def extract_skills(opts, entries, initsave):
crews = dict((c['id'], c['skill']) for c in initsave.crews
if c['type'] in opts.classes)
students = set(
[c['id'] for c in initsave.crews if c['status'] == 'Student'])
days = sorted(hhist.group_by_date(entries))
first = days[0][0].prev()
results = {first: histogram(opts, skills_from_crews(crews, students))}
for day, ents in days:
for ent in ents:
if ent['class'] != 'C':
continue
ent = ent['data']
if ent['class'] not in opts.classes:
continue
cmid = ent['cmid']
if ent['etyp'] == 'GE':
students.add(cmid)
elif ent['etyp'] == 'ST':
students -= set([cmid])
elif ent['etyp'] == 'SK':
crews[cmid] = ent['data']['skill']
elif ent['etyp'] in ['DE', 'PW']:
del crews[cmid]
results[day] = histogram(opts, skills_from_crews(crews, students))
return results
def extract_targ_profit(save, before=None, after=None, typ=None):
bombers = {b['id']: [b['type'], 0, True, True] for b in save.init.bombers}
targets = [[t['dmg'], 0,
dict((i, 0) for i in xrange(save.ntypes))]
for t in save.init.targets]
days = sorted(hhist.group_by_date(save.history))
classes = [[tcls, tcls], [icls, icls]]
for d in days:
daily_profit(d,
bombers,
targets,
classes,
d[0] >= after if after else True,
d[0] >= before if before else False,
typ=typ)
gains, losses = zip(*targets)[1:]
lossvalue = [
sum(l * hdata.Bombers[i]['cost'] for i, l in loss.items())
for loss in losses
]
return {
i: {
'gain': gains[i],
'loss': losses[i],
'cost': lossvalue[i]
}
for i in xrange(save.init.ntargets)
}
def extract_ops(opts, entries, initsave):
crews = dict(
(c['id'],
(c['tops'] if c['status'] == 'Crewman' else 0) + 30 * c['ft'])
for c in initsave.crews if c['type'] in opts.classes)
students = set(
[c['id'] for c in initsave.crews if c['status'] == 'Student'])
days = sorted(hhist.group_by_date(entries))
first = days[0][0].prev()
results = {first: histogram(opts, ops_from_crews(crews, students))}
for day, ents in days:
for ent in ents:
if ent['class'] != 'C':
continue
ent = ent['data']
if ent['class'] not in opts.classes:
continue
cmid = ent['cmid']
if ent['etyp'] == 'GE':
students.add(cmid)
elif ent['etyp'] == 'ST':
if cmid in students:
crews[cmid] = 0
students.remove(cmid)
elif ent['etyp'] == 'OP':
crews[cmid] += 1
elif ent['etyp'] in ['DE', 'PW']:
if cmid in crews: del crews[cmid]
results[day] = histogram(opts, ops_from_crews(crews, students))
return results
def extract_ops(opts, entries, initsave):
crews = dict((c['id'], (c['tops'] if c['status'] == 'Crewman' else 0) + 30 * c['ft']) for c in initsave.crews if c['type'] in opts.classes)
students = set([c['id'] for c in initsave.crews if c['status'] == 'Student'])
days = sorted(hhist.group_by_date(entries))
first = days[0][0].prev()
results = {first: histogram(opts, ops_from_crews(crews, students))}
for day, ents in days:
for ent in ents:
if ent['class'] != 'C':
continue
ent = ent['data']
if ent['class'] not in opts.classes:
continue
cmid = ent['cmid']
if ent['etyp'] == 'GE':
students.add(cmid)
elif ent['etyp'] == 'ST':
if cmid in students:
crews[cmid] = 0
students.remove(cmid)
elif ent['etyp'] == 'OP':
crews[cmid] += 1
elif ent['etyp'] in ['DE', 'PW']:
if cmid in crews: del crews[cmid]
results[day] = histogram(opts, ops_from_crews(crews, students))
return results
def extract_totals(save, before=None, after=None):
bombers = {b['id']:b['pff'] for b in save.init.bombers}
days = sorted(hhist.group_by_date(save.history))
totals = {}
for d in days:
total = daily_total(d, bombers, d[0]>=after if after else True, d[0]>=before if before else False)
if total is not None:
totals[d[0]] = total
return totals
def extract_targ_profit(save, before=None, after=None, typ=None):
bombers = {b['id']:[b['type'], 0, True, True] for b in save.init.bombers}
targets = [[t['dmg'], 0, dict((i,0) for i in xrange(save.ntypes))] for t in save.init.targets]
days = sorted(hhist.group_by_date(save.history))
classes = [[tcls,tcls], [icls,icls]]
for d in days:
daily_profit(d, bombers, targets, classes, d[0]>=after if after else True, d[0]>=before if before else False, typ=typ)
gains, losses = zip(*targets)[1:]
lossvalue = [sum(l*hdata.Bombers[i]['cost'] for i,l in loss.items()) for loss in losses]
return {i: {'gain': gains[i], 'loss': losses[i], 'cost': lossvalue[i]} for i in xrange(save.init.ntargets)}
def extract_totals(save, before=None, after=None):
bombers = {b['id']: b['pff'] for b in save.init.bombers}
days = sorted(hhist.group_by_date(save.history))
totals = {}
for d in days:
total = daily_total(d, bombers, d[0] >= after if after else True,
d[0] >= before if before else False)
if total is not None:
totals[d[0]] = total
return totals
def count_losses(ents):
days = sorted(hhist.group_by_date(ents))
de = 0
pw = 0
ex = 0
for d in days:
for ent in d[1]:
if ent['class'] != 'C': continue
if ent['data']['etyp'] == 'DE':
de += 1
elif ent['data']['etyp'] == 'PW':
pw += 1
elif ent['data']['etyp'] == 'EX':
ex += 1
return (de, pw, ex)
def count_losses(ents): days = sorted(hhist.group_by_date(ents)) de = 0 pw = 0 ex = 0 for d in days: for ent in d[1]: if ent['class'] != 'C': continue if ent['data']['etyp'] == 'DE': de += 1 elif ent['data']['etyp'] == 'PW': pw += 1 elif ent['data']['etyp'] == 'EX': ex += 1 return(de, pw, ex)
def count_losses(ents):
days = sorted(hhist.group_by_date(ents))
de = 0
pw = 0
ex = 0
for d in days:
for ent in d[1]:
if ent["class"] != "C":
continue
if ent["data"]["etyp"] == "DE":
de += 1
elif ent["data"]["etyp"] == "PW":
pw += 1
elif ent["data"]["etyp"] == "EX":
ex += 1
return (de, pw, ex)
def extract_prodloss(ents):
days = sorted(hhist.group_by_date(ents))
bentry = [b.get('entry', hhist.date(0, 0, 0)) for b in hdata.Bombers]
res = {}
for d in days:
row = [[0, 0] for b in hdata.Bombers]
for ent in d[1]:
if ent['class'] != 'A': continue
if ent['data']['type']['fb'] != 'B': continue
typ = ent['data']['type']['ti']
if ent['data']['etyp'] == 'CT':
if d[0].next() != bentry[typ]:
row[typ][0] += 1
elif ent['data']['etyp'] == 'CR':
row[typ][1] -= 1
res[d[0]] = row
return(res)
def extract_prodloss(ents):
days = sorted(hhist.group_by_date(ents))
bentry = [b.get('entry', hhist.date(0, 0, 0)) for b in hdata.Bombers]
res = {}
for d in days:
row = [[0, 0] for b in hdata.Bombers]
for ent in d[1]:
if ent['class'] != 'A': continue
if ent['data']['type']['fb'] != 'B': continue
typ = ent['data']['type']['ti']
if ent['data']['etyp'] == 'CT':
if d[0].next() != bentry[typ]:
row[typ][0] += 1
elif ent['data']['etyp'] == 'CR':
row[typ][1] -= 1
res[d[0]] = row
return (res)
def extract_profit(save, before=None, after=None, targ_id=None):
bombers = {b['id']:[b['type'], 0, True, True] for b in save.init.bombers}
targets = [[t['dmg'], 0, {i:0 for i in xrange(save.ntypes)}] for t in save.init.targets]
classes = [[tcls,tcls], [icls,icls]]
days = sorted(hhist.group_by_date(save.history))
for d in days:
daily_profit(d, bombers, targets, classes, d[0]>=after if after else True, d[0]>=before if before else False, targ_id=targ_id)
bombers = {i:bombers[i] for i in bombers if bombers[i][3]}
results = {i: {k:v for k,v in bombers.iteritems() if v[0] == i} for i in xrange(save.ntypes)}
full = {i: (len(results[i]), sum(v[1] for v in results[i].itervalues())) for i in results}
deadresults = {i: {k:v for k,v in results[i].iteritems() if not v[2]} for i in results}
dead = {i: (len(deadresults[i]), sum(v[1] for v in deadresults[i].itervalues())) for i in results}
if targ_id is None:
return {i: {'full':full[i], 'fullr':full[i][1]/full[i][0] if full[i][0] else 0,
'dead':dead[i], 'deadr':dead[i][1]/dead[i][0] if dead[i][0] else 0,
'opti':full[i][1]/dead[i][0] if dead[i][0] else 0}
for i in results
if save.prio[i] is not None or full[i][0]}
else:
return {i: {'full':full[i], 'fullr':full[i][1]/full[i][0] if full[i][0] else 0,
'dead':dead[i], 'deadr':dead[i][1]/targets[targ_id][2][i] if targets[targ_id][2][i] else 0,
'opti':full[i][1]/targets[targ_id][2][i] if targets[targ_id][2][i] else 0}
for i in results
if save.prio[i] is not None or full[i][0]}
import matplotlib.pyplot as plt
import optparse
def parse_args(argv):
x = optparse.OptionParser()
x.add_option('--legend', action='store_true', default=True)
x.add_option('--nolegend', dest='legend', action='store_false')
opts, args = x.parse_args()
return opts, args
if __name__ == '__main__':
opts, args = parse_args(sys.argv)
save = hsave.Save.parse(sys.stdin)
data = []
month = save.history[0]['date']
history = sorted(hhist.group_by_date(save.history))
i = 0
while month <= save.history[-1]['date']:
next = month.nextmonth()
d = month.copy()
types = {i:[0,0] for i in xrange(save.ntypes)}
while d < next:
if i >= len(history):
d = d.next()
continue
if history[i][0] > d:
d = d.next()
continue
if history[i][0] < d:
raise hhist.OutOfOrder(d, history[i][0])
raiding = {}
def extract_profit(save, before=None, after=None, targ_id=None):
bombers = {b['id']: [b['type'], 0, True, True] for b in save.init.bombers}
targets = [[t['dmg'], 0, {i: 0
for i in xrange(save.ntypes)}]
for t in save.init.targets]
classes = [[tcls, tcls], [icls, icls]]
days = sorted(hhist.group_by_date(save.history))
for d in days:
daily_profit(d,
bombers,
targets,
classes,
d[0] >= after if after else True,
d[0] >= before if before else False,
targ_id=targ_id)
bombers = {i: bombers[i] for i in bombers if bombers[i][3]}
results = {
i: {k: v
for k, v in bombers.iteritems() if v[0] == i}
for i in xrange(save.ntypes)
}
full = {
i: (len(results[i]), sum(v[1] for v in results[i].itervalues()))
for i in results
}
deadresults = {
i: {k: v
for k, v in results[i].iteritems() if not v[2]}
for i in results
}
dead = {
i:
(len(deadresults[i]), sum(v[1] for v in deadresults[i].itervalues()))
for i in results
}
if targ_id is None:
return {
i: {
'full': full[i],
'fullr': full[i][1] / full[i][0] if full[i][0] else 0,
'dead': dead[i],
'deadr': dead[i][1] / dead[i][0] if dead[i][0] else 0,
'opti': full[i][1] / dead[i][0] if dead[i][0] else 0
}
for i in results if save.prio[i] is not None or full[i][0]
}
else:
return {
i: {
'full':
full[i],
'fullr':
full[i][1] / full[i][0] if full[i][0] else 0,
'dead':
dead[i],
'deadr':
dead[i][1] /
targets[targ_id][2][i] if targets[targ_id][2][i] else 0,
'opti':
full[i][1] /
targets[targ_id][2][i] if targets[targ_id][2][i] else 0
}
for i in results if save.prio[i] is not None or full[i][0]
}