#This main function has not been maintained and is probably crashy and unreliable, it's here for legacy only.
if __name__ == "__main__":
weightFactors = [0.15]
#Old phone data import
#namecols = [0]
#timecols = [2]
#valcols = [2,3,4,5,6,7,8,9,10,11,12,13,14]
#parser = Parser("AllPhoneData_pruned.csv",namecols,timecols,valcols)
namecols = [0]
timecols = [2]
valcols = range(2,15)
contours = 4
parser = Parser("AllPhoneData_pruned.csv",namecols,timecols,valcols)
properties = parser.getProperties()[0:2]
for ind_attr in properties:
for dep_attr in properties:
if ind_attr == dep_attr:
continue
ods = []
for w in weightFactors:
ods.append(ObservedDistribution(parser, ind_attr, contours, dep_attr, w))
# Plotting code
#fig = OD.plotArtefacts()
#fig = OD.plotObservedContours(plot=fig, alpha=.9)
#fig.set_title(str(w))
#fig.set_xlabel(ind_attr)
fig.set_ylabel("Surprise (ignore sign)")
#print 'Surprisingness = ',round(surprise,3),', raw = ',abs(round(raw_surprise,3))
return surprise,raw_surprise
'''
#This main function has not been maintained and is probably crashy and unreliable, it's here for legacy only.
if __name__ == "__main__":
mpl.rc('figure',figsize=[9, 6])
mpl.rc('figure.subplot',left=0.05,right=0.995,top=0.995,bottom=0.05)
contours = 6
namecols = [1,2]
timecols = [11]
valcols = [3,4,5,6,7,8,9,11]
parser = Parser("prunedPhones.csv",namecols,timecols,valcols)
#Get either every dimension or a single dimension
val1s = [parser.getProperties()[0]]
val2s = [parser.getProperties()[1]]
weightFactors = [0.2]
Cs = [20]
gammas = [0.2]
#'''
od = ObservedDistribution(parser, val1s[0], contours, val2s[0], weightFactors[0])
ed = ExpectedDistribution(od,parallel=False)
edv = ExpectedDistributionVisualiser(ed,od,50,50)
fig = od.plotObservedContours(title='', alpha=0.25)
#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)
if __name__ == "__main__":
mpl.rc('figure',figsize=[18, 12])
mpl.rc('figure.subplot',left=0.075,right=0.995,top=0.925,bottom=0.075)
contours = 3
namecols = [0]
timecols = [2]
valcols = range(2,15)
parser = Parser("data/AllPhoneData_pruned.csv",namecols,timecols,valcols)
# Values to start the search with
Cs = {}
Cs['Release Year'] = 1
Cs['RAM Capacity (Mb)'] = 1
Cs['ROM Capacity (Mb)'] = 1
Cs['Storage (Mb)'] = 1
Cs['CPU Clock (MHz)'] = 1
Cs['Display Diagonal (in)'] = 1
Cs['Display Width(px)'] = 1
Cs['Display Length(px)'] = 1
Cs['Width (mm)'] = 1
Cs['Length (mm)'] = 1
Cs['Depth (mm)'] = 1
def plotThings(updater):
fig = updater.plotArtefacts()
fig = updater.plotObservedContours(plot=fig, alpha=.9)
fig.set_title(str(w))
fig.set_xlabel(ind_attr)
fig.set_ylabel(dep_attr)
if __name__ == "__main__":
weightFactors = [.15]
condition_train = lambda inst: inst.time < 2001
condition_test = lambda inst: inst.time >= 2001
namecols = [0]
timecols = [2]
valcols = [2,3,4,5,6,7,8,9,10,11,12,13,14]
parser_train = Parser("data/AllPhoneData_pruned.csv",namecols,timecols,valcols,condition_train)
parser_test = Parser("data/AllPhoneData_pruned.csv",namecols,timecols,valcols,condition_test)
contours = 6
properties = parser_train.getProperties()
for ind_attr in [properties[0]]:
for dep_attr in [properties[-1]]:
if ind_attr == dep_attr:
continue
for w in weightFactors:
updater = Updater(parser_train, ind_attr, contours, dep_attr, w, parser_test=parser_test, prefix="ods/")
plotThings(updater)
updater.update(2001)
plotThings(updater)
updater.show()
def findFile(namestart, parser, prefix='.', dir_name='.'):
for f in os.listdir(prefix):
fn, ext = os.path.splitext(f)
if ext == ".cbwb" and fn.startswith(namestart):
index = int(fn.strip(namestart))
print "Found",f,"and setting index to", index
if not parser is None:
parser.index = index + 1
return readObject(prefix+'/'+f)
return Node(directory=dir_name)
if __name__ == "__main__":
# Read in Data
namecols = [0]
timecols = [2]
valcols = [9]
parser = Parser("AllPhoneData_pruned.csv",namecols,timecols,valcols,normalize=True)
#t = readObject('test.cbwb')
t = findFile('test_', parser)
old_index = parser.index
while not parser.atEnd():
addInc(t, parser.getNext())
if parser.index >= old_index * 2:
t.saveObject('test_'+str(parser.index)+'.cbwb', remove='test_'+str(old_index)+'.cbwb')
old_index = parser.index
t.viz.plotClusters('time', Instance.properties[0], depth=2)
t.saveObject('test.cbwb')
