{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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 [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",
"Nejd\u0159\u00edve zjist\u00edme zda m\u00e1me p\u0159\u00edstup pro z\u00e1pis a \u010dten\u00ed do syst\u00e9mov\u00e9ho za\u0159\u00edzen\u00ed. A jak\u00e9 \u010d\u00edslo m\u00e1 I\u00b2C sb\u011brnice na kterou m\u00e1me p\u0159ipojen\u00e1 \u010didla. \n",
"P\u0159\u00edpadn\u011b je mo\u017en\u00e9 tuto \u010d\u00e1st p\u0159esko\u010dit a vyu\u017e\u00edt p\u0159\u00edmo predem ulo\u017een\u00fd datov\u00fd set.\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!i2cdetect -l"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"i2c-0\ti2c \ti915 gmbus ssc \tI2C adapter\r\n",
"i2c-1\ti2c \ti915 gmbus vga \tI2C adapter\r\n",
"i2c-2\ti2c \ti915 gmbus panel \tI2C adapter\r\n",
"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-B \tI2C adapter\r\n",
"i2c-7\ti2c \ti2c-tiny-usb at bus 001 device 013\tI2C adapter\r\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Proto\u017ee pro p\u0159ipojen\u00ed \u010didel k po\u010d\u00edta\u010di pou\u017e\u00edv\u00e1me adapt\u00e9r i2c-tiny-usb. Vid\u00edme, \u017ee sb\u011brnice m\u00e1 aktu\u00e1ln\u011b ozna\u010den\u00ed nap\u0159\u00edklad i2c-8. \n",
"\n",
"V p\u0159\u00edpad\u011b, \u017ee v\u00fd\u0161e uveden\u00fd p\u0159\u00edklad vr\u00e1t\u00ed chybu, nebo pojmenov\u00e1n\u00ed \"unknown\" tak nem\u00e1me p\u0159\u00edstup k syst\u00e9mov\u00fdm rozhran\u00edm. Ten z\u00edsk\u00e1me vytvo\u0159en\u00edm souboru s n\u00e1sleduj\u00edc\u00edm obsahem ve slo\u017ece: /etc/udev/rules.d/i2c-devices.rules"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"KERNEL==\"i2c-[0-9]*\", GROUP=\"i2c\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Toto ozna\u010den\u00ed budeme je\u0161t\u011b d\u00e1le pot\u0159ebovat, proto si jej ulo\u017e\u00edme da prom\u011bnn\u00e9. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"port = 7"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Budeme pokra\u010dovat na\u010dten\u00edm pot\u0159ebn\u00fdch modul\u016f pro zach\u00e1zen\u00ed s I\u00b2C sn\u00edma\u010di."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import time\n",
"import datetime\n",
"import sys\n",
"\n",
"from pymlab import config\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nyn\u00ed si nadefinujeme strukturu p\u0159ipojen\u00ed jednotliv\u00fdch \u010didel na I\u00b2C sb\u011brnici."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cfg = config.Config(\n",
" i2c = {\n",
" \"port\": port,\n",
" },\n",
" bus = [\n",
" {\n",
" \"type\": \"i2chub\",\n",
" \"address\": 0x72,\n",
" \n",
" \"children\": [\n",
" {\"name\": \"acc\", \"type\": \"imu01_acc\", \"sensitivity\": 4.0, \"channel\": 0, }, \n",
" ],\n",
" },\n",
" ],\n",
")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tuto strukturu inicializujeme, aby jsme dos\u00e1hli definovan\u00e9 konfigurace \u010didel."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cfg.initialize()\n",
"acc = cfg.get_device(\"acc\")\n",
"time.sleep(0.5)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"WARNING:pymlab.sensors.iic:HID device does not exist, we will try SMBus directly...\n"
]
}
],
"prompt_number": "*"
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\u010cten\u00ed dat z akcelerometru\n",
"-------------------------\n",
"\n",
"Nyn\u00ed u\u017e m\u016f\u017eeme p\u0159\u00edmo komunikovat se za\u0159\u00edzen\u00edm pojmenovan\u00fdm jako acc."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import sys\n",
"import time\n",
"from IPython.display import clear_output\n",
"\n",
"MEASUREMENTS = 1000\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",
" 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": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(999, [0.038024999999999996, -0.00975, 0.966225])\n"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.savez(\"calibration_data_3Dset\", data=list_meas)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Kalibrace akcelerometru\n",
"-----------------------\n",
"\n",
"Nam\u011b\u0159en\u00e1 data m\u016f\u017eeme tak\u00e9 z\u00edskat z p\u0159edem ulo\u017een\u00e9ho souboru. V n\u00e1sleduj\u00edc\u00edm bloku je otev\u0159en soubor s referen\u010dn\u00edmi daty, kter\u00fd se nach\u00e1z\u00ed v dokumenta\u010dn\u00ed slo\u017ece mudulu IMU01A. \n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = np.load('./calibration_data_set.npz')\n",
"x=data['x']\n",
"y=data['y']\n",
"z=data['z']"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from mpl_toolkits.mplot3d.axes3d import Axes3D\n",
"#%pylab qt\n",
"%pylab inline\n",
"fig = plt.figure()\n",
"ax = Axes3D(fig)\n",
"p = ax.scatter(x, y, z)\n",
"#pyplot.show()\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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FrzuhDhw4FHKtsu3fvztixY0VFp6DeiKVO\ngcBHqa5QpLCwkKioqGYZz6hRoxg1alSVr0dHR7Np0ybbvwcPHmwLigJBQxAZn0DgwzgvKYriEYEv\nIAKfQOCjOBeKFBYWCh89gU8gAp9A4KOMGDGCNWvWAKBWqwkPD2+2ZU6BoCkRe3wCQSvlwQcfZNu2\nbZSUlNCpUyfS09MxGAzANam1IUOGkJmZSZcuXQgKCmLVqlXNPGKBoGkQkmUCgUAg8CnEUqdAIBAI\nfAoR+AQCgUDgU4jAJxAIBAKfQgQ+gUAgEPgUIvAJBAKBwKcQgU8gEAgEPsX/B5KYXLk3/yC5AAAA\nAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xb5c440c>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"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": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"measurements = np.array(list_meas)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"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": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"0.0973014827316\n",
"remaining 703 after filtering"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" 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": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"initial guess : avg 9.55977014083 std 0.17596103611\n"
]
}
],
"prompt_number": 22
},
{
"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": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"optimized guess : avg 9.80797237599 std 0.141020849641\n"
]
}
],
"prompt_number": 23
},
{
"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"
]
},
{
"metadata": {},
"output_type": "display_data",
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iCSgUCm0/DDc3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uzZv3qx9TUlJiVFa77//Pn388cfa34VqtbW1UXR0NInFYvLy8qKioqJhufZCMbVf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\nSad09PTp0/H0008DUJeFd
nV1BQDY2dnp2QMA3t7eyMzMRE1NDZqamhAcHAxAXYHz6tWrANT9rplH\nA/br8e3XfA9jhDhy5Aj8/f1RWlqKl19+GTk5OSgsLIS9vT0OHDiATZs2obOzc8CxNEB5L01jnc7O\nTtTV1WHu3Lna51xdXZGRkQGZTIYDBw4gKSmp3/iB1menTJmCGzduAFA3phnstfdTWVkJQF1p8/nn\nn4eLiwvmzZsHmUwGmUyG1atXayuv8trwowP79fj2a55hjBAeHh5ISkqCpaUlVCoVPvroI1haWmLV\nqlWoqqrCs88+Cw8PD61j6zrfQD+3t7dj+fLlaGtrQ1ZWFh577DHt82+++SakUin27duH9vZ2vP32\n23q23H8TUfNzcnIy1q5diy+++ALOzs7axx9mCwB8++23KCgogIWFBT777DPMmjULISEhEIvF6Orq\ngre3N2bNmtVvHGPesF+Pb7/marVmQHl5OQ4dOoRdu3aZ2hSGGTbYr80PXpIyA0y1zZBhRhL2a/OD\nZxgMwzCMQfAMg2EYhjEIDhgMwzCMQXDAYBiGYQyCAwbDMAxjEBwwGIZhGIPggMEwDMMYxP8D50Ez\nctAxpREAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7f7113c306d0>"
]
}
],
"prompt_number": 26
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\u010cten\u00ed dat z gyroskopu\n",
"---------------------\n",
"\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cfg = config.Config(\n",
" i2c = {\n",
" \"port\": port,\n",
" },\n",
"\n",
"\tbus = [\n",
"\t\t{\n",
" \"type\": \"i2chub\",\n",
" \"address\": 0x72,\n",
" \n",
" \"children\": [\n",
" {\"name\": \"gyro\", \"type\": \"imu01_gyro\", \"channel\": 0, }\n",
" ],\n",
"\t\t},\n",
"\t],\n",
")\n",
"\n",
"cfg.initialize()\n",
"#acc = cfg.get_device(\"acc\")\n",
"gyro = cfg.get_device(\"gyro\")\n",
"sys.stdout.write(\" MLAB accelerometer sensor IMU01A module example \\r\\n\")\n",
"time.sleep(0.5)\n",
"gyro.route()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import sys\n",
"import time\n",
"from IPython.display import clear_output\n",
"\n",
"MEASUREMENTS = 100\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",
" clear_output()\n",
" (x, y, z) = gyro.axes()\n",
" list_meas.append([x, y, z])\n",
" print (n, list_meas[n])\n",
" sys.stdout.flush()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"measurements = np.array(list_meas)\n",
"\n",
"%pylab qt\n",
"plt.subplot(1, 1, 1)\n",
"plt.plot(measurements[:, 0])\n",
"plt.plot(measurements[:, 1])\n",
"plt.plot(measurements[:, 2])\n",
"plt.xlabel('sample number')\n",
"plt.ylabel('ADC')\n",
"plt.title('Raw sensors')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"<matplotlib.text.Text at 0x7f67ec372650>"
]
}
],
"prompt_number": "*"
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"help(map)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Help on built-in function map in module __builtin__:\n",
"\n",
"map(...)\n",
" map(function, sequence[, sequence, ...]) -> list\n",
" \n",
" Return a list of the results of applying the function to the items of\n",
" the argument sequence(s). If more than one sequence is given, the\n",
" function is called with an argument list consisting of the corresponding\n",
" item of each sequence, substituting None for missing values when not all\n",
" sequences have the same length. If the function is None, return a list of\n",
" the items of the sequence (or a list of tuples if more than one sequence).\n",
"\n"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}