| Line 9... |
Line 9... |
| 9 |
"cells": [ |
9 |
"cells": [ |
| 10 |
{ |
10 |
{ |
| 11 |
"cell_type": "markdown", |
11 |
"cell_type": "markdown", |
| 12 |
"metadata": {}, |
12 |
"metadata": {}, |
| 13 |
"source": [ |
13 |
"source": [ |
| 14 |
"Uk\u00e1zka pou\u017eit\u00ed n\u00e1stroje IPython na manipulaci se senzorov\u00fdmi daty z modulu ALTIMET01A\n", |
14 |
"P\u0159esn\u00e9 m\u011b\u0159en\u00ed tlaku a jeho pou\u017eit\u00ed k ur\u010den\u00ed nadmo\u0159sk\u00e9 v\u00fd\u0161ky\n", |
| 15 |
"=======\n", |
15 |
"=======\n", |
| 16 |
"\n", |
16 |
"\n", |
| 17 |
"P\u0159\u00edklad vyu\u017e\u00edv\u00e1 modulovou stavebnici MLAB a jej\u00ed Python knihovnu [pymlab](https://github.com/MLAB-project/MLAB-I2c-modules)\n", |
17 |
"P\u0159\u00edklad vyu\u017e\u00edv\u00e1 modulovou stavebnici MLAB a jej\u00ed Python knihovnu [pymlab](https://github.com/MLAB-project/MLAB-I2c-modules)\n", |
| 18 |
"\n", |
18 |
"\n", |
| 19 |
"Pou\u017eit\u00fd sn\u00edma\u010d [MPL3115A2](http://www.freescale.com/webapp/sps/site/prod_summary.jsp?code=MPL3115A2) m\u00e1 n\u00e1sleduj\u00edc\u00ed katalogov\u00e9 parametry: \n", |
19 |
"Pou\u017eit\u00fd sn\u00edma\u010d [MPL3115A2](http://www.freescale.com/webapp/sps/site/prod_summary.jsp?code=MPL3115A2) m\u00e1 n\u00e1sleduj\u00edc\u00ed katalogov\u00e9 parametry: \n", |
| Line 1870... |
Line 1870... |
| 1870 |
"ph=data['preassure']" |
1870 |
"ph=data['preassure']" |
| 1871 |
], |
1871 |
], |
| 1872 |
"language": "python", |
1872 |
"language": "python", |
| 1873 |
"metadata": {}, |
1873 |
"metadata": {}, |
| 1874 |
"outputs": [], |
1874 |
"outputs": [], |
| 1875 |
"prompt_number": 24 |
1875 |
"prompt_number": 3 |
| 1876 |
}, |
1876 |
}, |
| 1877 |
{ |
1877 |
{ |
| 1878 |
"cell_type": "markdown", |
1878 |
"cell_type": "markdown", |
| 1879 |
"metadata": {}, |
1879 |
"metadata": {}, |
| 1880 |
"source": [ |
1880 |
"source": [ |
| Line 2059... |
Line 2059... |
| 2059 |
"pl=data['preassure']" |
2059 |
"pl=data['preassure']" |
| 2060 |
], |
2060 |
], |
| 2061 |
"language": "python", |
2061 |
"language": "python", |
| 2062 |
"metadata": {}, |
2062 |
"metadata": {}, |
| 2063 |
"outputs": [], |
2063 |
"outputs": [], |
| 2064 |
"prompt_number": 25 |
2064 |
"prompt_number": 1 |
| 2065 |
}, |
2065 |
}, |
| 2066 |
{ |
2066 |
{ |
| 2067 |
"cell_type": "code", |
2067 |
"cell_type": "code", |
| 2068 |
"collapsed": false, |
2068 |
"collapsed": false, |
| 2069 |
"input": [ |
2069 |
"input": [ |
| Line 2210... |
Line 2210... |
| 2210 |
{ |
2210 |
{ |
| 2211 |
"metadata": {}, |
2211 |
"metadata": {}, |
| 2212 |
"output_type": "display_data", |
2212 |
"output_type": "display_data", |
| 2213 |
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kSOuPxRinT3NxS2sLACCTCGzduhXBwcH47LPPUF5ejujoaMTExCAtLQ2JiYlY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\noy0sgq7/u7VW8zhCHDYVAW9vb6xYsQI//vgjNm7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kSOuPxRinT3NxS2sLACCTCGzduhXBwcH47LPPUF5ejujoaMTExCAtLQ2JiYlY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\noy0sgq7/u7VW8zhCHDYVAW9vb6xYsQI//vgjNm7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|
| 2214 |
"text": [ |
2214 |
"text": [ |
| 2215 |
"<matplotlib.figure.Figure at 0x7f04e70453d0>" |
2215 |
"<matplotlib.figure.Figure at 0x7fd03e30b090>" |
| 2216 |
] |
2216 |
] |
| 2217 |
} |
2217 |
} |
| 2218 |
], |
2218 |
], |
| 2219 |
"prompt_number": 59 |
2219 |
"prompt_number": 4 |
| 2220 |
}, |
2220 |
}, |
| 2221 |
{ |
2221 |
{ |
| 2222 |
"cell_type": "code", |
2222 |
"cell_type": "code", |
| 2223 |
"collapsed": false, |
2223 |
"collapsed": false, |
| 2224 |
"input": [ |
2224 |
"input": [ |
| Line 2238... |
Line 2238... |
| 2238 |
{ |
2238 |
{ |
| 2239 |
"metadata": {}, |
2239 |
"metadata": {}, |
| 2240 |
"output_type": "display_data", |
2240 |
"output_type": "display_data", |
| 2241 |
"png": 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fP0737t257bbbeP/999m/fz9JSUmmt4gVEbkhQ8Iytfx7/Kr8er527dol5iQuWrRoUYl5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\niFSNMkOisLCQoqI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Dhg0b+Oqrr8q8LIJIVbphrt0kUlnCwsKYPHkyWVlZbNiwgXfffZeM\njAyio6NJSEjAarWya9cu/vKXvwDFl6Bu3bq1626JLVu2BGD79u1s2LCBtLQ0AIqKijh16hQAa9eu\nxcvLS189SbWnkYTIH3h4eDBkyBCio6MZOHAgv/zyC8OGDePTTz913eTo3nvv5YcffgCKL7e8fft2\n7rnnHtfyF18zbNgw1q1bx9dff83QoUOpX78+ACtWrMDf358FCxZUwRqKXD1d4E/kMg4dOkRgYCB7\n9uxh7Nix7N27lzvvvBOn08ndd9/NwoULiYqKYt++fZw7d44JEybwxBNP4HA4WLBgAS1atCA/P5+o\nqCgOHjxITk4O48aNIzIykqZNm7Jr1y7OnDlDUFAQ3377Lc2aNavqVRa5LIWEiIiY0tdNIiJiSiEh\nIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJiSiEhIiKm/j99TrGB0ZKj+wAAAABJRU5ErkJg\ngg==\n", 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fP0737t257bbbeP/999m/fz9JSUmmt4gVEbkhQ8Iytfx7/Kr8er527dol5iQuWrRoUYl5\nA6fTSWFhYYnHnp6eAHh5lf6veu6559i8eTORkZH07t2bwsLCEv15e3u7fr44R7Fy5Ur+9re/MWnS\nJAYMGECrVq345JNPTGu/lm0tItWD8er17/huyJC43IpbYm+8nVl4eDhxcXEMHz4cHx8f3n77bXr1\n6kWjRo3o3LkzixYtYsyYMWzdupWtW7eWWn7NmjVMnTqV/v37c/jwYRITExk5cqTp+xmGwdq1a+nX\nrx/PPPMM58+fZ9asWRQVFZkvUwG/ZCJy47ohQ+JGY3ZkUmRkJIcOHSIoKAin00nz5s359NNPAVi6\ndClPPvkk77//PoGBgdx7772l+nvllVeYNGkSM2fOpFGjRgwePPiKd56yWCxER0czfPhwOnXqhL+/\nPw899BBvvPFGBa6tiNxMdO0mMaVtKnLz0LWbRESkwikkRETElEJCRERMKSRERMSUQkJEREwpJERE\nxJRCQkRETCkkRETElFtCwul0Eh0djc1mw+FwsG/fvhLtCQkJBAUFYbPZWLRokev5WbNmYbPZ6Nq1\nK0uWLHFHaVUiNTWV3r1706FDB9q1a8f//M//sHPnTgDCwsI4ffr0FZe/2hsNiYhUNLdcliM+Pp78\n/HxSUlJIS0sjJiaG+Ph4AAoKCpg4cSLp6en4+Phgt9vp378/O3fuZNOmTaSkpHDmzBnmzp3rjtIq\n3YULF3jwwQdZu3YtHTt2BODTTz/l/vvvZ//+/axdu1ZnNYtIteWWkcTGjRuJiIgAii9znZ6e7mrL\nyMggMDAQq9WKt7c3ISEhJCcns2bNGtq1a8eAAQPo168f/fv3d0dple7s2bNkZ2eTm5vreu6xxx7j\n3XffJSoqCoDevXvz66+/0qRJE7Zs2eJ6nW5BKiJVzS0jiZycnBL3KPD09MTpdOLh4UFOTg5Wq9XV\n5uvrS3Z2NidPnuTgwYOsXLmS/fv3079/f3bt2nXZ/mNjY10/h4aGEhoaWmZNFXXJ6/JeFdXf35+5\nc+cSERHBn/70J+x2Ow6Hg0cffZR+/fqxePFi1q1bR/369bFYLCUuBljeW5aKiFyUlJREUlLSdffj\nlpDw8/Mr8ZfzxYAAsFqtJdpyc3OpV68et912G61atcLLy4sWLVpQq1YtTp48SYMGDUr1f2lIXK2q\nvOT1s88+y9NPP01SUhLJycnMmTOHOXPmkJaWVmU1icjN7Y9/QE+dOvWa+nHL1012u51Vq1YBxZO2\n7du3d7W1atWKPXv2kJWVRX5+PsnJydhsNkJCQvj2228BOHLkCGfOnOG2225zR3mVauPGjbz++uvU\nqVOHBx54gDlz5rBjxw48PDxYu3Ztidf+8SqN+fn5lV2uiEgJbhlJDBw4kMTEROx2OwBxcXEsXbqU\nvLw8oqKimDdvHuHh4TidTiIjIwkICOCBBx4gOTnZdW+F995776b4uqVhw4bMmDGD4OBgevbsCcDh\nw4c5c+YM7dq1w9PT0xUGDRs2ZPPmzXTu3JnU1FSOHj1alaWLiOh+EpUhKSmJV199lV9++QUfHx+s\nViuxsbGEhYXxyCOPsGXLFlasWMHx48cZM2YMtWrVonPnzmzbto358+dTv3592rdvT05OTqXWXZ23\nqYiUz7V+nhUSYkrbVOTmoZsOiYhIhVNIiIiIKYWEiIiYUkiIiIgphYSIiJhyy3kSVcHf3/+mOK+i\nOvH396/qEkSkit00h8CKiIg5HQIrIiIVTiEhIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJi\nSiEhIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJiSiEhIiKmFBIiImJKISEiIqbcEhJOp5Po\n6GhsNhsOh4N9+/aVaE9ISCAoKAibzcaiRYtcz9933304HA4cDgeRkZHuKE1ERMrBLbcvjY+PJz8/\nn5SUFNLS0oiJiSE+Ph6AgoICJk6cSHp6Oj4+Ptjtdh566CF8fX0BWLdunTtKEhGRa+CWkcTGjRuJ\niIgAIDg4mPT0dFdbRkYGgYGBWK1WvL29CQkJYf369fz000+cPXuW8PBw+vTpQ1pamjtKExGRcnDL\nSCInJwc/Pz/XY09PT5xOJx4eHuTk5GC1Wl1tvr6+ZGdn06pVKyZPnkxkZCR79uzh/vvvJzMzEw+P\n0jkWGxvr+jk0NJTQ0FB3rIaIyA0rKSmJpKSk6+7HLSHh5+dHbm6u6/HFgACwWq0l2nJzc/H396dF\nixYEBgYC0Lx5c2677TaOHj3KnXfeWar/S0NCRERK++Mf0FOnTr2mftzydZPdbmfVqlUApKam0r59\ne1dbq1at2LNnD1lZWeTn55OcnEz37t2Ji4sjJiYGgCNHjpCTk0NAQIA7yhMRkatkMQzDqOhODcNg\n7NixbNu2DYC4uDi2bNlCXl4eUVFRfPPNN0ybNg2n00lkZCRjxoyhsLCQJ598koMHDwIwd+5cunXr\nVrpgiwU3lCwiclO71n2nW0LCnRQSIiLld637Tp1MJyIiphQSIiJiSiEhIiKmFBIiImJKISEiIqYU\nEiIiYkohISIiphQSIiJiSiEhIiKmFBIiImJKISEiIqZMLxU+bNiwKy5osVj47LPPKrwgERGpPkxD\nYteuXfz9738vdUGoixeJevbZZ91enIiIVC3Tq8Bu2LCBkJAQ1+PCwkK8vLxM2yuLrgIrIlJ+FX4V\n2CZNmmCz2cjKygLg888/Jzg4mMOHDwNUSUCIiEjlMh1JPPDAA0RFRTFgwADXc19++SUff/wxK1as\nqLQC/0gjCRGR8qvwkUReXl6JgAAYMmQIp0+fLn91IiJyQzINCbPE0V/xIiI1h2lIBAUF8fbbb5d4\n7p133qF9+/ZuL0pERKoH05B47bXX2LlzJ3fccQf33XcfTZs2ZefOncybN68y6xMRkSpkOnF9UX5+\nPqdOnaJBgwZ4e3tXVl2mNHEtIlJ+17rvLDMkqhuFhIhI+VX40U0iIiJuCQmn00l0dDQ2mw2Hw8G+\nfftKtCckJBAUFITNZmPRokUl2o4fP07jxo3JzMx0R2kiIlIOZYbEnXfeiZeXFwEBAXh7e+Pr60vz\n5s1Zs2aN6TLx8fHk5+eTkpLC7NmziYmJcbUVFBQwceJEEhMTWb9+PR988AHHjx93tT3zzDPUqVOn\nAlZNRESuV5kh0bNnT3bs2MHRo0fZtWsXAwcOZNWqVbz88sumy2zcuJGIiAgAgoODSU9Pd7VlZGQQ\nGBiI1WrF29ubkJAQkpOTAZg8eTJjxowhICDgetdLREQqQJkhcejQIVq2bAlAs2bNOHjwIM2bN7/i\nkU45OTn4+fm5Hnt6euJ0Ol1tVqvV1ebr60t2djaLFy+mYcOGhIWFATppT0SkOjC9VPhFAQEBTJky\nhe7du7Np0yYCAgJITEzklltuMV3Gz8+P3Nxc12On04mHR3EeWa3WEm25ubnUq1ePt99+G4vFwtq1\na9m6dSsjR47k66+/5vbbby/Vf2xsrOvn0NBQQkNDr2ZdRURqjKSkJJKSkq67nzIPgT137hwffPAB\nu3btom3btkRGRvLvf/+bpk2bXnYHDrBs2TISEhKIi4sjNTWV6dOns3LlSqB43qFNmzakpaVRp04d\nbDYbCQkJJb5icjgcLFiwgBYtWpQuWIfAioiU27XuO8scSXh7e1OnTh0aNGhA27ZtycvLo3v37ldc\nZuDAgSQmJmK32wGIi4tj6dKl5OXlERUVxbx58wgPD8fpdBIZGak5CBGRaqrMkURkZCR33nkna9as\nYcqUKXzwwQesWrWqsuorRSMJEZHyc9vJdPv27WPatGnUrl2bAQMGkJ2dfU0FiojIjafMkCgqKuLk\nyZNA8STzxQloERG5+ZU5J/Haa69hs9n47bffCA4O5q233qqMukREpBq46gv8nThxggYNGmCxWNxd\n0xVpTkJEpPwq/Ogmh8Nh+kbff/99ud9IRERuPKYh8eWXXwIwadIkHnvsMXr06EFqair//Oc/K604\nERGpWqaz0A0aNKBBgwYcPHiQvn37UqtWLUJDQ9m1a1dl1iciIlWozIlrT09PPvzwQ7p27cqGDRt0\nhVYRkRqkzInrY8eOMWPGDHbv3k3r1q15+eWXqV+/fmXVV4omrkVEyq/Cb186ZcoUZs+ebbpgWe3u\nopAQESm/Cg+JRo0a0adPH9MFv//+e44dO1buN7xeCgkRkfKr8JBISkq6YqcWi4VevXqV+w2vl0JC\nRKT8KjwkqiuFhIhI+bntAn8iIlJzKSRERMRUmedJbNq0ibi4OAoLC3E6nRw9epTvvvuuMmoTEZEq\nVuZIYsyYMTgcDrKzs2nSpAnBwcGVUZeIiFQDZYZEgwYNGDZsGL6+vsTGxpKenl4ZdYmISDVQZkh4\nenry888/c+7cOXbt2sWhQ4cqoy4REakGyjwE9ueff2bnzp3ccccdTJgwgccff5xnn322suorRYfA\nioiUn9sOgU1NTWXo0KGEhISwZcsW3b5URKQGMR1JLF26lBUrVvD999/Tu3dvAJxOJ9u3b2fnzp2V\nWuSlNJIQESm/Cr8zXUREBAEBAZw8eZLo6GgAPDw8aNq06bVXKSIiN5SruizHypUr2bFjBy1btuSh\nhx6qjLpMaSQhIlJ+bpuTmDJlCh999BG33HILS5YsISYmpsxOnU4n0dHR2Gw2HA4H+/btK9GekJBA\nUFAQNpuNRYsWAVBUVMTo0aMJCQmhR48e7Nixo9wrIyIiFavMM66Tk5NJSUkBYMKECVd1Ml18fDz5\n+fmkpKSQlpZGTEwM8fHxABQUFDBx4kTS09Px8fHBbrfTv39/UlJS8PDwYMOGDaxfv54XX3zRtYyI\niFSNMkOisLCQoqIiPD09cTqdV3V008aNG4mIiAAgODi4xAl4GRkZBAYGYrVaAQgJCSE5OZnBgwfT\nr18/AA4cOIC/v/81rZCIiFScMkPikUcewW63061bN9LS0njkkUfK7DQnJwc/Pz/X40sDJicnxxUQ\nAL6+vmRnZ7teN2rUKJYvX85XX311LesjIiIVqMyQiImJISwsjN27d/PUU0/Rtm3bMjv18/MjNzfX\n9fjSEYjVai3RlpubW2LUsHjxYubMmUNwcDAZGRnUrl27VP+xsbGun0NDQwkNDS2zJhGRmiQpKYmk\npKTr7sf06Kbnn3/+8gtYLMycOfOKnS5btoyEhATi4uJITU1l+vTprFy5Eiiek2jTpg1paWnUqVMH\nm81GQkICa9eu5ddff+X5558nJyeHjh07kpGRwa233lrq/XV0k4hI+VT4eRItW7bEYrFcUzEDBw4k\nMTERu90OQFxcHEuXLiUvL4+oqCjmzZtHeHg4TqeTyMhIAgICGDx4MKNGjaJXr14UFBTw1ltvlQoI\nERGpXGWeJ3Hu3Dnmz59PZmYm7dq1IyoqCm9v78qqrxSNJEREys9t50kMHz6cw4cPEx4ezn/+8x8i\nIyOvqUAREbnxlDlxfeLECZYvXw7AgAEDCAkJcXtRIiJSPZQ5kmjevDnbt28His9faNy4sduLEhGR\n6qHMOQmbzcaxY8do1KgRJ0+exMvLCy8vLywWC9u2bausOl00JyEiUn7Xuu+8qgv8AZw6dYr69etf\n8xFPFUUhISJSfhV+COxF69evZ9y4cRQVFTF06FDuuusuTV6LiNQQZY4kevToQXx8PIMHD+brr78m\nNDSUH3/8sbLqK0UjCRGR8nPbIbAeHh7cdtttQPHlNi69JpOIiNzcygyJwMBApkyZwqlTp5g1axZ3\n3313ZdQlIiLVgGlIDB06FID58+dz9913ExISQt26dVm4cGGlFSciIlXLdOL6xIkTAHh7ezNmzJhK\nK0hERKoP04nru+++m8cee6zURMfVXAXWnTRxLSJSfhV+CKyPjw8tW7a8rqJEROTGZhoSf/rTnxg5\ncmRl1iIiItWM6cR1586dK7MOERGphq76shzVheYkRETKz20n04mISM2lkBAREVMKCRERMaWQEBER\nUwoJERExpZAQERFTCgkRETGlkBAREVNuCQmn00l0dDQ2mw2Hw8G+fftKtCckJBAUFITNZmPRokUA\nFBQU8MQTT9CzZ0+Cg4NJSEhwR2kiIlIOZd7j+lrEx8eTn59PSkoKaWlpxMTEEB8fDxSHwcSJE0lP\nT8fHxwd/HM5QAAAL5klEQVS73U7//v1ZtWoVDRs25OOPPyYrK4uOHTvSr18/d5QnIiJXyS0hsXHj\nRiIiIgAIDg4mPT3d1ZaRkUFgYCBWqxWAkJAQkpOTGTJkCIMHDwaKRyJeXm4pTUREysEte+KcnJwS\n98L29PTE6XTi4eFBTk6OKyAAfH19yc7Opk6dOgDk5uYyZMgQZsyY4Y7SRESkHNwSEn5+fuTm5roe\nXwwIAKvVWqItNzcXf39/AA4dOsSgQYMYN24cjz76qGn/sbGxrp9DQ0MJDQ2t2BUQEbnBJSUlkZSU\ndN39uOUqsMuWLSMhIYG4uDhSU1OZPn06K1euBIrnJNq0aUNaWhp16tTBZrORkJCAh4cHoaGhvPfe\nezgcDvOCdRVYEZFyu9Z9p1tCwjAMxo4dy7Zt2wCIi4tjy5Yt5OXlERUVxTfffMO0adNwOp1ERkYy\nZswYJkyYwJdfflnibnirV6+mVq1aJQtWSIiIlFu1Cgl3UkiIiJSf7ichIiIVTiEhIiKmFBIiImJK\nISEiIqYUEiIiYkohISIiphQSIiJiSiEhIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJiSiEh\nIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJiSiEhIiKmFBIiImJKISEiIqYUEiIiYkohISIi\nptwaEk6nk+joaGw2Gw6Hg3379pVoT0hIICgoCJvNxqJFi0q0paWl4XA43FmeiIiUwcudncfHx5Of\nn09KSgppaWnExMQQHx8PQEFBARMnTiQ9PR0fHx/sdjv9+/enUaNGzJ07l08++YS6deu6szwRESmD\nW0cSGzduJCIiAoDg4GDS09NdbRkZGQQGBmK1WvH29iYkJITk5GQAAgMDWbZsGYZhuLM8EREpg1tD\nIicnBz8/P9djT09PnE6nq81qtbrafH19yc7OBmDQoEF4ebl1kCMiIlfBrXtiPz8/cnNzXY+dTice\nHsW5ZLVaS7Tl5ubi7+9/Vf3Gxsa6fg4NDSU0NLRC6hURuVkkJSWRlJR03f1YDDd+p7Ns2TISEhKI\ni4sjNTWV6dOns3LlSqB4TqJNmzakpaVRp04dbDYbCQkJBAQEAHDgwAGGDRvGpk2bShZssehrKBGR\ncrrWfadbRxIDBw4kMTERu90OQFxcHEuXLiUvL4+oqCjmzZtHeHg4TqeTyMhIV0BcZLFY3FmeiIiU\nwa0jCXfQSEJEpPyudd+pk+lERMSUQkJEREwpJERExJRCQkRETCkkRETElEJCRERMKSRERMSUQkJE\nREwpJERExJRCQkRETCkkRETElEJCRERMKSRERMSUQkJEREwpJERExJRCQkRETCkkRETElEJCRERM\nKSRERMSUQkJEREx5VXUB18JiqeoKRESqP8O4/j5uyJCoiBUXEZGy6esmERExpZAQERFTbgkJp9NJ\ndHQ0NpsNh8PBvn37SrQnJCQQFBSEzWZj0aJFV7WMlJaUlFTVJVQb2ha/07b4nbbF9XNLSMTHx5Of\nn09KSgqzZ88mJibG1VZQUMDEiRNJTExk/fr1fPDBBxw/fpz4+HguXLhw2WXk8vQB+J22xe+0LX6n\nbXH93DJxvXHjRiIiIgAIDg4mPT3d1ZaRkUFgYCBWqxWAkJAQkpOT2bRpE/fff/9llxERkarhlpFE\nTk4Ofn5+rseenp44nU5X28WAAPD19SU7O/uKy4iISNVwy0jCz8+P3Nxc12On04mHR3EeWa3WEm25\nubnUq1fvistcqlmzZlh0ooTL1KlTq7qEakPb4nfaFr/TtijWrFmza1rOLSFht9tJSEhgyJAhpKam\n0r59e1dbq1at2LNnD1lZWdSpU4fk5GQmT56MxWIxXeZSe/fudUfJIiJyGRbDqPhT0wzDYOzYsWzb\ntg2AuLg4tmzZQl5eHlFRUXzzzTdMmzYNp9NJZGQkY8aMuewyLVq0qOjSRESkHNwSEiIicnO4YU6m\nq+nnURQUFPDEE0/Qs2dPgoODSUhIYO/evYSEhNCzZ0/Gjh1LTcv748eP07hxYzIzM2v0tpg1axY2\nm42uXbuyZMmSGrstnE4no0ePdq377t27a9y2SEtLw+FwAJiu+8KFC+natSvdu3dn5cqVZXdq3CD+\n7//+z3jyyScNwzCM1NRU46GHHqriiipXXFyc8eyzzxqGYRinT582GjdubPTv399Yv369YRiGER0d\nbSxfvrwqS6xU+fn5xoABA4yWLVsau3btMvr161cjt8W6deuMfv36GYZhGHl5ecYrr7xSY38vVq9e\nbQwdOtQwDMNITEw0Bg0aVKO2xZw5c4x27doZ3bt3NwzDuOxn4ujRo0a7du2M/Px8Izs722jXrp1x\n4cKFK/Z7w4wkrnTuRU0wZMgQpk2bBhT/xeTt7c2PP/5Iz549Abj//vtZu3ZtVZZYqSZPnsyYMWMI\nCAgAqLHbYs2aNbRr144BAwbQr18/+vfvz5YtW2rktqhduzbZ2dkYhkF2dja33HJLjdoWgYGBLFu2\nzDViuNxnYvPmzdjtdry9vfHz8yMwMNA1D2zmhgmJmn4eRZ06dahbty65ubkMGTKE1157rcT6161b\nl+zs7CqssPIsXryYhg0bEhYWBhQfKGFc8jVCTdoWJ06cYMuWLXz11VfMnz+f4cOH19htYbfbOX/+\nPK1ateKZZ55h/PjxNWpbDBo0CC+v3w9YvXTdLz0f7XLnqV3JDRMSV3sexc3s0KFD9O7dmxEjRjBs\n2LAS63/xfJOaIC4ujsTERBwOB1u3bmXkyJGcOHHC1V6TtkWDBg0ICwvDy8uLFi1aUKtWrRIf+pq0\nLebOnYvdbmf37t1s3bqVESNGUFBQ4GqvSdsCKLF/yMnJuez5aLm5ufj7+1+5H7dVWMHsdjurVq0C\nuOJ5FDerY8eOERYWxty5cxk1ahQAnTp1Yv369QCsXr3aNbS82a1fv56kpCTWrVtHx44d+cc//kFE\nRESN3BYhISF8++23ABw5coSzZ8/Sp0+fGrktzpw54/q2wd/fn8LCwhr7GYHL7x+CgoL44YcfuHDh\nAtnZ2WRkZNC2bdsr9nPD3HRo4MCBJCYmYrfbgeK/JmuSmTNnkp2dzbRp01xzE2+99Rbjx48nPz+f\n1q1bM3jw4CqusmpYLBbeeOMNoqKiaty2eOCBB0hOTiYoKAin08l7771HkyZNauS2mDx5Mk8++SQ9\nevSgoKCAWbNm0blz5xq3LS5ekeJynwmLxcL48ePp0aMHTqeTmTNncsstt1y5P8O4yY8JExGRa3bD\nfN0kIiKVTyEhIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIpWsSZMm5OfnV3UZIldFISFSyXT7\nXbmRKCRE/uDhhx8mOTkZgPT0dG699VYcDgcOh4M///nPREZGUlhYyOOPP47dbqdbt2588cUXAISG\nhvLII48QFhZGfn4+kZGR9OrVix49ergukQDFF1+bP38+Dz/8sEYVUq0pJET+ICoqiiVLlgDFl39Z\nvnw569at4/XXX6dJkybMmzeP+fPnc/vtt7Nx40bWrl3LSy+9xKlTp7BYLAwfPpw1a9bw4Ycf0rBh\nQ9avX098fDzjxo1zvcc777zDhg0b+Oqrr8q8LIJIVbphrt0kUlnCwsKYPHkyWVlZbNiwgXfffZeM\njAyio6NJSEjAarWya9cu/vKXvwDFl6Bu3bq1626JLVu2BGD79u1s2LCBtLQ0AIqKijh16hQAa9eu\nxcvLS189SbWnkYTIH3h4eDBkyBCio6MZOHAgv/zyC8OGDePTTz913eTo3nvv5YcffgCKL7e8fft2\n7rnnHtfyF18zbNgw1q1bx9dff83QoUOpX78+ACtWrMDf358FCxZUwRqKXD1d4E/kMg4dOkRgYCB7\n9uxh7Nix7N27lzvvvBOn08ndd9/NwoULiYqKYt++fZw7d44JEybwxBNP4HA4WLBgAS1atCA/P5+o\nqCgOHjxITk4O48aNIzIykqZNm7Jr1y7OnDlDUFAQ3377Lc2aNavqVRa5LIWEiIiY0tdNIiJiSiEh\nIiKmFBIiImJKISEiIqYUEiIiYkohISIiphQSIiJiSiEhIiKm/j99TrGB0ZKj+wAAAABJRU5ErkJg\ngg==\n", |
| 2242 |
"text": [ |
2242 |
"text": [ |
| - |
|
2243 |
"<matplotlib.figure.Figure at 0x7fd03e275390>" |
| - |
|
2244 |
] |
| - |
|
2245 |
} |
| - |
|
2246 |
], |
| - |
|
2247 |
"prompt_number": 5 |
| - |
|
2248 |
}, |
| - |
|
2249 |
{ |
| - |
|
2250 |
"cell_type": "markdown", |
| - |
|
2251 |
"metadata": {}, |
| - |
|
2252 |
"source": [ |
| - |
|
2253 |
"Z nam\u011b\u0159en\u00fdch hodnot je mo\u017en\u00e9 spo\u010d\u00edtat v\u00fd\u0161ku. Pou\u017eijeme k tomu barometrickou rovnici. " |
| - |
|
2254 |
] |
| - |
|
2255 |
}, |
| - |
|
2256 |
{ |
| - |
|
2257 |
"cell_type": "code", |
| - |
|
2258 |
"collapsed": false, |
| - |
|
2259 |
"input": [ |
| - |
|
2260 |
"from sympy import *\n", |
| - |
|
2261 |
"init_printing()\n", |
| - |
|
2262 |
"\n", |
| - |
|
2263 |
"#p0 = Symbol('p_0')\n", |
| - |
|
2264 |
"#l = Symbol('L')\n", |
| - |
|
2265 |
"#cp = Symbol('C_p')\n", |
| - |
|
2266 |
"#t0 = Symbol('T_0')\n", |
| - |
|
2267 |
"#g = Symbol('g')\n", |
| - |
|
2268 |
"#m = Symbol('M')\n", |
| - |
|
2269 |
"#r = Symbol('R')\n", |
| - |
|
2270 |
"#p = Symbol('p')\n", |
| - |
|
2271 |
"#h = Symbol('h')\n", |
| - |
|
2272 |
"\n", |
| - |
|
2273 |
"po = Symbol('po')\n", |
| - |
|
2274 |
"l = Symbol('l')\n", |
| - |
|
2275 |
"cp = Symbol('cp')\n", |
| - |
|
2276 |
"to = Symbol('to')\n", |
| - |
|
2277 |
"g = Symbol('g')\n", |
| - |
|
2278 |
"m = Symbol('m')\n", |
| - |
|
2279 |
"r = Symbol('r')\n", |
| - |
|
2280 |
"p = Symbol('p')\n", |
| - |
|
2281 |
"h = Symbol('h')\n", |
| - |
|
2282 |
"\n", |
| - |
|
2283 |
"bf = Eq(po*(1 - (l*h)/to)**((g*m)/(r*l)), p)\n", |
| - |
|
2284 |
"\n", |
| - |
|
2285 |
"bf" |
| - |
|
2286 |
], |
| - |
|
2287 |
"language": "python", |
| - |
|
2288 |
"metadata": {}, |
| - |
|
2289 |
"outputs": [ |
| - |
|
2290 |
{ |
| - |
|
2291 |
"latex": [ |
| - |
|
2292 |
"$$po \\left(- \\frac{h l}{to} + 1\\right)^{\\frac{g m}{l r}} = p$$" |
| - |
|
2293 |
], |
| - |
|
2294 |
"metadata": {}, |
| - |
|
2295 |
"output_type": "pyout", |
| 2243 |
"<matplotlib.figure.Figure at 0x7f04e72c54d0>" |
2296 |
"png": "iVBORw0KGgoAAAANSUhEUgAAAMQAAAA5BAMAAACbhJmfAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\n27jGBHDM01qo4RvdYgkTer/nUAAAAABJRU5ErkJggg==\n", |
| - |
|
2297 |
"prompt_number": 26, |
| - |
|
2298 |
"text": [ |
| - |
|
2299 |
" g\u22c5m \n", |
| - |
|
2300 |
" \u2500\u2500\u2500 \n", |
| - |
|
2301 |
" l\u22c5r \n", |
| - |
|
2302 |
" \u239b h\u22c5l \u239e \n", |
| - |
|
2303 |
"po\u22c5\u239c- \u2500\u2500\u2500 + 1\u239f = p\n", |
| - |
|
2304 |
" \u239d to \u23a0 " |
| - |
|
2305 |
] |
| - |
|
2306 |
} |
| - |
|
2307 |
], |
| - |
|
2308 |
"prompt_number": 26 |
| - |
|
2309 |
}, |
| - |
|
2310 |
{ |
| - |
|
2311 |
"cell_type": "markdown", |
| - |
|
2312 |
"metadata": {}, |
| - |
|
2313 |
"source": [ |
| - |
|
2314 |
"Ze kter\u00e9 vyj\u00e1d\u0159\u00edme v\u00fd\u0161ku v z\u00e1vislosti na tlaku a dosad\u00edme nam\u011b\u0159en\u00e9 tlaky a zn\u00e1m\u00e9 konstanty." |
| - |
|
2315 |
] |
| - |
|
2316 |
}, |
| - |
|
2317 |
{ |
| - |
|
2318 |
"cell_type": "code", |
| - |
|
2319 |
"collapsed": false, |
| - |
|
2320 |
"input": [ |
| - |
|
2321 |
"#bf.subs(p0, 101325,simultaneous=True); # standardn\u00ed tlak v Pa na hladin\u011b mo\u0159e\n", |
| - |
|
2322 |
"#bf.subs(l, 0.0065,simultaneous=True); # Pokles teploty s v\u00fd\u0161kou [K/m]\n", |
| - |
|
2323 |
"#bf.subs(cp, 1007,simultaneous=True); # specifick\u00e9 teplo p\u0159i konstantn\u00edm tlaku J/(kg\u2022K)\n", |
| - |
|
2324 |
"#bf.subs(t0, 288.15,simultaneous=True); # standardn\u00ed teplota na hladin\u011b mo\u0159e K\n", |
| - |
|
2325 |
"#bf.subs(g, 9.80665,simultaneous=True); # standardn\u00ed gravita\u010dn\u00ed zrychlen\u00ed na povrchu zem\u011b\n", |
| - |
|
2326 |
"#bf.subs(m, 0.0289644,simultaneous=True); # mol\u00e1rn\u00ed hmotnost such\u00e9ho vzduchu\tkg/mol\n", |
| - |
|
2327 |
"#bf.subs(r, 8.31447,simultaneous=True); # univerz\u00e1ln\u00ed plynov\u00e1 konstanta J/(mol\u2022K)\n", |
| - |
|
2328 |
"\n", |
| - |
|
2329 |
"bfh=solve(bf, h)\n", |
| - |
|
2330 |
"\n", |
| - |
|
2331 |
"#bfh.subs([(p0,101325), (l,0.0065), (cp,1007), (t0,288.15), (g,9.80665), (m,0.0289644), (r, 8.31447), (p, 98296.0)],simultaneous=True).evalf()\n", |
| - |
|
2332 |
"\n", |
| - |
|
2333 |
"\n", |
| - |
|
2334 |
"\n", |
| - |
|
2335 |
"#bf.subs(p, 98296.0)\n", |
| - |
|
2336 |
"#N(bf,5)\n", |
| - |
|
2337 |
"#bf.evalf(n=3)" |
| - |
|
2338 |
], |
| - |
|
2339 |
"language": "python", |
| - |
|
2340 |
"metadata": {}, |
| - |
|
2341 |
"outputs": [], |
| - |
|
2342 |
"prompt_number": 27 |
| - |
|
2343 |
}, |
| - |
|
2344 |
{ |
| - |
|
2345 |
"cell_type": "code", |
| - |
|
2346 |
"collapsed": false, |
| - |
|
2347 |
"input": [ |
| - |
|
2348 |
"lambdify(bf,h)" |
| - |
|
2349 |
], |
| - |
|
2350 |
"language": "python", |
| - |
|
2351 |
"metadata": {}, |
| - |
|
2352 |
"outputs": [ |
| - |
|
2353 |
{ |
| - |
|
2354 |
"ename": "SyntaxError", |
| - |
|
2355 |
"evalue": "invalid syntax (<string>, line 1)", |
| - |
|
2356 |
"output_type": "pyerr", |
| - |
|
2357 |
"traceback": [ |
| - |
|
2358 |
"\u001b[0;36m File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m lambda po*(-h*l/to + 1)**(g*m/(l*r)) == p: (h)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" |
| - |
|
2359 |
] |
| - |
|
2360 |
} |
| - |
|
2361 |
], |
| - |
|
2362 |
"prompt_number": 28 |
| - |
|
2363 |
}, |
| - |
|
2364 |
{ |
| - |
|
2365 |
"cell_type": "code", |
| - |
|
2366 |
"collapsed": false, |
| - |
|
2367 |
"input": [ |
| - |
|
2368 |
"type(cp)" |
| - |
|
2369 |
], |
| - |
|
2370 |
"language": "python", |
| - |
|
2371 |
"metadata": {}, |
| - |
|
2372 |
"outputs": [ |
| - |
|
2373 |
{ |
| - |
|
2374 |
"metadata": {}, |
| - |
|
2375 |
"output_type": "pyout", |
| - |
|
2376 |
"prompt_number": 60, |
| - |
|
2377 |
"text": [ |
| - |
|
2378 |
"sympy.core.symbol.Symbol" |
| - |
|
2379 |
] |
| - |
|
2380 |
} |
| - |
|
2381 |
], |
| - |
|
2382 |
"prompt_number": 60 |
| - |
|
2383 |
}, |
| - |
|
2384 |
{ |
| - |
|
2385 |
"cell_type": "code", |
| - |
|
2386 |
"collapsed": false, |
| - |
|
2387 |
"input": [ |
| - |
|
2388 |
"\n", |
| - |
|
2389 |
"\n", |
| - |
|
2390 |
"import sys\n", |
| - |
|
2391 |
"import time\n", |
| - |
|
2392 |
"\n", |
| - |
|
2393 |
"\n", |
| - |
|
2394 |
"\n", |
| - |
|
2395 |
"from IPython.display import clear_output\n", |
| - |
|
2396 |
"for i in range(10):\n", |
| - |
|
2397 |
" time.sleep(0.25)\n", |
| - |
|
2398 |
" clear_output()\n", |
| - |
|
2399 |
" print i\n", |
| - |
|
2400 |
" sys.stdout.flush()\n", |
| - |
|
2401 |
"\n" |
| - |
|
2402 |
], |
| - |
|
2403 |
"language": "python", |
| - |
|
2404 |
"metadata": {}, |
| - |
|
2405 |
"outputs": [ |
| - |
|
2406 |
{ |
| - |
|
2407 |
"output_type": "stream", |
| - |
|
2408 |
"stream": "stdout", |
| - |
|
2409 |
"text": [ |
| - |
|
2410 |
"9\n" |
| - |
|
2411 |
] |
| - |
|
2412 |
} |
| - |
|
2413 |
], |
| - |
|
2414 |
"prompt_number": 10 |
| - |
|
2415 |
}, |
| - |
|
2416 |
{ |
| - |
|
2417 |
"cell_type": "markdown", |
| - |
|
2418 |
"metadata": {}, |
| - |
|
2419 |
"source": [ |
| - |
|
2420 |
"V\u00fdvoj hodnot v \u010dase\n", |
| - |
|
2421 |
"------------------\n", |
| - |
|
2422 |
"\n", |
| - |
|
2423 |
"Vid\u00edme, \u017ee nam\u011b\u0159en\u00e9 hodnoty nevykazuj\u00ed \u017e\u00e1dn\u00fd trend, a m\u011b\u0159en\u00e9 chyby jsou zp\u016fsobeny pravd\u011bpodobn\u011b \u0161umem obvod\u016f \u010didla. Je to d\u016fsledek tepeln\u00e9 stability \u010didla, a faktu, \u017ee tlakov\u00e9 zm\u011bny v atmosf\u00e9\u0159e jsou relativn\u011b pomal\u00e9. S \u010dasovou konstantou minim\u00e1ln\u011b jednotky minut a na\u0161e m\u011b\u0159en\u00ed trvalo \u0159\u00e1dov\u011b des\u00edtky sekund. \n", |
| - |
|
2424 |
"\n", |
| - |
|
2425 |
"Absolutn\u00ed kalibrace tlaku\n", |
| - |
|
2426 |
"------------------\n", |
| - |
|
2427 |
"\n", |
| - |
|
2428 |
"V p\u0159\u00edpad\u011b, \u017ee by jsme pot\u0159ebovali tlakov\u00fd senzor pota\u017emo v\u00fd\u0161kom\u011br absolutn\u011b zkalibrovat, tak si k tomuto \u00fa\u010delu m\u016f\u017eeme p\u016fj\u010dit data z n\u011bkter\u00e9 kalibrovan\u00e9 stanice. V Praze pou\u017eijeme nap\u0159\u00edklad stanici CHMI pro Prahu 10. " |
| - |
|
2429 |
] |
| - |
|
2430 |
}, |
| - |
|
2431 |
{ |
| - |
|
2432 |
"cell_type": "code", |
| - |
|
2433 |
"collapsed": false, |
| - |
|
2434 |
"input": [ |
| - |
|
2435 |
"import openweather\n", |
| - |
|
2436 |
"from datetime import datetime\n", |
| - |
|
2437 |
"\n", |
| - |
|
2438 |
"ow = openweather.OpenWeather()\n", |
| - |
|
2439 |
"print ow.get_weather(61457)" |
| - |
|
2440 |
], |
| - |
|
2441 |
"language": "python", |
| - |
|
2442 |
"metadata": {}, |
| - |
|
2443 |
"outputs": [ |
| - |
|
2444 |
{ |
| - |
|
2445 |
"output_type": "stream", |
| - |
|
2446 |
"stream": "stdout", |
| - |
|
2447 |
"text": [ |
| - |
|
2448 |
"{u'main': {u'pressure': 1016, u'temp': 299.25, u'humidity': 38}, u'name': u'Prague 10', u'rain': {u'1h': 0}, u'station': {u'zoom': 10}, u'coord': {u'lat': 50.0787, u'lon': 14.4966}, u'date': u'2014-05-21 15:55:04', u'dt': 1400687704, u'calc': {u'dewpoint': 10.7}, u'id': 61457, u'wind': {u'gust': 12.1, u'deg': 225}}\n" |
| - |
|
2449 |
] |
| - |
|
2450 |
} |
| - |
|
2451 |
], |
| - |
|
2452 |
"prompt_number": 57 |
| - |
|
2453 |
}, |
| - |
|
2454 |
{ |
| - |
|
2455 |
"cell_type": "markdown", |
| - |
|
2456 |
"metadata": {}, |
| - |
|
2457 |
"source": [ |
| - |
|
2458 |
"Proto\u017ee datov\u00fd set byl nam\u011b\u0159en\u00fd v minulosti, mus\u00edme si st\u00e1hnout data pro toto \u010dasov\u00e9 obdob\u00ed." |
| - |
|
2459 |
] |
| - |
|
2460 |
}, |
| - |
|
2461 |
{ |
| - |
|
2462 |
"cell_type": "code", |
| - |
|
2463 |
"collapsed": false, |
| - |
|
2464 |
"input": [ |
| - |
|
2465 |
"start_date = datetime(2014, 4, 20)\n", |
| - |
|
2466 |
"end_date = datetime(2014, 4, 22)\n", |
| - |
|
2467 |
"print ow.get_historic_weather(61457, start_date, end_date)" |
| - |
|
2468 |
], |
| - |
|
2469 |
"language": "python", |
| - |
|
2470 |
"metadata": {}, |
| - |
|
2471 |
"outputs": [ |
| - |
|
2472 |
{ |
| - |
|
2473 |
"output_type": "stream", |
| - |
|
2474 |
"stream": "stderr", |
| - |
|
2475 |
"text": [ |
| - |
|
2476 |
"OpenWeather.do_request() got ValueError: No JSON object could be decoded (1. attempt)\n", |
| - |
|
2477 |
"OpenWeather.do_request() got ValueError: No JSON object could be decoded (2. attempt)\n" |
| - |
|
2478 |
] |
| - |
|
2479 |
}, |
| - |
|
2480 |
{ |
| - |
|
2481 |
"output_type": "stream", |
| - |
|
2482 |
"stream": "stdout", |
| - |
|
2483 |
"text": [ |
| - |
|
2484 |
"None\n" |
| - |
|
2485 |
] |
| - |
|
2486 |
}, |
| - |
|
2487 |
{ |
| - |
|
2488 |
"output_type": "stream", |
| - |
|
2489 |
"stream": "stderr", |
| - |
|
2490 |
"text": [ |
| - |
|
2491 |
"OpenWeather.do_request() got ValueError: No JSON object could be decoded (3. attempt)\n" |
| 2244 |
] |
2492 |
] |
| 2245 |
} |
2493 |
} |
| 2246 |
], |
2494 |
], |
| 2247 |
"prompt_number": 60 |
2495 |
"prompt_number": 60 |
| 2248 |
}, |
2496 |
}, |
| 2249 |
{ |
2497 |
{ |
| 2250 |
"cell_type": "code", |
2498 |
"cell_type": "code", |
| 2251 |
"collapsed": false, |
2499 |
"collapsed": false, |
| - |
|
2500 |
"input": [ |
| - |
|
2501 |
"stations = ow.find_stations_near(\n", |
| - |
|
2502 |
" 14.45, # longitude\n", |
| - |
|
2503 |
" 50.07, # latitude\n", |
| - |
|
2504 |
" 100 # kilometer radius\n", |
| - |
|
2505 |
")" |
| - |
|
2506 |
], |
| - |
|
2507 |
"language": "python", |
| - |
|
2508 |
"metadata": {}, |
| - |
|
2509 |
"outputs": [], |
| - |
|
2510 |
"prompt_number": 66 |
| - |
|
2511 |
}, |
| - |
|
2512 |
{ |
| - |
|
2513 |
"cell_type": "code", |
| - |
|
2514 |
"collapsed": false, |
| - |
|
2515 |
"input": [ |
| - |
|
2516 |
"print stations" |
| - |
|
2517 |
], |
| - |
|
2518 |
"language": "python", |
| - |
|
2519 |
"metadata": {}, |
| - |
|
2520 |
"outputs": [ |
| - |
|
2521 |
{ |
| - |
|
2522 |
"output_type": "stream", |
| - |
|
2523 |
"stream": "stdout", |
| - |
|
2524 |
"text": [ |
| - |
|
2525 |
"{u'list': [], u'message': u'', u'calctime': u'', u'cod': u'200', u'cnt': 0}\n" |
| - |
|
2526 |
] |
| - |
|
2527 |
} |
| - |
|
2528 |
], |
| - |
|
2529 |
"prompt_number": 64 |
| - |
|
2530 |
}, |
| - |
|
2531 |
{ |
| - |
|
2532 |
"cell_type": "code", |
| - |
|
2533 |
"collapsed": false, |
| 2252 |
"input": [], |
2534 |
"input": [], |
| 2253 |
"language": "python", |
2535 |
"language": "python", |
| 2254 |
"metadata": {}, |
2536 |
"metadata": {}, |
| 2255 |
"outputs": [] |
2537 |
"outputs": [] |
| 2256 |
} |
2538 |
} |