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Difficulty_ScoreAnalyze.py
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Difficulty_ScoreAnalyze.py
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import json
import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
def Analyze():
diff = [[],[]]
score = [[],[]]
diffSocre = [dict(),dict()]
for ids in range(1,16):
diffSocre[0]['%02d'%ids] = []
diffSocre[1]['%02d'%ids] = []
# print(diffSocre)
with open('./musync_data/SavAnalyze.json','r',encoding='utf8') as file:
data = json.load(file)
for ids in data["SaveData"]:
if float(ids["SyncNumber"][:-1]) != 0:
diffcute = int(ids["SongName"][3])
if ids["SongName"][1]=="4Key":
diff[0].append(diffcute-0.15)
score[0].append(float(ids["SyncNumber"][:-1]))
diffSocre[0]['%02d'%diffcute] += [float(ids["SyncNumber"][:-1])]
else: # 6Key Mode
diff[1].append(diffcute+0.15)
score[1].append(float(ids["SyncNumber"][:-1]))
diffSocre[1]['%02d'%diffcute] += [float(ids["SyncNumber"][:-1])]
# print(diffSocre)
diffSocreTrim = [dict(),dict()]
for ids in range(0,2):
for idx in diffSocre[ids].keys():
if len(diffSocre[ids][idx]) != 0:
diffSocreTrim[ids][idx] = [round(sum(diffSocre[ids][idx])/len(diffSocre[ids][idx]),3),len(diffSocre[ids][idx])]
# else:
# diffSocre.pop(ids, None)
# print(diffSocreTrim)
fig = plt.figure('难度与分数散点图', figsize=(7, 8))
fig.clear()
fig.subplots_adjust(**{"left":0.083,"bottom":0.07,"right":0.60,"top":0.994})
ax = fig.add_subplot()
axR = ax.twinx()
ax.yaxis.set_major_locator(MultipleLocator(1))
axR.yaxis.set_major_locator(MultipleLocator(1))
ax.xaxis.set_major_locator(MultipleLocator(1))
ax.set_xlim(0,16)
minScore = int(min([min(score[0]),min(score[1])]))
ax.set_ylim(minScore-1,125)
axR.set_ylim(minScore-1,125)
labels = []
for ids in diffSocreTrim[0].keys():
labels.append(f"难度: 4K {ids} Avg:{'%.3f'%diffSocreTrim[0][ids][0]:0>7s}% 计数:{diffSocreTrim[0][ids][1]:0=2d}")
labels.append("")
for ids in diffSocreTrim[1].keys():
labels.append(f"难度: 6K {ids} Avg:{'%.3f'%diffSocreTrim[1][ids][0]:0>7s}% 计数:{diffSocreTrim[1][ids][1]:0=2d}")
print("\n".join(labels))
for ids in range(1,16):
ax.plot([ids]*(125-minScore+2),[ids for ids in range(minScore-1,126)],linestyle='--',alpha=0.6,linewidth=1)
# diffSocreTrim:[{'diff':[avg,count]}, {'diff':[avg,count]}]
# [4K, 6K]
for ids in range(0,2): #ids <= [4K, 6K]
for idx in diffSocreTrim[ids].keys(): #idx <= diff
ax.plot([i for i in range(int(idx)+1)] if ids else [i for i in range(int(idx),17)], # '6k=>' if ids else '<=4K'
[diffSocreTrim[ids][idx][0]]*(int(idx)+1) if ids else [diffSocreTrim[ids][idx][0]]*(17-int(idx)), # '6k=>' if ids else '<=4K'
linestyle='--',alpha=1,linewidth=1)
if minScore < 122:
ax.plot([i for i in range(17)],[122]*17,linestyle='-',alpha=0.7,linewidth=1,color='black')
ax.text(14.5,122.5,'BlackEx',ha='center',va='top',fontsize=7.5,alpha=0.7)
if minScore < 120:
ax.plot([i for i in range(17)],[120]*17,linestyle='-',alpha=0.7,linewidth=1,color='red')
ax.text(14.5,120.5,'RedEx',ha='center',va='top',fontsize=7.5,alpha=0.7)
if minScore < 117:
ax.plot([i for i in range(17)],[117]*17,linestyle='-',alpha=0.7,linewidth=1,color='cyan')
ax.text(14.5,117.5,'CyanEx',ha='center',va='top',fontsize=7.5,alpha=0.7)
if minScore < 110:
ax.plot([i for i in range(17)],[110]*17,linestyle='-',alpha=0.7,linewidth=1,color='blue')
ax.text(14.5,110.5,'S',ha='center',va='top',fontsize=7.5,alpha=0.7)
if minScore < 95:
ax.plot([i for i in range(17)],[95]*17,linestyle='-',alpha=0.7,linewidth=1,color='green')
ax.text(14.5,95.5,'A',ha='center',va='top',fontsize=7.5,alpha=0.7)
if minScore < 75:
ax.plot([i for i in range(17)],[75]*17,linestyle='-',alpha=0.7,linewidth=1,color='orange')
ax.text(14.5,75.5,'B',ha='center',va='top',fontsize=7.5,alpha=0.7)
# supported values are '-', '--', '-.', ':', 'None', ' ', '', 'solid', 'dashed', 'dashdot', 'dotted'
ax.plot([int(i) for i in diffSocreTrim[0].keys()],[diffSocreTrim[0][ids][0] for ids in diffSocreTrim[0].keys()],
linestyle='-',color='orange',marker="D",markerfacecolor="Blue",alpha=0.7,linewidth=2,
label="4Key Mode")
ax.plot([int(i) for i in diffSocreTrim[1].keys()],[diffSocreTrim[1][ids][0] for ids in diffSocreTrim[1].keys()],
linestyle='-',color='orange',marker="D",markerfacecolor="Red",alpha=0.7,linewidth=2,
label="6Key Mode")
ax.scatter(diff[0],score[0],alpha=0.7,color='#8A68D0',s=5)
ax.scatter(diff[1],score[1],alpha=0.7,color='#F83535',s=5)
ax.text(18.2,123,"\n".join(labels),ha="left",va="top",alpha=1,
fontdict={'family':'LXGW WenKai Mono','weight':'normal','size':10})
ax.legend(prop={'family':'LXGW WenKai Mono','weight':'normal','size':10},framealpha=0.4) #show label
ax.set_xlabel('Difficulty') #x_label
ax.set_ylabel('SYNC.Rate')#y_label
plt.show()
if __name__ == '__main__':
Analyze()