Updated formatting of analysis/README.md

analysis/README.md

@@ -4,9 +4,9 @@ VMM3a/SRS Data Analysis Tool:
 vmm-sdat is the analysis software for VMM3a data, recorded with the SRS as PCAP or HDF5 files (GdGEM pipeline of the EFU). From the PCAP or HDF5 file, a root tree with the hits and clusters is created. 
 
 
-## Further analysis with the root tree [`examples_read_data']
+## Further analysis with the root tree [`examples_read_data`]
 
-The produced root tree can be further analyzed in different ways. Some general examples on how to read the data from the root tree are shown in `examples_read_data'.
+The produced root tree can be further analyzed in different ways. Some general examples on how to read the data from the root tree are shown in `examples_read_data`.
 
 
 ### Analysis with Python
@@ -20,41 +20,41 @@ The root framework provides the TSelector mechanism. Details can be found here:
 https://root.cern.ch/developing-tselector
 In short, the following steps are needed.
 1. Open root from the command line
-2. Open the root tree from the root prompt: `TFile f("example.root")'
-3. Get the event tree from the file: `TTree *t = f.Get<TTree>("clusters_detector")'
-4. Create the selector script: `t->MakeSelector("VMM3a_analysis")'
+2. Open the root tree from the root prompt: `TFile f("example.root")`
+3. Get the event tree from the file: `TTree *t = f.Get<TTree>("clusters_detector")`
+4. Create the selector script: `t->MakeSelector("VMM3a_analysis")`
 5. The last command creates two files, VMM3a_analysis.C, VMM3a_analysis.h
 6. Add the plot that you want to create to the script. ATTENTION: In the example provided in the analysis folder, this has already been done!! 
 
 So you need just to call the analysis script from your tree:
-1. At the command line: `root example.root'
-2. In root: `clusters_detector->Process("VMM3a_analysis.C++")'
+1. At the command line: `root example.root`
+2. In root: `clusters_detector->Process("VMM3a_analysis.C++")`
 
 
 ### Analysis with compiled root script
 In the CMakeList.txt in the main directory, the example executable accessTree is created.
 
-`add_executable(accessTree ${CMAKE_CURRENT_SOURCE_DIR}/analysis/accessTree.cpp)'
+`add_executable(accessTree ${CMAKE_CURRENT_SOURCE_DIR}/analysis/accessTree.cpp)`
 
 This example can be edited to analyze and plot different data from the tree. In principle the same things can be done with the compiled root script and the TSelector root script. The compiled executable will just be faster.
 
 
 ### Analysis with CINT root script
 This example creates a multitude of plots for the LET Multigrid detector that consists of grids and wires. It can be easily adapted to detector with an x/y readout by replacing wires with x and strips with y. To execute the script, the following strips are necessary:
-1. start root by typing in a terminal: `root'
-2. in root, type `.x plots_LET.C++("example_LET",".",0)'
+1. start root by typing in a terminal: `root`
+2. in root, type `.x plots_LET.C++("example_LET",".",0)`
 
 
 ### Normalization of histograms
 The script normalizeHisto can be used to normalize histograms, or carry out a 
 This example creates a multitude of plots for the LET Multigrid detector that consists of grids and wires. It can be easily adapted to detector with an x/y readout by replacing wires with x and strips with y. To execute the script, the following strips are necessary:
-1. start root by typing in a terminal: `root'
-2. in root, type `.x plots_LET.C++("example_LET",".",0)'
+1. start root by typing in a terminal: `root`
+2. in root, type `.x plots_LET.C++("example_LET",".",0)`
 
 
 ## Specific applications
 
-In addition to the analysis methods that are introduced in general in `examples_read_data', also specific analysis programs for one specific application are shown here.
+In addition to the analysis methods that are introduced in general in `examples_read_data`, also specific analysis programs for one specific application are shown here.
 
 
 ### RD51 Beam Telescope [`application_rd51_beam_telescope']