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temppreshumigasrsrprsrqsnrenerestbandtxpdlplltemodetimetime2
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" ], "text/plain": [ " temp pres humi gas rsrp rsrq snr enerest band txp \\\n", "933 28.84 96.309 38.126 46799.0 -56.0 28.0 14.0 8.0 20.0 -1.0 \n", "934 28.84 96.311 38.266 46694.0 -56.0 29.0 14.0 8.0 20.0 -1.0 \n", "935 28.85 96.313 38.307 46874.0 -56.0 30.0 16.0 8.0 20.0 -1.0 \n", "936 28.78 96.311 38.683 43794.0 -57.0 31.0 16.0 8.0 20.0 -1.0 \n", "937 28.75 96.311 38.983 45026.0 -56.0 31.0 16.0 8.0 20.0 0.0 \n", "\n", " dlpl ltemode time time2 \n", "933 83.0 2.0 1.748434e+09 (2025, 5, 28, 13, 59, 10, 2, 148, 1) \n", "934 83.0 2.0 1.748434e+09 (2025, 5, 28, 13, 59, 18, 2, 148, 1) \n", "935 83.0 2.0 1.748434e+09 (2025, 5, 28, 13, 59, 23, 2, 148, 1) \n", "936 84.0 2.0 1.748434e+09 (2025, 5, 28, 13, 59, 28, 2, 148, 1) \n", "937 84.0 2.0 1.748434e+09 (2025, 5, 28, 13, 59, 33, 2, 148, 1) " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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temppreshumigasrsrprsrqsnrenerestbandtxpdlplltemodetimetime2
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" ], "text/plain": [ " temp pres humi gas rsrp rsrq snr enerest band txp dlpl \\\n", "0 0.00 98.318 38.619 5480.0 -57.0 28.0 5.0 8.0 20.0 3.0 85.0 \n", "1 32.02 98.339 35.803 7416.0 -57.0 28.0 5.0 7.0 20.0 1.0 84.0 \n", "2 31.54 98.349 35.465 10492.0 -59.0 26.0 2.0 7.0 20.0 1.0 87.0 \n", "3 31.59 98.343 35.546 13663.0 -58.0 28.0 4.0 7.0 20.0 1.0 86.0 \n", "4 31.57 98.341 35.417 16467.0 -59.0 28.0 4.0 7.0 20.0 1.0 87.0 \n", "\n", " ltemode time time2 \n", "0 2.0 1.748426e+09 (2025, 5, 28, 11, 49, 16, 2, 148, 1) \n", "1 2.0 1.748426e+09 (2025, 5, 28, 11, 49, 27, 2, 148, 1) \n", "2 2.0 1.748426e+09 (2025, 5, 28, 11, 49, 37, 2, 148, 1) \n", "3 2.0 1.748426e+09 (2025, 5, 28, 11, 49, 47, 2, 148, 1) \n", "4 2.0 1.748426e+09 (2025, 5, 28, 11, 49, 57, 2, 148, 1) " ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import time\n", "import sys\n", "import json\n", "import numpy as np\n", "import pandas as pd\n", "import plotly.express as px\n", "import time\n", "\n", "cols = [ 'temp', 'pres', 'humi', 'gas', 'rsrp', 'rsrq', 'snr', 'enerest', 'band', 'txp', 'dlpl', 'ltemode', 'time']\n", "\n", "dg = pd.DataFrame(columns=cols, dtype=float)\n", "\n", "with open('savenb.csv') as f:\n", " for i, line in enumerate(f):\n", " dg.loc[i] = pd.Series(json.loads(line))\n", "\n", "dg['rsrp'] = dg['rsrp'] - 140 # to dBm\n", "dg['snr'] = dg['snr'] - 24 # to dB\n", "\n", "dg = dg[dg['ltemode'] == 2].reset_index(drop=True)\n", "\n", "dg = dg.fillna(0.0)\n", "\n", "dg['time2'] = dg['time'].apply(time.localtime)\n", "\n", "print('len: ', len(dg.index))\n", "display(dg.tail(5))\n", "dg.head(5)\n", "\n" ] }, { "cell_type": "code", "execution_count": 59, "id": "9a698481-3cb6-46de-96d8-0db62ece9631", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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timelatlonelevationaccuracybearingspeedsatellitesproviderhdop...dgpsidactivitybatteryannotationtimestamp_mstime_offsetdistancestarttimestamp_msprofile_namebattery_charging
01.748425e+0949.22780416.575121334.9830329.648001156.21.36842gps0.8...NaNNaN66NaN17484253908882025-05-28T11:43:10.888+02:000.0000001748425387714Default ProfileTrue
11.748425e+0949.22778716.575137326.3611457.504000NaN0.00033gps0.8...NaNNaN67NaN17484254514412025-05-28T11:44:11.441+02:002.1603701748425387714Default ProfileTrue
21.748426e+0949.22779116.575146327.2998057.504000NaN0.00031gps0.6...NaNNaN68NaN17484255124412025-05-28T11:45:12.441+02:002.9102571748425387714Default ProfileTrue
31.748426e+0949.22779716.575143327.6502089.648001NaN0.00038gps1.0...NaNNaN68NaN17484255734412025-05-28T11:46:13.441+02:003.6334001748425387714Default ProfileTrue
41.748426e+0949.22780116.575150325.92468310.720000NaN0.00038gps0.9...NaNNaN69NaN17484256350002025-05-28T11:47:15.000+02:004.2933991748425387714Default ProfileTrue
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5 rows × 24 columns

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" ], "text/plain": [ " time lat lon elevation accuracy bearing speed \\\n", "0 1.748425e+09 49.227804 16.575121 334.983032 9.648001 156.2 1.368 \n", "1 1.748425e+09 49.227787 16.575137 326.361145 7.504000 NaN 0.000 \n", "2 1.748426e+09 49.227791 16.575146 327.299805 7.504000 NaN 0.000 \n", "3 1.748426e+09 49.227797 16.575143 327.650208 9.648001 NaN 0.000 \n", "4 1.748426e+09 49.227801 16.575150 325.924683 10.720000 NaN 0.000 \n", "\n", " satellites provider hdop ... dgpsid activity battery annotation \\\n", "0 42 gps 0.8 ... NaN NaN 66 NaN \n", "1 33 gps 0.8 ... NaN NaN 67 NaN \n", "2 31 gps 0.6 ... NaN NaN 68 NaN \n", "3 38 gps 1.0 ... NaN NaN 68 NaN \n", "4 38 gps 0.9 ... NaN NaN 69 NaN \n", "\n", " timestamp_ms time_offset distance starttimestamp_ms \\\n", "0 1748425390888 2025-05-28T11:43:10.888+02:00 0.000000 1748425387714 \n", "1 1748425451441 2025-05-28T11:44:11.441+02:00 2.160370 1748425387714 \n", "2 1748425512441 2025-05-28T11:45:12.441+02:00 2.910257 1748425387714 \n", "3 1748425573441 2025-05-28T11:46:13.441+02:00 3.633400 1748425387714 \n", "4 1748425635000 2025-05-28T11:47:15.000+02:00 4.293399 1748425387714 \n", "\n", " profile_name battery_charging \n", "0 Default Profile True \n", "1 Default Profile True \n", "2 Default Profile True \n", "3 Default Profile True \n", "4 Default Profile True \n", "\n", "[5 rows x 24 columns]" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gps = pd.read_csv('nbiotgps.csv')\n", "gps['time'] = gps['time'].apply(lambda x: time.mktime(time.strptime(x[:-5], '%Y-%m-%dT%H:%M:%S')) +3600*2)\n", "gps['speed'] = gps['speed'] * 3.6 # m/s -> km/s\n", "gps.head(5)" ] }, { "cell_type": "code", "execution_count": 60, "id": "f3d732ee-3e78-4ac9-89f8-63c02abd9826", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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temppreshumigasrsrprsrqsnrenerestbandtxp...dgpsidactivitybatteryannotationtimestamp_mstime_offsetdistancestarttimestamp_msprofile_namebattery_charging
00.0098.31838.6195480.0-57.028.05.08.020.03.0...NaNNaN70NaN17484257576252025-05-28T11:49:17.625+02:007.3599821748425387714Default ProfileTrue
132.0298.33935.8037416.0-57.028.05.07.020.01.0...NaNNaN70NaN17484257576252025-05-28T11:49:17.625+02:007.3599821748425387714Default ProfileTrue
231.5498.34935.46510492.0-59.026.02.07.020.01.0...NaNNaN70NaN17484257576252025-05-28T11:49:17.625+02:007.3599821748425387714Default ProfileTrue
331.5998.34335.54613663.0-58.028.04.07.020.01.0...NaNNaN70NaN17484257576252025-05-28T11:49:17.625+02:007.3599821748425387714Default ProfileTrue
431.5798.34135.41716467.0-59.028.04.07.020.01.0...NaNNaN71NaN17484258184452025-05-28T11:50:18.445+02:008.5416911748425387714Default ProfileTrue
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5 rows × 37 columns

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" ], "text/plain": [ " temp pres humi gas rsrp rsrq snr enerest band txp ... \\\n", "0 0.00 98.318 38.619 5480.0 -57.0 28.0 5.0 8.0 20.0 3.0 ... \n", "1 32.02 98.339 35.803 7416.0 -57.0 28.0 5.0 7.0 20.0 1.0 ... \n", "2 31.54 98.349 35.465 10492.0 -59.0 26.0 2.0 7.0 20.0 1.0 ... \n", "3 31.59 98.343 35.546 13663.0 -58.0 28.0 4.0 7.0 20.0 1.0 ... \n", "4 31.57 98.341 35.417 16467.0 -59.0 28.0 4.0 7.0 20.0 1.0 ... \n", "\n", " dgpsid activity battery annotation timestamp_ms \\\n", "0 NaN NaN 70 NaN 1748425757625 \n", "1 NaN NaN 70 NaN 1748425757625 \n", "2 NaN NaN 70 NaN 1748425757625 \n", "3 NaN NaN 70 NaN 1748425757625 \n", "4 NaN NaN 71 NaN 1748425818445 \n", "\n", " time_offset distance starttimestamp_ms \\\n", "0 2025-05-28T11:49:17.625+02:00 7.359982 1748425387714 \n", "1 2025-05-28T11:49:17.625+02:00 7.359982 1748425387714 \n", "2 2025-05-28T11:49:17.625+02:00 7.359982 1748425387714 \n", "3 2025-05-28T11:49:17.625+02:00 7.359982 1748425387714 \n", "4 2025-05-28T11:50:18.445+02:00 8.541691 1748425387714 \n", "\n", " profile_name battery_charging \n", "0 Default Profile True \n", "1 Default Profile True \n", "2 Default Profile True \n", "3 Default Profile True \n", "4 Default Profile True \n", "\n", "[5 rows x 37 columns]" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.merge_asof(dg, gps, on='time', direction='nearest')\n", "len(df.index)\n", "\n", "i = 0\n", "def aproxpos(t):\n", " global i\n", " while i+2 < len(gps.index) and gps.at[i+1, 'time'] < t:\n", " i += 1\n", " t1, t2 = gps.at[i, 'time'], gps.at[i+1, 'time']\n", " la1, la2 = gps.at[i, 'lat'], gps.at[i+1, 'lat']\n", " lo1, lo2 = gps.at[i, 'lon'], gps.at[i+1, 'lon']\n", " \n", " la = (t-t1)*((la2-la1)/(t2-t1)) +la1\n", " lo = (t-t1)*((lo2-lo1)/(t2-t1)) +lo1\n", " return pd.Series([la, lo])\n", "\n", "df[['lat', 'lon']] = df['time'].apply(aproxpos)\n", "df.head(5)" ] }, { "cell_type": "code", "execution_count": 34, "id": "f865d9d4-cd00-429e-90b6-53e4b01237f8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "133" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "i" ] }, { "cell_type": "code", "execution_count": 61, "id": "5e753dcc-c84d-4b36-835f-9069eafb2c7d", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "speed=%{marker.size}
lat=%{lat}
lon=%{lon}
rsrp=%{marker.color}", "lat": { "bdata": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = px.scatter_map(df, lat='lat', lon='lon',color=\"rsrp\", opacity=1, size='speed', size_max=9,\n", " map_style=\"open-street-map\", color_continuous_scale='jet', zoom=8)\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 51, "id": "88382cf3-a640-44cf-8462-3106d2833cca", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from matplotlib import pyplot as plt\n", "a = dg['time'].diff()\n", "plt.plot(a)\n", "plt.grid()\n", "plt.show()\n", "plt.hist(a, bins=100)\n", "plt.grid()" ] }, { "cell_type": "code", "execution_count": 25, "id": "c0c837d4-d569-42da-a274-4dbf13d41efa", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "('{\"lati\": 49.223027547, \"long\": 16.580739947, \"alti\": NaN, \"rssi\": -1.950746802, \"snr\": 0.0, \"rttt\": NaN, \"temp\": 30.0, \"humi\": NaN, \"pres\": NaN, \"voc\": NaN}',\n", " lati 49.223028\n", " long 16.580740\n", " alti NaN\n", " rssi -1.950747\n", " snr 0.000000\n", " rttt NaN\n", " temp 30.000000\n", " humi NaN\n", " pres NaN\n", " voc NaN\n", " Name: 50, dtype: float64)" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import json\n", "s = dg.loc[50]\n", "js = json.dumps(s.to_dict())\n", "ss = pd.Series(json.loads(js))\n", "js, sss" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.2" } }, "nbformat": 4, "nbformat_minor": 5 }