Root Programming: Input/Output Comparison

[lamyaa]

Hi all,

I want ask you about root programming , if I have A (mass number) for output and input data for experiment how I can comparison between A input and A output
see attachments

 

[mfb]

Draw both in the same diagram? (histogram->Draw("SAME") iirc).
Draw a two-dimensional plot (probably not in the object browser)?

 

[lamyaa]

thanks a lot ,

but I am beginner in this programming

please, can you explain this point in details

how I can draw both in the same diagram?

 

[gbeagle]

It's not super easy to overlay two histograms on the same canvas in root using the root browser.

It's easiest to just use the command prompt or write a script to be executed by root. ROOT is essentially just a collection of C++ libraries, so there really isn't 'root programming' its just C++. One of the previous posters already gave the basic commands for that. I can give a more explicit example if you need it.

 

[LudusRex]

Hi there,

I can provide some insights on how to compare input and output data in root programming. First, it is important to understand the purpose of the experiment and the significance of the A (mass number) data being used. This will help in determining the appropriate method for comparison.

One approach could be to plot the input and output data on a graph and visually compare the trends and patterns. This can help identify any discrepancies or similarities between the two sets of data. Another method could be to use statistical analysis techniques such as calculating the mean, standard deviation, and performing a t-test to determine if there is a significant difference between the input and output data.

It is also important to consider any potential sources of error in the experiment that could affect the A data. This could include experimental conditions, measurement errors, or data processing techniques. By understanding these factors, it can help in accurately comparing the input and output data.

I hope this helps in your root programming and data analysis. Best of luck with your experiment!