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185f22b094
Minor consistency fixes for the copyright header and update the tables to current. PX4Buildbot will periodically update the tables automatically from this point.
177 lines
8.8 KiB
Python
Executable File
177 lines
8.8 KiB
Python
Executable File
#!/usr/bin/env python3
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############################################################################
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#
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# Copyright (c) 2020 Estimation and Control Library (ECL). All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions
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# are met:
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#
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# 1. Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# 2. Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in
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# the documentation and/or other materials provided with the
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# distribution.
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# 3. Neither the name ECL nor the names of its contributors may be
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# used to endorse or promote products derived from this software
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# without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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# OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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# AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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#
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############################################################################
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import math
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import json
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import urllib.request
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SAMPLING_RES = 10
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SAMPLING_MIN_LAT = -90
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SAMPLING_MAX_LAT = 90
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SAMPLING_MIN_LON = -180
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SAMPLING_MAX_LON = 180
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def constrain(n, nmin, nmax):
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return max(min(nmin, n), nmax)
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header = """/****************************************************************************
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*
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* Copyright (c) 2020 Estimation and Control Library (ECL). All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name ECL nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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"""
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print(header)
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print('#include <stdint.h>\n')
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LAT_DIM=int((SAMPLING_MAX_LAT-SAMPLING_MIN_LAT)/SAMPLING_RES)+1
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LON_DIM=int((SAMPLING_MAX_LON-SAMPLING_MIN_LON)/SAMPLING_RES)+1
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print('static constexpr float SAMPLING_RES = {}'.format(SAMPLING_RES) + ';')
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print('static constexpr float SAMPLING_MIN_LAT = {}'.format(SAMPLING_MIN_LAT) + ';')
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print('static constexpr float SAMPLING_MAX_LAT = {}'.format(SAMPLING_MAX_LAT) + ';')
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print('static constexpr float SAMPLING_MIN_LON = {}'.format(SAMPLING_MIN_LON) + ';')
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print('static constexpr float SAMPLING_MAX_LON = {}'.format(SAMPLING_MAX_LON) + ';')
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print('')
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print('static constexpr int LAT_DIM = {}'.format(LAT_DIM) + ';')
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print('static constexpr int LON_DIM = {}'.format(LON_DIM) + ';')
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print('\n')
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# Declination
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params = urllib.parse.urlencode({'lat1': 0, 'lat2': 0, 'lon1': 0, 'lon2': 0, 'latStepSize': 1, 'lonStepSize': 1, 'magneticComponent': 'd', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print("// Magnetic declination data in radians * 10^-4")
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print('// Model: {},'.format(data['model']))
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print('// Version: {},'.format(data['version']))
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print('// Date: {},'.format(data['result'][0]['date']))
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print('static constexpr const int16_t declination_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {")
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print('// LONGITUDE: ', end='')
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for l in range(SAMPLING_MIN_LON, SAMPLING_MAX_LON+1, SAMPLING_RES):
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print('{0:6d},'.format(l), end='')
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print('')
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for latitude in range(SAMPLING_MIN_LAT, SAMPLING_MAX_LAT+1, SAMPLING_RES):
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params = urllib.parse.urlencode({'lat1': latitude, 'lat2': latitude, 'lon1': SAMPLING_MIN_LON, 'lon2': SAMPLING_MAX_LON, 'latStepSize': 1, 'lonStepSize': SAMPLING_RES, 'magneticComponent': 'd', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print('/* LAT: {0:3d} */'.format(latitude) + ' { ', end='')
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for p in data['result']:
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# declination in radians * 10^-4
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declination_int = constrain(int(round(math.radians(p['declination'] * 10000))), 32767, -32768)
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print('{0:6d},'.format(declination_int), end='')
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print(' },')
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print("};\n")
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# Inclination
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params = urllib.parse.urlencode({'lat1': 0, 'lat2': 0, 'lon1': 0, 'lon2': 0, 'latStepSize': 1, 'lonStepSize': 1, 'magneticComponent': 'i', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print("// Magnetic inclination data in radians * 10^-4")
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print('// Model: {},'.format(data['model']))
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print('// Version: {},'.format(data['version']))
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print('// Date: {},'.format(data['result'][0]['date']))
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print('static constexpr const int16_t inclination_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {")
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print('// LONGITUDE: ', end='')
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for l in range(SAMPLING_MIN_LON, SAMPLING_MAX_LON+1, SAMPLING_RES):
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print('{0:6d},'.format(l), end='')
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print('')
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for latitude in range(SAMPLING_MIN_LAT, SAMPLING_MAX_LAT+1, SAMPLING_RES):
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params = urllib.parse.urlencode({'lat1': latitude, 'lat2': latitude, 'lon1': SAMPLING_MIN_LON, 'lon2': SAMPLING_MAX_LON, 'latStepSize': 1, 'lonStepSize': SAMPLING_RES, 'magneticComponent': 'i', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print('/* LAT: {0:3d} */'.format(latitude) + ' { ', end='')
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for p in data['result']:
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# inclination in radians * 10^-4
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inclination_int = constrain(int(round(math.radians(p['inclination'] * 10000))), 32767, -32768)
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print('{0:6d},'.format(inclination_int), end='')
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print(' },')
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print("};\n")
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# total intensity
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params = urllib.parse.urlencode({'lat1': 0, 'lat2': 0, 'lon1': 0, 'lon2': 0, 'latStepSize': 1, 'lonStepSize': 1, 'magneticComponent': 'i', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print("// Magnetic strength data in milli-Gauss * 10")
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print('// Model: {},'.format(data['model']))
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print('// Version: {},'.format(data['version']))
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print('// Date: {},'.format(data['result'][0]['date']))
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print('static constexpr const int16_t strength_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {")
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print('// LONGITUDE: ', end='')
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for l in range(SAMPLING_MIN_LON, SAMPLING_MAX_LON+1, SAMPLING_RES):
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print('{0:5d},'.format(l), end='')
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print('')
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for latitude in range(SAMPLING_MIN_LAT, SAMPLING_MAX_LAT+1, SAMPLING_RES):
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params = urllib.parse.urlencode({'lat1': latitude, 'lat2': latitude, 'lon1': SAMPLING_MIN_LON, 'lon2': SAMPLING_MAX_LON, 'latStepSize': 1, 'lonStepSize': SAMPLING_RES, 'magneticComponent': 'f', 'resultFormat': 'json'})
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f = urllib.request.urlopen("https://www.ngdc.noaa.gov/geomag-web/calculators/calculateIgrfgrid?%s" % params)
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data = json.loads(f.read())
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print('/* LAT: {0:3d} */'.format(latitude) + ' { ', end='')
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for p in data['result']:
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totalintensity_int = int(round(p['totalintensity']/10))
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print('{0:5d},'.format(totalintensity_int), end='')
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print(' },')
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print("};")
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