#!/usr/bin/python # # build databases from files systems.csv and stations.json from http://eddb.io/api # import cPickle import csv import json import requests def download(filename): r = requests.get('https://eddb.io/archive/v5/' + filename, stream=True) print '\n%s\t%dK' % (filename, len(r.content) / 1024) return r if __name__ == "__main__": # Ellipsoid that encompasses most of the systems in the bubble (but not outliers like Sothis) RX = RZ = 260 CY = -50 RY = 300 RX2 = RX * RX RY2 = RY * RY RZ2 = RZ * RZ def inbubble(x, y, z): return (x * x)/RX2 + ((y - CY) * (y - CY))/RY2 + (z * z)/RZ2 <= 1 # Sphere around Jaques JX, JY, JZ = -9530.50000, -910.28125, 19808.12500 RJ2 = 80 * 80 # Furthest populated system is Pekoe at 50.16 Ly def around_jaques(x, y, z): return ((x - JX) * (x - JX) + (y - JY) * (y - JY) + (z - JZ) * (z - JZ)) <= RJ2 # Sphere around outliers RO2 = 40 * 40 def around_outlier(cx, cy, cz, x, y, z): return ((x - ox) * (x - ox) + (y - oy) * (y - oy) + (z - oz) * (z - oz)) <= RO2 systems = { int(s['id']) : { 'name' : s['name'].decode('utf-8'), 'x' : float(s['x']), 'y' : float(s['y']), 'z' : float(s['z']), 'is_populated' : int(s['is_populated']), } for s in csv.DictReader(download('systems.csv').iter_lines()) } #} for s in csv.DictReader(open('systems.csv')) } print '%d\tsystems' % len(systems) # (system_id, is_populated) by system_name (ignoring duplicate names) system_ids = { str(s['name']) : (k, s['is_populated']) for k,s in systems.iteritems() if inbubble(s['x'], s['y'], s['z']) } print '%d\tsystems in bubble' % len(system_ids) extra_ids = { str(s['name']) : (k, s['is_populated']) for k,s in systems.iteritems() if around_jaques(s['x'], s['y'], s['z']) } system_ids.update(extra_ids) print '%d\tsystems in Colonia' % len(extra_ids) cut = { k : s for k, s in systems.iteritems() if s['is_populated'] and s['name'] not in system_ids } print '%d\toutlying populated systems:' % len(cut) extra_ids = {} for k1,o in sorted(cut.iteritems()): ox, oy, oz = o['x'], o['y'], o['z'] extra = { str(s['name']) : (k, s['is_populated']) for k,s in systems.iteritems() if around_outlier(ox, oy, oz, s['x'], s['y'], s['z']) } print '%-30s%7d %11.5f %11.5f %11.5f %4d' % (o['name'], k1, ox, oy, oz, len(extra)) extra_ids.update(extra) print '\n%d\tsystems around outliers' % len(extra_ids) system_ids.update(extra_ids) cut = { k : s for k,s in systems.iteritems() if s['name'] in system_ids and system_ids[s['name']][0] != k } print '\n%d duplicate systems' % len(cut) for k,s in sorted(cut.iteritems()): print '%-20s%8d %8d %11.5f %11.5f %11.5f' % (s['name'], system_ids[s['name']][0], k, s['x'], s['y'], s['z']) # Hack - ensure duplicate system names are pointing at the more interesting system system_ids['Amo'] = (866, True) system_ids['q Velorum'] = (15843, True) system_ids['M Carinae'] = (22627, False) system_ids['HH 17'] = (61275, False) system_ids['K Carinae'] = (375886, False) system_ids['d Velorum'] = (406476, False) system_ids['L Velorum'] = (2016580, False) system_ids['N Velorum'] = (3012033, False) system_ids['i Velorum'] = (3387990, False) with open('systems.p', 'wb') as h: cPickle.dump(system_ids, h, protocol = cPickle.HIGHEST_PROTOCOL) print '\n%d saved systems' % len(system_ids) # station_id by (system_id, station_name) stations = json.loads(download('stations.json').content) # let json do the utf-8 decode station_ids = { (x['system_id'], str(x['name'])) : x['id'] for x in stations if x['max_landing_pad_size'] } with open('stations.p', 'wb') as h: cPickle.dump(station_ids, h, protocol = cPickle.HIGHEST_PROTOCOL) print '\n%d saved stations' % len(station_ids)