#
from jhplot  import * 
from jhplot.stat  import LinReg
from java.awt import Color
from java.util import Random

print "\njhplot.regression:"
c1 = HPlot("Canvas")
c1.visible(1)
c1.setGTitle("Linear regression")
c1.setAutoRange()


p1= P1D("data")
rand = Random();
for i in range(500):
          x=rand.nextGaussian()
          y=rand.nextGaussian()
          p1.add(0.2*x, y)
c1.draw(p1);

#d="-0.3222682085734333456+(-0.0103614777304622313*x)"
#f1=F1D("ss",d,20,100,0)
#f1.parse()

r = LinReg(p1)
print "Intercept=",r.getIntercept(), "+/-",r.getInterceptError() 
print "Slope=",r.getSlope(),"+/-",r.getSlopeError() 


# f1= r.getResult() 
#print f1.getName()
#print f1.eval(22)

# get predictions as band
pC=r.getConfidenceBand(Color.red,0.5)
c1.draw(pC)

pP=r.getPredictionBand(Color.red,0.5)
c1.draw(pP)

# draw original data 
# c1.draw(p1)


# draw F1D function with the result
c1.draw(  r.getResult()  )

# draw P1D[2] with predictions 
c1.draw(   r.getPrediction() )

# draw P1D[2} with confidence
c1.draw(   r.getConfidence() )


# p.setErrFillColor(Color.blue,0.5)
# p.setErr(1)
# c1.draw(p)