def main():
"""
This is the main function which calls all other functions to solve the
optimisation model
"""
# initialise the concreteModel
RSO_model = ConcreteModel()
# get the data input as objects
Excel_file = 'Pyomo_RSO_Parameter_Input.xlsx'
set_input, fixed_par, variable_par = data_construction(Excel_file)
# set initialisation
fset.set_initialisation(RSO_model, set_input)
# parameter initialisation
fpar.parameter_initialisation(RSO_model, fixed_par, variable_par)
# variable initialisation
fvar.variable_initialisation(RSO_model)
# constraint initialisation
fcon.constraint_definition(RSO_model)
# set up the model
opt = SolverFactory('cplex')
results = opt.solve(RSO_model, tee=True, symbolic_solver_labels=True)
RSO_model.solutions.store_to(results)
results.write(filename='solution.yml')
def save(self):
'''Saves the summarised texts to the Summaries folder.
Encodes saved files in UTF-8 Format - non-UTF-8 characters cannot be
saved.
Attributes:
summaryNumber: The number of previous summaries + 1
completeName: File name in the format of Summary_#_date.txt
Raises:
Exception: Any errors flagged and printed
'''
try:
summaryNumber = str(v.settings["noOfSummaries"])
completeName = ("Summary_#" + summaryNumber + "_" + v.date +
".txt")
with open(os.path.join('Summaries', completeName),
"w",
encoding="utf-8") as file:
file.write(E.encrypt(self.summary))
v.settings["noOfSummaries"] += 1
v.save()
except Exception as e:
print(e)
def build_max_size_array():
start_day = Variables.get_start_day();
end_day = Variables.get_end_day();
max_size_array = {};
for today in range(start_day, end_day + 1):
max_size_array[Decimal(today)] = max_size_by_day(Decimal(today))
return max_size_array
def deleteAll(tickerName):
fileVariables = Variables()
directory = fileVariables.directory
fileEnding = fileVariables.returnFileEnding(tickerName)
for i in fileEnding:
try:
os.remove(directory+i)
except:
pass
def commitPrefs(self):
pref = vars.getVars("Pref")
# On sauvegarde le nom du driver, car l'index peut changer
pref["AUDIO_DRIVER"] = self.au.GetValue()
# Max output channels available on the selected driver
if self.radioSame.GetValue() == 1:
pref["NCHNLS"] = self.currentDriverMaxChannels
elif self.radioDiff.GetValue() == 1:
pref["NCHNLS"] = int(self.chnls.GetValue())
# Speakers setup
pref["SPEAKERS_SETUP"] = self.numSpkChoices.GetSelection()
if pref["SPEAKERS_SETUP"] == 0:
vars.setVars("Speakers_setup", SETUP_STEREO)
pref["NUM_SPEAKERS"] = len(SETUP_STEREO)
elif pref["SPEAKERS_SETUP"] == 1:
vars.setVars("Speakers_setup", SETUP_QUAD)
pref["NUM_SPEAKERS"] = len(SETUP_QUAD)
elif pref["SPEAKERS_SETUP"] == 2:
vars.setVars("Speakers_setup", SETUP_OCTO_STEREO)
pref["NUM_SPEAKERS"] = len(SETUP_OCTO_STEREO)
elif pref["SPEAKERS_SETUP"] == 3:
vars.setVars("Speakers_setup", SETUP_OCTO_DIAMAND)
pref["NUM_SPEAKERS"] = len(SETUP_OCTO_DIAMAND)
else:
pass
# OSC
pref["OSCPORT"] = int(self.OSCPortText.GetValue())
def initSpkPos(self,pos):
initPos = vars.getVars("Speakers_setup")
spk = vars.getVars("Speakers")
for i in spk:
if i.isInside(pos):
self.currentSpeaker = i
spkIndex = spk.index(i)
self.currentSpeaker.x = initPos[spkIndex][0] * self.size[0] # FL 02/09/2017
self.currentSpeaker.y = initPos[spkIndex][1] * self.size[1] # FL 02/09/2017
break
self.speakerAdjusted() # FL 29/05/17
def start():
v.stopped = False
t1 = threading.Thread(target=serverLoop)
t1.start()
va.debug("Start Game")
game()
va.debug("After game")
payload = {"username": v.username, "disconnect": True}
jpayload = json.dumps(str(payload))
r = requests.post(v.url, data=jpayload)
v.stopped = True
def __init__(self, parent, pos=(0,0), size=(100,100), numSpeakers=2):
wx.Panel.__init__(self, parent, pos=pos, size=size)
self.SetBackgroundStyle(wx.BG_STYLE_CUSTOM)
self.audio = vars.getVars("Audio")
self.pos = None
self.size = size
self.currentCircle = None
self.currentSpeaker = None
self.isAList = False
self.catch = False
self.catchSpeaker = False
self.shift = False
self.alt = False
self.s = False
self.numSpeakers = numSpeakers # FL 29/05/17
#OSC Variables
self.incs = [0, 0, 0, 0]
self.absPos = [0, 0, 0, 0] # FL 04/09/2017
self.mode2 = False # FL 04/09/2017
# Creation des cercles/sources
self.blueCircle = Source(self.size[0]*BLUE_START[0], self.size[1]*BLUE_START[1], CIRCLE_RADIUS)
self.redCircle = Source(self.size[0]*RED_START[0], self.size[1]*RED_START[1], CIRCLE_RADIUS)
speakers = []
for i in range(self.numSpeakers):
setup = vars.getVars("Speakers_setup")
x, y = self.size[0]*setup[i][0], self.size[1]*setup[i][1] #FL 02/09/2017
speakers.append(Speaker(x, y, SPEAKER_RADIUS))
vars.setVars("Speakers", speakers)
# print vars.getVars("Speakers")[0].c
self.speakerAdjusted() # FL 29/05/17
# méthode pour les controles
self.Bind(wx.EVT_PAINT, self.onPaint)
self.Bind(wx.EVT_LEFT_DOWN, self.onLeftDown)
self.Bind(wx.EVT_LEFT_UP, self.onLeftUp)
self.Bind(wx.EVT_RIGHT_DOWN, self.onRightDown)
self.Bind(wx.EVT_MOTION, self.onMotion)
self.Bind(wx.EVT_KEY_DOWN, self.onKeyDown)
self.Bind(wx.EVT_KEY_UP, self.onKeyUp)
self.on_timer()
def types(self, Trees, l, errores, var):
correct = False
for d in Trees:
sr = ConvertFormat.ConvertFormat(l).Convert()
if sr != False:
result = d.PostOrder(d.root, sr)
if result == None:
correct = True
if Search.Search().SearchTheVar(var, l) == True:
errores.append(
'Error la variable ya ha sido declarada anteriormente '
+ l)
else:
au = l.split(' ')
if ReservedWords.ReservedWord().IsReservedWord(au[1]):
errores.append(
'Error no puedes nombrar a una varibale con una palabra reservada '
+ l)
else:
var.append(
Variables.Variables(au[0], au[1],
self.AsignarValores(
au[0])))
errores.append('Cadena correcta ' + l)
break
else:
correct = False
if correct == False:
errores.append('Error en ' + l + ' Error de tipo')
return errores, var
def drawWeights(self, t, ax, logId, command):
matrix = self.refreshData(logId)
# ax.clear()
#Time Array
tAr = matrix[0]
id = 1
for line in matrix[1:]: # 0,120,20):
mT = tAr
if self.setRange and self.hardLim and len(line) > self.xRange:
line = line[-self.xRange:]
mT = tAr[-self.xRange:]
setPixel = False
if len(command) > 1:
setPixel = command[1] == 'p'
label = ''
if setPixel:
if id > Var.numBrainNeurons:
label = 'W {}'.format(id-Var.numBrainNeurons)
else:
pixel = Var.idMapper(id)
label = 'Px({},{})'.format(pixel.x,pixel.y)
else:
label = 'W {}'.format(id)
pLine = ax.plot(mT, line, label=label)
ax.annotate(label + ": {:.2f}".format(float(line[-1])), xy=(mT[-1], line[-1]), size=11, va='center')
id =id+1
ax.set_title(self.commandsDic[command[0]])
ax.set_ylabel('Weight')
def drawWeights(i, ax, name):
# print(i,ax,name)
# coordinates = [[(float(i),j+((2.*i)/(j+1.)))for i in range(NENTRIES)]for j in range(NLINES)]
with open(name + '.csv') as csv_file:
# with open('left-weights.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
matrix = []
for i in csv_reader:
matrix.append(i)
# print(matrix)
NLINES = len(matrix[1])
NENTRIES = len(matrix)
# NLINES = 17
coordinates = [[(matrix[i][0], matrix[i][j])
for i in range(1, NENTRIES)]for j in range(1, NLINES)]
# print(coordinates[0])
# bins = np.arange(0,40,5)
ax.clear()
xLeft = 0.
xRight = 0.
for i in range(len(coordinates)): # 0,120,20):
line = coordinates[i]
xA = []
yA = []
for (x, y) in line:
xA.append(x)
yA.append(float(y))
# deviation = np.std(yA)
# print('i: {} corresponds to Pixel({},{}) '.format(i, NUM_PIXEL_X -
# (i_invers % (NUM_PIXEL_Y)), int(math.floor(i_invers/NUM_PIXEL_Y))))
# if deviation>1:
if i > 9:
pLine = ax.plot(xA, yA, label='jointNeuron({})'.format(i))
ax.annotate('jointNeuron({}): {:.2f} '.format(i, yA[len(
yA)-1]), xy=(xA[len(xA)-1], yA[len(yA)-1]), size=11, va='center')
else:
p = Var.idMapper(i+1)
pLine = ax.plot(xA, yA, label='Pixel({},{}) '.format(p.x, p.y))
# if deviation > 3:
ax.annotate('Pixel({},{}): {:.2f} '.format(p.x, p.y, yA[len(
yA)-1]), xy=(xA[len(xA)-1], yA[len(yA)-1]), size=11, va='center')
# plt.hist(yA,bins,histtype='bar',rwidth=0.3)
if i == 0:
if len(xA) > xRange:
xLeft = xA[-xRange]
xRight = xA[-1]
ax.set_title(name[:-8])
# ax.set_xlabel('Time')
ax.set_ylabel('Weight')
if setXLim and xLeft > 0.:
ax.set_xlim(left=float(xLeft), right=float(xRight))
def radiusZone(self, e):
x = e.value
speakers = vars.getVars("Speakers")
for i in range(len(speakers)):
speakers[i].setZoneRad(x)
self.surface.speakerAdjusted()
self.surface.Refresh()
def masterAmp(self, e):
x = e.value
audio = vars.getVars("Audio")
if x == -60:
audio.player.mul = 0
else:
audio.player.mul = self.convertToMul(x) #FL 22/05/17
def distance(self,pos):
for i in range(self.numSpeakers):
SpkPos = vars.getVars("Speakers")[i].getCenter()
SpkRad = vars.getVars("Speakers")[i].getZoneRad()
dist = math.sqrt(math.pow((pos[0]-SpkPos[0]),2) + math.pow((pos[1]-SpkPos[1]),2))
amp = max(0, 1. - dist / float(SpkRad))
if self.isAList:
self.audio.setBlueAmp(i,amp)
self.audio.setRedAmp(i,amp)
elif self.currentCircle == self.blueCircle:
self.audio.setBlueAmp(i,amp)
elif self.currentCircle == self.redCircle:
self.audio.setRedAmp(i,amp)
def server():
t = time.clock()
payload = {"username": v.username, "position": (v.posx, v.posy)}
jpayload = json.dumps(str(payload))
try:
r = requests.post(v.url, data=jpayload)
except Exception as e:
va.debug(e)
# Response, status etc
if r.status_code == 200:
v.data = literal_eval(r.text)
v.fetched = True
else:
print(r.status_code)
print(r.text)
#print(v.data)
v.fetchTime = time.clock() - t
def downloadAll(tickerName):
fileVariables = Variables()
directory = fileVariables.directory
fileEnding = fileVariables.returnFileEnding(tickerName)
urlList = fileVariables.returnUrlList(tickerName)
if not os.path.exists(directory):
os.makedirs(directory)
counter = 0
for i in urlList:
try:
request.urlretrieve(i,directory + fileEnding[counter])
counter += 1
except:
print(i + " download failed")
def get_corr_hist(tree, mva_name, variable, cut, type, mva_binning):
nutple_varname = variable
# we would not find "jet_pt_1_" in the variables list,
# so we transform it to "jet_pt[1]" if it matches the
# pattern
match = IndexMatch.search(variable)
if match:
nutple_varname = "%s[%s]" % (variable[:-3], match.group(1))
if nutple_varname in Variables.Variables:
draw_var = "%s:%s" % (mva_name, Variables.conv_unit(nutple_varname))
# conv_unit returns jet_pt[1] in the above case, transform it back
draw_var = draw_var.replace(nutple_varname, variable)
binning = "(%s,%d,%d,%d)" % (Variables.binning(nutple_varname),
mva_binning[0], mva_binning[1],
mva_binning[2])
unit = Variables.unit(nutple_varname)
if unit and unit != "":
xtitle = "%s [%s]" % (Variables.title(nutple_varname), unit)
else:
xtitle = Variables.title(nutple_varname)
else:
draw_var = "%s:%s" % (mva_name, variable)
binning = ""
xtitle = variable
hist_name = variable + "_hist_" + type
draw_cmd = "%s>>%s%s" % (draw_var, hist_name, binning)
#tree.Draw(draw_cmd, "%s * (mc_weight * sf_total * xs_weight)" % cut)
tree.Draw(draw_cmd, "%s * (mc_weight)" % cut)
hist = gDirectory.Get(hist_name)
hist.SetDirectory(gROOT)
hist.SetTitle(";%s;%s output" % (xtitle, mva_name))
for xbin in xrange(hist.GetNbinsX() + 2):
for ybin in xrange(hist.GetNbinsY() + 2):
if hist.GetBinContent(xbin, ybin) < 0:
hist.SetBinContent(xbin, ybin, 0)
return hist
def onSpeaker(self,pos):
spk = vars.getVars("Speakers")
for i in spk:
if i.isInside(pos):
self.currentSpeaker = i
self.catchSpeaker = True
break
else:
self.currentSpeaker = None
self.catchSpeaker = False
def _reset_param(self):
Variables.clear_default_domain()
Variables.set_default_domain({'H_bn_t':lv.H_bn,'H_dp_t':lv.H_dp,'H_ap_t':lv.H_ap,\
'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn,\
'H_dp_tt':lv.H_dp,'H_ap_tt':lv.H_ap,'H_tt_tt':lv.H_tt,\
'H_bn_0':lv.H_bn,'H_dp_0':lv.H_dp,'H_ap_0':lv.H_ap,'H_tt_0':lv.H_tt})
fH_bn_t_UAtt_H_bn_tt = Factor(('H_bn_t','UA_tt','H_bn_tt'))
fH_bn_t_UAtt_H_bn_tt.zero()
for inst in Utils.inst_filling({'H_bn_t':lv.H_bn,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn}):
if (('bn' in inst['UA_tt'] or inst['H_bn_t'] == 'o') and inst['H_bn_tt'] == 'o') or\
(('bn' not in inst['UA_tt'] and inst['H_bn_t'] == 'x') and inst['H_bn_tt'] == 'x'):
fH_bn_t_UAtt_H_bn_tt[inst] = 1
fH_dp_t_UAtt_H_dp_tt = Factor(('H_dp_t','UA_tt','H_dp_tt'))
fH_dp_t_UAtt_H_dp_tt.zero()
for inst in Utils.inst_filling({'H_dp_t':lv.H_dp,'UA_tt':lv.UA,'H_dp_tt':lv.H_dp}):
if (('dp' in inst['UA_tt'] or inst['H_dp_t'] == 'o') and inst['H_dp_tt'] == 'o') or\
(('dp' not in inst['UA_tt'] and inst['H_dp_t'] == 'x') and inst['H_dp_tt'] == 'x'):
fH_dp_t_UAtt_H_dp_tt[inst] = 1
fH_ap_t_UAtt_H_ap_tt = Factor(('H_ap_t','UA_tt','H_ap_tt'))
fH_ap_t_UAtt_H_ap_tt.zero()
for inst in Utils.inst_filling({'H_ap_t':lv.H_ap,'UA_tt':lv.UA,'H_ap_tt':lv.H_ap}):
if (('ap' in inst['UA_tt'] or inst['H_ap_t'] == 'o') and inst['H_ap_tt'] == 'o') or\
(('ap' not in inst['UA_tt'] and inst['H_ap_t'] == 'x') and inst['H_ap_tt'] == 'x'):
fH_ap_t_UAtt_H_ap_tt[inst] = 1
fH_tt_t_UAtt_H_tt_tt = Factor(('H_tt_t','UA_tt','H_tt_tt'))
fH_tt_t_UAtt_H_tt_tt.zero()
for inst in Utils.inst_filling({'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_tt_tt':lv.H_tt}):
if (('tt' in inst['UA_tt'] or inst['H_tt_t'] == 'o') and inst['H_tt_tt'] == 'o') or\
(('tt' not in inst['UA_tt'] and inst['H_tt_t'] == 'x') and inst['H_tt_tt'] == 'x'):
fH_tt_t_UAtt_H_tt_tt[inst] = 1
fHt_UAtt_Htt = fH_bn_t_UAtt_H_bn_tt * fH_dp_t_UAtt_H_dp_tt * fH_ap_t_UAtt_H_ap_tt * fH_tt_t_UAtt_H_tt_tt
ls.store_model(fHt_UAtt_Htt,'_factor_Ht_UAtt_Htt.model')
fGbn_Ht_SAtt_UAtt = CPT(Factor(('H_bn_t','H_dp_t','H_ap_t','H_tt_t','UA_tt')),child='UA_tt',cpt_force=True)
factor_template = {'G_bn':lv.G_bn,'SA':lv.SA}
for factor in Utils.inst_filling(factor_template):
ls.store_model(fGbn_Ht_SAtt_UAtt,('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-'))
del fGbn_Ht_SAtt_UAtt
def onPaint(self, e):
w,h = self.GetSize()
dc = wx.AutoBufferedPaintDC(self)
# Surface
dc.SetBrush(wx.Brush(COLOR_BACK))
dc.DrawRectangle(0, 0, w+1, h+1)
# Le quadrillage
dc.SetPen(wx.Pen(COLOR_GRID, 2))
# for i in range(0, 600, 25):
# dc.DrawLine(0, i, w, i)
# dc.DrawLine(i, 0, i, h)
dc.SetBrush(wx.Brush(COLOR_GRID,style=wx.TRANSPARENT))
for i in range(8):
dc.DrawCircle(w/2,h/2,GRID_CIRCLE_RADIUS*(7*i))
# dc.DrawCircle(300,300,CIRCLE_RADIUS*(7*i))
for i in range(self.numSpeakers):
vars.getVars("Speakers")[i].draw(dc, COLOR_AV)
vars.getVars("Speakers")[i].drawZone(dc, COLOR_AV)
# ecriture de valeurs
if self.catch:
# conversion des positions X et Y entre 0 et 1
x = self.pos[0] / float(w)
y = 1.- self.pos[1] / float(h)
# affiche la position normalisee du pointeur
dc.DrawText("%.3f, %.3f" % (x,y), 10, 10)
# Les cercles
self.blueCircle.draw(dc,COLOR_BLUE)
self.redCircle.draw(dc,COLOR_RED)
def quit(self, e):
if os.path.isfile(EMPTY_AUDIO_FILE):
os.remove(EMPTY_AUDIO_FILE)
audio = vars.getVars("Audio")
audio.server.stop()
try:
self.audio.unregisterMeter()
except:
pass
# FL - START 22/05/17
try:
self.Destroy()
except:
pass
raise SystemExit
def getWholeSeason(year):
vars = Variables.Variables()
teams = vars.teams
months = ['october', 'november', 'december', 'january', 'febuary', 'march', 'april' ]
# months = ['february', 'march', 'april' ]
for month in months:
NBAurl = "http://www.basketball-reference.com/leagues/NBA_" + str(year) + "_games-" + month + ".html"
try:
tempWebFile = request.urlopen(NBAurl).read()
except:
return None
tempData = BeautifulSoup(tempWebFile,"lxml")
lines = tempData.find_all('tr')
parseWholeSeason(lines)
def loadVars(self):
'''
Fills dictionary with variables to have their U Q'd
Input: none
Output: none
'''
print '\nLoading uncertain variables...'
uVars = self.input_file('Variables/names','').split(' ')
self.varDict={}
for var in uVars:
path=self.input_file('Variables/'+var+'/path',' ')
dist=self.input_file('Variables/'+var+'/dist',' ')
args=self.input_file('Variables/'+var+'/args',' ').split(' ')
for a,arg in enumerate(args):
args[a]=float(arg)
self.varDict[var]=Variables.newVar(dist,var,path)
self.varDict[var].setDist(args)
def loadVars(self):
'''
Fills dictionary with variables to have their U Q'd
Input: none
Output: none
'''
print '\nLoading uncertain variables...'
uVars = self.input_file('Variables/names','').split(' ')
self.varDict={}
for var in uVars:
path=self.input_file('Variables/'+var+'/path',' ')
dist=self.input_file('Variables/'+var+'/dist',' ')
args=self.input_file('Variables/'+var+'/args',' ').split(' ')
for a,arg in enumerate(args):
args[a]=float(arg)
self.varDict[var]=Variables.newVar(dist,var,path)
self.varDict[var].setDist(args)
def loadVars(self):
print '\nLoading uncertain variables...'
uVars = self.input_file('Variables/names', '').split(' ')
self.varDict = {}
for var in uVars:
path = self.input_file('Variables/' + var + '/path', ' ')
dist = self.input_file('Variables/' + var + '/dist', ' ')
args = self.input_file('Variables/' + var + '/args',
' ').split(' ')
#print 'current:',var
for a, arg in enumerate(args):
#print " ",a,arg
args[a] = float(arg)
impwt = self.input_file('Variables/' + var + '/weight', 1.0)
self.varDict[var] = Variables.VariableFactory(
dist, var, path, impwt)
self.varDict[var].setDist(args)
def loadVars(self):
print '\nLoading uncertain variables...'
uVars = self.input_file('Variables/names', '').split(' ')
self.varDict = {}
doAnis = self.input_file('Sampler/SC/anis', 0)
for var in uVars:
path = self.input_file('Variables/' + var + '/path', ' ')
dist = self.input_file('Variables/' + var + '/dist', ' ')
args = self.input_file('Variables/' + var + '/args',
' ').split(' ')
for a, arg in enumerate(args):
args[a] = float(arg)
if doAnis:
impwt = self.input_file('Variables/' + var + '/weight', 1.0)
else:
impwt = 1
self.varDict[var] = Variables.VariableFactory(
dist, var, path, impwt)
self.varDict[var].setDist(args)
def testOrthogonal(vartype,polyords=[2,4],quadord=3,target=0,verbose=False):
import Variables as v
var = v.newVar(vartype,'x')
var.setDist([0,1.0])
var.setQuadrature(order=quadord)
tot = 0
for l,val in enumerate(var.pts):
tot+=var.evalNormPoly(val,polyords[0])*\
var.evalNormPoly(val,polyords[1])*\
var.wts[l]
if abs(tot-target)<1.0e-9:
if verbose:
print 'Passed orders',polyords,'with quad order',quadord
return True
else:
if verbose:
print 'ERROR! Failed orders',polyords,'with quad order',quadord
print ' Got',tot,'instead of',target
return False
def getAllFFA(year):
var = Variables.Variables()
teams = var.teams
offensiveRating = []
for (i,j) in teams.items():
"""Do an insert sort type of thing"""
ffaTemp = FFAteam(i,2017)
if(len(offensiveRating) == 0):
offensiveRating.append([i,j,ffaTemp])
continue
for k in range(0,len(offensiveRating)):
if(ffaTemp > offensiveRating[k][2]):
offensiveRating.insert(k, [i, j, ffaTemp])
break
if(k == len(offensiveRating) - 1):
offensiveRating.insert(k + 1, [i, j, ffaTemp])
break
return offensiveRating
def testOrthogonal(vartype,
polyords=[2, 4],
quadord=3,
target=0,
verbose=False):
import Variables as v
var = v.newVar(vartype, 'x')
var.setDist([0, 1.0])
var.setQuadrature(order=quadord)
tot = 0
for l, val in enumerate(var.pts):
tot+=var.evalNormPoly(val,polyords[0])*\
var.evalNormPoly(val,polyords[1])*\
var.wts[l]
if abs(tot - target) < 1.0e-9:
if verbose:
print 'Passed orders', polyords, 'with quad order', quadord
return True
else:
if verbose:
print 'ERROR! Failed orders', polyords, 'with quad order', quadord
print ' Got', tot, 'instead of', target
return False
def testOrthogonal(vartype,
polyords=[2, 4],
quadord=3,
target=0,
verbose=False):
import Variables as v
var = v.newVar(vartype, 'x')
var.setDist([0, 1.0])
#print 'Check variable!'
#print ' mean:',var.dist.mean()
#print ' std:',var.dist.std()
var.setQuadrature(order=quadord)
tot = 0
for l, val in enumerate(var.pts):
#tot+=var.evalNormPoly(val,polyords[0])*\
# var.evalNormPoly(val,polyords[1])*\
# np.exp(-val*val)*\
tot+=orthoNorms(var,val,polyords)*\
var.wts[l]*\
var.probdens(val)
if abs(tot - target) < 1.0e-9:
#print 'Passed orders',polyords,'with quad order',quadord
return True
else:
if verbose:
print 'checking', polyords
print 'ERROR! Failed orders', polyords, 'with quad order', quadord
print ' Got', tot, 'instead of', target
print ' val :', val
print ' poly1:', var.evalNormPoly(val, polyords[0])
print ' poly2:', var.evalNormPoly(val, polyords[1])
print ' wts :', var.wts[l]
print ' pdens:', var.probdens(val)
print ' norms', 1. / (var.norm(polyords[0])) * 1. / (var.norm(
polyords[1]))
return False
def MAP_learn(self,make_correction_model=False):
actCounts = {'bn':{'correct':0,'incorrect':0},
'dp':{'correct':0,'incorrect':0},
'ap':{'correct':0,'incorrect':0},
'tt':{'correct':0,'incorrect':0},
'yes':{'correct':0,'incorrect':0},
'no':{'correct':0,'incorrect':0},
'non-understanding':0}
Variables.clear_default_domain()
Variables.set_default_domain({'H_bn_t':lv.H_bn,'H_dp_t':lv.H_dp,'H_ap_t':lv.H_ap,\
'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn,\
'H_dp_tt':lv.H_dp,'H_ap_tt':lv.H_ap,'H_tt_tt':lv.H_tt,\
'H_bn_0':lv.H_bn,'H_dp_0':lv.H_dp,'H_ap_0':lv.H_ap,\
'H_tt_0':lv.H_tt})
fHt_UAtt_Htt = ls.load_model('_factor_Ht_UAtt_Htt.model')
for d, dialog in enumerate(lc.Corpus(self.data,prep=self.prep).dialogs()):
if len(dialog.turns) > 40:
continue
# c = ((len(dialog.turns)-1)/5)-1
# if c < 0: c = 0
avg_cs = reduce(operator.add,map(lambda x:x['CS'],dialog.turns))/len(dialog.turns)
if avg_cs > 0.7: c = 0
elif avg_cs > 0.5: c = 1
elif avg_cs > 0.3: c = 2
else: c = 3
self.q_class[c] += 1
cm_ua_template = self.cm_ua_template[c]
co_cs = self.co_cs[c]
inco_cs = self.inco_cs[c]
# MAP decoding
# print 'processing dialog #%d(%s)...'%(d,dialog.id)
Variables.change_variable('H_bn_0',lv.H_bn)
Variables.change_variable('H_dp_0',lv.H_dp)
Variables.change_variable('H_ap_0',lv.H_ap)
Variables.change_variable('H_tt_0',lv.H_tt)
dialog_factors = []
for t, turn in enumerate(dialog.abs_turns):
tmp_fHt_UAtt_Htt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,\
'UA_%s'%(t+1),'H_bn_%s'%(t+1),'H_dp_%s'%(t+1),\
'H_ap_%s'%(t+1),'H_tt_%s'%(t+1)),
new_domain_variables={'UA_%s'%(t+1):lv.UA,'H_bn_%s'%(t+1):lv.H_bn,\
'H_dp_%s'%(t+1):lv.H_dp,'H_ap_%s'%(t+1):lv.H_ap,\
'H_tt_%s'%(t+1):lv.H_tt})
tmp_fHt_UAtt_Htt[:] = fHt_UAtt_Htt[:]
# tmp_fHt_UAtt_Htt = fHt_UAtt_Htt.copy_rename({'H_bn_t':'H_bn_%s'%i,'H_dp_t':'H_dp_%s'%i,'H_ap_t':'H_ap_%s'%i,'H_tt_t':'H_tt_%s'%i,'UA_tt':'UA_%s'%(i+1),'H_bn_tt':'H_bn_%s'%(i+1),'H_dp_tt':'H_dp_%s'%(i+1),'H_ap_tt':'H_ap_%s'%(i+1),'H_tt_tt':'H_tt_%s'%(i+1)})
tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,'UA_%s'%(t+1)))
# tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%i,'H_dp_%s'%i,'H_ap_%s'%i,'H_tt_%s'%i,'UA_%s'%(i+1)),new_domain_variables={'UA_%s'%(i+1):UA,'H_bn_%s'%i:H_bn,'H_dp_%s'%i:H_dp,'H_ap_%s'%i:H_ap,'H_tt_%s'%i:H_tt})
try:
tmp_fGbn_Ht_SAtt_UAtt[:] = \
ls.load_model(('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-'))[:]
except:
print ('Error:cannot find _factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')
exit()
tmp_fUAtt_Ott = Factor(('UA_%s'%(t+1),))
tmp_fUAtt_Ott[:] = lo.getObsFactor(turn,use_cs=True)[:]
factor = tmp_fHt_UAtt_Htt * tmp_fGbn_Ht_SAtt_UAtt * tmp_fUAtt_Ott
dialog_factors.append(factor.copy(copy_domain=True))
jfr = JFR(SFR(dialog_factors))
jfr.condition({'H_bn_0':'x','H_dp_0':'x','H_ap_0':'x','H_tt_0':'x'})
jfr.map_calibrate()
# Populate error table using inferred and observed actions
for t, turn in enumerate(dialog.turns):
rf = jfr.factors_containing_variable('UA_%s'%(t+1))
max_ua = max(zip(rf[0].insts(),rf[0][:]),key=operator.itemgetter(1))[0][-1]
if max_ua == 'yes' and 'no' in turn['UA'] or\
max_ua == 'no' and 'yes' in turn['UA']:
print 'turn %d(%s): '%(t,turn) + max_ua + ' vs.' + ','.join(turn['UA'])
obs_ua_template = []
for act in turn['UA']:
if act.find('I:bn') == 0:# and max_ua.find('I:bn') > -1 and not dialog.goal['G_bn'] == '':
if dialog.goal['G_bn'] == act.split(':')[-1]:
obs_ua_template.append('I:bn:o')
actCounts['bn']['correct'] += 1
else:
obs_ua_template.append('I:bn:x')
actCounts['bn']['incorrect'] += 1
if dialog.goal['G_bn'] not in self.cm_bn:
self.cm_bn[dialog.goal['G_bn']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_bn[dialog.goal['G_bn']]:
self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] = 1
else:
self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] += 1
# try:
# self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] += 1
# except:
# try: self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] = 1
# except: self.cm_bn[dialog.goal['G_bn']] = {act.split(':')[-1]:1}
elif act.find('I:dp') == 0:# and max_ua.find('I:dp') > -1 and not dialog.goal['G_dp'] == '':
if dialog.goal['G_dp'] == act.split(':')[-1]:
obs_ua_template.append('I:dp:o')
actCounts['dp']['correct'] += 1
else:
obs_ua_template.append('I:dp:x')
actCounts['dp']['incorrect'] += 1
if dialog.goal['G_dp'] not in self.cm_p:
self.cm_p[dialog.goal['G_dp']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_p[dialog.goal['G_dp']]:
self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] = 1
else:
self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] += 1
# try:
# self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] += 1
# except:
# try: self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] = 1
# except: self.cm_p[dialog.goal['G_dp']] = {act.split(':')[-1]:1}
elif act.find('I:ap') == 0:# and max_ua.find('I:ap') > -1 and not dialog.goal['G_ap'] == '':
if dialog.goal['G_ap'] == act.split(':')[-1]:
obs_ua_template.append('I:ap:o')
actCounts['ap']['correct'] += 1
else:
obs_ua_template.append('I:ap:x')
actCounts['ap']['incorrect'] += 1
if dialog.goal['G_ap'] not in self.cm_p:
self.cm_p[dialog.goal['G_ap']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_p[dialog.goal['G_ap']]:
self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] = 1
else:
self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] += 1
# try:
# self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] += 1
# except:
# try: self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] = 1
# except: self.cm_p[dialog.goal['G_ap']] = {act.split(':')[-1]:1}
elif act.find('I:tt') == 0:# and max_ua.find('I:tt') > -1 and not dialog.goal['G_tt'] == '':
if dialog.goal['G_tt'] == act.split(':')[-1]:
obs_ua_template.append('I:tt:o')
actCounts['tt']['correct'] += 1
else:
obs_ua_template.append('I:tt:x')
actCounts['tt']['incorrect'] += 1
if dialog.goal['G_tt'] not in self.cm_tt:
self.cm_tt[dialog.goal['G_tt']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_tt[dialog.goal['G_tt']]:
self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] = 1
else:
self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] += 1
# try:
# self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] += 1
# except:
# try: self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] = 1
# except: self.cm_tt[dialog.goal['G_tt']] = {act.split(':')[-1]:1}
# elif act.find('I:') == 0:
# obs_ua_template.append(':'.join(act.split(':')[:-1]))
else:
obs_ua_template.append(act)
# if ','.join(sorted(obs_ua_template)).find('yes,') > -1 or\
# ','.join(sorted(obs_ua_template)).find(',yes') > -1 or\
# ','.join(sorted(obs_ua_template)).find('no,') > -1 or\
# ','.join(sorted(obs_ua_template)).find(',no') > -1:
# print 'Check'
# print dialog.id
# print t
# print ','.join(sorted(obs_ua_template))
if max_ua not in cm_ua_template:
cm_ua_template[max_ua] = {','.join(sorted(obs_ua_template)):1}
elif ','.join(sorted(obs_ua_template)) not in cm_ua_template[max_ua]:
cm_ua_template[max_ua][','.join(sorted(obs_ua_template))] = 1
else:
cm_ua_template[max_ua][','.join(sorted(obs_ua_template))] += 1
# try:
# cm_ua_template[max_ua][','.join(sorted(obs_ua_template))] += 1
# except:
# try: cm_ua_template[max_ua][','.join(sorted(obs_ua_template))] = 1
# except: cm_ua_template[max_ua] = {','.join(sorted(obs_ua_template)):1}
if len(obs_ua_template) == 1:
# try:
if len(obs_ua_template[0].split(':')) == 3:
dummy,field,val = obs_ua_template[0].split(':')
if val == 'o':
co_cs[field].append(turn['CS'])
else:
inco_cs[field].append(turn['CS'])
# except:
else:
if obs_ua_template[0] == 'yes':
if config.getboolean('UserSimulation','extendedSystemActionSet'):
if dialog.abs_turns[t]['SA'][0] in ['C:bn:o','C:dp:o','C:ap:o','C:tt:o']:
co_cs['yes'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] in ['C:bn:x','C:dp:x','C:ap:x','C:tt:x']:
inco_cs['yes'].append(turn['CS'])
else:
if dialog.abs_turns[t]['SA'][0] == 'C:o':
co_cs['yes'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] == 'C:x':
inco_cs['yes'].append(turn['CS'])
elif obs_ua_template[0] == 'no':
if config.getboolean('UserSimulation','extendedSystemActionSet'):
if dialog.abs_turns[t]['SA'][0] in ['C:bn:x','C:dp:x','C:ap:x','C:tt:x']:
co_cs['no'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] in ['C:bn:o','C:dp:o','C:ap:o','C:tt:o']:
inco_cs['no'].append(turn['CS'])
else:
if dialog.abs_turns[t]['SA'][0] == 'C:x':
co_cs['no'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] == 'C:o':
inco_cs['no'].append(turn['CS'])
else:
try:
if make_correction_model and len(obs_ua_template) == 2 and 'no' in obs_ua_template:
if ','.join(obs_ua_template).find(':x') > -1:
inco_cs['correction'].append(turn['CS'])
else:
co_cs['correction'%len(obs_ua_template)].append(turn['CS'])
else:
if ','.join(obs_ua_template).find(':x') > -1:
inco_cs['multi%d'%len(obs_ua_template)].append(turn['CS'])
else:
co_cs['multi%d'%len(obs_ua_template)].append(turn['CS'])
except:
print len(obs_ua_template)
for c in range(self.q_class_max):
cm_ua_template = self.cm_ua_template[c]
co_cs = self.co_cs[c]
inco_cs = self.inco_cs[c]
co_cs['single'] = co_cs['bn'] + co_cs['dp'] + co_cs['ap'] +\
co_cs['tt'] + co_cs['yes'] + co_cs['no']
inco_cs['single'] = inco_cs['bn'] + inco_cs['dp'] + inco_cs['ap'] +\
inco_cs['tt'] + inco_cs['yes'] + inco_cs['no']
for n in range(2,6,1):
co_cs['multi'] += co_cs['multi%d'%n]
inco_cs['multi'] += inco_cs['multi%d'%n]
co_cs['total'] = co_cs['single'] + co_cs['multi']
inco_cs['total'] = inco_cs['single'] + inco_cs['multi']
print 'Writing parameters...'
def make_dist(ft):
tot = sum(ft.values())
for k, v in ft.items(): ft[k] = float(v)/tot
return ft
def make_dists(cm):
for key in cm.keys():
cm[key] = make_dist(cm[key])
return cm
def generate_cs_pd(cs):
cs_pd = {}
for key in cs.keys():
cs_pd[key] = {}
for val in cs[key]:
try:
cs_pd[key][int(val/0.01)/float(100)] += 1
except:
cs_pd[key][int(val/0.01)/float(100)] = 1
return make_dists(cs_pd)
ls.store_model(make_dists(self.cm_bn),'_confusion_matrix_bn.model')
ls.store_model(make_dists(self.cm_p),'_confusion_matrix_p.model')
ls.store_model(make_dists(self.cm_tt),'_confusion_matrix_tt.model')
ls.store_model(make_dist(self.q_class),'_quality_class.model')
for c in range(self.q_class_max):
ls.store_model(make_dists(self.cm_ua_template[c]),'_confusion_matrix_ua_class_%d.model'%c)
ls.store_model(self.co_cs[c],'_correct_confidence_score_class_%d.model'%c)
ls.store_model(self.inco_cs[c],'_incorrect_confidence_score_class_%d.model'%c)
ls.store_model(generate_cs_pd(self.co_cs[c]),'_correct_confidence_score_prob_dist_class_%d.model'%c)
ls.store_model(generate_cs_pd(self.inco_cs[c]),'_incorrect_confidence_score_prob_dist_class_%d.model'%c)
pprint.pprint(actCounts)
def writeVarToDisk():
vars.writeCeciliaPrefsToFile()
pady=10,
command=ocr.lift)
# Packing the buttons and making them fill the bar on the X-Axis
ocrButton.pack(fill="x")
tldrButton.pack(fill="x")
settingsButton.pack(fill="x")
# Displays the first page (Home_Page)
home.show()
# ====== Python Boiler Plate ====== #
if __name__ == "__main__":
# File checking and save loading
try:
v.load()
except:
pass
checkFiles()
# Interface Boiler-Plate
root = tk.Tk()
root.title("Combined OCR & TL;DR Software")
root.configure(bg="#DADFE1")
main = MainWindow(root)
main.pack(side="top", fill="both", expand=True)
root.wm_geometry("1000x700")
root.mainloop()
def getHistoricalPrices(tickerName):
fileVariables = Variables()
directory = fileVariables.directory
fileEnding = fileVariables.returnFileEnding(tickerName)
try:
csv_file = open(directory + tickerName + '-Y.csv', "r")
reader = csv.reader(csv_file, delimiter=' ')
yahoo_data_array = []
except:
try:
csv_file = open(directory + tickerName + '.csv', "r")
reader = csv.reader(csv_file, delimiter=' ')
yahoo_data_array = []
except:
print('Error : File Not Opening')
switched = False
for lines in reader:
if ('Date' in lines or 'Date' in lines[0].split(',')):
split = lines[0].split(',')
if (split[5] == 'Volume'):
switched = True
pass
else:
yahoo_data_array.insert(0, lines[0].split(','))
# print(switched)
"""If volume and adj close is switched, switch it around [5] and [6]"""
if (switched == True):
index = 0
for i in yahoo_data_array:
temp = []
if (i[5] == 'null'):
del yahoo_data_array[index]
continue
for j in range(0, 5):
temp.append(i[j])
temp.append(i[6])
temp.append(i[5])
del yahoo_data_array[index]
yahoo_data_array.insert(index, temp)
index += 1
for i in yahoo_data_array:
dates = i[0].split('-')
i[0] = dates[0] + '/' + dates[1] + '/' + dates[2]
firstDate = float(yahoo_data_array[0][0].split('/')[0])
if (firstDate < 2016):
yahoo_data_array.reverse()
i = 0
while (i < len(yahoo_data_array)):
if ('null' in yahoo_data_array[i]):
del yahoo_data_array[i]
i -= 1
i += 1
yahoo_data_array = addHistoricalSplit(yahoo_data_array)
return yahoo_data_array
DATABASE_NAME = 'ConcertoDb_TIF_WA6358_59_b9500bbf-f52a-474a-92c5-b863ed31d004' #TIF Database
VEHICLE_NUMBER = '2'
DEFINITIONNUMBER_EVENT = '41' # consult SQL-query "get_DefinitionNumber_and_respective_DinGroup" to find the correct DefinitionNumber
DEFINITIONNUMBER_ASV = '6'
NUMBER_ASV_POSITIONS = 7 # only the first NUMBER_ASV_POSITIONS positions of ASV string are relevant
START_EVENTS_FORMATTED = datetime.strptime(
'2017-01-17',
"%Y-%m-%d") # point of time of very first event AND event ASV
TIMEFRAME_EVENT_ASV = 3 * 24 # hours
TIME_AFTER_LAST_EVENT = 10 * 24 # hours (no_event values start at that point of time)
TIMEFRAME_NO_EVENT_ASV = 6 * 24 # hours
FRACTION_TEST = 0.3 # fraction of examples that will be train data
SQL_PART_ROUTINE = Variables.get_sql_join(
DATABASE_NAME, VEHICLE_NUMBER
) # SQL query that executes relevant joins, not containing SELECT statement
#####################################
print(
'-----------------------\nSVM on Concerto Data\napproach: TRANSMISSION\n-----------------------'
)
bool_reload = False
if SL.check_dir(
): # folder "__cached_data__" exists - use it or set bool to reload from SQL database
bool_reload = VS.yes_no(
'Use previously stored data for SVC approach? [yes/no]')
if bool_reload: # using stored data
def onSelectButton(self, data):
surface = vars.getVars("Surface")
if data % 2 == 1: # JR 07/09/2017
surface.modeChange()
def getParameterNames( self ):
return Variables.getNames( self.getVariables() )
'R:bn',\
'R:dp',\
'R:ap',\
'R:tt',\
'C:o',\
'C:x',\
'C:-'\
'I:bus'\
)
H_bn = ('x','o')
H_dp = ('x','o')
H_ap = ('x','o')
H_tt = ('x','o')
Variables.clear_default_domain()
'''
Let's Go Dynamic Graphical Model
Initial State
Transition Network
Evidences
'''
fH0 = Factor(('H_bn_0','H_dp_0','H_ap_0','H_tt_0'),
data=[0]*16,\
new_domain_variables={'H_bn_0':H_bn,'H_dp_0':H_dp,'H_ap_0':H_ap,'H_tt_0':H_tt})
fH0[{'H_bn_0':'x','H_dp_0':'x','H_ap_0':'x','H_tt_0':'x'}] = 1
def extract_usr_model():
import Variables
from Parameters import Factor
import LetsgoCorpus as lc
import LetsgoSerializer as ls
import LetsgoVariables as lv
Variables.clear_default_domain()
Variables.set_default_domain({'H_bn_t':lv.H_bn,'H_dp_t':lv.H_dp,'H_ap_t':lv.H_ap,\
'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn,\
'H_dp_tt':lv.H_dp,'H_ap_tt':lv.H_ap,'H_tt_tt':lv.H_tt})
# estimate the ratio of dialogs w/ bn and dialogs w/o bn in the goal
#
try:
fGbnO_Ht_SAttCO_UAtt = ls.load_model('_factor_o_C-o.model').marginalise_onto(['UA_tt']).normalised()
fGbnX_Ht_SAttCO_UAtt = ls.load_model('_factor_x_C-o.model').marginalise_onto(['UA_tt']).normalised()
fGbn_Ht_SAttCO_UAtt = (fGbnO_Ht_SAttCO_UAtt + fGbnX_Ht_SAttCO_UAtt).normalised()
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttCX_UAtt = ls.load_model('_factor_o_C-x.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAtt_UAttX
fGbnX_Ht_SAttCX_UAtt = ls.load_model('_factor_x_C-x.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAtt_UAttX
fGbn_Ht_SAttCX_UAtt = (fGbnO_Ht_SAttCX_UAtt + fGbnX_Ht_SAttCX_UAtt).normalised()
# print fGbn_Ht_SAtt_UAttX
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttBN_UAtt = ls.load_model('_factor_o_R-bn.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAttBN_UAtt
fGbnX_Ht_SAttBN_UAtt = ls.load_model('_factor_x_R-bn.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAttBN_UAtt
fGbn_Ht_SAttBN_UAtt = (fGbnO_Ht_SAttBN_UAtt + fGbnX_Ht_SAttBN_UAtt).normalised()
# print fGbn_Ht_SAttBN_UAtt
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttDP_UAtt = ls.load_model('_factor_o_R-dp.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAttDP_UAtt
fGbnX_Ht_SAttDP_UAtt = ls.load_model('_factor_x_R-dp.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAttDP_UAtt
fGbn_Ht_SAttDP_UAtt = (fGbnO_Ht_SAttDP_UAtt + fGbnX_Ht_SAttDP_UAtt).normalised()
# print fGbn_Ht_SAttDP_UAtt
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttAP_UAtt = ls.load_model('_factor_o_R-ap.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAttAP_UAtt
fGbnX_Ht_SAttAP_UAtt = ls.load_model('_factor_x_R-ap.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAttAP_UAtt
fGbn_Ht_SAttAP_UAtt = (fGbnO_Ht_SAttAP_UAtt + fGbnX_Ht_SAttAP_UAtt).normalised()
# print fGbn_Ht_SAttAP_UAtt
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttTT_UAtt = ls.load_model('_factor_o_R-tt.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAttTT_UAtt
fGbnX_Ht_SAttTT_UAtt = ls.load_model('_factor_x_R-tt.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAttTT_UAtt
fGbn_Ht_SAttTT_UAtt = (fGbnO_Ht_SAttTT_UAtt + fGbnX_Ht_SAttTT_UAtt).normalised()
# print fGbn_Ht_SAttTT_UAtt
except:
print ('Error:cannot find model')
exit()
try:
fGbnO_Ht_SAttOP_UAtt = ls.load_model('_factor_o_R-open.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnO_Ht_SAttOP_UAtt
fGbnX_Ht_SAttOP_UAtt = ls.load_model('_factor_x_R-open.model').marginalise_onto(['UA_tt']).normalised()
# print fGbnX_Ht_SAttOP_UAtt
fGbn_Ht_SAttOP_UAtt = (fGbnO_Ht_SAttOP_UAtt + fGbnX_Ht_SAttOP_UAtt).normalised()
# print fGbn_Ht_SAttOP_UAtt
except:
print ('Error:cannot find model')
exit()
um = {}
um['C-o'] = fGbn_Ht_SAttCO_UAtt.insts_data_dict()
um['C-x'] = fGbn_Ht_SAttCX_UAtt.insts_data_dict()
um['R-bn'] = fGbn_Ht_SAttBN_UAtt.insts_data_dict()
um['R-dp'] = fGbn_Ht_SAttDP_UAtt.insts_data_dict()
um['R-ap'] = fGbn_Ht_SAttAP_UAtt.insts_data_dict()
um['R-tt'] = fGbn_Ht_SAttTT_UAtt.insts_data_dict()
um['R-open'] = fGbn_Ht_SAttOP_UAtt.insts_data_dict()
print um
print 'Writing parameters...'
ls.store_model(um,'_user_action.model')
print 'Done'
def Sampling_learn(self,make_correction_model=False):
start_time = time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime())
actCounts = {'bn':{'correct':0,'incorrect':0},
'dp':{'correct':0,'incorrect':0},
'ap':{'correct':0,'incorrect':0},
'tt':{'correct':0,'incorrect':0},
'yes':{'correct':0,'incorrect':0},
'no':{'correct':0,'incorrect':0},
'non-understanding':0}
Variables.clear_default_domain()
Variables.set_default_domain({'H_bn_t':lv.H_bn,'H_dp_t':lv.H_dp,'H_ap_t':lv.H_ap,\
'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn,\
'H_dp_tt':lv.H_dp,'H_ap_tt':lv.H_ap,'H_tt_tt':lv.H_tt,\
'H_bn_0':lv.H_bn,'H_dp_0':lv.H_dp,'H_ap_0':lv.H_ap,\
'H_tt_0':lv.H_tt})
fHt_UAtt_Htt = ls.load_model('_factor_Ht_UAtt_Htt.model')
for d, dialog in enumerate(lc.Corpus(self.data,prep=self.prep).dialogs()):
if len(dialog.turns) > 40:
continue
print 'processing dialog #%d...'%d
avg_cs = reduce(operator.add,map(lambda x:x['CS'],dialog.turns))/len(dialog.turns)
if avg_cs > 0.7: c = 0
elif avg_cs > 0.5: c = 1
elif avg_cs > 0.3: c = 2
else: c = 3
self.q_class[c] += 1
cm_ua_template = self.cm_ua_template[c]
co_cs = self.co_cs[c]
inco_cs = self.inco_cs[c]
Variables.change_variable('H_bn_0',lv.H_bn)
Variables.change_variable('H_dp_0',lv.H_dp)
Variables.change_variable('H_ap_0',lv.H_ap)
Variables.change_variable('H_tt_0',lv.H_tt)
dialog_factors = []
for t, turn in enumerate(dialog.abs_turns):
tmp_fHt_UAtt_Htt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,\
'UA_%s'%(t+1),'H_bn_%s'%(t+1),'H_dp_%s'%(t+1),\
'H_ap_%s'%(t+1),'H_tt_%s'%(t+1)),
new_domain_variables={'UA_%s'%(t+1):lv.UA,'H_bn_%s'%(t+1):lv.H_bn,\
'H_dp_%s'%(t+1):lv.H_dp,'H_ap_%s'%(t+1):lv.H_ap,\
'H_tt_%s'%(t+1):lv.H_tt})
tmp_fHt_UAtt_Htt[:] = fHt_UAtt_Htt[:]
# tmp_fHt_UAtt_Htt = fHt_UAtt_Htt.copy_rename({'H_bn_t':'H_bn_%s'%i,'H_dp_t':'H_dp_%s'%i,'H_ap_t':'H_ap_%s'%i,'H_tt_t':'H_tt_%s'%i,'UA_tt':'UA_%s'%(i+1),'H_bn_tt':'H_bn_%s'%(i+1),'H_dp_tt':'H_dp_%s'%(i+1),'H_ap_tt':'H_ap_%s'%(i+1),'H_tt_tt':'H_tt_%s'%(i+1)})
tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,'UA_%s'%(t+1)))
# tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%i,'H_dp_%s'%i,'H_ap_%s'%i,'H_tt_%s'%i,'UA_%s'%(i+1)),new_domain_variables={'UA_%s'%(i+1):UA,'H_bn_%s'%i:H_bn,'H_dp_%s'%i:H_dp,'H_ap_%s'%i:H_ap,'H_tt_%s'%i:H_tt})
try:
tmp_fGbn_Ht_SAtt_UAtt[:] = \
ls.load_model(('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-'))[:]
except:
print ('Error:cannot find _factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')
exit()
tmp_fUAtt_Ott = Factor(('UA_%s'%(t+1),))
tmp_fUAtt_Ott[:] = lo.getObsFactor(turn,use_cs=True)[:]
factor = tmp_fHt_UAtt_Htt * tmp_fGbn_Ht_SAtt_UAtt * tmp_fUAtt_Ott
dialog_factors.append(factor.copy(copy_domain=True))
jfr = JFR(SFR(dialog_factors))
jfr.condition({'H_bn_0':'x','H_dp_0':'x','H_ap_0':'x','H_tt_0':'x'})
jfr.calibrate()
# Populate error table using inferred and observed actions
for t, turn in enumerate(dialog.turns):
obs_ua_template = []
for act in turn['UA']:
if act.find('I:bn') == 0:# and max_ua.find('I:bn') > -1 and not dialog.goal['G_bn'] == '':
if dialog.goal['G_bn'] == act.split(':')[-1]:
obs_ua_template.append('I:bn:o')
actCounts['bn']['correct'] += 1
else:
obs_ua_template.append('I:bn:x')
actCounts['bn']['incorrect'] += 1
if dialog.goal['G_bn'] not in self.cm_bn:
self.cm_bn[dialog.goal['G_bn']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_bn[dialog.goal['G_bn']]:
self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] = 1
else:
self.cm_bn[dialog.goal['G_bn']][act.split(':')[-1]] += 1
elif act.find('I:dp') == 0:# and max_ua.find('I:dp') > -1 and not dialog.goal['G_dp'] == '':
if dialog.goal['G_dp'] == act.split(':')[-1]:
obs_ua_template.append('I:dp:o')
actCounts['dp']['correct'] += 1
else:
obs_ua_template.append('I:dp:x')
actCounts['dp']['incorrect'] += 1
if dialog.goal['G_dp'] not in self.cm_p:
self.cm_p[dialog.goal['G_dp']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_p[dialog.goal['G_dp']]:
self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] = 1
else:
self.cm_p[dialog.goal['G_dp']][act.split(':')[-1]] += 1
elif act.find('I:ap') == 0:# and max_ua.find('I:ap') > -1 and not dialog.goal['G_ap'] == '':
if dialog.goal['G_ap'] == act.split(':')[-1]:
obs_ua_template.append('I:ap:o')
actCounts['ap']['correct'] += 1
else:
obs_ua_template.append('I:ap:x')
actCounts['ap']['incorrect'] += 1
if dialog.goal['G_ap'] not in self.cm_p:
self.cm_p[dialog.goal['G_ap']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_p[dialog.goal['G_ap']]:
self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] = 1
else:
self.cm_p[dialog.goal['G_ap']][act.split(':')[-1]] += 1
elif act.find('I:tt') == 0:# and max_ua.find('I:tt') > -1 and not dialog.goal['G_tt'] == '':
if dialog.goal['G_tt'] == act.split(':')[-1]:
obs_ua_template.append('I:tt:o')
actCounts['tt']['correct'] += 1
else:
obs_ua_template.append('I:tt:x')
actCounts['tt']['incorrect'] += 1
if dialog.goal['G_tt'] not in self.cm_tt:
self.cm_tt[dialog.goal['G_tt']] = {act.split(':')[-1]:1}
elif act.split(':')[-1] not in self.cm_tt[dialog.goal['G_tt']]:
self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] = 1
else:
self.cm_tt[dialog.goal['G_tt']][act.split(':')[-1]] += 1
else:
obs_ua_template.append(act)
if len(obs_ua_template) == 1:
if len(obs_ua_template[0].split(':')) == 3:
dummy,field,val = obs_ua_template[0].split(':')
if val == 'o':
co_cs[field].append(turn['CS'])
else:
inco_cs[field].append(turn['CS'])
else:
if obs_ua_template[0] == 'yes':
if config.getboolean('UserSimulation','extendedSystemActionSet'):
if dialog.abs_turns[t]['SA'][0] in ['C:bn:o','C:dp:o','C:ap:o','C:tt:o']:
co_cs['yes'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] in ['C:bn:x','C:dp:x','C:ap:x','C:tt:x']:
inco_cs['yes'].append(turn['CS'])
else:
if dialog.abs_turns[t]['SA'][0] == 'C:o':
co_cs['yes'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] == 'C:x':
inco_cs['yes'].append(turn['CS'])
elif obs_ua_template[0] == 'no':
if config.getboolean('UserSimulation','extendedSystemActionSet'):
if dialog.abs_turns[t]['SA'][0] in ['C:bn:x','C:dp:x','C:ap:x','C:tt:x']:
co_cs['no'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] in ['C:bn:o','C:dp:o','C:ap:o','C:tt:o']:
inco_cs['no'].append(turn['CS'])
else:
if dialog.abs_turns[t]['SA'][0] == 'C:x':
co_cs['no'].append(turn['CS'])
elif dialog.abs_turns[t]['SA'][0] == 'C:o':
inco_cs['no'].append(turn['CS'])
else:
try:
if make_correction_model and len(obs_ua_template) == 2 and 'no' in obs_ua_template:
if ','.join(obs_ua_template).find(':x') > -1:
inco_cs['correction'].append(turn['CS'])
else:
co_cs['correction'%len(obs_ua_template)].append(turn['CS'])
else:
if ','.join(obs_ua_template).find(':x') > -1:
inco_cs['multi%d'%len(obs_ua_template)].append(turn['CS'])
else:
co_cs['multi%d'%len(obs_ua_template)].append(turn['CS'])
except:
print len(obs_ua_template)
rf = jfr.factors_containing_variable('UA_%s'%(t+1))
ua_factor = rf[0].copy().marginalise_onto(['UA_%s'%(t+1)]).normalised()#[{'UA_1':inst['UA_tt']}]
# print ua_factor
ua_pt = dict(zip(map(lambda x:x[0],ua_factor.insts()),ua_factor[:]))
# print ua_pt
for r in range(10):
sampled_ua = MultinomialSampler(ua_pt).sample()
# print sampled_ua
if sampled_ua not in cm_ua_template:
cm_ua_template[sampled_ua] = {','.join(sorted(obs_ua_template)):1}
elif ','.join(sorted(obs_ua_template)) not in cm_ua_template[sampled_ua]:
cm_ua_template[sampled_ua][','.join(sorted(obs_ua_template))] = 1
else:
cm_ua_template[sampled_ua][','.join(sorted(obs_ua_template))] += 1
for c in range(self.q_class_max):
cm_ua_template = self.cm_ua_template[c]
co_cs = self.co_cs[c]
inco_cs = self.inco_cs[c]
co_cs['single'] = co_cs['bn'] + co_cs['dp'] + co_cs['ap'] +\
co_cs['tt'] + co_cs['yes'] + co_cs['no']
inco_cs['single'] = inco_cs['bn'] + inco_cs['dp'] + inco_cs['ap'] +\
inco_cs['tt'] + inco_cs['yes'] + inco_cs['no']
for n in range(2,6,1):
co_cs['multi'] += co_cs['multi%d'%n]
inco_cs['multi'] += inco_cs['multi%d'%n]
co_cs['total'] = co_cs['single'] + co_cs['multi']
inco_cs['total'] = inco_cs['single'] + inco_cs['multi']
print 'Writing parameters...'
def make_dist(ft):
tot = sum(ft.values())
for k, v in ft.items(): ft[k] = float(v)/tot
return ft
def make_dists(cm):
for key in cm.keys():
cm[key] = make_dist(cm[key])
return cm
def generate_cs_pd(cs):
cs_pd = {}
for key in cs.keys():
cs_pd[key] = {}
for val in cs[key]:
try:
cs_pd[key][int(val/0.01)/float(100)] += 1
except:
cs_pd[key][int(val/0.01)/float(100)] = 1
return make_dists(cs_pd)
ls.store_model(make_dists(self.cm_bn),'_confusion_matrix_bn.model')
ls.store_model(make_dists(self.cm_p),'_confusion_matrix_p.model')
ls.store_model(make_dists(self.cm_tt),'_confusion_matrix_tt.model')
ls.store_model(make_dist(self.q_class),'_quality_class.model')
for c in range(self.q_class_max):
ls.store_model(make_dists(self.cm_ua_template[c]),'_confusion_matrix_ua_class_%d.model'%c)
ls.store_model(self.co_cs[c],'_correct_confidence_score_class_%d.model'%c)
ls.store_model(self.inco_cs[c],'_incorrect_confidence_score_class_%d.model'%c)
ls.store_model(generate_cs_pd(self.co_cs[c]),'_correct_confidence_score_prob_dist_class_%d.model'%c)
ls.store_model(generate_cs_pd(self.inco_cs[c]),'_incorrect_confidence_score_prob_dist_class_%d.model'%c)
pprint.pprint(actCounts)
end_time = time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime())
print 'Start time: %s'%start_time
print 'End time: %s'%end_time
os.chdir(uncDir)
#print 'in dir:',inputDir
os.chdir(inputDir)
inputDir = os.getcwd()
os.chdir(uncDir)
#load variables
uVars = input_file('Variables/names','').split(' ')
varDict={}
for var in uVars:
path=input_file('Variables/'+var+'/path',' ')
dist=input_file('Variables/'+var+'/dist',' ')
args=input_file('Variables/'+var+'/args',' ').split(' ')
for a,arg in enumerate(args):
args[a]=float(arg)
varDict[var]=Variables.newVar(dist,var,path)
varDict[var].setDist(args)
#build sampler
samplerType = input_file('Sampler/active','')
if samplerType in ['mc','MC','mC','MonteCarlo','Monte Carlo']:
sampler = spr.MonteCarlo(varDict,input_file)
elif samplerType in ['SC','sc','StochPoly']:
sampler = spr.StochasticPoly(varDict,input_file)
else:
raise IOError ('Sampler type not recognized: |'+samplerType+'|')
#for var in varDict.values():
# print var.name,var.pts,var.wts
#print sampler.runords
def EM_learn(self):
print 'Parameter learning start...'
start_time = time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime())
logliks = []
if not self.inc:
self._reset_param()
else:
Variables.clear_default_domain()
Variables.set_default_domain({'H_bn_t':lv.H_bn,'H_dp_t':lv.H_dp,'H_ap_t':lv.H_ap,\
'H_tt_t':lv.H_tt,'UA_tt':lv.UA,'H_bn_tt':lv.H_bn,\
'H_dp_tt':lv.H_dp,'H_ap_tt':lv.H_ap,'H_tt_tt':lv.H_tt,\
'H_bn_0':lv.H_bn,'H_dp_0':lv.H_dp,'H_ap_0':lv.H_ap,\
'H_tt_0':lv.H_tt})
fHt_UAtt_Htt = ls.load_model('_factor_Ht_UAtt_Htt.model')
prevloglik = -1000000000000000
loglik = 0.0
for i in range(self.iter):
print 'Iterate %d'%i
ess = {}
factor_template = {'G_bn':lv.G_bn,'SA':lv.SA}
for factor in Utils.inst_filling(factor_template):
ess[('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-')] = \
Factor(('H_bn_t','H_dp_t','H_ap_t','H_tt_t','UA_tt'))
ess[('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-')][:] = \
[sys.float_info.min] * len(ess[('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-')][:])
# ess[('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-')].zero()
for d, dialog in enumerate(lc.Corpus(self.data,prep=self.prep).dialogs()):
if len(dialog.turns) > 40:
continue
print 'processing dialog #%d...'%d
Variables.change_variable('H_bn_0',lv.H_bn)
Variables.change_variable('H_dp_0',lv.H_dp)
Variables.change_variable('H_ap_0',lv.H_ap)
Variables.change_variable('H_tt_0',lv.H_tt)
dialog_factors = []
for t, turn in enumerate(dialog.abs_turns):
tmp_fHt_UAtt_Htt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,\
'UA_%s'%(t+1),'H_bn_%s'%(t+1),'H_dp_%s'%(t+1),\
'H_ap_%s'%(t+1),'H_tt_%s'%(t+1)),
new_domain_variables={'UA_%s'%(t+1):lv.UA,'H_bn_%s'%(t+1):lv.H_bn,\
'H_dp_%s'%(t+1):lv.H_dp,'H_ap_%s'%(t+1):lv.H_ap,\
'H_tt_%s'%(t+1):lv.H_tt})
tmp_fHt_UAtt_Htt[:] = fHt_UAtt_Htt[:]
# tmp_fHt_UAtt_Htt = fHt_UAtt_Htt.copy_rename({'H_bn_t':'H_bn_%s'%i,'H_dp_t':'H_dp_%s'%i,'H_ap_t':'H_ap_%s'%i,'H_tt_t':'H_tt_%s'%i,'UA_tt':'UA_%s'%(i+1),'H_bn_tt':'H_bn_%s'%(i+1),'H_dp_tt':'H_dp_%s'%(i+1),'H_ap_tt':'H_ap_%s'%(i+1),'H_tt_tt':'H_tt_%s'%(i+1)})
tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,'H_tt_%s'%t,'UA_%s'%(t+1)))
# tmp_fGbn_Ht_SAtt_UAtt = Factor(('H_bn_%s'%i,'H_dp_%s'%i,'H_ap_%s'%i,'H_tt_%s'%i,'UA_%s'%(i+1)),new_domain_variables={'UA_%s'%(i+1):UA,'H_bn_%s'%i:H_bn,'H_dp_%s'%i:H_dp,'H_ap_%s'%i:H_ap,'H_tt_%s'%i:H_tt})
try:
tmp_fGbn_Ht_SAtt_UAtt[:] = \
ls.load_model(('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-'))[:]
except:
print ('Error:cannot find _factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')
exit()
tmp_fUAtt_Ott = Factor(('UA_%s'%(t+1),))
tmp_fUAtt_Ott[:] = lo.getObsFactor(turn,use_cs=True)[:]
factor = tmp_fHt_UAtt_Htt * tmp_fGbn_Ht_SAtt_UAtt * tmp_fUAtt_Ott
dialog_factors.append(factor.copy(copy_domain=True))
jfr = JFR(SFR(dialog_factors))
jfr.condition({'H_bn_0':'x','H_dp_0':'x','H_ap_0':'x','H_tt_0':'x'})
jfr.calibrate()
for t, turn in enumerate(dialog.abs_turns):
rf = jfr.factors_containing_variable('UA_%s'%(t+1))
from operator import add
if t == 0:
for inst in Utils.inst_filling({'H_bn_t':['x'],'H_dp_t':['x'],\
'H_ap_t':['x'],'H_tt_t':['x'],'UA_tt':lv.UA}):
ess[('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')][inst] += \
rf[0].copy().marginalise_onto(['UA_1']).normalised()[{'UA_1':inst['UA_tt']}]
loglik += math.log(rf[0].copy().z())
print 'dialog loglik: %e'%loglik
else:
ess[('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')][:] =\
map(add,ess[('_factor_%s_%s.model'%(dialog.abs_goal['G_bn'],turn['SA'][0])).replace(':','-')][:],\
rf[0].copy().marginalise_onto(['H_bn_%s'%t,'H_dp_%s'%t,'H_ap_%s'%t,\
'H_tt_%s'%t,'UA_%s'%(t+1)]).normalised()[:])
print 'Writing parameters...'
factor_template = {'G_bn':lv.G_bn,'SA':lv.SA}
for factor in Utils.inst_filling(factor_template):
factor = ('_factor_%s_%s.model'%(factor['G_bn'],factor['SA'])).replace(':','-')
ls.store_model(CPT(ess[factor],child='UA_tt',cpt_force=True),factor)
logliks.append(loglik)
relgain = ((loglik - prevloglik)/math.fabs(prevloglik))
print 'prevloglik: %e'%prevloglik
print 'loglik: %e'%loglik
print 'relgain: %e'%relgain
if relgain < self.tol:
break
prevloglik = loglik
loglik = 0.0
print 'Parameter learning done'
end_time = time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime())
print 'Log likelihood (%d): %s'%(len(logliks),logliks)
print 'Start time: %s'%start_time
print 'End time: %s'%end_time
import Variables as Var
# style.use('seaborn-poster')
# style.use('ggplot')
style.use('seaborn-bright')
style.use('seaborn-whitegrid')
style.use('seaborn-paper')
AnimInterv = 5000
xRange = 600
setXLim = False # True
animated = False # False
for i in range(Var.numBrainNeurons):
p = Var.idMapper(i + 1)
print('i: {} corresponds to Pixel({},{}) '.format(i, p.x, p.y))
def drawWeights(i, ax, name):
# print(i,ax,name)
# coordinates = [[(float(i),j+((2.*i)/(j+1.)))for i in range(NENTRIES)]for j in range(NLINES)]
with open(name + '.csv') as csv_file:
# with open('left-weights.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
matrix = []
for i in csv_reader:
matrix.append(i)
# print(matrix)
NLINES = len(matrix[1])
NENTRIES = len(matrix)
import Variables as v
import matplotlib.pyplot as plt
import numpy as np
test=v.newVar('lognormal')
test.setDist([10.,4.])
vals=test.sample(n=int(1e6))
hist,bounds=np.histogram(vals,bins=100)
ctrs=np.zeros(len(bounds)-1)
for c in range(len(ctrs)):
ctrs[c]=0.5*(bounds[c]+bounds[c+1])
plt.plot(ctrs,hist)
plt.show()
print np.average(vals)
