mirror of
https://github.com/EDCD/EDMarketConnector.git
synced 2025-04-17 01:22:19 +03:00
09730adbe6
This was historically used by the core EDDB plugin to construct a valid URL for a given station. EDDB has long-since provided alternate URL formats that negate the need for this. Plugin authors have been warned not to use this already.
117 lines
4.2 KiB
Python
Executable File
117 lines
4.2 KiB
Python
Executable File
#!/usr/bin/env python3
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#
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# build databases from files systems.csv and stations.json from http://eddb.io/api
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#
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import pickle
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import csv
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import json
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import requests
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def download(filename):
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r = requests.get('https://eddb.io/archive/v6/' + filename, stream=True)
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print('\n%s\t%dK' % (filename, len(r.content) / 1024))
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return r
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if __name__ == "__main__":
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# Ellipsoid that encompasses most of the systems in the bubble (but not outliers like Sothis)
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RX = RZ = 260
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CY = -50
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RY = 300
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RX2 = RX * RX
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RY2 = RY * RY
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RZ2 = RZ * RZ
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def inbubble(x, y, z):
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return (x * x)/RX2 + ((y - CY) * (y - CY))/RY2 + (z * z)/RZ2 <= 1
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# Sphere around Jaques
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JX, JY, JZ = -9530.50000, -910.28125, 19808.12500
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RJ2 = 80 * 80 # Furthest populated system is Pekoe at 50.16 Ly
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def around_jaques(x, y, z):
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return ((x - JX) * (x - JX) + (y - JY) * (y - JY) + (z - JZ) * (z - JZ)) <= RJ2
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# Sphere around outliers
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RO2 = 40 * 40
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def around_outlier(cx, cy, cz, x, y, z):
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return ((x - ox) * (x - ox) + (y - oy) * (y - oy) + (z - oz) * (z - oz)) <= RO2
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# Load all EDDB-known systems into a dictionary
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systems = { int(s['id']) : {
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'name' : s['name'],
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'x' : float(s['x']),
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'y' : float(s['y']),
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'z' : float(s['z']),
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'is_populated' : int(s['is_populated']),
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} for s in csv.DictReader(download('systems.csv').iter_lines(decode_unicode=True)) }
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#} for s in csv.DictReader(open('systems.csv')) }
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print('%d\tsystems' % len(systems))
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# Build another dict containing all systems considered to be in the
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# main populated bubble (see constants above and inbubble() for
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# the criteria).
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# (system_id, is_populated) by system_name (ignoring duplicate names)
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system_ids = {
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str(s['name']) : (k, s['is_populated'])
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for k,s in systems.items() if inbubble(s['x'], s['y'], s['z'])
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}
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print('%d\tsystems in bubble' % len(system_ids))
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# Build another dict for systems considered to be around Colonia
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extra_ids = {
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str(s['name']) : (k, s['is_populated'])
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for k,s in systems.items() if around_jaques(s['x'], s['y'], s['z'])
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}
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system_ids.update(extra_ids)
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print('%d\tsystems in Colonia' % len(extra_ids))
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# Build another dict for systems that are marked as populated, but
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# didn't make it into the bubble list.
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cut = {
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k : s for k, s in systems.items()
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if s['is_populated'] and s['name'] not in system_ids
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}
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print('%d\toutlying populated systems:' % len(cut))
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# Build another dict with all the systems, populated or not, around any
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# of the outliers.
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extra_ids = {}
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for k1,o in sorted(cut.items()):
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ox, oy, oz = o['x'], o['y'], o['z']
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extra = {
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str(s['name']) : (k, s['is_populated'])
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for k,s in systems.items() if around_outlier(ox, oy, oz, s['x'], s['y'], s['z'])
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}
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print('%-30s%7d %11.5f %11.5f %11.5f %4d' % (o['name'], k1, ox, oy, oz, len(extra)))
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extra_ids.update(extra)
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print('\n%d\tsystems around outliers' % len(extra_ids))
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system_ids.update(extra_ids)
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# Re-build 'cut' dict to hold duplicate (name) systems
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cut = {
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k : s
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for k,s in systems.items() if s['name'] in system_ids and system_ids[s['name']][0] != k
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}
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print('\n%d duplicate systems' % len(cut))
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for k,s in sorted(cut.items()):
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print('%-20s%8d %8d %11.5f %11.5f %11.5f' % (s['name'], system_ids[s['name']][0], k, s['x'], s['y'], s['z']))
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# Hack - ensure duplicate system names are pointing at the more interesting system
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system_ids['Amo'] = (866, True)
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system_ids['C Puppis'] = (25068, False)
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system_ids['q Velorum'] = (15843, True)
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system_ids['M Carinae'] = (22627, False)
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system_ids['HH 17'] = (61275, False)
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system_ids['K Carinae'] = (375886, False)
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system_ids['d Velorum'] = (406476, False)
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system_ids['L Velorum'] = (2016580, False)
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system_ids['N Velorum'] = (3012033, False)
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system_ids['i Velorum'] = (3387990, False)
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with open('systems.p', 'wb') as h:
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pickle.dump(system_ids, h, protocol = pickle.HIGHEST_PROTOCOL)
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print('\n%d saved systems' % len(system_ids))
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