72 lines
2.9 KiB
Python
72 lines
2.9 KiB
Python
# =============================================================================
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# Copyright (C) 2019 Ryan Holmes
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#
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# This file is part of pyfa.
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#
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# pyfa is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# pyfa is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with pyfa. If not, see <http://www.gnu.org/licenses/>.
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# =============================================================================
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import math
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# Just copy-paste penalization chain calculation code (with some modifications,
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# as multipliers arrive in different form) in here to not make actual attribute
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# calculations slower than they already are due to extra function calls
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def calculateMultiplier(multipliers):
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"""
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multipliers: dictionary in format:
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{stacking group name: [(mult, resist attr ID), (mult, resist attr ID)]}
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"""
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val = 1
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for penalizedMultipliers in multipliers.values():
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# A quick explanation of how this works:
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# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
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l1 = [v[0] for v in penalizedMultipliers if v[0] > 1]
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l2 = [v[0] for v in penalizedMultipliers if v[0] < 1]
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# 2: The most significant bonuses take the smallest penalty,
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# This means we'll have to sort
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abssort = lambda _val: -abs(_val - 1)
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l1.sort(key=abssort)
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l2.sort(key=abssort)
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# 3: The first module doesn't get penalized at all
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# Any module after the first takes penalties according to:
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# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
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for l in (l1, l2):
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for i in range(len(l)):
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bonus = l[i]
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val *= 1 + (bonus - 1) * math.exp(- i ** 2 / 7.1289)
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return val
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def calculateRangeFactor(srcOptimalRange, srcFalloffRange, distance, restrictedRange=True):
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"""Range strength/chance factor, applicable to guns, ewar, RRs, etc."""
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if distance is None:
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return 1
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if srcFalloffRange > 0:
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# Most modules cannot be activated when at 3x falloff range, with few exceptions like guns
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if restrictedRange and distance > srcOptimalRange + 3 * srcFalloffRange:
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return 0
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return 0.5 ** ((max(0, distance - srcOptimalRange) / srcFalloffRange) ** 2)
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elif distance <= srcOptimalRange:
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return 1
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else:
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return 0
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def calculateLockTime(srcScanRes, tgtSigRadius):
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if not srcScanRes or not tgtSigRadius:
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return None
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return min(40000 / srcScanRes / math.asinh(tgtSigRadius) ** 2, 30 * 60)
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