def testTempsPfunc(nMax, p, nomMethode, fois = 10, **kwargs):
"""
Teste le temps d'execution moyen d'un algorithme pour le probleme de
couverture de graphe passe par l'argument nomMethode. Son fonctionnement
est identique a la fonction testTempsN, a part le fait que l'argument p est
maintenant une fonction de n.
Args :
nMax : valeur maximale du nombre de sommets du graphe.
p : fonction prennant en argument une valeur de n et renvoyant la
probabilite de presence d'une arete pour cette valeur de n.
nomMethode : chaine de caracteres donnant le nom de la methode a tester.
fois (facultatif) : nombre de repetitions pour chaque valeur de n et p.
**kwargs (facultatif) : arguments passes a la methode a tester.
Returns :
res : tableau numpy de taille 10 avec les temps moyens d'execution en
secondes pour chaque n.
n : tableau numpy de taille 10 contenant les valeurs de n utilises
dans les tests.
"""
n = np.linspace(nMax / 10, nMax, 10, dtype = int)
res = np.zeros(n.shape)
progressBar = ProgressBar(maxValue = n.size * fois)
for ni in range(n.size):
for f in range(fois):
progressBar.update(ni * fois + f + 1)
graphe = Graphe(nbSommets = n[ni], probaArete = p(n[ni]))
start = t.process_time()
getattr(graphe, nomMethode)(**kwargs)
res[ni] += t.process_time() - start
print("")
return res / fois, n
def testNoeud(n, p, listAlgo):
"""
Calcule le nombre de noeuds dans l'arbre de branchement visites par les
differents algorithmes de branchement passes dans listAlgo.
Args :
n : tableau numpy avec les valeurs de n a etre testes.
p : tableau numpy de meme taille que n avec les valeurs correspondants
de p a etre testes.
listAlgo : une liste d'algorithmes a etre testes. Elle doit etre une
liste de tuples. Dans chaque tuple, la premiere entree est une chaine
de caracteres contenant le nom de la methode utilisee et la deuxieme
entree doit etre un dictionnaire avec les arguments passes a la methode.
Les cles de ce dictionnaire sont les noms des arguments (chaines de
caracteres) et les valeurs sont les valeurs des arguments.
Returns :
res : tableau numpy de taille len(listAlgo) x n.size contenant, en
ligne i et colonne j, le nombre de noeuds visites par l'algorithme
listAlgo[i] dans un graphe aleatoire a n[j] sommets et probabilite
d'aretes p[j].
"""
assert n.size == p.size
res = np.zeros((len(listAlgo), n.size), dtype = int)
progressBar = ProgressBar(maxValue = n.size * len(listAlgo))
for ni in range(n.size):
for i, (algoName, algoArgs) in enumerate(listAlgo):
progressBar.update(ni * len(listAlgo) + i + 1)
graphe = Graphe(nbSommets = n[ni], probaArete = p[ni])
_, noeuds = getattr(graphe, algoName)(**algoArgs)
res[i, ni] = noeuds
print("")
return res
def main():
fileName = sys.argv[1]
fileH = MY_FILEH(fileName)
syshostPattern = re.compile(r'syshost:([^ ]*) ')
fnSz = os.path.getsize(fileName)
pbar = ProgressBar(maxVal=fnSz)
sz = 0
t1 = time.time()
with open(fileName) as f:
for line in f:
sz += len(line)
pbar.update(sz)
m = syshostPattern.search(line)
if (not m):
continue
syshost = m.group(1)
fh = fileH.get_file_handle(syshost)
fh.write(line)
fileH.close_file_handles()
pbar.fini()
t2 = time.time()
print("Time: ", time.strftime("%T", time.gmtime(t2-t1)))
def main():
"""
Walks the list of users via the passwd_generator and load the
link and run files.
"""
# Push command line on to XALT_Stack
sA = []
sA.append("CommandLine:")
for v in sys.argv:
sA.append('"'+v+'"')
XALT_Stack.push(" ".join(sA))
args = CmdLineOptions().execute()
xalt = XALTdb(dbConfigFn(args.dbname))
num = int(capture("getent passwd | wc -l"))
pbar = ProgressBar(maxVal=num)
icnt = 0
t1 = time.time()
rmapT = Rmap(args.rmapD).reverseMapT()
iuser = 0
lnkCnt = 0
runCnt = 0
xaltDir = args.datadir
if (os.path.isdir(xaltDir)):
iuser += 1
linkFnA = files_in_tree(xaltDir, "*/link.*.json")
XALT_Stack.push("link_json_to_db()")
lnkCnt += link_json_to_db(xalt, args.listFn, rmapT, linkFnA)
XALT_Stack.pop()
if (args.delete):
remove_files(linkFnA)
#remove_files(files_in_tree(xaltDir, "*/.link.*.json"))
runFnA = files_in_tree(xaltDir, "*/run.*.json")
XALT_Stack.push("run_json_to_db()")
runCnt += run_json_to_db(xalt, args.listFn, rmapT, runFnA)
XALT_Stack.pop()
if (args.delete):
remove_files(runFnA)
#remove_files(files_in_tree(xaltDir, "*/.run.*.json"))
icnt += 1
pbar.update(icnt)
xalt.connect().close()
pbar.fini()
t2 = time.time()
rt = t2 - t1
if (args.timer):
print("Time: ", time.strftime("%T", time.gmtime(rt)))
print("num users: ", iuser, ", num links: ", lnkCnt, ", num runs: ", runCnt)
def _dist_matrix(self, x, y):
"""Computes the M x N distance matrix between the training
dataset and testing dataset (y) using the DTW distance measure
Arguments
---------
x : array of shape [n_samples, n_timepoints]
y : array of shape [n_samples, n_timepoints]
Returns
-------
Distance matrix between each item of x and y with
shape [training_n_samples, testing_n_samples]
"""
# Compute the distance matrix
dm_count = 0
# Compute condensed distance matrix (upper triangle) of pairwise dtw distances
# when x and y are the same array
if (np.array_equal(x, y)):
x_s = np.shape(x)
dm = np.zeros((x_s[0] * (x_s[0] - 1)) // 2, dtype=np.double)
p = ProgressBar(np.shape(dm)[0], True)
for i in range(0, x_s[0] - 1):
for j in range(i + 1, x_s[0]):
dm[dm_count] = self._dtw_distance(
x[i, ::self.subsample_step],
y[j, ::self.subsample_step])
dm_count += 1
p.animate(dm_count)
# Convert to squareform
dm = squareform(dm)
return dm
# Compute full distance matrix of dtw distnces between x and y
else:
x_s = np.shape(x)
y_s = np.shape(y)
dm = np.zeros((x_s[0], y_s[0]))
dm_size = x_s[0] * y_s[0]
p = ProgressBar(dm_size, True)
for i in range(0, x_s[0]):
for j in range(0, y_s[0]):
dm[i, j] = self._dtw_distance(x[i, ::self.subsample_step],
y[j, ::self.subsample_step])
# Update progress bar
dm_count += 1
p.animate(dm_count)
return dm
def convert_save(self, filename):
widgets = [' ', Bar('#'), ' ', BarLabel('Parsing "%s" ....' % filename, 'Parsing "%s" Done' % filename), ' | ',Percentage(),' | ', ETA(), ' ']
tmpname = filename + '.' + self.convertTo
fr = open(filename)
fw = open(tmpname, 'w')
bar = ProgressBar(widgets=widgets, maxval=os.path.getsize(filename)).start()
try:
while True:
line = fr.readline()
if not line: break
fw.write( self.__parse(line) )
bar.update(fr.tell())
shutil.move(tmpname, filename)
bar.finish()
finally:
fr.close()
fw.close()
def __init__(self, state, actionList, regions, names):
discountFactor = 0.9
self.rsa = {}
self.regions = regions
self.names = names
p = ProgressBar(len(actionList), 'Querying', 'Complete')
p.show(0)
for act in actionList:
ns = self.nextStates(state, act)
nextqsa = 0
for s in ns:
A = self.possibleActions(s, regions)
a = self.argmax(s,A)
nextqsa += float(a[1])
qsa = self.getQsa(state, act)
rw = qsa - discountFactor*(1./float(len(ns)))*nextqsa
self.rsa[act] = rw
p.show(actionList.index(act)+1)
def main():
args = CmdLineOptions().execute()
xalt = XALTdb(ConfigFn)
num = int(capture("getent passwd | wc -l"))
pbar = ProgressBar(maxVal=num)
icnt = 0
t1 = time.time()
rmapT = Rmap(args.rmapD).reverseMapT()
iuser = 0
lnkCnt = 0
runCnt = 0
for user, hdir in passwd_generator():
xaltDir = os.path.join(hdir,".xalt.d")
if (os.path.isdir(xaltDir)):
iuser += 1
linkFnA = files_in_tree(xaltDir, "*/link.*.json")
lnkCnt += link_json_to_db(xalt, user, rmapT, linkFnA)
if (args.delete):
remove_files(linkFnA)
remove_files(files_in_tree(xaltDir, "*/.link.*.json"))
runFnA = files_in_tree(xaltDir, "*/run.*.json")
runCnt += run_json_to_db(xalt, user, rmapT, runFnA)
if (args.delete):
remove_files(runFnA)
remove_files(files_in_tree(xaltDir, "*/.run.*.json"))
icnt += 1
pbar.update(icnt)
xalt.connect().close()
pbar.fini()
t2 = time.time()
rt = t2 - t1
if (args.timer):
print("Time: ", time.strftime("%T", time.gmtime(rt)))
print("num users: ", iuser, ", num links: ", lnkCnt, ", num runs: ", runCnt)
def classify(self, data):
"""
classify() classifies each data item in the input by finding the best prototype vector.
Keyword Arguments:
data -- the test data to classify
"""
guesses = []
progressBar = ProgressBar(100, len(data), "Classifying Data")
for index, entry in enumerate(data):
progressBar.update(index)
values = util.Counter()
# for each label, compute activation
for label in self.legalLabels:
activation = 0
# sum over the weights * values to get activation
for key, value in entry.items():
activation += self.weights[label][key] * value
values[label] = activation
# add classification guess for data by getting the argmax
guesses.append(values.argMax())
progressBar.clear()
return guesses
def testEcart(nMax, p, nomMethode, fois = 10):
"""
Teste l'ecart entre les solutions donnees par les algorithmes approches et
la solution exacte. L'algorithme approche a etre teste est donne par
l'argument nomMethode, alors que l'algorithme exact de comparaison est
l'algorithme de branchement ameliore avec sommets pris par ordre
decroissant de degre et elimination de sommets de degre 1.
La fonction cree des graphes aleatoires a n sommets pour 10 valeurs de n
allant de nMax/10 jusqu'à nMax, avec un choix aleatoire de presence
d'aretes donne par la probabilite constante p. Pour chaque n et p, le temps
est calcule par une moyenne sur fois graphes.
Args :
nMax : valeur maximale du nombre de sommets du graphe.
p : probabilite de presence d'une arete, constante.
nomMethode : chaine de caracteres donnant le nom de la methode a tester.
fois (facultatif) : nombre de repetitions pour chaque valeur de n et p.
Returns :
res : tableau numpy de taille 10 x fois avec, en ligne i et colonne j,
le rapport entre la longueur de la solution trouvee par nomMethode
et la solution exacte avec un graphe a n[i] sommets et lors de
l'execution j.
n : tableau numpy de taille 10 contenant les valeurs de n utilises
dans les tests.
"""
n = np.linspace(nMax / 10, nMax, 10, dtype = int)
res = np.zeros((n.size, fois))
progressBar = ProgressBar(maxValue = n.size * fois)
for ni in range(n.size):
for f in range(fois):
progressBar.update(ni * fois + f + 1)
graphe = Graphe(nbSommets = n[ni], probaArete = p)
resMethode = getattr(graphe, nomMethode)()
resExacte, _ = graphe.algoBranchementAmeliore(sommetMax = True, elimDegre1 = True)
res[ni, f] = len(resMethode) / len(resExacte) if len(resExacte) != 0 else 1
print("")
return res, n
def trainingHelper(self, trainingData, trainingLabels, iterations):
"""
trainingHelper() classifies training data using the perceptron weights
and updates the perceptron weights if the perceptron is incorrect.
Keyword Arguments:
trainingData -- training data for the perceptron
trainingLabels -- labels for the associated training data
iterations -- desired number of iterations over the training dataset.
"""
for i in range(iterations):
progressBar = ProgressBar(100, len(trainingData), "Learning Weights, Iteration {0} of {1}"
.format(i + 1, iterations))
for j in range(len(trainingData)):
progressBar.update(j)
values = util.Counter()
# Go over each label, and create the value from the training data and current vectors
for label in self.legalLabels:
activation = 0
for key, value in trainingData[j].items():
activation += self.weights[label][key] * value
values[label] = activation
# Here, we update values in weight vectors if we reach an incorrect conclusion.
if values.argMax() != trainingLabels[j]:
for key, value in trainingData[j].items():
self.weights[trainingLabels[j]][key] += value
self.weights[values.argMax()][key] -= value
progressBar.clear()
def __init__ (self, da, de, p, n, listaDeArquivos, rgb, histograma, pb=True): self.da = float(da)/float(100) self.de = float(de)/float(100) self.p = float(p)/float(100) self.n = float(n)/float(100) self.listaDeArquivos = listaDeArquivos self.lms = not rgb self.equalizar = histograma if pb: self.pb = ProgressBar() print "Iniciado correacao... da: " + str(self.da) self.resultado = [] if self.pb: self.pb.setTotal(len(listaDeArquivos))
def main():
"""
read from syslog file into XALT db.
"""
sA = []
sA.append("CommandLine:")
for v in sys.argv:
sA.append('"'+v+'"')
XALT_Stack.push(" ".join(sA))
args = CmdLineOptions().execute()
xalt = XALTdb(ConfigFn)
syslogFile = args.syslog
# should add a check if file exists
num = int(capture("cat "+syslogFile+" | wc -l"))
icnt = 0
t1 = time.time()
rmapT = Rmap(args.rmapD).reverseMapT()
lnkCnt = 0
runCnt = 0
badCnt = 0
count = 0
if num != 0:
pbar = ProgressBar(maxVal=num)
if (os.path.isfile(syslogFile)):
f=open(syslogFile, 'r')
for line in f:
if "XALT_LOGGING" in line:
i=line.find("link:")
if i == -1 :
i=line.find("run:")
if i == -1:
continue # did not find a link or run, continue to next line
array=line[i:].split(":")
type = array[0].strip()
syshost = array[1].strip()
try:
resultT=json.loads(base64.b64decode(array[2]))
XALT_Stack.push("XALT_LOGGING: " + type + " " + syshost)
# XALT_Stack.push("XALT_LOGGING resultT: " + resultT)
if ( type == "link" ):
XALT_Stack.push("link_to_db()")
xalt.link_to_db(rmapT, resultT)
XALT_Stack.pop()
lnkCnt += 1
elif ( type == "run" ):
XALT_Stack.push("run_to_db()")
xalt.run_to_db(rmapT, resultT)
XALT_Stack.pop()
runCnt += 1
else:
print("Error in xalt_syslog_to_db")
XALT_Stack.pop()
except:
badCnt += 1
# figure out length of array[2], as it might be
# near the syslog message size limit
strg=array[2]
lens = len(strg)
# lenx = lens - (lens % 4 if lens % 4 else 4)
print("xalt_syslog_to_db: undecodable entry! length: ",lens)
# resultT = base64.decodestring(strg[:lenx])
# print("result: ",result)
count += 1
pbar.update(count)
pbar.fini()
# what should be done if there are errors?
# what went wrong?
# how do we restart?
#
# xalt.connect().close()
t2 = time.time()
rt = t2 - t1
if (args.timer):
print("Time: ", time.strftime("%T", time.gmtime(rt)))
#
print("total processed : ", count, ", num links: ", lnkCnt, ", num runs: ", runCnt, ", badCnt: ", badCnt)
def main():
pygame.init()
screen = pygame.display.set_mode((640, 480),pygame.SWSURFACE)
pygame.key.set_repeat(100, 100)
'''TEST'''
g=Gui()
#g.enableDirtyRect()
g.optimizeDraw()
i=PygameInput()
Image.mImageLoader=PygameImageLoader()
gr=PygameGraphics()
gr.setTarget(screen)
f=ImageFont("C:\Python25\Projects\Guichan\consolefont.bmp")
#f=ImageFont("consolefont.bmp")
f.setColorkey( Color(255,0,255) )
f.setGlyphSpacing(2)
f2=PygameFont("C:\Python25\Projects\Guichan\LiberationMono-Regular.ttf",14,Color(0,0,0,255))
#f2=PygameFont("C:\Python25\Projects\Guichan\Caracteres L1.ttf",13,Color(0,0,0,255))
f2.setGlyphSpacing(1)
Widget.setGlobalFont(f2)
c=Container()
c.setOpaque(False)
c.setPosition(0,0)
c.setSize(640,480)
c.setBaseColor( Color(255,0,0,255) )
a=ActionListener()
a.action=action
b, b2=Button("YEY!"), Button("WHa?")
b.setPosition(0,50)
b.setActionEventId("Button 1")
b.addActionListener(a)
b2.setPosition(100,100)
b2.setActionEventId("Button 2")
b2.addActionListener(a)
b2.setBaseColor( Color(200,200,200) )
b2.setCaption("ABCDEFGHIJKLMNOPQRSTUVWXYZ!@#$%^&*()")
w,w2=Window("Hey over here!"), Window("Trapped in a window!")
wColor=w.getBaseColor()
wColor.a=200
w.setBaseColor(wColor)
w.setTextColor(Color(255,0,255))
xyz=Button("XYZ")
xyz.setTextColor(Color(0,255,255))
pb=ProgressBar(100.0)
pb.setBaseColor( Color(255,255,0) )
pb.setForegroundColor( Color(0,255,255) )
pb.setSize(100, 20)
pb.setPosition(300, 300)
pb.setValue(50.0)
c.add(w,0,100)
c.add(b)
c.add(b2)
c.add(xyz,10,10)
c.add(pb)
check=Checkbox("Ye what? GET BACK HERE BOY!")
check.setActionEventId("Checkbox")
check.addActionListener(a)
text=TextField("Hey Hey Hey Hey Hey Hey Hey Hey")
text.setBackgroundColor( Color(255,255,255,255) )
text.setMaxSize(150)
text2=TextBox("Hey, HeyTrapped in a window!\nWhat's goin' onTrapped in a window!\ntodays???Trapped in a window!")
text2.setTabSize(10)
sc=ScrollArea(text2)
sc.setSize(200,100)
rBox=Container()
r1=RadioButton("1984","Dystopia")
r2=RadioButton("Fahrenheit 451","Dystopia")
r3=RadioButton("Brave New World","Dystopia")
rBox.add(r1,0,0)
rBox.add(r2,0,r1.getY()+r1.getHeight())
rBox.add(r3,0,r2.getY()+r2.getHeight())
label=Label("WE AIN'T GOT IT")
ico_image=Image.load("C:\Python25\Projects\Guichan\May.bmp")
ico=Icon(ico_image)
lb=ListBox( List_ListModel(["Bollocks!","Never!","Cuppa tea, mate?","Hello!","Goodbye!","OK Computer!","Oh Inverted World!","How To Disappear Completely!","Hold Still!","It Takes A Train To Cry!","A","B","C","D","E","F","G","H","I",]) )
sc2=ScrollArea(lb)
sc2.setSize(125,100)
lb.setWidth(110)
slider=Slider(0,100)
slider.setOrientation(Slider.Orientation.VERTICAL)
slider.setSize(15,100)
slider.setActionEventId("Slider")
#slider.addActionListener(a)
ib=ImageButton(ico_image)
ta=TabbedArea()
c.add(w2)
ta.addTab("Text",[ (text,0,0), (sc,0,50) ])
ta.addTab("Check",check)
ta.addTab("Radio",rBox)
ta.addTab("List",[ (sc2,0,0) ])
ta.addTab("Label",label)
ta.addTab("Icon",[ (ico,0,0), (ib,100,0) ])
ta.addTab("Slider",slider)
ta.setSize(300,300)
w2.add(ta,0,0)
g.setGraphics(gr)
w2.resizeToContent()
w.setSize(300,300)
g.setInput(i)
g.setTop(c)
clock=pygame.time.Clock()
g.mDirtyRect.addRect( Rectangle(0,0,640,480) )
done=False
while done == False:
clock.tick(0)
for event in pygame.event.get():
if event.type==KEYDOWN:
if event.key == K_ESCAPE:
c.remove(b)
c.remove(b2)
done=True
elif event.key == K_RETURN:
w=Window("It'a window!")
w.add(Checkbox("Kool thing"))
w.resizeToContent()
c.add(w, 10, 10)
elif event.key == K_LEFT:
pb.setValue( pb.getValue()-1.0 )
elif event.key == K_RIGHT:
pb.setValue( pb.getValue()+1.0 )
if event.type == ACTIVEEVENT:
if event.gain == 1:
g.mDirtyRect.addRect( Rectangle(0,0,640,480) )
i.pushInput(event)
g.logic()
b2.setCaption( str( int(clock.get_fps()) ) )
fRect=GuichanToPygameDirtyRect(g.mDirtyRect.getList())
#for ix in fRect: screen.fill((255,0,0),ix)
screen.fill((255,0,0))
g.draw()
#pygame.display.update( GuichanToPygameDirtyRect(g.mDirtyRect.getList()) )
pygame.display.update()
g.mDirtyRect.clearList()
def main():
"""
read from syslog file into XALT db.
"""
sA = []
sA.append("CommandLine:")
for v in sys.argv:
sA.append('"'+v+'"')
XALT_Stack.push(" ".join(sA))
args = CmdLineOptions().execute()
xalt = XALTdb(dbConfigFn(args.dbname))
syslogFile = args.syslog
# should add a check if file exists
num = int(capture("cat "+syslogFile+" | wc -l"))
icnt = 0
t1 = time.time()
rmapT = Rmap(args.rmapD).reverseMapT()
lnkCnt = 0
runCnt = 0
badCnt = 0
count = 0
recordT = {}
if (num == 0):
return
pbar = ProgressBar(maxVal=num)
fnA = [ args.leftover, syslogFile ]
for fn in fnA:
if (not os.path.isfile(fn)):
continue
f=open(fn, 'r')
for line in f:
if (not ("XALT_LOGGING" in line)):
continue
t, done = parseSyslog(line, recordT)
if (not done):
continue
try:
XALT_Stack.push("XALT_LOGGING: " + t['kind'] + " " + t['syshost'])
if ( t['kind'] == "link" ):
XALT_Stack.push("link_to_db()")
xalt.link_to_db(rmapT, json.loads(t['value']))
XALT_Stack.pop()
lnkCnt += 1
elif ( t['kind'] == "run" ):
XALT_Stack.push("run_to_db()")
xalt.run_to_db(rmapT, json.loads(t['value']))
XALT_Stack.pop()
runCnt += 1
else:
print("Error in xalt_syslog_to_db", file=sys.stderr)
XALT_Stack.pop()
except Exception as e:
print(e, file=sys.stderr)
badCnt += 1
count += 1
pbar.update(count)
f.close()
pbar.fini()
t2 = time.time()
rt = t2 - t1
if (args.timer):
print("Time: ", time.strftime("%T", time.gmtime(rt)))
print("total processed : ", count, ", num links: ", lnkCnt, ", num runs: ", runCnt, ", badCnt: ", badCnt)
leftover = args.leftover
if (os.path.isfile(leftover)):
os.rename(leftover, leftover + ".old")
# if there is anything left in recordT file write it out to the leftover file.
if (recordT):
f = open(leftover, "w")
for key in recordT:
r = recordT[key]
s = r.prt("XALT_LOGGING V=2", key)
f.write(s)
f.close()
def main():
"""
Walks the list of users via the passwd_generator and load the
link and run files.
"""
# Find transmission style
transmission = os.environ.get("XALT_TRANSMISSION_STYLE")
if (not transmission):
transmission = "@XALT_TRANSMISSION_STYLE@"
if (not transmission):
transmission = "file"
transmission = transmission.lower()
# Push command line on to XALT_Stack
sA = []
sA.append("CommandLine:")
for v in sys.argv:
sA.append('"'+v+'"')
XALT_Stack.push(" ".join(sA))
args = CmdLineOptions().execute()
xalt = XALTdb(args.confFn)
num = int(capture("getent passwd | wc -l"))
pbar = ProgressBar(maxVal=num)
icnt = 0
t1 = time.time()
rmapT = Rmap(args.rmapD).reverseMapT()
iuser = 0
lnkCnt = 0
runCnt = 0
pkgCnt = 0
for user, hdir in passwd_generator():
XALT_Stack.push("User: "******"link")
if (os.path.isdir(xaltDir)):
iuser += 1
linkFnA = files_in_tree(xaltDir, "*/link." + args.syshost + ".*.json")
XALT_Stack.push("link_json_to_db()")
lnkCnt += link_json_to_db(xalt, args.listFn, rmapT, args.delete, linkFnA)
XALT_Stack.pop()
xaltDir = build_xaltDir(user, hdir, transmission, "run")
if (os.path.isdir(xaltDir)):
runFnA = files_in_tree(xaltDir, "*/run." + args.syshost + ".*.json")
XALT_Stack.push("run_json_to_db()")
runCnt += run_json_to_db(xalt, args.listFn, rmapT, args.delete, runFnA)
XALT_Stack.pop()
xaltDir = build_xaltDir(user, hdir, transmission, "pkg")
if (os.path.isdir(xaltDir)):
pkgFnA = files_in_tree(xaltDir, "*/pkg." + args.syshost + ".*.json")
XALT_Stack.push("pkg_json_to_db()")
pkgCnt += pkg_json_to_db(xalt, args.listFn, args.syshost, args.delete, pkgFnA)
XALT_Stack.pop()
icnt += 1
v = XALT_Stack.pop()
carp("User",v)
pbar.update(icnt)
xalt.connect().close()
pbar.fini()
t2 = time.time()
rt = t2 - t1
if (args.timer):
print("Time: ", time.strftime("%T", time.gmtime(rt)))
print("num users: ", iuser, ", num links: ", lnkCnt, ", num pkgs: ", pkgCnt, ", num runs: ", runCnt)
class NewCorrecaoEngine ():
def __init__ (self, da, de, p, n, listaDeArquivos, rgb, histograma, pb=True):
self.da = float(da)/float(100)
self.de = float(de)/float(100)
self.p = float(p)/float(100)
self.n = float(n)/float(100)
self.listaDeArquivos = listaDeArquivos
self.lms = not rgb
self.equalizar = histograma
if pb:
self.pb = ProgressBar()
print "Iniciado correacao... da: " + str(self.da)
self.resultado = []
if self.pb:
self.pb.setTotal(len(listaDeArquivos))
##
def start(self, quandoTermina):
if self.pb:
self.pb.show()
i = 0
while (i<len(self.listaDeArquivos)):
arquivo = self.listaDeArquivos[i]
label = str(str(arquivo).split('/')[-1])
im3 = Image.open(str(arquivo))
if self.pb:
self.pb.setLabel('[1/1] Aplicando filtor unico em ' +str(label))
filtro1 = FiltroDeImagem(debug=False)
filtro1.carregarImg(str(arquivo))
filtro1.callBackPogresso(self.percentagem)
im1 = filtro1.filtrarNovo(self.lms, self.equalizar, self.p, self.de, self.da)
# Filtro 1 { Protan }
#self.pb.setLabel('[1/6] Aplicando filtro Protan em ' + str(label))
#filtro1 = FiltroDeImagem(debug=False)
#filtro1.carregarImg(str(arquivo))
#filtro1.callBackPogresso(self.percentagem)
#im1 = filtro1.filtrarProtan(equalizar = self.equalizar, lms = self.lms)
# Filtro 2 { Deutan }
#self.pb.setLabel('[2/6] Aplicando filtro Deutan em ' + str(label))
#filtro2 = FiltroDeImagem(debug=False)
#filtro2.carregarImg(str(arquivo))
#filtro2.callBackPogresso(self.percentagem)
#im2 = filtro2.filtrarDeutan(equalizar = self.equalizar, lms = self.lms)
# Fuzzy 1
#fuz1 = Fuzzy(False,self.p,self.de,self.da,self.n)
#self.pb.setLabel('[3/6] Aplicando filtro Fuzzy 1 em ' + str(label))
#fuz1.callBackProgresso(self.percentagem)
#im1 = fuz1.multiplicaProtan(im1)
# Fuzzy 2
#fuz2 = Fuzzy(False,self.p,self.de,self.da,self.n)
#self.pb.setLabel('[4/6] Aplicando filtro Fuzzy 2 em ' + str(label))
#fuz1.callBackProgresso(self.percentagem)
#im2 = fuz1.multiplicaDeutan(im2)
#self.pb.setLabel('[5/6] Aplicando filtro Fuzzy 3 em ' + str(label))
#fuz1.callBackProgresso(self.percentagem)
#im3 = fuz1.multiplicaNormal(im3)
# Soma da matrizes
#self.pb.setLabel('[6/6] Aplicando soma de matrizes em ' + str(label))
#fuz1.callBackProgresso(self.percentagem)
#im4 = Image.open(str(arquivo))
#im4 = fuz1.soma(im1, im2, im3, im4)
im1.save("default_output/" + str(i) + ".bmp", "BMP")
self.resultado.append((label, str(arquivo), "default_output/" + str(i) + ".bmp"))
i = i + 1
return self.resultado
def percentagem(self, x):
if self.pb:
return self.pb.setPercentagem(x)
else:
return 0