import json
from matplotlib import pyplot as plt
from island.match import Match
from island.matches import Matches

matches = Matches('wos-data-new')
max_round = 17

alive = []
yerr_min = []
yerr_max = []
x = []
al_al = []

survivals = {}
with open('winner.json','r') as f:
    survivals = json.load(f)

for i in range(max_round):
    defects = []
    for j in range(len(matches.data)):
        defector = set()
        for row in matches.data[j].query('action', 'done').where(lambda x: x['rno']==i+1 and (x['act_a']=='D' or x['act_b']=='D')).raw_data:
            if row['act_a']=='D':
                defector.add(row['a'])
            if row['act_b'] == 'D':
                defector.add(row['b'])

        if defector:
            # print("[%d,%d] %s" % (i,j,str(defector)))
            incr = 0
            for k in survivals[matches.names[j]]:
                if k in defector:
                    incr += 1
                    # print(k)
            defects.append(float(incr) / float(len(defector)))

    print(i)
    print(defects)
    if defects:

        al_al.append(defects)
        alive.append(sum(defects) / len(defects))
        yerr_min.append(alive[-1] - min(defects))
        yerr_max.append(max(defects) - alive[-1])
        print("%f, %f, %f"%(yerr_min[-1], yerr_max[-1], alive[-1]))
        x.append(i+1)
    else:
        al_al.append([])

plt.figure()
# plt.errorbar(x, alive, yerr=[yerr_min, yerr_max], fmt='o', capsize=4)
plt.boxplot(al_al, showmeans=True, meanline=True)
plt.show()
# plt.savefig('graph/survive_after_defect.png')