output = open(args.output + "/" + blog + '_PREw_predTime.pkl', 'wb')
cPickle.dump(prec_curveWA, output)
output = open(args.output + "/" + blog + '_RECw_predTime.pkl', 'wb')
cPickle.dump(rec_curveWA, output)
output = open(args.output + "/" + blog + '_F1Mw_predTime.pkl', 'wb')
cPickle.dump(f1_curveWA, output)
#Plot results
#print acc_curve
#xlb,dat_crv,lb_crv=plOT.getScoresCurves(acc_curve,nyrs)
#print xlb
#print dat_crv
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(acc_curveWA, nyrs)
legends = ["Years", "Accuracy", "Accuracy of predictions over time"]
#plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+blog+"_acc_svc_ovrtm.png")
plOT.plotBehaviorN(xlbWA, dat_crvWA, lb_crvWA, legends,
"../plots/" + blog + "_accWA_svc_ovrtm.png")
#xlb,dat_crv,lb_crv=plOT.getScoresCurves(prec_curve,nyrs)
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(prec_curveWA, nyrs)
legends = ["Years", "Precision", "Precision of predictions over time"]
#plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+blog+"_prec_svc_ovrtm.png")
plOT.plotBehaviorN(xlbWA, dat_crvWA, lb_crvWA, legends,
"../plots/" + blog + "_precWA_svc_ovrtm.png")
#xlb,dat_crv,lb_crv=plOT.getScoresCurves(rec_curve,nyrs)
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(rec_curveWA, nyrs)
legends = ["Years", "recall", "Recall of predictions over time"]
#plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+blog+"_rec_svc_ovrtm.png")
plOT.plotBehaviorN(xlbWA, dat_crvWA, lb_crvWA, legends,
"../plots/" + blog + "_recWA_svc_ovrtm.png")
#cPickle.dump(acc_curveWA, output)
#output = open(args.output+"/"+blog+'_PREw_predTime.pkl', 'wb')
#cPickle.dump(prec_curveWA, output)
#output = open(args.output+"/"+blog+'_RECw_predTime.pkl', 'wb')
#cPickle.dump(rec_curveWA, output)
#output = open(args.output+"/"+blog+'_F1Mw_predTime.pkl', 'wb')
#cPickle.dump(f1_curveWA, output)
#Plot results
#print acc_curve
xlb, dat_crv, lb_crv = plOT.getScoresCurves(acc_curve, nyrs)
#print xlb
#print dat_crv
#xlbWA,dat_crvWA,lb_crvWA=plOT.getScoresCurves(acc_curveWA,nyrs)
legends = ["Years", "Accuracy", "Accuracy of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
"../plots/" + blog + "_acc_svc_ovrtm.png")
#plOT.plotBehaviorN(xlbWA,dat_crvWA,lb_crv,legends,"../plots/"+blog+"_accWA_svc_ovrtm.png")
xlb, dat_crv, lb_crv = plOT.getScoresCurves(prec_curve, nyrs)
#xlbWA,dat_crvWA,lb_crvWA=plOT.getScoresCurves(prec_curveWA,nyrs)
legends = ["Years", "Precision", "Precision of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
"../plots/" + blog + "_prec_svc_ovrtm.png")
#plOT.plotBehaviorN(xlbWA,dat_crvWA,lb_crv,legends,"../plots/"+blog+"_precWA_svc_ovrtm.png")
xlb, dat_crv, lb_crv = plOT.getScoresCurves(rec_curve, nyrs)
#xlbWA,dat_crvWA,lb_crvWA=plOT.getScoresCurves(rec_curveWA,nyrs)
legends = ["Years", "recall", "Recall of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
"../plots/" + blog + "_rec_svc_ovrtm.png")
#plOT.plotBehaviorN(xlbWA,dat_crvWA,lb_crv,legends,"../plots/"+blog+"_recWA_svc_ovrtm.png")
cPickle.dump(acc_curveWA, output)
output = open(resDirSV + blog + '_PREw_predTime.pkl', 'wb')
cPickle.dump(prec_curveWA, output)
output = open(resDirSV + blog + '_RECw_predTime.pkl', 'wb')
cPickle.dump(rec_curveWA, output)
output = open(resDirSV + blog + '_F1Mw_predTime.pkl', 'wb')
cPickle.dump(f1_curveWA, output)
#Plot results
#print acc_curve
xlb, dat_crv, lb_crv = plOT.getScoresCurves(acc_curve, nyrs)
#print xlb
#print dat_crv
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(acc_curveWA, nyrs)
legends = ["Years", "Accuracy", "Accuracy of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
plotsDir + blog + "_acc_svc_ovrtm.png")
plOT.plotBehaviorN(xlbWA, dat_crvWA, lb_crv, legends,
plotsDir + blog + "_accWA_svc_ovrtm.png")
xlb, dat_crv, lb_crv = plOT.getScoresCurves(prec_curve, nyrs)
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(prec_curveWA, nyrs)
legends = ["Years", "Precision", "Precision of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
plotsDir + blog + "_prec_svc_ovrtm.png")
plOT.plotBehaviorN(xlbWA, dat_crvWA, lb_crv, legends,
plotsDir + blog + "_precWA_svc_ovrtm.png")
xlb, dat_crv, lb_crv = plOT.getScoresCurves(rec_curve, nyrs)
xlbWA, dat_crvWA, lb_crvWA = plOT.getScoresCurves(rec_curveWA, nyrs)
legends = ["Years", "recall", "Recall of predictions over time"]
plOT.plotBehaviorN(xlb, dat_crv, lb_crv, legends,
#a.append(0)
g += 2
else:
a.append(float(y))
data.append(a)
else:
for y in dat:
if y == "":
#a.append(0)
g += 2
else:
a.append(int(y))
data.append(a)
t += 1
return data
path = "../comparative/"
#allfiles=os.listdir("latestTAL/predOT-master/results/shots/predictions")
allfiles = next(os.walk(path))[2]
lb_crv = ["lastYr", "eachYr", "eachYrW"]
for blf in allfiles:
prplt = getDataToPlot(path + blf)
print prplt
blname = blf.split('.')[0]
legends = [
"Years", "F1-measure",
"Comparative of approaches for re-training over time"
]
plOT.plotBehaviorN(prplt[0], prplt[1:], lb_crv, legends,
path + "plots/" + blname + "_f1_3approach.png")
# -*- coding: utf-8 -*- """ Created on Sat Jan 27 20:53:28 2018 @author: ivan """ import cPickle import plotOverTime as plOT fileIn="../testing/test_correct_nologs/results/coupleofpixels_F1M_predTime.pkl" output = open(fileIn) restoredVar=cPickle.load(output) print type(restoredVar) #nyrs=[2009,2010,2011,2012,2013,2014,2015] nyrs=4 xlb,dat_crv,lb_crv=plOT.getScoresCurves(restoredVar,nyrs) print dat_crv print xlb #xlbWA,dat_crvWA,lb_crvWA=plOT.getScoresCurves(f1_curveWA,nyrs) legends=["Years","f1-measure","F1-measure of predictions over time"] plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends) #plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+blog+"_f1_svc_ovrtm.png") #plOT.plotBehaviorN(xlbWA,dat_crvWA,lb_crv,legends,"../plots/"+blog+"_f1WA_svc_ovrtm.png")
if tictac:
print datetime.now() - startTime
if v:
print "-------------------------------------------------------"
# break
#Plot results
#a=[[0.6,0.8,1,0.32],[0.47,0.5,.21,0.9]]
Sco_crv, Yr_crv = plOT.getScoresCurve(acc_curve)
Sco_crvWA, Yr_crvWA = plOT.getScoresCurve(acc_curveWA)
curvesToplot = [Sco_crv, Sco_crvWA]
#b=[2007,2008,2009,2010]
#c=[2007,2008]
#x=["x label","y label","title"]
#plotBehaviorN(b,a,c,x,"sample.png")
plOT.plotBehaviorN(b, curvesToplot, c, x, "sample.png")
#save results into files
output = open(args.output + "/" + blog + '_ACC_predTime.pkl', 'wb')
cPickle.dump(acc_curve, output)
output = open(args.output + "/" + blog + '_PRE_predTime.pkl', 'wb')
cPickle.dump(prec_curve, output)
output = open(args.output + "/" + blog + '_REC_predTime.pkl', 'wb')
cPickle.dump(rec_curve, output)
output = open(args.output + "/" + blog + '_F1M_predTime.pkl', 'wb')
cPickle.dump(f1_curve, output)
output = open(args.output + "/" + blog + '_ACCw_predTime.pkl', 'wb')
cPickle.dump(acc_curveWA, output)
output = open(args.output + "/" + blog + '_PREw_predTime.pkl', 'wb')
cPickle.dump(prec_curveWA, output)
#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]
#nyrs=4
xlb,dat_crv,lb_crv=plOT.getScoresCurves(restoredVar,nyrs)
#print dat_crv
#print xlb
#xlbWA,dat_crvWA,lb_crvWA=plOT.getScoresCurves(f1_curveWA,nyrs)
operMes=resultType(fnamep[1])
legends=["Years",operMes,operMes+" of predictions over time"]
plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+args.blog+"_"+fnamep[1]+"_svc_ovrtm.png")
#plOT.plotBehaviorN(xlb,dat_crv,lb_crv,legends,"../plots/"+blog+"_f1_svc_ovrtm.png")
#plOT.plotBehaviorN(xlbWA,dat_crvWA,lb_crv,legends,"../plots/"+blog+"_f1WA_svc_ovrtm.png")