Daniel Agar
5 years ago
2 changed files with 221 additions and 47 deletions
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#!/usr/bin/env python3 |
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############################################################################ |
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# |
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# Copyright (c) 2020 ECL Development Team. 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 json |
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import urllib.request |
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SAMPLING_RES = 10 |
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SAMPLING_MIN_LAT = -60 |
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SAMPLING_MAX_LAT = 60 |
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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 PX4 Development Team. 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 PX4 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 degrees") |
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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 int8_t declination_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {") |
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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(' { ', end='') |
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for p in data['result']: |
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declination_int = constrain(int(round(p['declination'])), 127, -128) |
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print('{0:4d},'.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 degrees") |
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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 int8_t inclination_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {") |
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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(' { ', end='') |
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for p in data['result']: |
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inclination_int = constrain(int(round(p['inclination'])), 127, -128) |
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print('{0:4d},'.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 micro-Tesla or centi-Gauss") |
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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 int8_t strength_table[{}][{}]'.format(LAT_DIM, LON_DIM) + " {") |
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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(' { ', end='') |
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for p in data['result']: |
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totalintensity_int = int(round(p['totalintensity'] / 1000)) |
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print('{0:4d},'.format(totalintensity_int), end='') |
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print(' },') |
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print("};") |
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