Two-Dimensional Histograms | CERN ROOT Tutorial

☰ 1. Introduction to ROOT

☰ 1.1. What Is ROOT?
☰ 1.2. Installing ROOT
☰ 1.3. Starting ROOT
☰ 1.4. Your First ROOT Session

☰ 2. C++ Basics for ROOT

☰ 2.1. Why ROOT Uses C++
☰ 2.2. Variables and Data Types
☰ 2.3. Operators
☰ 2.4. Conditional Statements
☰ 2.5. Loops
☰ 2.6. Functions
☰ 2.7. Arrays and Vectors

☰ 3. ROOT Macros

☰ 3.1. What Is a ROOT Macro?
☰ 3.2. Running ROOT Macros
☰ 3.3. Functions Inside ROOT Macros
☰ 3.4. Compiling ROOT Macros
☰ 3.5. Organizing a ROOT Project

☰ 4. ROOT Objects and the ROOT Object Model

☰ 4.1. Introduction to ROOT Classes
☰ 4.2. Object Names and Titles
☰ 4.3. ROOT Collections
☰ 4.4. Inspecting ROOT Objects

☰ 5. Histograms

☰ 5.1. Introduction to Histograms
☰ 5.2. Creating a 1D Histogram
☰ 5.3. Filling Histograms
☰ 5.4. Drawing Histograms
☰ 5.5. Histogram Properties
☰ 5.6. Accessing Histogram Bins
☰ 5.7. Histogram Errors
☰ 5.8. Normalizing Histograms
☰ 5.9. Combining Histograms

☰ 6. Two-Dimensional Histograms

☰ 6.1. Creating 2D Histograms
☰ 6.2. Filling 2D Histograms
☰ 6.3. Drawing 2D Histograms
☰ 6.4. Projections
☰ 6.5. Profiles

☰ 7. Graphs

☰ 7.1. Introduction to TGraph
☰ 7.2. Creating a TGraph
☰ 7.3. Graph Styling
☰ 7.4. TGraphErrors
☰ 7.5. TGraphAsymmErrors
☰ 7.6. MultiGraph

☰ 8. Canvases and Plotting

☰ 8.1. TCanvas
☰ 8.2. Dividing a Canvas
☰ 8.3. Drawing Multiple Objects
☰ 8.4. Legends
☰ 8.5. Text and Annotations
☰ 8.6. Logarithmic Axes
☰ 8.7. Saving Plots

☰ 9. Styling ROOT Plots

☰ 9.1. ROOT Plot Styles
☰ 9.2. Axis Configuration
☰ 9.3. Line Styles
☰ 9.4. Marker Styles
☰ 9.5. Publication-Quality Figures

☰ 10. Mathematical Functions

☰ 10.1. Introduction to TF1
☰ 10.2. Built-in Functions
☰ 10.3. Custom Functions
☰ 10.4. Evaluating Functions
☰ 10.5. Function Integrals

☰ 11. Curve Fitting

☰ 11.1. Introduction to Fitting
☰ 11.2. Gaussian Fits
☰ 11.3. Polynomial Fits
☰ 11.4. Custom Fit Functions
☰ 11.5. Fit Parameters
☰ 11.6. Goodness of Fit
☰ 11.7. Fit Residuals
☰ 11.8. Fitting Graphs

☰ 12. ROOT Files

☰ 12.1. Introduction to ROOT Files
☰ 12.2. Creating ROOT Files
☰ 12.3. Writing Objects
☰ 12.4. Reading ROOT Files
☰ 12.5. Exploring ROOT Files
☰ 12.6. Directories Inside ROOT Files

☰ 13. TTrees

☰ 13.1. Introduction to TTrees
☰ 13.2. Creating a TTree
☰ 13.3. Filling a TTree
☰ 13.4. Writing a TTree to a File
☰ 13.5. Reading a TTree
☰ 13.6. Inspecting TTrees
☰ 13.7. Drawing Data from TTrees
☰ 13.8. Applying Selection Cuts
☰ 13.9. Branch Addresses

☰ 14. Event-Based Data Analysis

☰ 14.1. Understanding Event Data
☰ 14.2. Event Loops
☰ 14.3. Event Selection
☰ 14.4. Derived Quantities
☰ 14.5. Analysis Workflow

☰ 15. Working with Real Experimental Data

☰ 15.1. Importing Text Data
☰ 15.2. Converting Data to ROOT
☰ 15.3. Data Cleaning
☰ 15.4. Data Calibration
☰ 15.5. Signal and Background

☰ 16. Random Numbers and Simulations

☰ 16.1. Random Number Generation
☰ 16.2. Common Distributions
☰ 16.3. Simple Monte Carlo Simulation
☰ 16.4. Detector Resolution Simulation
☰ 16.5. Efficiency Simulation

☰ 17. Statistical Analysis with ROOT

☰ 17.1. Basic Statistics
☰ 17.2. Probability Distributions
☰ 17.3. Statistical Uncertainties
☰ 17.4. Chi-Square Tests
☰ 17.5. Confidence Intervals

☰ 18. Modern ROOT with RDataFrame

☰ 18.1. Introduction to RDataFrame
☰ 18.2. Loading Data
☰ 18.3. Filtering Data
☰ 18.4. Defining New Columns
☰ 18.5. Creating Histograms
☰ 18.6. Statistical Operations
☰ 18.7. Saving Results
☰ 18.8. Multithreading

☰ 19. ROOT and Python

☰ 19.1. Introduction to PyROOT
☰ 19.2. ROOT Objects in Python
☰ 19.3. Reading ROOT Files with Python
☰ 19.4. PyROOT and NumPy
☰ 19.5. PyROOT and Matplotlib
☰ 19.6. Choosing Between C++ and Python

☰ 20. Advanced TTree Techniques

☰ 20.1. Trees with Multiple Branches
☰ 20.2. Storing std::vector Objects
☰ 20.3. TChain
☰ 20.4. Friends
☰ 20.5. Efficient TTree Analysis

☰ 21. ROOT for Particle and Nuclear Physics

☰ 21.1. Four-Vectors
☰ 21.2. Particle Kinematics
☰ 21.3. Invariant Mass
☰ 21.4. Angular Distributions
☰ 21.5. Detector Spectra

☰ 22. Debugging and Common ROOT Problems

☰ 22.1. ROOT Object Ownership
☰ 22.2. Null Pointers
☰ 22.3. Segmentation Faults
☰ 22.4. Missing Histograms
☰ 22.5. ROOT File Problems
☰ 22.6. TTree Branch Problems
☰ 22.7. Histogram Range Problems
☰ 22.8. Fit Failures
☰ 22.9. Debugging ROOT Macros

☰ 23. Writing Better ROOT Analysis Code

☰ 23.1. Separating Analysis and Plotting
☰ 23.2. Using Functions
☰ 23.3. Using Header Files
☰ 23.4. Naming Conventions
☰ 23.5. Avoiding Hard-Coded Values
☰ 23.6. Configuration Parameters
☰ 23.7. Reproducible Analysis
☰ 23.8. Version Control with Git

☰ 24. Final Project

☰ 24.1. Project Overview
☰ 24.2. Analyze a complete scientific dataset using ROOT.
☰ 24.3. Import the Data
☰ 24.4. Explore the Dataset
☰ 24.5. Apply Data Selection
☰ 24.6. Create Histograms
☰ 24.7. Fit the Data
☰ 24.8. Calculate Physical Quantities
☰ 24.9. Estimate Statistical Uncertainties
☰ 24.10. Create Publication-Quality Figures
☰ 24.11. Save the Analysis Results
☰ 24.12. Write a Short Analysis Report

☰ 25. Appendices

☰ 25.1. A. ROOT Command Cheat Sheet
☰ 25.2. B. ROOT Histogram Classes
☰ 25.3. C. ROOT Graph Classes
☰ 25.4. D. Common TTree Commands
☰ 25.5. E. Common Drawing Options
☰ 25.6. F. Common Fit Functions
☰ 25.7. G. ROOT C++ Cheat Sheet
☰ 25.8. H. PyROOT Cheat Sheet
☰ 25.9. I. Common ROOT Errors and Solutions
☰ 25.10. J. Recommended ROOT Analysis Workflow

6. Two-Dimensional Histograms

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