pico-tracker/sim/si_fir_filter/si_fir_filter.ipynb

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"metadata": {
"name": ""
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"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Let's plot some filters "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 453
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Reflects an array of coefficients about the last element \n",
"def sym_fir_coeff(coeff):\n",
" for i in range(len(coeff)-2, -1, -1):\n",
" coeff.append(coeff[i])\n",
"\n",
" return coeff\n",
"\n",
"# Normalises the si's 8-bit coefficients to 0 - 1 \n",
"def si_normalise_coeff(coeff):\n",
" coeff = [x-0x100 if x > 0x7f else x for x in coeff]\n",
" return [x/0x300 for x in coeff] # 0x300 seems to be the value required to get 0 gain at dc.. Not sure about this: Test!\n",
"\n",
"def si_coeff(coeff):\n",
" norm = [int(x*0x300) for x in coeff]\n",
" return [x+0x100 if x < 0 else x for x in norm]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 454
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"These are the default si coefficients"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Default si coefficients \n",
"si_default_fir_coeff = [0x1, 0x3, 0x8, 0x11, 0x21, 0x36, 0x4d, 0x60, 0x67]\n",
"si_fir_coeff = si_normalise_coeff(sym_fir_coeff(si_default_fir_coeff))\n",
"print si_fir_coeff"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[0.0013020833333333333, 0.00390625, 0.010416666666666666, 0.022135416666666668, 0.04296875, 0.0703125, 0.10026041666666667, 0.125, 0.13411458333333334, 0.125, 0.10026041666666667, 0.0703125, 0.04296875, 0.022135416666666668, 0.010416666666666666, 0.00390625, 0.0013020833333333333]\n"
]
}
],
"prompt_number": 455
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"Setup graph"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 456
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from scipy import signal\n",
"from pylab import *\n",
"from __future__ import division\n",
"import matplotlib.pyplot as plt"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 457
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w,h=signal.freqz(si_fir_coeff,1) # Compute impulse response \n",
"\n",
"plt.plot(w/pi,20*log10(abs(h)))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ufCUwZ84c9OnTB9OmTUNlZSV27NgBADh58iR69epV/Tyj0QhTzalzRORQnp5y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\nAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc03f6cd0>"
]
}
],
"prompt_number": 458
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So this a Gaussian Filter with B\\*T=0.5. Nice\n",
"\n",
"Let's generate some more filter coefficients. I got these from [\"Free online FIR filter design\"](http://t-filter.appspot.com/fir/index.html). Happy days"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"t_fir_coeff = [0.01665389596732681,\n",
" 0.07353658710395161,\n",
" 0.10040345335534452,\n",
" 0.04751332314075821,\n",
" -0.06317967799551721,\n",
" -0.09143711477971043,\n",
" 0.06319322564548596,\n",
" 0.31257963657965065,\n",
" 0.43524399610103215,\n",
" 0.31257963657965065,\n",
" 0.06319322564548596,\n",
" -0.09143711477971043,\n",
" -0.06317967799551721,\n",
" 0.04751332314075821,\n",
" 0.10040345335534452,\n",
" 0.07353658710395161,\n",
" 0.01665389596732681]\n",
"t2_fir_coeff = [\n",
" 0.005896897045205714,\n",
"0.010704119037845003,\n",
"-0.00007850080590466364,\n",
"-0.03065101327252804,\n",
"-0.04934969829168403,\n",
"-0.0032240578718828747,\n",
"0.12395841691052671,\n",
"0.27093078431580997,\n",
"0.33655204899827573,\n",
"0.27093078431580997,\n",
"0.12395841691052671,\n",
"-0.0032240578718828747,\n",
"-0.04934969829168403,\n",
"-0.03065101327252804,\n",
"-0.00007850080590466364,\n",
"0.010704119037845003,\n",
"0.005896897045205714\n",
"]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 459
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w,h=signal.freqz(t_fir_coeff,1) # Compute impulse response \n",
"\n",
"plt.plot(w/pi,20*log10(abs(h)))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Ezp2Tk+mlpVazQmpRnz7n7xXYudO7y39bwiJA5AZ7O0ivImA/M6nNpu/SU1d0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\nAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc0323250>"
]
}
],
"prompt_number": 460
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"This has a different response. Much sharper. Interesting. Lot more passband ripple too though"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w,h=signal.freqz(t2_fir_coeff,1) # Compute impulse response \n",
"\n",
"plt.plot(w/pi,20*log10(abs(h)))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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9Xbu/qjp3lvuq6YYAGRly3uCuu/SNwWbQoNpHAtu3y0c0uvMkxbpGSdu2yXjc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\nIvJiLAJERF7s/wHM5T5WRtVSZgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcbfe0cc90>"
]
}
],
"prompt_number": 461
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Much less passband ripple"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's try a filter with a passband"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"\n",
"sampling frequency: 16000 Hz\n",
"\n",
"* 0 Hz - 500 Hz\n",
" gain = 0\n",
" desired attenuation = -40 dB\n",
" actual attenuation = -33.20090552393641 dB\n",
"\n",
"* 1200 Hz - 2500 Hz\n",
" gain = 1\n",
" desired ripple = 5 dB\n",
" actual ripple = 7.628523622719886 dB\n",
"\n",
"* 3500 Hz - 8000 Hz\n",
" gain = 0\n",
" desired attenuation = -40 dB\n",
" actual attenuation = -33.20090552393641 dB\n",
"\"\"\"\n",
"\n",
"p_fir_coeff = [\n",
"0.03315273058205705,\n",
"0.04369271452900486,\n",
"0.010060937885865288,\n",
"-0.07363298137328711,\n",
"-0.14853046126761885,\n",
"-0.13375882936132458,\n",
"-0.007516054328839414,\n",
"0.15276142842227725,\n",
"0.2256656942570718,\n",
"0.15276142842227725,\n",
"-0.007516054328839414,\n",
"-0.13375882936132458,\n",
"-0.14853046126761885,\n",
"-0.07363298137328711,\n",
"0.010060937885865288,\n",
"0.04369271452900486,\n",
"0.03315273058205705,\n",
"]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 462
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w,h=signal.freqz([x/2 for x in p_fir_coeff],1) # Compute impulse response \n",
"\n",
"plt.plot(w/pi,20*log10(abs(h)))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Ztq3ytgi+iI8HLl9umpSzciWfOllN2rThvXzcyc2uWLuWv31qlaz6RLAH+Pzb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\nSUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc053d110>"
]
}
],
"prompt_number": 463
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"p_si_coeff_values = si_coeff([x/4 for x in p_fir_coeff])[0:9]\n",
"\n",
"print p_si_coeff_values\n",
"print \", \".join(hex(n) for n in p_si_coeff_values)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[6, 8, 1, 242, 228, 231, 255, 29, 43]\n",
"0x6, 0x8, 0x1, 0xf2, 0xe4, 0xe7, 0xff, 0x1d, 0x2b\n"
]
}
],
"prompt_number": 464
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"p_si_fir_coeff = si_normalise_coeff(sym_fir_coeff(p_si_coeff_values))\n",
"print p_si_fir_coeff"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[0.0078125, 0.010416666666666666, 0.0013020833333333333, -0.018229166666666668, -0.036458333333333336, -0.032552083333333336, -0.0013020833333333333, 0.037760416666666664, 0.055989583333333336, 0.037760416666666664, -0.0013020833333333333, -0.032552083333333336, -0.036458333333333336, -0.018229166666666668, 0.0013020833333333333, 0.010416666666666666, 0.0078125]\n"
]
}
],
"prompt_number": 465
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w,h=signal.freqz(p_si_fir_coeff,1) # Compute impulse response \n",
"\n",
"plt.plot(w/pi,20*log10(abs(h)))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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uXIlBgwYBANLS0pCbm4va2lqUlpaipKQEia4MUzfp3JnGJDurf3L0KD3KMYHN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\nRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc01995d0>"
]
}
],
"prompt_number": 466
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Some more resources, have sections on normalisation\n",
"\n",
"[here](http://www.mikroe.com/chapters/view/72/chapter-2-fir-filters/)\n",
"[here](http://dsp.stackexchange.com/questions/4693/fir-filter-gain)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generate some test aprs data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 466
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"samp_rate = 60*1000"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 467
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def create_sine(frequency, amplitude=1.0, bits=1, bitrate=1200, sr=samp_rate):\n",
" global phase\n",
" \n",
" w = 2.0 * pi * frequency\n",
" t = arange(0, (bits / bitrate), bits / sr)\n",
" \n",
" wave = sin(w * t + phase)\n",
" phase += (w * bits / bitrate)\n",
" \n",
" return wave\n",
" \n",
"def random_data(length=200):\n",
" return [0 if x < 0.5 else 1 for x in rand(length)]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 468
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def get_afsk(len_afsk=25, sq=False, sr=samp_rate, dl=1, dh=1):\n",
" global phase\n",
" phase = pi/2\n",
" \n",
" if sq: # Square Wave\n",
" afsk = concatenate([[-dl if x < 0 else dl for x in create_sine(1200, sr=sr)] if x \n",
" else [-dh if x < 0 else dh for x in create_sine(2200, sr=sr)]\n",
" for x in random_data(len_afsk)])\n",
" \n",
" else: \n",
" afsk = concatenate([create_sine(1200, sr=sr) * dl if x \n",
" else create_sine(2200, sr=sr) * dh for x in random_data(len_afsk)])\n",
" \n",
" \n",
" \n",
" return afsk"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 469
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"Let's see what it looks like in the time domain"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.plot(get_afsk(len_afsk=12))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 470,
"text": [
"[<matplotlib.lines.Line2D at 0x7fbcc001de50>]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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ZRfGcc55UGZqrRWAduXN1IG9FYJWxUXs8VMcD6TOArJisDqrKAXAMG8c4qebV\nAf1IsFymeX0uA8iqCJxlDSDqmdOsAQD2nV1Wcxx1z5wOLyBfDMC27umiqhxAVpGTzgub04pCTKSA\nqDQ0K5YVpTjcwreLDMDFFBAn+JqYiGe63PUMuMMAiiJwDFw2TlFKpzoeSC8KSVIYzjzlLcWgUvie\nnJxKMwSRBQOwzWQ5Tta07pVKU0c6xF03L7oHZBek6iK3DiCKImURnaqOB2hRCKUAaYIBZGHEbUS2\nKuOj2maBdLuAAL4RzyrNRtU9lWtnwQCobaBRpwYD/CJwkQKCe7sgVccDbjAAnW37QaQRndpw0EnP\nHDdf3C6gyUngwgXxfmEVJK1jzxNsxXSqLKsUqsq181QD4Basi41gjhoYEzQ0DzUAaWDC0iFZGQkT\nDjouQk1yABwGMDoq3iscZhDCoMJWGhrC2UpW+sMZC6gzNMpYiTzoXtz4wgF8CFuFqDRSQGlFIVFn\nkQBqyhb23gMgnSjeloOOcz42HYCuzDnpEJflw7nvPLFvju4BhQOwmiPLisJKUPKQaReB81o/sGVg\nuA5AV+Yq98oJRLhO1rTuyfFJDjqL+ptLDRiqBwXqILcOIIsUQ546EWwW3PLWo64yPmks52Aw0wyA\nw3QAew6aetCfyrVrRffk+JotAru+DT5PUUjYWSRAsrJylc1Gmi2NCDNqrDwYjMoCdGXOuVeugXG1\niSJv7Juqe4CZNw+qwjkHkFWUWC6LKC/uEC5Ti1A3Ckm7DdRmCohqYFTlQ3XQcc8M8NJANmoAWaWA\nsnQAJoIv13UvbnxNMICsFqHKZhRThais85Au55jj5MOJjDk1AIDXCmqjBkB9TsAOg1Y5xdSWfKpJ\n9+LGFw7gQ2SVJogqgKleG6BFIdRFGHevNh2djZe6qIy31QUEuMUAbKXoVOVjg2WlUQPIg+7J8YUD\niEGe85BpFqLi8pA2I8w8yse2A0izBpDXPH41sW+q7snxNVsE5hZJXDUwEmkWgamRWtZFYBvyMZEC\n4hSBq70GoDI+jzWAtHVP1rnCNmEWbaCIP2fD9d2IukcCAPTzSOLulVsD4ESYWR4XwEkBcV4PqBt5\nJsmHsw7jDr3jOgCbeXxTbaBpnAXE0b24M6lqhgHEPST3nA1bBkbF+egeCQDY60W2Rbe5b26qxhSQ\nDQbAMTA2jpFQGZ8Vu5NIkwHY0r2abwO1lf8E7Hci6Ob/AXoUkpWiZmlguKzHFQagYiRcK/Bzr227\nMw1IjwEn4c7yAAAgAElEQVRknerSQS4dgI38pxxvU3l08/+AnTykTUfHnSOOfAsGkE59xzX52KoB\nUF/JmpXuUZA7B6AS5SW9WYhTHOU4n7wwAI6R4FJ1m0YiLzWArOSTdQoojRfC6NZiymV9o5v1kRc6\nyJ0DiFtEdXVTr/+jjLetPGkyAC5VtxHB1NeLDoe4VzNmZdxcYgA2N4LFjeVu5nKZAUxOikPYdBow\nAJrcbQUiKgGuLqrKAXDH216EeWEAtsZyd/Ny0oO1VAOoRv3hpn5HRoTxD6tNxYEid1tzVC6LIDfO\nQeuicAAaY7kpoGqpAXBSKVnmt7PaCWy6BmDzOV1NP3FTI7oykKAyAI7uRY1VGa+LXDqAuAni5qht\nFoE5DIBSiLJhJFx20Dbv26UagK1ImjveZn3IhO7pBl8ATe5ZOmhd5NIBxE2Qyx0uFAZQLovvHh3V\nG5dVIcpV+eRpJ7DNlkiOfOL2eCSNTbp2GimgNBmADd2T403uBcidA1CZIBcpLEBjAEA2eUibOeao\nBRy3SxXINnWVFwbA2UWcdO24PR5JY4HsWCmQLgPIkkHrIncOgGNgkiIYF2sAgPkoJKsoPGm8CQPj\n4vsAKDUAWy2RHPlwdC9pfFEDmBqbKwewd+9erFmzBqtWrcKjjz4a+pmvfOUrWLVqFTo7O3Hw4MHY\n73PdwOSJAdjYLcotYnENTJYpoDwwAJs5Zi77zjL9mqcaAKdGowuWA6hUKnjggQewd+9eHD58GE88\n8QTeeuutaZ955pln8M477+DIkSP43ve+h/vvvz/2O5N6XV01MK4xAFf76W0aGJuRMfX1gJ7n1kvh\nOVE81zgVNYAqSwHt378fK1euREdHBxoaGnD33Xfj6aefnvaZPXv24J577gEAbN68GYODg+jv74++\noYTNXDYpbFIXUBY7gQHzeUjVA8Oixo6PxztoapHRtoPmtoFS92PU1cUbziCydHSuMjRuCsiVGgC3\nRuNUG2hfXx+WLVt26d/t7e3o6+tL/Exvb2/s99qKEmuJAdiKQkw46LgI08UUA0BnAJTIk+OspGzy\nyKBtn8PlQg3ANQYQ0W+hhpLitjovsBqjxj344IMAxE63F1/cgttv33LZZ1yNYFxkALbOxpfPGvb9\nth103t4JTIk8OekQ/7utw54nr/rDTQG5UgMol4VzrlSmjt7wQ2WO9+/fh//4j316NxUBlgNoa2tD\nT0/PpX/39PSgvb099jO9vb1oa2sL/T7pAL77XeCGG8KvmfUCzksXUBppgjBnZls+ccpo0+nNnCnG\nRyluFCiRp6lOkbDPcNtAXWRothnAqVN6Y+Lu1X8cSpQDSGJo69dvwc03b7n0u4ceekjvBn1gpYA2\nbdqEI0eO4OjRoxgbG8NTTz2FHTt2TPvMjh078MMf/hAA8Nprr6GlpQWtra2x35tkJKhbpbkOwEQe\nMg81gKycbJbySbp2qUSTgw0GkFUalKN7SddOQ/dcqAEAdm2ULlgMoL6+Hrt378a2bdtQqVRw3333\nYe3atXjssccAADt37sStt96KZ555BitXrkRjYyP++Z//OfF7szIwcUVg7h4CwK0aALXYDfAWsK3F\nH/eq0KTrqlwbmKoDzJ0b/zk/0q4BAPbmWGXs2bPR/28rKPE3JkRlpUdGgI98JPr7o2C6BgDEy5fL\nsnTBcgAAsH37dmzfvn3a73bu3Dnt37t379b6Tls0lLP4VfYQJG3RdqkGkCUDsNFmGPeq0KTrymsn\nOQBKHSDtGkDS+KwYmjzBMip9xnlmf2NC1GdcqQEAdlmwLpzbCQwkGwmOgeE6AMpYCZcYANcB2Jjj\nrOs7qgxAB1QGwE0BZSUfG3oL8CNjV/YBAIUDSISLRsKEYNJkADbfj2uTZbmYn5ZIiwHYlg81kHG1\nBVtlfJ5qADV9HDTgphE34QDSYgBJ+XBuOoRbZ3FRPq4xAFvHBeRVfzjPDLizDwCwx9AoyKUDyGrx\ncxag56UXhUxMTL09KAwqKYa8GRjuMbouMQCus4pzsjZZVsEABGy32lb1cdBAdjQ0rgvIxDk1ukcC\nSOhGIUnP6d+MQhmfZZ64VhgAtwbgmoPmOC2gumoALrWB5s4BuLqAVSIQygIE9KOQJGUBqi+NwzUw\nLjEA2dEyORn+/3l0srXEALJONeug6hyATePEzUFSFiBgngEA1WckOHlXlWsD6TEA/3EOYcgqFcM5\nqMyEfGqlBpCb46BtwUUDk7T4y2URsUWlVdJkAKoOwIaych20qzlmID0GAMTPse00qGu653nxPf5J\n4wG6HGbOFNeOOvwwDAUDYMLFQlTSWP8ZH2FImwEk1RpsFgpddNAmdwLrgBp52jTiHP3JinnEbcJM\nGk95J4ME5QgQzlrM1XHQtpBlkZE6Vo6Pum8XawC2UkBZbINXMYpR7zFI2qUqkSYDsJVOse2gqdeN\nq3uoBDRx933xovj+qHdNJ8E0A7clHwpy5wCypL+cRehiDcC1KN7mWNkWG5aiU5kvID8MICv94TLo\nqLoHdz1TZSBhmoEXKaAEuGhguJ01easBuGgkOGOBaAev6gBqoQaQ1XXjxpvQPWrwBejpX9KhkYA9\nBk1B4QAMjU0az3EAM2YIaqwqeBM1gLydBsphaDYZAFXuNpmsy/pjgwFwdA/QYwBJhxIC9upvFOTS\nAbi4EzhpPGcR6haiOMqWdIyEHFtrBgZInwFcvHj572WnWVy9IisdsBVAZal7QHq6pzK+cACOFiiT\nrs2loTpRCOdeVSIYbprA1mmttlNAaTOAsHmSz5nUEePaHg/OmsyT7nGdVeEAkM8iVtJ416IQjjHM\nMwNIuwZgughsQj4usru48bWieyrja94B2Mx/2u4CSisPyc2HZxXBpJFi4KSAXKgBZCkf7k5gTlCS\nF90zcQxLzR8HneciVl6ikKQUQ9LYLBy0zHtHtXLaLgLrMoDxcZGzV/nuIDj3msdNfnHja0X3gKII\nDMBeHl/FwEQd55BlGyiQXhSSZQrI9n2nXQOQMo/L10chLh/uKkNraBA1pLDNdlkGJWnqXhoMrWgD\ntRSFxB3nUG1RCMcYchmajd3WnN3PthgAt/U3Sj4zZyaPzaIIbGszV63onsr4mmcANl+2IMdHLWBu\nK5prnQg2HJ3tNIGN4rWqA5g9WxiCsAg3DByZR93rxYtuy8eGETehe66x76INNAbVZmAA96IQrrJl\nEWHGjU8jBVQui+h7dDT5swCv+MhlALWWorMZfKWle3J8cRy0owaGo3guRiGcVAp1jm11WqXBAAC9\nOoCtFBA3xZDVZq5a0D3OGjZx7LUunHUAUROUxwUM8FvRXKoBxMmHew4KVdFtp70kdOoAWTmAqOes\nVISMbO0ijhvPue9a0T3usdcU5MoBJL3sPG4swFtI3Nxr2lFIFsqmuoCj2B1njtPYCQzkgwEkzRHV\nwGTF0PKke7abEWpiH4ANJQeyjULSrgG4mkrJOsLkOoCsGQDHGF68aLdFEciuSO+S7tmuv9WsA8ja\nwHDzkC6dBcTZdWnzGAlqi6Nt5y6hywA4XUBhh8GpzFGcfKhjgez2l1RbDYCrPzW7D0Blgsplkeek\nvvjDVm7ctTykjSIwl8JyottaYQC2DSlXf2ykN2qFAXAbMCioOgdgazMXxziNjorFnfTKwTi4VgOg\n7pUwsVs0C+YioSMHW22gVPmorGGpPy6lcUw4AJfYN9dJRr3alILcOYAkJU8anwUN5UYgQPXUAJJ2\ni7reBaQjB47cZ87MZg0njbe9rqIcV5YpoDRrABz9oSB3DkBFUV2LQrjpH8A8A7Bx8iJXPtwUEMd5\n2GAALhaBVeXj0nEOXAbg2km8HN0DzKaBcuUAVA7CihufRmrEBQZgm4a66KBVokRTbaBZ1wBsPydH\n/1x0AFz9mz0buHBBLe1i28YAZltBc+UAVJQ8bnxWNQBuDhKwUwMwXYhSGQuEL+BKRZzEWl9Pu7ar\nDMD0WUBZpYDkJr+8MYDJSVGDmz07fnwc5BEgFy4kfzYN/alZBsBZwJOTU687jAOnhc4VBmA7jWMj\nwpRjk45O5jrovNQAbOXSOfJJ2uQXNVaOp64rTg1gZEQY/7jNoypQlXtaDLomawCqCzhsIansgoy7\ndtYpoLRqAJzNQpwFbCJ9lEYKKOsuINt1kqjx3PREVgzAhO4B6nLn1ABUdA+oAQYgJyiYc+OkgLIs\nUOatBmBzM5YcHyYfTnrP9h4CibwwAE4AFTY+rfSri/U3wDwDoOqeHF/VDqCuTqRqJiam/z6NCMbV\nRTh7tshlTk4mf9Z2MdVGEZhjnOR4juNSibyA7LuAuEyHoz9Z1d+4usetvwHqcufUALhOlgInHQDA\nNxJZpBji8pBcB1BXB8yapVaI4tLQpOeUzjnojDhpAhPysa14QH4YgGmGlmULKbcG4BoD4OgeUOMO\ngBPBZLWJLO0ohBttJc1x1G7rrFNA1MhYxwHkoQsoLoWaZQooixZSF2sANmo0VOTKAXAjGJXJjTMS\nWS9C1SiEUwPgdopQo0RuCohTu8gTA1CZp6xTqKYdtAsOwDQDCDvOgdPkQoWzDiDsITlRSJZ7CLKI\nQmynQ6LSOFSWlWWR3gYD4B4AyK2zROlPVgzAdm3JFd1TCb7kO02CB+4VKSAfTKcJOJMr9xBQqZ2r\nUYjpPCQ3RUcdq7qJzEQKSFUGo6PiXqkHAM6YQT8OWo53SX+4rJRal3JR9wB+gFvV+wAA850inMnl\n7iFwNQ/JbUULjh8dpbMHE6knFfmYeCWkigy4MucyABs1mjTkQ33mqLqUi7oH2GlUoSB3DiCLCIab\nn3a1BkBNpUSNz2qfRhoFZAlVGbjgAFxJAaWRfo0ab6oBwzQDsDFPFOTKAagqOode2WhRzFMXUFqK\nHhb9pOGgw9IqNmoAXJlHHQfNZUpZ6A+3AYPrAFyrAQCFA0iE6U6RrPLTQL56kbPKE7teoJSQ9D4p\nB5s1A7CVZqOMTUs+YeNd1D0gOtAsHMCHMB1hZnmMhIt5SFsMYNYs2tg08tMzZ/IZAKAmB67hiXMA\nrheBObpnegObi7oH8IIgk22gCX0T0RgYGMBdd92F9957Dx0dHfjXf/1XtLS0XPa5jo4ONDc3o1wu\no6GhAfv371f6/iyjENM96mkuwkpFtCAmdZ9wawA20my2jdOsWWYdQMhyv4SsGYANBp0VA8ibA1AN\nRnKdAtq1axe2bt2Kt99+GzfddBN27doV+rlSqYR9+/bh4MGDysYfcKsQxaVmphbh3LnA0FD8Z3Q6\nlsbHL2+by2OhXVU+M2eKTqUgVK8toSIHrsylAw/2imfZyZNVEwXn2mnqHqBeAwhbi7lqA92zZw/u\nueceAMA999yDn/3sZ5Gf9QhvMDa9CLljdaLi4OOaWoRNTcD58/GfUb3XUik8JaIzTyapfhrdLWHP\n63nqzyyhIgcTMs/KUdpIoXJeRMNJq6SpewAvHclNNVNAdgD9/f1obW0FALS2tqK/vz/0c6VSCTff\nfDM2bdqE73//+8rfnxUN5XQBRe3wM9UFpBKFqCoLEJ4SySPL0mEAweedmBAy09mwpcoAuDI3EYz4\n4XoKKOo9Hiovoom6dpq6B6jrn2ndoyK2BrB161acOHHist9/61vfmvbvUqmEUoSEXnnlFSxduhQn\nT57E1q1bsWbNGtx4442hn33wwQcv/X1gYAvGxrZM+/8su0xUUwRyvNyVOjmpXhxNgkoUIt+ApIIo\nGppGrjf4HGkYtlmz6LTbDxU5nD8vPseB6Sg+DwVkqsOLGn/hAu91kBKqDEBV/zgpoN7efXjrrX1K\nTjEJsQ7g+eefj/y/1tZWnDhxAkuWLMHx48exePHi0M8tXboUALBo0SLceeed2L9/v5ID+KM/cqeL\nQSdFIK8tow4ZwXBfSQeIKETF8Mydq/Z93BSQyUgvzSKj501FlFQHkBQN6sghCjYaIThjVSJpF3SP\nOj4OqgxAVe5hDED1Xtes2YLm5i2Q5vKhhx5KHhQBslnasWMHHn/8cQDA448/jjvuuOOyz4yMjGDo\nw1kbHh7Gc889hw0bNih9v+k2qayiEIqBiYKK4RkaUjc8nIjYtRSQinzq6i5fGxT5qDhiHTlEwUYh\n1/ZYju6FnedDYd+UaydBhQFMTKg7StPsmwqyA/j617+O559/HqtXr8aLL76Ir3/96wCAY8eO4bbb\nbgMAnDhxAjfeeCM2btyIzZs341Of+hRuueUWpe93qQuIswhNOgDThifIAHQKbqYPs+JGtqpzHIy8\ndDuAAPOOOArBZ/U8vSAoC3bHGRt2ng83BWRK/2QbaNwb+WTaTyU1E8a+uTumKSDvA1iwYAFeeOGF\ny35/5ZVX4uc//zkAYPny5Th06BDp+7kRTBYbwcLGu84A/ItQGn+VdJVrbaCq8pGRV3Pz1Ni8MIBK\nRRgXlYJ1VJ95Gukjqu75ry0/74oDKJdFbn9kJLq2w9E9IGf7AGwjqyiEs0kp7NqmHYCK4VEtPgZp\nqO5zcpxsFtEpcHnkZasIrCOHKATnSUc+pus7acknqH/cGkCa+sfRPYAX4FKRKweQx06EtFNAnCIw\nJVLzI63jNjiFQlMOIIsUkC7TCYsw0yq0U8aGjXelBgAkF4ILBmAQWfUiu1wDaGwUBj5uXx2nCJyW\nstkwTqr3HfbMeUkBcR1Alh1EVAfACb5kzSQtBqAbfJlswKAidw7AdhQSljt1hQHU14vvunAh+jOc\nInBadJvTAsdt9UuLAZhoAw2uRR1H51oKSOe+TTkAyia/OJhkAKblQ0WuHAC3jU3VAYTl5lyoAQDJ\nxodDQ9NKAXHyn2Fn5HAMI6ULKE0GEHTQWaaAbOsewK9L2da9pBoANwWUmzZQ28iyDXR8fHqaxRUG\nACQbH90ohJoO4bSBcowTwJvjsM4nV2sAYdGwznNSAxkTTRR+/eEW6V3SPZMMgJoCMtkG6qwDyOqt\nRLIX2dVFmGR8dI4g4Cpb2B4ClfEc+iuvzcmNc2sASZHgxIS4J+4RBGHRcFYMQFU+5bLQoSBDozou\nl4Ivk11AwUCkUhF7DOoVGvPDuuiocNYBBIU5OSkUi/OyBWoU4hINNckAwpRNR1GDRlh1D0FUdJqG\nopuoAahEgqobguIQxlaoDqBSET8qBoZzVAdgVj6u6Z4tBiBlq7JmgrrHQW4cgM4EmXAAeY5C0mgD\nDc7R6CivR51jYLIoApuSQRzC2ArVAYyPi9+loT+mU3TVqHuc+ltY+oiKXDkA6iICqmsR2upE4FB1\nTpQH8CO9NNtApQyi2nFNdAAB4UZC9VRZk7l0gKd/1RR8JaVf09K9mksBcZRcjq+WQpSpXmROvpWj\n5KZTQFwGoNsFNGOGyHVHKaEtBjA6qucATHXTAOk5Wc5ZTVnrHjcFxNEfKpx2AP4dn1wDw1nAo6Pq\nBT2O41JBtTIArqJTUyOULiAgPh1gygGErUNVB8A1pJzzfEyuDdd0z2YKiBPgUuG0A6B2ephmADqK\n50IUQu1E4FB1TnpC99pZF4GB+IKgiXOAgMvlo8sATKUxdcdzHQDV6blQBOZ04HECKCqcdgDUCZKd\nDhMTtPEuL8I4BjAxISI36hvBuFRdx4AHz33nRHppGSc/4uTgSgqI4wC4NTRT6yovugfwj2HRtU+E\nV61fBmcdADdSM2ncOIuQmmKIwrx5wLlz4f+n237IMRKcBRy21yItRTfFAJLkYKMIzOm00plfudva\nH0BxdvPqpuhMBV9p6h7AP4ZFdY7q60W7tV8+VDjrAGbPphcogenKIydKpQcacJsBzJsHDA6G/59u\n94lJqk5x0FI+nqdn3EwekcBxAGfPhv+fqS4gkwxA5924pZL4rDxzSm5SUj1Tp1oZQJzMAd5hcBz9\n4cBZBzBr1vRDz3QnyL8IdSMBkzUAUy+llmhpiV6EupFnVkXg4LVlhKj63mSugaFGp360tEQ7YpsM\nQKcITHUewfFyflWZJWeDoeu6FyVzIL19AHK8iUKwsw4gjAFQJ4gyuZxFSO1iUEHcIjx3Tp8BcFJA\nphaw7hwF1wYnBURNE5iUQxRMFto5c0zRPVOBRV50b3xcv/7GWYdV7wDCGIBuCojqADjU20+dAfF3\nncgrCXEpoMFBYP589e/i1klMMQBKdBqcY6ri2UgB6cohChxjGJYCos4xR/fk+DQYgG3dmzVLpMLC\nDO/goHAQVJZEmeOqTgEFozwTFFZnrMlFmFYK6MwZ8f+q4LaiZeUAOHNsygHERYO6cogCxxhy9rIA\n0/WPo3tAejWA4LowzQBKpWj9S1P35PiqZgD19VMHwAH6htS/kLiTqxNJBKNTXeVJQpzh0Y08TURq\nshWNkwKiRKcc+ZhoA41zxC4wAG407F/HFN0z1VzA0T3TDACIlruuzOvrhe5I+1bUAAIolS43EtRF\nyK2w6ypecAGbjEKamsR3hrWAcaMQnXutq5tedNOdY7+B4jIAnUjPZAoozhGbYACcaFiemit39HKi\n+LQdgKu6B0TLnSJzv3w5AS4HzjoAYLpAR0b0JsgfSXCMk26Lou0UUKkENDeH9yPrLkKOA5DjTcwx\nJT0hx05OCidEzY3bSgGZYABhtSjdOR4ZEX/Xla1/jjm6NzkpnJBqfjvMubuSAgKi5U6RuX8tcnSP\nA6cdQFYMwL+Q5Dn3qj3QnAWsiqgoRHcRBiO1kRFgzhzaeN05njNnyjhxolNpFKnFN91nlkgqApti\nAJw6GIdlmdI9nWPcg/cMuFUEBqLlTmUA/gCXqnscOO0A/AK9cIE+QboLmGOcbDMAID4PmSYD4NRZ\ngrKlzjElcvI/M9UBREWC4+NizZg4C4gbTMyZw2NZfv3JQvcA/cK3vy5VzQygJhyAqShEV8mDiuOi\nAzDFALgOwISj5IzlOgBd4yaR5IS5bwMDeMYQ4DlZU0Vgju4Bes8s61JUm6ECU8EXwK8B+OeJCqcd\nAEfROYvQnzvl5Kfl+LRSQBQGwEmHNDZOzxM3NqqPDbIsqmxNMACKkTBZDIxCmANIs86SRfDl1z0g\n3cBCBSbl7tc/ju5x4LQDMEUlKVEIJz+dlxRQ8NTUNOfYJAPgtJBSU0CzZ4szcoKdGKYKwIAwEOPj\nU/LRdbJZMQBTugfw9M9l9g3wUkDBeaKicAAhCHZA6BonTuFOBSYXIXeOh4fF3zlzzDHiFPYQ7PCi\nGImoTUEmGUCpND0lkqaTdUH3PI9WH6LuL1GB6RSQCd3jwGkHwEkBNTZOTZBunje4gKlRlzzzXvZk\nm0IYDfU8sTDnzdP7Lm6+Vs7T8HB6LIu7LvzX1TmELogwOZhkAMB0BzA8zGMA1FRmVrp38aKQjY7+\ncNJeKjDVgQeY0z0OnHYAXBrqj051x1KVTtL2SmXqnk0UBP0Ii0KGhsS1dJ2Nf544xpTjKNM0bFK2\nk5P0ArCEbQYAmAtG0kylBNeFbgeR7OTRXRcAb22owCQD4OheTTgA/0JKcxH6C1G6i9C/g9lG+gcI\nTwFRDU9Tk5lFyKH658/rtU1yqHNd3ZRxoxaAJaLkYJoBjIwIg8iZY911zNE9TmrQ38nDdQBppl8p\ncjelexw47QD8E0SJ4qmLMJjaoC5CaoExCfPnAwMD039HPYBM0nVKuiqrOeZETsDUM3PlY1IOUZDz\ndPGi3oZE4PJARsfJcnSPE3wBU8+sy3iAy+t3pvUvTOaeRwvA/Kkyiv5UfQ2gqWnqBehpMwBq5ARM\nLWBTb4YK4oorgFOnpv+OGnnKOaakq0wxAF3jNHeuGQfATRGYlEMU5Bzr1lgAHsvi6B4nMACm7puj\ne4Ad/Vu4UMjc/z7ekRHhnHVfLGTKvnHgtANobMxmEXIZgBSsrtKpIszwcBkAxRiaTAHpzLFfcShv\n3zLFAEzKIQqcaNhfy9KdY47umWIAHN2bmBC1OJOvhJT3Vi5Pj765ugcUKaBQ+BVd15tz6JWkztRC\nVFOTMEzyJe2msWgRcPLk9N+dPCl+rwu/MaRE0pw0DnWsNE6eR5tjUw7ApByiINcihQEE9YfKAHR1\nTwZfsm5BDSw4uief13QDBnC53Lm6B9BS3DXlAM6dE6dgqiIYnepMbkODKEaNjdEW4dy50xehacyf\nL77ffyT0Bx8Aixfrf5efrehG0hyW5Zetbgqovl7Q7QsXaPdtMwVElUMUOAxAnhrreTSWJWWrq3tS\nf8bH6SkgqgOwrXvA5XLn6h5Ad7JcOO8AhodFS+XoqH6UyMlDSuFQFyHVqKqgrk44gdOnp35HXYRy\nnnSVHJgyTpOTeu+rBaYfac2ZY04KiMvQwhiALQfAMYaygKxT4M8yzWZC9yj3rIqg3Lm6J9teqafp\ncuC0A5BUf2hI/J1aoKREA/PmCQNFibzyFIWYcACUArLfAehGp8CUkaAap5ERcX3djXN+BGVQqYh8\n8MKF9O8MQqY0KIbUvw5159dfA6C85N7fCEHVvWpnAEHdo9o3Dpx2AH4l1zVOfgZAadGS535zFqGt\nGgAgFlx//9S/T57k0VCKA+A8Z5AB6I7353qp0Sll57QfQRmcPi3WmTxjyQTkxiPKOpRzTDGG/hQQ\nR/+y0j2bDiAod24KiKN7XOTGAVCjvMlJsQh1FZ2zCIOFKBu48krg2LGpf2fBAOSmGErr4+zZIkdM\nrbP41wa1CHz2rP4z+7F4sTD68rWLptM/wNQ6pDwnxxj603sU/ZM6QHGyzc183bMZfLmge/JICn87\nKgW5cAAUClouizFnzojv0J1guQgp1/Yrnq08ZFvb9EV47BiwZIn+90iqz3EAlDY4+WpLaoqCk+ud\nO1c8LzcFVF8vFP/ECfFvqgzi4J/jBQv0xnIcQLksajrnzgkHp1ssX7BA3DOHARS6F40ZM0TNQKbp\nqMiFA6BQUEBEpe+9JyZaZwclMLUIT5/Wz+mmQUP9UYjMtVJa0fzKpjvH8+dPKTll81NzszCe5TJ9\nEw3FASxcKOTKTQEB0+XQ0wMsW8b7viCkfAYG9OfYnwLSdbCAmOPjx8X86rZTyh2zlDnOk+4BdLlz\ndAT5y4sAAAsNSURBVA8Qcxz1XmpVOO0AWlqEgaFEAoCIQrq7aZs0ZCFqYIAWeVHTE6q48kqgr0/8\nvbcXaG+nnWp5xRVC0dJmAIC4Xnc3zXFxagALFkwZJ04KCLjcAXzkI7zvC0LOMXUdDg3RTyhtaREB\nFFX3qAxAOq486J7n0eXO0T2gBhxAY6OY4BMnaItw/nzgN7+hRXncKOTsWdEpcMUV+tdWQVubMPwA\nL/KUHQ0UYzhzpkiD9PXRGcBvfkObI3nflOBAMgBuCggwJ4coyHVIMeJNTYId9vfTctSLFwPvvkvX\nvawYgG3dk05/clJcq1SiraPmZtFBd/IkzQHIAJkDpx1AqSSiw7ffpkWYXAZw7JgwcLonCra2CqXr\n7xd/t4EVK4RyAmYcADUKaWmhz3Fzs3gGiqK2tgJHjwoF0r32woV04xTEypXAO++Iv9twABwGUFcn\nDOKRIzSWxdW93l7aGTn+tJeuA5C6d+KEPd2bM0fcV18fT+alkvie7u4cMoAf//jHWL9+PcrlMg4c\nOBD5ub1792LNmjVYtWoVHn30Ue3rLF4MHDwoUhy6mD9fTC5FyVtahHHSVTpARAjHj9tdhEuWCON3\n5oxQ0hUraN8jD7fq76cZCTnHFAawaBFw+DDdARw6BCxdqp+fXrBARJeU7rAgVq8W8w/w5BAFDgMA\nBEM5eJDOALLSvcFBISNKCqhcFrKwpXuAkPuvf82X+RVXAL/6FU33MmUAGzZswE9/+lN8/OMfj/xM\npVLBAw88gL179+Lw4cN44okn8NZbb2ldZ9Ei+iJcsAD4v/+jTe6yZcCBA7RNPUuXishgYGDq2vv2\n7dP/ohiUSmIRHjkCvPEGsGED7XtmzRKpnDfeADo69Me3tABvvrmPFCV2dACvv05zAEuWiHWxdKn+\n2IULRevesWNq6ypOdtIBnDsnqPzy5fr3E4eWFtEqeOwYLRhpbxfrOE4Hop4vS93r7qZ1PgEiADt0\naKozx7TuAVNyf/NNuu4BYu2//jpN9zJlAGvWrMHq1atjP7N//36sXLkSHR0daGhowN13342nn35a\n6zqLF4uiDoVmLVki0gRr1uiPXblSGAnKApw7V/S319VNbQqysQjXrRMLneMAgKmIi6LoK1YAvb37\nSFFQR4dQcioDGBkRyq4L2b20cKFaei9OdlddJdjTq68Keeh2myWhXBbz1NNDi+Lb24UDiRsb9XxS\n9yjrYskSYcQputfaKoKnSoX2OtUrrxRrQzIAW7r3P//D170rrhC6R3EA994L3HIL/dqA5RpAX18f\nlvksd3t7O/pk+VwRUsEpi3DzZvHn2rX6Y6VANm7UHysxOUkfq4KbbgIee0woOCfylC2CFGXr6hJ/\ndnbqj/3oR8Wfq1bpj5XRHcVBy+cMnuNDQUMD8Fu/BfzFXwA33MD/vjBUKuJPSgpIzg/FUcoxbW36\nY+W6oBg2mdKjHqst8+mmN+X58clPAs8+C/zXf/HkLmNoqQs66Oqi2TY/Yh3A1q1bsWHDhst+/u3f\n/k3py0sGzmL98peFQCmL8LrrxJ9XX60/Vh7MtGWL/lgA+Nu/BX7yE9pYVfzO7wh6f/fdvMjzy1+m\nj+3qEvKhpMoka7jzTv2xra3AX/0V8Pu/rz8WEApsqmB7113AL38J3HOPme8LYulSujG84QYRKFB0\nYMcOEXhdc43+WHluEfW+GxrE9Sm4917g//0/8+8C8OOaa0TgtWgRL/i6917xp8kjxLXgMbFlyxbv\n9ddfD/2/X/ziF962bdsu/fvhhx/2du3aFfpZAMVP8VP8FD/FD+GHCiPHVnkRB1Js2rQJR44cwdGj\nR3HllVfiqaeewhNPPKH1HQUKFChQwA7INYCf/vSnWLZsGV577TXcdttt2L59OwDg2LFjuO222wAA\n9fX12L17N7Zt24Z169bhrrvuwlpu0qpAgQIFChhByStC7wIFChSoSWS+E5i7UcwFfOELX0Brays2\n+PrBBgYGsHXrVqxevRq33HILBn0Nu4888ghWrVqFNWvW4LnnnsvilrXQ09OD3/7t38b69etxzTXX\n4Dvf+Q6A6njG0dFRbN68GRs3bsS6devw53/+5wCq49n8qFQq6Orqwu233w6gup6vo6MD1157Lbq6\nunDDhy051fR8g4OD+MxnPoO1a9di3bp1+O///m9zz0euHhjAxMSEt2LFCq+7u9sbGxvzOjs7vcOH\nD2d5SyS89NJL3oEDB7xrrrnm0u/+9E//1Hv00Uc9z/O8Xbt2eX/2Z3/meZ7n/epXv/I6Ozu9sbEx\nr7u721uxYoVXqVQyuW9VHD9+3Dt48KDneZ43NDTkrV692jt8+HDVPOPw8LDneZ43Pj7ubd682Xv5\n5Zer5tkk/uZv/sb7gz/4A+/222/3PK+61mdHR4d3+vTpab+rpuf7wz/8Q++f/umfPM8Ta3RwcNDY\n82XqAF599dVpXUKPPPKI98gjj2R4R3R0d3dPcwBXX321d+LECc/zhAG9+uqrPc+7vBNq27Zt3i9+\n8Yt0b5aJ3/3d3/Wef/75qnvG4eFhb9OmTd6bb75ZVc/W09Pj3XTTTd6LL77ofepTn/I8r7rWZ0dH\nh3fq1Klpv6uW5xscHPSuuuqqy35v6vkyTQGZ2CjmKvr7+9H64VbE1tZW9H/4Drljx46h3berLW/P\nfPToURw8eBCbN2+ummecnJzExo0b0draeinVVS3PBgB/8id/gm9/+9uo850XXk3PVyqVcPPNN2PT\npk34/ve/D6B6nq+7uxuLFi3C5z//eVx33XX44z/+YwwPDxt7vkwdgImNYnlAqVSKfda8zMP58+fx\n6U9/Gn/3d3+HuYEzgvP8jHV1dTh06BB6e3vx0ksv4T//8z+n/X+en+3f//3fsXjxYnR1dUW2Wuf5\n+QDglVdewcGDB/Hss8/i7//+7/Hyyy9P+/88P9/ExAQOHDiAL37xizhw4AAaGxuxa9euaZ/hPF+m\nDqCtrQ09PT2X/t3T0zPNe+UZra2tOPHhuwKPHz+OxR/uSw8+c29vL9oo25xTxvj4OD796U/jc5/7\nHO644w4A1feM8+bNw2233YbXX3+9ap7t1VdfxZ49e3DVVVfhs5/9LF588UV87nOfq5rnA4ClH54I\nuGjRItx5553Yv39/1Txfe3s72tvbcf311wMAPvOZz+DAgQNYsmSJkefL1AH4N4qNjY3hqaeewg7q\n/m/HsGPHDjz++OMAgMcff/yS0dyxYweefPJJjI2Nobu7G0eOHLnUueAqPM/Dfffdh3Xr1uGrX/3q\npd9XwzOeOnXqUgfFhQsX8Pzzz6Orq6sqng0AHn74YfT09KC7uxtPPvkkPvnJT+JHP/pR1TzfyMgI\nhoaGAADDw8N47rnnsGHDhqp5viVLlmDZsmV4+8Mzx1944QWsX78et99+u5nnM1qxIOCZZ57xVq9e\n7a1YscJ7+OGHs74dEu6++25v6dKlXkNDg9fe3u794Ac/8E6fPu3ddNNN3qpVq7ytW7d6Z86cufT5\nb33rW96KFSu8q6++2tu7d2+Gd66Gl19+2SuVSl5nZ6e3ceNGb+PGjd6zzz5bFc/4v//7v15XV5fX\n2dnpbdiwwfvrv/5rz/O8qni2IPbt23epC6hanu83v/mN19nZ6XV2dnrr16+/ZEOq5fk8z/MOHTrk\nbdq0ybv22mu9O++80xscHDT2fMVGsAIFChSoUWS+EaxAgQIFCmSDwgEUKFCgQI2icAAFChQoUKMo\nHECBAgUK1CgKB1CgQIECNYrCARQoUKBAjaJwAAUKFChQoygcQIECBQrUKP4/6UbTi3pLErYAAAAA\nSUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcbfea9f10>"
]
}
],
"prompt_number": 470
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"Yay, it's phase continous. Sorry about the global\n",
"\n",
"And as a square wave"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.plot(get_afsk(len_afsk=10, sq=True, dh=3/1.6)) # test out the different deviations for high/low tone"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 471,
"text": [
"[<matplotlib.lines.Line2D at 0x7fbcc04a3750>]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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wAnDej4gvVgAScOsOieKqA733OlkDcMpGxM7pdsci68571JdZ3FIiKo4zxTh3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\n8SicABiGYTwKJwCGYRiPwgmAYRjGo/w/fWhTnntcgMEAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcbfd5bcd0>"
]
}
],
"prompt_number": 471
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Plots a set of afsk spectrums\n",
"\n",
"def plot_afsk_spectrum(afsks, num=\"\", sr=samp_rate, p_avg=True, p_max=True):\n",
" S = sr/(1200*15)\n",
" len_afsk = 25\n",
"\n",
" n_afsk = (len_afsk/1200)*samp_rate # Total number of samples\n",
" \n",
" win = blackman(len(afsks[0]))\n",
" \n",
" ffts = [fft(afsk*win) for afsk in afsks]\n",
"\n",
" yf_average = average(ffts, axis=0)\n",
" yf_maximum = amax(ffts, axis=0)\n",
"\n",
" xf = np.linspace(0.0, 0.5*sr/S, n_afsk/(2*S))\n",
" \n",
" if p_avg:\n",
" avg, = plt.semilogy(xf, 2* 2.0 * np.abs(yf_average[0:n_afsk/(2*S)]), label='Avg'+num)\n",
" if p_max:\n",
" maxi, = plt.semilogy(xf, 2.0 * np.abs(yf_maximum[0:n_afsk/(2*S)]), label='Max'+num)\n",
" \n",
" if p_avg and p_max:\n",
" plt.legend(handles=[avg,maxi])\n",
" \n",
" plt.grid()\n",
" \n",
"def plot_afsk_spectrum2(afsks1, afsks2, p_avg=True, p_max=True):\n",
" plot_afsk_spectrum(afsks1, \"1\", p_avg=p_avg, p_max=p_max)\n",
" plot_afsk_spectrum(afsks2, \"2\", p_avg=p_avg, p_max=p_max)\n",
" plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 472
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see that while on average the energy is at 1.2kHz and 2.2kHz there's actually things going to up to 3kHz or so"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"afsks = [get_afsk() for x in range(100)]\n",
"\n",
"plot_afsk_spectrum(afsks)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Zs2cjKioKKSkp2LdvH1JTU2UW82/6v9g2bBs+6/UZdLU11065rIzWDlIXbm5A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\nw4aAYRhmiMOGgGEYZojDhoBhGGaI838xKnzupus8vgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc00c5e50>"
]
}
],
"prompt_number": 473
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"Let's compare that with the squarewave"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"afsks = [get_afsk(sq = False) for x in range(100)]\n",
"afsks_sq = [get_afsk(sq = True) for x in range(100)]\n",
"\n",
"plot_afsk_spectrum2(afsks, afsks_sq)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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qlSI0NFSsWrXKeOyXX34pwsPDhVqtFkII8eOPP4rAwEBRUlJi8vmUSqU4deqUycfaWyNL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\nMbbIcSFgjLFFjgsBY4wtcv8D2TXZEXUeiUcAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc00ddf50>"
]
}
],
"prompt_number": 474
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hmm the square wave is less that 10dB down at ~4kHz. Not great"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# What happens when we add a filter?\n",
"Let's tune the deviation ratios too"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Start by defining the tx data rate `DATA_RATE` and oversampling ratio `TXOSR` "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"tx_data_rate = 1600\n",
"tx_osr = 10\n",
"\n",
"# Our filter samples at the product of these two values\n",
"filter_samp_rate = tx_data_rate * tx_osr"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 475
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Deviation for high tone\n",
"devl = devh = 1800 # Not sure how this works"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 476
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"# Which fir filter to use\n",
"fir = p_si_fir_coeff"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 477
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"afsks = [get_afsk(sq = False, sr=filter_samp_rate, dl=devl, dh=devh) for x in range(100)]\n",
"afsks_filtered = [convolve(afsk, fir, mode='valid') for afsk in afsks] \n",
"\n",
"afsk_time = get_afsk(len_afsk=12, sq = False, sr=filter_samp_rate, dl=devl, dh=devh)\n",
"plt.plot(convolve(afsk_time, fir, mode='valid'))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 478,
"text": [
"[<matplotlib.lines.Line2D at 0x7fbcc0c93550>]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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5oi9x7decQUcHuz/T0+3fo7pz6fHj8fMFAL8Y+C1fAPhYDHTsVhiNagL5s8/Y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\n5XXOYMAA9s9qz3qvS1tFnYG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XyCQ6TCSaLwB6OoPTp9UW+MhcwBQmIqyYOZNdF6LXI9DT\nGSRLuDh6B4VLl9i9eM01XvfKGmUxeP7555GSkoLmKC9UUVGB/Px8FBYWYuvWrV2v7927F8XFxcjP\nz8ejjz7K3UZ0aenRo8D48aq9dh/VnIFqmCU6gSyz2jM6TCSaPAZ6958SyAQAlJSwQVw2TBQ9QUkG\nMQC6Q0XHjgHXXuvfEmslMairq8O2bdtw7bXXdr1WU1ODTZs2oaamBlVVVVi+fDmMLwrWH3nkEaxb\ntw6hUAihUAhVVVVc7URXEx07lhxiEBsmUqkmknEG0QnkM2eAq64SOz7WkpMzIHSQlgaUlcnNjqPd\ntp/DLbGYYnDkCJCX53Vv7FESg8cffxx///d/3+O1yspKLFq0CGlpaRg7dizy8vKwa9cuNDY2orW1\nFSUlJQCABx54AJs3b+ZqxwwTdXQAn3wCjB2r0uvEEFtaqhImklnCrhomUnUGlDMg7Ni4Efj618WP\ni3YGyZIzALrFIBQC8vO97o090mJQWVmJYDCI66+/vsfrDQ0NCAaDXd8Hg0GEw+Fer+fm5iIcDnO1\nNWwYG1A/+YTNcJNhYImOb6omkGVqk6MTyKqbgukIEyXD34xIDOnp4quPgd7OIFnEwFyFHAr52xk4\nRq/Kyspw8uTJXq8/88wzqKio6JEPMKL3LtDMgAHsD79/f3IkjwHg6quBvXvZ1147gzNngJEjxY6n\nMBHhN5I5Z3D2LAsTyTiiROEoBtu2bbN8/cMPP0RtbS2mTJkCAKivr8f06dOxa9cu5Obmoq6uruu9\n9fX1CAaDyM3NRX19fY/Xc3NzbdteuXJl19elpaXIyirFnj3JkS8A2AwgFGJfy1QTRc+sdTiDwkKx\n46PDRDqqiSiBTKgS7QxkJihe4WaYqLq6GtXV1VrOJZXXnjx5Mpqamrq+HzduHPbu3YsRI0agvLwc\nixcvxuOPP45wOIxQKISSkhIEAgEMHToUu3btQklJCTZs2IAf/OAHtm1EiwHArNbevcCtt8r0OPHk\n57M/vmHoCROJOoPMTDaYt7Wpl5bKxGcpTEToJpmdwaFDQFMTMGaM3nOXlpaitLS06/tVq1ZJn0tL\nkVMgahlgUVERFi5ciKKiIqSmpmLt2rVdP1+7di0efPBBXLx4EXPmzMHdd9/N3cbw4UwMli7V0WP3\nGTGChbdOn5arJooNE4kOpoEAcweffSZXTaQzgVxXBxQUiB1PELEka85gxAi2DYefy0oBTWJw7Nix\nHt+vWLECK1as6PW+6dOn44MPPpBqIyuLDWrJEiYCut2BF84A6C4v9SKBHC0Ghw4BX/ua2PEEEUus\nMxg1ytv+8JKVBRw4AMya5XVPnEmKFchA9yZryZJABlje4MgRbxadAd1JZB1hIpVqoo8+AiZOFDue\nIGJJ5pxBe7u/y0qBJBODIUPEwx1eouIMVLejAJgzOHuWCYLoik9dK5BbWlioKqqqmCCkuOIK9sS+\nzz9PvjAR4O+yUiDJxOC66/y/S2E0ZkWRjBgMGsQ2qOvoUHMGJ06wtkVjlarOYMAA9hn27WOVTMn0\ndyP8yYABbKO7P/85OcWAnIEmsrKSK18AsD/+gQNskY3oYBwIdC9ck3UGw4ezvZxkNgVTLS0F2DF/\n/SuFiAh9LFsGrFuXXGJghrj9LgY+zm33ZMEC4I47vO6FGHl5LF4uuuDLxAy1yDqDYcPkxUDVGQDs\nZt2zB5g6VfxYgrCivBxYvrx7IWoykJ4O/PSn+stKdZM0zmDkSKCoyOteiHHllWx2LhoiMsnIYCGm\n7duB4mLx401nIJNnycpiiWdAfh+YzExyBoReBg4EFi9mNfvJkkAGgKef9ndZKZBEYpCs5OXJi8EV\nVwC//S0bzG+7Tfx4FWdwww0s3m8Y8s4gI4PlLEgMCJ0sW8b+TxZnkCz4XKuSn/x8tuhKhowM4IUX\n2C6PMglYs7RURgyys5mIHTumFiZKTU2+XA/hb6ZMAX7+cyAnx+ue9C1IDFwmL6/ng+lFyMhgA+mc\nOXLHDx/O/pctx73xRhbmURGDvDy2hz1B6OSxx7zuQd+DxMBlpk0DPv1U7ti8POArX5Evyxw2jP0v\n4wwAJgZ79qhVE1GIiCCSAxIDl/na1+S3Yvi//1etbdMZyIrBjBnA//7frMRUprQ1MzM5HkREEASJ\nQZ9G1RlMnw7s3s3WHMg8jOShh7oFiSAIf0Ni0IdRzRmMGAHk5rLtJGS4+Wa54wiCSDxUWtqHUXUG\nAMsbUAkfQfR9SAz6MKmpbOW27ApogIlBMi3uIQhCDhKDPs6//RtbDi/LrbeqiQlBEMlBwHDzSfaS\nBAIB+LBb/Zb2dv8vpScIQm3sJGdAxIWEgCD6PiQGBEEQBIkBQRAEQWJAEARBgMSAIAiCAIkBQRAE\nARIDgiAIAiQGBEEQBEgMCIIgCJAYEARBECAxIAiCIKAoBr/85S8xceJETJ48GU8++WTX6xUVFcjP\nz0LxCLsAAAhjSURBVEdhYSG2bt3a9frevXtRXFyM/Px8PProoypNEwRBEBqRFoM33ngDW7ZswYED\nB/Dhhx/i7/7u7wAANTU12LRpE2pqalBVVYXly5d3bZz0yCOPYN26dQiFQgiFQqiqqtLzKTyiurra\n6y5wkQz9TIY+AtRP3VA//YO0GPzmN7/BT37yE6SlpQEARn6xz3FlZSUWLVqEtLQ0jB07Fnl5edi1\naxcaGxvR2tqKkpISAMADDzyAzZs3a/gI3pEsF0gy9DMZ+ghQP3VD/fQP0mIQCoXw5ptv4uabb0Zp\naSn27NkDAGhoaEAwGOx6XzAYRDgc7vV6bm4uwuGwQtcJgiAIXThuTlxWVoaTJ0/2ev2ZZ55Be3s7\nzp49i507d+Kvf/0rFi5ciGPHjrnWUYIgCMJFDEnuvvtuo7q6uuv78ePHG59++qlRUVFhVFRUdL0+\ne/ZsY+fOnUZjY6NRWFjY9fof/vAH47vf/a7luQHQP/pH/+gf/ZP4J4v0Y0vmzZuHHTt24I477sDh\nw4cRiURw1VVXoby8HIsXL8bjjz+OcDiMUCiEkpISBAIBDB06FLt27UJJSQk2bNiAH/zgB5bnNugp\nZwRBEAlFWgyWLVuGZcuWobi4GOnp6fjtb38LACgqKsLChQtRVFSE1NRUrF27FoFAAACwdu1aPPjg\ng7h48SLmzJmDu+++W8+nIAiCIJTw5TOQCYIgiMTiqxXIVVVVKCwsRH5+Pp599lmvu9NFXV0d7rzz\nTkyaNAmTJ0/GL37xCwBAc3MzysrKUFBQgFmzZqGlpcXjnjI6OjowdepUzJ07F4A/+9nS0oIFCxZg\n4sSJKCoqwq5du3zZz4qKCkyaNAnFxcVYvHgxLl++7Hk/ly1bhuzsbBQXF3e95tQnu0WgXvTziSee\nwMSJEzFlyhTce++9OHfunC/7afL8888jJSUFzc3Nvu2n6OJfW6SzDZppb283xo8fb9TW1hqRSMSY\nMmWKUVNT43W3DMMwjMbGRmP//v2GYRhGa2urUVBQYNTU1BhPPPGE8eyzzxqGYRhr1qwxnnzySS+7\n2cXzzz9vLF682Jg7d65hGIYv+/nAAw8Y69atMwzDMNra2oyWlhbf9bO2ttYYN26ccenSJcMwDGPh\nwoXGyy+/7Hk/33zzTWPfvn3G5MmTu16z69PBgweNKVOmGJFIxKitrTXGjx9vdHR0eNbPrVu3drX/\n5JNP+rafhmEYn3zyiTF79mxj7NixxpkzZ3zZzx07dhhf/vKXjUgkYhiGYZw6dUq6n74Rg3feeceY\nPXt21/exVUl+4mtf+5qxbds2Y8KECcbJkycNw2CCMWHCBI97Zhh1dXXGzJkzjR07dhhf/epXDcMw\nfNfPlpYWY9y4cb1e91s/z5w5YxQUFBjNzc1GW1ub8dWvftXYunWrL/pZW1vbY1Cw69Pq1auNNWvW\ndL1v9uzZxrvvvutZP6P505/+ZNx///2GYfiznwsWLDDef//9HmLgt37ed999xuuvv97rfTL99E2Y\nKBwOY/To0V3fm4vV/Mbx48exf/9+3HTTTWhqakJ2djYAIDs7G01NTR73Dnjsscfw3HPPISWl+0/r\nt37W1tZi5MiReOihhzBt2jR85zvfwYULF3zXzxEjRuBHP/oRxowZg2uuuQbDhw9HWVmZ7/oJ2P+N\n7RaB+oGXXnoJc+bMAeC/flZWViIYDOL666/v8brf+im6+NcJ34iBWXHkZ86fP4/58+fjxRdfxJAh\nQ3r8LBAIeP4ZXnnlFYwaNQpTp061Lc/1Qz/b29uxb98+LF++HPv27UNGRgbWrFnT4z1+6OfRo0fx\nwgsv4Pjx42hoaMD58+fxu9/9rsd7/NDPWOL1yQ/9feaZZ5Ceno7Fixfbvserfn7++edYvXo1Vq1a\n1fWa3f0EePv7jF78+9xzz2HhwoW2743XT9+IQW5uLurq6rq+r6ur66FsXtPW1ob58+djyZIlmDdv\nHgA2AzNXaDc2NmLUqFFedhHvvPMOtmzZgnHjxmHRokXYsWMHlixZ4rt+BoNBBINBzJgxAwCwYMEC\n7Nu3Dzk5Ob7q5549e3DLLbfgyiuvRGpqKu699168++67vusnYH8txt5X9fX1yM3N9aSPJi+//DJe\nffVV/P73v+96zU/9PHr0KI4fP44pU6Zg3LhxqK+vx/Tp09HU1OSrfgLsXrr33nsBADNmzEBKSgpO\nnz4t1U/fiMGNN96IUCiE48ePIxKJYNOmTSgvL/e6WwDYrODb3/42ioqK8MMf/rDr9fLycqxfvx4A\nsH79+i6R8IrVq1ejrq4OtbW12LhxI+666y5s2LDBd/3MycnB6NGjcfjwYQDA9u3bMWnSJMydO9dX\n/SwsLMTOnTtx8eJFGIaB7du3o6ioyHf9BOyvxfLycmzcuBGRSAS1tbVdi0C9oqqqCs899xwqKysx\naNCgrtf91M/i4mI0NTWhtrYWtbW1CAaD2LdvH7Kzs33VT6B78S+AXot/hfupJ62hh1dffdUoKCgw\nxo8fb6xevdrr7nTx1ltvGYFAwJgyZYpxww03GDfccIPx2muvGWfOnDFmzpxp5OfnG2VlZcbZs2e9\n7moX1dXVXdVEfuzne++9Z9x4443G9ddfb3z96183WlpafNnPZ5991igqKjImT55sPPDAA0YkEvG8\nn9/85jeNq6++2khLSzOCwaDx0ksvOfbpmWeeMcaPH29MmDDBqKqq8qyf69atM/Ly8owxY8Z03UeP\nPPKIb/qZnp7e9fuMZty4cV0JZL/1MxKJGN/61reMyZMnG9OmTTPeeOMN6X7SojOCIAjCP2EigiAI\nwjtIDAiCIAgSA4IgCILEgCAIggCJAUEQBAESA4IgCAIkBgRBEARIDAiCIAgA/x/dnlEOFHSgNgAA\nAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc164e810>"
]
}
],
"prompt_number": 478
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot_afsk_spectrum2(afsks, afsks_filtered, p_max=False) # Average"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ZEnNbv9gwmG0Ili1bhtTUVJ11vb29SE5ORmpqKnJycrBp0ybkXn1a33777fj9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\nuK54yDLfSnuLNp/cTEREEQci6Mf8Hwec09vbS729vertnKo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UFhaGoqIilJaWorOzEwcP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\nYDzmsEDAYDAYjzn/H8It+qCYyoc+AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc00dd450>"
]
}
],
"prompt_number": 479
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot_afsk_spectrum2(afsks, afsks_filtered, p_avg=False) # Maximum"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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4cbb658kTfStRDS+vqmMWQvHgAQsOL11adV+5nFXvNTcnWrmStT16xFxK8fHa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\ncTIQCCFEHycDgRBC9HEyEAghRB/3H/7qUspT5+PxAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc0716810>"
]
}
],
"prompt_number": 480
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### And for a squarewave input"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"afsks = [get_afsk(sq = True, sr=filter_samp_rate, dl=devl, dh=devh) for x in range(100)]\n",
"afsks_filtered = [convolve(afsk, fir, mode='valid') for afsk in afsks] \n",
"\n",
"afsk_time = get_afsk(len_afsk=12, sq = True, sr=filter_samp_rate, dl=devl, dh=devh)\n",
"plt.plot(convolve(afsk_time, fir, mode='valid'))\n",
"plt.grid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Bdz4nJwepqalIT0/HTs7gup2egR1hIrVmANAGe9w4oKSE/TxmaGmh9kZprFjt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\ncnIyACA+Ph4zZ87sc9WUB6O3XVbm7515sX9/ZSU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hISEhBEkGAnBLHNENdrrBRkDaaTek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\nGBARETgGREQEjgEREYFjQEREAP4AfVQ7QqIud50AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc039c390>"
]
}
],
"prompt_number": 484
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot_afsk_spectrum2(afsks, afsks_filtered, p_max=False) # Average"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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63uTWJJcSAnaG0dZWcSGQqxx66SVKzLMYDMCTTyr+KIrQhBCI9a77Qgi++IJE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\nAJxtOct5LsASySHJUHYo0dnfyY6p+9RwVbk6TIMlAj0C4ePqw3uOAAB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UUlBQQPr6+njX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\ne7Xi6OLJdAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbcc06da650>"
]
}
],
"prompt_number": 482
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot_afsk_spectrum2(afsks, afsks_filtered, p_avg=False) # Maximum"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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kUpqoEBHR9LllZdQ4BQa2IwNACB2iLs8M8PCgfyyqTl7Flfr+vkppw8UBZDIZ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\nS3V1dZLw+uCDD2jnzp20efNmImL/HSYnJ9Pg4GBQG2un3bt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"text": [
"<matplotlib.figure.Figure at 0x7fbcc1943790>"
]
}
],
"prompt_number": 483
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 483
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 483
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 483
}
],
"metadata": {}
}
]
}