tictac = args.time
if tictac:
startTime = datetime.now()
#variables where the final results will be stored
acc_curve = []
prec_curve = []
rec_curve = []
f1_curve = []
#acc_curveWA=[]
#prec_curveWA=[]
#rec_curveWA=[]
#f1_curveWA=[]
#create object blog Handler
curBlog = flog.Blog(blog)
#first_year=earliest year of the data
first_year = curBlog.getBlogOriginDate().year
#last_year=latest year of the data
last_year = curBlog.getBlogLastDate().year
nyrs = last_year - first_year
#last_year=2013
if v:
print "blog's life from " + str(first_year) + " to " + str(last_year)
if v:
print "///////////////////////////////////////////////////////////"
#for each year
#fix the hypothetical current year=curr_yr
for curr_year in range(first_year, last_year):
#get all examples up to curr_yr(included)=pre_train_set
#pre_train_set=curBlog.getPostsBetweeDates(str(first_year)+"-01-01",str(curr_year)+"-12-31")
return "F1-measure"
if tp=="PRE" or tp=="PREw":
return "Precision"
if tp=="REC" or tp=="RECw":
return "Recall"
parser = argparse.ArgumentParser(description='process to evaluate the fall in performance in category prediction over time')
parser.add_argument('blog', metavar='blog', type=str, help='location of the blog')
args=parser.parse_args()
path="latestTAL/predOT-master/results/"+args.blog+"/"
#allfiles=os.listdir("latestTAL/predOT-master/results/shots/predictions")
#allfiles=next(os.walk(path))[2]
#fileIn="../testing/test_correct_nologs/results/coupleofpixels_F1M_predTime.pkl"
curBlog=flog.Blog(args.blog)
#first_year=earliest year of the data
first_year=curBlog.getBlogOriginDate().year
#last_year=latest year of the data
last_year=curBlog.getBlogLastDate().year
nyrs=last_year-first_year
for fl in next(os.walk(path))[2]:
fileIn=fl
output = open(fileIn)
restoredVar=cPickle.load(output)
fnamep=fileIn.split('_')
#print type(restoredVar)
#nyrs=[2009,2010,2011,2012,2013,2014,2015]