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