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Presentation style with logo and LaTeX equation
Source code name: "style2_pres.py"
Programming language: Python
Topic: Plots/2D
DMelt Version 1. Last modified: 05/09/2015. License: Pro
https://datamelt.org/code/cache/style2_pres_6628.py
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from java.awt import *
from java.util import Random
from jhplot import *
from jhplot.shapes import *
def applyStyleGray(c1,f1,h1,p1):
style="Presentation style with logo and LaTeX equation"
st = Font.BOLD + Font.ITALIC;
f = Font("Serif",st,14);
c1.setAntiAlias(True)
c1.setGTitle(style,f,Color.red)
c1.setNameX("X values",Font("Serif", Font.ITALIC, 20),Color.blue)
c1.setNameY("Y values",Font("Serif", Font.ITALIC, 20),Color.blue)
c1.setTicFont(Font("Serif", Font.ITALIC, 14))
c1.setAxisPenTicWidth(1)
c1.setGridAll(0,True)
c1.setGridAll(1,True)
f1.setColor(Color.blue)
f1.setPenWidth(3)
# apply style for histogram
h1.setFill(1)
h1.setPenWidth(2)
h1.setErrX(0)
h1.setErrY(1)
h1.setFillColor( Color(0xFF0096) )
# apply style for data points
p1.setSymbol(4)
p1.setSymbolSize(6)
p1.setColor( Color.green )
return style
# make empty canvas in some range
c1 =HPlot("Canvas")
c1.visible()
c1.setLegend(0)
c1.setRange(0,100,0,100)
c1.setMarginLeft(70)
h1 = H1D("Histogram",20, 50.0, 100.0)
f1=F1D("cos(x)*x",1,50)
p1= P1D("X-Y data")
rand = Random(10)
for i in range(500):
h1.fill(85+10*rand.nextGaussian())
if (i<200): p1.add(56+7*rand.nextGaussian(),70+7*rand.nextGaussian())
# apply style
style=applyStyleGray(c1,f1,h1,p1)
## now put a few points
c1.draw(f1)
c1.draw(h1)
c1.draw(p1)
# draw keys
f=Font("Serif", Font.ITALIC, 18)
k=HKey(h1.getTitle(),0.2,0.8,f,Color.black,"NDC",h1 )
k.setKeySpace(-2)
c1.add(k)
k=HKey(p1.getTitle(),0.2,0.75,f,Color.black,"NDC",p1 )
k.setKeySpace(2)
c1.add(k)
k=HKey(f1.getTitle(),0.2,0.7,f,Color.black,"NDC",f1 )
k.setKeySpace(-2)
c1.add(k)
# put here a picture
#pic= Picture(0.81, 0.95, "globus12_small.png")
#pic.setPosCoord("NDC")
#c1.add(pic)
# show latex equation
lab=HLabelEq("\int_{i=1}^{100}\omega_{i}(x)dx", 5, 50, "USER")
lab.setFontSize(18)
lab.setColor(Color.blue);
c1.add(lab)
# now show all objects
c1.update();
import sys
expfile=sys.argv[0].replace(".py",".png")
c1.export(expfile)
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