def addCourse():
global tfCourseName
global tfCourseId
global tfCourseFee
global frame
global btnEnter
frame = JFrame("Add Course ")
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE)
frame.setSize(450, 450)
frame.setLocation(200, 200)
frame.setLayout(None)
frame.setVisible(True)
panel = JPanel()
panel.setSize(450, 450)
panel.setLocation(0, 0)
panel.setLayout(None)
panel.setVisible(True)
panel.setBackground(Color.LIGHT_GRAY)
heading = JLabel("ADD COURSE")
heading.setBounds(200, 30, 150, 40)
lbCourseName = JLabel("Course Name ")
lbCourseId = JLabel("Course Id")
lbCourseFee = JLabel(" Course Fee")
tfCourseName = JTextField()
tfCourseId = JTextField()
tfCourseFee = JTextField()
lbCourseName.setBounds(70, 120, 130, 30)
lbCourseId.setBounds(70, 170, 130, 30)
lbCourseFee.setBounds(70, 220, 130, 30)
tfCourseName.setBounds(220, 120, 150, 30)
tfCourseId.setBounds(220, 170, 150, 30)
tfCourseFee.setBounds(220, 220, 150, 30)
btnEnter = JButton("Enter", actionPerformed=clickAddCourseFee)
btnEnter.setBounds(300, 300, 100, 40)
btnCancel = JButton("Cancel", actionPerformed=clickCancel)
btnCancel.setBounds(70, 300, 100, 40)
panel.add(heading)
panel.add(lbCourseName)
panel.add(lbCourseId)
panel.add(lbCourseFee)
panel.add(tfCourseFee)
panel.add(tfCourseName)
panel.add(tfCourseId)
panel.add(tfCourseFee)
panel.add(btnEnter)
panel.add(btnCancel)
frame.add(panel)
def showLoginIdPassword(data):
global frame
frame = JFrame("Show Id Password ")
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE)
frame.setSize(500,350)
frame.setLocation(200,200)
frame.setLayout(None)
frame.setVisible(True)
panel = JPanel()
panel.setSize(500,350)
panel.setLocation(0,0)
panel.setLayout(None)
panel.setVisible(True)
panel.setBackground(Color.LIGHT_GRAY)
heading = JLabel("LoginId AND Password")
heading.setBounds(200,30,150,40)
lbLoginId = JLabel("LoginId")
lbPassword = JLabel("password")
tfLoginId = JTextField(data[0].encode('ascii'))
tfPassword = JTextField(data[1].encode('ascii'))
tfLoginId.setEditable(False)
tfPassword.setEditable(False)
lbLoginId.setBounds(50,100,150,30)
lbPassword.setBounds(50,150,150,30)
tfLoginId.setBounds(220,100,150,30)
tfPassword.setBounds(220,150,150,30)
btnOk = JButton("Ok",actionPerformed=clickOk)
btnOk.setBounds(250,220,100,30)
panel.add(heading)
panel.add(lbLoginId)
panel.add(lbPassword)
panel.add(tfLoginId)
panel.add(tfPassword)
panel.add(btnOk)
frame.add(panel)
def __init__(self):
# Panel for Measurements
self.setLayout(BorderLayout())
# LINE_START
p3= JPanel()
p3.setLayout(GridLayout(3,1))
button1= JButton('Mode Estimation', actionPerformed= self.modeComputation)
button2= JButton('button2', actionPerformed= self.modeComputation)
button3= JButton('button3', actionPerformed= self.modeComputation)
p3.add(button1)
p3.add(button2)
p3.add(button3)
self.add(p3, BorderLayout.LINE_START)
# LINE_END
reportMeas= JPanel()
reportMeas.setSize(Dimension(800,640))
self.add(reportMeas, BorderLayout.CENTER)
def doall(locations, fileobs,filerun1,filerun2,stime,etime,imageDir='d:/temp',weights=None,filter_type="AVE",normalize=False):
obs=HecDss.open(fileobs,True)
obs.setTimeWindow(stime,etime)
run1=HecDss.open(filerun1,True)
run1.setTimeWindow(stime,etime)
if filerun2 != None:
run2=HecDss.open(filerun2,True)
run2.setTimeWindow(stime,etime)
else:
run2=None
rms1=0
rms1_min,rms1_max=0,0
rms2=0
rms2_min,rms2_max=0,0
rmsmap={}
#run2=None
sumwts=0
average_interval=None;
for l in locations:
data1=get_matching(obs,'A=%s C=%s E=15MIN'%(l,type))
if data1 == None:
data1=get_matching(obs,'A=%s C=%s E=1DAY'%(l,type))
if data1 == None:
data1=get_matching(obs,'A=%s C=%s E=IR-DAY'%(l,type))
if data1 == None:
data1=get_matching(obs,'A=%s C=%s E=1HOUR'%(l,type))
drun1=get_matching(run1,'B=%s C=%s'%(l,type))
if run2 != None:
drun2=get_matching(run2, 'B=%s C=%s'%(l,type))
else:
drun2=None
avg_intvl="1DAY"
if data1 != None:
if average_interval != None:
dobsd=TimeSeriesMath(data1).transformTimeSeries(average_interval, None, filter_type, 0)
else:
dobsd=TimeSeriesMath(data1)
if normalize:
dobsd=dobsd.divide(TimeSeriesMath(data1).mean())
dobsm=TimeSeriesMath(data1).transformTimeSeries(avg_intvl, None, filter_type, 0)
dobsm_max=TimeSeriesMath(data1).transformTimeSeries(avg_intvl, None, "MAX", 0)
dobsm_max.data.fullName=dobsm_max.data.fullName+"MAX"
dobsm_min=TimeSeriesMath(data1).transformTimeSeries(avg_intvl, None, "MIN", 0)
dobsm_min.data.fullName=dobsm_min.data.fullName+"MIN"
if normalize:
dobsm=dobsm.divide(TimeSeriesMath(data1).mean())
if drun1==None:
continue;
else:
if average_interval != None:
drun1d=TimeSeriesMath(drun1).transformTimeSeries(average_interval, None, filter_type, 0)
else:
drun1d=TimeSeriesMath(drun1)
if normalize:
drun1d=drun1d.divide(TimeSeriesMath(drun1).mean())
if drun2 != None:
if average_interval != None:
drun2d=TimeSeriesMath(drun2).transformTimeSeries(average_interval, None, filter_type, 0)
else:
drun2d=TimeSeriesMath(drun2)
if normalize:
drun2d=drun2d.divide(TimeSeriesMath(drun2).mean())
drun1m=TimeSeriesMath(drun1).transformTimeSeries(avg_intvl, None, filter_type, 0)
drun1m_max=TimeSeriesMath(drun1).transformTimeSeries(avg_intvl, None, "MAX", 0)
drun1m_min=TimeSeriesMath(drun1).transformTimeSeries(avg_intvl, None, "MIN", 0)
if normalize:
drun1m=drun1m.divide(TimeSeriesMath(drun1).mean())
if drun2 != None:
drun2m=TimeSeriesMath(drun2).transformTimeSeries(avg_intvl, None, filter_type, 0)
drun2m_max=TimeSeriesMath(drun2).transformTimeSeries(avg_intvl, None, "MAX", 0)
drun2m_min=TimeSeriesMath(drun2).transformTimeSeries(avg_intvl, None, "MIN", 0)
if normalize:
drun2m=drun2m.divide(TimeSeriesMath(drun2).mean())
else:
drun2m=None
if weights != None:
sumwts=sumwts+weights[l]
lrms1 = calculate_rms(drun1m.data, dobsm.data)*weights[l]
lrms1_min=calculate_rms(drun1m_min.data,dobsm_min.data)*weights[l]
lrms1_max=calculate_rms(drun1m_max.data,dobsm_max.data)*weights[l]
rms1=rms1+lrms1
rms1_min=rms1_min+lrms1_min
rms1_max=rms1_max+lrms1_max
lrms2 = calculate_rms(drun2m.data,dobsm.data)*weights[l]
lrms2_min=calculate_rms(drun2m_min.data,dobsm_min.data)*weights[l]
lrms2_max=calculate_rms(drun2m_max.data,dobsm_max.data)*weights[l]
rmsmap[l] = lrms1,lrms2,lrms1_min,lrms2_min,lrms1_max,lrms2_max
rms2=rms2+lrms2
rms2_min=rms2_min+lrms2_min
rms2_max=rms2_max+lrms2_max
plotd = newPlot("Hist vs New Geom [%s]"%l)
if data1 != None:
plotd.addData(dobsd.data)
plotd.addData(drun1d.data)
if drun2 != None:
plotd.addData(drun2d.data)
plotd.showPlot()
legend_label = plotd.getLegendLabel(drun1d.data)
legend_label.setText(legend_label.getText()+" ["+str(int(lrms1*100)/100.)+","+str(int(lrms1_min*100)/100.)+","+str(int(lrms1_max*100)/100.)+"]")
legend_label = plotd.getLegendLabel(drun2d.data)
legend_label.setText(legend_label.getText()+" ["+str(int(lrms2*100)/100.)+","+str(int(lrms2_min*100)/100.)+","+str(int(lrms2_max*100)/100.)+"]")
plotd.setVisible(False)
xaxis=plotd.getViewport(0).getAxis("x1")
vmin =xaxis.getViewMin()+261500. # hardwired to around july 1, 2008
xaxis.setViewLimits(vmin,vmin+10000.)
if data1 != None:
pline = plotd.getCurve(dobsd.data)
pline.setLineVisible(1)
pline.setLineColor("blue")
pline.setSymbolType(Symbol.SYMBOL_CIRCLE)
pline.setSymbolsVisible(0)
pline.setSymbolSize(3)
pline.setSymbolSkipCount(0)
pline.setSymbolFillColor(pline.getLineColorString())
pline.setSymbolLineColor(pline.getLineColorString())
g2dPanel = plotd.getPlotpanel()
g2dPanel.revalidate();
g2dPanel.paintGfx();
plotm = newPlot("Hist vs New Geom Monthly [%s]"%l)
plotm.setSize(1800,1200)
if data1 != None:
plotm.addData(dobsm.data)
#plotm.addData(dobsm_max.data)
#plotm.addData(dobsm_min.data)
plotm.addData(drun1m.data)
#plotm.addData(drun1m_max.data)
#plotm.addData(drun1m_min.data)
if drun2 != None:
plotm.addData(drun2m.data)
#plotm.addData(drun2m_max.data)
#plotm.addData(drun2m_min.data)
plotm.showPlot()
if data1 != None:
pline = plotm.getCurve(dobsm.data)
pline.setLineVisible(1)
pline.setLineColor("blue")
pline.setSymbolType(Symbol.SYMBOL_CIRCLE)
pline.setSymbolsVisible(0)
pline.setSymbolSize(3)
pline.setSymbolSkipCount(0)
pline.setSymbolFillColor(pline.getLineColorString())
pline.setSymbolLineColor(pline.getLineColorString())
plotm.setVisible(False)
if data1 != None:
plots=do_regression_plots(dobsm,drun1m,drun2m)
if plots != None:
spanel = plots.getPlotpanel()
removeToolbar(spanel)
mpanel = plotm.getPlotpanel()
removeToolbar(mpanel)
dpanel = plotd.getPlotpanel()
removeToolbar(dpanel)
from javax.swing import JPanel,JFrame
from java.awt import GridBagLayout, GridBagConstraints
mainPanel = JPanel()
mainPanel.setLayout(GridBagLayout())
c=GridBagConstraints()
c.fill=c.BOTH
c.weightx,c.weighty=0.5,1
c.gridx,c.gridy,c.gridwidth,c.gridheight=0,0,10,4
if data1 != None:
if plots != None:
pass
#mainPanel.add(spanel,c)
c.gridx,c.gridy,c.gridwidth,c.gridheight=0,0,10,4
c.weightx,c.weighty=1,1
mainPanel.add(mpanel,c)
c.gridx,c.gridy,c.gridwidth,c.gridheight=0,4,10,6
mainPanel.add(dpanel,c)
fr=JFrame()
fr.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE)
fr.getContentPane().add(mainPanel)
fr.setSize(1100,850);
fr.show();
mainPanel.setSize(1100,850);
mainPanel.setBackground(Color.WHITE);
#import time; time.sleep(5)
saveToPNG(mainPanel,imageDir+l+".png")
if weights != None:
rms1=(rms1+rms1_min+rms1_max)/sumwts
rms2=(rms2+rms2_min+rms2_max)/sumwts
print 'RMS Run 1: %f'%rms1
print 'RMS Run 2: %f'%rms2
for loc in rmsmap.keys():
print loc, rmsmap[loc]
compression = float(line[0:line.index('\t')])
stringpart = line[line.index("for") + 3:].strip()
oldstring, newstring = stringpart.split(" <=> ")
record = Record(compression, oldstring, newstring)
records.append(record)
numberOfStringPairs = len(records)
frame = JFrame("test")
frame.setSize(600, 400)
panel = JPanel(GridLayout(numberOfStringPairs, 2))
size = Dimension(600, 200 * numberOfStringPairs)
panel.setSize(size)
panel.setPreferredSize(size)
records.sort()
for record in records:
try:
oldname, oldVertices, oldEdges = record.oldstring.split(' ')
newname, newVertices, newEdges = record.newstring.split(' ')
oldPanel = LinearViewPanel(300, 200)
oldPanel.renderVertices(oldVertices)
oldPanel.renderEdges(oldEdges)
oldPanel.setToolTipText(oldname)
panel.add(oldPanel)
newPanel = LinearViewPanel(300, 200)
def doall(locations,
fileobs,
filerun1,
filerun2,
stime,
etime,
imageDir='d:/temp',
weights=None,
filter_type="AVE",
normalize=False):
obs = HecDss.open(fileobs, True)
obs.setTimeWindow(stime, etime)
run1 = HecDss.open(filerun1, True)
run1.setTimeWindow(stime, etime)
if filerun2 != None:
run2 = HecDss.open(filerun2, True)
run2.setTimeWindow(stime, etime)
else:
run2 = None
rms1 = 0
rms1_min, rms1_max = 0, 0
rms2 = 0
rms2_min, rms2_max = 0, 0
rmsmap = {}
#run2=None
sumwts = 0
average_interval = None
for l in locations:
data1 = get_matching(obs, 'A=%s C=%s E=15MIN' % (l, type))
if data1 == None:
data1 = get_matching(obs, 'A=%s C=%s E=1DAY' % (l, type))
if data1 == None:
data1 = get_matching(obs, 'A=%s C=%s E=IR-DAY' % (l, type))
if data1 == None:
data1 = get_matching(obs, 'A=%s C=%s E=1HOUR' % (l, type))
drun1 = get_matching(run1, 'B=%s C=%s' % (l, type))
if run2 != None:
drun2 = get_matching(run2, 'B=%s C=%s' % (l, type))
else:
drun2 = None
avg_intvl = "1DAY"
if data1 != None:
if average_interval != None:
dobsd = TimeSeriesMath(data1).transformTimeSeries(
average_interval, None, filter_type, 0)
else:
dobsd = TimeSeriesMath(data1)
if normalize:
dobsd = dobsd.divide(TimeSeriesMath(data1).mean())
dobsm = TimeSeriesMath(data1).transformTimeSeries(
avg_intvl, None, filter_type, 0)
dobsm_max = TimeSeriesMath(data1).transformTimeSeries(
avg_intvl, None, "MAX", 0)
dobsm_max.data.fullName = dobsm_max.data.fullName + "MAX"
dobsm_min = TimeSeriesMath(data1).transformTimeSeries(
avg_intvl, None, "MIN", 0)
dobsm_min.data.fullName = dobsm_min.data.fullName + "MIN"
if normalize:
dobsm = dobsm.divide(TimeSeriesMath(data1).mean())
if drun1 == None:
continue
else:
if average_interval != None:
drun1d = TimeSeriesMath(drun1).transformTimeSeries(
average_interval, None, filter_type, 0)
else:
drun1d = TimeSeriesMath(drun1)
if normalize:
drun1d = drun1d.divide(TimeSeriesMath(drun1).mean())
if drun2 != None:
if average_interval != None:
drun2d = TimeSeriesMath(drun2).transformTimeSeries(
average_interval, None, filter_type, 0)
else:
drun2d = TimeSeriesMath(drun2)
if normalize:
drun2d = drun2d.divide(TimeSeriesMath(drun2).mean())
drun1m = TimeSeriesMath(drun1).transformTimeSeries(
avg_intvl, None, filter_type, 0)
drun1m_max = TimeSeriesMath(drun1).transformTimeSeries(
avg_intvl, None, "MAX", 0)
drun1m_min = TimeSeriesMath(drun1).transformTimeSeries(
avg_intvl, None, "MIN", 0)
if normalize:
drun1m = drun1m.divide(TimeSeriesMath(drun1).mean())
if drun2 != None:
drun2m = TimeSeriesMath(drun2).transformTimeSeries(
avg_intvl, None, filter_type, 0)
drun2m_max = TimeSeriesMath(drun2).transformTimeSeries(
avg_intvl, None, "MAX", 0)
drun2m_min = TimeSeriesMath(drun2).transformTimeSeries(
avg_intvl, None, "MIN", 0)
if normalize:
drun2m = drun2m.divide(TimeSeriesMath(drun2).mean())
else:
drun2m = None
if weights != None:
sumwts = sumwts + weights[l]
lrms1 = calculate_rms(drun1m.data, dobsm.data) * weights[l]
lrms1_min = calculate_rms(drun1m_min.data,
dobsm_min.data) * weights[l]
lrms1_max = calculate_rms(drun1m_max.data,
dobsm_max.data) * weights[l]
rms1 = rms1 + lrms1
rms1_min = rms1_min + lrms1_min
rms1_max = rms1_max + lrms1_max
lrms2 = calculate_rms(drun2m.data, dobsm.data) * weights[l]
lrms2_min = calculate_rms(drun2m_min.data,
dobsm_min.data) * weights[l]
lrms2_max = calculate_rms(drun2m_max.data,
dobsm_max.data) * weights[l]
rmsmap[
l] = lrms1, lrms2, lrms1_min, lrms2_min, lrms1_max, lrms2_max
rms2 = rms2 + lrms2
rms2_min = rms2_min + lrms2_min
rms2_max = rms2_max + lrms2_max
plotd = newPlot("Hist vs New Geom [%s]" % l)
if data1 != None:
plotd.addData(dobsd.data)
plotd.addData(drun1d.data)
if drun2 != None:
plotd.addData(drun2d.data)
plotd.showPlot()
legend_label = plotd.getLegendLabel(drun1d.data)
legend_label.setText(legend_label.getText() + " [" +
str(int(lrms1 * 100) / 100.) + "," +
str(int(lrms1_min * 100) / 100.) + "," +
str(int(lrms1_max * 100) / 100.) + "]")
legend_label = plotd.getLegendLabel(drun2d.data)
legend_label.setText(legend_label.getText() + " [" +
str(int(lrms2 * 100) / 100.) + "," +
str(int(lrms2_min * 100) / 100.) + "," +
str(int(lrms2_max * 100) / 100.) + "]")
plotd.setVisible(False)
xaxis = plotd.getViewport(0).getAxis("x1")
vmin = xaxis.getViewMin() + 261500. # hardwired to around july 1, 2008
xaxis.setViewLimits(vmin, vmin + 10000.)
if data1 != None:
pline = plotd.getCurve(dobsd.data)
pline.setLineVisible(1)
pline.setLineColor("blue")
pline.setSymbolType(Symbol.SYMBOL_CIRCLE)
pline.setSymbolsVisible(0)
pline.setSymbolSize(3)
pline.setSymbolSkipCount(0)
pline.setSymbolFillColor(pline.getLineColorString())
pline.setSymbolLineColor(pline.getLineColorString())
g2dPanel = plotd.getPlotpanel()
g2dPanel.revalidate()
g2dPanel.paintGfx()
plotm = newPlot("Hist vs New Geom Monthly [%s]" % l)
plotm.setSize(1800, 1200)
if data1 != None:
plotm.addData(dobsm.data)
#plotm.addData(dobsm_max.data)
#plotm.addData(dobsm_min.data)
plotm.addData(drun1m.data)
#plotm.addData(drun1m_max.data)
#plotm.addData(drun1m_min.data)
if drun2 != None:
plotm.addData(drun2m.data)
#plotm.addData(drun2m_max.data)
#plotm.addData(drun2m_min.data)
plotm.showPlot()
if data1 != None:
pline = plotm.getCurve(dobsm.data)
pline.setLineVisible(1)
pline.setLineColor("blue")
pline.setSymbolType(Symbol.SYMBOL_CIRCLE)
pline.setSymbolsVisible(0)
pline.setSymbolSize(3)
pline.setSymbolSkipCount(0)
pline.setSymbolFillColor(pline.getLineColorString())
pline.setSymbolLineColor(pline.getLineColorString())
plotm.setVisible(False)
if data1 != None:
plots = do_regression_plots(dobsm, drun1m, drun2m)
if plots != None:
spanel = plots.getPlotpanel()
removeToolbar(spanel)
mpanel = plotm.getPlotpanel()
removeToolbar(mpanel)
dpanel = plotd.getPlotpanel()
removeToolbar(dpanel)
from javax.swing import JPanel, JFrame
from java.awt import GridBagLayout, GridBagConstraints
mainPanel = JPanel()
mainPanel.setLayout(GridBagLayout())
c = GridBagConstraints()
c.fill = c.BOTH
c.weightx, c.weighty = 0.5, 1
c.gridx, c.gridy, c.gridwidth, c.gridheight = 0, 0, 10, 4
if data1 != None:
if plots != None:
pass
#mainPanel.add(spanel,c)
c.gridx, c.gridy, c.gridwidth, c.gridheight = 0, 0, 10, 4
c.weightx, c.weighty = 1, 1
mainPanel.add(mpanel, c)
c.gridx, c.gridy, c.gridwidth, c.gridheight = 0, 4, 10, 6
mainPanel.add(dpanel, c)
fr = JFrame()
fr.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE)
fr.getContentPane().add(mainPanel)
fr.setSize(1100, 850)
fr.show()
mainPanel.setSize(1100, 850)
mainPanel.setBackground(Color.WHITE)
#import time; time.sleep(5)
saveToPNG(mainPanel, imageDir + l + ".png")
if weights != None:
rms1 = (rms1 + rms1_min + rms1_max) / sumwts
rms2 = (rms2 + rms2_min + rms2_max) / sumwts
print 'RMS Run 1: %f' % rms1
print 'RMS Run 2: %f' % rms2
for loc in rmsmap.keys():
print loc, rmsmap[loc]
#tabbed pane enkripsi dan dekripsi
myTabbedPane = JTabbedPane()
myTabbedPane.setSize(310, 214)
myTabbedPane.setLocation(21, 299)
#global regFont
#regFont = awt.Font("Arial", Font.PLAIN, 13)
#panel1
panel1 = JPanel()
panel1.setOpaque(True)
panel1.setBackground(Color.WHITE)
panel1.setLayout(None)
myTabbedPane.addTab("Enkripsi", panel1)
panel1.setSize(393, 214)
panel1.setLocation(0, 0)
plainTextLabel = JLabel("Pesan asli")
plainTextLabel.setSize(140, 15)
plainTextLabel.setLocation(13, 13)
plainTextLabel.setFont(regFont)
cariPesanButton = JButton("cari pesan", actionPerformed=searchFile)
cariPesanButton.setSize(100, 20)
cariPesanButton.setLocation(166, 13) #y=308
cariPesanButton.setFont(regFont)
plainTextFile = JLabel("n/a")
plainTextFile.setSize(143, 15)
plainTextFile.setLocation(166, 41)
informasiPane = JPanel()
informasiTabbedPane = JTabbedPane()
informasiTabbedPane.setSize(610, 600)
informasiTabbedPane.setLocation(0, 0)
#global regFont
#regFont = awt.Font("Arial", Font.PLAIN, 13)
#panel1
mainFormHelper = JPanel()
mainFormHelper.setOpaque(True)
mainFormHelper.setLayout(None)
informasiTabbedPane.addTab("Halaman Utama", mainFormHelper)
mainFormHelper.setSize(610, 599)
mainFormHelper.setLocation(0, 0)
naiveFormHelper = JPanel()
naiveFormHelper.setOpaque(True)
naiveFormHelper.setLayout(None)
informasiTabbedPane.addTab("Naive Form", naiveFormHelper)
naiveFormHelper.setSize(610, 599)
naiveFormHelper.setSize(0, 0)
hackerFormHelper = JPanel()
hackerFormHelper.setOpaque(True)
hackerFormHelper.setLayout(None)
informasiTabbedPane.addTab("Hacker Form", hackerFormHelper)
hackerFormHelper.setSize(610, 599)
hackerFormHelper.setSize(0, 0)
