.90284999999999993, -0.16965, -0.047774999999999998)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(10, 1.0125374999999999, 0.084824999999999998, -0.14624999999999999)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(11, 0.92917499999999997, 0.244725, -0.1028625)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(12, 0.80291249999999992, 0.59670000000000001, -0.44264999999999999)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
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| "\n", |
| "(13, 0.57329999999999992, 0.77171249999999991, -0.4914)" |
| ] |
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| "\n", |
| "(14, 0.35197499999999998, 0.84532499999999999, -0.48067499999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(15, 0.10237499999999999, 0.92527499999999996, -0.40121249999999997)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(16, -0.086774999999999991, 0.90479999999999994, -0.312975)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
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| "\n", |
| "(17, -0.47872499999999996, 0.81461249999999996, -0.27689999999999998)" |
| ] |
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| "(21, -0.83460000000000001, -0.638625, -0.2457)" |
| ] |
| }, |
| { |
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| "text": [ |
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| ] |
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| { |
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| "stream": "stdout", |
| "text": [ |
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| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(24, -0.33344999999999997, -0.30419999999999997, -0.96914999999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(25, -0.39097499999999996, 0.075075000000000003, -0.82289999999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(26, -0.80145, 0.252525, -0.74002499999999993)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(27, -0.53576250000000003, 0.69029999999999991, -0.54794999999999994)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(28, -0.16574999999999998, 0.9204, -0.48701249999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(29, 0.2588625, 0.83752499999999996, -0.40462499999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(30, 0.65617499999999995, 0.61522500000000002, -0.34709999999999996)" |
| ] |
| }, |
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| "(31, 0.69419999999999993, 0.18817499999999998, -0.61181249999999998)" |
| ] |
| }, |
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| ] |
| }, |
| { |
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| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(34, 0.56940000000000002, -0.41827500000000001, -0.56940000000000002)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(35, 0.43290000000000001, -0.70492499999999991, -0.59572499999999995)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(36, 0.084824999999999998, -0.73904999999999998, -0.76439999999999997)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
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| "(37, -0.27299999999999996, -0.54599999999999993, -0.82192500000000002)" |
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| "(38, -0.47969999999999996, -0.46507499999999996, -0.70784999999999998)" |
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| }, |
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| "(40, -0.67079999999999995, -0.071175000000000002, -0.71954999999999991)" |
| ] |
| }, |
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| "(41, -0.76049999999999995, 0.21742499999999998, -0.70687499999999992)" |
| ] |
| }, |
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| "\n", |
| "(42, -0.64934999999999998, 0.35392499999999999, -0.80047499999999994)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(43, -0.57427499999999998, 0.357825, -0.83947499999999997)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(44, -0.43338749999999998, 0.17257499999999998, -1.0208249999999999)" |
| ] |
| }, |
| { |
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| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(45, -0.063375000000000001, 0.110175, -1.1456249999999999)" |
| ] |
| }, |
| { |
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| "stream": "stdout", |
| "text": [ |
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| "(46, 0.43290000000000001, 0.1794, -0.88139999999999996)" |
| ] |
| }, |
| { |
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| "text": [ |
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| "(47, 0.45581249999999995, 0.14722499999999999, -0.96524999999999994)" |
| ] |
| }, |
| { |
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| "text": [ |
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| "(48, 0.56745000000000001, 0.14527499999999999, -0.75074999999999992)" |
| ] |
| }, |
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| "text": [ |
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| "(49, 0.73904999999999998, 0.034124999999999996, -0.61814999999999998)" |
| ] |
| }, |
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| "(50, 0.84483749999999991, -0.012674999999999999, -0.41144999999999998)" |
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| }, |
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| "(51, 0.92771249999999994, -0.10627499999999999, -0.15989999999999999)" |
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| }, |
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| "(52, 0.96232499999999999, -0.11943749999999999, 0.067275000000000001)" |
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| "(53, 0.92917499999999997, -0.207675, 0.47774999999999995)" |
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| ] |
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| "(56, 0.268125, -0.37829999999999997, 0.83362499999999995)" |
| ] |
| }, |
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| }, |
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| ] |
| }, |
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| ] |
| }, |
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| }, |
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| }, |
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| "stream": "stdout", |
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| "\n", |
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| ] |
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| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(997, -0.28079999999999999, 0.86872499999999997, 0.03705)" |
| ] |
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| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(998, -0.40365000000000001, 0.81119999999999992, 0.33296249999999999)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n", |
| "(999, -0.51528750000000001, 0.53039999999999998, 0.71662499999999996)" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n" |
| ] |
| } |
| ], |
| "prompt_number": 72 |
| "prompt_number": 7 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "np.savez(\"calibration_data_set\", x=x, y=y, z=z)" |
| "np.savez(\"calibration_data_3Dset\", data=list_meas)" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [], |
| "prompt_number": 73 |
| "prompt_number": 8 |
| }, |
| { |
| "cell_type": "markdown", |
| 8264,49 → 282,142 |
|---|
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "std(p)" |
| "import scipy\n", |
| "from scipy import optimize\n", |
| "import calibration_utils\n", |
| "\n", |
| "sensor_ref = 9.81\n", |
| "sensor_res = 10\n", |
| "noise_window = 20\n", |
| "noise_threshold = 40" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [], |
| "prompt_number": 11 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "measurements = np.array(list_meas)" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [], |
| "prompt_number": 12 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "meas_median=scipy.median(scipy.array([scipy.linalg.norm(v) for v in measurements]))\n", |
| "noise_threshold = meas_median * 0.1\n", |
| "print noise_threshold\n", |
| "flt_meas, flt_idx = calibration_utils.filter_meas(measurements, noise_window, noise_threshold)\n", |
| "print(\"remaining \"+str(len(flt_meas))+\" after filtering\")" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "metadata": {}, |
| "output_type": "pyout", |
| "prompt_number": 9, |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "2.3585270827361722" |
| "0.0973014827316\n", |
| "remaining 703 after filtering" |
| ] |
| }, |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "\n" |
| ] |
| } |
| ], |
| "prompt_number": 9 |
| "prompt_number": 14 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "plt.plot(p)" |
| " p0 = calibration_utils.get_min_max_guess(flt_meas, sensor_ref)\n", |
| " cp0, np0 = calibration_utils.scale_measurements(flt_meas, p0)\n", |
| " print(\"initial guess : avg \"+str(np0.mean())+\" std \"+str(np0.std()))\n", |
| "\n", |
| " def err_func(p, meas, y):\n", |
| " cp, np = calibration_utils.scale_measurements(meas, p)\n", |
| " err = y*scipy.ones(len(meas)) - np\n", |
| " return err" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "metadata": {}, |
| "output_type": "pyout", |
| "prompt_number": 9, |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "[<matplotlib.lines.Line2D at 0xa00bb2c>]" |
| "initial guess : avg 9.55977014083 std 0.17596103611\n" |
| ] |
| }, |
| } |
| ], |
| "prompt_number": 15 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| " p1, cov, info, msg, success = optimize.leastsq(err_func, p0[:], args=(flt_meas, sensor_ref), full_output=1)\n", |
| " if not success in [1, 2, 3, 4]:\n", |
| " print(\"Optimization error: \", msg)\n", |
| " print(\"Please try to provide a clean logfile.\")\n", |
| " sys.exit(1)\n", |
| "\n", |
| " cp1, np1 = calibration_utils.scale_measurements(flt_meas, p1)\n", |
| " print(\"optimized guess : avg \"+str(np1.mean())+\" std \"+str(np1.std()))" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "metadata": {}, |
| "output_type": "display_data", |
| "png": 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lM5Md3A0Nxt5nV+TiJkE3WuEC2OPQ4+OZiFlxL1gRtchFa0yC0w5dPvhK3Ffk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\nHr14Uf2G0lLIoXMIL4Lety/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|
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "<matplotlib.figure.Figure at 0x9eb46cc>" |
| "optimized guess : avg 9.80797237599 std 0.141020849641\n" |
| ] |
| } |
| ], |
| "prompt_number": 9 |
| "prompt_number": 16 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [ |
| "%pylab qt\n", |
| "#%pylab inline\n", |
| "calibration_utils.plot_results(True, measurements, flt_idx, flt_meas, cp0, np0, cp1, np1, sensor_ref)" |
| ], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "output_type": "stream", |
| "stream": "stdout", |
| "text": [ |
| "Populating the interactive namespace from numpy and matplotlib\n" |
| ] |
| } |
| ], |
| "prompt_number": 18 |
| }, |
| { |
| "cell_type": "code", |
| "collapsed": false, |
| "input": [], |
| "language": "python", |
| "metadata": {}, |
| "outputs": [] |
| } |
| ], |
| "metadata": {} |