Features

C++ highlighting
C++ Tab-completion
Python(Magic Cell) highlighting
Python(Magic Cell) Tab-completion (using jedi)
R(Magic Cell) highlighting
R(Magic Cell) Tab-completion (using jedi)
JSROOT implemented
ipython magics supported(shell,python,html,etc..)
I/O capture for segfault and in general
new magic added %%doc to show documentation for classes
magics %%cpp to declare functions and classes in cells or to compile with ACLiC
Tested under Gnu/Linux and MacOSX Yisemite

OPINION NOTE:

I think that with this system, we can do a real data analysis using multiple languages and working between they



In [1]:

    
#include <iostream>
#include <TCanvas.h>
#include <TF1.h>
#include <TRInterface.h>

Plotting system



In [2]:

    
TF1 f("f","sin(x)",0,6);
f.Draw();
gPad->Draw();









    












    









    



Info in <TCanvas::MakeDefCanvas>:  created default TCanvas with name c1

Segfault capture



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int *a=0;
a[10]=0;

Using our magic %%cpp magic to declare functions and classes



In [3]:

    
%%cpp -d
void MyFunction()
{
    std::cout<<"Hello from MyFucntion"<<std::endl;
}



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MyFunction();









    



Hello from MyFucntion



In [5]:

    
%%cpp -d
class Test
{
  private:
    std::string msg;
  public:
  Test(std::string _msg);
  void Print();  
};
Test::Test(std::string _msg)
{
    msg=_msg;
}
void Test::Print()
{
    std::cout<<msg<<std::endl;
}



In [6]:

    
Test t("Hello from Class");
t.Print();









    



Hello from Class

Using our magic %%doc (require discussion)



In [7]:

    
%%doc -c TTree

Using other internal magics

NOTE:

the ipython kernels enable a set of default magics for all kernels, in iPyROOT in Cpp mode, the magics dont work(is a bug)
In this kernel the default magics is working

Bash



In [8]:

    
%%shell
for i in $(seq 1 1 10)
do
    echo -n $i" "
done









    



1 2 3 4 5 6 7 8 9 10

HTML and Javascript

LHC Video from CERN's channel in youtube (may useful for tutorials)



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%%html
<iframe width="100%" height="500" src="https://www.youtube.com/embed/pQhbhpU9Wrg" frameborder="0" allowfullscreen></iframe>

Time to measure the time taken for the execution of the cell



In [9]:

    
%%time
for(int i=0;i<3;i++)
{
    sleep(1);
}
std::cout<<"Done!"<<std::endl;









    



Done!
Time: 3.02104997635 seconds.

Using Python Magic

NOTE

support highlighting
support Tab-completion (lets try)



In [10]:

    
%%python
from ROOT import TF1, gPad
print("Testing Python")
f=TF1("f","tanh(x)",-10,10)
f.Draw()
gPad.Draw()
print("DONE!")









    



Testing Python






    












    



DONE!

Using R Magic

Interaction using ROOT-R

NOTE

support highlighting
support Tab-completion (lets try)

Plotting Normal Distribution in R



In [11]:

    
%%r
x <- seq(-4, 4, length=100)
hx <- dnorm(x)

plot(x, hx, type="l", lty=1, xlab="x value",
  ylab="Density", main="Normal Distributions",col="blue")

legend("topright", inset=.05, title="Distributions",
  c("normal"), lwd=2, lty=c(1), col="blue")

Interaction with C++

Getting variables(data) from R and ploting with ROOT



In [12]:

    
ROOT::R::TRInterface &r=ROOT::R::TRInterface::Instance();
std::vector<float> x;
std::vector<float> hx;
r["x"]>>x;
r["hx"]>>hx;
TCanvas c("c");
TGraph g(x.size(),&x.begin()[0],&hx.begin()[0]);
g.Draw();
c.Draw();

Other R plots examples



In [13]:

    
%%r
attach(mtcars)
par(mfrow=c(2,2))
plot(wt,mpg, main="Scatterplot of wt vs. mpg")
plot(wt,disp, main="Scatterplot of wt vs disp")
hist(wt, main="Histogram of wt")
boxplot(wt, main="Boxplot of wt")



In [14]:

    
%%r
x <- seq(-4, 4, length=100)
hx <- dnorm(x)

degf <- c(1, 3, 8, 30)
colors <- c("red", "blue", "darkgreen", "gold", "black")
labels <- c("df=1", "df=3", "df=8", "df=30", "normal")

plot(x, hx, type="l", lty=2, xlab="x value",
  ylab="Density", main="Comparison of t Distributions")

for (i in 1:4){
  lines(x, dt(x,degf[i]), lwd=2, col=colors[i])
}

legend("topright", inset=.05, title="Distributions",
  labels, lwd=2, lty=c(1, 1, 1, 1, 2), col=colors)



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