#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(dep_attr)
#OD.save(ind_attr+'-'+dep_attr+'-'+str(w)+'.png')
#OD.save("".join([ind_attr,dep_attr,'_David.pdf']))
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()
'''
#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)
edv.save('dummy.pdf')
#'''
gammas['RAM Capacity (Mb)'] = 1e-2
gammas['ROM Capacity (Mb)'] = 1e-2
gammas['Storage (Mb)'] = 1
gammas['CPU Clock (MHz)'] = 1e-2
gammas['Display Diagonal (in)'] = 1e-2
gammas['Display Width(px)'] = 1e-2
gammas['Display Length(px)'] = 1e-2
gammas['Width (mm)'] = 1e-2
gammas['Length (mm)'] = 1e-2
gammas['Depth (mm)'] = 1e-2
gammas['Volume (cubic cm)'] = 1e-2
gammas['Mass (grams)'] = 1e-2
gammas['Pixel Density (per inch)'] = 1e-2
#Get either every dimension or a single dimension
val1s = parser.getProperties()
val2s = parser.getProperties()
# Values that we've found through previous executions of this grid-search
printFound = True
found = {}
#found[('Release Year','Width (mm)')] = {'C':1000,'gamma':0.1}
prefix = "gridoutput/"
if not os.path.exists(prefix):
os.makedirs(prefix)
t = time.localtime(time.time())
logfn = os.path.join(prefix,"gridlog_"+str(t[0])+'.'+str(t[1])+'.'+str(t[2])+'_'+str(t[3])+'.'+str(t[4])+'.'+str(t[5])+".xml")
with open(logfn,'w') as f:
writer = XMLWriter(f)
rootnode = writer.start("root")
