def plotAndSave(od,ed,fn): surprise = Surprise(od, plotprefix="") edv = surprise.createVisualiser(50,50) #fig=edv.plotSurpriseGradient() fig = od.plotArtefacts(stroke='black',fill='white') edv.plotExpectationContours(plot=fig,showDU=True,showMU=True) #edv.plotUncertaintyChannel(onMedian=False,plot=pl.gcf().add_subplot(14,1,14)) edv.save(fn)
defaults = {'C': 3,'gamma': 0.1}
val1 = ['Release Year']
val2 = ['Width (mm)']
for v1 in val1:
for v2 in val2:
if v1 is not v2:
start_time = time.time()
print "Modelling",v1,"(independent) against",v2,"(dependent)."
od = Updater(parser, v1, contours, v2, None)
#fig = od.plotObservedContours()
if (v1,v2) in found.keys():
#ed = ExpectedDistribution(od,found[(v1,v2)])
s = Surprise(od,params=found[(v1,v2)])
else:
#ed = ExpectedDistribution(od,defaults)
s = Surprise(od,params=defaults)
edv = s.createVisualiser(100,100) #ExpectedDistributionVisualiser(ed,od,None,50,20)
edv.setLimits()
#fig=edv.plotSurpriseGradient()
fig=od.plotArtefacts(stroke='black',fill='black')
#od.plotObservedContours(plot=fig)
edv.plotExpectationContours(plot=fig,showDU=True,showMU=True)
#edv.plotUncertaintyChannel(onMedian=False,plot=pl.gcf().add_subplot(14,1,14))
fn = "".join(['-'.join([v1,v2,str(od.weight_std_ratio),str(s.params['C']),str(s.params['gamma']),'plotone.png'])])
edv.save(fn)
#edv.show()
print time.time() - start_time, "seconds"
mpl.rc('figure',figsize=[18, 12])
mpl.rc('figure.subplot',left=0.05,right=0.995,top=0.995,bottom=0.05)
namecols = [0]
timecols = [2]
valcols = [2,3,4,5,6,7,8,9,10,11,12,13,14]
parser = Parser("data/AllPhoneData_pruned.csv",namecols,timecols,valcols)
contours = 4
properties = parser.getProperties()
gridlog = Log(sys.argv[1])
for ind_attr in properties:
for dep_attr in properties:
if ind_attr == dep_attr:
continue
updater = Updater(parser, ind_attr, contours, dep_attr, None)
surprise = None
params = gridlog.getBestParams(ind_attr,dep_attr)
if params is not None:
print "Found",params,"for independent:",ind_attr,"dependent:",dep_attr
surprise = Surprise(updater, params=params,lims=updater.allLimits([5,5]))
else:
print "Found no params in log for independent:",ind_attr,"dependent:",dep_attr,", using defaults"
surprise = Surprise(updater, params={'C':1,'gamma':0.01},lims=updater.allLimits([5,5]))
edv = surprise.createVisualiser(250,100)
fig=edv.plotSurpriseGradient()
updater.plotArtefacts(plot=fig,stroke='black',fill='white')
updater.plotObservedContours(plot=fig)
edv.plotExpectationContours(plot=fig,showDU=True,showMU=True)
fn = "".join(['-'.join([ind_attr,dep_attr,str(updater.weight_std_ratio),str(surprise.ed.params[0.5]['C']),str(surprise.ed.params[0.5]['gamma'])])+'_hires.png'])
edv.save(fn)
