#!/usr/bin/python # -*- coding: utf-8 -*- # # build databases from files systems.csv and stations.json from http://eddb.io/api # import cPickle import csv import json import requests if __name__ == "__main__": 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 # 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 = 75 * 75 # 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 # Get Points Of Interest from Canonn Research - https://api.canonn.technology/api/docs/#!/System/V1StellarSystemsGet POIS = [(s['name'], s['edsmCoordX'], s['edsmCoordY'], s['edsmCoordZ']) for s in requests.get('https://api.canonn.technology/api/v1/stellar/systems').json() if s.get('edsmCoordX') and s.get('edsmCoordY') and s.get('edsmCoordZ')] POIS.extend([ # http://elite-dangerous.wikia.com/wiki/Alien_Crash_Site ('Pleiades Sector AB-W b2-4', -137.56250, -118.25000, -380.43750), ('HIP 17862', -81.43750, -151.90625, -359.59375), ('HIP 17403', -93.68750, -158.96875, -367.62500), # http://elite-dangerous.wikia.com/wiki/Thargoid_Surface_Site ('HIP 19026', -117.87500, -65.12500, -330.90625), # POI ('HIP 22460', -41.31250, -58.96875, -354.78125), ('Col 70 Sector FY-N c21-3', 687.06250, -362.53125, -697.06250), ]) POIS.sort() 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 by system_name (ignoring duplicate names) system_ids = { str(s['name']) : k for k,s in systems.iteritems() if s['is_populated'] or inbubble(s['x'], s['y'], s['z']) or around_jaques(s['x'], s['y'], s['z']) # skip unpopulated systems outside the bubble and those with a bogus name } print '\n%d systems around Jacques' % len([s for s in systems.itervalues() if around_jaques(s['x'], s['y'], s['z'])]) cut = { k : s for k,s in systems.iteritems() if s['is_populated'] and not inbubble(s['x'], s['y'], s['z']) and not around_jaques(s['x'], s['y'], s['z']) } print '\n%d populated systems outside bubble calculation:' % 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 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 systems around outliers' % len(extra_ids) system_ids.update(extra_ids) print '\n%d POIs:' % len(POIS) extra_ids = {} for name,ox,oy,oz in POIS: extra = { str(s['name']) : k for k,s in systems.iteritems() if around_outlier(ox, oy, oz, s['x'], s['y'], s['z']) } print '%-37s %11.5f %11.5f %11.5f %4d' % (name, ox, oy, oz, len(extra)) extra_ids.update(extra) print '\n%d systems around POIs' % len(extra_ids) system_ids.update(extra_ids) cut = { k : s for k,s in systems.iteritems() if inbubble(s['x'], s['y'], s['z']) and system_ids.get(s['name']) is None } print '\n%d dropped systems inside bubble calculation:' % len(cut) for k,s in sorted(cut.iteritems()): print '%s%s%7d %11.5f %11.5f %11.5f' % (s['name'].encode('utf-8'), ' '*(30-len(s['name'])), k, s['x'], s['y'], s['z']) cut = { k : s for k,s in systems.iteritems() if system_ids.get(s['name']) and system_ids[s['name']] != k and (s['is_populated'] or inbubble(s['x'], s['y'], s['z'])) } print '\n%d duplicate systems inside bubble calculation:' % 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']], k, s['x'], s['y'], s['z']) # Hack - ensure duplicate system names are pointing at the more interesting system system_ids['Amo'] = 866 system_ids['K Carinae'] = 375886 # both unpopulated # Some extra interesting systems system_ids['Sagittarius A*'] = 21276 system_ids["Thor's Eye"] = 34950 system_ids['Great Annihilator'] = 35985 system_ids['Beagle Point'] = 47005 system_ids['Rendezvous Point'] = 91161 system_ids['Myeia Thaa ZE-R d4-0'] = 125069 # Podar system_ids['Iorant FR-C c26-0'] = 141581 # The Treehouse system_ids['Phae Phlai AA-A h0'] = 144202 # Explorer's End system_ids['Oevasy SG-Y d0'] = 145249 # Salomé's Reach / Semotus Beacon / Ishum's Reach system_ids['Syreadiae JX-F c0'] = 8538488 # Zurara 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'] } cut = [ x for x in stations if any(ord(c) >= 128 for c in x['name']) ] print '\n%d dropped stations:' % len(cut) for s in cut: print '%-30s%7d %s' % (s['name'], s['id'], systems[s['system_id']]['name']) with open('stations.p', 'wb') as h: cPickle.dump(station_ids, h, protocol = cPickle.HIGHEST_PROTOCOL) print '\n%d saved stations' % len(station_ids)