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jlaura/pfeffernusse_ctx_pds.ipynb

Created February 27, 2018 16:52
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SpiceWebService - Example Usage - CTX
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pfeffernusse_ctx_pds.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"import pvl\n",
"import requests"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create the necessary input data\n",
"\n",
"To create an ISD we require the following:\n",
"\n",
"- target_name, e.g. Mercury\n",
"- capture_date (PDS data product dates appear to be ISO 8601 compliant)\n",
"- instrument, e.g. mdis-nac\n",
"- focal_plane_temperature (optionally included for temperature dependent focal lengths)\n",
"- spacecraft_id, e.g. messenger\n",
"- spacecraft_clock_count, from the label\n",
"- exposure_duration, from the label\n",
"- lighttime_correction, to tell spice what to use\n",
"- min_elevation (make optional?)\n",
"- max_elevation (make optional?)\n",
"\n",
"For the last two, it might be easier/better to take the intital center point from the PDS label and hit a low res. DEM to find these automatically for the user."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#label = pvl.load('/data/usgs_csm/CSM-SET/notebooks/J03_046060_1986_XN_18N282W.IMG')\n",
"#print(label)\n",
"label = pvl.load('/data/messenger_sample/EN0211587012M.IMG')\n",
"data = {'target_name': label['TARGET_NAME'],\n",
" 'capture_date': label['START_TIME'].isoformat(),\n",
" 'instrument': label['INSTRUMENT_NAME'], \n",
" 'focal_plane_temperature': label['FOCAL_PLANE_TEMPERATURE'].value,\n",
" 'spacecraft_id' : label['INSTRUMENT_HOST_NAME'],\n",
" 'spacecraft_clock_count': label['SPACECRAFT_CLOCK_START_COUNT'],\n",
" 'exposure_duration': label['EXPOSURE_DURATION'].value,\n",
" 'lighttime_correction':'LT+S', \n",
" 'min_elevation': -100,\n",
" 'max_elevation': 100\n",
" }\n",
"import json\n",
"data = json.dumps(data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Standard API landing page"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'apis': {'1.0': 'api/1.0'}, 'status': 'success'}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = requests.get('http://smalls:8002')\n",
"r.json()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Pushing the API into a namespace and versioning is good practice"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'data': {'available_missions': {'mercury': {'messenger': '/api/1.0/mercury/messenger'}}},\n",
" 'success': True}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = requests.get('http://smalls:8002/api/1.0')\n",
"r.json()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example listing of the kernels"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"{'data': {'meta_kernels': [{'mission': 'mars_reconnaissance_oribter'},\n",
" {'mission': 'messenger'}]},\n",
" 'success': True}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = requests.get('http://smalls:8002/api/1.0/missions')\n",
"r.json()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'data': {'kernels': {'metakernels': '/api/1.0/missions/mars_reconnaissance_orbiter/metakernels'}},\n",
" 'success': True}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = requests.get('http://smalls:8002/api/1.0/missions/mars_reconnaissance_orbiter')\n",
"r.json()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example generation of the ISD object\n",
"\n",
"Notice that every endpoint returns with a `success` key and a `data` key at the top level. This helps the user know if the call was successful and that all of the response is within the `data` key."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\"PDS_VERSION_ID\": \"PDS3\", \"FILE_NAME\": \"J03_046060_1986_XN_18N282W.IMG\", \"RECORD_TYPE\": \"FIXED_LENGTH\", \"RECORD_BYTES\": 5056, \"FILE_RECORDS\": 18433, \"LABEL_RECORDS\": 1, \"^IMAGE\": 2, \"SPACECRAFT_NAME\": \"MARS_RECONNAISSANCE_ORBITER\", \"INSTRUMENT_NAME\": \"CONTEXT CAMERA\", \"INSTRUMENT_HOST_NAME\": \"MARS RECONNAISSANCE ORBITER\", \"MISSION_PHASE_NAME\": \"ESP\", \"TARGET_NAME\": \"MARS\", \"INSTRUMENT_ID\": \"CTX\", \"PRODUCER_ID\": \"MRO_CTX_TEAM\", \"DATA_SET_ID\": \"MRO-M-CTX-2-EDR-L0-V1.0\", \"PRODUCT_CREATION_TIME\": \"2016-10-04T21:05:58\", \"SOFTWARE_NAME\": \"makepds05 $Revision: 1.16 $\", \"UPLOAD_ID\": \"UNK\", \"ORIGINAL_PRODUCT_ID\": \"4A_04_10E803E100\", \"PRODUCT_ID\": \"J03_046060_1986_XN_18N282W\", \"START_TIME\": \"2016-05-24T11:51:26.043000\", \"STOP_TIME\": \"2016-05-24T11:52:00.636000\", \"SPACECRAFT_CLOCK_START_COUNT\": \"1148557929:105\", \"SPACECRAFT_CLOCK_STOP_COUNT\": \"N/A\", \"FOCAL_PLANE_TEMPERATURE\": [295.8, \"K\"], \"SAMPLE_BIT_MODE_ID\": \"SQROOT\", \"OFFSET_MODE_ID\": \"197/230/219\", \"LINE_EXPOSURE_DURATION\": [1.877, \"MSEC\"], \"SAMPLING_FACTOR\": 1, \"SAMPLE_FIRST_PIXEL\": 0, \"RATIONALE_DESC\": \"Ride-along with HiRISE\", \"DATA_QUALITY_DESC\": \"OK\", \"ORBIT_NUMBER\": 46060, \"IMAGE\": {\"LINES\": 18432, \"LINE_SAMPLES\": 5056, \"LINE_PREFIX_BYTES\": 0, \"LINE_SUFFIX_BYTES\": 0, \"SAMPLE_TYPE\": \"UNSIGNED_INTEGER\", \"SAMPLE_BITS\": 8, \"SAMPLE_BIT_MASK\": 255, \"CHECKSUM\": 4012652948, \"SAMPLES\": 5056}}\n"
]
}
],
"source": [
"import datetime\n",
"import json\n",
"import numpy as np\n",
"class NumpyEncoder(json.JSONEncoder):\n",
" def default(self, obj):\n",
" if isinstance(obj, np.ndarray):\n",
" return obj.tolist()\n",
" elif isinstance(obj, datetime.date):\n",
" return obj.isoformat()\n",
" return json.JSONEncoder.default(self, obj)\n",
"\n",
" \n",
"label = pvl.load('/data/usgs_csm/CSM-SET/notebooks/J03_046060_1986_XN_18N282W.IMG')\n",
"# Homogenize the data keys\n",
"label['IMAGE']['SAMPLES'] = label['IMAGE']['LINE_SAMPLES']\n",
"\n",
"# Since we want to pass the 'raw' label, we must serialize it\n",
"data = json.dumps(label, cls=NumpyEncoder)\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'data': {'isd': '{\"DT_EPHEM\": 0.15016, \"NUMBER_OF_EPHEM\": 231, \"T0_QUAT\": -17.298431992530823, \"MIN_VALID_HT\": -8000, \"SEMI_MAJOR_AXIS\": 3396190.0, \"QUATERNIONS\": [0.44952472860454074, -0.650326767154696, 0.2332535013479794, 0.5662114608554338, 0.4495527843900355, -0.6503571799691237, 0.2332112057591029, 0.5661716753937452, 0.4495807944710761, -0.6503871990905886, 0.2331684885810699, 0.566132543168713, 0.4496083504336671, -0.6504170958981307, 0.23312591474611905, 0.5660938442144942, 0.44963532207843643, -0.6504470599936377, 0.23308368467835094, 0.5660553817620824, 0.4496615122268406, -0.6504775228895638, 0.2330421128059219, 0.5660166872948886, 0.4496886638761759, -0.6505075510892894, 0.2330007639414586, 0.5659776281442331, 0.4497170872152782, -0.6505372878183401, 0.23295970468270547, 0.565937765676325, 0.44974591414553106, -0.650566941001349, 0.2329188583366568, 0.5658975820912265, 0.44977210359838066, -0.650597101347536, 0.23287794030248082, 0.565858932476413, 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856216.9795913702, 3373527.4844388943, 1168270.4865505074, 856238.9112098905, 3373357.711949141, 1168756.8273703747, 856260.8232321511, 3373187.872311629, 1169243.1458445794, 856282.7143710696, 3373017.9678580877, 1169729.4407316805, 856304.5852513179, 3372847.99737502, 1170215.712688626, 856326.4358992499, 3372677.960887119, 1170701.9616859537, 856348.2663015008, 3372507.858470296, 1171188.187666197, 856370.0770218138, 3372337.688861084, 1171674.391282718, 856391.8669322272, 3372167.4544456666, 1172160.5712933782, 856413.6365316177, 3371997.1540563884, 1172646.7283311288, 856435.3858823873, 3371826.7876899284, 1173132.8623282688, 856457.1149433663, 3371656.355360231, 1173618.9733033297, 856478.8244138577, 3371485.8559047314, 1174105.0618225106, 856500.5129488923, 3371315.291654419, 1174591.126722772, 856522.1812483901, 3371144.661437766, 1175077.168558431, 856543.8292605802, 3370973.9652767973, 1175563.1873413692, 856565.4576734961, 3370803.2020259737, 1176049.1836430214, 856587.0651698451, 3370632.3739652443, 1176535.1562409424, 856608.6523616549, 3370461.480003665, 1177021.105754087, 856630.219308018, 3370290.520069713, 1177507.0321907543, 856651.7659613787, 3370119.4942110204, 1177992.9355003557, 856673.2929576726, 3369948.4012509263, 1178478.8162930321, 856694.7990363044, 3369777.243552041, 1178964.673349689, 856716.2848507575, 3369606.019915863, 1179450.5072859314, 856737.750430717, 3369434.730377009, 1179936.3180590046, 856759.1962688171, 3369263.3737677806, 1180422.1062581518, 856780.6212475225, 3369091.9524171995, 1180907.8707224661, 856802.0258758331, 3368920.465123531, 1181393.6119870208, 856823.4102924204, 3368748.9119725376, 1181879.3300575316, 856844.7743728742, 3368577.292932986, 1182365.024963694, 856866.118775949, 3368405.6068139714, 1182850.697234883, 856887.4422964662, 3368233.8559950567, 1183336.345691428, 856908.7454763728, 3368062.0392624307, 1183821.9709479837, 856930.0283725503, 3367890.156663376, 1184307.5729603774, 856951.2909796075, 3367718.208188549, 1184793.1517419093, 856972.5338715051, 3367546.192682774, 1185278.7078271867, 856993.7558736933, 3367374.112490006, 1185764.2400845252, 857014.9575268881, 3367201.9663842022, 1186249.7490689475, 857036.1389064272, 3367029.7544659926, 1186735.234771687, 857057.3006328614, 3366857.4755151775, 1187220.6977541805, 857078.4413783486, 3366685.131888593, 1187706.1368783298, 857099.561770023, 3366512.722385911, 1188191.5526789771, 857120.6619017539, 3366340.2470726883, 1188676.9451620707, 857141.7416930847, 3366167.705892071, 1189162.3143228448, 857162.8017986129, 3365995.097740521, 1189647.6607365513, 857183.840953872, 3365822.424900551, 1190132.9832004549, 857204.859793018, 3365649.6862469222, 1190618.2823230461, 857225.8583114343, 3365476.8817565986, 1191103.5580727353, 857246.8371332189, 3365304.01030342, 1191588.8110394832, 857267.7949757831, 3365131.0741714006, 1192074.0400312545, 857288.7325150396, 3364958.072270181, 1192559.2456323106, 857309.6496812962, 3364785.0045301113, 1193044.4278115302, 857330.5465784103, 3364611.871017628, 1193529.5865933886, 857351.4237286558, 3364438.670508027, 1194014.722543604, 857372.2799174702, 3364265.4053802737, 1194499.8344639766, 857393.1157548688, 3364092.07447697, 1194984.9229553982, 857413.9312789198, 3363918.6777673922, 1195469.9879755804, 857434.7264970988, 3363745.2152913534, 1195955.0295506492, 857455.5019124715, 3363571.6858681734, 1196440.0482434921, 857476.2564158401, 3363398.0918339076, 1196925.0428758524, 857496.9905343419, 3363224.4320399803, 1197410.0140182134, 857517.7043160307, 3363050.7064565583, 1197894.9616468137, 857538.3983942568, 3362876.9139672415, 1198379.8863820285, 857559.0714870611, 3362703.056880889, 1198864.7869945266, 857579.7242196316, 3362529.134053299, 1199349.6640505109, 857600.3565842785, 3362355.145448046, 1199834.5176404943, 857620.9686163036, 3362181.0911367475, 1200319.3476312077, 857641.5608972831, 3362006.9699042086, 1200804.1546784176, 857662.1321800709, 3361832.78408336, 1201288.9375670392, 857682.6830954014, 3361658.5325341574, 1201773.6968858545, 857703.2136859354, 3361484.215277377, 1202258.432634629, 857723.7239107868, 3361309.8322338415, 1202743.1447781909, 857744.2143839807, 3361135.3823941206, 1203227.8339043856, 857764.683845978, 3360960.867945458, 1203712.4988404044, 857785.1329176936, 3360786.287776251, 1204197.1401522153, 857805.5616444323, 3360611.6419261764, 1204681.7578381698, 857825.9706521074, 3360436.929208339, 1205166.3524779994, 857846.3586157985, 3360262.151948462, 1205650.922864957], \"CENTER_EPHEMERIS_TIME\": 517362771.526828, \"INT_TIME\": 0.001877, \"NUMBER_OF_QUATERNIONS\": 231, \"ITRANSS\": [0.0, 0.0, 142.85714285714], \"IKCODE\": -74021, \"PLATFORM_ID\": \"UNKNOWN\", \"ISIS_Z_DIRECTION\": 1, \"MAX_VALID_HT\": 8000, \"TRI_PARAMETERS\": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 352.9271664, 0.0, 0.0], \"TRAJ_ID\": \"UNKNOWN\", \"ITRANSL\": [0.0, 142.85714285714, 0.0], \"REF_DATE_TIME\": \"UNKNOWN\"}',\n",
" 'loaded_kernels': None},\n",
" 'success': True}"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r = requests.post('http://smalls:8002/api/1.0/missions/mars_reconnaissance_orbiter/csm_isd', data=data)\n",
"r.json()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Use the ISD"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import usgscam as cam\n",
"from cycsm.isd import Isd"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"isd = r.json()['data']['isd']"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"i = Isd.loads(isd)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"plugin = cam.genericls.GenericLsPlugin()\n",
"camera = plugin.from_isd(i, plugin.modelname(0))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(18432.0, 5000.0)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"camera.imagesize"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[701107.7192418213, 3142968.175070605, 1072678.7253195439]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"xyz = camera.imageToGround(9126, 2500, 0)\n",
"xyz"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[9126.000016312359, 2500.000000206428]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"camera.groundToImage(*xyz)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Random CTX Image\n",
"\n",
"The above could be perceived as being too canned. Here, pull a random image from the PDS and instantiate a camera model."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from ftplib import FTP\n",
"import os\n",
"from random import choice"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"# Run only once to avoid too many open FTP connections\n",
"ftp = FTP('pdsimage2.wr.usgs.gov')\n",
"ftp.login()\n",
"dirs = ftp.nlst('archive/mro-m-ctx-2-edr-l0-v1.0/')"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"data_dir = choice(dirs)\n",
"f = choice(ftp.nlst(data_dir + '/data'))\n",
"fname = os.path.basename(f)\n",
"with open('/data/ctx_sample/{}'.format(fname), 'wb') as file:\n",
" ftp.retrbinary('RETR {}'.format(f), file.write)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/data/ctx_sample/F04_037269_2011_XI_21N056W.IMG'"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"newfile = os.path.join('/data/ctx_sample/{}'.format(fname))\n",
"newfile"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"# Utility Func for working with PVL\n",
"def find_in_dict(obj, key):\n",
" \"\"\"\n",
" Recursively find an entry in a dictionary\n",
"\n",
" Parameters\n",
" ----------\n",
" obj : dict\n",
" The dictionary to search\n",
" key : str\n",
" The key to find in the dictionary\n",
"\n",
" Returns\n",
" -------\n",
" item : obj\n",
" The value from the dictionary\n",
" \"\"\"\n",
" if key in obj:\n",
" return obj[key]\n",
" for k, v in obj.items():\n",
" if isinstance(v,dict):\n",
" item = find_in_dict(v, key)\n",
" if item is not None:\n",
" return item\n",
" \n",
"def data_from_cube(header):\n",
" data = {}\n",
" data['START_TIME'] = find_in_dict(header, 'StartTime')\n",
" data['SPACECRAFT_NAME'] = find_in_dict(header, 'SpacecraftName')\n",
" data['INSTRUMENT_NAME'] = find_in_dict(header, 'InstrumentId')\n",
" data['SAMPLING_FACTOR'] = find_in_dict(header, 'SpatialSumming')\n",
" data['SAMPLE_FIRST_PIXEL'] = find_in_dict(header, 'SampleFirstPixel')\n",
" data['IMAGE'] = {}\n",
" data['IMAGE']['LINES'] = find_in_dict(header, 'Lines')\n",
" data['TARGET_NAME'] = find_in_dict(header, 'TargetName')\n",
" data['LINE_EXPOSURE_DURATION'] = find_in_dict(header, 'LineExposureDuration')\n",
" data['SPACECRAFT_CLOCK_START_COUNT'] = find_in_dict(header, 'SpacecraftClockCount')\n",
" return data"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Processing a new image: /data/CTX/calibrated/B01_010045_1878_XN_07N205W.cal.cub\n",
"{\"START_TIME\": \"2008-09-17T05:08:10.820000\", \"SPACECRAFT_NAME\": \"Mars_Reconnaissance_Orbiter\", \"INSTRUMENT_NAME\": \"CTX\", \"SAMPLING_FACTOR\": 1, \"SAMPLE_FIRST_PIXEL\": 0, \"IMAGE\": {\"LINES\": 7168}, \"TARGET_NAME\": \"Mars\", \"LINE_EXPOSURE_DURATION\": [1.877, \"MSEC\"], \"SPACECRAFT_CLOCK_START_COUNT\": \"0906095311:038\"}\n",
"(7168.0, 5000.0)\n",
"[-3035183.4483585223, 1452666.3622457734, 457215.05215266405]\n"
]
},
{
"data": {
"text/plain": [
"[3584.000022561103, 2500.0000033572246]"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"\n",
"# Simple helper function to use the API\n",
"def create_data_pacakge(in_file):\n",
" label = pvl.load(in_file)\n",
" return json.dumps(label, cls=NumpyEncoder)\n",
"\n",
"#newfile = '/data/ctx_sample/F04_037269_2011_XI_21N056W.IMG'\n",
"newfile = '/data/CTX/calibrated/B01_010045_1878_XN_07N205W.cal.cub'\n",
"\n",
"print('Processing a new image: {}'.format(newfile))\n",
"# Call the func to create the data package for submission to the micro-service\n",
"data = pvl.load(newfile)\n",
"if 'cub' in os.path.splitext(newfile)[1]:\n",
" data = data_from_cube(data) \n",
"data = json.dumps(data, cls=NumpyEncoder)\n",
"\n",
"print(data)\n",
"# Call the micro-service\n",
"r = requests.post('http://localhost:5000/api/1.0/missions/mars_reconnaissance_oribter/ctx/csm_isd', data=data)\n",
"\n",
"# Get the ISD back and instantiate a local ISD for the image\n",
"isd = r.json()['data']['isd']\n",
"i = Isd.loads(isd)\n",
"\n",
"# Create the plugin and camera as usual\n",
"plugin = cam.genericls.GenericLsPlugin()\n",
"camera = plugin.from_isd(i, plugin.modelname(0))\n",
"\n",
"shape = camera.imagesize\n",
"# Call I2G\n",
"gnd = camera.imageToGround(shape[0] / 2, shape[1] / 2, 0)\n",
"print(gnd)\n",
"\n",
"# Call G2I\n",
"camera.groundToImage(*gnd)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-56.62606257827925, 21.679360463340597)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pyproj\n",
"from math import sqrt\n",
"\n",
"semi_major = i.param(\"SEMI_MAJOR_AXIS\")\n",
"semi_minor = semi_major * sqrt(1 - i.param(\"ECCENTRICITY\")**2)\n",
"\n",
"ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor)\n",
"lla = pyproj.Proj(proj='longlat', a=semi_major, b=semi_minor)\n",
"\n",
"gnd = camera.imageToGround(shape[0], shape[1], 0)\n",
"\n",
"\n",
"lons, lats, alts = pyproj.transform(ecef, lla, gnd[0], gnd[1], gnd[2])\n",
"lons, lats"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Camera Testing",
"language": "python",
"name": "ct"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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