def pie_graph(start_time,end_time,groupby,generate,**kwargs):
start = time.time()
graph_data = retrieve_date(start_time,end_time,groupby,generate,**kwargs)
data_dict = Counter()
for key,columns in graph_data:
data_dict[columns[groupby]] +=columns[generate]
#print columns[groupby],columns[generate]
#pairs = zip(groupby_list,sum_generate_list)
pairs = data_dict.items()
pairs.sort(key=lambda x:x[1],reverse=True)
groupby_list,sum_generate_list = zip(*pairs)
groupby_list = list(groupby_list)
sum_generate_list = list(sum_generate_list)
#print type(groupby_list),type(sum_generate_list)
if len(groupby_list)>10:
groupby_list = groupby_list[:10]
groupby_list.extend(['']*(len(sum_generate_list)-10))
end = time.time()
def my_display( x ):
if x > 5:
return '%.1f' % x + '%'
else:
return ""
explode=[.0]*len(groupby_list)
explode[0] = 0
pylab.figure()
pylab.pie(sum_generate_list,labels=groupby_list,autopct=my_display,shadow=False,explode=explode)
pylab.title('%s groupby %s from %s to %s'%(generate,groupby,start_time,end_time))
pylab.xlabel('Processing time is: %.5ss'%(end-start))
pylab.savefig('foo.png')
imgData = cStringIO.StringIO()
pylab.savefig(imgData, format='png')
imgData.seek(0)
pylab.close()
return imgData
def generate_linegraph(start_time="",end_time="",groupby="unknow",generate="unknow",cumulative=False,**kwargs):
'''generate:CPUTime,DiskSpace,ExecTime,InputSandBoxSize,OutPutSandBoxSize,JobCount
groupby:site,user,processingtype,country,grid
dafaule cumulative=Falese,if you want to generate a cumulative graph,set it True
'''
#day_start_time = int(time.mktime(time.strptime(start_time,'%Y-%m-%d'))/86400)
#day_finish_time = int(time.mktime(time.strptime(finish_time,'%Y-%m-%d'))/86400)
if((generate=="unknow") or(groupby=="unknow")):
print "error"
return -1
groupby_list = []
fig = figure()
ax = axes()
start = time.time()
zorder = 0.0
y_max = 0.0
y_max_list = []
data_dict = {}
graph_data = retrieve_date(start_time,end_time,groupby,generate,**kwargs)
for key,columns in graph_data:
data_dict.setdefault(columns[groupby],{'time':[],'value':[]})
data_dict[columns[groupby]]['time'].append(columns["startTime"])
data_dict[columns[groupby]]['value'].append(columns[generate])
#print data_dict
if cumulative:
for key in data_dict.keys():
data_dict[key]['value'] = make_cumulative_data(data_dict[key]['value'])
#print data_dict
#return 0
for key in data_dict.keys():
groupby_list.append(key)
color = generate_color(str(key))
x_min = data_dict[key]['time'][0]
x_max = data_dict[key]['time'][-1]
y_tmp_max = max(data_dict[key]['value'])
if y_max<y_tmp_max: y_max = y_tmp_max
y_max_list.append(y_max)
'''
#set the value of Y-axis don't konw the unit
if generate in ("CPUTime","ExecTime"):
value_list = [int(item/86400) for item in value_list]
ax.set_ylabel("days")
elif generate in ("DiskSpace","InputSandBoxSize","OutputSandBoxSize"):
value_list = [int(item/(1024*1024)) for item in value_list]
ax.set_ylabel("MB")
else:
ax.set_ylabel("Total")
'''
pairs = zip(data_dict[key]['value'],data_dict[key]['time'])
pairs = [(x_min,0)]+pairs+[(x_max,0)]
poly = Polygon(pairs,fill=True,facecolor=color,zorder=-y_max)
ax.add_patch(poly)
zorder -=0.1
stamp_start_time = int(time.mktime(time.strptime(start_time,'%Y-%m-%d')))
stamp_end_time = int(time.mktime(time.strptime(end_time,'%Y-%m-%d')))
ax.set_xlim(stamp_start_time,stamp_end_time+1)
ax.set_ylim(0,max(y_max_list)+1)
ax.set_xticklabels([time.strftime('%y-%m-%d',time.localtime(x_time)) for x_time in ax.get_xticks()])
#set the legend
fontP = FontProperties() #set legend size
fontP.set_size('xx-small')
ax.legend(groupby_list,loc=0,bbox_to_anchor=(1,1.05),prop = fontP)
title('%s groupby %s from %s to %s'%(generate,groupby,start_time,end_time))
end = time.time()
xlabel('Processing time is: %.5ss'%(end-start))
savefig('linegraph')
imgData = cStringIO.StringIO()
savefig(imgData, format='png')
imgData.seek(0)
close()
return imgData
