/Modules/Sensors/MAG01A/SW/Python/MAG_test.ipynb
110,7 → 110,7
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
"prompt_number": 29
},
{
"cell_type": "markdown",
142,7 → 142,7
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
"prompt_number": 30
},
{
"cell_type": "markdown",
170,7 → 170,7
]
}
],
"prompt_number": 5
"prompt_number": 31
},
{
"cell_type": "markdown",
188,9 → 188,6
"from IPython.display import clear_output\n",
"\n",
"MEASUREMENTS = 500\n",
"#x = np.zeros(MEASUREMENTS)\n",
"#y = np.zeros(MEASUREMENTS)\n",
"#z = np.zeros(MEASUREMENTS)\n",
"list_meas = []\n",
"\n",
"for n in range(MEASUREMENTS):\n",
237,7 → 234,7
"cell_type": "markdown",
"metadata": {},
"source": [
"Zpracov\u00e1n\u00ed dat\n",
"Zpracov\u00e1n\u00ed dat 2D\n",
"-----------\n",
"\n",
"V dal\u0161\u00ed \u010d\u00e1sti budeme pracovat s daty v ulo\u017een\u00e9m souboru, kter\u00fd na\u010dteme do pol\u00ed x, y, z. "
247,13 → 244,15
"cell_type": "code",
"collapsed": false,
"input": [
"data = np.load('./calibration_data_3Dset.npz')\n",
"list_meas = data['data']"
"data = np.load('./calibration_data_2Dset.npz')\n",
"x = data['x']\n",
"y = data['y']\n",
"z = data['z']"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 142
"prompt_number": 42
},
{
"cell_type": "markdown",
271,11 → 270,7
"%pylab inline\n",
"fig = plt.figure()\n",
"ax = Axes3D(fig)\n",
"#plt.subplot(121)\n",
"p = ax.scatter((list_meas)[1],(list_meas)[5],(list_meas)[3])\n",
"#p = ax.plot3D(list_meas)\n",
"#plt.subplot(122)\n",
"#p = ax.scatter(x, y, z)\n"
"p = ax.scatter(x,y,z)"
],
"language": "python",
"metadata": {},
290,13 → 285,13
{
"metadata": {},
"output_type": "display_data",
"png": 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FtWkXG/b47DzYRB5gNHkkKiuPxicEsTCbkTSsxOG8dchX+6d/i1vP10rwKrXo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\n3JIhLfhhZEu6gZ1bMcxMWUJcyTPA1thXuVw2v49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B5hA2KIlI13Wz9BrgvTh3ELD3IQzX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\nmYkzu+yyC4CtiTNOlTu8gF1co7auyM1JVm61WkUqlWogft5aYi0I2WT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G2Q6PpyNYNg6W3YKKipGCZk8ETSAQhd1eLTKvViESievaD4JRo0Zg1KgRqq9r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CTXI0Q6BHCqCYQSaqINVt1F3lTU6xQRhEi7hdMWEUxPnjfrFGsVUZ6IQMJZU3OlnPQWrtbpKuVd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\nUWQAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7f3f8205d590>"
"<matplotlib.figure.Figure at 0x7effb8981ad0>"
]
}
],
"prompt_number": 143
"prompt_number": 43
},
{
"cell_type": "markdown",
317,21 → 312,21
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 144,
"prompt_number": 44,
"text": [
"[<matplotlib.lines.Line2D at 0x7f3f820aa790>]"
"[<matplotlib.lines.Line2D at 0x7effdb72c550>]"
]
},
{
"metadata": {},
"output_type": "display_data",
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ZIYQQX331lUhLSxMLFy5UNK733nvPO0DEbreLhQsXKh6TEEK43W7x4IMPirvu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\nPxGRxjDxExFpDBM/EZHGMPETEWnM/wPulkrNjSVVUQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7f3f81d6bad0>"
"<matplotlib.figure.Figure at 0x7effb80d0e90>"
]
}
],
"prompt_number": 144
"prompt_number": 44
},
{
"cell_type": "markdown",
351,17 → 346,14
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'float' object is not iterable",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-145-8671977becc2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mxoffset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mxoffset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: 'float' object is not iterable"
"output_type": "stream",
"stream": "stdout",
"text": [
"26.0\n"
]
}
],
"prompt_number": 145
"prompt_number": 45
},
{
"cell_type": "code",
372,7 → 364,16
],
"language": "python",
"metadata": {},
"outputs": []
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"-180.5\n"
]
}
],
"prompt_number": 46
},
{
"cell_type": "code",
382,13 → 383,31
],
"language": "python",
"metadata": {},
"outputs": []
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 47,
"text": [
"[<matplotlib.lines.Line2D at 0x7effb8413050>]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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KFeLFF18UX3/9tSzvvV/X4xeDJn/l5eUBePrkr8jIyBEnf/ljDkB5eTkcDgcA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\n8RMRqcz/A1D+DQmdcGLaAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7effb83053d0>"
]
}
],
"prompt_number": 47
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"D\u00e1le pot\u0159ebujeme kompenzovat soft-iron efekty. K tomu mus\u00edme pracovat s nam\u011b\u0159en\u00fdmi daty, jako s elipsou a naj\u00edt jej\u00ed hlavn\u00ed a vedlej\u0161\u00ed poloosu. Postup je trochu komplikovan\u011bj\u0161\u00ed, proto adoptujeme k\u00f3d z [PaparazziUAV](http://wiki.paparazziuav.org/wiki/ImuCalibration). Ten pomoc\u00ed fitov\u00e1n\u00ed elipsoindu najde korek\u010dn\u00ed parametry citlivosti pro jednotliv\u00e9 osy. Zanedb\u00e1v\u00e1 ale p\u0159\u00edpadnou rotaci elipsoidu popsanou v \u010dl\u00e1nku [Compensating for Tilt, Hard-Iron, and Soft-Iron Effects](http://www.sensorsmag.com/sensors/motion-velocity-displacement/compensating-tilt-hard-iron-and-soft-iron-effects-6475)"
"Interaktivn\u00ed test, kter\u00fd vypisuje aktua\u00e1ln\u00ed azimut. Lze si na n\u011bm vyzkou\u0161et funkci kompasu. Je vid\u011bt, \u017ee p\u0159i vzniku v\u011bt\u0161\u00edho n\u00e1klonu, dvouos\u00fd kompas za\u010dne ukazovat p\u0159esn\u011b opa\u010dn\u00fd sm\u011br."
]
},
{
395,9 → 414,96
"cell_type": "code",
"collapsed": false,
"input": [
"try:\n",
"\n",
" for n in range(MEASUREMENTS):\n",
" (x, y, z) = mag_sensor.axes()\n",
" phi = np.arctan2(x-xoffset, z-zoffset)\n",
" clear_output()\n",
" print ((phi*180)/pi+180)\n",
" sys.stdout.flush()\n",
"except KeyboardInterrupt:\n",
" sys.exit(0)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"308.027821813\n"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Vid\u00edme, \u017ee po tomto zp\u016fsobu korekce m\u00e1 vykreslen\u00fd \u00fatvar od kru\u017enice je\u0161t\u011b v\u00fdznamn\u00e9 odchylky. Nyn\u00ed pot\u0159ebujeme kompenzovat soft-iron efekty. K tomu mus\u00edme pracovat s nam\u011b\u0159en\u00fdmi daty, jako s elipsou a naj\u00edt jej\u00ed hlavn\u00ed a vedlej\u0161\u00ed poloosu. Postup je trochu komplikovan\u011bj\u0161\u00ed, proto adoptujeme k\u00f3d z [PaparazziUAV](http://wiki.paparazziuav.org/wiki/ImuCalibration). Ten pomoc\u00ed fitov\u00e1n\u00ed elipsoindu najde korek\u010dn\u00ed parametry citlivosti pro jednotliv\u00e9 osy. Zanedb\u00e1v\u00e1 ale p\u0159\u00edpadnou rotaci elipsoidu popsanou v \u010dl\u00e1nku [Compensating for Tilt, Hard-Iron, and Soft-Iron Effects](http://www.sensorsmag.com/sensors/motion-velocity-displacement/compensating-tilt-hard-iron-and-soft-iron-effects-6475)\n",
"Tento p\u0159\u00edstup je tak\u00e9 v\u00fdhodn\u00fd v tom, \u017ee vyu\u017e\u00edv\u00e1 v\u0161echny 3 osy magnetometru. Proto nen\u00ed pot\u0159eba pro kompenzaci n\u00e1klonu pou\u017e\u00edvat akcelerometr. Kompenzace akcererometrem by ale pozd\u011bji m\u011bla b\u00fdt vyu\u017eita ke korekci rotace os magnetometru v\u016f\u010di vn\u011bj\u0161\u00edmu pouzdru.\n",
"\n",
"Zpracov\u00e1n\u00ed dat 3D\n",
"-----------\n",
"\n",
"K tomu pou\u017eijeme datov\u00fd set, kde jsou body rozprost\u0159en\u00e9 po cel\u00e9m povrchu koule. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = np.load('./calibration_data_3Dset.npz')\n",
"list_meas = data['data']\n",
"x = list_meas[:, 0]\n",
"y = list_meas[:, 1]\n",
"z = list_meas[:, 2]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from mpl_toolkits.mplot3d.axes3d import Axes3D\n",
"#%pylab qt ## po odkomentovani a zakomentovani nasledujiciho radku udela vystup do QT okna. \n",
"%pylab inline\n",
"fig = plt.figure()\n",
"ax = Axes3D(fig)\n",
"p = ax.scatter(x,y,z)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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X6yksLESv1ye1WkbowjZ48GBk+QMkSUYQTHi9F0hLS0EUU4INlvszOp2uze8v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ZfbMZkS2LLlE3bu3ABci16/mm+++Ykvvnjf/buekWFtadJNmzbhcMxAFCf9bhj+JGbzaAoKJrNr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\n",
"text": [
"<matplotlib.figure.Figure at 0x7f10f2b9d950>"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import scipy\n",
"from scipy import optimize\n",
"\n",
"import calibration_utils\n",
"\n",
"sensor_ref = 1.\n",
408,7 → 514,7
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 146
"prompt_number": 3
},
{
"cell_type": "markdown",
426,7 → 532,7
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 147
"prompt_number": 4
},
{
"cell_type": "markdown",
447,19 → 553,17
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"flt_meas = measurements"
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"460.895326306\n",
"remaining 346 after filtering\n"
]
}
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
"prompt_number": 5
},
{
"cell_type": "markdown",
492,7 → 596,7
]
}
],
"prompt_number": 150
"prompt_number": 6
},
{
"cell_type": "markdown",
525,7 → 629,7
]
}
],
"prompt_number": 151
"prompt_number": 7
},
{
"cell_type": "markdown",
539,6 → 643,7
"collapsed": false,
"input": [
"%pylab qt\n",
"#%pylab inline\n",
"calibration_utils.plot_results(False, measurements, flt_idx, flt_meas, cp0, np0, cp1, np1, sensor_ref)\n",
"calibration_utils.plot_mag_3d(flt_meas, cp1, p1)"
],
561,7 → 666,7
]
}
],
"prompt_number": 152
"prompt_number": 8
},
{
"cell_type": "markdown",
586,34 → 691,16
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": "*"
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 92,
"output_type": "stream",
"stream": "stdout",
"text": [
"583.14932841582277"
"(1.0033330291141624, 159.16410600293204, 61.66914855382452)\n"
]
}
],
"prompt_number": 92
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
"prompt_number": 35
}
],
"metadata": {}
/Modules/Sensors/MAG01A/SW/Python/calibration_utils.py
131,7 → 131,7
 
 
def plot_results(block, measurements, flt_idx, flt_meas, cp0, np0, cp1, np1, sensor_ref):
"""Plot calibration results."""
"""Plot calibration results in 2D graphs."""
plt.subplot(3, 1, 1)
plt.plot(measurements[:, 0])
plt.plot(measurements[:, 1])
139,8 → 139,8
plt.plot(flt_idx, flt_meas[:, 0], 'ro')
plt.plot(flt_idx, flt_meas[:, 1], 'ro')
plt.plot(flt_idx, flt_meas[:, 2], 'ro')
plt.xlabel('time (s)')
plt.ylabel('ADC')
plt.xlabel('sample number')
plt.ylabel('miligauss')
plt.title('Raw sensors')
 
plt.subplot(3, 2, 3)
149,10 → 149,16
plt.plot(cp0[:, 2])
plt.plot(-sensor_ref*np.ones(len(flt_meas)))
plt.plot(sensor_ref*np.ones(len(flt_meas)))
plt.xlabel('sample number')
plt.ylabel('-')
plt.title('First approximation')
 
plt.subplot(3, 2, 4)
plt.plot(np0)
plt.plot(sensor_ref*np.ones(len(flt_meas)))
plt.xlabel('sample number')
plt.ylabel('-')
plt.title('magnitude')
 
plt.subplot(3, 2, 5)
plt.plot(cp1[:, 0])
160,10 → 166,16
plt.plot(cp1[:, 2])
plt.plot(-sensor_ref*np.ones(len(flt_meas)))
plt.plot(sensor_ref*np.ones(len(flt_meas)))
plt.xlabel('sample number')
plt.ylabel('-')
plt.title('separate axes')
 
plt.subplot(3, 2, 6)
plt.plot(np1)
plt.plot(sensor_ref*np.ones(len(flt_meas)))
plt.xlabel('sample number')
plt.ylabel('-')
plt.title('magnitude')
 
# if we want to have another plot we only draw the figure (non-blocking)
# also in matplotlib before 1.0.0 there is only one call to show possible