Example #1
0
from jhplot import HChart,P1D

c1 = HChart("Canvas",600,500, 2, 1)
c1.setGTitle("Polar coordinates")
c1.visible()

c1.cd(1,1)
c1.setName("Polar coordinates-I")
c1.setChartPolar()
p1= P1D("test 1")
p2= P1D("test 2")
# fill
rand = Random() 
for i in range(20):
      x=4.0*i # x-value
      p1.add(i*4, 10.0*rand.nextGaussian());
      p2.add(i*2, 5.0*rand.nextGaussian());
c1.add(p1)
c1.add(p2)
c1.update()

c1.cd(2,1)
p3= P1D("Example")
for i in range(0,3*360,5):
    p3.add( 90-i,i)
c1.setChartPolar()
c1.setName("Polar coordinates-II")
c1.add(p3)
c1.update()

# export to some image (png,eps,pdf,jpeg...)
Example #2
0
# NeuralNetwork.  Build a bayesian Self-Organizing Map. Example II

from jhplot  import *
from java.awt import Color
from java.util import Random


c1 = HPlot("Canvas")
c1.setGTitle("Bayesian Self-Organizing Map")
c1.visible()
c1.setAutoRange()

h1 = H1D("Data",20, -100.0, 300.0)
r = Random()
for i in range(2000):
      h1.fill(100+r.nextGaussian()*100)


p1d=P1D(h1,0,0)

p1d.setErrToZero(1)
bs=HBsom()
bs.setNPoints(30)
bs.setData(p1d)
bs.run()
result=bs.getResult()
result.setStyle("pl")
result.setColor(Color.blue)
c1.draw(p1d)
c1.draw(result)
Example #3
0
#@OUTPUT Integer series1_strokeWidth

series1_strokeColor = "rgb(" + str(r.nextInt(255)) + "," + str(
    r.nextInt(255)) + "," + str(r.nextInt(255)) + ")"
series1_fillColor = series1_strokeColor
series1_strokeWidth = 1

series1_xvalues = []
series1_yvalues = []
series1_error = []

currentY = 0
for i in range(29):
    series1_xvalues.append(i)
    series1_yvalues.append(currentY)
    currentY += r.nextGaussian()
    series1_error.append(abs(r.nextGaussian()))

    r = Random()

# Series 2 Outputs
#@OUTPUT Double[] series2_xvalues
#@OUTPUT Double[] series2_yvalues
#@OUTPUT Double[] series2_error
#@OUTPUT String series2_fillColor
#@OUTPUT String series2_strokeColor
#@OUTPUT Integer series2_strokeWidth

series2_strokeColor = "rgb(" + str(r.nextInt(255)) + "," + str(
    r.nextInt(255)) + "," + str(r.nextInt(255)) + ")"
series2_fillColor = series1_strokeColor
Example #4
0
from java.awt import Color

c1 = HPlot3D("Canvas", 500, 500)
c1.setGTitle("Interactive 3D galaxy")
c1.setRange(-10, 10, -10, 10, -10, 10)
c1.setNameX("X")
c1.setNameY("Y")
c1.visible(1)

# create P2D objects in 3D
p1 = P2D("Galaxy")
p1.setSymbolSize(2)
p1.setSymbolColor(Color.blue)

rand = Random()
for i in range(5000):
    x = 3 * rand.nextGaussian()
    y = 3 * rand.nextGaussian()
    z = 0.4 * rand.nextGaussian()
    p1.add(x, y, z)
c1.draw(p1)

h2 = P2D("Core")
h2.setSymbolSize(2)
h2.setSymbolColor(Color.yellow)
for i in range(5000):
    x = 0.9 * rand.nextGaussian()
    y = 0.9 * rand.nextGaussian()
    z = 0.8 * rand.nextGaussian()
    h2.add(x, y, z)
c1.draw(h2)
Example #5
0
# Data clustering | C | 1.7 | S.Chekanov | Perform a cluster analysis using jMinHEP GUI

from java.util import Random 
from jminhep.cluster    import *
from jhplot import *

# create data for analysis 
data = DataHolder("Example")
# fill 3D data with Gaussian random numbers
rand = Random()
for i in range(100):
      a =[]
      a.append( 10*rand.nextGaussian() )
      a.append( 2*rand.nextGaussian()+1 )
      a.append( 10*rand.nextGaussian()+3 )
      data.add( DataPoint(a) )

# start jMinHEP GUI
c1=HCluster(data)
Example #6
0
c1 = HPlot3D("Canvas",500,500)
c1.setGTitle("Interactive 3D galaxy") 
c1.setRange(-10,10,-10,10,-10,10)
c1.setNameX("X")
c1.setNameY("Y")
c1.visible(1)


# create P2D objects in 3D 
p1= P2D("Galaxy")
p1.setSymbolSize(2);
p1.setSymbolColor(Color.blue);

rand = Random()
for i in range(5000):
      x=3*rand.nextGaussian()
      y=3*rand.nextGaussian()
      z=0.4*rand.nextGaussian()
      p1.add(x,y,z)
c1.draw(p1)

h2=P2D("Core")
h2.setSymbolSize(2) 
h2.setSymbolColor(Color.yellow)
for i in range(5000):
      x=0.9*rand.nextGaussian()
      y=0.9*rand.nextGaussian()
      z=0.8*rand.nextGaussian()
      h2.add(x,y,z)
c1.draw(h2)
c1.valueLine(8.0, "First", "category3");

c1.valueLine(3.0, "Second", "category1");
c1.valueLine(2.8, "Second", "category2");
c1.valueLine(4.0, "Second", "category3");
c1.valueLine(1.0, "Second", "category3");
c1.update()



# new plot. Fill a  histogram
h1=H1D("histogram",20,-2,2) 
h1.setFillColor(Color.blue)
rand = Random()
for i in range(1000):
	h1.fill(rand.nextGaussian())

c1.cd(2,1)
c1.setName("Histogram example")
c1.setRange(0,-2,2)
c1.setRange(1,0,100)
c1.add(h1)
c1.update()



c1.export("a.pdf")
# export to some image (png,eps,pdf,jpeg...)
# c1.export(Editor.DocMasterName()+".png")

Example #8
0
import math
from java.util import Random
from java.lang import Double

r = Random()

# Series 1 Outputs
#@OUTPUT Double[] series1_xvalues
#@OUTPUT Double[] series1_yvalues
#@OUTPUT Double[] series1_size
#@OUTPUT String[] series1_label
#@OUTPUT String[] series1_color
#@OUTPUT String series1_markerColor

series1_markerColor = "lightgreen"

series1_xvalues = []
series1_yvalues = []
series1_size = []
series1_color = []
series1_label = []

for i in range(99):
    series1_xvalues.append(Double.valueOf(r.nextGaussian()))
    series1_yvalues.append(Double.valueOf(r.nextGaussian()))
    series1_size.append(
        Double.valueOf(4 / math.sqrt(series1_xvalues[i] * series1_xvalues[i] +
                                     series1_yvalues[i] * series1_yvalues[i])))
    series1_color.append("rgb(" + str(r.nextInt(255)) + "," +
                         str(r.nextInt(255)) + "," + str(r.nextInt(255)) + ")")
    series1_label.append("point " + str(i))
Example #9
0
# NeuralNetwork. Build a bayesian Self-Organizing Map. Example I

from java.util import Random
from jhplot  import *

h1 = H1D("Data",20, -100.0, 300.0)
r = Random()
for i in range(2000):
      h1.fill(100+r.nextGaussian()*100) 
      h1.fill(100+r.nextDouble()*100) 
      
          
p1d=P1D(h1,0,0)
# write to a file
p1d.toFile("data.txt")

bs=HBsom()
bs.setNPoints(30)
bs.setData(p1d)
bs.visible()
Example #10
0
r = Random()

# Series 1 Outputs
#@OUTPUT Double[] series1_values
#@OUTPUT String series1_strokeColor
#@OUTPUT Integer series1_strokeWidth

series1_strokeColor = "rgb(" + str(r.nextInt(255)) + "," + str(
    r.nextInt(255)) + "," + str(r.nextInt(255)) + ")"
series1_strokeWidth = 2

series1_values = []

for i in range(999):
    series1_values.append(Double.valueOf(r.nextGaussian()))

# Series 2 Outputs
#@OUTPUT Double[] series2_values
#@OUTPUT String series2_strokeColor
#@OUTPUT Integer series2_strokeWidth

series2_strokeColor = "rgb(" + str(r.nextInt(255)) + "," + str(
    r.nextInt(255)) + "," + str(r.nextInt(255)) + ")"
series2_strokeWidth = 2

series2_values = []

for i in range(999):
    series2_values.append(Double.valueOf(r.nextGaussian() - 5))
Example #11
0
c1.cd(1, 1)
c1.setChartPie()
c1.setName("Pie example")
c1.valuePie("Hamburg", 1.0)
c1.valuePie("London", 2.0)
c1.valuePie("Paris", 1.0)
c1.valuePie("Bern", 1.0)
c1.update()

# new plot
c1.cd(1, 2)
c1.setName("XY example")
c1.setNameX("weeks")
c1.setNameY("density")
p1 = P1D("test 1")
p1.setColor(Color.red)
p2 = P1D("test 2")
# fill
rand = Random()
for i in range(1000):
    x = 4.0 * i  # x-value
    p1.add(i * 4, 10.0 * rand.nextGaussian())
    p2.add(i * 2, 5.0 * rand.nextGaussian())
c1.add(p1)
c1.add(p2)
c1.update()

# export to some image (png,eps,pdf,jpeg...)
# c1.export(Editor.DocMasterName()+".png")
# 3D Plots | C | 1.7 | S.Chekanov | 3D histogram (H2D) and a 3D (F2D) function overlyed on HPlot3D

from jhplot import HPlot3D, H2D, F2D
from java.util import Random

c1 = HPlot3D("Canvas", 600, 400)
c1.setGTitle("F2D and H2D objects")
c1.setTextBottom("Global X")
c1.setTextLeft("Global Y")


c1.setNameX("X")
c1.setNameY("Y")

c1.setColorMode(4)
c1.visible(1)

h1 = H2D("My 2D Test 1", 30, -3.0, 3.0, 30, -3.0, 3.0)
f1 = F2D("8*(x*x+y*y)", -3.0, 3.0, -3.0, 5.0)
rand = Random()
for i in range(1000):
    h1.fill(0.4 * rand.nextGaussian(), rand.nextGaussian())
c1.draw(h1, f1)

# export to some image (png,eps,pdf,jpeg...)
# c1.export(Editor.DocMasterName()+".svg")
c1.export("image.pdf")
c1.export("image.eps")