cd /alice/sim/2016/LHC16g1/246757/AOD198/0002/
cp alien://AliAOD.root file://AliAOD.root
-
AliEn legacy shell
In case you are using AliEn legacy software please use aliensh instead of alien.py.
+
AliEn legacy shell
In case you are using AliEn legacy software please use aliensh instead of alien.py.
The syntax in aliensh is slightly different, you should use alien: and file: prefix. For example:
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var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"Step 6 -Using Monte Carlo data","level":"1.5.2.6","depth":3,"next":{"title":"Step 7 -Run your code on GRID","level":"1.5.2.7","depth":3,"path":"analysis/grid.md","ref":"analysis/grid.md","articles":[]},"previous":{"title":"Step 5 -Particle identification","level":"1.5.2.5","depth":3,"path":"analysis/pid.md","ref":"analysis/pid.md","articles":[]},"dir":"ltr"},"config":{"plugins":["katex","panels@git+https://github.com/lhcb/gitbook-plugin-panels.git#117012fdc18c96831cb88196980c0ea73b0c87b8","collapsible-menu","block-align","page-toc"],"styles":{"website":"css/website.css"},"pluginsConfig":{"collapsible-menu":{},"block-align":{},"search":{},"page-toc":{"position":"before-first","selector":".markdown-section h1, .markdown-section h2, .markdown-section h3, .markdown-section h4","showByDefault":true},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"panels":{},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2},"highlight":{},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":false}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"ALICE Analysis Tutorial","gitbook":"*","description":"Introduction to the common analysis techniques and tools of ALICE"},"file":{"path":"analysis/MC.md","mtime":"2024-02-16T14:51:36.337Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2024-02-16T14:52:24.685Z"},"basePath":"..","book":{"language":""}});
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});
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var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"Transition from ROOT5 to ROOT6","level":"1.5.2.10","depth":3,"next":{"title":"Rivet","level":"1.6","depth":1,"path":"rivet/rivet-tutorial.md","ref":"rivet/rivet-tutorial.md","articles":[{"title":"Getting started with Rivet","level":"1.6.1","depth":2,"path":"rivet/getting-started.md","ref":"rivet/getting-started.md","articles":[]},{"title":"Using Rivet in ALICE","level":"1.6.2","depth":2,"path":"rivet/rivet-in-alice.md","ref":"rivet/rivet-in-alice.md","articles":[]},{"title":"Implementing a Rivet analysis","level":"1.6.3","depth":2,"path":"rivet/implementing-rivet-analysis.md","ref":"rivet/implementing-rivet-analysis.md","articles":[]},{"title":"Introduction to heavy-ion features","level":"1.6.4","depth":2,"path":"rivet/hi-features.md","ref":"rivet/hi-features.md","articles":[]},{"title":"Reference manual for Rivet in ALICE","level":"1.6.5","depth":2,"path":"rivet/reference-manual.md","ref":"rivet/reference-manual.md","articles":[]},{"title":"Procedures for publishing Rivet analyses","level":"1.6.6","depth":2,"path":"rivet/publishing-procedures.md","ref":"rivet/publishing-procedures.md","articles":[]},{"title":"Advanced topics","level":"1.6.7","depth":2,"path":"rivet/advanced-topics.md","ref":"rivet/advanced-topics.md","articles":[]},{"title":"Advanced heavy-ion features","level":"1.6.8","depth":2,"path":"rivet/advanced-hi-features.md","ref":"rivet/advanced-hi-features.md","articles":[]},{"title":"Coding conventions for Rivet plugins","level":"1.6.9","depth":2,"path":"rivet/coding-conventions.md","ref":"rivet/coding-conventions.md","articles":[]},{"title":"References","level":"1.6.10","depth":2,"path":"rivet/references.md","ref":"rivet/references.md","articles":[]}]},"previous":{"title":"Some hints","level":"1.5.2.9","depth":3,"path":"analysis/hints.md","ref":"analysis/hints.md","articles":[]},"dir":"ltr"},"config":{"plugins":["katex","panels@git+https://github.com/lhcb/gitbook-plugin-panels.git#117012fdc18c96831cb88196980c0ea73b0c87b8","collapsible-menu","block-align","page-toc"],"styles":{"website":"css/website.css"},"pluginsConfig":{"collapsible-menu":{},"block-align":{},"search":{},"page-toc":{"position":"before-first","selector":".markdown-section h1, .markdown-section h2, .markdown-section h3, .markdown-section h4","showByDefault":true},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"panels":{},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2},"highlight":{},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":false}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"ALICE Analysis Tutorial","gitbook":"*","description":"Introduction to the common analysis techniques and tools of ALICE"},"file":{"path":"analysis/ROOT5-to-6.md","mtime":"2024-02-16T14:51:36.337Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2024-02-16T14:52:24.685Z"},"basePath":"..","book":{"language":""}});
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});
These three lines form an include guard (sometimes called macro guard, or header guard). This construct is used to avoid the problem of double inclusion: should the header of your class be included more than once, the include guard will protect your code from double definitions which result in invalid code.
-
Include guards
What is the risk of not using include guards?
-
drum roll Click to expand
Say that you have a header file, called grandparent.h, in which you define a struct
+
Include guards
What is the risk of not using include guards?
+
drum roll Click to expand
Say that you have a header file, called grandparent.h, in which you define a struct
These functions will be the heart of our analysis. In the UserCreateOutputObjects, we will define whatever output we want to write to our root files. The UserExec function will be called for all events in the data sample that we are looking at. Finally, Terminate is called at the very end of the analysis.
-
Virtual functions
In the code snippet above, we see the virtual keyword. Do you know what this means ?
-
Click to show answer Click to expand
Consider the following simple program which is an example of runtime polymorphism.
+
Virtual functions
In the code snippet above, we see the virtual keyword. Do you know what this means ?
+
Click to show answer Click to expand
Consider the following simple program which is an example of runtime polymorphism.
The main thing to note about the program is, derived class function is called using a base class pointer. The idea is, virtual functions are called according to the type of object pointed or referred, not according to the type of pointer or reference. In other words, virtual functions are resolved late, at runtime (which makes them powerful, but costly):
class Employee
{
@@ -1013,7 +1026,7 @@
The implementation of your
}
As you see, in the constructor, we initialize members to their default values. Always initialize members to default values (and pointers to nullptr). If you fail to do so, values contained by the members will be random, which can lead to unexpected behavior of your code.
-
Undefined behavior
You have written a small function
+
Undefined behavior
You have written a small function
intf(int x){
int a;
@@ -1028,12 +1041,12 @@
The implementation of your
f(-10)
?
-
drum rollClick to expand
f(10) will return 42. The output of f(-10) is undefined, since variable a was not initialized.
+
drum rollClick to expand
f(10) will return 42. The output of f(-10) is undefined, since variable a was not initialized.
In the second constructor of this task, we define what the input and output does the analysis class handle. In our case, the input is of type TChain, and as we will see later, the output is a TList.
UserCreateOutputObjects()
In our UserCreateOutputObjects function, we will define the output objects of our task. These are commonly histograms, profiles, etc. In our specific example, we will add one histogram, and define a list to which we will attach the histogram.
-
Output lists
Adding all your output histograms to a list makes your life easier: the list will allow you to manipulate many output objects simultaneously. By calling TList::SetOwner(true), we transfer ownership of all memory allocated by the list items to the TList itself, this means that in our destructor, we can simply call delete list to delete all our list items, rather than calling delete for all items individually.
+
Output lists
Adding all your output histograms to a list makes your life easier: the list will allow you to manipulate many output objects simultaneously. By calling TList::SetOwner(true), we transfer ownership of all memory allocated by the list items to the TList itself, this means that in our destructor, we can simply call delete list to delete all our list items, rather than calling delete for all items individually.
The implementation of the UserCreateOutputObjects method looks like this
...
@@ -1161,7 +1174,7 @@
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var gitbook = gitbook || [];
gitbook.push(function() {
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});
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var gitbook = gitbook || [];
gitbook.push(function() {
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});
All the code that you will find in ROOT, AliRoot and AliPhysics is written in the form of C++ classes. A class is a data type which is defined by the user, and allows for creating data members and functions specific for that class. By convention, each class in AliPhysics, AliRoot, and ROOT, is stored in its own header (.h) and implementation file, which have the same name as the class it defines (so later on, we will see that your analysis class, stored in a file 'AliAnalysisTaskMyTask', is called 'AliAnalysisTaskMyTask').
-
C++ .... ?
If you have never heard of classes (or C++), it might be a good idea to go through a C++ manual, an excellent one, with plenty of hands-on examples, can be found here: http://www.cplusplus.com/doc/tutorial/.
+
C++ .... ?
If you have never heard of classes (or C++), it might be a good idea to go through a C++ manual, an excellent one, with plenty of hands-on examples, can be found here: http://www.cplusplus.com/doc/tutorial/.
Classes are extended structures which contain both variables and functions (which are called methods) as members. Often, variables must be accessed through these methods. This might sound a bit abstract, but it becomes much more clear when you look at in a small code example:
class Rectangle
@@ -853,7 +866,7 @@
Inheritance
Classes are nice and important, because they can be derived from one-another (a feature called inheritance. Look at the figure below
In this figure, Rectangle is derived from base class Polygon, and inherits its members. If we want to define a second class, Triangle, which is also a polygon and will therefore have features in common with Rectangle, we can also derive it from base class Polygon. This avoids having to repeat common code for multiple which share features.
-
Beware
Classes are very powerful, but inheritance can sometimes make it tricky to understand how code is structured!
+
Beware
Classes are very powerful, but inheritance can sometimes make it tricky to understand how code is structured!
Let's take a look at how our classes would look like when we put them down as C++ code. First, we define out base class, the polygon
class Polygon
@@ -880,7 +893,7 @@
Inheritance
}
Again, width and height are defined in the base class Polygon, but also the Triangle class gets its own GetArea method. So now we have seen how inheritance makes our classes (and our life) simpler: by defining common functionality in a base class, we avoid repetition of code, which could easily lead to mistakes.
-
Example from AliPhysics - The AliMCEvent class
Inheritance is used widely in C++ code, and therefore also in AliROOT and AliPhysics. Take a look at the AliMCEvent class below
+
Example from AliPhysics - The AliMCEvent class
Inheritance is used widely in C++ code, and therefore also in AliROOT and AliPhysics. Take a look at the AliMCEvent class below
class AliMCEvent : public AliVEvent {
public:
....
@@ -890,7 +903,7 @@
Inheritance
Here AliMCEvent is derived from its base class AliVEvent, in the same way as the Triangle is derived from the base class Polygon. Classes such as AliESDEvent and AliAODEvent are also derived from AliVEvent, preventing a lot of boilerplate (i.e. needlessly repetitive) code.
-
Class headers ... ?
C++ classes are, in code bases, usually split into a header file (extention .h) and an implementation file (extension .cxx). A header file is generally used to define all of the functions, variables and constants contained in a class. There are multiple good reasons for splitting code into an implementation and a header - can you think of a few?
+
Class headers ... ?
C++ classes are, in code bases, usually split into a header file (extention .h) and an implementation file (extension .cxx). A header file is generally used to define all of the functions, variables and constants contained in a class. There are multiple good reasons for splitting code into an implementation and a header - can you think of a few?
AliAnalysisTaskSE
Now that you are an expert at C++ classes, you might wonder why classes are relevant to writing an analysis task. The reason is the following: in the AliPhysics analysis framework, all analysis tasks are derived from the same base class, called AliAnalysisTaskSE, where SE stands for 'single event'. This class in turn, is derived from the class AliAnalysisTask (if you are interested, you can go through the code and follow the full chain of inheritance).
@@ -913,7 +926,7 @@
Class constructors and destructorsare your class constructors and destructor. These are standard C++ features, that are called when you create or delete an instance of your class. We will later on see, why you need to define two different class constructors.
AliAnalysisTaskSE::UserCreateOutputObjects()
In this function, the user (i.e. the analyzer) can define the output objects of the analysis. These are e.g. histograms in which you store your physics results. These output objects can be attached to the output file(s) of the analysis.
-
Please note
When you are designing your class for your analysis, it (obviously) pays off to think about which output you need to extract the physics; do you want ten 1D histograms, or will four 2D histograms supply much more information? Or would you prefer writing certain information to a TTree, such that you have full information available when post-processing on your laptop? All these different output objects bring memory and size considerations, so choose well.
+
Please note
When you are designing your class for your analysis, it (obviously) pays off to think about which output you need to extract the physics; do you want ten 1D histograms, or will four 2D histograms supply much more information? Or would you prefer writing certain information to a TTree, such that you have full information available when post-processing on your laptop? All these different output objects bring memory and size considerations, so choose well.
AliAnalysisTaskSE::UserExec()
This function is called for each, single event over which your analysis task runs. This function is your 'event loop'. Examples of useful things to do in the UserExec() function:
@@ -922,7 +935,7 @@
AliAnalysisTaskSE::UserExec()
Access the physics objects specific to your analysis (e.g. the charged particles in this event, or find the highest momentum particle)
Fill the histograms or other output objects
-
Please note
If the function AliAnalysisTaskSE::SelectCollisionCandidates(UInt_t trigger_mask) is called before you launch your analysis, UserExec() will only be executed for events which pass the trigger selection that you have specified.
+
Please note
If the function AliAnalysisTaskSE::SelectCollisionCandidates(UInt_t trigger_mask) is called before you launch your analysis, UserExec() will only be executed for events which pass the trigger selection that you have specified.
AliAnalysisTaskSE::Terminate()
The Terminate function is called at the very end of the analysis, when all events in your input data have been analyzed. Often, you leave the Terminate function empty: usually it is more practical to write a small macro that performs post-processing on your analysis output files, rather than deferring this functionality to the Terminate function.
@@ -969,7 +982,7 @@
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Rule of thumb: all calls to new should be accompanied by a call to
+
new - delete
Rule of thumb: all calls to new should be accompanied by a call to
delete somewhere in your code
Destructors and PROOF
@@ -1018,7 +1031,7 @@
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});
Note that we will first test if our code is actually 'grid compatible', by simulating a Grid node on our computer. Before you launch this test, browse through the runAnalysis.C macro and try to convince yourself of the fact that you understand the logic, and whether or not the configuration makes sense.
Running a Grid test
-
AliEn-ROOT-Legacy tokens
In case you are using AliEn-ROOT-Legacy, for instance with ROOT5, then you should first create an access token using command alien-token-init.
+
AliEn-ROOT-Legacy tokens
In case you are using AliEn-ROOT-Legacy, for instance with ROOT5, then you should first create an access token using command alien-token-init.
If you think everything is OK, and run the Grid test by simply launching the runAnalysis macro
aliroot runAnalysis.C
@@ -923,7 +936,7 @@
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Risk losing your code because it's not part of AliPhysics and your hard drive crashes?
To avoid these headaches, users are encouraged to run their jobs in a more automated and efficient way by using the LEGO framework.
-
Why LEGO trains are crucial
A train can easily contain multiple instances of your analysis, meaning you can run your default configuration and in addition multiple cut variations and other cross-checks. The success rate of the jobs is EXACTLY the same for each of your configurations, as they are all handled in parallel. This means that the all the configurations handle the exact same set of data.
+
Why LEGO trains are crucial
A train can easily contain multiple instances of your analysis, meaning you can run your default configuration and in addition multiple cut variations and other cross-checks. The success rate of the jobs is EXACTLY the same for each of your configurations, as they are all handled in parallel. This means that the all the configurations handle the exact same set of data.
This is in contrast to submitting your jobs one after each other (possibly running into quota problems) and having random job crashes, resulting in a situation where your default configuration and the variations did not handle exactly the same set of data.
How does it work
@@ -854,14 +867,14 @@
How does it work
submit the train to the Grid
study the resource consumption of the train for each wagon (CPU usage, virtual and resident memory)
-
Note
The fact that the trains run on the Grid, requires that all code is contained in an AliEn package. Therefore, the train uses the regularly deployed AliPhysics "AN" tags, so you will have to make sure that your analysis code is available in AliPhysics.
+
Note
The fact that the trains run on the Grid, requires that all code is contained in an AliEn package. Therefore, the train uses the regularly deployed AliPhysics "AN" tags, so you will have to make sure that your analysis code is available in AliPhysics.
Within AliPhysics, your analysis code will be part of a shared library that contains many other analyses from your working group or analysis group. If you have never added a class to AliPhysics, ask your PWG or PAG coordinators for help.
By clicking on the top right 'help' tab, you will be guided to a webpage where it is explained in detail how you can join a LEGO train and perform a highly efficient analysis.
-
Join the LEGO trains!
Everyone is encouraged to use the LEGO train system for running analysis rather than running analysis by yourself on Grid. Not only will you benefit yourself, but by running trains that contain analyses of multiple users in one go, we conserve resources: the LEGO train has to only run on instance of AliPhysics to perform multiple analyses, and it has to only retrieve the input data once.
+
Join the LEGO trains!
Everyone is encouraged to use the LEGO train system for running analysis rather than running analysis by yourself on Grid. Not only will you benefit yourself, but by running trains that contain analyses of multiple users in one go, we conserve resources: the LEGO train has to only run on instance of AliPhysics to perform multiple analyses, and it has to only retrieve the input data once.
As a consequence: LEGO train jobs have higher priority in the job queues than user jobs! Furthermore, your analysis will always be reproducible, and you will receive a simple mail with a link to your final output file when your train run is done. So if you want to perform fast, safe, and efficient analysis: use the LEGO trains!
How to add your analysis task to the LEGO train system
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In this section, we will take a look at option 1: how to run on data that you have stored locally, on your own computer.
-
Please note
For practical purposes it is (nearly) impossible to process a whole dataset locally on your laptop, but launching a local test provides you with an environment to test your analysis task!
+
Please note
For practical purposes it is (nearly) impossible to process a whole dataset locally on your laptop, but launching a local test provides you with an environment to test your analysis task!
To run a local analysis, we need to
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ALICE uses MonALISA (Monitoring Agents using a Large Integrated Services Architecture) for monitoring and control of its Gird operations. The AliMonitor webpage, that we have seen in previous sections, provides us with access to the MonALISA services. In this section, we will cover some of these services.
-
VO registration
For full access to all MonALISA serivces, make sure that you have a valid certificate and ALICE VO registration!
+
VO registration
For full access to all MonALISA serivces, make sure that you have a valid certificate and ALICE VO registration!
Run numbers
In the previous section, we have seen that data that are stored are identified by their run number. If you want to look up which run numbers correspond to a given data taking period, go to ALIMONITOR and click on the tab 'Run Condition Table' (RCT).
@@ -845,7 +858,7 @@
Run numbers
To ensure that detector systems that you need to use in your analysis were functioning properly, you can check quality flags for all detector subsystems in the columns on the right-hand side of the table. The number '1' means that data taking was successful; to only display run numbers for which data quality is guaranteed for a given sub detector, type a '1' in the field of the first row of the table that corresponds to said detector (see the circle on the top right of the above picture).
If you scroll down, to the bottom of the table, you will see a button labeled: 'Show list of runs'. Clicking this button will open a pop-up window which lists the run numbers that are displayed in the table as a list of comma separated numbers. You can now easily copy these numbers into your steering macro, and add these run numbers to the analysis plugin.
-
Which data format to take?
You might note that, for all runs, data is stored in two distinct formats
+
Which data format to take?
You might note that, for all runs, data is stored in two distinct formats
AliESDs.root: event summary data
AliAOD.root: analysis object data
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When you run an analysis in test mode, a Grid environment is simulated locally for testing. Input data is downloaded from the file catalogue, following your configuration of the analysis plugin. After this, your analysis is executed. Running in test mode is an excellent way of convincing yourself that you have set up the plugin correctly.
Once your analysis test is finished, and you are convinced that your analysis output looks sane, you can submit your analysis to the Grid nodes. To do this, simply look at at the code snippet above, and assume that the variable gridTest is set to kFALSE.
-
Create AliEn legacy token!
Only ALICE members with a valid registration can submit jobs to the Grid and access the ALICE data. To identify yourself as an ALICE member, you will have to make sure that you have a valid token prior to launching your Grid jobs, be it in full or in test mode. If you are using AliEn legacy, then you need to obtain a token manually. If you are using JAliEn, then the token will be obtained automatically.
+
Create AliEn legacy token!
Only ALICE members with a valid registration can submit jobs to the Grid and access the ALICE data. To identify yourself as an ALICE member, you will have to make sure that you have a valid token prior to launching your Grid jobs, be it in full or in test mode. If you are using AliEn legacy, then you need to obtain a token manually. If you are using JAliEn, then the token will be obtained automatically.
$ alien-token-init <username>
if all is fine, you should be prompted for your password, and see something like
=> Trying to connect to Server [0] root://pcapiserv03.cern.ch:10000 as User <username>
@@ -946,7 +959,7 @@
Merging via JDL
mgr->SetRunMode("full");
This will prepare the plugin for writing merging jobs, when your analysis is done.
-
More than on merging stage?
By specifying
+
More than on merging stage?
By specifying
alienHandler->SetMaxMergeStages(1);
we tell the plugin that all output files can be merged in one go.
@@ -967,7 +980,7 @@
Merging via JDL
mgr->SetRunMode("terminate");
and running runAnalysis.C a final time. This will trigger downloading of the merged output files (the resulting files from the merging jobs) and a final 'local' merge of said files into one, single output file. When the process is done your high-statistics output files is ready - time to start writing a paper!
-
Merging is 'dumb'
Keep in mind: merging can be a memory-hungry process. During merging, all files that are to be merged are kept in random access memory. ROOT files tend to be heavily compressed when written to disk, so their size in RAM might be surprisingly large.
+
Merging is 'dumb'
Keep in mind: merging can be a memory-hungry process. During merging, all files that are to be merged are kept in random access memory. ROOT files tend to be heavily compressed when written to disk, so their size in RAM might be surprisingly large.
When your output files are large, or if you have a large number of output files to be merged, you might need to merge in multiple stages, to avoid running out of RAM!
@@ -1013,7 +1026,7 @@
No results matching "
var gitbook = gitbook || [];
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});
Use alienv list to list loaded modules. Use exit to exit this environment.
The module xjalienfs is now available, which is what we will use to get our data.
Get a valid token (optional)
-
JAliEn tokens
You can skip this step if you are using JAliEn. JAliEn clients create the token automatically, but you can still run alien-token-init to refresh it manually.
+
JAliEn tokens
You can skip this step if you are using JAliEn. JAliEn clients create the token automatically, but you can still run alien-token-init to refresh it manually.
The ALICE file catalogue is only accessible if you are an ALICE member.
If you are using AliEn-ROOT-Legacy or ROOT5, then you first need to authenticate yourself and obtain a token
@@ -958,7 +971,7 @@
Get a valid token (optional)
and copy the AliAOD.root file that is inside this folder to your local hard drive by doing
cp AliAOD.root file:.
Note the syntax of the copy command, here we tell to copy the remote file AliAOD.root to our own laptop by specifying file:. .
-
JAliEn and AliEn shell documentation
You can find more information about the alien.py shell at jalien.docs.cern.ch. Reference documentation for the legacy AliEn shell is available at alien.web.cern.ch.
+
JAliEn and AliEn shell documentation
You can find more information about the alien.py shell at jalien.docs.cern.ch. Reference documentation for the legacy AliEn shell is available at alien.web.cern.ch.
Trouble ?
If for some reason this does not work for you - no fear. You can ask a colleague to provide a file for you, or send a mail to our mailing lists if you are having trouble with access.
@@ -1005,7 +1018,7 @@
No results matching "
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gitbook.push(function() {
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});
In the second subsection of this tutorial, you saw that the streamer directives looked a bit different. This is, because we sometimes use member comments in header files for yet another purpose: creating automatic code documentation with Doxygen. Doxygen is a way of documenting your code inside the source code itself, by factoring special comments that will be ignored by the C++ compiler.
+
Streamers and doxygen
In the second subsection of this tutorial, you saw that the streamer directives looked a bit different. This is, because we sometimes use member comments in header files for yet another purpose: creating automatic code documentation with Doxygen. Doxygen is a way of documenting your code inside the source code itself, by factoring special comments that will be ignored by the C++ compiler.
Doxygen uses both //!< and ///< to introduce a data member comment. Until ROOT 5, this allowed using //!< for indicating a transient data member. ROOT 6 abruptly broke this compatibility and //!< does not mean transient anymore: we are now forced to use //!<! for introducing a Doxygen comment interpreted as transient in both ROOT 5 and ROOT 6.
Pitfalls
@@ -916,7 +929,7 @@
Pitfalls
in the empty I/O constructor (remember that we said in Section 3: you always need to specify an empty I/O constructor for your classes!)
Persistent members are read from the .root file
-
Example 1 - 'unexpected' behavior
Take a look at the class below
+
Example 1 - 'unexpected' behavior
Take a look at the class below
class SomeClass : public TObject
Int_t fAbsEta; //!// setter
@@ -930,9 +943,9 @@
Pitfalls
In your steering macro, you call
SomeClass->SetAbsEta(3);
You now launch your analysis to run on the Grid. What is the value of fAbsEta when the analysis starts to run at a Grid node?
-
Click to show answerClick to expand
After copying (e.g. to grid) the value of fAbsEta = 0. The member is not persistent (//!), so after copying, the value of fAbsEta will be equal to its default value as specified in the I/O constructor of your class.
+
Click to show answerClick to expand
After copying (e.g. to grid) the value of fAbsEta = 0. The member is not persistent (//!), so after copying, the value of fAbsEta will be equal to its default value as specified in the I/O constructor of your class.
-
Example 2 - expected behavior?
Now take a look at a second, very similar class:
+
Example 2 - expected behavior?
Now take a look at a second, very similar class:
class SomeClass : public TObject
Int_t fAbsEta; //// setter
@@ -946,7 +959,7 @@
Pitfalls
SomeClass->SetAbsEta(3);
And launch our analysis task on the Grid. What is the value of fAbsEta when your task starts to run on a Grid node?
-
Click to show answerClick to expand
After copying (e.g. to grid) fAbsEta = 3. The member is declared as persistent, so the value it has is retained.
+
Click to show answerClick to expand
After copying (e.g. to grid) fAbsEta = 3. The member is declared as persistent, so the value it has is retained.
So you see, that the streamer can have quite an important effect on your analysis!
Runtime
@@ -1058,7 +1071,7 @@
No results matching "
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"The ROOT streamer","level":"1.5.1.9","depth":3,"next":{"title":"Destructors","level":"1.5.1.10","depth":3,"path":"analysis/destructor.md","ref":"analysis/destructor.md","articles":[]},"previous":{"title":"Troubleshooting","level":"1.5.1.8","depth":3,"path":"analysis/trouble.md","ref":"analysis/trouble.md","articles":[]},"dir":"ltr"},"config":{"plugins":["katex","panels@git+https://github.com/lhcb/gitbook-plugin-panels.git#117012fdc18c96831cb88196980c0ea73b0c87b8","collapsible-menu","block-align","page-toc"],"styles":{"website":"css/website.css"},"pluginsConfig":{"collapsible-menu":{},"block-align":{},"search":{},"page-toc":{"position":"before-first","selector":".markdown-section h1, .markdown-section h2, .markdown-section h3, .markdown-section h4","showByDefault":true},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"panels":{},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2},"highlight":{},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":false}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"ALICE Analysis Tutorial","gitbook":"*","description":"Introduction to the common analysis techniques and tools of ALICE"},"file":{"path":"analysis/streamer.md","mtime":"2024-02-16T14:51:36.357Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2024-02-16T14:52:24.685Z"},"basePath":"..","book":{"language":""}});
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});
and by e.g. clicking on the 'stderr', we can check the error information of our job.
Mmm, so the job crashed with a segmentation violation, and if we remember correctly from our programming classes, we know that this points at illegal memory access ... so we had better go to our analysis code, and check our pointers ....
-
Can you spot the mistake?
Below, we see the UserCreateOutputObjects and a snippet of the UserExec() methods of the task that ran and segfaulted. What is wrong ?
+
Can you spot the mistake?
Below, we see the UserCreateOutputObjects and a snippet of the UserExec() methods of the task that ran and segfaulted. What is wrong ?
AliAnalysisTaskMyTask::UserCreateOutputObjects()
{
// create a new TList that OWNS its objects
@@ -886,7 +899,7 @@
Example: validation error
...
fHistPt->Fill(track->Pt());
-
Click to show answerClick to expand
We forgot to initialize the histogram that we try to fill: the pointer fHistPt has value NULL
+
Click to show answerClick to expand
We forgot to initialize the histogram that we try to fill: the pointer fHistPt has value NULL
Example: execution error
Let's take a look at another example. We are again running our jobs, but now we notice that subjobs of a given masterjob start to go into an 'Execution error' state.
@@ -963,7 +976,7 @@
No results matching "
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"Troubleshooting","level":"1.5.1.8","depth":3,"next":{"title":"The ROOT streamer","level":"1.5.1.9","depth":3,"path":"analysis/streamer.md","ref":"analysis/streamer.md","articles":[]},"previous":{"title":"Offline analysis database","level":"1.5.1.7","depth":3,"path":"analysis/oadb.md","ref":"analysis/oadb.md","articles":[]},"dir":"ltr"},"config":{"plugins":["katex","panels@git+https://github.com/lhcb/gitbook-plugin-panels.git#117012fdc18c96831cb88196980c0ea73b0c87b8","collapsible-menu","block-align","page-toc"],"styles":{"website":"css/website.css"},"pluginsConfig":{"collapsible-menu":{},"block-align":{},"search":{},"page-toc":{"position":"before-first","selector":".markdown-section h1, .markdown-section h2, .markdown-section h3, .markdown-section h4","showByDefault":true},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"panels":{},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2},"highlight":{},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":false}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"ALICE Analysis Tutorial","gitbook":"*","description":"Introduction to the common analysis techniques and tools of ALICE"},"file":{"path":"analysis/trouble.md","mtime":"2024-02-16T14:51:36.357Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2024-02-16T14:52:24.685Z"},"basePath":"..","book":{"language":""}});
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});
The alidist directory contains software recipes, telling aliBuild how the software is built. Your
alidist directory and your software source code are Git directories managed by you: you need
to keep them up-to-date manually.
-
Check names of your remote repositories
With older versions of aliBuild, the central remote repository (used for pulling updates) would be
+
Check names of your remote repositories
With older versions of aliBuild, the central remote repository (used for pulling updates) would be
called origin instead of the usual name upstream and the personal (fork) remote repository (used
for pushing changes) would be called <your-github-username> instead of the usual name origin.
Please check your settings using git remote -v and adjust the Git commands mentioned in
@@ -891,7 +904,7 @@
Source code and recipes
git fetch --all --tags
git checkout v5-09-42-01
-
Why manual updates?
Software downloaded under your working directory is your responsibility. Our tools will not take any
+
Why manual updates?
Software downloaded under your working directory is your responsibility. Our tools will not take any
action to update it: imagine if you lose important data because of an automatic update!
As a developer, and ALICE contributor, you must be capable of using and understanding git.
@@ -949,7 +962,7 @@
Build and rebuild
will not have to rerun it from scratch because of test failures like this.
Using the combinations above on CentOS 7 will make aliBuild automatically download the precompiled
binaries for almost all packages.
-
AliPhysics with ROOT 6 and the Grid
The command above will produce AliPhysics with ROOT 6 as a dependency. When using this version, you
+
AliPhysics with ROOT 6 and the Grid
The command above will produce AliPhysics with ROOT 6 as a dependency. When using this version, you
will only be able to submit Grid analysis jobs using ROOT 6-based builds (whose name ends with
_ROOT6). If you still need ROOT 5 only for submitting Grid jobs, there is no need to install it:
just use it from CVMFS by logging in to lxplus.cern.ch.
@@ -978,7 +991,7 @@
Rebuild existing installations
Replace <num-parallel-jobs> with a sensible number (e.g. slightly more than the actual number of
your cores).
-
You lied. aliBuild is rebuilding everything! 🤬
One or more of the following actions might change the way aliBuild sees and uses the dependencies
+
You lied. aliBuild is rebuilding everything! 🤬
One or more of the following actions might change the way aliBuild sees and uses the dependencies
and might result in a full (or nearly) rebuild. So, if an important conference is approaching
(well: it always does, doesn't it?) plan the following actions accordingly as they might increase
the build time:
@@ -1004,7 +1017,7 @@
Use your local software installat
loaded packages if you have doubts.
The alienv enter command drops you to a new shell. Unload the packages by simply exiting it with
the exit command.
-
I have several AliPhysics versions. Which one is AliPhysics/latest?
aliBuild will tell you exactly what you need to type in order to load the software you have just
+
I have several AliPhysics versions. Which one is AliPhysics/latest?
aliBuild will tell you exactly what you need to type in order to load the software you have just
built. Just use aliBuild's suggestion in place of AliPhysics/latest wherever appropriate: for
instance, if you have several AliPhysics versions, AliPhysics/latest will point to the version you
have built more recently, not the latest.
@@ -1024,7 +1037,7 @@
Run a single command in the env
it in the current shell:
Even if this is technically possible, it is strongly not recommended to load the environment with
+
🚫Do not load alienv automatically in your shell
Even if this is technically possible, it is strongly not recommended to load the environment with
alienv in your ~/.bashrc! You must keep your environment pristine for safely running
aliBuild. By not loading the environment automatically, you will avoid a huge source of errors.
Do you still find annoying to type alienv enter AliPhysics/latest every time you want to use it?
@@ -1085,7 +1098,7 @@
Build the s
alienv setenv AliPhysics/latest-aliroot6-o2 -c aliroot
The aliroot command will be run with the correct environment in both cases.
-
Migrating from ROOT 5 to ROOT 6
While you are at it, if you want to migrate your existing code to ROOT 6 (and make sure it works
+
Migrating from ROOT 5 to ROOT 6
While you are at it, if you want to migrate your existing code to ROOT 6 (and make sure it works
there) check out our migration guide.
Build specific releases (tags) of the software
@@ -1166,7 +1179,7 @@
No results matching "
+
@@ -1182,7 +1195,7 @@
No results matching "
var gitbook = gitbook || [];
gitbook.push(function() {
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Building software has become an increasingly complicated operation, as our software has many
dependencies and we expect it to work both on your laptop and on the Grid. In addition, we support
many Linux distributions and recent macOS versions.
-
Please follow the instructions closely!
Most of the paths and procedures presented here can be adapted to your system and your taste. You
+
Please follow the instructions closely!
Most of the paths and procedures presented here can be adapted to your system and your taste. You
can for instance decide to use different path names, or a different directory structure, it's up to
you, however we do not recommend you use different ways of installing the required
dependencies.
If your operating system is not in any list, it does not mean our software won't work on it;
it will be just more difficult for you to get support for it.
+
Only in case you cannot install aliBuild in the way described above, you can install aliBuild manually.
+This procedure should only be used as a fall-back, in case you cannot follow the instructions for your operating system linked above.
Configure aliBuild
-
After you are done installing alibuild you need to configure it by adding two
-following lines to your ~/.bashrc or ~/.bash_profile (depending on your
-configuration):
+
After you are done installing alibuild you need to configure it by adding the two
+following lines to your ~/.bashrc, ~/.bash_profile, ~/.zshrc or ~/.zprofile
+(depending on your operating system and configuration):
The first line tells what directory is used as "build cache", the second line installs a "shell
helper" that makes easier to run certain aliBuild-related commands.
@@ -899,41 +914,6 @@
Configure aliBuild
Note that this directory tends to grow in size over time, and it is the one you need to remove in
case of cleanups.
-
I don't have root permissions
-
In case you don't have root permissions, one of the possibilities is installing aliBuild under a
-user-owned directory. Start with opening your ~/.bashrc or ~/.bash_profile (this depends on your
-system), and add the following lines:
Now close all your terminals and reopen them to load the new configuration. Check if it works by
-printing the variable:
-
echo$PYTHONUSERBASE
-
-
The operations above need to be performed only once. Now, to install or upgrade aliBuild, just do:
-
pip install alibuild --upgrade --user
-
-
-
This time we did not specify sudo and we have added the --user option. The Python variable
-PYTHONUSERBASE tells pip where to install the package.
-
-
Verify you have aliBuild in your path:
-
type aliBuild
-
-
I need a special version of aliBuild
-
In some cases you might want to install a "release candidate" version, or you want to get the code
-directly from GitHub. By default, the last stable version is installed. Do not install a special
-version of aliBuild if you were not instructed to do so or if you don't know what you are doing, we
-provide no support for unstable releases!
-
To install a release candidate (for instance, v1.5.1rc3):
-
sudo pip install alibuild=v1.5.1rc3 --upgrade
-
-
To install from GitHub (you can specify a tag or a hash, or another branch, instead of master):
Do not forget to drop sudo and add --user in case you do not have root permissions!
-
Build the packages
When aliBuild is installed on your computer and your prerequisites are satisfied, you can move to
the next step.
@@ -983,7 +963,7 @@
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In the first instance, you should always follow the instructions for your operating system linked under "Prerequisites" here.
+This ensures that you only have a single installation of aliBuild, and that it is updated automatically with the rest of your system.
+
If you cannot follow the instructions linked above for any reason (such as if you are using a shared machine and you do not have administrative access), see below for alternative ways to install aliBuild.
+
If you follow these instructions, you are responsible for keeping aliBuild up to date manually.
+Please remember to update aliBuild before asking for support, as any issues you encounter may already be solved in the latest version.
+
I don't have root permissions
+
In case you don't have root permissions, one of the possibilities is installing aliBuild under a
+user-owned directory. Start with opening your ~/.bashrc, ~/.bash_profile, ~/.zshrc or ~/.zprofile
+(this depends on your system), and add the following line at the end:
+
export PATH="$HOME/.local/bin:$PATH"
+
+
Now close all your terminals and reopen them to load the new configuration.
+The operations above need to be performed only once. Now, to install or upgrade aliBuild, just do:
In some cases you might want to install a "release candidate" version, or you want to get the code
+directly from GitHub. By default, the last stable version is installed. Do not install a special
+version of aliBuild if you were not instructed to do so or if you don't know what you are doing, we
+provide no support for unstable releases!
+
First, remove any other copy of aliBuild installed on your system in any other way, to avoid conflicts.
+
To install a release candidate (for instance, v1.5.1rc3):
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Homebrew might sometimes install multiple versions of some packages, such as llvm or python. This can happen after you have used brew for a while.
+
Check installed package versions
Homebrew might sometimes install multiple versions of some packages, such as llvm or python. This can happen after you have used brew for a while.
Make sure you have only the currently-supported versions of packages installed, as listed in the dependencies of alisw/system-deps/o2-full-deps, paying particular attention to llvm and python.
You may have to run brew uninstall for package versions that are unsupported by ALICE, if they have ended up installed on your system.
@@ -932,7 +945,7 @@
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In order to run an analysis in the postprocessing mode one should run an analysis for every beam/energy combination and then use the rivet-merge script with the output files from the previous runs provided as parameters (check rivet-merge --help):
This will use the RAW histograms from you output files (check that your .yoda files contain them, they contain results from the analysis before the final scaling in the finalize method), merge them, and call finalize part of the analysis again on the merged histograms. Now, as all the histograms will be available, the finalize method will (in our case) create and fill R_AA histograms and save them to the output .yoda file containing final results.
-
Beware
There is no information about beam and energy when running rivet-merge script - this should be taken into account when implementing such an analysis. Also note, that an analysis with reentrant finalize should be validated to allow running in every mode, and so in the .info file it should be marked as: Status: REENTRANT
+
Beware
There is no information about beam and energy when running rivet-merge script - this should be taken into account when implementing such an analysis. Also note, that an analysis with reentrant finalize should be validated to allow running in every mode, and so in the .info file it should be marked as: Status: REENTRANT
A full example of an analysis with the reentrant finalize mode enabled is provided below:
// -*- C++ -*-
@@ -1122,7 +1135,7 @@
Postprocessing with reentrant fi
}
Event mixing
-
WARNING
This feature is still under development and its usage might change in the coming versions of Rivet. Description of this procedure was prepared for Rivet version 2.7.2.
+
WARNING
This feature is still under development and its usage might change in the coming versions of Rivet. Description of this procedure was prepared for Rivet version 2.7.2.
Event mixing is a procedure that enables to project out an event mixed of several events. In Rivet it is implemented in a form of a projection class called EventMixingProjection. It is based on a mixing observable provided as an input to define what should qualify as a mixable event, where the mixing observable can be defined as number of final state particles, centrality, event plane angle, etc. It contains a buffer that is filled with events over the runtime. This buffer can be used within an analysis to perform required operations. A declaration of an event mixing projection looks like this:
voidinit(){
@@ -1385,7 +1398,7 @@
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Coding conventions for Rivet plugins are different than those for AliRoot/AliPhysics!
+
Beware
Coding conventions for Rivet plugins are different than those for AliRoot/AliPhysics!
@@ -881,7 +894,7 @@
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initialisation (histograms an
addProjection(cfs, "CFS");
Here, we use the charged final state (with a rapidity cut) and will deal with the particle identification directly in the analysis code.
-
Note
This example did not use the ALICE::PrimaryParticles projection because it was implemented before this projection was introduced in Rivet. The selection of primary particles according to the ALICE definition is therefore done by hand, by looking at the particle ancestors. The code below could in principle be simplified by removing the large set of if statements if the ALICE::PrimaryParticles projection is used
+
Note
This example did not use the ALICE::PrimaryParticles projection because it was implemented before this projection was introduced in Rivet. The selection of primary particles according to the ALICE definition is therefore done by hand, by looking at the particle ancestors. The code below could in principle be simplified by removing the large set of if statements if the ALICE::PrimaryParticles projection is used
const ALICE::PrimaryParticles& aprim = apply<ALICE::PrimaryParticles>(event, "APRIM");
for (const Particle& p : aprim.particles()) {
...
@@ -1196,7 +1209,7 @@
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rivet -a ALICE_2010_S8625980 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc
where -a is used to specify the analysis you want to run (you can use any analysis that was distributed with Rivet). You can also list more than one analysis.
-
Beware
Beware the absence (!) of extension of your analysis name specified at the rivet command, i.e. no "rivet -a ALICE_2010_S8625980.cc ...". This would make your analysis not recognisable by Rivet, and it will complain so.
+
Beware
Beware the absence (!) of extension of your analysis name specified at the rivet command, i.e. no "rivet -a ALICE_2010_S8625980.cc ...". This would make your analysis not recognisable by Rivet, and it will complain so.
The command line above runs the analysis on the given input (~1000 generated events, here) and stores the produced output, typically histograms, in the file Rivet.yoda. Based on this yoda file, you can produce plots by running:
rivet-mkhtml Rivet.yoda
@@ -864,7 +877,7 @@
Using Rivet on lxplus
scp -r lxplus.cern.ch:<myRivetDir>/rivet-plots /tmp/myRivetPlots
open /tmp/myRivetPlots/index.html (on Mac OS X, otherwise point browser to file:///tmp/myRivetPlots/index.html)
-
N.B.
If on lxplus you use a directory under /tmp you have to copy from the exact host you are working on instead of lxplus.cern.ch, e.g. lxplus012.cern.ch. You can get actual name of the hosting machine with hostname.
+
N.B.
If on lxplus you use a directory under /tmp you have to copy from the exact host you are working on instead of lxplus.cern.ch, e.g. lxplus012.cern.ch. You can get actual name of the hosting machine with hostname.
We recommend not to use direclty the directory /tmp to avoid clashes with other user. Please use /tmp/ to follow this tutorial even if stated differently.
Running Rivet together with a generator
@@ -891,14 +904,14 @@
Running Rivet together with a g
rivet -a ALICE_2010_S8625980 /tmp/$USER/fifo_$UID.hepmc
rm /tmp/$USER/fifo_$UID.hepmc
-
Note
aligenmc is the script developed within ALICE that does the running of a chosen generator, with a dedicated configuration file, and writing the output to the specified file/FIFO.
+
Note
aligenmc is the script developed within ALICE that does the running of a chosen generator, with a dedicated configuration file, and writing the output to the specified file/FIFO.
For further instructions on how to run different generators, see:
aligenmc is not yet updated to generate heavy-ion collisions with the Pythia8/Angantyr model. In case you want to generate Pb-Pb collisions with Pythia8/Angantyr model you can
+
Pythia8/Angantyr
aligenmc is not yet updated to generate heavy-ion collisions with the Pythia8/Angantyr model. In case you want to generate Pb-Pb collisions with Pythia8/Angantyr model you can
Beware that this line is valid only for Pb-Pb 2.76 TeV collisions. Should you need to change the collision energy (the the beams), make sure you run only the initial part
@@ -948,7 +961,7 @@
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diff --git a/search_index.json b/search_index.json
index 86ab38ca..47a146bd 100644
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๏ธ","๐):","๐ช","๐ฆ","๐ซdo","๐ ","๐คฌone","๐งช","๐งน"],"pipeline":["stopWordFilter","stemmer"]},"store":{"./":{"url":"./","title":"Introduction","keywords":"","body":"Welcome to the ALICE Analysis Tutorial documentation\nThis is a community-contributed place where we collect all our documentation. Every ALICE member can\ncontribute, and the Analysis Tutorial Committee will review every contribution.\n\nAs a first step, you should make sure you are correctly registered as an ALICE user.\nThen you should head of to the section on how to build ALICE software.\nFinally you can dive in in the analysis framework documentation.\nIf you are looking for the old analysis tutorial using the old Run 2 framework, it can be found here.\n\nIf you would like to improve these pages you can have a look at the CONTRIBUTING documentation.\n"},"start/":{"url":"start/","title":"Getting started","keywords":"","body":"Getting started in ALICE\nAre you a registered ALICE member?\nUse this link to check if your CERN account is connected to ALICE. In\ncase you see a message saying that you are not an ALICE member, you need to fix the problem: many\nservices are not accessible if you are not considered an ALICE member.\nDrop an email to the ALICE Secretariat, they will help you: alice.secretariat@cern.ch\nDo you have access to lxplus?\nWhen you have a CERN account you can typically login to lxplus via SSH:\nssh USERNAME@lxplus.cern.ch\n\nIf, in spite of providing the correct password, you are not allowed to connect, go on your CERN\naccount management page. You need to Sign in and to select Resources\nand Services like in the picture below:\n\n\nThen click the big List Services button and check if the following services are enabled for you:\n\n\nYou need:\n\nLXPLUS and Linux\nAFS Workspaces\nEOS/CERNBox\n\nIn case some of them are missing, just click on the service to subscribe. For Linux, you may be\nrequested to provide a \"group\" and a \"reason\" for requesting the subscription.\n\nGroup: z2 (it corresponds to ALICE)\nReason: just type something like \"new ALICE member\", it's enough\n\nIt will take at least two full working hours before you will be able to use the services\nUsing the Grid: get a certificate\nThe procedure for getting or renewing a certificate is illustrated here.\nRequesting support\nThere are different ways to request support in ALICE. For simple requests concerning Run 2 software\nthere are two mailing lists:\n\nGeneral questions on analysis, build problems, etc.: alice-project-analysis-task-force@cern.ch\nProblems with jobs submission, certificates, trains: alice-analysis-operations@cern.ch\n\nYou can self-subscribe to them if you are an ALICE member. Go\nto the CERN egroups page, search for the group name, click on it and then\nyou will be presented with an option to subscribe. You can unsubscribe using the same procedure.\nSupport for Run 3 does not rely on mailing lists. We are using Discourse:\n\nALICE Talk\n\nWe also use Mattermost for direct messages or public groups (seek support in the Town Square)\n\nThe ALICE Mattermost team\n\nFor reporting actual bugs and track progress of important development, we use\nJira:\n\nThe ALICE Jira\n\n"},"start/cert.html":{"url":"start/cert.html","title":"Get a Grid certificate","keywords":"","body":"Get a Grid certificate\nWe will illustrate how to get, renew, register and prepare your digital certificates to use the\nALICE Grid services.\nObtain a digital certificate\nYour home institute may provide you with a digital certificate. However, we reccommend you get one\nfrom CERN, because the procedure is very easy and automated when you have a CERN account.\n\nGenerate a new CERN Grid User\n certificate\n\nYou will be asked whether you want to protect your certificate with a password. Note that in most\ncases you will not be allowed to import the certificate if you don't specify a password, so please\nprotect it with a password.\nโ ๏ธ This is not your CERN password. Use a new, arbitrary one.\nProceed until you get a message saying that your certificate is ready to be downloaded: click on it\nand a file called myCertificate.p12 will be downloaded.\nRegister your certificate in your browser\nThere are several ways to add your newly downloaded certificate to your browser, and they depend on\nthe browser and the operating system. We will focus on Firefox as an example.\nOpen Firefox, go to the Preferences, select Privacy and security on the left hand menu.\nScroll the settings page to the bottom and click on the Show certificates... button.\nA new window will open: click the Personal certificates tab. Click Import... and select the\nmyCertificate.p12 file you have just generated. Type the password you have used in the\nprevious step (this is not your CERN password).\nYour newly imported certificate will appear in the list.\nAdd the CERN Grid certificates to your browser\nIn case you navigate to an ALICE HTTPS site and you get a security warning, it is probably because\nyour browser does not have any means to recognize the site as valid.\nโ ๏ธ Most people ignore security exceptions. Do not do that, ever. This is bad, very bad. Someone\ncan steal your data. For real. Without you knowing it.\nGo to this site, there are two links at\nthe bottom of the page saying \"CERN Root/Grid Certification Authority\", etc.: with Firefox as your\nbrowser, click on both of them, and Firefox will ask you if you want to \"trust\" them: say \"yes\" to\nall questions.\nTest your browser setup\nNavigate to the ALICE Grid monitoring page. If you have your personal\ncertificate installed, and the CERN Grid certificates installed as well, Firefox should ask you to\nselect a certificate to be used to authenticate to the site.\nIn case you have many, select the one that identifies you (it should have your full name somewhere)\nissued by the CERN Grid Certification Authority, and tell Firefox to remember it.\nYou should be able to see the page without further ado. Next to the address bar, a green lock icon\nshould appear. If you see broken locks, red icons, warnings of various kinds, then there is some\nkind of security problem and you should repeat the steps above.\nRegister your certificate to the ALICE Grid\nThis operation needs to be performed only once. With Firefox, click on this\nlink and follow the guided procedure, after having selected\nyour personal certificate for authenticating.\nWhen the registration to the VO is successful, you will receive an email informing you. The\nregistration procedure does not involve any modification or re-download of your current certificate.\nIn case you are not receiving this email, you might want to ping Latchezar Betev:\n\n\n\nConvert your certificate for using the Grid tools\nKeep at hand the myCertificate.p12 file you have previously downloaded. You need to convert it\ninto two files (a \"certificate\" and a \"key\") in order to use the ALICE Grid services from the\ncommand line.\nYou will export your certificates to the following directory:\n~/.globus\nNow export the certificate with the following command (you will be prompted for the export\npassword you have selected when you have generated it):\nopenssl pkcs12 -clcerts -nokeys -in ~/Downloads/myCertificate.p12 -out ~/.globus/usercert.pem\n\nThe result will be a file called usercert.pem in your ~/.globus directory. Note that\nyour input file ending with .p12 may have a different name and may be stored in a different\nlocation.\nTime to export the private key:\nopenssl pkcs12 -nocerts -in ~/Downloads/myCertificate.p12 -out ~/.globus/userkey.pem\nchmod 0400 ~/.globus/userkey.pem\n\nWhen it says:\nEnter Import Password:\nyou should provide it with the export password you have entered when you generated it. The next\nquestion will be:\nEnter PEM pass phrase:\nYou should provide it with another password that will be used to protect the private key. You can\nuse the same password as before if you want, but please do not use your CERN password (yes, we\nare stressing this point a lot). This question will be asked twice for confirmation.\nTest your certificate\nYour certificate will be available to the ALICE Grid command line client.\nEnter your ALICE environment and create a \"temporary access token\":\nalienv enter AliPhysics/latest\nalien-token-destroy\nalien-token-init YOUR_ALIEN_USERNAME\n\nโ ๏ธ This assumes you have completed your installation. You do not have\neither alienv or the alien-token-* commands available in case you have never done it.\nThe alien-token-init command will ask you for a password. This is the last password you have used\nwhen you have converted your .p12 certificate into two .pem files.\n Creating JAliEn and AliEn tokensNote that the new JAliEn Grid clients automatically create tokens, while AliEn-ROOT-Legacy (ROOT5) requires running alien-token-init manually.\nThere is alien-token-init for JAliEn, and you can use it to test your credentials or (re)create tokens manually.\n\n"},"building/":{"url":"building/","title":"Build ALICE software","keywords":"","body":"Build ALICE software\nALICE software can be build using officially supported tool called aliBuild:\n๐งช Install ALICE software with alibuild\nThis tool provides users with a way to build the ALICE software directly on their system. On CC7\nyou will benefit from precompiled binaries which will make you save plenty of time. This method\nworks on any modern Linux distribution and macOS.\n"},"building/custom.html":{"url":"building/custom.html","title":"๐งช Installation via alibuild","keywords":"","body":"๐งช Installation via alibuild\nBuilding software has become an increasingly complicated operation, as our software has many\ndependencies and we expect it to work both on your laptop and on the Grid. In addition, we support\nmany Linux distributions and recent macOS versions.\n Please follow the instructions closely!Most of the paths and procedures presented here can be adapted to your system and your taste. You\ncan for instance decide to use different path names, or a different directory structure, it's up to\nyou, however we do not recommend you use different ways of installing the required\ndependencies.\nIn case you do not have particular needs, or you don't know what you are doing, please follow the\nprocedure very carefully and without diverging from it at all.\nThis will make support easier in case something does not work as expected.\n\naliBuild\nALICE uses aliBuild to build software. aliBuild:\n\nknows how to build software via per-package recipes,\nmanages the dependencies consistently,\nrebuilds only what's necessary,\nallows several versions of the same software to be installed at the same time.\n\nOperating systems we support\nAs per policy, the primary supported platform is CERN\nCentOS 7:\nthis is also our official deployment platform for Run 3 software.\nOther operating systems, such as macOS, are supported as development platforms and on a\nbest-effort basis.\nPrerequisites\nAccording to your operating system, please follow the prerequisites below. You will find a list of\npackages to install and configurations to perform.\nPrimary supported platform:\n\nCentOS 7\nCentOS/AlmaLinux 8\nAlmaLinux 9\n\nPlatforms supported on a best-effort basis:\n\nmacOS Ventura (13.0)\nUbuntu (20.04 LTS, 22.04 LTS)\nFedora\nLinux Mint\nFollow the instructions for the Ubuntu version your Linux Mint version is based on.\nSpecify the corresponding Ubuntu architecture when running the aliBuild command\nusing the -a option (e.g. -a ubuntu2004_x86-64 for Ubuntu 20.04).\nUse the -a option also with the alienv command.\n\n\n\nIf your operating system is not in any list, it does not mean our software won't work on it;\nit will be just more difficult for you to get support for it.\nConfigure aliBuild\nAfter you are done installing alibuild you need to configure it by adding two\nfollowing lines to your ~/.bashrc or ~/.bash_profile (depending on your\nconfiguration):\nexport ALIBUILD_WORK_DIR=\"$HOME/alice/sw\"\neval \"`alienv shell-helper`\"\n\nThe first line tells what directory is used as \"build cache\", the second line installs a \"shell\nhelper\" that makes easier to run certain aliBuild-related commands.\nYou need to close and reopen your terminal for the change to be effective. The directory\n~/alice/sw will be created the first time you run aliBuild.\n\nNote that this directory tends to grow in size over time, and it is the one you need to remove in\ncase of cleanups.\n\nI don't have root permissions\nIn case you don't have root permissions, one of the possibilities is installing aliBuild under a\nuser-owned directory. Start with opening your ~/.bashrc or ~/.bash_profile (this depends on your\nsystem), and add the following lines:\nexport PYTHONUSERBASE=\"$HOME/user_python\"\nexport PATH=\"$PYTHONUSERBASE/bin:$PATH\"\n\nNow close all your terminals and reopen them to load the new configuration. Check if it works by\nprinting the variable:\necho $PYTHONUSERBASE\n\nThe operations above need to be performed only once. Now, to install or upgrade aliBuild, just do:\npip install alibuild --upgrade --user\n\n\nThis time we did not specify sudo and we have added the --user option. The Python variable\nPYTHONUSERBASE tells pip where to install the package.\n\nVerify you have aliBuild in your path:\ntype aliBuild\n\nI need a special version of aliBuild\nIn some cases you might want to install a \"release candidate\" version, or you want to get the code\ndirectly from GitHub. By default, the last stable version is installed. Do not install a special\nversion of aliBuild if you were not instructed to do so or if you don't know what you are doing, we\nprovide no support for unstable releases!\nTo install a release candidate (for instance, v1.5.1rc3):\nsudo pip install alibuild=v1.5.1rc3 --upgrade\n\nTo install from GitHub (you can specify a tag or a hash, or another branch, instead of master):\nsudo pip install git+https://github.com/alisw/alibuild@master --upgrade\n\n\nDo not forget to drop sudo and add --user in case you do not have root permissions!\n\nBuild the packages\nWhen aliBuild is installed on your computer and your prerequisites are satisfied, you can move to\nthe next step.\n\n๐ Build the packages\n\n"},"building/prereq-centos7.html":{"url":"building/prereq-centos7.html","title":"Prerequisites for CentOS 7","keywords":"","body":"aliBuild Prerequisites for CentOS 7\nFor ALICE O2, CERN CentOS 7 (CC7)is the officialy supported target platform. Since CC7 is CentOS 7 with additional CERN packages, instructions apply to vanilla CentOS 7 as well.\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps \nyum update -y\nyum install -y alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-centos8.html":{"url":"building/prereq-centos8.html","title":"Prerequisites for CentOS 8","keywords":"","body":"aliBuild Prerequisites for CentOS 8\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\n\nyum install -y epel-release\nyum install -y dnf-plugins-core\nyum config-manager --set-enabled powertools\nyum update -y\n\ndnf group install -y \"Development Tools\"\n\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_el8.x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-alma9.html":{"url":"building/prereq-alma9.html","title":"Prerequisites for Alma 9","keywords":"","body":"aliBuild Prerequisites for Alma 9\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\n\ndnf install -y epel-release dnf-plugins-core\ndnf update -y\ndnf config-manager --set-enabled crb\ndnf group install -y 'Development Tools'\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_el9.x86-64/\nenabled=1\ngpgcheck=0\nEOF\ndnf update -y\ndnf install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-macos.html":{"url":"building/prereq-macos.html","title":"Prerequisites for macOS","keywords":"","body":"aliBuild prerequisites for macOS\nALICE software on macOS is supported on a best effort basis. Even though we systematically check macOS builds there is no guarantee that software builds or runs correctly. Support requests might have low priority. That said, we were able to successfully build on:\n\nVentura (13.0) on x86, M1 and M2\nSonoma (14.0) on x86, M1 and M2\n\nGet Xcode\nXcode bundles the necessary tools to build software in the apple ecosystem including compilers, build systems and version control.\n\nDownload it from the App Store\nOpen once installed. It will ask to install additional components - approve the action.\nOpen a terminal (Applicaions>Utilities>Terminal) and install the command line tools using:sudo xcode-select --install\n\n\napprove the license conditions bysudo xcodebuild -license\n\n\n\nGet Homebrew\nHomebrew is a command-line package manager for macOS used to install software packages similar to yum on CentOS or apt on Ubuntu.\n\nInstall Homebrew using the instructions on their webpage.\nOnce installed detect any problems regarding Homebrew and your system usingbrew doctor\n\n\n\nUninstall ROOT\nIf you have an existing ROOT installation on your system, this will interfere with the aliBuild installation, and will cause difficult-to-debug compilation errors.\nPlease uninstall any existing copy of ROOT on your system.\nThe uninstallation method depends on how you installed it.\nFor example, if you originally installed ROOT using Homebrew, you should uninstall it using brew uninstall root.\nAfter uninstalling ROOT, remove any reference to ROOT from your .zprofile, .zshrc and any other shell configuration files.\nThen close and re-open your terminal window.\nInstall the required packages\nNote that Homebrew does not run as root. Do not prepend sudo to any of the following commands.\n\nInstall the prerequisites and aliBuild via:brew install alisw/system-deps/o2-full-deps alisw/system-deps/alibuild\n\n\nSet up Homebrew in your shell by running the following command:echo 'eval \"$(/opt/homebrew/bin/brew shellenv)\"' >> ~/.zprofile\n\n\nClose Terminal and reopen it to apply changes.\n\n Check installed package versionsHomebrew might sometimes install multiple versions of some packages, such as llvm or python. This can happen after you have used brew for a while.\nMake sure you have only the currently-supported versions of packages installed, as listed in the dependencies of alisw/system-deps/o2-full-deps, paying particular attention to llvm and python.\nYou may have to run brew uninstall for package versions that are unsupported by ALICE, if they have ended up installed on your system.\n\n(Recommended) Exclude your work directory from Spotlight\nThe mac search engine (Spotlight) will be indexing the build directory which can have severe effects on your system performance. To avoid that, you can exclude your working directory (we are assuming ~/alice - create if not yet existing).\nGo to (Apple) menu>System preferences>Spotlight. In the Privacy tab, hit the + button. Now select the ~/alice directory and confirm.\nYou are now ready for installing aliBuild and start building ALICE software\nTroubleshooting:\nSome users have reported that homebrew commands might terminate with an error. The solution oddly enough seems to be to execute the above command multiple times until brew does not complain anymore.\nIf you have just upgraded your Xcode or macOS, you should run brew reinstall instead, in order to force the reinstallation of already installed packages. You also might want to run brew cleanup at the end to free up some space.\n"},"building/prereq-ubuntu.html":{"url":"building/prereq-ubuntu.html","title":"Prerequisites for Ubuntu","keywords":"","body":"aliBuild prerequisites for Ubuntu\nALICE software on Ubuntu is supported on a best effort basis. There is no guarantee that software builds or runs correctly. Support requests might have low priority. We were able to successfully build on:\n\nUbuntu 18.04 LTS\nUbuntu 20.04 LTS\nUbuntu 22.04 LTS\n\nInstall required system packages\nWith root permissions, i.e. sudo, update your package sources:\nsudo apt update -y\n\nWith root permissions, i.e. sudo, install the following packages:\nsudo apt install -y curl libcurl4-gnutls-dev build-essential gfortran libmysqlclient-dev xorg-dev libglu1-mesa-dev libfftw3-dev libxml2-dev git unzip autoconf automake autopoint texinfo gettext libtool libtool-bin pkg-config bison flex libperl-dev libbz2-dev swig liblzma-dev libnanomsg-dev rsync lsb-release environment-modules libglfw3-dev libtbb-dev python3-dev python3-venv python3-pip graphviz libncurses-dev software-properties-common gtk-doc-tools\n\nInstalling aliBuild\nAliBuild, our build tool, is installed as a standard ubuntu package, provided you enable the alisw PPA repository.\nThis is done with:\nsudo add-apt-repository ppa:alisw/ppa \nsudo apt update\nsudo apt install python3-alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-fedora.html":{"url":"building/prereq-fedora.html","title":"Prerequisites for Fedora","keywords":"","body":"aliBuild prerequisites for Fedora\nALICE software on Fedora is supported on a best effort basis. There is no guarantee that software builds or runs correctly. Support requests might have low priority.\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\nyum install -y epel-release\nyum install -y dnf-plugins-core\nyum config-manager --set-enabled powertools\nyum update -y\n\ndnf group install -y \"Development Tools\"\n\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_fedora.x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/build.html":{"url":"building/build.html","title":"๐ Build the packages","keywords":"","body":"๐ Build the packages\nALICE software has several dependencies: aliBuild takes care of downloading them for you. aliBuild\nwill also automatically download precompiled binaries on supported versions of CentOS/Alma and Ubuntu.\naliBuild will download and compile all the dependencies caching data under $ALIBUILD_WORK_DIR. You\nwill never need to access this directory. The source code for the packages you will actually develop\nwill be stored elsewhere.\nIn the following example, we will assume that you need to download AliRoot/AliPhysics for developing\nRun 2 software, and O2/O2Physics for Run 3.\nPrepare your source code\nWe assume your work area is ~/alice.\nSo, first off, create the directory and move to it:\nmkdir -p ~/alice\ncd ~/alice\n\nIf you want to develop analysis code, download AliPhysics:\naliBuild init AliPhysics@master\n\nOnly if you need to develop the Run 2 core software (unlikely), download AliRoot:\naliBuild init AliRoot@master\n\nIf you need to develop for Run 3, download O2Physics:\naliBuild init O2Physics@master\n\nOnly if you need to develop the Run 3 core software (unlikely), download O2:\naliBuild init O2@dev\n\nSource code and recipes\nIf you perform ls under your work directory, you will see the packages you have downloaded via\naliBuild init, plus an alidist directory.\nThe alidist directory contains software recipes, telling aliBuild how the software is built. Your\nalidist directory and your software source code are Git directories managed by you: you need\nto keep them up-to-date manually.\n Check names of your remote repositoriesWith older versions of aliBuild, the central remote repository (used for pulling updates) would be\ncalled origin instead of the usual name upstream and the personal (fork) remote repository (used\nfor pushing changes) would be called instead of the usual name origin.\nPlease check your settings using git remote -v and adjust the Git commands mentioned in\nthe following instructions accordingly, if needed.\n\nUpdate your software by cding into its directory and running:\n# use dev instead of master for O2\ngit checkout master\ngit pull --rebase upstream master\n\nThis will work in most cases and will keep your changes. It will also complain if there is some\nconflict you need to solve manually. You also have the nuclear option, to be used if you are sure\nyou do not have any important data:\n# use dev instead of master for O2\ngit checkout master\ngit fetch --all\ngit reset --hard upstream/master\n\nInstead of resetting to the current upstream version, you may want to download specific versions of\nthe software:\ncd ~/alice/AliPhysics\ngit fetch --all --tags\ngit checkout v5-09-42-01\n\n Why manual updates?Software downloaded under your working directory is your responsibility. Our tools will not take any\naction to update it: imagine if you lose important data because of an automatic update!\nAs a developer, and ALICE contributor, you must be capable of using and understanding git.\n\nCheck your prerequisites\naliBuild comes with the command aliDoctor that will help you identifying if your prerequisites\nwere installed correctly. In general, aliBuild is capable of building all required software\ndependencies, but it has also the ability to take them \"from the system\" if possible, resulting in\nless time spent for building for you.\nRun the aliDoctor command to check dependencies for Run 2 software:\ncd ~/alice\naliDoctor AliPhysics\n\nFor Run 2 software based on ROOT 6 (note: this is the only option on macOS):\ncd ~/alice\naliDoctor AliPhysics\n\nFor Run 3 software:\ncd ~/alice\naliDoctor O2Physics\n\naliDoctor will warn you that some packages have to be built as they could not be found from the\nsystem. If you have followed the instructions, this list should contain nothing more than:\n\nboost\nCMake\nGSL\nnanomsg\nprotobuf\nflatbuffers\nVc\nyaml-cpp\nZeroMQ\nSWIG\n\nIn particular, you should never have Python or Python-modules. If the output is longer than this\nlist, please go through the prerequisites once again and run aliDoctor again. If the output\ncontains those packages, or less packages, then you are fine and you may continue.\n\nIf you think a package is shown but should not be in the list because you are sure you have\ninstalled it, it might just be that its version it's incompatible (this frequently happens with\nCMake) or you are missing the \"development\" package for that component.\n\nBuild and rebuild\nYou can build the whole Run 2 software stack based on ROOT 6 with:\ncd ~/alice\naliBuild build AliPhysics\nSimilarly, for O2Physics:\ncd ~/alice\naliBuild build O2Physics\nIf you want to build O2 and run the tests as well (same way as they are run on the pull request\ncheckers), with --debug to see the full output:\ncd ~/alice\naliBuild build O2 --debug -e ALIBUILD_O2_TESTS=1\nโ ๏ธ It is recommended to run the first O2 build without the tests enabled to let it complete. You\nwill not have to rerun it from scratch because of test failures like this.\nUsing the combinations above on CentOS 7 will make aliBuild automatically download the precompiled \nbinaries for almost all packages.\n AliPhysics with ROOT 6 and the GridThe command above will produce AliPhysics with ROOT 6 as a dependency. When using this version, you\nwill only be able to submit Grid analysis jobs using ROOT 6-based builds (whose name ends with\n_ROOT6). If you still need ROOT 5 only for submitting Grid jobs, there is no need to install it:\njust use it from CVMFS by logging in to lxplus.cern.ch.\n\nOther build options\nThe options above are suitable for a CentOS 7 installation, since precompiled binaries\nwill be downloaded. You also have other installation options according to your needs: it is not\nguaranteed that cached binaries are available for the following options, but they may be faster to\nbuild.\nBuild AliPhysics based on ROOT 5 (legacy):\naliBuild build AliPhysics --defaults user # without GEANT 3, GEANT 4, DPMJET\naliBuild build AliPhysics --defaults release # full ROOT 5 stack\n\nโ ๏ธ ROOT 5 does not work on macOS. Use a ROOT 6 version compatible with ROOT 5 if you really need it\n(see below).\n\nRebuild existing installations\nAs a general rule, your existing installation can be smartly rebuilt by using the exact same\naliBuild build command as you did the first time. aliBuild will not rebuild existing software and\nit will simply rebuild the changes.\nYou may find it fast to skip the aliBuild part completely. You can simply move to the build\ndirectory and run make (the alienv part is explained\nlater):\ncd $ALIBUILD_WORK_DIR/BUILD/AliPhysics-latest/AliPhysics\nalienv setenv GCC-Toolchain/latest -c cmake --build . -- -j install\n\nReplace with a sensible number (e.g. slightly more than the actual number of\nyour cores).\n You lied. aliBuild is rebuilding everything! ๐คฌOne or more of the following actions might change the way aliBuild sees and uses the dependencies\nand might result in a full (or nearly) rebuild. So, if an important conference is approaching\n(well: it always does, doesn't it?) plan the following actions accordingly as they might increase\nthe build time:\n\nUpdating recipes in alidist\nRemoving the cache $ALIBUILD_WORK_DIR or forgetting to export the variable\nAdding or removing system dependencies as seen by aliDoctor\nUpdating your operating system or compilers (including Xcode on macOS)\n\n\nUse your local software installations\nYou will not find the packages you have built immediately available on your shell: we provide a tool\ncalled alienv that configures your shell according to the packages you want to load. alienv is\ncapable of switching between different versions of the same package without a hassle.\nList your available packages with:\nalienv q\n\nLoad the latest version you have built of a package (AliPhysics for instance):\nalienv enter AliPhysics/latest\n\nโ ๏ธ Dependencies are loaded automatically. Do not attempt to load AliRoot and ROOT as well, you will\nfind them automatically in the environment! alienv enter is verbose and will inform you about the\nloaded packages if you have doubts.\nThe alienv enter command drops you to a new shell. Unload the packages by simply exiting it with\nthe exit command.\n I have several AliPhysics versions. Which one is AliPhysics/latest?aliBuild will tell you exactly what you need to type in order to load the software you have just\nbuilt. Just use aliBuild's suggestion in place of AliPhysics/latest wherever appropriate: for\ninstance, if you have several AliPhysics versions, AliPhysics/latest will point to the version you\nhave built more recently, not the latest.\n\nLoad environment in the current shell or script\nIf you know what you are doing, you can also load the environment in your current shell, and\nsubsequently unload it (this is not recommended):\nalienv load AliPhysics/latest\nalienv unload AliPhysics/latest\n\nIf you want to load the environment inside a script you are developing, just add this line (works\nwith Bash scripts):\nsource $(alienv printenv AliPhysics/latest)\n\nRun a single command in the environment\nYou can also run a single command (for instance, aliroot) in the given environment without loading\nit in the current shell:\nalienv setenv AliPhysics/latest -c aliroot myMacro.C+\n\n ๐ซDo not load alienv automatically in your shellEven if this is technically possible, it is strongly not recommended to load the environment with\nalienv in your ~/.bashrc! You must keep your environment pristine for safely running\naliBuild. By not loading the environment automatically, you will avoid a huge source of errors.\nDo you still find annoying to type alienv enter AliPhysics/latest every time you want to use it?\nYou can add the following line in your ~/.bashrc to make it more convenient:\nalias ali='alienv enter AliPhysics/latest'\n\nYou are creating an alias called ali, that will load the environment by just typing it at the\nprompt. Of course you can name it any way you want.\n\nSpecial build needs\nRead below if you have some advanced requirements for your local installation.\nBuild by using less resources\nBuilding takes by default all the available CPU and most of the memory of your computer,\nconsiderably slowing down your work. In some cases you may want to reduce the number of cores\navailable to aliBuild by using the -j option:\naliBuild build AliPhysics -j 1\n\nDo not use the cache on CentOS 7\naliBuild will attempt to fetch the precompiled binaries automatically\non CentOS 7: no need to specify extra options.\nIf you want not to use them for some reason, it is important you follow the CentOS 7\nprerequisites first: this will allow aliBuild to take as many packages as\npossible from the system. You will then need to add the --always-prefer-system option to the\naliBuild build command. For instance:\naliBuild build AliPhysics --always-prefer-system\n\nBuild the same source multiple times with different options\naliBuild and alienv give you the ability to build the same development source with different\ndefaults without duplicating the source, and without conflicts.\nImagine we are under ~/alice and we have cloned AliRoot and AliPhysics with the aliBuild init\ncommand above. We build AliPhysics twice, once with ROOT 5 and a second time against ROOT 6.\nLet's first build AliPhysics with ROOT 5:\naliBuild build AliPhysics --defaults user -z aliroot5\n\nโ ๏ธ Note the -z aliroot5 command; it is assigning a nickname to the build for distinguishing it\nmore easily when using it.\nThe command ends with a message saying what to do to use the package:\nalienv enter AliPhysics/latest-aliroot5-user\n\n\nLet's now build the same AliPhysics with ROOT 6:\naliBuild build AliPhysics -z aliroot6\n\nNow, the message tells us to type:\nalienv enter AliPhysics/latest-aliroot6-o2\n\nKeep in mind that:\n\naliBuild always tells you what is the package name to load at the end of the build\nyou can load the two environments separately, in two different shells, with no chance of a mixup\nyou have used the same set of sources for generating two distinct builds\nalienv enter AliPhysics/latest will load the latest you have built, which can either be the\nROOT 5 or ROOT 6-based version: given its ambiguity, do use explicit names instead\n\nIt is also possible to directly run aliroot (or any command you want) without \"entering\" the\nenvironment:\nalienv setenv AliPhysics/latest-aliroot5-user -c aliroot\nalienv setenv AliPhysics/latest-aliroot6-o2 -c aliroot\n\nThe aliroot command will be run with the correct environment in both cases.\n Migrating from ROOT 5 to ROOT 6While you are at it, if you want to migrate your existing code to ROOT 6 (and make sure it works\nthere) check out our migration guide.\n\nBuild specific releases (tags) of the software\nIt might come useful to build a certain tag of AliRoot and AliPhysics instead of simply pulling the\nmaster.\n\nNote that we only guarantee that the current AliPhysics master works against the latest AliRoot\ntag! It is therefore possible (though a rare occurrence) that the current AliRoot master breaks\nthe current AliPhysics master.\n\nIf you have your source code in \"development mode\" (i.e. downloaded locally by means of aliBuild\ninit), since your AliRoot/AliPhysics/O2 directories are mere Git\nrepositories, you simply need to cd into them and\ncheckout the Git version you want.\nFor instance, if you want to build AliPhysics against AliRoot v5-09-33, you would need to first\nmove to the AliRoot directory and check the version out:\ncd ~/alice/AliRoot\ngit fetch upstream --tags\ngit checkout v5-09-33\n\nThen update your AliPhysics master:\ncd ~/alice/AliPhysics\ngit checkout master\ngit pull --rebase upstream master\n\nand then build normally using the aliBuild command. You might want to build using different -z\noptions as explained here in order\nto have different builds usable in parallel without duplicating your source code.\n๐งน Delete obsolete builds\nWith frequent rebuilding of packages, obsolete builds can pile up and occupy a lot of precious\ndisk space.\nBasic cleanup\nThe simplest way to get rid of obsolete builds is to let aliBuild do its best by running:\naliBuild clean\n\nwhich can take the optional argument --aggressive-cleanup that deletes also source code of built\ndependency packages and downloaded .tar.gz archives.\nIn general, it's good practice to run aliBuild clean always after aliBuild build.\nThis might not be enough, as aliBuild will not delete any build directory pointed to by a symlink\nthat has \"latest\" in its name, even when that build is not needed by any other package anymore.\nManual intervention is therefore sometimes needed.\nDeep cleanup\nIf you want to keep only the latest builds of your development packages (and their dependencies),\nyou can make aliBuild delete the rest with a little trick.\n\nDelete symlinks to all builds:find $ALIBUILD_WORK_DIR/$(aliBuild architecture)/ -mindepth 2 -maxdepth 2 -type l -delete\nfind $ALIBUILD_WORK_DIR/BUILD/ -mindepth 1 -maxdepth 1 -type l -delete\n\nIn case you specified the architecture manually (using the -a option with aliBuild build), you should replace $(aliBuild architecture) with your manually specified architecture.\nRecreate symlinks to the latest builds of development packages (and their dependencies)\nby running aliBuild build for each development package.\nLet aliBuild delete all the other builds by running aliBuild clean.\n\n"},"building/precomp.html":{"url":"building/precomp.html","title":"๐ฆ Use the precompiled binaries","keywords":"","body":"๐ฆ Use the precompiled binaries\nYou can run our precompiled binaries from CVMFS by simply logging to lxplus or lxplus7:\nssh @lxplus.cern.ch\nssh @lxplus7.cern.ch # required for O2\n\nIf you are an ALICE user, you are welcomed with a message telling you exactly what to do. To load\na specific analysis tag of AliPhysics you can do:\n/cvmfs/alice.cern.ch/bin/alienv enter AliPhysics/vAN-20181121_ROOT6-1\n\nYou can list all the available versions with (very slow ๐):\n/cvmfs/alice.cern.ch/bin/alienv q\n\nor you can simply consult the list of Grid packages here.\n\nO2 is available on the \"nightlies\" repository of ALICE. You can use it only from lxplus7.cern.ch:\nit will not work on SLC6. List the packages:\n/cvmfs/alice-nightlies.cern.ch/bin/alienv q\n\nLoad a specific version:\n/cvmfs/alice-nightlies.cern.ch/bin/alienv enter O2/nightly-20181121-1\n\n"},"building/devel.html":{"url":"building/devel.html","title":"๐ช Develop a single package (Experimental)","keywords":"","body":"Develop a single package reusing a CVMFS / RPM installation EXPERIMENTAL\nFor those cases where you want to develop a single O2Suite package, for example ALICE O2, it's now possible to reuse a preexisting installation in CVMFS or\ninstalled via the RPM packages.\nIn order to do so you must make sure you point WORK_DIR to your base installation folder. E.g. for lxplus:\nexport WORK_DIR=/cvmfs/alice.cern.ch\n\nand that you properly set your ALIBUILD_ARCH_PREFIX. E.g. for lxplus:\nexport ALIBUILD_ARCH_PREFIX=el7-x86_64/Packages\n\nassuming you want to use nightly-20200810-1 as baseline, you can then do:\n. $WORK_DIR/$ALIBUILD_ARCH_PREFIX/O2/nightly-20210120-1/etc/profile.d/init.sh\n\nThis will fill your environment with all the requirements needed to properly build O2.\nYou can checkout and build most of the AliceO2Group packages with:\ngit clone --origin upstream https://github.com/AliceO2Group/AliceO2 O2\nmkdir -p O2/objs\ncd O2/objs\ncmake ..\ncmake --build . --target all -j8\n\nThis is not a replacement for the full alibuild environment, which allows you to build multiple packages at once or to keep track of\nchanges in alidist, however it should work already fairly well to develop a single package.\nCaveats:\n\nRuntime environment is currently not handled fully and you need to either use -DCMAKE_INSTALL_PREFIX or run executables from stage/bin.\n\n"},"analysis/welcome.html":{"url":"analysis/welcome.html","title":"Writing an analysis task","keywords":"","body":"How to write your analysis task for AliPhysics\nThe goal of this introduction is to explain to you how you can write and run a minimal analysis task for the AliPhysics analysis framework. This task will not give you any real 'physics' results, it's just a minimal example of what you need know to do a data analysis for the ALICE experiment. It is assumed that you have basic knowledge of both C++ and ROOT.\nAt the end of this introduction, you will understand what happens in your analysis task, and you will understand how to run it on your laptop, on the Grid, and in 'LEGO-trains'. What all of this means will become clear later on. After you have read this introduction, you can follow steps 1 through 7 of the Analysis tutorial exercises, which will give you hands-on experience with building an analysis from the grounds up, and running it. This of course requires that you have a working version of the ALICE software stack available on your computer. \n"},"analysis/classes.html":{"url":"analysis/classes.html","title":"AliAnalysisTaskSE","keywords":"","body":"Introduction - C++ classes\nAll the code that you will find in ROOT, AliRoot and AliPhysics is written in the form of C++ classes. A class is a data type which is defined by the user, and allows for creating data members and functions specific for that class. By convention, each class in AliPhysics, AliRoot, and ROOT, is stored in its own header (.h) and implementation file, which have the same name as the class it defines (so later on, we will see that your analysis class, stored in a file 'AliAnalysisTaskMyTask', is called 'AliAnalysisTaskMyTask'). \n C++ .... ?If you have never heard of classes (or C++), it might be a good idea to go through a C++ manual, an excellent one, with plenty of hands-on examples, can be found here: http://www.cplusplus.com/doc/tutorial/. \n\nClasses are extended structures which contain both variables and functions (which are called methods) as members. Often, variables must be accessed through these methods. This might sound a bit abstract, but it becomes much more clear when you look at in a small code example:\n class Rectangle\n {\n private:\n int width, height;\n public:\n Rectangle(int,int);\n int GetArea() {return height * width;}\n }\n\nHere we defined a class, called Rectangle, which has variables width and height, and a method called GetArea which gives us access to the members. \nInheritance\nClasses are nice and important, because they can be derived from one-another (a feature called inheritance. Look at the figure below \n\nIn this figure, Rectangle is derived from base class Polygon, and inherits its members. If we want to define a second class, Triangle, which is also a polygon and will therefore have features in common with Rectangle, we can also derive it from base class Polygon. This avoids having to repeat common code for multiple which share features. \n BewareClasses are very powerful, but inheritance can sometimes make it tricky to understand how code is structured!\n\nLet's take a look at how our classes would look like when we put them down as C++ code. First, we define out base class, the polygon\nclass Polygon\n{\n private:\n int width, height;\n}\n\nThis example lives in 2-dimensional space, so our polygon is fully defined by its width and its height. The two polygons that we want to define, are a rectangle and a triangle. The rectangle can be defined as follows\n class Rectangle : public Polygon\n {\n public:\n Rectangle(int,int);\n int GetArea() {return height * width;}\n }\n\nNote that we do not have to define the members height and width here, as they are already defined in our base class! The only method that is specific to the rectangle, is the GetArea method. \nOur triangle class can be written as\n class Triangle : public Polygon\n {\n public:\n Triangle(int,int);\n int GetArea() {return (height * width)/2;}\n }\n\nAgain, width and height are defined in the base class Polygon, but also the Triangle class gets its own GetArea method. So now we have seen how inheritance makes our classes (and our life) simpler: by defining common functionality in a base class, we avoid repetition of code, which could easily lead to mistakes.\n Example from AliPhysics - The AliMCEvent classInheritance is used widely in C++ code, and therefore also in AliROOT and AliPhysics. Take a look at the AliMCEvent class below\n class AliMCEvent : public AliVEvent {\n public:\n ....\n private:\n ....\n }\n\nHere AliMCEvent is derived from its base class AliVEvent, in the same way as the Triangle is derived from the base class Polygon. Classes such as AliESDEvent and AliAODEvent are also derived from AliVEvent, preventing a lot of boilerplate (i.e. needlessly repetitive) code.\n\n Class headers ... ? C++ classes are, in code bases, usually split into a header file (extention .h) and an implementation file (extension .cxx). A header file is generally used to define all of the functions, variables and constants contained in a class. There are multiple good reasons for splitting code into an implementation and a header - can you think of a few? \n\nAliAnalysisTaskSE\nNow that you are an expert at C++ classes, you might wonder why classes are relevant to writing an analysis task. The reason is the following: in the AliPhysics analysis framework, all analysis tasks are derived from the same base class, called AliAnalysisTaskSE, where SE stands for 'single event'. This class in turn, is derived from the class AliAnalysisTask (if you are interested, you can go through the code and follow the full chain of inheritance). \nSince all analysis tasks derive from AliAnalysisTaskSE, all analyses share the following common, base methods:\n AliAnalysisTaskSE::AliAnalysisTaskSE();\n AliAnalysisTaskSE::AliAnalysisTaskSE(const char*);\n AliAnalysisTaskSE::~AliAnalysisTaskSE();\n AliAnalysisTaskSE::UserCreateOutputObjects();\n AliAnalysisTaskSE::UserExec(Option_t*);\n AliAnalysisTaskSE::Terminate(Option_t*);\n\nThese are methods that you will always need to implement. \nIn the following section, we will go through these methods in detail.\nClass constructors and destructors\nThe functions\n AliAnalysisTaskSE::AliAnalysisTaskSE(); // class constructor\n AliAnalysisTaskSE::AliAnalysisTaskSE(const char*); // class constructor\n AliAnalysisTaskSE::~AliAnalysisTaskSE(); // class destructor\n\nare your class constructors and destructor. These are standard C++ features, that are called when you create or delete an instance of your class. We will later on see, why you need to define two different class constructors. \nAliAnalysisTaskSE::UserCreateOutputObjects()\nIn this function, the user (i.e. the analyzer) can define the output objects of the analysis. These are e.g. histograms in which you store your physics results. These output objects can be attached to the output file(s) of the analysis. \n Please noteWhen you are designing your class for your analysis, it (obviously) pays off to think about which output you need to extract the physics; do you want ten 1D histograms, or will four 2D histograms supply much more information? Or would you prefer writing certain information to a TTree, such that you have full information available when post-processing on your laptop? All these different output objects bring memory and size considerations, so choose well.\n\nAliAnalysisTaskSE::UserExec()\nThis function is called for each, single event over which your analysis task runs. This function is your 'event loop'. Examples of useful things to do in the UserExec() function:\n\nCheck if an event has properties that you want to have in your analysis, if not return;\nAccess the physics objects specific to your analysis (e.g. the charged particles in this event, or find the highest momentum particle)\nFill the histograms or other output objects\n\n Please noteIf the function AliAnalysisTaskSE::SelectCollisionCandidates(UInt_t trigger_mask) is called before you launch your analysis, UserExec() will only be executed for events which pass the trigger selection that you have specified. \n\nAliAnalysisTaskSE::Terminate()\nThe Terminate function is called at the very end of the analysis, when all events in your input data have been analyzed. Often, you leave the Terminate function empty: usually it is more practical to write a small macro that performs post-processing on your analysis output files, rather than deferring this functionality to the Terminate function. \n"},"analysis/alianalysistaskmytask.html":{"url":"analysis/alianalysistaskmytask.html","title":"Your analysis task","keywords":"","body":"Your analysis task\nIn the previous section we discussed some of the basics of writing an analysis task from a 'theoretical viewpoint'. In this section, we will go through a working analysis class line-by-line. \nAs you now know, your own analysis task will be derived from the base class AliAnalysisTaskSE. We will use a fixed format to write our tasks, which means that we need to create three files:\n\nThe header file (.h) which contains function prototypes and in which your class members are defined\n\nThe implementation file (.cxx), in which the methods of your analysis are implemented\n\nAn AddTask.C macro which creates an instance of your class\nand configures it.\n\n\nThe class header (.h)\nLetโs start by looking at our header (the .h file), where we define the prototypes of all the methods that we want to implement in our class\n#ifndef AliAnalysisTaskMyTask_H\n#define AliAnalysisTaskMyTask_H\n\nclass AliAnalysisTaskMyTask : public AliAnalysisTaskSE \n{\npublic:\n // two class constructors\n AliAnalysisTaskMyTask();\n AliAnalysisTaskMyTask(const char *name);\n // class destructor\n virtual ~AliAnalysisTaskMyTask();\n // called once at beginning of runtime\n virtual void UserCreateOutputObjects();\n // called for each event\n virtual void UserExec(Option_t\\* option);\n // called at end of analysis\n virtual void Terminate(Option_t\\* option);\n /// \\cond CLASSDEF\n ClassDef(AliAnalysisTaskMyTask, 1);\n /// \\endcond\n};\n\n#endif\n\nLet's go through the snippet of code line-by-line. First of all, we see\n#ifndef AliAnalysisTaskMyTask_H\n#define AliAnalysisTaskMyTask_H\n.\n.\n.\n#endif\n\nThese three lines form an include guard (sometimes called macro guard, or header guard). This construct is used to avoid the problem of double inclusion: should the header of your class be included more than once, the include guard will protect your code from double definitions which result in invalid code. \n Include guardsWhat is the risk of not using include guards?\n drum roll Click to expandSay that you have a header file, called grandparent.h, in which you define a struct\nstruct foo {\n int member;\n};\n\nand you create a second file parent.h where you write\n#include \"grandparent.h\"\n\nand even a third one, child.h in which you do\n#include \"grandparent.h\"\n#include \"parent.h\"\n\nAfter preprocessing, the content of the file child.h will be\nstruct foo {\n int member;\n};\nstruct foo {\n int member;\n};\n\nsince child.h has indirectly included two copies of the text in the header file grandparent.h. This will cause a compilation error, since the struct foo will be defined twice. Using include guards, this problem would not have arisen. \n\nClass definition and constructors\nIf we continue looking at the code, we see the class definition and two class constructors\nclass AliAnalysisTaskMyTask : public AliAnalysisTaskSE \n{\npublic:\n // two class constructors\n AliAnalysisTaskMyTask();\n AliAnalysisTaskMyTask(const char *name);\n // class destructor\n virtual ~AliAnalysisTaskMyTask();\n\nThe first line means that we define a class AliAnalysisTaskMyTask, which is derived from AliAnalysisTaskSE. \nClass constructors and destructor\nThe two functions AliAnalysisTaskMyTask() and AliAnalysisTaskMyTask(const char *name) are class constructors. A class constructor is a special function in a class that is called when a new object of the class is created. \nWe always need to define two class constructors for our analysis task, why this is, will be explained later. The third function is the class destructor. A destructor is also a special function which is called when the created object is deleted. We will later see, that a class that has pointer data members should include, in addition to a destructor, a copy constructor and an assignment operator - but for now we can just forget about those. \nAliAnalysisTaskSE inherited functions\nAfter the constructors and destructors, we define the prototypes of the functions that we have already seen in the AliAnalysisTaskSE section\n // called once at beginning of runtime\n virtual void UserCreateOutputObjects();\n // called for each event\n virtual void UserExec(Option_t* option);\n // called at end of analysis\n virtual void Terminate(Option_t* option);\n\nThese functions will be the heart of our analysis. In the UserCreateOutputObjects, we will define whatever output we want to write to our root files. The UserExec function will be called for all events in the data sample that we are looking at. Finally, Terminate is called at the very end of the analysis. \n Virtual functions In the code snippet above, we see the virtual keyword. Do you know what this means ? \n Click to show answer Click to expandConsider the following simple program which is an example of runtime polymorphism.\nThe main thing to note about the program is, derived class function is called using a base class pointer. The idea is, virtual functions are called according to the type of object pointed or referred, not according to the type of pointer or reference. In other words, virtual functions are resolved late, at runtime (which makes them powerful, but costly):\nclass Employee \n{ \npublic: \n virtual void raiseSalary() \n { /* common raise salary code */ } \n\n virtual void promote() \n { /* common promote code */ } \n}; \n\nclass Manager: public Employee { \n virtual void raiseSalary() \n { /* Manager specific raise salary code, may contain \n increment of manager specific incentives*/ } \n\n virtual void promote() \n { /* Manager specific promote */ } \n}; \n\n// Similarly, there may be other types of employees \n\n// We need a very simple function to increment salary of all employees \n// Note that emp[] is an array of pointers and actual pointed objects can \n// be any type of employees. This function should ideally be in a class \n// like Organization, we have made it global to keep things simple \nvoid globalRaiseSalary(Employee *emp[], int n) \n{ \n for (int i = 0; i raiseSalary(); // Polymorphic Call: Calls raiseSalary() \n // according to the actual object, not \n // according to the type of pointer \n} \n\nOutputs ???\nIn Derived\n\nSo, virtual functions allow us to create a list of base class pointers and call methods of any of the derived classes without even knowing the type of the derived class object. \n\nHistograms, lists, and more\nNow that we have defined the methods of our analysis class, it is time to add some members. What we are going to add, are three pointer data members\n\nfAOD which is a pointer to an event\nfOutputList which is a (pointer to a) list that holds all our output objects\nfHistPt which is a (pointer to a) histogram that will hold our pt spectrum\n\nSince these members are part of our class definition, we have to add them to our header file\n class AliAnalysisTaskMyTask : public AliAnalysisTaskSE\n .\n .\n .\n private:\n AliAODEvent* fAOD; //!\nIn the code snippet above, you might see something interesting: when we write comments that describe what our class members are doing, we append the expression ! to the double slashes // that start our comment giving us //!. Contrary to what you might think, this expression mark is seen by ROOT (even though it's written as a comment) and it is essential for the correct documentation generation. We will get later to the logic of this locution, but for now a rule of thumb suffices: pointers to objects that are initialized at run-time (in the User* methods) should be marked with a //!.\nThe ClassDef definition\nAt the very end of our header file, we add the following line\n/// \\cond CLASSDEF\nClassDef(AliAnalysisTaskMyTask, 1);\n/// \\endcond\n};\n\nThere is a lot going on behind this one single line: ClassDef is a C preprocessor macro that must be used if your class derives from TObject. ClassDef contains member declarations, i.e. it inserts a few new members into your class; the ClassDef macro family is defined in the file Rtypes.h, should you be interested.\nThe two comments surrounding the ClassDef statement are required to properly produce the documentation.\nHow all this works exactly is not very relevant at this point. We will later see that you will need to increase the version number whenever you change the definition of your class, or ROOT will not be able to handle objects written before and after this change in one process. The version number 0 (zero) disables I/O for the class completely, so we start counting at 1. \nThe implementation of your analysis task (.cxx)\nWe are for now done with our class header, it's time to move to the implementation of the class: the AliAnalysisTaskMyTask.cxx file, in which we will actually implement our methods. Let's start by defining our class constructors. As stated before, ROOT requires two class constructors (weโll get later to why this is necessary), one of which is the I/O constructor, which is not allowed to allocate any memory. So we start our implementation with\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD{0}, fOutputList{0}, fHistPt{0}\n {\n // ROOT IO constructor, don't allocate memory here!\n }\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask(const char* name) : AliAnalysisTaskSE(name),\n fAOD{0}, fOutputList{0}, fHistPt{0}\n {\n DefineInput(0, TChain::Class()); \n DefineOutput(1, TList::Class()); \n }\n\nAs you see, in the constructor, we initialize members to their default values. Always initialize members to default values (and pointers to nullptr). If you fail to do so, values contained by the members will be random, which can lead to unexpected behavior of your code. \n Undefined behavior You have written a small function\nint f(int x)\n{\n int a;\n if(x>0) a = 42;\n return a; \n}\n\nWhat happens when you call\nf(10)\n\nand what happens when you call\nf(-10)\n\n?\n drum rollClick to expandf(10) will return 42. The output of f(-10) is undefined, since variable a was not initialized. \n\nIn the second constructor of this task, we define what the input and output does the analysis class handle. In our case, the input is of type TChain, and as we will see later, the output is a TList. \nUserCreateOutputObjects()\nIn our UserCreateOutputObjects function, we will define the output objects of our task. These are commonly histograms, profiles, etc. In our specific example, we will add one histogram, and define a list to which we will attach the histogram. \n Output listsAdding all your output histograms to a list makes your life easier: the list will allow you to manipulate many output objects simultaneously. By calling TList::SetOwner(true), we transfer ownership of all memory allocated by the list items to the TList itself, this means that in our destructor, we can simply call delete list to delete all our list items, rather than calling delete for all items individually. \n\nThe implementation of the UserCreateOutputObjects method looks like this \n ...\n #include \"TList.h\"\n #include \"TH1F.h\"\n ...\n AliAnalysisTaskMyTask::UserCreateOutputObjects()\n {\n // create a new TList that OWNS its objects\n fOutputList = new TList();\n fOutputList->SetOwner(true);\n\n // create our histo and add it to the list\n fHistPt = new TH1F(\"fHistPt\", \"fHistPt\", 100, 0, 100);\n fOutputList->Add(fHistPt);\n\n // add the list to our output file\n PostData(1,fOutputList); \n }\n\nNote that we create a TList and make it the owner of the memory of all its elements. After we create the histogram, we add it to the output list. Finally, in the last line, we call PostData, which will notify the client tasks of the data container that that the data pointer has changed compared to the previous post. \nUserExec\nThe UserExec is the heart of our analysis: it is called for each event in our input data set. First, we need to access our event, which we can do via a call to the method InputEvent \n ...\n #include \"AliAODEvent.h\"\n ...\n AliAnalysisTaskMyTask::UserExec(Option_t*)\n {\n // get an event from the analysis manager\n fAOD = dynamic_cast(InputEvent());\n\n // check if there actually is an event\n if(!fAOD)\n ::Fatal(\"AliAnalysisTaskMyTask::UserExec\", \"No AOD event found, check the event handler.\");\n\nOnce we have access to our input event, we can e.g. loop over all the tracks that it contains, and store the pt of the tracks in our histogram:\n ...\n // let's loop over the tracks and fill our histogram\n\n // first we get the number of tracks\n int iTracks{fAOD->GetNumberOfTracks()};\n\n // and then loop over them\n for(int i{0}; i (fAOD->GetTrack(i));\n if(!track) continue;\n\n // here we do some track selection\n if(!track->TestFilterbit(128) continue;\n\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n // and save the data gathered in this iteration\n PostData(1, fOutputList);\n }\n\nTake a look at the code and make sure that you understand the logic of all the lines. In principle, this is all you need in an analysis task to run a small analysis. \nAlmost there: the AddTask macro\nThe last thing that we need to fully define our analysis task, is a small file, that we will call the AddTask macro, that instantiates our task (class), defines its in- and output, and connects it to the analysis manager. We will put this piece of code in an independent, third file, called AddMyTask.C. It is important, that this macro defines a function, in our case called AddMyTask, that returns a pointer to our analysis task. We need to follow this exact convention if we later on want to run our analysis in the automated LEGO train system. \nOur AddTask macro looks as follows:\nAliAnalysisTaskMyTask* AddMyTask(TString name = \"name\") {\n AliAnalysisManager *mgr = AliAnalysisManager::GetAnalysisManager();\n\n // resolve the name of the output file\n TString fileName = AliAnalysisManager::GetCommonFileName();\n fileName += \":MyTask\"; // create a subfolder in the file\n\n // now we create an instance of your task\n AliAnalysisTaskMyTask* task = new AliAnalysisTaskMyTask(name.Data()); \n\n // add your task to the manager\n mgr->AddTask(task);\n\n // connect the manager to your task\n mgr->ConnectInput(task,0,mgr->GetCommonInputContainer());\n // same for the output\n mgr->ConnectOutput(task,1,mgr->CreateContainer(\"MyOutputContainer\", TList::Class(), AliAnalysisManager::kOutputContainer, fileName.Data()));\n\n // important: return a pointer to your task\n return task;\n}\n\nAnd that's it - we now have our three files that contain a minimal analysis!\n"},"analysis/local.html":{"url":"analysis/local.html","title":"Running locally","keywords":"","body":"Running locally\nNow that we have seen how a task is built up, we will take a look at how you can run your analysis task. Basically, there are three options for running a task:\n\nRun on local data (i.e. some input files that are stored on your laptop)\n\nRun on GRID (either in test or full mode) yourself\n\nRun on GRID using the LEGO train system\n\n\nIn this section, we will take a look at option 1: how to run on data that you have stored locally, on your own computer. \n Please noteFor practical purposes it is (nearly) impossible to process a whole dataset locally on your laptop, but launching a local test provides you with an environment to test your analysis task!\n\nTo run a local analysis, we need to\n\nCompile our code, and\nLaunch our analysis\n\nSteering macros\nTo do so, we usually use another small macro, commonly referred to as a steering macro, which steers the analysis. This macro will \n\ncreate an analysis manager and data handler, \nwill define which data files to run on, \ncompile your code, and then \ninstruct the analysis manager to run your analysis. \n\nAn example of a steering macro to run the task AliAnalysisTaskMyTask on data that's stored on your laptop, looks as follows:\n void runAnalysis() {\n // header location\n gInterpreter->ProcessLine(\".include $ROOTSYS/include\");\n gInterpreter->ProcessLine(\".include $ALICE_ROOT/include\");\n\n // create the analysis manager\n AliAnalysisManager *mgr = new AliAnalysisManager(\"AnalysisMyTask\");\n AliAODInputHandler *aodH = new AliAODInputHandler();\n mgr->SetInputEventHandler(aodH);\n\n // compile the class (locally) with debug symbols\n gInterpreter->LoadMacro(\"AliAnalysisTaskMyTask.cxx++g\");\n\n // load the addtask macro and create the task\n AliAnalysisTaskMyTask *task = reinterpret_cast(gInterpreter->ExecuteMacro(\"AddMyTask.C\"));\n\n // if you want to run locally, we need to define some input\n TChain* chain = new TChain(\"aodTree\");\n chain->Add(\"/scratch/.../AliAOD.root\");\n\n // start the analysis locally\n mgr->StartAnalysis(\"local\", chain);\n }\n\nRead the above code snippet line-by-line, and try to understand the comments. \nRunning\nTo run your analysis, it will now suffice to type in a terminal (after sourcing the AliRoot environment): \naliroot runAnalysis.C\nThis will trigger executing of the steering macro, which will in turn launch the analysis. If all goes well, this minimal task should produce one histogram, which looks like\n\nTry for yourself?\nIf you want to try this for yourself, you can now go from steps 1 through 5 of the 'Analysis tutorial exercises'.\n"},"analysis/rungrid.html":{"url":"analysis/rungrid.html","title":"Running on Grid","keywords":"","body":"Running on Grid\nThe Worldwide LHC Computing Grid, usually simply referred to as Grid, is a global collaboration of computer centers. It has been up and running since 2002, to provide resources to store, distribute and analyze the petabytes of data that are generated by the LHC. \nOn the picture below, from http://alimonitor.cern.ch/map.jsp, you can see the distribution of computing centers that are working for the ALICE collaboration. We will the Grid to run your analysis on a larger scale than your laptop can provide. \n\nTo run your analysis on the Grid, all we need to do is expand our steering macro a little bit. In this section, we will explain how. \nConfiguring the AliEn plugin\nIn order to run your analysis transparently either on your local computer or on the Grid, we will use the AliEn plugin. The plugin hides a lot of complex operations that have to be performed in order to run your analysis on Grid, e.g.\n\nUsing all existing types of input data to be processed (root files, raw AliEn collections or XML collections) detecting their type automatically;\nGenerate XML collections corresponding to requested runs and/or data patterns;\nAutomatically detect presence of tags in input data and allow using tag-based cuts in a very simple way;\nAutomatically connect to AliEn (generate a token if needed)\nGenerate automatically: JDL, analysis macro to be run in grid, execution and validation scripts according a simple to understand user-driven configuration; \nCopy all needed files in user's AliEn space and submit the job automatically;\nStart an alien shell to allow inspecting the job status;\nDo automatic output merging and terminate the analysis tasks.\n\nThe implementation of the plugin is for the Alice Environment is provided in the class AliAnalysisAlien. In the following code snippet, you can an example of how the plugin is created. These lines would go into your runAnalysis.C steering macro. Read through the code and the comments, and make sure that you understand what happens in each line. \n // create an instance of the plugin\n AliAnalysisAlien *alienHandler = new AliAnalysisAlien();\n // if our class relies on code that has to be compiled, then we need to tell the Grid nodes\n // where the headers can be found\n alienHandler->AddIncludePath(\"-I. -I$ROOTSYS/include -I$ALICE_ROOT -I$ALICE_ROOT/include -I$ALICE_PHYSICS/include\");\n // here we tell which source files need to be copied to the Grid nodes\n alienHandler->SetAdditionalLibs(\"AliAnalysisTaskMyTask.cxx AliAnalysisTaskMyTask.h\");\n alienHandler->SetAnalysisSource(\"AliAnalysisTaskMyTask.cxx\");\n // here we specify which version of aliphysics will be used on the Grid nodes\n // only specificy the AliPhysics version, other dependencies (AliRoot, ROOT, etc)\n // will be resolved automatically\n alienHandler->SetAliPhysicsVersion(\"vAN-20160330-2\");\n // here we specify where the input data of our analysis is stored\n alienHandler->SetGridDataDir(\"/alice/data/2011/LHC11h_2\");\n // and here we specify a specific pattern of filenames\n alienHandler->SetDataPattern(\"*ESDs/pass2/AOD145/*AOD.root\");\n // here we set the run prefix: use '000' for data, or nothing for MC\n alienHandler->SetRunPrefix(\"000\");\n // specify the runnumber to be analyzed. you can call this function multiple times with \n // different runnumbers\n alienHandler->AddRunNumber(167813);\n\nSo far, we have defined the following things\n\nWhich input data has to be analyzed;\nWhich AliPhysics version has to be used;\nWhat kind of analysis sources have to be used.\n\nThese are options that you likely have to change very often. However, there are many more analysis details that we can provide:\n // number of files per subjob, this specifies how many input files\n // each Grid node will analyze. For slow analyses, you might want to \n // lower this number\n alienHandler->SetSplitMaxInputFileNumber(40);\n // the TTL is the 'time to live', which specifies how long a job can run, in seconds\n // the longer you make this time, the lower the jobs priority will be. However, if the job doesn't\n // finish within its TTL, it will be killed, so choose a reasonable number\n alienHandler->SetTTL(10000);\n // do you want to create a subfolder in which the output of each runnumber is stored? \n alienHandler->SetOutputToRunNo(kTRUE);\n // do you want to keep your jobs log files ? \n alienHandler->SetKeepLogs(kTRUE);\n // we can specify that we want to, later on, use Grid to also merge\n // our output. to enable this, we will set 'SetMergeViaJDL' to kTRUE\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1);\n // define the output folders, and give them a sensible name\n // jobs *cannot* overwrite output, so make sure that\n // folders with names as these do not yet exist in your AliEn space\n alienHandler->SetGridWorkingDir(\"myWorkingDir\");\n alienHandler->SetGridOutputDir(\"myOutputDir\");\n // lastly, we give names to the automatically generated analysis scripts\n alienHandler->SetJDLName(\"myTask.jdl\");\n alienHandler->SetExecutable(\"myTask.sh\");\n\nTest of full mode ?\nWe are nearly ready to launch our analysis on Grid. But before we go 'full blast' and use thousands of CPU's, we might want to do a test run to make sure that everything is configured correctly (and to make sure that we do not misuse ROOT's streamer, which will be covered in a later section). \nTo test your Grid analysis, we can specify to the plugin that we want to go for a test run, rather than launching a complete analysis. In the code snippet presented below, let's assume that the variable gridTest is set to kTRUE. As you can see, we specify to the plugin that we want to run in test mode. We also specify that we want to run over one test file (if you want to run over more test files, you can increase this number). \n // connect the alien plugin to the manager\n mgr->SetGridHandler(alienHandler);\n if(gridTest) {\n // speficy on how many files you want to run\n alienHandler->SetNtestFiles(1);\n // and launch the analysis\n alienHandler->SetRunMode(\"test\");\n mgr->StartAnalysis(\"grid\");\n } else {\n // else launch the full grid analysis\n alienHandler->SetRunMode(\"full\");\n mgr->StartAnalysis(\"grid\");\n }\n\nReady to go?\nWhen you run an analysis in test mode, a Grid environment is simulated locally for testing. Input data is downloaded from the file catalogue, following your configuration of the analysis plugin. After this, your analysis is executed. Running in test mode is an excellent way of convincing yourself that you have set up the plugin correctly. \nOnce your analysis test is finished, and you are convinced that your analysis output looks sane, you can submit your analysis to the Grid nodes. To do this, simply look at at the code snippet above, and assume that the variable gridTest is set to kFALSE. \n Create AliEn legacy token!Only ALICE members with a valid registration can submit jobs to the Grid and access the ALICE data. To identify yourself as an ALICE member, you will have to make sure that you have a valid token prior to launching your Grid jobs, be it in full or in test mode. If you are using AliEn legacy, then you need to obtain a token manually. If you are using JAliEn, then the token will be obtained automatically.\n$ alien-token-init \nif all is fine, you should be prompted for your password, and see something like\n => Trying to connect to Server [0] root://pcapiserv03.cern.ch:10000 as User \n ...\n Creating token ..................................... Done\n Your token is valid until: Thu Apr 7 15:23:52 2016\nafter this, you are good to go, and can launch your analysis by executing your steering macro\n$ aliroot runAnalysis.C \n\nMerging output on Grid\nYou can check the progress of the jobs that are running on Grid by going to (http://alimonitor.cern.ch/map.jsp)[http://alimonitor.cern.ch/map.jsp] and clicking on the tab My Jobs, at the top left of the page. When all your jobs are finished (we will later, in the section AliMonitor look at tracing your jobs in more detail), you are of course interested in looking at the output that they have produced. However, this output is stored as thousands of files, scattered over multiple job sites. To obtain one, single file as output of your analysis, we need to merge all these thousands of files. \nMerging via JDL\nThe easiest way to merge your output is using the MergeViaJDL option that the plugin provides. Using this option will allow you to submit special merging jobs, which run on the Grid nodes and merge your output files. To enable merging via JDL, you have to configure your plugin as follows, before you start your analysis:\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1); // just one step\n ....\n mgr->SetRunMode(\"full\");\n\nThis will prepare the plugin for writing merging jobs, when your analysis is done. \n More than on merging stage?By specifying\n alienHandler->SetMaxMergeStages(1);\n\nwe tell the plugin that all output files can be merged in one go. \nIf your output files are quite large, you might want to increase the number of merging stages by specifying a larger number here: this will tell the plugin that we want to merge in multiple, consecutive stages.\n\nWhen all your normal analysis jobs have finished, we want to launch the merging jobs to Grid. To do this, we again make a small modification to our steering macro, and change the run mode from full to terminate:\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1); // just one\n ....\n mgr->SetRunMode(\"terminate\");\n\nTo now launch the merging jobs, simply run\n$ aliroot runAnalysis.C\nagain. The merging jobs will be launched, and you can monitor their progress on via the 'Jobs' tab on http://alimonitor.cern.ch/map.jsp.\nWhen all your merging jobs have finished running, there is one step to be taken still, which is downloading the output of the merging jobs, so that you have your analysis output available on your laptop. This is done by again making a small change to your steering macro:\n alienHandler->SetMergeViaJDL(kFALSE);\n alienHandler->SetMaxMergeStages(1); // just one\n mgr->SetRunMode(\"terminate\");\n\nand running runAnalysis.C a final time. This will trigger downloading of the merged output files (the resulting files from the merging jobs) and a final 'local' merge of said files into one, single output file. When the process is done your high-statistics output files is ready - time to start writing a paper!\n Merging is 'dumb'Keep in mind: merging can be a memory-hungry process. During merging, all files that are to be merged are kept in random access memory. ROOT files tend to be heavily compressed when written to disk, so their size in RAM might be surprisingly large. \nWhen your output files are large, or if you have a large number of output files to be merged, you might need to merge in multiple stages, to avoid running out of RAM!\n\n"},"analysis/lego.html":{"url":"analysis/lego.html","title":"The LEGO train system","keywords":"","body":"The LEGO train system\nBy now, your code is running well on Grid, you're submitting and merging jobs like a seasoned professional. However, do you really want to \n\nStay up all night to resubmit jobs? \nRisk losing your code because it's not part of AliPhysics and your hard drive crashes? \n\nTo avoid these headaches, users are encouraged to run their jobs in a more automated and efficient way by using the LEGO framework. \n Why LEGO trains are crucialA train can easily contain multiple instances of your analysis, meaning you can run your default configuration and in addition multiple cut variations and other cross-checks. The success rate of the jobs is EXACTLY the same for each of your configurations, as they are all handled in parallel. This means that the all the configurations handle the exact same set of data.\nThis is in contrast to submitting your jobs one after each other (possibly running into quota problems) and having random job crashes, resulting in a situation where your default configuration and the variations did not handle exactly the same set of data.\n\nHow does it work\nThe LEGO framework is a tool to run and manage analysis trains on AliEn. It builds on existing infrastructure, the analysis framework, MonALISA and LPM. LEGO provides a web interface for users and operators which allows to:\n\nregister train wagons\nconfigure trains (handlers, wagons, input datasets, global Variables)\ntest the wagons and the train in a well-defined environment\nstudy the test results\nsubmit the train to the Grid\nstudy the resource consumption of the train for each wagon (CPU usage, virtual and resident memory) \n\n NoteThe fact that the trains run on the Grid, requires that all code is contained in an AliEn package. Therefore, the train uses the regularly deployed AliPhysics \"AN\" tags, so you will have to make sure that your analysis code is available in AliPhysics. \nWithin AliPhysics, your analysis code will be part of a shared library that contains many other analyses from your working group or analysis group. If you have never added a class to AliPhysics, ask your PWG or PAG coordinators for help.\n\nHow to access the LEGO train system\nThe LEGO train system can be accessed via (https://alimonitor.cern.ch/trains/)\n\nBy clicking on the top right 'help' tab, you will be guided to a webpage where it is explained in detail how you can join a LEGO train and perform a highly efficient analysis. \n Join the LEGO trains!Everyone is encouraged to use the LEGO train system for running analysis rather than running analysis by yourself on Grid. Not only will you benefit yourself, but by running trains that contain analyses of multiple users in one go, we conserve resources: the LEGO train has to only run on instance of AliPhysics to perform multiple analyses, and it has to only retrieve the input data once. \nAs a consequence: LEGO train jobs have higher priority in the job queues than user jobs! Furthermore, your analysis will always be reproducible, and you will receive a simple mail with a link to your final output file when your train run is done. So if you want to perform fast, safe, and efficient analysis: use the LEGO trains!\n\nHow to add your analysis task to the LEGO train system\nAs seen in the screenshot above, the train pages are grouped by PWG, collision system, and AOD or ESD data processing. Once you are in the correct train page:\n\nClick Add new wagon\nConfigure the wagon by either setting it up from scratch, or copying it from an existing wagon(available under advanced settings, and allows in addition to not only copy your own wagons, but also from any other user!)\nCheck that your macro is defined and configured correctly in the basic settings tab\nCheck the dependencies (if your dependency is not available you can just create another wagon and configure it accordingly then define it as a dependency for your own wagon)\nUse a unique filename for your wagon\nExpert mode: Add subwagons (easiest way to run multiple analysis with a single wagon)\nActivate your wagon for the dataset you want to process (if it is not available, ask an operator to add it)\nCheck the runlist of the dataset! (Do not blindly use the runlists which happen to be there, make sure proper QA is done such that only high quality runs are used for your analysis)\nAsk the train operators to start a train test for your activated wagons (each PAG and/or PWG has a different system, please ask the coordinators)\nCheck that the train test output is successful and take responsibility in debugging if there are problems\nIf all is ok, confirm with the train operator that the train can be started\n\nThis seems to be quite a long list, but once your wagons are set up it takes only a few minutes to get your analyses on the grid. You just need to wait for the email to announcing the completion of the run.\n"},"analysis/monalisa.html":{"url":"analysis/monalisa.html","title":"AliMonitor","keywords":"","body":"MonALISA - the ALICE Grid monitoring toolset\nALICE uses MonALISA (Monitoring Agents using a Large Integrated Services Architecture) for monitoring and control of its Gird operations. The AliMonitor webpage, that we have seen in previous sections, provides us with access to the MonALISA services. In this section, we will cover some of these services. \n VO registrationFor full access to all MonALISA serivces, make sure that you have a valid certificate and ALICE VO registration!\n\nRun numbers\nIn the previous section, we have seen that data that are stored are identified by their run number. If you want to look up which run numbers correspond to a given data taking period, go to ALIMONITOR and click on the tab 'Run Condition Table' (RCT). \n\nA large table is shown - you can select a data taking period from the drop down menu at the top left corner of the table. As soon as you select a data taking period, the corresponding list of run numbers is displayed in the table. \n\nTo ensure that detector systems that you need to use in your analysis were functioning properly, you can check quality flags for all detector subsystems in the columns on the right-hand side of the table. The number '1' means that data taking was successful; to only display run numbers for which data quality is guaranteed for a given sub detector, type a '1' in the field of the first row of the table that corresponds to said detector (see the circle on the top right of the above picture). \nIf you scroll down, to the bottom of the table, you will see a button labeled: 'Show list of runs'. Clicking this button will open a pop-up window which lists the run numbers that are displayed in the table as a list of comma separated numbers. You can now easily copy these numbers into your steering macro, and add these run numbers to the analysis plugin. \n Which data format to take?You might note that, for all runs, data is stored in two distinct formats\n\nAliESDs.root: event summary data\nAliAOD.root: analysis object data\nin various passes. \n\nESD files contain full information about events, AOD files contain a subset of information that has been selected for physics analysis. \n\nunless otherwise specified, use is discouraged as data are very\nlarge\nAOD files contain information necessary for physics analysis and is the preferred format\nAOD files contain pre filtered collections of tracks, to be selected via their\nfilterbit. Always apply a filterbit selection when running on AODs, to avoid double counting of tracks!\n\nWhen multiple passes are available for a data set, this means that the data has been reconstructed more than once, with slightly different approaches. As a rule-of-thumb: take the latest pass, but discuss this within your working group!\n\nAvailable packages\nThe AliMonitor webpage can be used to check which software packages are accessible on the Grid nodes. In the menu on the left-hand side of the page, click on 'Job information', then on 'User views', then on 'Grid packages'. A large table will load, if the CVMFS status is listed as 'available', a certain software package is available on Grid. If it's listed as n/a, it is (probably) archived, and cannot be selected for analysis. \nKeep in mind: when specifying a version of the software stack to be used, to only call โSetAliPhysicsVersion(โ..โ)โ in your steering macro. The right dependencies are automatically resolved. \n\nDaily tags (AN) of AliPhysics are a snapshot of all code that is in the central repository at 16h Geneva time. The daily tacks are usually available on Grid in about two hours after the tagging. \nRun quota - how many jobs can you run?\nWe have to share computing resources, so the number of jobs that you can run is not infinite. To check your quotas, which limit both how many jobs you can run, how much CPU hours they can consume, and how much diskspace your output files take up, click at the menu on the left-hand side of the AliMonotir page on 'Job information', then on 'User views' and then on 'Quotas. \n\nYou will see the five job activity quantifiers that apply for all users\n\nthe number of files that you have currently stored\nthe disk space that the files take up\nthe number of unfinished jobs that you have in the job queue\nthe running time of your jobs, integrated over the last 24 hours\nthe CPU cost of your jobs, integrated over the last 24 hours\n\nIf you are over (one of the) quota, i.e. one of the bars is completely red, you cannot submit jobs. In case of being over the file quota, you have to remove files from your alien space. Job quota just require a bit of waiting. \nBe patient, when you are over your quota. Not all quota are refreshed instantaneously, it can sometimes take up to 12 hours before your quota are refreshed. \n"},"analysis/oadb.html":{"url":"analysis/oadb.html","title":"Offline analysis database","keywords":"","body":"OADB and large shared files\nThe Offline Analysis Database (OADB) is a repository of relatively large configuration/calibration files that are used by the analysis framework, \ncontaining for example the 'TPC splines' with the parametrised dE/dx response of the TPC and calibration files for event plane calculation.\nThe data are generally stored in ROOT files, and the primary repository is on the CERN EOS file system, which is accessible from lxplus:\n/eos/experiment/alice/analysis-data\nWe have preserved the same directory structure found on AliPhysics, and the\nsame permissions: for instance, PWGLF is writable by all members of\nalice-svn-pwglf (whose members can be edited by the group conveners).\nUsing the OADB on the grid\nEvery day, in concomitance with the AliPhysics daily tag (at 4pm Geneva time),\nthis folder is snapshotted on CVMFS under the following path:\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD\ncarrying the same name as the corresponding AliPhysics tag. Moreover, at\nevery AliRoot/AliPhysics production release, we also snapshot at:\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01\nwhere the last component is the AliPhysics tag name.\nCVMFS brings the advantage to make data access from Grid jobs reliable and\nfaster due to caching (files unchanged in two different snapshots are not\ndownloaded twice).\nUsing the OADB on your local system\nIf your system is connected to the network, you can access the OADB via (x)rootd, but setting the ALICE_DATA environment variable\nexport ALICE_DATA=root://eospublic.cern.ch//eos/experiment/alice/analysis-data\n\nIf you want to have your OADB data locally, you can download it from lxplus:\nexport OADB_PATH=/path/to/my/local/oadb\nrsync -av --delete cern_user@lxplus.cern.ch:/eos/experiment/alice/analysis-data/ $OADB_PATH/\n\n\nTrailing slashes are important to rsync! Do not forget them!\n\nNote that the variable $OADB_PATH must be exported to the environment where\nyou run your local analysis in order to make it visible to the job.\nAccessing the OADB from code\nIn order to profit from the separate storage for large files we have created an\ninterface in AliRoot to allow transparent access to OADB files using a relative\npath. For instance, if you want to access the following large OADB data file:\nPWGLF/FORWARD/CORRECTIONS/data/fmd_corrections.root\nyou can do:\nTFile::Open(AliDataFile::GetFileNameOADB(\"PWGLF/FORWARD/CORRECTIONS/data/fmd_corrections.root\"))\n\nThe static function AliDataFile::GetFileNameOADB returns the first accessible\nfull URL of the OADB file by finding the first match from the following ordered\nlist of paths:\n\n$OADB_PATH/\n$ALICE_DATA/OADB/\n$ALICE_PHYSICS/OADB/\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01/OADB/ (for Grid jobs, or with CVMFS installed)\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD/OADB/ (for Grid jobs, or with CVMFS installed)\nroot://eospublic.cern.ch//eos/experiment/alice/analysis-data/OADB/\n\nThis means that for laptop analysis it will always be possible to access data\nfiles, somehow, and in a transparent fashion. \nNon-OADB data files\nThe same EOS path has also PWG-specific directories, outside the OADB one, for\nother analysis-specific data. The following interface can be used to access\nfiles from there:\nTFile::Open(AliDataFile::GetFileName(\"PWGMM/my_large_data.root\"))\n\n\nNote the difference between GetFileName() and GetFileNameOADB().\n\nIn this case, the file will be searched in the following locations in order:\n\n$ALICE_DATA/\n$ALICE_PHYSICS/\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01/ (for Grid jobs, or with CVMFS installed)\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD/ (for Grid jobs, or with CVMFS installed)\n\n"},"analysis/trouble.html":{"url":"analysis/trouble.html","title":"Troubleshooting","keywords":"","body":"Troubleshooting - when Grid does not do what you want it to do\nSometimes, running jobs does not go as smoothly as you would like it to go. In this section, we will cover some basic troubleshooting. \nFirst off all: be informed!\nGrid operations are complex. Often, job failures are a result of mistakes of users, but sometimes, certain Grid sites experience general problems. To quickly resolve these problems, it is important that we clearly communicate problems. To do so, ALICE makes extensive use of mailing lists. You can self-subscribe to mailing lists pertaining to Grid operations by surfing to e-groups.cern.ch . There, make sure that you are subscribed to\n\nalice-analysis-operations\nalice-project-analysis-task-force\nyour PAGโs mailing list\n\nALICE also employes a more professional bug and feature tracking suite, called JIRA, which you can access via\n\nhttps://alice.its.cern.ch/jira/projects/ALPHY\n\nTroubleshooting 101 - what should you do?\nSometimes, you will see mails such as\n `Dear experts,\n All my jobs are going into error. \n Could you check? Thanks!'\nbeing sent to the mailing lists. The experts can (and probably will) check, but you yourself should\nbe the first to take a look at why your job is not doing what you want it to do. The starting point is\n\nGo to โmy jobsโ on MonaLISA\nTake a look at the job trace and, if available, the stderr\nand stdout\n\nThe trace tells you exactly how your job was handled, from copying of files to Grid nodes, to executing the job, to checking if the expected output files were actually created. Stdout and stderr are the standard handles for the normal information and error information. Depending on whether or not the process actually ran, these files may or may not be available. \nIf you have checked your job's trace, stdout and stderr, and still cannot solve an issue, it is completely fine to write a mail to the mailing list. However, be complete in your message, specify what goes wrong, and provide some examples of job numbers. Do not kill your jobs! If the jobs are purged from the queue, debug information is lost. \nExample: validation error\nLet's take a look at an example of troubleshooting. We have some jobs running, and check their progress on MonALISA. Unfortunately, we see that all of our subjobs, corresponding to a given masterjob, go into the error state 'Validation error'\n\nThe first thing to do, is click on the masterjob number, to get a detailed overview of the subjobs. This table allows us access to the trace and log files\n\nClicking on 'log files' leads us to a page where we can consult the log files\n\nand by e.g. clicking on the 'stderr', we can check the error information of our job. \n\nMmm, so the job crashed with a segmentation violation, and if we remember correctly from our programming classes, we know that this points at illegal memory access ... so we had better go to our analysis code, and check our pointers ....\n Can you spot the mistake? Below, we see the UserCreateOutputObjects and a snippet of the UserExec() methods of the task that ran and segfaulted. What is wrong ? \n AliAnalysisTaskMyTask::UserCreateOutputObjects()\n {\n // create a new TList that OWNS its objects\n fOutputList = new TList();\n fOutputList->SetOwner(kTRUE);\n // add the list to our output file\n PostData(1,fOutputList);\n }\n ...\n AliAnalysisTaskMyTask::UserExec() {\n // called for each event\n ...\n fHistPt->Fill(track->Pt());\n\n Click to show answerClick to expandWe forgot to initialize the histogram that we try to fill: the pointer fHistPt has value NULL\n\nExample: execution error\nLet's take a look at another example. We are again running our jobs, but now we notice that subjobs of a given masterjob start to go into an 'Execution error' state. \n\nAgain, after clicking on the masterjob ID, the popup window of subjobs opens. If we hover with the mouse over the ID of a certain subjob, an graph of memory usage over time is shown. In this particular case, we clearly see that memory usage increases linearly over time\n\nLet's click on the trace of the subjob\n\nFrom the trace, we see that the job was killed because it used too much memory. The fact that we saw that the memory consumption increased linearly over time, probably means that there is a memory leak somewhere in our code ... better go back to the drawing board. \nWhat is the perfect workflow?\nBy now, we have seen that we can run our analysis\n\nlocally, on some data on our laptop\non Grid, either in test mode or full mode\non the LEGO trains\n\nEven though there is no perfect workflow, it is generally wise to\n\nDownload some AliAOD.root files to your computer\nDevelop your task\nTest locally (fast, no internet connection needed)\n\nWhen this goes well\n\nCheck in โtestโ grid mode. There are a few subtle differences\nbetween running LOCALLY and on GRID (covered in the next section)\n\nIf the code is robust:\n\nDonโt spend long nights (re)submitting jobs to GRID ...\n... rather get your code checked into AliPhysics\nAnd use the LEGO trains\n\n"},"analysis/streamer.html":{"url":"analysis/streamer.html","title":"The ROOT streamer","keywords":"","body":"The ROOT Streamer\nSometimes, mails like\n`Dear experts,\n my task worked fine but now \n on grid it does not. can you take a look ? '\nare sent on the mailing list. Some unexpected errors are caused by misuse of the ROOT streamer. The streamer has been mentioned a couple of times before now in other sections. So what is the โstreamer to begin with?\n\nThe ROOT streamer decomposes an object into its data members\n(serialization) and writes it to disk\n\nThis sounds more confusing than it is. Take a look at our class example from section 1\nclass Polygon\n{\n private:\n int width, height;\n}\n\nThe job of the streamer here would be, to save values of height and width, so that they can be written to disk. \nThe automatically generated streamer\nROOT automatically generates a steamer for us, if we instruct it to do so. Remember from the earlier sections, that we put the following lines in our task:\n // tell ROOT the class version\n ClassDef(AliAnalysisMyTask,1);\n };\n\nBy doing this, a streamer is constructed for us by invoking the ClassDef macro. \nCustomization\nROOT generates a streamer for us, but we have the task of customizing it. Customization means defining what data members should and should not be touched by the streamer. Customization is done in the header *.h) of a class, by giving specific instructions in the comments written after the declaration of data members (i.e. โ//โ). Let's take a look at this in practice. \nCustomizing: โmember persistenceโ\n\nPersistent Members (//) are โstreamedโ (copied/stored)\n class SomeClass : public TObject {\n private:\n Int_t fMinEta; // min eta value\n Int_t fMaxEta; // max eta value\n ...\n\n\nTransient Members (//!) are not streamed\n class SomeClass : public TObject {\n ...\n AliAODEvent* fAOD; //! current event\n TH1F* fHistPt; //! our histogram\n\n\n\nSo if we would write the object defined by the code snippets above to disk, the value of fMinEta and fMaxEta will be saved (//), but the values of fAOD and fHistPt will be ignored (//!).\nAdvanced use cases\nWe can customize the streamer in more sophisticated ways\n\nThe Pointer to Objects (//-$>$) calls streamer of the object\ndirectly\n class SomeClass : public TObject {\n private:\n TClonesArray *fTracks; //->\n ...\n\n\nVariable Length Array, (so that not just the pointer is copied)\n class SomeClass : public TObject {\n Int_t fNvertex;\n ...\n Float_t *fClosestDistance; //[fNvertex]\n\nAll this is explained in detail in 11.3 of the ROOT documentation https://root.cern.ch/root/htmldoc/guides/users-guide/ROOTUsersGuide.html\n\n\n Streamers and doxygenIn the second subsection of this tutorial, you saw that the streamer directives looked a bit different. This is, because we sometimes use member comments in header files for yet another purpose: creating automatic code documentation with Doxygen. Doxygen is a way of documenting your code inside the source code itself, by factoring special comments that will be ignored by the C++ compiler. \nDoxygen uses both //!\n\nPitfalls\nWe started this section out, by saying that the streamer definition can be a source of confusion. Why is this so? \nLet's start by realizing when the streamer definition is actually relevant: this is when objects are written to disk or copied. If you run your analysis locally, your analysis task is (probably) never copied or stored to disk, ergo the streamer information is never used and specifying // or //! are equivalent\nIf you run on Grid, or on the LEGO train system, the situation is different, and the following happens\n\nYour task is initialized locally and added to the analysis manager\nThe manager is stored locally in a .root file\nThis file is copied to grid nodes, invoking the streamer\nAt the grid node, a fresh instance of your task is created\nNon-persistent members are initialized to their default values found\nin the empty I/O constructor (remember that we said in Section 3: you always need to specify an empty I/O constructor for your classes!)\nPersistent members are read from the .root file\n\n Example 1 - 'unexpected' behaviorTake a look at the class below\n class SomeClass : public TObject \n Int_t fAbsEta; //!\n // setter\n SetAbsEta(Float_t eta) {fAbsEta = eta;}\n\n // ROOT IO constructor\n SomeClass::SomeClass() : \n fAbsEta(0) {;}\n\n\nIn your steering macro, you call\n SomeClass->SetAbsEta(3);\nYou now launch your analysis to run on the Grid. What is the value of fAbsEta when the analysis starts to run at a Grid node?\n Click to show answerClick to expandAfter copying (e.g. to grid) the value of fAbsEta = 0. The member is not persistent (//!), so after copying, the value of fAbsEta will be equal to its default value as specified in the I/O constructor of your class.\n\n Example 2 - expected behavior?Now take a look at a second, very similar class:\n class SomeClass : public TObject \n Int_t fAbsEta; //\n // setter\n SetAbsEta(Float_t eta) {fAbsEta = eta;}\n\n // ROOT IO constructor\n SomeClass::SomeClass() : \n fAbsEta(0) {;}\n\nAgain, we call\n SomeClass->SetAbsEta(3);\n\nAnd launch our analysis task on the Grid. What is the value of fAbsEta when your task starts to run on a Grid node? \n Click to show answerClick to expandAfter copying (e.g. to grid) fAbsEta = 3. The member is declared as persistent, so the value it has is retained. \n\nSo you see, that the streamer can have quite an important effect on your analysis!\nRuntime\nWhen you launch your analysis to Grid, it's important to realize that some methods of your analysis task are called on your laptop when you execute your steering macro, whereas other methods are only called on the Grid nodes. The execution on Grid is what we call runtime. \nLooking at the functions of our analysis task, we can e.g. say that \n // constructor: called locally\n AliAnalysisMyTask(const char*);\n\n // function called once at RUNTIME\n virtual void UserCreateOutputObjects();\n\n // functions for each event at RUNTIME\n virtual void UserExec(Option_t*);\n\nIt makes no sense to make data members that are initialized at runtime persistent. Therefore, as a rule-of-thumb, for all your output histograms, use the flag for non-persistence, i.e.\n TH1F* fHistPt; //! pt histo\n\nAutomatic Schema Evolution\nIf you develop your code, the layout of persistent members of your class probably changes, i.e.\nclass Polygon\n{\n private:\n int width;\n}\n\nwhich would take up 4 bytes, could change to \nclass Polygon\n{\n private:\n int width, height;\n}\n\nwhich would take up 8 bytes when written to disk. The ClassDef value of your class bookkeeps this evolution for ROOT and avoids compatibility problems such as\n `The StreamerInfo of class AliAnalysisTaskMyTask\n has the same version (=1) as the active class but a \n different checksum. Do not try to write, ..., \n the files will not be readable.'\nIf you commit your code to AliPhysics (or AliROOT), you should make sure to increment the ClassDef value when you change the list of persistent members, i.e. if we have a class\n class SomeClass : public TObject {\n private:\n Int_t fAbsEta; // min eta value\n ...\n ClassDef(SomeClass, 1);\n\nand we add a persistent member, we have to increment to ClassDef value\n class SomeClass : public TObject {\n private:\n Int_t fMinEta; // min eta value\n Int_t fMaxEta; // max eta value\n ...\n ClassDef(SomeClass, 2);\n\nIf the list of non-persistent members changes, e.g. when we change\n class SomeClass : public TObject {\n private:\n Int_t fAbsEta; //! min eta value\n ...\n ClassDef(SomeClass, 1);\n\ninto \n class SomeClass : public TObject {\n private:\n Int_t fMinEta; //! min eta value\n Int_t fMaxEta; //! max eta value\n ...\n ClassDef(SomeClass, 1);\n\nwe do not have to increment the ClassDef value, because the streamer definition of the class does not change. \n"},"analysis/destructor.html":{"url":"analysis/destructor.html","title":"Destructors","keywords":"","body":"Destructors\nWe are at the end of the manual for writing a task, but we forgot to implement one important aspect of our analysis task: the destructor, copy constructor and assignment operator. Out class dynamically allocates memory (use of the new), for example when we create our histograms\n\n // create our histo and add it to the list\n fHistPt = new TH1F(\"fHistPt\", \"fHistPt\", 100, 0, 100);\n\nThis has two implications:\n\nAfter usage, we are responsible for freeing the allocated memory\n(else itโs lost!)\n\nA bit more advanced: you might have to think about the copy constructor\nand assignment operator \n\n\nImplementing the destructor\nMemory allocated with new cannot be used again, unless it is realased by delete. Never deleting memory is called a memory leak. Leaks are bad: they waste resources and can crash your system, and for that reason, we should implement a destructor\nSuppose we have a constructor that looks like this\n MyClass::MyClass()\n {\n n = new int;\n p = new float;\n x = new float[5];\n }\n\nThe destructor should be\n MyClass::~MyClass()\n {\n delete n;\n delete p;\n delete[] x;\n }\n\nOur life is not so easy however: \n\nWe did not allocate memory in the class constructor but in\nUserCreateOutputObjects\n\nWe might want to free that memory, but what if\nUserCreateOutputObjects was not called? โif it hasnโt, freeing\nthe memory will cause serious problems (the infamous โglibc double\nfree or corruptionโ)\n\nTo avoid this, initialize our pointers to NULL in the member\ninitialization list\n ...\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD(0), fOutputList(0), fHistPt(0)\n {\n // ROOT IO constructor, don't allocate memory here!\n }\n ...\n\n\nWith our pointers initialized to NULL, we can go ahead and write our\ndestructor\n\n AliAnalysisMyTask::~AliAnalysisMyTask()\n {\n if(fOutputList) delete fOutputList;\n }\n\n\nA little trick we applied is\nfOutputList->SetOwner(kTRUE);\nwhich tells the destructor of TList* to delete all objects added to\nit\n\nNote that fAOD is not deleted - this pointer points to memory that\nwas not allocated by our task\n\n\n new - deleteRule of thumb: all calls to new should be accompanied by a call to\ndelete somewhere in your code\n\nDestructors and PROOF\nIf you run on PROOF, your analysis class is not the owner of its output list. A little trick to avoid segmentation violations when running on PROOF is to write\n AliAnalysisMyTask::~AliAnalysisMyTask()\n {\n if(AliAnalysisManager::GetAnalysisManager()->GetAnalysisType()\n != AliAnalysisManager::kProofAnalysis) delete fOutputList;\n }\n\nThis only deletes the output list if youโre not running PROOF. \nCopy constructor and assignment operator\nSometimes in AliRoot code you see copy constructors and assignment operators (these two always go together). In principle, we donโt need them because our analysis class is never copied (apart from the streamer actions, which do not rely on these constructors). However, you might occasionally see compiler warnings such as\n warning: 'class AliAnalysisTaskMyTask' has pointer \n data members but does not override 'AliAnalysisTaskMyTask(const\n AliAnalysisTaskMyTask&)' or 'operator=(const AliAnalysisTaskMyTask&)' \n [-Weffc++]\"\nGenerally, these can be squashed by defining prototypes \n private:\n // not implemented\n AliAnalysisTaskMyTask(const AliAnalysisTaskMyTask&); \n AliAnalysisTaskMyTask& operator=(const AliAnalysisTaskMyTask&);\n\nDefining these functions as private implicates that we do not have provide an implementation. \nSo what does this mean, what are copy constructors and assignment operators, why do I need them, and how can I get them? If you are interested in this, keep reading. \nIn a nutshell:\n MyObject A; // initialization by default constructor\n MyObject B(A); // initialization by copy constructor\n MyObject C = A; // Also initialization by copy constructor\n B = C; // assignment by copy assignment operator\n\nThe copy constructor and assignment operator are automatically generated, but if your class has pointer members, they need to be customized (this is not a ROOT feature, just c++!). \nIf we wanted to implement our own copy constructor for our class, here is what it would look like\n AliAnalysisMyTask::AliAnalysisMyTask\n (const AliAnalysisMyTask& other) : AliAnalysisTaskSE(other),\n fOutputList(NULL), fHistPt(NULL)\n {\n if(other.fOutputList) fOutputList = (TList*)other.fOutputList->Clone();\n if(other.fHistPt) fHistPt = new TH1F(*other.fHistPt);\n }\n\n\nOperating on NULL pointers is not allowed and the code will crash if\nyou attempt to do that\n\nOperating on uninitialized pointers is undefined and much more\ndangerous\n\nThe TH1F and most ROOT histogram classes have public copy\nconstructors, so we can use them\n\nThe TList copy constructor is private, so we need to make a Clone of\nit instead\n\n\nThe assignment operator is very similar to the copy constructor, but it has the additional requirements for checking for self-assignment and returning a value. In our case, it could look like\n AliAnalysisMyTask& AliAnalysisMyTask::operator=\n (const AliAnalysisMyTask& other)\n {\n if(&other == this) return *this;\n outputlist = NULL;\n fHistPt = NULL;\n AliAnalysisTaskSE::operator=(other);\n if(other.fOutputList) fOutputList = (TList*)other.fOutputList->Clone();\n if(other.fHistPt) fHistPt = new TProfile(*other.fHistPt);\n return *this;\n }\n\n"},"analysis/":{"url":"analysis/","title":"Analysis tutorial exercises","keywords":"","body":"Writing a mini-analysis\nIn the following exercises, you will write a very small, but realistic, data analysis from the grounds up. The starting point is a minimal task that fills a histogram with a transverse momentum distribution. This task has already been written for you. As you go along, you will add code to this task, so that in the end, you can run a mini-analysis measuring the centrality dependence of charged pions production at mid-rapidity. \nThese exercises assume that you have read the previous section ('Writing an analysis task'). \nTo access ALICE data and run the analysis on the Grid, you will need to be an ALICE member (a CERN lightweight account does not suffice). When in doubt about this, ask your supervisor. \n"},"analysis/setup.html":{"url":"analysis/setup.html","title":"Step 1 - Setup the tutorial","keywords":"","body":"Obtain your source code\nThe starting point for these exercises is the analysis template called AliAnalysisTaskMyTask. To obtain the source code of this analysis, choose one of the following two options: \n\nClone the Git repository. Programmers use version control systems when developing their code. You will also use version control (in our case through Git) when you are contributing to the ALICE code base. So why not start with Git right now? You can clone the example task repository, which you can find it on here, by typing, in a terminal\n\ngit clone https://github.com/rbertens/ALICE_analysis_tutorial.git\n\nThis will clone the remote repository, so that you have access to a carbon copy of the full repository on your local computer. \n\nA more robust approach to working with Git, is creating a remote fork of a certain repository, and working on this fork. For this, you will need to open a GitHub [https://github.com/] account (which you will need in any case if you want to contribute to ALICE software). If you have a GitHub account, you create a fork of the example task repository by surfing here and clicking on fork at the top right of the screen. If you have forked the repository, you can proceed to cloning it on your laptop in the way as explained in option 1; this then allows you to develop the code, and push commits to your own fork\n\nWhichever approach you chose, the end result should be that you have stored these files on your laptop. One word of caution: the path in which you store these files cannot contain spaces! E.g. /home/my task/ will not work, use /home/my_task/ .\nA first look at your task\nAs a start, just take a look at code that makes up the task:\n\nAliAnalysisTaskMyTask.cxx\n\nAliAnalysisTaskMyTask.h\n\nAddMyTask.C\n\nrunAnalysis.C\n\n\nYou will see that the code is extensively documented. Can you tell\n\nwhich function is called for each event?\n\nwhere are the output histogram defined?\n\nwhere are the output histogram filled?\n\n\nRemember, that for now, the name โAliAnalysisTaskMyTaskโ doesnโt sound so bad, but when you develop a task โin real lifeโ, make sure to give it a meaningful name, that explains what the task is aimed at.\nObtain input data\nTo run your own analysis task, you will also need to download a file that contains reconstructed collisions. This input file is called AliAOD.root, short for Analysis Object Data. In the following steps, will assume that we are looking at Pb-Pb data that was taken in 2015. You can also choose to run on data from a different period or collision system. \nSource your environment\nWe will get the data form the ALICE file catalogue. To access the file catalogue, you will need to use xjalienfs or xalienfs packages and have a valid Grid certificate. This means that, at this point, we will assume that you have built all the ALICE software (see our build manual for that ).\nLoad your ALICE environment as explained here, e.g. by doing\nalienv enter AliPhysics::latest\nYou should see which module files are currently loaded, e.g.\n 1) BASE/1.0\n 2) AliEn-Runtime/v2-19-le-49\n 3) OpenSSL/v1.0.2o-9\n 4) Python-modules/1.0-11\n 5) XRootD/v4.11.1-14\n 6) ROOT/v6-18-04-alice2-1\n 7) boost/v1.70.0-6\n 8) cgal/4.6.3-5\n 9) fastjet/v3.2.1_1.024-alice3-21\n10) Vc/1.4.1-5\n11) xjalienfs/1.0.6-2\n12) JAliEn-ROOT/0.6.0-2\n13) AliRoot/master-1\n14) RooUnfold/V02-00-01-alice4-25\n15) treelite/a7a0839-2\n16) KFParticle/alice-v1.1-1-9\n17) AliPhysics/latest\n12) AliPhysics/latest\nUse alienv list to list loaded modules. Use exit to exit this environment.\nThe module xjalienfs is now available, which is what we will use to get our data. \nGet a valid token (optional)\n JAliEn tokensYou can skip this step if you are using JAliEn. JAliEn clients create the token automatically, but you can still run alien-token-init to refresh it manually.\n\nThe ALICE file catalogue is only accessible if you are an ALICE member. \nIf you are using AliEn-ROOT-Legacy or ROOT5, then you first need to authenticate yourself and obtain a token\nalien-token-init \nwhere username is your CERN username. You should be prompted to provide your PEM pass phrase, which is not the same as your CERN password unless you set them to be the same yourself. \nIf all goes well, you will see something like\n[AliPhysics/latest] ~/sw $> alien-token-init rbertens\n---------------------------------------------------------------\nSetting central config:\n===============================================================\nexport alien_API_SERVER_LIST=\"pcapiserv03.cern.ch:10000|pcapiserv08.cern.ch:10000|\"\nexport TERMINFO=/usr/share/terminfo\n===============================================================\n---------------------------------------------------------------\nSetting closest site to: CERN\n===============================================================\nUsing X509_CERT_DIR=/home/rbertens/sw/slc7_x86-64/AliEn-Runtime/v2-19-le-1/globus/share/certificates\n*********************************************************************************\nAttention: You don't have a valid grid proxy ( or less than 1 hour left ) - doing xrdgsiproxy init for you ...\n*********************************************************************************\nEnter PEM pass phrase:\n++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\nfile : /tmp/x509up_u1000\nissuer : /DC=ch/DC=cern/OU=Organic Units/OU=Users/CN=rbertens/CN=718303/CN=Redmer Alexander Bertens\nsubject : /DC=ch/DC=cern/OU=Organic Units/OU=Users/CN=rbertens/CN=718303/CN=Redmer Alexander Bertens/CN=708532894\npath length : 0\nbits : 512\ntime left : 12h:0m:0s\n++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n=> Trying to connect to Server [1] root://pcapiserv08.cern.ch:10000 as User rbertens \n/alice/cern.ch/user/a/alidaq/\n/alice/cern.ch/user/r/rbertens/\nYour identity: rbertens\nCreating token ..................................... Done\nYour token is valid until: Wed Nov 1 13:21:18 2017\nFor comparison, here is the output from the JAlien alien-token-init\n[AliPhysics/latest] ~ > alien-token-init\nINFO: JAliEn client automatically creates tokens, alien-token-init is deprecated\nDN >>> /C=ch/O=AliEn2/CN=Users/CN=nhardi/OU=nhardi\nISSUER >>> /C=ch/O=AliEn/CN=AliEn CA\nBEGIN >>> 2020-03-26 10:06:05\nEXPIRE >>> 2020-04-26 08:16:48\nOpen the AliEn shell\nYou can now enter the alice environment shell by typing\nalien.py\nOnce you type this command, a the alice environment shell is loaded, and you should see\n[AliPhysics/latest] ~ > alien.py\nWelcome to the ALICE GRID\nsupport mail: adrian.sevcenco@cern.ch\n\nAliEn[nhardi]:/alice/cern.ch/user/n/nhardi/ >\nThe AliEn legacy shell aliensh and JAliEn shell alien.py are very similar. The command prompt for aliensh shell looks like this:\n[AliPhysics/latest] ~/sw $> aliensh\n [ aliensh 1.0.140x (C) ARDA/Alice: Andreas.Joachim.Peters@cern.ch/Derek.Feichtinger@cern.ch]\naliensh:[alice] [1] /alice/cern.ch/user/r/rbertens/ >\nThis shell works a lot like a normal unix shell, but it is not - not all commands that you expect to find are defined. \nMove to the directory where the data we are looking for is stored\ncd /alice/data/2015/LHC15o/000246757/pass1/AOD/002/\nand copy the AliAOD.root file that is inside this folder to your local hard drive by doing\ncp AliAOD.root file:.\nNote the syntax of the copy command, here we tell to copy the remote file AliAOD.root to our own laptop by specifying file:. . \n JAliEn and AliEn shell documentationYou can find more information about the alien.py shell at jalien.docs.cern.ch. Reference documentation for the legacy AliEn shell is available at alien.web.cern.ch.\n\nTrouble ?\nIf for some reason this does not work for you - no fear. You can ask a colleague to provide a file for you, or send a mail to our mailing lists if you are having trouble with access.\n"},"analysis/running.html":{"url":"analysis/running.html","title":"Step 2 - Running the task","keywords":"","body":"Step 2 - Running the task\nIt is now time to run this simple analysis. To run the task, make sure that the ALICE environment is (still) sourced, and type\n$ aliroot runAnalysis.C\nin the folder where you have stored the analysis code. This command launches aliroot (the ALICE extension of the ROOT data analysis framework), and executes the macro โrunAnalysis.Cโ. The macro will\n\ncompile your analysis code\n\nadd your analysis task to the analysis manager\n\nrun the analysis over the input data file that you have provided\n\n\nAs the code starts running, the analysis manager prints some information to your screen, e.g.\n______________________________________________________________________________\n task: name ACTIVE=0 POST_LOOP=0\n INPUT #0: TChain [NO CONTAINER]\n OUTPUT #1: TList -> [MyOutputContainer]\n Container: MyOutputContainer DATA TYPE: TList\n = Filename: AnalysisResults.root folder: MyTask\nI-AliAnalysisManager::SetUseProgressBar: Progress bar enabled, updated every 25 events.\n ### NOTE: Debug level reset to 0 ###\n(class TClass*)0x37637e0\n===== RUNNING LOCAL ANALYSIS AnalysisTaskExample ON TREE aodTree\n(class TClass*)0x37637e0\nInitialization time: 2.69299 [sec]\nE-AliAnalysisManager::GetRunFromAlienPath: Invalid AliEn path string\nI-AliAODInputHandler::Notify: Moving to file AliAOD.root\nProocessing event [=====| ] 525 [ 50.92 %] TIME 00:00:08 ETA 00:00:08\nThis information is useful: you can see what kind of input and output your job is digesting - and, when something is wrong, you will get detailed information on what is going wrong. \nCaveats\nMake sure though, that the macro โknowsโ where you stored the AliAOD.root file on your laptop (if the AliAOD.root file is in a different folder than the analysis source code, open the runAnalysis.C file, and change the lines where the input file is accessed, just search for AliAOD.root ).\nBy default, the macro will run the task just on your laptop. Later on, weโll see how you can run your analysis on Grid.\nThere are some difference between interaction with ROOT5 and ROOT6; a quick ROOT5 to ROOT6 guide can be found here.\nTake a look at the output\nIf all goes well, your simple task runs over the input data, and fills one histogram with the distribution of transverse momentum of all charged particle tracks in all events. \nOnce the task is done running, take a look at the outputfile \nAnalysisResults.root\n that your analysis has generated. The easiest way to do so is to open a TBrowser (ROOTโs โgraphical user interfaceโ) while you are in (ali)root \nnew TBrowser\nand take a look at the distribution in the histogram. No idea how to use a TBrowser, or what a TBrowser even is? Donโt hesitate to ask, and take a look at the ROOT userโs guide.\n"},"analysis/modify.html":{"url":"analysis/modify.html","title":"Step 3 - Modify the task","keywords":"","body":"Step 3\nIf you managed to run the task, congratulations! This is step one towards becoming a professional physicist (no turning back from here ... ) If it didnโt work, ask for help. Also this is a very significant part of becoming a physicist ...\nAt this point, itโs time to expand our task a bit. What we will do is\n\nAdd some event selection criteria\n\nAdd some track selection criteria\n\n\nBut letโs not go too fast.\nThe event loop\nCollisions are referred to as โeventsโ. In our analysis task, the function \nAliAnalysisTaskSE::UserExec\nis called once for each event in the input data set. You never have to explicitly call this function yourself ! Remember, from programming 101 classes, the lecture about inheritance in C++? The UserExec function is called by a base class that you do not have to worry about. We will later see that this function is only called when an event passes your trigger selection. \nFun !\nItโs time to add some code to our task. First, create additional output histograms in which youโll store\n\nThe primary vertex positions along the beam line for all events\n\nJust like the example histogram fHistPt, you have to add these histograms as members of your class. So: create the pointers in the header file, remember to initialize the pointers in your class constructors, and donโt forget to create instances of the histograms in the UserCreateOutput method.\nOne of the trickiest things in programming can be finding out what methods to use out of millions of lines of code. To help you out, here's a line of code to obtain the vertex position along the beam line\nfloat vertexZ = fAOD->GetPrimaryVertex()->GetZ();\n\nYou can of course just copy-paste these lines into your task and hope that it works, but try to think of\n\ndo you understand the logic of these lines?\n\ncan you find out in which classes these methods are defined?\n\n\nTry to run the code again, after youโve added these histograms.\nAll set?\nItโs almost time to run the modified analysis. Not all collisions in the detector are actually usable for physics analysis. Events which happen very far from the center of the detector, for example, are usually not used for analysis (any idea why?). To make sure that we only look at high quality data, we do โevent selectionโ. Letโs add some event selection criteria to your task.\n\nModify the code such that only primary vertices are accepted within 10 cm of detector center. Such selections in the event sample or track sample are usually referred to as โcutsโ. \nGenerally, we want to see how much data we โthrow awayโ when applying a cut. How would you go about doing that?\n\nBesides rejecting data via cuts, we also make data selection while data taking, by โtriggeringโ: selecting collisions in which we expect certain processes to have occurred. You can check which triggers are selected in the AddMyTask.C macro , where we call\n task->SelectCollisionCandidates(AliVEvent::kAnyINT);\nAs you can see, trigger classes are defined in the class AliVEvent. A quick look into the source code of that classt tells us which triggers are available\n enum EOfflineTriggerTypes { \n kMB = BIT( 0), // Minimum bias trigger in PbPb 2010-11\n kINT1 = BIT( 0), // V0A | V0C | SPD minimum bias trigger\n kINT7 = BIT( 1), // V0AND minimum bias trigger\n kMUON = BIT( 2), // Single muon trigger in pp2010-11, INT1 suite\n kHighMult = BIT( 3), // High-multiplicity SPD trigger\n kHighMultSPD = BIT( 3), // High-multiplicity SPD trigger\n kEMC1 = BIT( 4), // EMCAL trigger in pp2011, INT1 suite\n kCINT5 = BIT( 5), // V0OR minimum bias trigger\n kINT5 = BIT( 5), // V0OR minimum bias trigger\n kCMUS5 = BIT( 6), // Single muon trigger, INT5 suite\n kMUSPB = BIT( 6), // Single muon trigger in PbPb 2011\n kINT7inMUON = BIT( 6), // INT7 in MUON or MUFAST cluster\n kMuonSingleHighPt7 = BIT( 7), // Single muon high-pt, INT7 suite\n kMUSH7 = BIT( 7), // Single muon high-pt, INT7 suite\n kMUSHPB = BIT( 7), // Single muon high-pt in PbPb 2011\n kMuonLikeLowPt7 = BIT( 8), // Like-sign dimuon low-pt, INT7 suite\n kMUL7 = BIT( 8), // Like-sign dimuon low-pt, INT7 suite\n kMuonLikePB = BIT( 8), // Like-sign dimuon low-pt in PbPb 2011\n kMuonUnlikeLowPt7 = BIT( 9), // Unlike-sign dimuon low-pt, INT7 suite\n kMUU7 = BIT( 9), // Unlike-sign dimuon low-pt, INT7 suite\n kMuonUnlikePB = BIT( 9), // Unlike-sign dimuon low-pt in PbPb 2011\n kEMC7 = BIT(10), // EMCAL/DCAL L0 trigger, INT7 suite\n kEMC8 = BIT(10), // EMCAL/DCAL L0 trigger, INT8 suite\n kMUS7 = BIT(11), // Single muon low-pt, INT7 suite\n kMuonSingleLowPt7 = BIT(11), // Single muon low-pt, INT7 suite\n kPHI1 = BIT(12), // PHOS L0 trigger in pp2011, INT1 suite\n kPHI7 = BIT(13), // PHOS trigger, INT7 suite\n kPHI8 = BIT(13), // PHOS trigger, INT8 suite\n kPHOSPb = BIT(13), // PHOS trigger in PbPb 2011\n kEMCEJE = BIT(14), // EMCAL/DCAL L1 jet trigger\n kEMCEGA = BIT(15), // EMCAL/DCAL L1 gamma trigger\n kHighMultV0 = BIT(16), // High-multiplicity V0 trigger\n kCentral = BIT(16), // Central trigger in PbPb 2011\n kSemiCentral = BIT(17), // Semicentral trigger in PbPb 2011\n kDG = BIT(18), // Double gap diffractive\n kDG5 = BIT(18), // Double gap diffractive\n kZED = BIT(19), // ZDC electromagnetic dissociation\n kSPI7 = BIT(20), // Power interaction trigger\n kSPI = BIT(20), // Power interaction trigger\n kINT8 = BIT(21), // 0TVX trigger\n kMuonSingleLowPt8 = BIT(22), // Single muon low-pt, INT8 suite\n kMuonSingleHighPt8 = BIT(23), // Single muon high-pt, INT8 suite\n kMuonLikeLowPt8 = BIT(24), // Like-sign dimuon low-pt, INT8 suite\n kMuonUnlikeLowPt8 = BIT(25), // Unlike-sign dimuon low-pt, INT8 suite\n kMuonUnlikeLowPt0 = BIT(26), // Unlike-sign dimuon low-pt, no additional L0 requirement\n kUserDefined = BIT(27), // Set when custom trigger classes are set in AliPhysicsSelection\n kTRD = BIT(28), // TRD trigger\n // Bits 29 and above are reserved for FLAGS\n kFastOnly = BIT(30), // The fast cluster fired. This bit is set in to addition another trigger bit, e.g. kMB\n kAny = 0xffffffff, // to accept any defined trigger\n kAnyINT = kMB | kINT7 | kINT5 | kINT8 | kSPI7 // to accept any interaction (aka minimum bias) trigger\n };\nbut that may be a bit cryptic .. We wonโt have time to cover triggers in detail, but if you have questions, ask - and if you do analysis - make sure that you are using the correct trigger configuration. \n"},"analysis/track.html":{"url":"analysis/track.html","title":"Step 4 -The track loop","keywords":"","body":"Step 4\nIn this exercise we are going to study the particles that are produced in each event. Out end goal is to identify charged pions, but first weโll familiarize ourselves with the analysis code some more.\n\nPlot the pseudorapidity and azimuthal distributions of the particles for all accepted events in a two-dimensional histogram\n\nMake sure that the axis have proper ranges (how large is the detector?) and a reasonable amount of bins\n\n\nIf youโve added this histogram, run the analysis, and look at the two dimensional histogram. Does the distribution make sense?\nTIP\nIf you have no idea how to extract information on tracks (like azimuthal angle, pseudorapidity, etc) from tracks, it can be useful to look in the source file of the track class to see if you find what you need. You can see that the track class if of type AliAODTrack. You can open the header file of that class AliAODTrack.h to see which methods are defined in this class, to give you a flavor\n\n // kinematics\n virtual Double_t OneOverPt() const { return (fMomentum[0] != 0.) ? 1./fMomentum[0] : -999.; }\n virtual Double_t Phi() const { return fMomentum[1]; }\n virtual Double_t Theta() const { return fMomentum[2]; }\n\n virtual Double_t Px() const { return fMomentum[0] * TMath::Cos(fMomentum[1]); }\n virtual Double_t Py() const { return fMomentum[0] * TMath::Sin(fMomentum[1]); }\n virtual Double_t Pz() const { return fMomentum[0] / TMath::Tan(fMomentum[2]); }\n virtual Double_t Pt() const { return fMomentum[0]; }\n virtual Double_t P() const { return TMath::Sqrt(Pt()*Pt()+Pz()*Pz()); }\n virtual Bool_t PxPyPz(Double_t p[3]) const { p[0] = Px(); p[1] = Py(); p[2] = Pz(); return kTRUE; }\n\n virtual Double_t Xv() const { return GetProdVertex() ? GetProdVertex()->GetX() : -999.; }\n virtual Double_t Yv() const { return GetProdVertex() ? GetProdVertex()->GetY() : -999.; }\n virtual Double_t Zv() const { return GetProdVertex() ? GetProdVertex()->GetZ() : -999.; }\n virtual Bool_t XvYvZv(Double_t x[3]) const { x[0] = Xv(); x[1] = Yv(); x[2] = Zv(); return kTRUE; }\nIt can be hard at first to find where members and methods are defined, and what the design of a software package is. An IDE might help you with that. \nTrack selection\nJust as some events are not of fit to do analysis with, some tracks are also not good for looking at certain observables. In addition to โevent cutsโ, we therefore have to apply โtrack cutsโ as well. In ALICE, we usually use a system of predefined track selection criteria, that are checked by reading the filterbit of a track. \n\nCheck in the code where the filterbit selection is done\n\nChange the filterbit selection from value 1 to 128 to 512\n\n\nHow does your eta, phi distribution change, if you run your task again with filterbit 512? What do you think is the cause of the difference? Keep in mind for later, that you will have to choose your filterbit selection wisely, different types of analyses need different track selections. Discuss with your colleagues, working group or supervisor to decide on what would be best for your analysis. \nTIP\n\nIf you ran your task again, you have - most likely - overwritten the output of the previous run, which makes it hard to compare the distributions obtained with the different filterbits - it can be useful to keep all output files you generate on a safe place on your hard drive\n\n... if you keep the files make sure that you will remember which event and track selections you used. In a few weeks, you have probably forgotten which filterbit was set for a certain output file. You can create readme files, or add a histogram as bookkeeping device.\n\n\n"},"analysis/pid.html":{"url":"analysis/pid.html","title":"Step 5 -Particle identification","keywords":"","body":"Step 5\nIn this section, weโll try to identify particles, by using the amount of energy they have lost per distance traveled in the Time Projection Chamber (TPC). Some specific technical information on how to implement this in your task is given at the end of this document, but general steps to follow are explained here. First, the goals. What we want to do is\n\nidentify pions\n\ncheck how โpureโ our pion sample is\n\n\nWeโll do this by looking at the TPC signal, and seeing how well this signal corresponds to the expected signal for a certain particle species. Look at the figure for clarification, you see lines (the expected signal a particle leaves in the TPC, โthe hypothesisโ) and in colors, the actual signals that were deposited.\n\nStart by storing the TPC signals for all charged particles in your events, in a two-dimensional histogram (such as shown in the figure). First follow the โtechnical stepsโ from Sec. 8, and then try to make such a plot.\nHint, you can get this information by doing\nfYour2DHistogram->Fill(track->P(), track->GetTPCsignal());\n\nIf your histogram is empty after running, try using Filterbit 1 rather than 128.\nAs a second step, you identify particles, and store only the TPC signal that corresponds to pions. \nBEFORE YOU START ...\nTo speed things up a bit, the code that you will need for this exercise is given and explained here. It is recommended to read the entire section prior to implementing the methods. \nTo identify particles, you will add an additional task to your analysis, the โPID responseโ task. This task makes sure that parametrizations that we use for e.g. specific energy loss in the TPC are loaded. To add this task to your analysis, open your runAnalysis.C macro, and add the following lines. Make sure that these lines are called before your own task is added to that analysis manager, your task will depend on this task:\n// load the macro and add the task\nTMacro PIDadd(gSystem->ExpandPathName(\"$ALICE_ROOT/ANALYSIS/macros/AddTaskPIDResponse.C\"));\nAliAnalysisTaskPIDResponse* PIDresponseTask = reinterpret_cast(PIDadd.Exec());\n\nthe above code snippet will work under ROOT6. If you are running ROOT5, the lines to use are a bit different:\ngROOT->LoadMacro(\"$ALICE_ROOT/ANALYSIS/macros/AddTaskPIDResponse.C\");\nAddTaskPIDResponse();\n\nAs a second step, youโll have to make some changed to the header of our analysis. First, youโll add another class member, which is a pointer to the AliPIDresponse object that weโll use in our class. To do this, remember how you added pointers to histograms earlier in this tutorial, so add\n\na forward declaration of the type, i.e. โclass AliPIDResponseโ\n\nthe pointer itself, i.e. โAliPIDResponse* fPIDResponse; //! pid response objectโ\n\n\nDonโt forget to add this new pointer fPIDResponse to the member initialization list in your class constructors (in the .cxx files)!\nAfter making changes to the header, you can add the actual identification routine. This will be done in the implementation of the class. You need to go through a few steps:\n\nRetrieve the AliPIDResponse object from the analysis manager;\n\nmake our poiter โfPIDResponseโ point to the AliPIDResponse object;\n\ninclude the header for the AliPIDResponse class, so that the compiler knows how it is defined\n\n\nThe code to do this might be a bit difficult to figure out by yourself, so itโs given here below\nAliAnalysisManager *man = AliAnalysisManager::GetAnalysisManager();\nif (man) {\n AliInputEventHandler* inputHandler = (AliInputEventHandler*)(man->GetInputEventHandler());\n if (inputHandler) fPIDResponse = inputHandler->GetPIDResponse();\n}\n\nDo you understand\n\nwhat happens in each line?\n\nin which function (UserCreateOutputObjects, UserExcec, Terminate, etc) to put this code?\n\n\nNow that weโve retrieved our PID response object, itโs time to use it. To extract information for different particle species, you can use the functions\ndouble kaonSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kKaon);\ndouble pionSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kPion);\ndouble protonSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kProton);\n\nWhat these functions return you, is a probability that a particle is of a certain type, expressed in standard deviations (ฯ\\sigmaฯ) . To identify a particle, weโll require that its PIDresponse signal lies withim 3 standard deviations of the expected signal. To check this, you can write a few lines such as\nif (std::abs(fPIDResponse->NumberOfSigmasTPC(track, AliPID::kPion)) \nPutting what you have read in practice\nUse the code snippets given in the above sections to implement your particle identification routines. If you are confident that can โisolateโ the pions, create new histograms to store the pionโs\n\ntransverse momentum\n\npseudorapidity\n\nazimuthal angle\n\n\nCentrality\nMost heavy-ion analyses report their results in intervals of collision centrality. In order to access collision centrality within your analysis, you will have to add yet another task to the chain of tasks that is called in your run macro. This third task also needs to be executed prior your own task (note, that the procedure for obtaining centrality for run 1 data can be different - when in doubt, ask your supervisor). The task, called AliMultSelectionTask, can be added to the manager using the following instructions:\n TMacro multSelection(gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/COMMON/MULTIPLICITY/macros/AddTaskMultSelection.C\"));\n AliMultSelectionTask* multSelectionTask = reinterpret_cast(multSelection.Exec());\n\nor, using the ROOT5 equivalent\n gROOT->LoadMacro(\"$ALICE_PHYSICS/OADB/COMMON/MULTIPLICITY/macros/AddTaskMultSelection.C\");\n AliMultSelectionTask* multSelectionTask = AddTaskMultSelection(kFALSE);\n\nTo access centrality within your analysis task, you need to obtain a pointer to the AliMultSelection object, and obtain the collision centrality through this object, e.g. by doing\n Float_t centrality(0);\n AliMultSelection *multSelection =static_cast(fAOD->FindListObject(\"MultSelection\"));\n if(multSelection) centrality = multSelection->GetMultiplicityPercentile(\"V0M\");\n\nUsing the above code snippets, can you select pions in 0-10% centrality, and 50-60% centrality? Does the number of pions change in the way you would expect them to change ?\n"},"analysis/MC.html":{"url":"analysis/MC.html","title":"Step 6 -Using Monte Carlo data","keywords":"","body":"Monte Carlo events\nA large fraction of our recorded data is accompanied by simulated events that we call Monte Carlo (MC) productions. Different MC generators, like PYTHIA, DPMJET, and HIJING are used to simulate collisions, after which a detector response is simulated using GEANT. \nThe main reason for analyzing MC events is that it enables the analyzer to calculate efficiency and acceptance corrections specific for their analysis, and study the difference between the true and reconstructed observables. So, in MC, we have by construction more information available. In MC, we can for example just ask the PDG code of the particles in the event, and then verify how well our data analysis performs. \nAccessing MC productions\nFirst, we have to download the MC data. Since we downloaded Pb-Pb data from the period LHC15o with run number 246757, we will download an AOD file from the same run of a MC that is anchored to this period; namely LHC16g1.\nalien.py\ncd /alice/sim/2016/LHC16g1/246757/AOD198/0002/\ncp alien://AliAOD.root file://AliAOD.root\n\n AliEn legacy shellIn case you are using AliEn legacy software please use aliensh instead of alien.py.\nThe syntax in aliensh is slightly different, you should use alien: and file: prefix. For example:\naliensh\ncp alien:AliAOD.root file:AliAOD.root\n\nIt might be useful to rename the file to AliAOD_MC.root to avoid confusion later on. If you do so, of course you have to change the name of the input data file that you specify in runAnalysis.C.\nNow if we don't do anything else and run the analysis, the MC data will be processed as if it was data, and should produce a similar output when compared to real data. But of course we want to and can do more!\nAccessing the MC information\nWe will add a few things to our code to be able to obtain information that is provided directly by the Monte Carlo generator itself (often referred to as 'true level' or 'generator level'). First, we add our new global variable to the header in the list of private objects:\nAliMCEvent* fMCEvent; //! corresponding MC event\n\nThen we add fMCEvent to the constructors\n...\nAliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD(0), fMCEvent(0), fOutputList(0), fHistPt(0)\n{\n...\n\nand\n...\nAliAnalysisTaskMyTask::AliAnalysisTaskMyTask(const char* name) : AliAnalysisTaskSE(name),\n fAOD(0), fMCEvent(0), fOutputList(0), fHistPt(0)\n{\n...\n\nIn UserExec we can now use our new global variable to obtain the MC event through the MCEvent method\nfMCEvent = MCEvent();\n\nNow let's use the information by creating a new function that loops over the MC particles:\nin the header file we declare our new function ProcessMCParticles\nvoid ProcessMCParticles();\n\nThen we put the implementation in the .cxx file:\nvoid AliAnalysisTaskMyTask::ProcessMCParticles()\n{\n // process MC particles\n TClonesArray* AODMCTrackArray = dynamic_cast(fInputEvent->FindListObject(AliAODMCParticle::StdBranchName()));\n if (AODMCTrackArray == NULL) return;\n\n // Loop over all primary MC particle\n for(Long_t i = 0; i GetEntriesFast(); i++) {\n\n AliAODMCParticle* particle = static_cast(AODMCTrackArray->At(i));\n if (!particle) continue;\n cout GetPdgCode() \nFinally we call our newly created function in UserExec:\nif(fMCEvent) ProcessMCParticles();\n\nYou can run the code and enjoy the list of PDG code values of each particle in the MC event... although it might be more useful to fill a histogram with the values instead of printing them to the terminal.\n"},"analysis/grid.html":{"url":"analysis/grid.html","title":"Step 7 -Run your code on GRID","keywords":"","body":"Step 7\nIs your pion analysis running smoothly on your laptop? If yes, then it is time to 'scale things up' a bit. We will run your task on the Grid. \nThe macro\nrunAnalysis.C\nthat you used in the previous exercises already contains all the information that you need for running on the Grid. In fact, all that you have to do is open it, and make a minor change at the start of the macro\nvoid runAnalysis()\n{\n // set if you want to run the analysis locally (kTRUE), or on grid (kFALSE)\n Bool_t local = kFALSE;\n // if you run on grid, specify test mode (kTRUE) or full grid model (kFALSE)\n Bool_t gridTest = kTRUE;\nNote that we will first test if our code is actually 'grid compatible', by simulating a Grid node on our computer. Before you launch this test, browse through the runAnalysis.C macro and try to convince yourself of the fact that you understand the logic, and whether or not the configuration makes sense.\nRunning a Grid test\n AliEn-ROOT-Legacy tokens In case you are using AliEn-ROOT-Legacy, for instance with ROOT5, then you should first create an access token using command alien-token-init.\n\nIf you think everything is OK, and run the Grid test by simply launching the runAnalysis macro\naliroot runAnalysis.C\nYou will notice that the running time for the task is now probably a bit longer, as we have to wait for data to be retrieved. Does your analysis run fine? If it exits without problems, make sure to check your histograms and see if the output is as you expected it to be !\nLaunching your job on Grid\nIf the Grid test was successful, you can launch your analysis on Grid. Set the flag โgridTestโ in your macro to kFALSE,\nvoid runAnalysis()\n{\n // set if you want to run the analysis locally (kTRUE), or on grid (kFALSE)\n Bool_t local = kFALSE;\n // if you run on grid, specify test mode (kTRUE) or full grid model (kFALSE)\n Bool_t gridTest = kFALSE;\nand relaunch your analysis. \nMonitoring your jobs\nOnce you have submitted your job to Grid, you can track the progress at https://alimonitor.cern.ch/users/jobs.jsp. You will need your digital certificate to get access to the job pages!\nMerging your job's output\nOnce your jobs are all in done, it is time to merge the output files that were generated on the independent Grid nodes into one output file that is on your laptop. We will do this in two stages\n\nMerge all the output files that were generated by one masterjob into one output file that is still stored on the Grid\nMerge these 'master' output files into one output file on your laptop. \n\nNote that, since we only launched one masterjob, these two steps may seem a bit silly here. However, if you launch multiple masterjobs, this approach is very useful. \nMerging: step 1\nTo perform step 1 of the merging, open the runAnalysis.C macro again, and change the argument of SetRunMode() into terminate\nalienHandler->SetRunMode(\"terminate\")\nafter you have made this change, you have to launch your job again. The job that you are now launching is a merging job: an instruction send to the grid nodes to combine the independent AnalysisResults.root files of sub-jobs into one merged file per master-job. \nJust as with a normal job, you can monitor the progress of the merging job via https://alimonitor.cern.ch/users/jobs.jsp. \nMerging: step 2\nOnce the merging job is finished, you will need to retrieve the final output on your laptop. One more change to your runAnalysis.C macro needs to be made. Open the file, and set\nalienHandler->SetMergeViaJDL(kFALSE);\nThen, launch the macro again. If all goes well, it should proceed to merge the output of the merging jobs into one final output file on your laptop. \nHappy analyzing ! \n"},"analysis/bonus.html":{"url":"analysis/bonus.html","title":"Bonus content","keywords":"","body":"Bonus contents\nMinimal systematics\nAs you can see in the figure, the TPC signals of different particle species cross each other. In\nthese regions, it is difficult (or impossible) to identify particles. Because of this ambiguity,\nwe have to estimate what the uncertainty on our identification routine is.\n\nRun the main code multiple times, varying the number of standard deviations that you require the signal to be in from 3 to 4, and from 3 to 2.\n\nHow do your spectra change? Do these changes make sense to you?\n\n\nIf you are very enthusiastic,\n\nTry to estimate the systematic uncertainty that particle identification introduces to your measurement.\n\nMake it presentable\nBy now, you have made quite a few nice plots. Modify the code such that the labels, titles, markers, colors, legends of your plots look decent and presentable for fellow colleagues\n\nDid you know that you can use LaTeX in ROOT? This comes in handy when you are labeling axes, etc.\n\nStore one or two of your pictures. You can store them as ROOT files, macros, or as graphics.\nAlways use vector graphics (.ps, .pdf)!\n\nNever be afraid to make titles and axis labels larger, itโs better if things look a bit\n\"cartoonish\" than when half of the collaboration cannot read whatโs on your plots - especially\nwhen they are broadcast or projected\n\n\nIn practice, we usually donโt use the TBrowser for \"postprocessing\", but write dedicated code that opens our AnalysisResults.root files, does some final calculations, and makes our plot pretty.\n"},"analysis/hints.html":{"url":"analysis/hints.html","title":"Some hints","keywords":"","body":"AliRoot and AliPhysics documentations\nThe Doxygen documentation of AliROOT and AliPhysics is available here http://alidoc.cern.ch/ . It is generated daily.\nCleaning up and improving your code\n\nOne of the most important things you can do is make sure your code\nis readable\n\nThis means using whitespace freely, consistent indentation,\netc\n\nThis is valid C++ code:\n\n\n for(int i=0;i\nbut it looks bad\n\nThis is C++ code equivalent to that:\n\n for(int i=0; i\nand it looks much **better**\n\nThere are no wrongs or rights, but be consistent\n\nFault tolerance\n\nCheck e.g. the snippet\n\n for(Int_t i(0); i (fAOD->GetTrack(i));\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n\n\nWe can build in fault tolerance:\n\n for(Int_t i(0); i (fAOD->GetTrack(i));\n if(!track) continue;\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n\n\nFinally, itโs a very good idea to comment your code\n\nComments improve readability and maintainability\n\nComments should be useful, though, and comments that are overly\nobvious can be avoided\n\n\n // no comment: bad\n a++;\n\n // pointless comment, also not so good\n\n a++; // adding 1 to a\n\n\n // descriptive comment, very good\n\n a++; // adding 1 to a to make a point during a tutorial\n\n\nItโs also a good idea to document your code as youโre writing it -\nyou will forget how it works and no-one will continue with\nuncommented tasks\n\n"},"analysis/ROOT5-to-6.html":{"url":"analysis/ROOT5-to-6.html","title":"Transition from ROOT5 to ROOT6","keywords":"","body":"Transition from ROOT5 to ROOT6\nROOT6 is similar to ROOT5: It comes with the same library of classes (base\nclasses, histogram classes like TH1, ...) which share the same interface as under\nROOT5. It provides a command line interface as ROOT5, and runs macros just\nlike under ROOT5. Therefore it is possible to build and run the ALICE\nsimulation, reconstruction and analysis framework under ROOT6. AliPhysics can be\nbuilt against ROOT6 in the following way:\naliBuild -z --defaults o2 build AliPhysics\n\nIf you have aliBuild v1.12.0 or later, you don't need to specify --defaults o2.\nFor classes in AliRoot or AliPhysics this transition is transparent. For code in\nmacros there are however a few difference. This page tries to summarize the\ndifferences in behaviour observed so far and gives some suggestions how to solve\nthese issues so work can go on smoothly under ROOT6.\nWhat is a just-in-time compiler?\nFor the command line interface and running macros ROOT5 uses CINT, which is an\ninterpreter for C/C++. An interpreter processes a macro line-by-line. It depends\non the implementation of the interpreter how C++ code will be handled and how\nclose the interpretation comes to the language standard. ROOT5 allows for some\ndeviations from the language standards, which means that some coding errors\nwhich would thrown by a compiler leading in a break of the compilation are still\ntolerated by ROOT5. Furthermore the standard library is not fully supported as\nits handling has to be implemented into the compiler. Macro can however also be\nrun in the compiled mode by ROOT5 (adding a \"+\" to the macro name). In this case\nROOT calls an external compiler to compile the macro to a library which is loaded\ninto ROOT. Once the macro runs in compiled mode it is expected to be fully\ncompatible with the C++ standard and coding error free as the compiler will not\ntolerate compiler errors.\nIn contrast to this ROOT6 uses a just-in-time compiler called cling. A\njust-in-time compiler translates each statement, no matter whether it is a single\ncommand or a complicated macro, into machine code as it would be a program and\nonly afterwards runs this piece of code. In order to translate code into machine\ncode the compiler must know how to translate every single line. Based on powerful\ncompiler library this means for ROOT6 that all macro must comply to 100% with\nthe C++ language standard, and exceptions will not be tolerated. Furthermore this\nalso means that all symbols and objects must be known at compile time. This has\nthree side effects:\n\nLoading Functions with gROOT->LoadMacro(...);: This function loads all\nfunctions it finds within the macro into ROOT during run time. For an interpreter\nthis is sufficient as the functions are used after they are loaded. However the\ncompiler must know all symbols used in a macro at compile time.\nLoading libraries with gSystem->Load(...);: Here we have the same problem:\nThe symbols in the libraries must be known before they are used.\nCompiling ALICE analysis tasks on the fly with gROOT->LoadMacro(\"...+\");:\nAs the analysis task compiled like this will be converted in a library it must be\nknow to the just-in-time compiler before.\n\nFor all three cases exist workarounds which will be discussed in the next\nsections. In general macros which were running under ROOT5 in the compiled mode\nwill also run under ROOT6. Macros which were running only in the interpreted\nmode might contain coding errors which were not handled by ROOT5 and might\ntherefore need fixes. However the just-in-time compiler will give precise error\nmessages leading exactly to the lines which need fixes.\nHow can I call macros inside macros?\nCalling macros inside macros is a bit tricky as the result of a macro will be\navailable only at runtime. There are however several workarounds which cover the \nmost common use cases:\n\nUsing ROOT's TMacro:\nTMacro is a wrapper class around the macro processing. It is constructed with\nthe macro path. The macro is run using TMacro::Exec. The result of\nTMacro::Exec() is a number representing an address in memory where to\nfind the resulting object. This has to be cast into a pointer to an object of\nthe expected type. Example:\nTMacro physseladd(gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/macros/AddTaskPhysicsSelection.C\"));\nAliPhysicsSelectionTask *physseltask = reinterpret_cast(physseladd.Exec());\n\nThe macro is still evaluated at runtime, however with the reinterpret_cast to\nAliPhysicsSelectionTask * we tell ROOT that the result of the macro\ninterpretation must be of type AliPhysicsSelectionTask *, so the type is known\nat compile time. TMacro::Exec optionally gets a string representation of the\nfunction arguments. This might be a bit complicated to handle, particularly if\nthe arguments are dynamic and change at run time. The method works both for\nROOT5 and ROOT6.\n\nUsing gROOT/gInterpreter->ProcessLine: \nMacro execution can be launched as well via gROOT->ProcessLine() /\ngInterpreter->ProcessLine(). As with TMacro this method is focused on running\na macro and not loading content from it. The ProcessLine method returns a\nlong number representing an address in memory where to find the output objects.\nThis number has to be cast to the expected output type using a\nreinterpret_cast in order to access the content of the output objects. The\nfollowing example runs the add macro for the physics selection task:\nAliPhysicsSelectionTask *physseltask = reinterpret_cast(gInterpreter->ProcessLine(Form(\".x %s\", gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/macros/AddTaskPhysicsSelection.C\"))))\n\nAdding function arguments is possible here as well as a simple string\nrepresentation after the macro path, surrounded with (). This method also works\nboth under ROOT5 and ROOT6.\n\nIncluding macros:\nAs ROOT6 compiles the macro it is possible to include macros and treat them\nas if they were header files. In order for this to work it is essential to tell\nROOT before where to find the macro. This can be done using the preprocessor\nmacro R_ADD_INCLUDE_PATH(...). For the just-in-time compiler macros\nincluded will look as if they were part of the code itself. The following macro\nruns under ROOT6:\n#ifdef __CLING__\n// Tell ROOT where to find AliRoot headers\nR__ADD_INCLUDE_PATH($ALICE_ROOT)\n#include \n\n// Tell ROOT where to find AliPhysics headers\nR__ADD_INCLUDE_PATH($ALICE_PHYSICS)\n#include \n#endif\n\nvoid simpleaddtest(){\n AliAnalysisManager *mgr = new AliAnalysisManager;\n\n // Take function from macro AddESDHandler\n // no gROOT->LoadMacro for ROOT6\n AddESDHandler();\n\n AliPhysicsSelectionTask *test = AddTaskPhysicsSelection(kTRUE);\n\n mgr->InitAnalysis();\n mgr->PrintStatus();\n}\n\nIn particular when passing arguments to the macro (in the example above passing\nkTRUE to AddTaskPhysicsSelection) this method is very convenient. This method\nis specific to ROOT6. The part including macros has to be protected (see\nbelow).\n\n\nDo I need to include header files in my macros?\nROOT6 comes with a technique called pre-compiled header files. Header files\nfrom a certain library are compiled to a binary format by rootcling, the\nsuccessor of rootcint, and loaded into ROOT6 by an auto-loading mechanism\nsimilar to the rootmap mechanism. Once rootcling is invoked with the\nargument -rml name a .pcm-file is created containing the pre-compiled\nheaders. ROOT6 will search for .pcm-files in the LD_LIBRARY_PATH.\nThe following packages in ALICE provide .pcm support:\n\nAliRoot\nAliPhysics\nRooUnfold\nFairRoot\no2\n\nFor libraries providing .pcm-support NO headers should be included in macros.\nFor libraries handled by the user make sure to\n\nrun rootcling with the arguments -rmf for the .rootmap file\nand -rml for the .pcm file\nInstall both the .rootmap and the .pcm file of your library path in the \nlibrary location (usually PROJECT_PATH/lib)\n\nI get a huge amount of errors, and my macro doesn't run. What can I do?\nHere are few examples that commonly appear in user macros and which are tolerated by ROOT5 but not anymore by ROOT6:\n\nUndefined symbols:\nMaybe you have something like this in your code:\ntaskname = \"mytask\";\n\nThe variable taskname was not defined before. It was implicitly defined in ROOT5 as const char *. In ROOT6 this leads to the error\nerror: use of undeclared identifier 'taskname'\nThe variable taskname must be defined with a type before a value can be assigned. In this case the proper code would be\nconst char *taskname = \"mytask\";\n\nThanks to C++11 ROOT6 can also detect the type implicitly using the keyword\nauto. In this case the code looks the following:\nauto taskname = \"mytask\";\n\nThis will however not be transparent to ROOT5 as ROOT5 doesn't understand\nC++11.\nNote: On the command line ROOT6 automatically adds the auto keyword. The \nstatement above will be possible in the interpreted mode of ROOT6.\n\nMissing forward declarations\nConsider this macro:\nvoid fail_forward() {\n int result = test(2,4);\n printf(\"2 + 4 = %d\\n\", result);\n}\n\nint test(int a, int b) {\n return a + b;\n}\n\nUnder ROOT5 this macro will run, but under ROOT6 it will raise the following compiler error:\nerror: use of undeclared identifier 'test'\nThe function test is defined, but after it is used. In ROOT5 this is\nno problem: During interpretation the interpreter loads all functions. But\nunder ROOT6 the macro is compiled, and now the order matters: Functions need\nto be declared before they are used. Adding a forward declaration is \nsufficient in order to make the macro working. The following version of\nthe macro will run also under ROOT6:\nint test(int a, int b);\n\nvoid run_forward() {\n int result = test(2,4);\n printf(\"2 + 4 = %d\\n\", result);\n}\n\nint test(int a, int b) {\n return a + b;\n}\n\n\nHandling of pointer and objects:\nROOT5 does not enforce using the proper access operator for objects, pointers and\nreferences, but will allow the usage of the operator -> for\nreferences and the operator . for pointers. ROOT6 distinguishes\nbetween them, and consequently the proper access operator needs to be used.\nConsider the following macro:\nvoid fail_access(){\n TH1F *ptr = new TH1F(\"ptr\", \"ptr\", 1, 0., 1.);\n ptr.SetTitle(\"test1\");\n printf(\"Title 1: %s\\n\", ptr.GetTitle());\n\n TH1F obj(\"obj\", \"obj\", 1, 0., 1.);\n obj->SetTitle(\"test2\");\n printf(\"Title 2: %s\\n\", obj.GetTitle());\n}\n\nConsequently the wrong access operator is used. ROOT5 will warn about the\nincorrect access operator, but it will run the macro. Trying this under ROOT6\nends in the following errors:\n...: error: member reference type 'TH1F *' is a pointer; did you mean to use '->'?\nptr.SetTitle(\"test1\");\n ~~~^\n ->\n...: error: member reference type 'TH1F *' is a pointer; did you mean to use '->'?\n printf(\"Title 1: %s\\n\", ptr.GetTitle());\n ~~~^\n ->\n...: error: member reference type 'TH1F' is not a pointer; did you mean to use '.'?\n obj->SetTitle(\"test2\");\n ~~~^~\n .\n...: error: member reference type 'TH1F' is not a pointer; did you mean to use '.'?\n printf(\"Title 2: %s\\n\", obj->GetTitle());\n ~~~^~\n .\n\n\nI get a huge amount of unknown symbols from classes in AliRoot or AliPhysics? Do I still need to include header files?\nIn case the compilation of a macro under ROOT6 fails libraries and pre-compiled\nheaders from external packages are not loaded. The consequence is that ROOT6\ndoes not know about these classes and will raise errors about unknown symbols.\nOnce all the initial compiler errors are fixed (usually at the very top of\nthe error log), the next time the macros are compiled ROOT6 will also load the\nlibraries and .pch files from external libraries and the errors disappear. Header\nfrom ALICE libraries should NOT be included.\nHow do I distinguish between ROOT5 and ROOT6 in my macros?\nSometimes macros require different treatment for ROOT5 and ROOT6. It is then\nnecessary to know which ROOT version is used while the macro is running.\nROOT5 defines the preprocessor macro __CINT__, which can be used to check\nwhether one is in an interpreter session. In current (up to at least v6-12-04)\nhowever also ROOT6 exports __CINT__, so this macro cannot be used to\ndistinguish between ROOT versions.\nROOT6 in addition __CLING__ which is not present in ROOT5. The following lines \nindicate how to run ROOT5/ROOT6 specific code:\n#if defined(__CLING__)\n // ROOT6-specific code here ...\n#elif defined(__CINT__)\n // ROOT5-specific code here ...\n#endif\n\nI heard TF1 has changed fundamentally. Is there something to be aware of?\nTF1 is based on TFormula for the formula representation. TFormula got a heavy\nchange: In ROOT5 formulas were always interpreted on-the-fly. With ROOT6 they\nare compiled by the just-in-time compiler. While this leads to a significant\nspeedup in particular when the formula is evaluated multiple times (in fit\nprocedures for example) it comes on cost of breaking backward compatibility, for\nwhich reading TFormula/TF1 object created with ROOT6 with ROOT5 will lead to\nerrors. For what concerns TFormala a ROOT5-compatible version has been added to\nROOT6 as ROOT::v5::TFormula, however something similar does not exist for\nTF1. In order to read a TF1 object from a ROOT file under ROOT5 it has to be\ncreated under ROOT5.\nNow my macro finally works under ROOT6. Will it still work under ROOT5?\nIt depends whether the macro now contains something which ROOT5 does NOT\nunderstand.\n\nROOT6 is fully compatible with C++11. In ROOT5 C++11 support is not\nimplemented, but the standard C++98 is used. C++11-specific code will not\nbe understood.\nAll NEW features provided by ROOT6 are of course not ported to ROOT5.\nThis in particular affects:\nTTreeReader\nTProcPool\nTDataFrame\n...\n\n\nStandard library support in ROOT5, while it comes out-if-the-box in ROOT6.\nIf the macro should run under both ROOT versions consider ROOT containers\ninstead.\nIf your classes write stl-containers containing ROOT-objects to a ROOT-file \nthey must be declared to ROOT5 in your LinkDef.h file. Example:#pragma link C++ class std::vector+;\n\nFor ROOT6 this is not necessary.\n\n\n\n"},"rivet/rivet-tutorial.html":{"url":"rivet/rivet-tutorial.html","title":"Rivet","keywords":"","body":"Rivet in ALICE\nIn this tutorial, we will go through the ALICE documentation on Rivet. You can follow the examples yourself.\nFor past recorded tutorials on Rivet, follow the link to the Analysis tutorial: https://alice-analysis.web.cern.ch/content/tutorials.\n"},"rivet/getting-started.html":{"url":"rivet/getting-started.html","title":"Getting started with Rivet","keywords":"","body":"Getting started with Rivet\nOverview\nRivet (Robust Independent Validation of Experiment and Theory) is a generator-agnostic framework to replicate analyses performed on experimental data on the output of Monte Carlo event generators. The latter are interfaced through event records written in the HepMC format. Rivet reads these input data and reproduces the selected analysis as well as produces comparison plots to the published data.\nAnalyses for Rivet are implemented as plugins, the official ones being distributed together with Rivet. This design allows for the easy implementation and usage of new analysis even before they become official. Each plugin needs to contain the required information to reproduce the analysis, to produce the comparison plots, and the required references for documentation. The detailed content of a plugin is explained below.\nAnalysis plugin\nAn analysis plugin can be distributed with Rivet or added on-top of a Rivet installation (e.g. for local development). It always comprises the following elements:\n\nidentifier: __I (for older analyses the SPIRES ID was used)\ntitle\ndescription:\nshort summary of the analysis content collision system and energies \nreference to paper \nstatus: preliminary, unvalidated, validated, obsolete, \\dots\n\n\ncode:\ncode to reproduce the analysis on Monte Carlo output\n\n\ndata:\nmeasured data points and uncertainties\n\n\n\n"},"rivet/rivet-in-alice.html":{"url":"rivet/rivet-in-alice.html","title":"Using Rivet in ALICE","keywords":"","body":"Using Rivet in ALICE\nRivet has been integrated into the ALICE build system and is maintained there. Thus, it is also deployed to cvmfs, from where it can be used by Grid workernodes, interactive lxplus sessions, or other machines using software from cvmfs (e.g. CERN Linux desktops). It can also be installed locally using aliBuild. However, if you just get started and want to gain experience with Rivet, we recommend to use the cvmfs installation on lxplus, as this is maintained centrally and known to work (if it is not, please report!).\nUsing Rivet on lxplus\nIn order to use Rivet on lxplus, you just have to logon and use alienv to enter a shell with the proper environment loaded (same procedure as for AliPhysics):\nssh lxplus.cern.ch\nalienv enter Rivet\n\nYou can then check which packages and versions are loaded using:\nalienv list\n\nNow you have all the rivet tools (rivet, rivet-build, ...) available. To list the available analyses (those distributed with the used version of Rivet), you can use:\nrivet --list-analyses\nrivet --list-analyses ALICE_\n\nwhere the second command only lists analyses for ALICE publications. You can display the details of one of these analyses (here ALICE_2010_S8625980) using:\nrivet --show-analysis ALICE_2010_S8625980\n\nAssuming you have some output from a Monte Carlo generator in a HepMC file (e.g. /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc or see here for instructions on running MC generators), you can run an analysis (e.g. ALICE_2010_S8625980) on this input using:\nrivet -a ALICE_2010_S8625980 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\nwhere -a is used to specify the analysis you want to run (you can use any analysis that was distributed with Rivet). You can also list more than one analysis.\n BewareBeware the absence (!) of extension of your analysis name specified at the rivet command, i.e. no \"rivet -a ALICE_2010_S8625980.cc ...\". This would make your analysis not recognisable by Rivet, and it will complain so.\n\nThe command line above runs the analysis on the given input (~1000 generated events, here) and stores the produced output, typically histograms, in the file Rivet.yoda. Based on this yoda file, you can produce plots by running:\nrivet-mkhtml Rivet.yoda\n\nThis command puts the plots in the subdirectory rivet-plots/. The directory also contains an index.html, which you can open in a browser to look and navigate through the plots. If you have run Rivet on an lxplus node you probably must copy this directory to your local PC and then point your browser to the directory, i.e.\nscp -r lxplus.cern.ch:/rivet-plots /tmp/myRivetPlots\nopen /tmp/myRivetPlots/index.html (on Mac OS X, otherwise point browser to file:///tmp/myRivetPlots/index.html)\n\n N.B.If on lxplus you use a directory under /tmp you have to copy from the exact host you are working on instead of lxplus.cern.ch, e.g. lxplus012.cern.ch. You can get actual name of the hosting machine with hostname.\nWe recommend not to use direclty the directory /tmp to avoid clashes with other user. Please use /tmp/ to follow this tutorial even if stated differently.\n\nRunning Rivet together with a generator\nYou can use Rivet to run on the output of an arbitrary generator for which an interface to HepMC exists - e.g. those which have been integrated into the ALICE build system and are, thus, available on cvmfs or for local installation. There are two common options to run the generator and Rivet:\n\nintermediate file:\nrun generator writing to hepmc file\nrun Rivet reading from hepmc file (see example above)\n\n\nFIFO (first-in-first-out pipe, on Linux)\ncreate FIFO (NB: not possible on afs, need to use /tmp on lxplus)\nrun generator writing to FIFO (process won't finish)\nrun Rivet reading from FIFO\n\n\n\nThe latter option avoids writing a file to disk and is beneficial if the generator is fast. You can run a generator directly or use aligenmc after you have set it up with:\nalienv enter AliGenerators\n\nThen, you would have to do something like:\nmkfifo /tmp/$USER/fifo_$UID.hepmc\naligenmc -g pythia8 -E 7000 -N 10000 -o /tmp/$USER/fifo_$UID.hepmc &> /tmp/$USER/aligenmc_$UID.log &\nrivet -a ALICE_2010_S8625980 /tmp/$USER/fifo_$UID.hepmc\nrm /tmp/$USER/fifo_$UID.hepmc\n\n Notealigenmc is the script developed within ALICE that does the running of a chosen generator, with a dedicated configuration file, and writing the output to the specified file/FIFO.\nFor further instructions on how to run different generators, see:\n\naligenmc -h\nMC generator documentation\n\n\n Pythia8/Angantyraligenmc is not yet updated to generate heavy-ion collisions with the Pythia8/Angantyr model. In case you want to generate Pb-Pb collisions with Pythia8/Angantyr model you can \nrun-pythia -n 100 -e 2760 -o /tmp/$USER/fifo_$UID.hepmc -c \"Beams:idA 1000822080\" -c \"Beams:idB 1000822080\" -c \"HeavyIon:SigFitNGen = 0\" -c \"HeavyIon:SigFitDefPar = 12.32,1.63,0.19,0.0,0.0,0.0,0.0,0.0\" \n\nBeware that this line is valid only for Pb-Pb 2.76 TeV collisions. Should you need to change the collision energy (the the beams), make sure you run only the initial part\nrun-pythia -n 100 -e 2760 -o /tmp/$USER/fifo_$UID.hepmc -c \"Beams:idA 1000822080\" -c \"Beams:idB 1000822080\"\n\n\n"},"rivet/implementing-rivet-analysis.html":{"url":"rivet/implementing-rivet-analysis.html","title":"Implementing a Rivet analysis","keywords":"","body":"Implementing a Rivet analysis\nIn order to implement a new analysis, you can start from a template created by the Rivet tools. Best start in a new directory for the implementation and create the template therein:\nmkdir myRivet\ncd myRivet\nrivet-mkanalysis \n\nwhere ID specifies the identifier of the analysis. If you are aiming for an official analysis, you should use the proper identifier; if you are just testing, you can use essentially what you want. If you use an identifier referring to a published analysis, e.g. ALICE_2011_I1080735, you automatically get the reference data (taken from HepData) and the metadata (taken from spires/inspire) for this analysis.\nIn the next step, you \"just\" have to add the missing bits and pieces to the template. In more detail, the rivet-mkanalysis command will give you a bunch of files, amongst others a cc-file for the implementation of the analysis. This cc-file contains already the required class and the mandatory methods:\n\ninit\nanalyze\nfinalize\n\nwhich you still have to fill with useful content, of course. We will explain the required implementations in more details below, the template (for an assumed analysis ALICE_2016_test) contains:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/FinalState.hh\"\n#include \"Rivet/Projections/FastJets.hh\"\n#include \"Rivet/Projections/DressedLeptons.hh\"\n#include \"Rivet/Projections/MissingMomentum.hh\"\n#include \"Rivet/Projections/PromptFinalState.hh\"\n\nnamespace Rivet {\n\n\n /// @brief Add a short analysis description here\n class ALICE_2016_test : public Analysis {\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2016_test);\n\n\n /// @name Analysis methods\n ///@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Initialise and register projections\n\n // The basic final-state projection:\n // all final-state particles within\n // the given eta acceptance\n const FinalState fs(Cuts::abseta 20*GeV;\n DressedLeptons dressed_leps(photons, bare_leps, 0.1, lepton_cuts);\n declare(dressed_leps, \"leptons\");\n\n // Missing momentum\n declare(MissingMomentum(fs), \"MET\");\n\n // Book histograms\n // specify custom binning\n book(_h[\"XXXX\"], \"myh1\", 20, 0.0, 100.0);\n book(_h[\"YYYY\"], \"myh2\", logspace(20, 1e-2, 1e3));\n book(_h[\"ZZZZ\"], \"myh3\", {0.0, 1.0, 2.0, 4.0, 8.0, 16.0});\n // take binning from reference data using HEPData ID (digits in \"d01-x01-y01\" etc.)\n book(_h[\"AAAA\"], 1, 1, 1);\n book(_p[\"BBBB\"], 2, 1, 1);\n book(_c[\"CCCC\"], 3, 1, 1);\n\n }\n\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Retrieve dressed leptons, sorted by pT\n vector leptons = apply(event, \"leptons\").dressedLeptons();\n\n // Retrieve clustered jets, sorted by pT, with a minimum pT cut\n Jets jets = apply(event, \"jets\").jetsByPt(Cuts::pT > 30*GeV);\n\n // Remove all jets within dR 5*GeV && Cuts::abseta (event, \"MET\").missingPt() fill(bjets[0].pT()/GeV);\n\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n\n normalize(_h[\"XXXX\"]); // normalize to unity\n normalize(_h[\"YYYY\"], crossSection()/picobarn); // normalize to generated cross-section in fb (no cuts)\n scale(_h[\"ZZZZ\"], crossSection()/picobarn/sumW()); // norm to generated cross-section in pb (after cuts)\n\n }\n\n ///@}\n\n\n /// @name Histograms\n ///@{\n map _h;\n map _p;\n map _c;\n ///@}\n\n\n };\n\n\n DECLARE_RIVET_PLUGIN(ALICE_2016_test);\n\n}\n\nRivet usually does not use a separate header file for the implementation of the main class of the analysis (you can add further classes and headers if the analysis gets more complex). When extending the code for the Rivet plugin, be careful to follow Rivet coding conventions (which are different from the ALICE ones) such that the analysis can eventually be submitted to the Rivet team for integration into the official distribution.\nYou can already try and compile the plugin at this stage to make sure that the setup and preparations are correct:\nrivet-build RivetALICE_2016_test.so ALICE_2016_test.cc\n\nwhich builds the shared library RivetALICE_2016_test.so to be used by Rivet.\nRequired member variables and methods\nFor the plugin to do something useful, you need to add code in a few places. The basic steps are usually very straight-forward.\nmember variables\nYou can add member variables in the private section (below the Analysis methods section). They should follow the naming conventions of Rivet. This is the place where you add the pointers for histograms, profiles, etc. There are special Rivet structures for such pointers which should be used:\nHisto1DPtr _h_0000; // for a histogram\nProfile1DPtr _h_0001; // for a profile\n\nOf course, you can also add variables of your own, e.g. to define pt/rapidity ranges, jet radii, ...\ninit\nThe code in this method is run once at the beginning of the run. It is used to set up the analysis.\nHere, you have to book the histograms (using the previously added pointers). When implementing a published analysis, the preferred way to book the histograms is to let Rivet take the histogram details from the reference data:\nbook(_h_0000, \"d01-x01-y01\");\nbook(_h_0001, \"TMP/test\", refData(1, 1, 1));\n\nwhere d01-x01-y01 refers to the reference data (following HepData naming conventions for the histograms). If you don't have a reference histogram or you need to use a different binning, you can book a histogram as follows:\nbook(_hist, \"pt_h\", 10, 0., 20.);\n\nIn addition to the histogram bookings, you need to add all the projections required for the analysis. Rivet uses projections to extract (and re-use) observables from the final state, e.g. particles (after cuts), jets, .... E.g. for an analysis based on charged particles in the rapidity interval etamax, you would use:\n// need to #include \"Rivet/Projections/ChargedFinalState.hh\"\nconst ChargedFinalState cfs(Cuts::abseta \nFor an analysis based on jets you would use:\nconst FinalState fs_jet(Cuts::abseta \nFor an analysis based on primary particles according to the ALICE definition you would use:\n// need to #include \"Rivet/Projections/AliceCommon.hh\"\n// Charged, primary particles with |eta| 150 MeV\ndeclare(ALICE::PrimaryParticles(Cuts::abseta 150*MeV && Cuts::abscharge > 0), \"APRIM\");\n\nFor more details on possible projections, see the reference page\nanalyze\nThe code in this method is run for every event and is used for the actual (event-wise) analysis. The event for analysis is passed as parameter to the function. Commonly, you apply the projections, and fill some histograms:\nconst ALICE::PrimaryParticles & aprim = apply(event, \"APRIM\");\n\nfor (const Particle &p : aprim.particles()) {\n _h_0000->fill(p.pT()/GeV);\n}\n\nN.B.: Here, the iterations use C++11 constructs.\nfinalize\nThe code in this method is run once after the run. It is typically used for scaling and/or normalization of histograms. In order to normalize a histogram to the number of events, you can make use of Rivet helpers:\nscale(_h_0000, 1./sumOfWeights());\n\nwhere sumOfWeights() is provided by Rivet.\nexample analysis\nIn order to explain the required steps in a real life situation, we will go through the implementation for the analysis published as :\n\nMeasurement of pion, kaon and proton production in proton-proton collisions at sqrt(s) = 7 TeV\nALICE internal draft : ID-183,\njournal reference : Eur.Phys.J C75 (2015) no. 5, 226,\nInspire : ID-1357424,\narXiv : arXiv:1504.00024.\n\n\n\nThe content we now want to reproduce in Rivet is the following:\n\ntransverse momentum spectra of identified pions, kaons, protons\nparticle ratios: kaons / pions, protons / pions\nFor the implementation, you can to the ALICE Rivet reference page to look up the individual ingredients you might need for your analysis.\n\nNow, we go step by step.\nidentifier and template\nFirst, we need to find the identifier for the analysis we want to implement. The analysis was published in 2015 and has the inspire ID 1357424. Thus, the identifier is ALICE_2015_I1357424.\nNow, we can create the template structure (don't forget to load the environment for Rivet and to change to an appropriate directory):\nrivet-mkanalysis ALICE_2015_I1357424\n\nAs mentioned before, the analysis can already be compiled and run (even though it does nothing useful at this stage):\nrivet-build RivetALICE_2015_I1357424.so ALICE_2015_I1357424.cc\nrivet --pwd -a ALICE_2015_I1357424 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\ninitialisation (histograms and projections)\nFirst, we book the required histograms. We need one histogram for each of the pt spectra of pions, kaons, and protons. Eventually, we also want to plot the ratios of the spectra for which a different binning was used. Therefore, we need additional temporary histograms.\nSo, we add the required member variables (in the private section):\n // histograms for spectra\n Histo1DPtr _histPtPions;\n Histo1DPtr _histPtProtons;\n Histo1DPtr _histPtKaons;\n\n // temporary histograms for ratios\n Histo1DPtr _histPtPionsR1;\n Histo1DPtr _histPtPionsR2;\n Histo1DPtr _histPtProtonsR;\n Histo1DPtr _histPtKaonsR;\n\n // scatter plots for ratios\n Scatter2DPtr _histPtKtoPi;\n Scatter2DPtr _histPtPtoPi;\n\nThen, we add the booking of the histograms (in the init method):\n // plots from the paper\n book(_histPtPions , \"d01-x01-y01\"); // pions\n book(_histPtKaons , \"d01-x01-y02\"); // kaons\n book(_histPtProtons , \"d01-x01-y03\"); // protons\n book(_histPtKtoPi , \"d02-x01-y01\"); // K to pi ratio \n book(_histPtPtoPi , \"d03-x01-y01\"); // p to pi ratio\n\n // temp histos for ratios\n book(_histPtPionsR1 , \"TMP/pT_pi1\", refData(2, 1, 1)); // pi histo compatible with more restricted kaon binning\n book(_histPtPionsR2 , \"TMP/pT_pi2\", refData(3, 1, 1)); // pi histo compatible with more restricted proton binning\n book(_histPtKaonsR , \"TMP/pT_K\", refData(2, 1, 1)); // K histo with more restricted binning\n book(_histPtProtonsR , \"TMP/pT_p\", refData(3, 1, 1)); // p histo with more restricted binning\n\nNext, we book the projections for the identified particles (also in the init method):\n const ChargedFinalState cfs(Cuts::absrap \nHere, we use the charged final state (with a rapidity cut) and will deal with the particle identification directly in the analysis code.\n NoteThis example did not use the ALICE::PrimaryParticles projection because it was implemented before this projection was introduced in Rivet. The selection of primary particles according to the ALICE definition is therefore done by hand, by looking at the particle ancestors. The code below could in principle be simplified by removing the large set of if statements if the ALICE::PrimaryParticles projection is used\nconst ALICE::PrimaryParticles& aprim = apply(event, \"APRIM\");\nfor (const Particle& p : aprim.particles()) {\n ...\n}\n\nWe did not modify this tutorial to reflect the actual code for this analysis as in Rivet.\n\nanalysis\nHere, we just use the previously declared projection to loop over all the charged particles in the selected rapidity range and to fill the histograms. \nNote: We exclude feed-down from particles decaying weakly into ฯ, K, p:\n const ChargedFinalState& cfs = apply(event, \"CFS\");\n for (const Particle& p : cfs.particles()) {\n // protections against mc generators decaying long-lived particles\n if ( !(p.hasAncestor(310) || p.hasAncestor(-310) || // K0s\n p.hasAncestor(130) || p.hasAncestor(-130) || // K0l\n p.hasAncestor(3322) || p.hasAncestor(-3322) || // Xi0\n p.hasAncestor(3122) || p.hasAncestor(-3122) || // Lambda\n p.hasAncestor(3222) || p.hasAncestor(-3222) || // Sigma+/-\n p.hasAncestor(3312) || p.hasAncestor(-3312) || // Xi-/+ \n p.hasAncestor(3334) || p.hasAncestor(-3334) )) // Omega-/+ \n { \n switch (abs(p.pid())) {\n case 211: // pi+\n _histPtPions->fill(p.pT()/GeV);\n _histPtPionsR1->fill(p.pT()/GeV);\n _histPtPionsR2->fill(p.pT()/GeV);\n break;\n case 2212: // proton\n _histPtProtons->fill(p.pT()/GeV);\n _histPtProtonsR->fill(p.pT()/GeV);\n break;\n case 321: // K+\n _histPtKaons->fill(p.pT()/GeV);\n _histPtKaonsR->fill(p.pT()/GeV);\n break;\n } // particle switch\n } // primary pi, K, p only\n } // particle loop\n\nfinalise\nIn the end, we build the particle ratios to pions (K/ฯ and P/ฯ) and normalize the histograms in order to show 1/Nev dยฒN/dpt dy event-normalised spectra :\n divide(_histPtKaonsR, _histPtPionsR1, _histPtKtoPi);\n divide(_histPtProtonsR, _histPtPionsR2, _histPtPtoPi);\n\n scale(_histPtPions, 1./sumOfWeights());\n scale(_histPtProtons, 1./sumOfWeights());\n scale(_histPtKaons, 1./sumOfWeights());\n\ntry your new analysis\nNow, try and run the analysis on the test file:\nrivet-buildplugin Rivet_test.so ALICE_2015_I1357424.cc\nrivet --pwd -a ALICE_2015_I1357424 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\nN.B.: Note the option --pwd which instructs Rivet to look for the specified analyses (also) in the current working directory.\nNext, create the plots and compare:\nrivet-mkhtml --pwd Rivet.yoda\n\n(if needed copy plots/ directory locally).\nIn case of problems, you can look at the reference implementation - but first try to sort it out yourself.\nexperiment with the analysis\nIn order to gather experience with programming Rivet plugins, it is good to experiment a bit. You can e.g. try to:\n\nreplace the projection to use particle identification\nmove the primary selection to a separate function\n...\n\n"},"rivet/hi-features.html":{"url":"rivet/hi-features.html","title":"Introduction to heavy-ion features","keywords":"","body":"Introduction to heavy-ion features\nSeveral heavy-ion features were added to the recent version of Rivet (2.7.x). The ones that will be used in this tutorial are described below. In order to get to know other, more advanced heavy-ion features go to this section.\nA lot of heavy-ion analyses require the calibration of some global event observable, e.g. centrality, thrust, etc. There might be multiple approaches on how to deal with this: using the calibration provided by the experiment together with the analysis, generating your own calibration files, or even using values provided by the generator. All mentioned solutions are already supported by Rivet. On top of that, the first two methods are supported in a form of a new kind of analyses, so called calibration analyses. They are 'dummy' analyses used to produce calibration plots that are afterwards used by the main analysis.\nCalibration analysis\nA calibration analysis is essential in case our generator does not provide some global event observable(s) required by the main analysis. Such a calibration analysis is similar to a regular one but instead of producing comparisons to the existing experimental data it produces distributions of different observables, such as impact parameter distribution. It should be pointed out that there might be multiple analyses using the same calibration analysis. An example of a calibration analysis producing a V0M multiplicity distribution and an impact parameter distribution is provided below:\n#include \n#include \n#include \n\nnamespace Rivet {\n\n /// Dummy analysis for centrality calibration in Pb-Pb at 5.02TeV\n ///\n /// @author Christian Holm Christensen \n class ALICE_2015_PBPBCentrality : public Analysis {\n public:\n\n /// Constructor \n ALICE_2015_PBPBCentrality()\n : Analysis(\"ALICE_2015_PBPBCentrality\")\n { }\n\n /// Initialize this analysis. \n void init() {\n ALICE::V0AndTrigger v0and;\n declare(v0and,\"V0-AND\");\n\n ALICE::V0MMultiplicity v0m;\n declare(v0m,\"V0M\");\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n book(_v0m, \"V0M\");\n book(_imp, \"V0M_IMP\",100,0,20);\n }\n\n\n /// Analyse a single event.\n void analyze(const Event& event) {\n // Get and fill in the impact parameter value if the information is valid.\n _imp->fill(apply(event, \"HepMC\").impact_parameter());\n\n // Check if we have any hit in either V0-A or -C. If not, the\n // event is not selected and we get out.\n if (!apply(event,\"V0-AND\")()) return;\n\n // Fill in the V0 multiplicity for this event\n _v0m->fill(apply(event,\"V0M\")());\n }\n\n\n /// Finalize this analysis\n void finalize() {\n _v0m->normalize();\n _imp->normalize();\n }\n\n /// The distribution of V0M multiplicity\n Histo1DPtr _v0m;\n /// The distribution of impact parameters\n Histo1DPtr _imp;\n\n };\n\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2015_PBPBCentrality);\n\n}\n\nThis calibration analysis can be run in the same way as any other analysis:\nrivet -a ALICE_2015_PBPBCentrality -o calibration.yoda /path/to/generator.hepmc\nThis will produce the calibration plots and save them to calibration.yoda to use in the future. Once this is done we can proceed to the next step.\nSelecting calibration method\nAny analysis can load yoda files from calibration analysis assuming it contains the necessary information about the calibration methods. Possible options that allow the selection of the calibratino method are the following:\n\nREF (default): get calibration histogram from reference data\nGEN: get generated calibration histogram\nIMP: get impact parameter calibration histogram\nUSR: get user-defined calibration histogram\nRAW: get generated centrality (available only with HepMC3)\n\nThe information about possible methods for a particular analysis is stored in the .info file of this analysis. An example of how an .info file may look like is provided below:\n[...]\nOptions:\n - cent=REF,GEN,IMP,USR\nBeams: [Pb, Pb] # PDG of lead ion\nEnergies: [574080] # This is _total_ energy of beams, so this becomes 208*2760=574080\n[...]\nPreloading calibration files\nIn order to run an analysis with preloading a calibration file one needs to use the '-p' flag (see rivet --help) to provide the path to the calibration .yoda file and choose a method of calibration by adding ':var=METHOD' after the name of the analysis. This will look something like that:\nrivet -a ALICE__I:cent=GEN -p /path/to/calibration.yoda /path/to/generator.hepmc\nThis means that Rivet will run our selected analysis with an option GEN (generated calibration histogram) for the centrality calibration using the plots stored in calibration.yoda file. In case of not specifying the calibration method, Rivet will try to access the reference calibration file - if it was not provided with the calibration analysis the run will fail. Next section will cover how to access and use the centrality value inside the main analysis.\nExtracting centrality\nPreloading and selecting the method of calibration of centrality gives us access to the centrality estimator inside our main analysis. This is done in the form of a special projection class CentralityProjection. It allows an analysis to cut on percentiles of single event quantities preloaded (or supplied by the experiment) from a histogram. In order to use it one needs to declare it in the init function:\nvoid init () {\n [...]\n // Declare centrality projection for centrality estimation\n const CentralityProjection cp = declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n [...]\n}\n\nThen, one can use it to extract centrality value in the analyze function like this:\nconst CentralityProjection& centrProj = apply(event, \"V0M\");\ndouble centr = centrProj();\n\nThis gives us a value of centrality as a percentage and it can be used to do whatever one wants to do with it: fill the histogram as a function of centrality, fill the histograms for different centrality ranges, remove events with particular centrality, etc. A full example of an analysis using centrality is provided below:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Tools/Cuts.hh\"\n#include \"Rivet/Projections/SingleValueProjection.hh\"\n#include \"Rivet/Tools/AliceCommon.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/HepMCHeavyIon.hh\"\n\nnamespace Rivet {\n\n /// @brief ALICE PbPb at 2.76 TeV multiplicity at mid-rapidity\n class ALICE_2010_I880049 : public Analysis { \n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2010_I880049);\n\n /// @name Analysis methods\n //@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Declare centrality projection\n declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n\n // Trigger projections\n declare(ChargedFinalState((Cuts::eta > 2.8 && Cuts::eta 0.1*GeV), \"VZERO1\");\n declare(ChargedFinalState((Cuts::eta > -3.7 && Cuts::eta 0.1*GeV), \"VZERO2\");\n declare(ChargedFinalState(Cuts::abseta 0.15*GeV),\n \"SPD\");\n\n // Charged, primary particles with |eta| 50 MeV\n declare(ALICE::PrimaryParticles(Cuts::abseta 50*MeV && Cuts::abscharge > 0), \"APRIM\");\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n // Histograms and variables initialization\n book(_histNchVsCentr, 1, 1, 1);\n book(_histNpartVsCentr, 1, 1, 2);\n\n }\n\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Charged, primary particles with at least pT = 50 MeV\n // in eta range of |eta| (event,\"APRIM\").particles();\n\n // Trigger projections\n const ChargedFinalState& vz1 =\n applyProjection(event,\"VZERO1\");\n const ChargedFinalState& vz2 =\n applyProjection(event,\"VZERO2\");\n const ChargedFinalState& spd =\n applyProjection(event,\"SPD\");\n int fwdTrig = (vz1.particles().size() > 0 ? 1 : 0);\n int bwdTrig = (vz2.particles().size() > 0 ? 1 : 0);\n int cTrig = (spd.particles().size() > 0 ? 1 : 0);\n\n if (fwdTrig + bwdTrig + cTrig (event, \"V0M\");\n double centr = centrProj();\n if (centr > 80) vetoEvent;\n // Calculate number of charged particles and fill histogram\n double nch = chargedParticles.size();\n _histNchVsCentr->fill(centr, nch);\n\n // Attempt to extract Npart form GenEvent.\n if (event.genEvent()->heavy_ion()) {\n const HepMCHeavyIon & hi = apply(event, \"HepMC\");\n _histNpartVsCentr->fill(centr, hi.Npart_proj() + hi.Npart_targ());\n }\n }\n\n\n /// Normalise histograms etc., after the run\n //void finalize() { }\n\n //@}\n\n\n private:\n\n /// @name Histograms\n //@{\n Profile1DPtr _histNchVsCentr;\n Profile1DPtr _histNpartVsCentr;\n //@}\n\n };\n\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2010_I880049);\n\n}\n\nRun an example\nWe can now try to run an aleady installed Rivet software with an already existing example analysis with an already existing .hepmc file and (optionally) .yoda calibration file. In order to do that follow the steps described below.\nLog in to your lxplus account (check that you have an access to lxplus here):\nssh @lxplus.cern.ch\nAfter logging in you can enter the environment as follows:\nalienv enter Rivet\nThis will load all the environment required for Rivet. The following command should prompt us that we are going to use Rivet version 3.1.1:\nrivet --version\nLet's create a directory for our results:\nmkdir /path/to/rivet-hi-tutorial\ncd /path/to/rivet-hi-tutorial\nNow, as an example we are going to use ALICE_2010_I880049 as our main analysis together with the calibration analysis ALICE_2015_PBPBCentrality. You can list available ALICE analyses and check that they are available to use by typing:\nrivet --list-analyses | grep ALICE_\nWe will use an already generated .hepmc file that contains some events from EPOS-LHC for Pb-Pb beam at 2.76 TeV, which corresponds to our analysis. This file is located here: /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nFirst, we need to run our calibration analysis. Let's assume that our output files will be saved as /path/to/rivet-hi-tutorial/calibration.yoda\nrivet -a ALICE_2015_PBPBCentrality -o /path/to/rivet-hi-tutorial/calibration.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nThis will produce our calibration plots (beware that this might take some time). In case of any problems with generating these plots you can use already generated ones from here: /eos/project/a/alipwgmm/rivet/yoda/calibration_epos_PbPb2760.yoda\nNext step is to run the main analysis. Let's choose for example generated V0M multiplicity distribution as calibration method. We will use the same .hepmc file as we used for calibration (it doesn't have to be the same) and run Rivet again:\nrivet -a ALICE_2010_I880049:cent=GEN -p /path/to/rivet-hi-tutorial/calibration.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nIn case you want to use an already generated calibration file instead, you can try:\nrivet -a ALICE_2010_I880049:cent=GEN -p /eos/project/a/alipwgmm/rivet/yoda/calibration_epos_PbPb2760.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nAgain, this might take some time. After it's done, you can create the plots like that:\nrivet-mkhtml Rivet.yoda\n"},"rivet/reference-manual.html":{"url":"rivet/reference-manual.html","title":"Reference manual for Rivet in ALICE","keywords":"","body":"Reference manual for Rivet in ALICE\nBooking histograms/profiles\nThere are several ways to book a histogram:\n\ncorresponding to HepData_hist = bookHisto1D(\"d01-x01-y01\");\n\n\nre-using properties from HepData_hist = bookHisto1D(\"TMP/test\", refData(1, 1, 1));\n\n\nmanual_hist = bookHisto1D(\"pt_h\", 10, 0., 20., \"final state particles\", \"$p_\\\\perp$\", \"counts\");\n_prof = bookProfile1D(\"cos2phi_pt_h\", 10, 0., 20.);\n\n\n\nBooking projections\nparticle level\nIn order to select all final state particles in a given rapidity range:\n const FinalState fs(-_etamax, _etamax);\n addProjection(fs, \"FS\");\n\nor if you want to constrain to charged particles:\n const ChargedFinalState cfs(-_etamax, _etamax);\n addProjection(cfs, \"CFS\");\n\nYou can further add a minimum transverse momentum and particle identification:\n IdentifiedFinalState pionfs(-_etamax, _etamax, 0.*GeV);\n pionfs.acceptId(111);\n addProjection(pionfs, \"PIONFS\");\n\nderived projections\nYou can also add projections which are derived from a final state, e.g. for multiplicity:\n addProjection(Multiplicity(fs), \"Mult\");\n\nor for thrust:\n addProjection(Thrust(fs), \"Thrust\");\n\njets\nIn order to add a projection for jets, you first have to add (or re-use) a particle-level projection which serves as input to a jet finder. You can use the jet finders provided with the FastJet package.\n const FinalState fs_jet(-_etamax - _jet_r, _etamax + _jet_r);\n addProjection(fs_jet, \"FS_JET\");\n FastJets fj02(fs_jet, FastJets::ANTIKT, _jet_r);\n fj02.useInvisibles();\n addProjection(fj02, \"Jets02\");\n\nand more ...\nThe list of basic projections can be found under the Hepforge page for Rivet (see References).\nNormalisation\nYou can normalize a given histogram to unity:\n normalize(_h_sin2phi);\n\nYou can normalize to the number of events:\n scale(_h_stat, 1. / sumOfWeights());\n\nor to cross section:\n scale(_h_stat, crossSection() / sumOfWeights());\n\nYou might have to account for the considered phase space:\n const double fac = crossSection() / (millibarn * sumOfWeights() * 2 * pi * 2 * _etamax);\n scale(_h_pt_jet02, fac);\n\n"},"rivet/publishing-procedures.html":{"url":"rivet/publishing-procedures.html","title":"Procedures for publishing Rivet analyses","keywords":"","body":"Procedures for publishing Rivet analyses\nAs Rivet analyses will be published for the ALICE collaboration, they will have to undergo approval. The exact rules will still have to be defined, here we outline what we have in mind:\nValidation\nAll analyses contributed to Rivet must be shown to actually work by comparing to a (sufficiently large) Monte Carlo sample - this is also required by the Rivet author. For ALICE, we have to distinguish the cases of\n\nnew analysis\nRivet validation/approval can happen together with paper approval\n\n\nalready published analysis:\nneed to ensure to reproduce MC comparisons from published paper\nseparate validation/approval of Rivet analysis (t.b.d., could be by PB/PF)\n\n\n\nSubmission of analysis\nThe contributions to Rivet from the LHC experiments are organized through contact persons. For ALICE this is channeled through PAG-MC, i.e. after approval the analysis will be submitted centrally to the Rivet repository.\n"},"rivet/advanced-topics.html":{"url":"rivet/advanced-topics.html","title":"Advanced topics","keywords":"","body":"Advanced topics (installations)\nInstalling Rivet locally\nIf beyond CVMFS deployment (lxplus, Grid nodes), you wish to have your own environment lcoally, note that Rivet can be installed using aliBuild (analogous to AliPhysics). \nIt can be done :\n\nin your local computer natively (beware the difficulties associated with software dependencies...) \nunder alidock (a priori, smoother, but note the potential LaTeX dependencies of Rivet (See alidock/issue-145 to have custom docker image).\n\nAssuming you have followed the instructions to install AliPhysics in a repository ~/alice, you can run:\ncd ~/alice\naliBuild build Rivet\nThis will build and install Rivet as well as its dependencies (2019/10/18):\n\nPython-modules\nboost\nGMP\nCMake\nGSL\nYODA, histogramming\nMPFR\nHepMC, output format for generators, input for Rivet analysis\ncgal\nfastjet\nRivet\n\nSubsequently, you can setup the environment to use Rivet by:\nalienv enter Rivet/latest-ali-master\nThen, you can use Rivet in the same way as explained above for the installation from cvmfs. \nInstalling MC generators locally\nNote however that the above instructions just provide you with Rivet and Yoda basically but do not include the various generators themselves...\nUnder CVMFS, you will typically find generators that are centrally installed :\n\nAMPT, \nCRMC (= EPOS-LHC, 2012), \nDPMJET, \nEPOS-3.111 (2015), \nFONLL, \nHerwig-7, \nJETSCAPE-3\nJEWEL-2,\nPOWHEG, \n(Rivet-3.x),\nSHERPA-2, \nTherminator2, \n(aligenmc),\nPYTHIA-6.4, \nPYTHIA-8.2\n\nand several utilities coming along (Sacrifice for Pythia, ThePEG for Herwig, Agile for fortran MC, LHAPDF sets, ...).\nThe version of the generators as well as their dependencies naturally evolve with time and should normally be managed accordingly in ALICE.\nSuch MC generators available in ALICE are encompassed into the bundle AliGenerators.\nOne can find its constituents under https://alimonitor.cern.ch/packages, take for instance AliGenerators::v20190924-1.\nSuch a bundle can also be built locally with aliBuild and is managed via the recipealidist/aligenerators.sh and alidist/defaults-pwgmmtest.sh. Such a meta-recipe relies on the recipes of the individual generators alidist/[generator.sh].\ncd ~/alice\naliBuild build AliGenerators --debug --defaults generators -j 6\n"},"rivet/advanced-hi-features.html":{"url":"rivet/advanced-hi-features.html","title":"Advanced heavy-ion features","keywords":"","body":"Advanced heavy-ion feratures\nThis section covers more advanced heavy-ion features introduced in Rivet version 2.7.0+. It explains how event mixing is implemented in Rivet and how to use it, as well as it presents the idea of reentrant finalize for analyses which require more than one beam and/or energy within the same analysis.\nPlease follow the basic tutorial of implementing a Rivet analysis here and a section covering basic heavy-ion features here first before going into this section.\nPostprocessing with reentrant finalize\nPostprocessing is a method that enables to merge results coming from different Rivet runs. This is useful for analyses which require different beams and/or energies to obtain final results, but also is useful when one wants to simply increase the statistics by merging multiple runs for the same beam/energy. Note, that such an analysis must be implemented in a certain way to allow proper running for all modes, so one should take great care when writing it.\nIn case of running an analysis for different beams/energies, first step is to declare them in the .info file like this:\n[...]\nBeams: [[p, p], [Pb, Pb]]\n# This is _total_ energy of beams, so this becomes 208*2760=574080\nEnergies: [2760, 574080]\n[...]\nThen, inside the analysis' init function, one should declare objects for each beam/energy separately, e.g.:\nvoid init() {\n // Initialize PbPb objects\n book(_histNch, 1, 1, 1);\n book(_counterSOW, \"counter.pbpb\"); // Sum of weights counter for PbPb\n book(_counterNcoll, \"counter.ncoll\"); // Ncoll counter for PbPb\n // Initialize pp objects\n std::string namePP = _mkAxisCode(1, 1, 1) + \"-pp\";\n book(_histNchPP, namePP, refData(1, 1, 1));\n book(_counterSOWPP, \"counter.pp\"); // Sum of weights counter for pp\n // Book ratios, to be used in finalize\n book(_histRAA, 16, 1, 1);\n [...]\n}\n\nSill in the analyze method, one can check the beam type and assign the value to a variable (bool isHI, in this case) depending on the beam type\nconst ParticlePair& beam = beams();\nif (beam.first.pid() == PID::PROTON && beam.second.pid() == PID::PROTON) isHI = false;\nelse if (beam.first.pid() == PID::LEAD && beam.second.pid() == PID::LEAD) isHI = true;\nelse {\n MSG_ERROR(\"Beam error (found)!\");\n return;\n}\n\nIn the analyze method, one can then use the information gathered about the beam type to steer the analysis as required\nif (isHI) {\n const HepMC::HeavyIon* hi = event.genEvent()->heavy_ion();\n if (!hi.ok()) {\n MSG_WARNING(\"HEPMC Heavy ion container needed for this analysis, but not \"\n \"found for this event. Skipping.\");\n vetoEvent;\n }\n // process PbPb event, fill PbPb histograms\n}\nelse {\n // process pp event, fill pp histograms\n}\n\nFinally, the regular finalize method is called, but in case we have entries in the histograms for both beam types, we do an additional step of dividing them one by another to create R_AA plot:\nvoid finalize() {\n // Regular finalize, scaling, etc.\n [...]\n\n // Postprocessing of the histograms in case there are\n // entries in histograms for both beam types\n if (_histNchPP->numEntries() > 0 && _histNch->numEntries() > 0) {\n // Initialize and fill R_AA histograms\n divide(_histNch, _histNchPP, _histRAA);\n }\n}\n\nIn order to run an analysis in the postprocessing mode one should run an analysis for every beam/energy combination and then use the rivet-merge script with the output files from the previous runs provided as parameters (check rivet-merge --help):\nrivet-merge /path/to/result1.yoda /path/to/result2.yoda ...\nThis will use the RAW histograms from you output files (check that your .yoda files contain them, they contain results from the analysis before the final scaling in the finalize method), merge them, and call finalize part of the analysis again on the merged histograms. Now, as all the histograms will be available, the finalize method will (in our case) create and fill R_AA histograms and save them to the output .yoda file containing final results.\n BewareThere is no information about beam and energy when running rivet-merge script - this should be taken into account when implementing such an analysis. Also note, that an analysis with reentrant finalize should be validated to allow running in every mode, and so in the .info file it should be marked as: Status: REENTRANT\n\nA full example of an analysis with the reentrant finalize mode enabled is provided below:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/Beam.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Tools/Cuts.hh\"\n#include \"Rivet/Projections/SingleValueProjection.hh\"\n#include \"Rivet/Tools/AliceCommon.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/HepMCHeavyIon.hh\"\n\nnamespace Rivet {\n\n /// @brief ALICE PbPb at 2.76 TeV R_AA analysis.\n class ALICE_2012_I1127497 : public Analysis {\n\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2012_I1127497);\n\n /// @name Analysis methods\n //@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n // Declare centrality projection\n declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n\n // Charged, primary particles with |eta| 150 MeV\n declare(ALICE::PrimaryParticles(Cuts::abseta 150*MeV && Cuts::abscharge > 0), \"APRIM\");\n\n // Loop over all histograms\n for (size_t ihist = 0; ihist (\"beam\",\"NONE\");\n if (beamOpt != \"NONE\") {\n MSG_WARNING(\"You are using a specified beam type, instead of using what\"\n \"is provided by the generator. \"\n \"Only do this if you are completely sure what you are doing.\");\n if (beamOpt==\"PP\") isHI = false;\n else if (beamOpt==\"HI\") isHI = true;\n else {\n MSG_ERROR(\"Beam error (option)!\");\n return;\n }\n }\n else {\n const ParticlePair& beam = beams();\n if (beam.first.pid() == PID::PROTON && beam.second.pid() == PID::PROTON) isHI = false;\n else if (beam.first.pid() == PID::LEAD && beam.second.pid() == PID::LEAD)\n isHI = true;\n else {\n MSG_ERROR(\"Beam error (found)!\");\n return;\n }\n }\n }\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Charged, primary particles with at least pT = 150 MeV\n // in eta range of |eta| (event,\"APRIM\").particlesByPt();\n\n // Check type of event.\n if ( isHI ) {\n\n const HepMCHeavyIon & hi = apply(event, \"HepMC\");\n if (!hi.ok()) {\n MSG_WARNING(\"HEPMC Heavy ion container needed for this analysis, but not \"\n \"found for this event. Skipping.\");\n vetoEvent;\n }\n // Prepare centrality projection and value\n const CentralityProjection& centrProj =\n apply(event, \"V0M\");\n double centr = centrProj();\n // Veto event for too large centralities since those are not used\n // in the analysis at all\n if ((centr 80.)) vetoEvent;\n\n // Fill PbPb histograms and add weights based on centrality value\n for (size_t ihist = 0; ihist fill();\n _counterNcoll[ihist]->fill(hi.Ncoll());\n for (const Particle& p : chargedParticles) {\n double pT = p.pT()/GeV;\n if (pT binAt(pT).xMid();\n _histNch[PBPB][ihist]->fill(pT, 1/pTAtBinCenter);\n }\n }\n }\n }\n\n }\n else {\n\n // Fill all pp histograms and add weights\n for (size_t ihist = 0; ihist fill();\n for (const Particle& p : chargedParticles) {\n double pT = p.pT()/GeV;\n if (pT binAt(pT).xMid();\n _histNch[PP][ihist]->fill(pT, 1/pTAtBinCenter);\n }\n }\n }\n\n }\n\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n\n // Right scaling of the histograms with their individual weights.\n for (size_t itype = 0; itype sumW() > 0.) {\n scale(_histNch[itype][ihist],\n (1. / _counterSOW[itype][ihist]->sumW() / 2. / M_PI));\n }\n }\n }\n\n // Postprocessing of the histograms\n for (size_t ihist = 0; ihist numEntries() > 0 && _histNch[PBPB][ihist]->numEntries() > 0) {\n // Initialize and fill R_AA histograms\n divide(_histNch[PBPB][ihist], _histNch[PP][ihist], _histRAA[ihist]);\n // Scale by Ncoll. Unfortunately some generators does not provide\n // Ncoll value (eg. JEWEL), so the following scaling will be done\n // only if there are entries in the counters\n double ncoll = _counterNcoll[ihist]->sumW();\n double sow = _counterSOW[PBPB][ihist]->sumW();\n if (ncoll > 1e-6 && sow > 1e-6)\n _histRAA[ihist]->scaleY(1. / (ncoll / sow));\n\n }\n }\n\n }\n\n //@}\n\n private:\n\n bool isHI;\n static const int NHISTOS = 15;\n static const int EVENT_TYPES = 2;\n static const int PP = 0;\n static const int PBPB = 1;\n\n /// @name Histograms\n //@{\n Histo1DPtr _histNch[EVENT_TYPES][NHISTOS];\n CounterPtr _counterSOW[EVENT_TYPES][NHISTOS];\n CounterPtr _counterNcoll[NHISTOS];\n Scatter2DPtr _histRAA[NHISTOS];\n //@}\n\n std::vector> _centrRegions;\n\n };\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2012_I1127497);\n\n\n}\n\nEvent mixing\n WARNINGThis feature is still under development and its usage might change in the coming versions of Rivet. Description of this procedure was prepared for Rivet version 2.7.2.\n\nEvent mixing is a procedure that enables to project out an event mixed of several events. In Rivet it is implemented in a form of a projection class called EventMixingProjection. It is based on a mixing observable provided as an input to define what should qualify as a mixable event, where the mixing observable can be defined as number of final state particles, centrality, event plane angle, etc. It contains a buffer that is filled with events over the runtime. This buffer can be used within an analysis to perform required operations. A declaration of an event mixing projection looks like this:\nvoid init () {\n [...]\n // Charged final state to manage the mixing observable\n ChargedFinalState cfsMult(Cuts::abseta pTmin*GeV);\n addProjection(pp,\"APRIM\");\n // The event mixing projection\n declare(EventMixingFinalState(&cfsMult, pp, 5, 0, 100, 10),\"EVM\");\n\n [...]\n}\n\nIn this case the first parameter of the event mixing projection defines a mixing observable. The second parameter is used to project out an event that is added to the buffer. The other parameters are: number of events to mix, minimal and maximal value of the mixing observable, and number of bins for that observable (so that for each bin there is a separate buffer). One can use it in the analyze method like this:\nvoid analyze(const Event& event) {\n [...]\n const EventMixingFinalState& evm = applyProjection(event, \"EVM\");\n // Test if we have enough mixing events available to continue.\n if (!evm.hasMixingEvents()) return;\n // Loop over the particles in the mixing buffer\n for(const Particle& pMix : evm.particles()){\n [...]\n }\n [...]\n}\n\nThis enables to check if we already have enough events in our buffer (method hasMixingEvents will return false in case the number of events in the buffer is lower than requested) and gives us access to the mixing buffer within the analysis. Note, that in this case first few events will be skipped as we require our buffers to be filled before going further. Full example can be found here:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/PrimaryParticles.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Projections/EventMixingFinalState.hh\"\nnamespace Rivet {\n\n\n /// @brief Correlations of identified particles in pp.\n /// Also showcasing use of EventMixingFinalState.\n\n class ALICE_2016_I1507157 : public Analysis {\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2016_I1507157);\n\n\n /// @name Analysis methods\n //@{\n\n /// @brief Calculate angular distance between particles.\n double phaseDif(double a1, double a2){\n double dif = a1 - a2;\n while (dif 3*M_PI/2)\n dif -= 2*M_PI;\n return dif;\n }\n\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n double etamax = 0.8;\n double pTmin = 0.5; // GeV \n\n // Trigger\n declare(ALICE::V0AndTrigger(), \"V0-AND\");\n // Charged tracks used to manage the mixing observable.\n ChargedFinalState cfsMult(Cuts::abseta pTmin*GeV);\n addProjection(pp,\"APRIM\");\n\n // The event mixing projection\n declare(EventMixingFinalState(&cfsMult, pp, 5, 0, 100, 10),\"EVM\");\n // The particle pairs.\n pid = {{211, -211}, {321, -321}, {2212, -2212}, {3122, -3122}, {211, 211},\n {321, 321}, {2212, 2212}, {3122, 3122}, {2212, 3122}, {2212, -3122}};\n // The associated histograms in the data file.\n vector refdata = {\"d04-x01-y01\",\"d04-x01-y02\",\"d04-x01-y03\",\n \"d06-x01-y02\",\"d05-x01-y01\",\"d05-x01-y02\",\"d05-x01-y03\",\"d06-x01-y01\",\n \"d01-x01-y02\",\"d02-x01-y02\"};\n for (int i = 0, N = refdata.size(); i (event, \"V0-AND\")()) return;\n // The projections\n const PrimaryParticles& pp = \n applyProjection(event,\"APRIM\");\n const EventMixingFinalState& evm = \n applyProjection(event, \"EVM\");\n\n // Test if we have enough mixing events available to continue.\n if (!evm.hasMixingEvents()) return;\n\n for(const Particle& p1 : pp.particles()) {\n // Start by doing the signal distributions\n for(const Particle& p2 : pp.particles()) {\n if(isSame(p1,p2))\n continue;\n double dEta = abs(p1.eta() - p2.eta());\n double dPhi = phaseDif(p1.phi(), p2.phi());\n if(dEta 0);\n if (samesign && ((pid1 == p1.pid() && pid2 == p2.pid()) || \n (pid1 == -p1.pid() && pid2 == -p2.pid()))) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n if (!samesign && abs(pid1) == abs(pid2) &&\n pid1 == p1.pid() && pid2 == p2.pid()) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n if (!samesign && abs(pid1) != abs(pid2) && \n ( (pid1 == p1.pid() && pid2 == p2.pid()) ||\n (pid2 == p1.pid() && pid1 == p2.pid()) ) ) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n }\n }\n }\n // Then do the background distribution\n for(const Particle& pMix : evm.particles()){\n double dEta = abs(p1.eta() - pMix.eta());\n double dPhi = phaseDif(p1.phi(), pMix.phi());\n if(dEta 0);\n if (samesign && ((pid1 == p1.pid() && pid2 == pMix.pid()) || \n (pid1 == -p1.pid() && pid2 == -pMix.pid()))) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n if (!samesign && abs(pid1) == abs(pid2) &&\n pid1 == p1.pid() && pid2 == pMix.pid()) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n if (!samesign && abs(pid1) != abs(pid2) && \n ( (pid1 == p1.pid() && pid2 == pMix.pid()) ||\n (pid2 == p1.pid() && pid1 == pMix.pid()) ) ) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n }\n }\n }\n }\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n for (int i = 0, N = pid.size(); i scaleW(sc);\n divide(signal[i],background[i],ratio[i]);\n }\n }\n\n //@}\n\n\n /// @name Histograms\n //@{\n vector > pid;\n vector signal;\n vector background;\n vector ratio;\n vector nsp;\n vector nmp;\n\n //@}\n\n };\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2016_I1507157);\n\n}\n\n"},"rivet/coding-conventions.html":{"url":"rivet/coding-conventions.html","title":"Coding conventions for Rivet plugins","keywords":"","body":"Coding conventions for Rivet plugins\nSome inventory is made in the Rivet webpage: Rivet - Coding Style\n BewareCoding conventions for Rivet plugins are different than those for AliRoot/AliPhysics!\n\n"},"rivet/references.html":{"url":"rivet/references.html","title":"References","keywords":"","body":"References\nRivet official\n\nRivet user manual: arXiv:1003:0694\n\nRivet wiki: writing an analysis\n\nRivet tutorial documentation (GitLab) GitLab:HepCedar-Tutorials\n\n\"Confronting Experimental Data with Heavy-Ion Models: Rivet for Heavy Ions\" arXiv:2001.10737\n\n\"Robust Independent Validation of Experiment and Theory: Rivet version 3\" arXiv:1912.05451\n\n\nALICE Rivet\n\nRivet & ALICE (conceptual overview) (2016) Jochen Klein : Indico.infn:10971\n\nALICE Rivet hackathon workshop 2020-11 : Indico.cern:969010\n\n\nALICE building framework\nalibuild primer\nalibuild reference\n"},"CONTRIBUTING.html":{"url":"CONTRIBUTING.html","title":"Contributing","keywords":"","body":"Welcome to the ALICE Analysis Tutorial documentation\n\nThis is a community-contributed place where we collect all our documentation. Every ALICE member can\ncontribute, and the Analysis Tutorial Committee will review every contribution.\nWhere can I see the documentation online?\nDocumentation is published on GitHub pages at the following address:\n\nhttps://alice-doc.github.io/alice-analysis-tutorial/\n\nHow can I contribute to the documentation?\nFirst off you need a GitHub account. Fork the\nalice-doc/alice-analysis-tutorial repository, then clone it to your\nlaptop:\ngit clone https://github.com//alice-analysis-tutorial\ncd alice-analysis-tutorial/\ngit remote add upstream https://github.com/alice-doc/alice-analysis-tutorial\n\nDocumentation is written in Markdown and it\nis generated using GitBook. You need to install GitBook first. GitBook\nis a NodeJS package, meaning that you need npm to install it. You can get npm easily.\nOn Ubuntu:\nsudo apt install npm\n\nOn macOS (assuming you have Homebrew):\nbrew install npm\n\nOn CentOS 7 (you need EPEL enabled):\nsudo yum install npm\n\nOnce npm is installed, you can install GitBook:\nsudo npm install -g gitbook-cli@2.3.0\n\nDo not use sudo on macOS.\nOnce GitBook is installed, you should find it in your $PATH, check it with:\ntype gitbook\n\nTo preview the documentation pages locally while you are editing them, move to the repository's root\ndirectory and run:\ncd alice-analysis-tutorial/\nmake serve\n\nThe command will not exit and a local website will be visible at the following address:\n\nhttp://localhost:4000\n\nThe website uses GitBook. Editing the pages using your favorite text\neditor: whenever you save, the page currently opened in your local preview will be refreshed\nautomatically.\nWhen you are happy with your modifications, commit them, push them to your repository and open a\npull request, for instance:\ngit commit -a -m 'I am happy with my doc'\ngit push origin\n\nthen navigate to your GitHub repository online to open a pull request.\n"}}}
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๏ธ","๐):","๐ช","๐ฆ","๐ซdo","๐ ","๐คฌone","๐งช","๐งน"],"pipeline":["stopWordFilter","stemmer"]},"store":{"./":{"url":"./","title":"Introduction","keywords":"","body":"Welcome to the ALICE Analysis Tutorial documentation\nThis is a community-contributed place where we collect all our documentation. Every ALICE member can\ncontribute, and the Analysis Tutorial Committee will review every contribution.\n\nAs a first step, you should make sure you are correctly registered as an ALICE user.\nThen you should head of to the section on how to build ALICE software.\nFinally you can dive in in the analysis framework documentation.\nIf you are looking for the old analysis tutorial using the old Run 2 framework, it can be found here.\n\nIf you would like to improve these pages you can have a look at the CONTRIBUTING documentation.\n"},"start/":{"url":"start/","title":"Getting started","keywords":"","body":"Getting started in ALICE\nAre you a registered ALICE member?\nUse this link to check if your CERN account is connected to ALICE. In\ncase you see a message saying that you are not an ALICE member, you need to fix the problem: many\nservices are not accessible if you are not considered an ALICE member.\nDrop an email to the ALICE Secretariat, they will help you: alice.secretariat@cern.ch\nDo you have access to lxplus?\nWhen you have a CERN account you can typically login to lxplus via SSH:\nssh USERNAME@lxplus.cern.ch\n\nIf, in spite of providing the correct password, you are not allowed to connect, go on your CERN\naccount management page. You need to Sign in and to select Resources\nand Services like in the picture below:\n\n\nThen click the big List Services button and check if the following services are enabled for you:\n\n\nYou need:\n\nLXPLUS and Linux\nAFS Workspaces\nEOS/CERNBox\n\nIn case some of them are missing, just click on the service to subscribe. For Linux, you may be\nrequested to provide a \"group\" and a \"reason\" for requesting the subscription.\n\nGroup: z2 (it corresponds to ALICE)\nReason: just type something like \"new ALICE member\", it's enough\n\nIt will take at least two full working hours before you will be able to use the services\nUsing the Grid: get a certificate\nThe procedure for getting or renewing a certificate is illustrated here.\nRequesting support\nThere are different ways to request support in ALICE. For simple requests concerning Run 2 software\nthere are two mailing lists:\n\nGeneral questions on analysis, build problems, etc.: alice-project-analysis-task-force@cern.ch\nProblems with jobs submission, certificates, trains: alice-analysis-operations@cern.ch\n\nYou can self-subscribe to them if you are an ALICE member. Go\nto the CERN egroups page, search for the group name, click on it and then\nyou will be presented with an option to subscribe. You can unsubscribe using the same procedure.\nSupport for Run 3 does not rely on mailing lists. We are using Discourse:\n\nALICE Talk\n\nWe also use Mattermost for direct messages or public groups (seek support in the Town Square)\n\nThe ALICE Mattermost team\n\nFor reporting actual bugs and track progress of important development, we use\nJira:\n\nThe ALICE Jira\n\n"},"start/cert.html":{"url":"start/cert.html","title":"Get a Grid certificate","keywords":"","body":"Get a Grid certificate\nWe will illustrate how to get, renew, register and prepare your digital certificates to use the\nALICE Grid services.\nObtain a digital certificate\nYour home institute may provide you with a digital certificate. However, we reccommend you get one\nfrom CERN, because the procedure is very easy and automated when you have a CERN account.\n\nGenerate a new CERN Grid User\n certificate\n\nYou will be asked whether you want to protect your certificate with a password. Note that in most\ncases you will not be allowed to import the certificate if you don't specify a password, so please\nprotect it with a password.\nโ ๏ธ This is not your CERN password. Use a new, arbitrary one.\nProceed until you get a message saying that your certificate is ready to be downloaded: click on it\nand a file called myCertificate.p12 will be downloaded.\nRegister your certificate in your browser\nThere are several ways to add your newly downloaded certificate to your browser, and they depend on\nthe browser and the operating system. We will focus on Firefox as an example.\nOpen Firefox, go to the Preferences, select Privacy and security on the left hand menu.\nScroll the settings page to the bottom and click on the Show certificates... button.\nA new window will open: click the Personal certificates tab. Click Import... and select the\nmyCertificate.p12 file you have just generated. Type the password you have used in the\nprevious step (this is not your CERN password).\nYour newly imported certificate will appear in the list.\nAdd the CERN Grid certificates to your browser\nIn case you navigate to an ALICE HTTPS site and you get a security warning, it is probably because\nyour browser does not have any means to recognize the site as valid.\nโ ๏ธ Most people ignore security exceptions. Do not do that, ever. This is bad, very bad. Someone\ncan steal your data. For real. Without you knowing it.\nGo to this site, there are two links at\nthe bottom of the page saying \"CERN Root/Grid Certification Authority\", etc.: with Firefox as your\nbrowser, click on both of them, and Firefox will ask you if you want to \"trust\" them: say \"yes\" to\nall questions.\nTest your browser setup\nNavigate to the ALICE Grid monitoring page. If you have your personal\ncertificate installed, and the CERN Grid certificates installed as well, Firefox should ask you to\nselect a certificate to be used to authenticate to the site.\nIn case you have many, select the one that identifies you (it should have your full name somewhere)\nissued by the CERN Grid Certification Authority, and tell Firefox to remember it.\nYou should be able to see the page without further ado. Next to the address bar, a green lock icon\nshould appear. If you see broken locks, red icons, warnings of various kinds, then there is some\nkind of security problem and you should repeat the steps above.\nRegister your certificate to the ALICE Grid\nThis operation needs to be performed only once. With Firefox, click on this\nlink and follow the guided procedure, after having selected\nyour personal certificate for authenticating.\nWhen the registration to the VO is successful, you will receive an email informing you. The\nregistration procedure does not involve any modification or re-download of your current certificate.\nIn case you are not receiving this email, you might want to ping Latchezar Betev:\n\n\n\nConvert your certificate for using the Grid tools\nKeep at hand the myCertificate.p12 file you have previously downloaded. You need to convert it\ninto two files (a \"certificate\" and a \"key\") in order to use the ALICE Grid services from the\ncommand line.\nYou will export your certificates to the following directory:\n~/.globus\nNow export the certificate with the following command (you will be prompted for the export\npassword you have selected when you have generated it):\nopenssl pkcs12 -clcerts -nokeys -in ~/Downloads/myCertificate.p12 -out ~/.globus/usercert.pem\n\nThe result will be a file called usercert.pem in your ~/.globus directory. Note that\nyour input file ending with .p12 may have a different name and may be stored in a different\nlocation.\nTime to export the private key:\nopenssl pkcs12 -nocerts -in ~/Downloads/myCertificate.p12 -out ~/.globus/userkey.pem\nchmod 0400 ~/.globus/userkey.pem\n\nWhen it says:\nEnter Import Password:\nyou should provide it with the export password you have entered when you generated it. The next\nquestion will be:\nEnter PEM pass phrase:\nYou should provide it with another password that will be used to protect the private key. You can\nuse the same password as before if you want, but please do not use your CERN password (yes, we\nare stressing this point a lot). This question will be asked twice for confirmation.\nTest your certificate\nYour certificate will be available to the ALICE Grid command line client.\nEnter your ALICE environment and create a \"temporary access token\":\nalienv enter AliPhysics/latest\nalien-token-destroy\nalien-token-init YOUR_ALIEN_USERNAME\n\nโ ๏ธ This assumes you have completed your installation. You do not have\neither alienv or the alien-token-* commands available in case you have never done it.\nThe alien-token-init command will ask you for a password. This is the last password you have used\nwhen you have converted your .p12 certificate into two .pem files.\n Creating JAliEn and AliEn tokensNote that the new JAliEn Grid clients automatically create tokens, while AliEn-ROOT-Legacy (ROOT5) requires running alien-token-init manually.\nThere is alien-token-init for JAliEn, and you can use it to test your credentials or (re)create tokens manually.\n\n"},"building/":{"url":"building/","title":"Build ALICE software","keywords":"","body":"Build ALICE software\nALICE software can be build using officially supported tool called aliBuild:\n๐งช Install ALICE software with alibuild\nThis tool provides users with a way to build the ALICE software directly on their system. On CC7\nyou will benefit from precompiled binaries which will make you save plenty of time. This method\nworks on any modern Linux distribution and macOS.\n"},"building/custom.html":{"url":"building/custom.html","title":"๐งช Installation via alibuild","keywords":"","body":"๐งช Installation via alibuild\nBuilding software has become an increasingly complicated operation, as our software has many\ndependencies and we expect it to work both on your laptop and on the Grid. In addition, we support\nmany Linux distributions and recent macOS versions.\n Please follow the instructions closely!Most of the paths and procedures presented here can be adapted to your system and your taste. You\ncan for instance decide to use different path names, or a different directory structure, it's up to\nyou, however we do not recommend you use different ways of installing the required\ndependencies.\nIn case you do not have particular needs, or you don't know what you are doing, please follow the\nprocedure very carefully and without diverging from it at all.\nThis will make support easier in case something does not work as expected.\n\naliBuild\nALICE uses aliBuild to build software. aliBuild:\n\nknows how to build software via per-package recipes,\nmanages the dependencies consistently,\nrebuilds only what's necessary,\nallows several versions of the same software to be installed at the same time.\n\nOperating systems we support\nAs per policy, the primary supported platform is CERN\nCentOS 7:\nthis is also our official deployment platform for Run 3 software.\nOther operating systems, such as macOS, are supported as development platforms and on a\nbest-effort basis.\nPrerequisites\nAccording to your operating system, please follow the prerequisites below. You will find a list of\npackages to install and configurations to perform.\nPrimary supported platform:\n\nCentOS 7\nCentOS/AlmaLinux 8\nAlmaLinux 9\n\nPlatforms supported on a best-effort basis:\n\nmacOS Ventura and Sonoma (13.0, 14.0)\nUbuntu (20.04 LTS, 22.04 LTS)\nFedora\nLinux Mint\nFollow the instructions for the Ubuntu version your Linux Mint version is based on.\nSpecify the corresponding Ubuntu architecture when running the aliBuild command\nusing the -a option (e.g. -a ubuntu2004_x86-64 for Ubuntu 20.04).\nUse the -a option also with the alienv command.\n\n\n\nIf your operating system is not in any list, it does not mean our software won't work on it;\nit will be just more difficult for you to get support for it.\nOnly in case you cannot install aliBuild in the way described above, you can install aliBuild manually.\nThis procedure should only be used as a fall-back, in case you cannot follow the instructions for your operating system linked above.\nConfigure aliBuild\nAfter you are done installing alibuild you need to configure it by adding the two\nfollowing lines to your ~/.bashrc, ~/.bash_profile, ~/.zshrc or ~/.zprofile\n(depending on your operating system and configuration):\nexport ALIBUILD_WORK_DIR=\"$HOME/alice/sw\"\neval \"$(alienv shell-helper)\"\n\nThe first line tells what directory is used as \"build cache\", the second line installs a \"shell\nhelper\" that makes easier to run certain aliBuild-related commands.\nYou need to close and reopen your terminal for the change to be effective. The directory\n~/alice/sw will be created the first time you run aliBuild.\n\nNote that this directory tends to grow in size over time, and it is the one you need to remove in\ncase of cleanups.\n\nBuild the packages\nWhen aliBuild is installed on your computer and your prerequisites are satisfied, you can move to\nthe next step.\n\n๐ Build the packages\n\n"},"building/prereq-centos7.html":{"url":"building/prereq-centos7.html","title":"Prerequisites for CentOS 7","keywords":"","body":"aliBuild Prerequisites for CentOS 7\nFor ALICE O2, CERN CentOS 7 (CC7)is the officialy supported target platform. Since CC7 is CentOS 7 with additional CERN packages, instructions apply to vanilla CentOS 7 as well.\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps \nyum update -y\nyum install -y alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-centos8.html":{"url":"building/prereq-centos8.html","title":"Prerequisites for CentOS 8","keywords":"","body":"aliBuild Prerequisites for CentOS 8\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\n\nyum install -y epel-release\nyum install -y dnf-plugins-core\nyum config-manager --set-enabled powertools\nyum update -y\n\ndnf group install -y \"Development Tools\"\n\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_el8.x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-alma9.html":{"url":"building/prereq-alma9.html","title":"Prerequisites for Alma 9","keywords":"","body":"aliBuild Prerequisites for Alma 9\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\n\ndnf install -y epel-release dnf-plugins-core\ndnf update -y\ndnf config-manager --set-enabled crb\ndnf group install -y 'Development Tools'\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_el9.x86-64/\nenabled=1\ngpgcheck=0\nEOF\ndnf update -y\ndnf install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-macos.html":{"url":"building/prereq-macos.html","title":"Prerequisites for macOS","keywords":"","body":"aliBuild prerequisites for macOS\nALICE software on macOS is supported on a best effort basis. Even though we systematically check macOS builds there is no guarantee that software builds or runs correctly. Support requests might have low priority. That said, we were able to successfully build on:\n\nVentura (13.0) on x86, M1 and M2\nSonoma (14.0) on x86, M1 and M2\n\nGet Xcode\nXcode bundles the necessary tools to build software in the apple ecosystem including compilers, build systems and version control.\n\nDownload it from the App Store\nOpen once installed. It will ask to install additional components - approve the action.\nOpen a terminal (Applicaions>Utilities>Terminal) and install the command line tools using:sudo xcode-select --install\n\n\napprove the license conditions bysudo xcodebuild -license\n\n\n\nGet Homebrew\nHomebrew is a command-line package manager for macOS used to install software packages similar to yum on CentOS or apt on Ubuntu.\n\nInstall Homebrew using the instructions on their webpage.\nOnce installed detect any problems regarding Homebrew and your system usingbrew doctor\n\n\n\nUninstall ROOT\nIf you have an existing ROOT installation on your system, this will interfere with the aliBuild installation, and will cause difficult-to-debug compilation errors.\nPlease uninstall any existing copy of ROOT on your system.\nThe uninstallation method depends on how you installed it.\nFor example, if you originally installed ROOT using Homebrew, you should uninstall it using brew uninstall root.\nAfter uninstalling ROOT, remove any reference to ROOT from your .zprofile, .zshrc and any other shell configuration files.\nThen close and re-open your terminal window.\nInstall the required packages\nNote that Homebrew does not run as root. Do not prepend sudo to any of the following commands.\n\nInstall the prerequisites and aliBuild via:brew install alisw/system-deps/o2-full-deps alisw/system-deps/alibuild\n\n\nSet up Homebrew in your shell by running the following command:echo 'eval \"$(/opt/homebrew/bin/brew shellenv)\"' >> ~/.zprofile\n\n\nClose Terminal and reopen it to apply changes.\n\n Check installed package versionsHomebrew might sometimes install multiple versions of some packages, such as llvm or python. This can happen after you have used brew for a while.\nMake sure you have only the currently-supported versions of packages installed, as listed in the dependencies of alisw/system-deps/o2-full-deps, paying particular attention to llvm and python.\nYou may have to run brew uninstall for package versions that are unsupported by ALICE, if they have ended up installed on your system.\n\n(Recommended) Exclude your work directory from Spotlight\nThe mac search engine (Spotlight) will be indexing the build directory which can have severe effects on your system performance. To avoid that, you can exclude your working directory (we are assuming ~/alice - create if not yet existing).\nGo to (Apple) menu>System preferences>Spotlight. In the Privacy tab, hit the + button. Now select the ~/alice directory and confirm.\nYou are now ready for installing aliBuild and start building ALICE software\nTroubleshooting:\nSome users have reported that homebrew commands might terminate with an error. The solution oddly enough seems to be to execute the above command multiple times until brew does not complain anymore.\nIf you have just upgraded your Xcode or macOS, you should run brew reinstall instead, in order to force the reinstallation of already installed packages. You also might want to run brew cleanup at the end to free up some space.\n"},"building/prereq-ubuntu.html":{"url":"building/prereq-ubuntu.html","title":"Prerequisites for Ubuntu","keywords":"","body":"aliBuild prerequisites for Ubuntu\nALICE software on Ubuntu is supported on a best effort basis. There is no guarantee that software builds or runs correctly. Support requests might have low priority. We were able to successfully build on:\n\nUbuntu 18.04 LTS\nUbuntu 20.04 LTS\nUbuntu 22.04 LTS\n\nInstall required system packages\nWith root permissions, i.e. sudo, update your package sources:\nsudo apt update -y\n\nWith root permissions, i.e. sudo, install the following packages:\nsudo apt install -y curl libcurl4-gnutls-dev build-essential gfortran libmysqlclient-dev xorg-dev libglu1-mesa-dev libfftw3-dev libxml2-dev git unzip autoconf automake autopoint texinfo gettext libtool libtool-bin pkg-config bison flex libperl-dev libbz2-dev swig liblzma-dev libnanomsg-dev rsync lsb-release environment-modules libglfw3-dev libtbb-dev python3-dev python3-venv python3-pip graphviz libncurses-dev software-properties-common gtk-doc-tools\n\nInstalling aliBuild\nAliBuild, our build tool, is installed as a standard ubuntu package, provided you enable the alisw PPA repository.\nThis is done with:\nsudo add-apt-repository ppa:alisw/ppa \nsudo apt update\nsudo apt install python3-alibuild\n\nYou are now ready to start building ALICE software\n"},"building/prereq-fedora.html":{"url":"building/prereq-fedora.html","title":"Prerequisites for Fedora","keywords":"","body":"aliBuild prerequisites for Fedora\nALICE software on Fedora is supported on a best effort basis. There is no guarantee that software builds or runs correctly. Support requests might have low priority.\nInstall or Upgrade the Required Packages\nWith root permissions, i.e. sudo or as root install the prerequisites using:\nyum install -y epel-release\nyum install -y dnf-plugins-core\nyum config-manager --set-enabled powertools\nyum update -y\n\ndnf group install -y \"Development Tools\"\n\ncat /etc/yum.repos.d/alice-system-deps.repo\n[alice-system-deps]\nname=alice-system-deps\nbaseurl=https://s3.cern.ch/swift/v1/alibuild-repo/RPMS/o2-full-deps_fedora.x86-64/\nenabled=1\ngpgcheck=0\nEOF\nyum update -y\nyum install -y alice-o2-full-deps alibuild\n\nYou are now ready to start building ALICE software\n"},"building/manual-install.html":{"url":"building/manual-install.html","title":"Fall-back manual installation method","keywords":"","body":"Fall-back manual installation method\nIn the first instance, you should always follow the instructions for your operating system linked under \"Prerequisites\" here.\nThis ensures that you only have a single installation of aliBuild, and that it is updated automatically with the rest of your system.\nIf you cannot follow the instructions linked above for any reason (such as if you are using a shared machine and you do not have administrative access), see below for alternative ways to install aliBuild.\nIf you follow these instructions, you are responsible for keeping aliBuild up to date manually.\nPlease remember to update aliBuild before asking for support, as any issues you encounter may already be solved in the latest version.\nI don't have root permissions\nIn case you don't have root permissions, one of the possibilities is installing aliBuild under a\nuser-owned directory. Start with opening your ~/.bashrc, ~/.bash_profile, ~/.zshrc or ~/.zprofile\n(this depends on your system), and add the following line at the end:\nexport PATH=\"$HOME/.local/bin:$PATH\"\n\nNow close all your terminals and reopen them to load the new configuration.\nThe operations above need to be performed only once. Now, to install or upgrade aliBuild, just do:\npython3 -m pip install alibuild --upgrade --user\n\n\nThis time we did not specify sudo and we have added the --user option.\n\nVerify you have aliBuild in your path:\ntype aliBuild\n\nYou are responsible for keeping aliBuild up to date manually.\nYou can update by running the following command:\npython3 -m pip install alibuild --upgrade --user\n\nNow continue by configuring aliBuild.\nI need a special version of aliBuild\nIn some cases you might want to install a \"release candidate\" version, or you want to get the code\ndirectly from GitHub. By default, the last stable version is installed. Do not install a special\nversion of aliBuild if you were not instructed to do so or if you don't know what you are doing, we\nprovide no support for unstable releases!\nFirst, remove any other copy of aliBuild installed on your system in any other way, to avoid conflicts.\nTo install a release candidate (for instance, v1.5.1rc3):\npython3 -m pip install --user --upgrade alibuild==v1.5.1rc3\n\nTo install from GitHub (you can specify a tag or a hash, or another branch, instead of master):\npython3 -m pip install --user --upgrade 'git+https://github.com/alisw/alibuild@master'\n\nNow continue by configuring aliBuild.\n"},"building/build.html":{"url":"building/build.html","title":"๐ Build the packages","keywords":"","body":"๐ Build the packages\nALICE software has several dependencies: aliBuild takes care of downloading them for you. aliBuild\nwill also automatically download precompiled binaries on supported versions of CentOS/Alma and Ubuntu.\naliBuild will download and compile all the dependencies caching data under $ALIBUILD_WORK_DIR. You\nwill never need to access this directory. The source code for the packages you will actually develop\nwill be stored elsewhere.\nIn the following example, we will assume that you need to download AliRoot/AliPhysics for developing\nRun 2 software, and O2/O2Physics for Run 3.\nPrepare your source code\nWe assume your work area is ~/alice.\nSo, first off, create the directory and move to it:\nmkdir -p ~/alice\ncd ~/alice\n\nIf you want to develop analysis code, download AliPhysics:\naliBuild init AliPhysics@master\n\nOnly if you need to develop the Run 2 core software (unlikely), download AliRoot:\naliBuild init AliRoot@master\n\nIf you need to develop for Run 3, download O2Physics:\naliBuild init O2Physics@master\n\nOnly if you need to develop the Run 3 core software (unlikely), download O2:\naliBuild init O2@dev\n\nSource code and recipes\nIf you perform ls under your work directory, you will see the packages you have downloaded via\naliBuild init, plus an alidist directory.\nThe alidist directory contains software recipes, telling aliBuild how the software is built. Your\nalidist directory and your software source code are Git directories managed by you: you need\nto keep them up-to-date manually.\n Check names of your remote repositoriesWith older versions of aliBuild, the central remote repository (used for pulling updates) would be\ncalled origin instead of the usual name upstream and the personal (fork) remote repository (used\nfor pushing changes) would be called instead of the usual name origin.\nPlease check your settings using git remote -v and adjust the Git commands mentioned in\nthe following instructions accordingly, if needed.\n\nUpdate your software by cding into its directory and running:\n# use dev instead of master for O2\ngit checkout master\ngit pull --rebase upstream master\n\nThis will work in most cases and will keep your changes. It will also complain if there is some\nconflict you need to solve manually. You also have the nuclear option, to be used if you are sure\nyou do not have any important data:\n# use dev instead of master for O2\ngit checkout master\ngit fetch --all\ngit reset --hard upstream/master\n\nInstead of resetting to the current upstream version, you may want to download specific versions of\nthe software:\ncd ~/alice/AliPhysics\ngit fetch --all --tags\ngit checkout v5-09-42-01\n\n Why manual updates?Software downloaded under your working directory is your responsibility. Our tools will not take any\naction to update it: imagine if you lose important data because of an automatic update!\nAs a developer, and ALICE contributor, you must be capable of using and understanding git.\n\nCheck your prerequisites\naliBuild comes with the command aliDoctor that will help you identifying if your prerequisites\nwere installed correctly. In general, aliBuild is capable of building all required software\ndependencies, but it has also the ability to take them \"from the system\" if possible, resulting in\nless time spent for building for you.\nRun the aliDoctor command to check dependencies for Run 2 software:\ncd ~/alice\naliDoctor AliPhysics\n\nFor Run 2 software based on ROOT 6 (note: this is the only option on macOS):\ncd ~/alice\naliDoctor AliPhysics\n\nFor Run 3 software:\ncd ~/alice\naliDoctor O2Physics\n\naliDoctor will warn you that some packages have to be built as they could not be found from the\nsystem. If you have followed the instructions, this list should contain nothing more than:\n\nboost\nCMake\nGSL\nnanomsg\nprotobuf\nflatbuffers\nVc\nyaml-cpp\nZeroMQ\nSWIG\n\nIn particular, you should never have Python or Python-modules. If the output is longer than this\nlist, please go through the prerequisites once again and run aliDoctor again. If the output\ncontains those packages, or less packages, then you are fine and you may continue.\n\nIf you think a package is shown but should not be in the list because you are sure you have\ninstalled it, it might just be that its version it's incompatible (this frequently happens with\nCMake) or you are missing the \"development\" package for that component.\n\nBuild and rebuild\nYou can build the whole Run 2 software stack based on ROOT 6 with:\ncd ~/alice\naliBuild build AliPhysics\nSimilarly, for O2Physics:\ncd ~/alice\naliBuild build O2Physics\nIf you want to build O2 and run the tests as well (same way as they are run on the pull request\ncheckers), with --debug to see the full output:\ncd ~/alice\naliBuild build O2 --debug -e ALIBUILD_O2_TESTS=1\nโ ๏ธ It is recommended to run the first O2 build without the tests enabled to let it complete. You\nwill not have to rerun it from scratch because of test failures like this.\nUsing the combinations above on CentOS 7 will make aliBuild automatically download the precompiled \nbinaries for almost all packages.\n AliPhysics with ROOT 6 and the GridThe command above will produce AliPhysics with ROOT 6 as a dependency. When using this version, you\nwill only be able to submit Grid analysis jobs using ROOT 6-based builds (whose name ends with\n_ROOT6). If you still need ROOT 5 only for submitting Grid jobs, there is no need to install it:\njust use it from CVMFS by logging in to lxplus.cern.ch.\n\nOther build options\nThe options above are suitable for a CentOS 7 installation, since precompiled binaries\nwill be downloaded. You also have other installation options according to your needs: it is not\nguaranteed that cached binaries are available for the following options, but they may be faster to\nbuild.\nBuild AliPhysics based on ROOT 5 (legacy):\naliBuild build AliPhysics --defaults user # without GEANT 3, GEANT 4, DPMJET\naliBuild build AliPhysics --defaults release # full ROOT 5 stack\n\nโ ๏ธ ROOT 5 does not work on macOS. Use a ROOT 6 version compatible with ROOT 5 if you really need it\n(see below).\n\nRebuild existing installations\nAs a general rule, your existing installation can be smartly rebuilt by using the exact same\naliBuild build command as you did the first time. aliBuild will not rebuild existing software and\nit will simply rebuild the changes.\nYou may find it fast to skip the aliBuild part completely. You can simply move to the build\ndirectory and run make (the alienv part is explained\nlater):\ncd $ALIBUILD_WORK_DIR/BUILD/AliPhysics-latest/AliPhysics\nalienv setenv GCC-Toolchain/latest -c cmake --build . -- -j install\n\nReplace with a sensible number (e.g. slightly more than the actual number of\nyour cores).\n You lied. aliBuild is rebuilding everything! ๐คฌOne or more of the following actions might change the way aliBuild sees and uses the dependencies\nand might result in a full (or nearly) rebuild. So, if an important conference is approaching\n(well: it always does, doesn't it?) plan the following actions accordingly as they might increase\nthe build time:\n\nUpdating recipes in alidist\nRemoving the cache $ALIBUILD_WORK_DIR or forgetting to export the variable\nAdding or removing system dependencies as seen by aliDoctor\nUpdating your operating system or compilers (including Xcode on macOS)\n\n\nUse your local software installations\nYou will not find the packages you have built immediately available on your shell: we provide a tool\ncalled alienv that configures your shell according to the packages you want to load. alienv is\ncapable of switching between different versions of the same package without a hassle.\nList your available packages with:\nalienv q\n\nLoad the latest version you have built of a package (AliPhysics for instance):\nalienv enter AliPhysics/latest\n\nโ ๏ธ Dependencies are loaded automatically. Do not attempt to load AliRoot and ROOT as well, you will\nfind them automatically in the environment! alienv enter is verbose and will inform you about the\nloaded packages if you have doubts.\nThe alienv enter command drops you to a new shell. Unload the packages by simply exiting it with\nthe exit command.\n I have several AliPhysics versions. Which one is AliPhysics/latest?aliBuild will tell you exactly what you need to type in order to load the software you have just\nbuilt. Just use aliBuild's suggestion in place of AliPhysics/latest wherever appropriate: for\ninstance, if you have several AliPhysics versions, AliPhysics/latest will point to the version you\nhave built more recently, not the latest.\n\nLoad environment in the current shell or script\nIf you know what you are doing, you can also load the environment in your current shell, and\nsubsequently unload it (this is not recommended):\nalienv load AliPhysics/latest\nalienv unload AliPhysics/latest\n\nIf you want to load the environment inside a script you are developing, just add this line (works\nwith Bash scripts):\nsource $(alienv printenv AliPhysics/latest)\n\nRun a single command in the environment\nYou can also run a single command (for instance, aliroot) in the given environment without loading\nit in the current shell:\nalienv setenv AliPhysics/latest -c aliroot myMacro.C+\n\n ๐ซDo not load alienv automatically in your shellEven if this is technically possible, it is strongly not recommended to load the environment with\nalienv in your ~/.bashrc! You must keep your environment pristine for safely running\naliBuild. By not loading the environment automatically, you will avoid a huge source of errors.\nDo you still find annoying to type alienv enter AliPhysics/latest every time you want to use it?\nYou can add the following line in your ~/.bashrc to make it more convenient:\nalias ali='alienv enter AliPhysics/latest'\n\nYou are creating an alias called ali, that will load the environment by just typing it at the\nprompt. Of course you can name it any way you want.\n\nSpecial build needs\nRead below if you have some advanced requirements for your local installation.\nBuild by using less resources\nBuilding takes by default all the available CPU and most of the memory of your computer,\nconsiderably slowing down your work. In some cases you may want to reduce the number of cores\navailable to aliBuild by using the -j option:\naliBuild build AliPhysics -j 1\n\nDo not use the cache on CentOS 7\naliBuild will attempt to fetch the precompiled binaries automatically\non CentOS 7: no need to specify extra options.\nIf you want not to use them for some reason, it is important you follow the CentOS 7\nprerequisites first: this will allow aliBuild to take as many packages as\npossible from the system. You will then need to add the --always-prefer-system option to the\naliBuild build command. For instance:\naliBuild build AliPhysics --always-prefer-system\n\nBuild the same source multiple times with different options\naliBuild and alienv give you the ability to build the same development source with different\ndefaults without duplicating the source, and without conflicts.\nImagine we are under ~/alice and we have cloned AliRoot and AliPhysics with the aliBuild init\ncommand above. We build AliPhysics twice, once with ROOT 5 and a second time against ROOT 6.\nLet's first build AliPhysics with ROOT 5:\naliBuild build AliPhysics --defaults user -z aliroot5\n\nโ ๏ธ Note the -z aliroot5 command; it is assigning a nickname to the build for distinguishing it\nmore easily when using it.\nThe command ends with a message saying what to do to use the package:\nalienv enter AliPhysics/latest-aliroot5-user\n\n\nLet's now build the same AliPhysics with ROOT 6:\naliBuild build AliPhysics -z aliroot6\n\nNow, the message tells us to type:\nalienv enter AliPhysics/latest-aliroot6-o2\n\nKeep in mind that:\n\naliBuild always tells you what is the package name to load at the end of the build\nyou can load the two environments separately, in two different shells, with no chance of a mixup\nyou have used the same set of sources for generating two distinct builds\nalienv enter AliPhysics/latest will load the latest you have built, which can either be the\nROOT 5 or ROOT 6-based version: given its ambiguity, do use explicit names instead\n\nIt is also possible to directly run aliroot (or any command you want) without \"entering\" the\nenvironment:\nalienv setenv AliPhysics/latest-aliroot5-user -c aliroot\nalienv setenv AliPhysics/latest-aliroot6-o2 -c aliroot\n\nThe aliroot command will be run with the correct environment in both cases.\n Migrating from ROOT 5 to ROOT 6While you are at it, if you want to migrate your existing code to ROOT 6 (and make sure it works\nthere) check out our migration guide.\n\nBuild specific releases (tags) of the software\nIt might come useful to build a certain tag of AliRoot and AliPhysics instead of simply pulling the\nmaster.\n\nNote that we only guarantee that the current AliPhysics master works against the latest AliRoot\ntag! It is therefore possible (though a rare occurrence) that the current AliRoot master breaks\nthe current AliPhysics master.\n\nIf you have your source code in \"development mode\" (i.e. downloaded locally by means of aliBuild\ninit), since your AliRoot/AliPhysics/O2 directories are mere Git\nrepositories, you simply need to cd into them and\ncheckout the Git version you want.\nFor instance, if you want to build AliPhysics against AliRoot v5-09-33, you would need to first\nmove to the AliRoot directory and check the version out:\ncd ~/alice/AliRoot\ngit fetch upstream --tags\ngit checkout v5-09-33\n\nThen update your AliPhysics master:\ncd ~/alice/AliPhysics\ngit checkout master\ngit pull --rebase upstream master\n\nand then build normally using the aliBuild command. You might want to build using different -z\noptions as explained here in order\nto have different builds usable in parallel without duplicating your source code.\n๐งน Delete obsolete builds\nWith frequent rebuilding of packages, obsolete builds can pile up and occupy a lot of precious\ndisk space.\nBasic cleanup\nThe simplest way to get rid of obsolete builds is to let aliBuild do its best by running:\naliBuild clean\n\nwhich can take the optional argument --aggressive-cleanup that deletes also source code of built\ndependency packages and downloaded .tar.gz archives.\nIn general, it's good practice to run aliBuild clean always after aliBuild build.\nThis might not be enough, as aliBuild will not delete any build directory pointed to by a symlink\nthat has \"latest\" in its name, even when that build is not needed by any other package anymore.\nManual intervention is therefore sometimes needed.\nDeep cleanup\nIf you want to keep only the latest builds of your development packages (and their dependencies),\nyou can make aliBuild delete the rest with a little trick.\n\nDelete symlinks to all builds:find $ALIBUILD_WORK_DIR/$(aliBuild architecture)/ -mindepth 2 -maxdepth 2 -type l -delete\nfind $ALIBUILD_WORK_DIR/BUILD/ -mindepth 1 -maxdepth 1 -type l -delete\n\nIn case you specified the architecture manually (using the -a option with aliBuild build), you should replace $(aliBuild architecture) with your manually specified architecture.\nRecreate symlinks to the latest builds of development packages (and their dependencies)\nby running aliBuild build for each development package.\nLet aliBuild delete all the other builds by running aliBuild clean.\n\n"},"building/precomp.html":{"url":"building/precomp.html","title":"๐ฆ Use the precompiled binaries","keywords":"","body":"๐ฆ Use the precompiled binaries\nYou can run our precompiled binaries from CVMFS by simply logging to lxplus or lxplus7:\nssh @lxplus.cern.ch\nssh @lxplus7.cern.ch # required for O2\n\nIf you are an ALICE user, you are welcomed with a message telling you exactly what to do. To load\na specific analysis tag of AliPhysics you can do:\n/cvmfs/alice.cern.ch/bin/alienv enter AliPhysics/vAN-20181121_ROOT6-1\n\nYou can list all the available versions with (very slow ๐):\n/cvmfs/alice.cern.ch/bin/alienv q\n\nor you can simply consult the list of Grid packages here.\n\nO2 is available on the \"nightlies\" repository of ALICE. You can use it only from lxplus7.cern.ch:\nit will not work on SLC6. List the packages:\n/cvmfs/alice-nightlies.cern.ch/bin/alienv q\n\nLoad a specific version:\n/cvmfs/alice-nightlies.cern.ch/bin/alienv enter O2/nightly-20181121-1\n\n"},"building/devel.html":{"url":"building/devel.html","title":"๐ช Develop a single package (Experimental)","keywords":"","body":"Develop a single package reusing a CVMFS / RPM installation EXPERIMENTAL\nFor those cases where you want to develop a single O2Suite package, for example ALICE O2, it's now possible to reuse a preexisting installation in CVMFS or\ninstalled via the RPM packages.\nIn order to do so you must make sure you point WORK_DIR to your base installation folder. E.g. for lxplus:\nexport WORK_DIR=/cvmfs/alice.cern.ch\n\nand that you properly set your ALIBUILD_ARCH_PREFIX. E.g. for lxplus:\nexport ALIBUILD_ARCH_PREFIX=el7-x86_64/Packages\n\nassuming you want to use nightly-20200810-1 as baseline, you can then do:\n. $WORK_DIR/$ALIBUILD_ARCH_PREFIX/O2/nightly-20210120-1/etc/profile.d/init.sh\n\nThis will fill your environment with all the requirements needed to properly build O2.\nYou can checkout and build most of the AliceO2Group packages with:\ngit clone --origin upstream https://github.com/AliceO2Group/AliceO2 O2\nmkdir -p O2/objs\ncd O2/objs\ncmake ..\ncmake --build . --target all -j8\n\nThis is not a replacement for the full alibuild environment, which allows you to build multiple packages at once or to keep track of\nchanges in alidist, however it should work already fairly well to develop a single package.\nCaveats:\n\nRuntime environment is currently not handled fully and you need to either use -DCMAKE_INSTALL_PREFIX or run executables from stage/bin.\n\n"},"analysis/welcome.html":{"url":"analysis/welcome.html","title":"Writing an analysis task","keywords":"","body":"How to write your analysis task for AliPhysics\nThe goal of this introduction is to explain to you how you can write and run a minimal analysis task for the AliPhysics analysis framework. This task will not give you any real 'physics' results, it's just a minimal example of what you need know to do a data analysis for the ALICE experiment. It is assumed that you have basic knowledge of both C++ and ROOT.\nAt the end of this introduction, you will understand what happens in your analysis task, and you will understand how to run it on your laptop, on the Grid, and in 'LEGO-trains'. What all of this means will become clear later on. After you have read this introduction, you can follow steps 1 through 7 of the Analysis tutorial exercises, which will give you hands-on experience with building an analysis from the grounds up, and running it. This of course requires that you have a working version of the ALICE software stack available on your computer. \n"},"analysis/classes.html":{"url":"analysis/classes.html","title":"AliAnalysisTaskSE","keywords":"","body":"Introduction - C++ classes\nAll the code that you will find in ROOT, AliRoot and AliPhysics is written in the form of C++ classes. A class is a data type which is defined by the user, and allows for creating data members and functions specific for that class. By convention, each class in AliPhysics, AliRoot, and ROOT, is stored in its own header (.h) and implementation file, which have the same name as the class it defines (so later on, we will see that your analysis class, stored in a file 'AliAnalysisTaskMyTask', is called 'AliAnalysisTaskMyTask'). \n C++ .... ?If you have never heard of classes (or C++), it might be a good idea to go through a C++ manual, an excellent one, with plenty of hands-on examples, can be found here: http://www.cplusplus.com/doc/tutorial/. \n\nClasses are extended structures which contain both variables and functions (which are called methods) as members. Often, variables must be accessed through these methods. This might sound a bit abstract, but it becomes much more clear when you look at in a small code example:\n class Rectangle\n {\n private:\n int width, height;\n public:\n Rectangle(int,int);\n int GetArea() {return height * width;}\n }\n\nHere we defined a class, called Rectangle, which has variables width and height, and a method called GetArea which gives us access to the members. \nInheritance\nClasses are nice and important, because they can be derived from one-another (a feature called inheritance. Look at the figure below \n\nIn this figure, Rectangle is derived from base class Polygon, and inherits its members. If we want to define a second class, Triangle, which is also a polygon and will therefore have features in common with Rectangle, we can also derive it from base class Polygon. This avoids having to repeat common code for multiple which share features. \n BewareClasses are very powerful, but inheritance can sometimes make it tricky to understand how code is structured!\n\nLet's take a look at how our classes would look like when we put them down as C++ code. First, we define out base class, the polygon\nclass Polygon\n{\n private:\n int width, height;\n}\n\nThis example lives in 2-dimensional space, so our polygon is fully defined by its width and its height. The two polygons that we want to define, are a rectangle and a triangle. The rectangle can be defined as follows\n class Rectangle : public Polygon\n {\n public:\n Rectangle(int,int);\n int GetArea() {return height * width;}\n }\n\nNote that we do not have to define the members height and width here, as they are already defined in our base class! The only method that is specific to the rectangle, is the GetArea method. \nOur triangle class can be written as\n class Triangle : public Polygon\n {\n public:\n Triangle(int,int);\n int GetArea() {return (height * width)/2;}\n }\n\nAgain, width and height are defined in the base class Polygon, but also the Triangle class gets its own GetArea method. So now we have seen how inheritance makes our classes (and our life) simpler: by defining common functionality in a base class, we avoid repetition of code, which could easily lead to mistakes.\n Example from AliPhysics - The AliMCEvent classInheritance is used widely in C++ code, and therefore also in AliROOT and AliPhysics. Take a look at the AliMCEvent class below\n class AliMCEvent : public AliVEvent {\n public:\n ....\n private:\n ....\n }\n\nHere AliMCEvent is derived from its base class AliVEvent, in the same way as the Triangle is derived from the base class Polygon. Classes such as AliESDEvent and AliAODEvent are also derived from AliVEvent, preventing a lot of boilerplate (i.e. needlessly repetitive) code.\n\n Class headers ... ? C++ classes are, in code bases, usually split into a header file (extention .h) and an implementation file (extension .cxx). A header file is generally used to define all of the functions, variables and constants contained in a class. There are multiple good reasons for splitting code into an implementation and a header - can you think of a few? \n\nAliAnalysisTaskSE\nNow that you are an expert at C++ classes, you might wonder why classes are relevant to writing an analysis task. The reason is the following: in the AliPhysics analysis framework, all analysis tasks are derived from the same base class, called AliAnalysisTaskSE, where SE stands for 'single event'. This class in turn, is derived from the class AliAnalysisTask (if you are interested, you can go through the code and follow the full chain of inheritance). \nSince all analysis tasks derive from AliAnalysisTaskSE, all analyses share the following common, base methods:\n AliAnalysisTaskSE::AliAnalysisTaskSE();\n AliAnalysisTaskSE::AliAnalysisTaskSE(const char*);\n AliAnalysisTaskSE::~AliAnalysisTaskSE();\n AliAnalysisTaskSE::UserCreateOutputObjects();\n AliAnalysisTaskSE::UserExec(Option_t*);\n AliAnalysisTaskSE::Terminate(Option_t*);\n\nThese are methods that you will always need to implement. \nIn the following section, we will go through these methods in detail.\nClass constructors and destructors\nThe functions\n AliAnalysisTaskSE::AliAnalysisTaskSE(); // class constructor\n AliAnalysisTaskSE::AliAnalysisTaskSE(const char*); // class constructor\n AliAnalysisTaskSE::~AliAnalysisTaskSE(); // class destructor\n\nare your class constructors and destructor. These are standard C++ features, that are called when you create or delete an instance of your class. We will later on see, why you need to define two different class constructors. \nAliAnalysisTaskSE::UserCreateOutputObjects()\nIn this function, the user (i.e. the analyzer) can define the output objects of the analysis. These are e.g. histograms in which you store your physics results. These output objects can be attached to the output file(s) of the analysis. \n Please noteWhen you are designing your class for your analysis, it (obviously) pays off to think about which output you need to extract the physics; do you want ten 1D histograms, or will four 2D histograms supply much more information? Or would you prefer writing certain information to a TTree, such that you have full information available when post-processing on your laptop? All these different output objects bring memory and size considerations, so choose well.\n\nAliAnalysisTaskSE::UserExec()\nThis function is called for each, single event over which your analysis task runs. This function is your 'event loop'. Examples of useful things to do in the UserExec() function:\n\nCheck if an event has properties that you want to have in your analysis, if not return;\nAccess the physics objects specific to your analysis (e.g. the charged particles in this event, or find the highest momentum particle)\nFill the histograms or other output objects\n\n Please noteIf the function AliAnalysisTaskSE::SelectCollisionCandidates(UInt_t trigger_mask) is called before you launch your analysis, UserExec() will only be executed for events which pass the trigger selection that you have specified. \n\nAliAnalysisTaskSE::Terminate()\nThe Terminate function is called at the very end of the analysis, when all events in your input data have been analyzed. Often, you leave the Terminate function empty: usually it is more practical to write a small macro that performs post-processing on your analysis output files, rather than deferring this functionality to the Terminate function. \n"},"analysis/alianalysistaskmytask.html":{"url":"analysis/alianalysistaskmytask.html","title":"Your analysis task","keywords":"","body":"Your analysis task\nIn the previous section we discussed some of the basics of writing an analysis task from a 'theoretical viewpoint'. In this section, we will go through a working analysis class line-by-line. \nAs you now know, your own analysis task will be derived from the base class AliAnalysisTaskSE. We will use a fixed format to write our tasks, which means that we need to create three files:\n\nThe header file (.h) which contains function prototypes and in which your class members are defined\n\nThe implementation file (.cxx), in which the methods of your analysis are implemented\n\nAn AddTask.C macro which creates an instance of your class\nand configures it.\n\n\nThe class header (.h)\nLetโs start by looking at our header (the .h file), where we define the prototypes of all the methods that we want to implement in our class\n#ifndef AliAnalysisTaskMyTask_H\n#define AliAnalysisTaskMyTask_H\n\nclass AliAnalysisTaskMyTask : public AliAnalysisTaskSE \n{\npublic:\n // two class constructors\n AliAnalysisTaskMyTask();\n AliAnalysisTaskMyTask(const char *name);\n // class destructor\n virtual ~AliAnalysisTaskMyTask();\n // called once at beginning of runtime\n virtual void UserCreateOutputObjects();\n // called for each event\n virtual void UserExec(Option_t\\* option);\n // called at end of analysis\n virtual void Terminate(Option_t\\* option);\n /// \\cond CLASSDEF\n ClassDef(AliAnalysisTaskMyTask, 1);\n /// \\endcond\n};\n\n#endif\n\nLet's go through the snippet of code line-by-line. First of all, we see\n#ifndef AliAnalysisTaskMyTask_H\n#define AliAnalysisTaskMyTask_H\n.\n.\n.\n#endif\n\nThese three lines form an include guard (sometimes called macro guard, or header guard). This construct is used to avoid the problem of double inclusion: should the header of your class be included more than once, the include guard will protect your code from double definitions which result in invalid code. \n Include guardsWhat is the risk of not using include guards?\n drum roll Click to expandSay that you have a header file, called grandparent.h, in which you define a struct\nstruct foo {\n int member;\n};\n\nand you create a second file parent.h where you write\n#include \"grandparent.h\"\n\nand even a third one, child.h in which you do\n#include \"grandparent.h\"\n#include \"parent.h\"\n\nAfter preprocessing, the content of the file child.h will be\nstruct foo {\n int member;\n};\nstruct foo {\n int member;\n};\n\nsince child.h has indirectly included two copies of the text in the header file grandparent.h. This will cause a compilation error, since the struct foo will be defined twice. Using include guards, this problem would not have arisen. \n\nClass definition and constructors\nIf we continue looking at the code, we see the class definition and two class constructors\nclass AliAnalysisTaskMyTask : public AliAnalysisTaskSE \n{\npublic:\n // two class constructors\n AliAnalysisTaskMyTask();\n AliAnalysisTaskMyTask(const char *name);\n // class destructor\n virtual ~AliAnalysisTaskMyTask();\n\nThe first line means that we define a class AliAnalysisTaskMyTask, which is derived from AliAnalysisTaskSE. \nClass constructors and destructor\nThe two functions AliAnalysisTaskMyTask() and AliAnalysisTaskMyTask(const char *name) are class constructors. A class constructor is a special function in a class that is called when a new object of the class is created. \nWe always need to define two class constructors for our analysis task, why this is, will be explained later. The third function is the class destructor. A destructor is also a special function which is called when the created object is deleted. We will later see, that a class that has pointer data members should include, in addition to a destructor, a copy constructor and an assignment operator - but for now we can just forget about those. \nAliAnalysisTaskSE inherited functions\nAfter the constructors and destructors, we define the prototypes of the functions that we have already seen in the AliAnalysisTaskSE section\n // called once at beginning of runtime\n virtual void UserCreateOutputObjects();\n // called for each event\n virtual void UserExec(Option_t* option);\n // called at end of analysis\n virtual void Terminate(Option_t* option);\n\nThese functions will be the heart of our analysis. In the UserCreateOutputObjects, we will define whatever output we want to write to our root files. The UserExec function will be called for all events in the data sample that we are looking at. Finally, Terminate is called at the very end of the analysis. \n Virtual functions In the code snippet above, we see the virtual keyword. Do you know what this means ? \n Click to show answer Click to expandConsider the following simple program which is an example of runtime polymorphism.\nThe main thing to note about the program is, derived class function is called using a base class pointer. The idea is, virtual functions are called according to the type of object pointed or referred, not according to the type of pointer or reference. In other words, virtual functions are resolved late, at runtime (which makes them powerful, but costly):\nclass Employee \n{ \npublic: \n virtual void raiseSalary() \n { /* common raise salary code */ } \n\n virtual void promote() \n { /* common promote code */ } \n}; \n\nclass Manager: public Employee { \n virtual void raiseSalary() \n { /* Manager specific raise salary code, may contain \n increment of manager specific incentives*/ } \n\n virtual void promote() \n { /* Manager specific promote */ } \n}; \n\n// Similarly, there may be other types of employees \n\n// We need a very simple function to increment salary of all employees \n// Note that emp[] is an array of pointers and actual pointed objects can \n// be any type of employees. This function should ideally be in a class \n// like Organization, we have made it global to keep things simple \nvoid globalRaiseSalary(Employee *emp[], int n) \n{ \n for (int i = 0; i raiseSalary(); // Polymorphic Call: Calls raiseSalary() \n // according to the actual object, not \n // according to the type of pointer \n} \n\nOutputs ???\nIn Derived\n\nSo, virtual functions allow us to create a list of base class pointers and call methods of any of the derived classes without even knowing the type of the derived class object. \n\nHistograms, lists, and more\nNow that we have defined the methods of our analysis class, it is time to add some members. What we are going to add, are three pointer data members\n\nfAOD which is a pointer to an event\nfOutputList which is a (pointer to a) list that holds all our output objects\nfHistPt which is a (pointer to a) histogram that will hold our pt spectrum\n\nSince these members are part of our class definition, we have to add them to our header file\n class AliAnalysisTaskMyTask : public AliAnalysisTaskSE\n .\n .\n .\n private:\n AliAODEvent* fAOD; //!\nIn the code snippet above, you might see something interesting: when we write comments that describe what our class members are doing, we append the expression ! to the double slashes // that start our comment giving us //!. Contrary to what you might think, this expression mark is seen by ROOT (even though it's written as a comment) and it is essential for the correct documentation generation. We will get later to the logic of this locution, but for now a rule of thumb suffices: pointers to objects that are initialized at run-time (in the User* methods) should be marked with a //!.\nThe ClassDef definition\nAt the very end of our header file, we add the following line\n/// \\cond CLASSDEF\nClassDef(AliAnalysisTaskMyTask, 1);\n/// \\endcond\n};\n\nThere is a lot going on behind this one single line: ClassDef is a C preprocessor macro that must be used if your class derives from TObject. ClassDef contains member declarations, i.e. it inserts a few new members into your class; the ClassDef macro family is defined in the file Rtypes.h, should you be interested.\nThe two comments surrounding the ClassDef statement are required to properly produce the documentation.\nHow all this works exactly is not very relevant at this point. We will later see that you will need to increase the version number whenever you change the definition of your class, or ROOT will not be able to handle objects written before and after this change in one process. The version number 0 (zero) disables I/O for the class completely, so we start counting at 1. \nThe implementation of your analysis task (.cxx)\nWe are for now done with our class header, it's time to move to the implementation of the class: the AliAnalysisTaskMyTask.cxx file, in which we will actually implement our methods. Let's start by defining our class constructors. As stated before, ROOT requires two class constructors (weโll get later to why this is necessary), one of which is the I/O constructor, which is not allowed to allocate any memory. So we start our implementation with\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD{0}, fOutputList{0}, fHistPt{0}\n {\n // ROOT IO constructor, don't allocate memory here!\n }\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask(const char* name) : AliAnalysisTaskSE(name),\n fAOD{0}, fOutputList{0}, fHistPt{0}\n {\n DefineInput(0, TChain::Class()); \n DefineOutput(1, TList::Class()); \n }\n\nAs you see, in the constructor, we initialize members to their default values. Always initialize members to default values (and pointers to nullptr). If you fail to do so, values contained by the members will be random, which can lead to unexpected behavior of your code. \n Undefined behavior You have written a small function\nint f(int x)\n{\n int a;\n if(x>0) a = 42;\n return a; \n}\n\nWhat happens when you call\nf(10)\n\nand what happens when you call\nf(-10)\n\n?\n drum rollClick to expandf(10) will return 42. The output of f(-10) is undefined, since variable a was not initialized. \n\nIn the second constructor of this task, we define what the input and output does the analysis class handle. In our case, the input is of type TChain, and as we will see later, the output is a TList. \nUserCreateOutputObjects()\nIn our UserCreateOutputObjects function, we will define the output objects of our task. These are commonly histograms, profiles, etc. In our specific example, we will add one histogram, and define a list to which we will attach the histogram. \n Output listsAdding all your output histograms to a list makes your life easier: the list will allow you to manipulate many output objects simultaneously. By calling TList::SetOwner(true), we transfer ownership of all memory allocated by the list items to the TList itself, this means that in our destructor, we can simply call delete list to delete all our list items, rather than calling delete for all items individually. \n\nThe implementation of the UserCreateOutputObjects method looks like this \n ...\n #include \"TList.h\"\n #include \"TH1F.h\"\n ...\n AliAnalysisTaskMyTask::UserCreateOutputObjects()\n {\n // create a new TList that OWNS its objects\n fOutputList = new TList();\n fOutputList->SetOwner(true);\n\n // create our histo and add it to the list\n fHistPt = new TH1F(\"fHistPt\", \"fHistPt\", 100, 0, 100);\n fOutputList->Add(fHistPt);\n\n // add the list to our output file\n PostData(1,fOutputList); \n }\n\nNote that we create a TList and make it the owner of the memory of all its elements. After we create the histogram, we add it to the output list. Finally, in the last line, we call PostData, which will notify the client tasks of the data container that that the data pointer has changed compared to the previous post. \nUserExec\nThe UserExec is the heart of our analysis: it is called for each event in our input data set. First, we need to access our event, which we can do via a call to the method InputEvent \n ...\n #include \"AliAODEvent.h\"\n ...\n AliAnalysisTaskMyTask::UserExec(Option_t*)\n {\n // get an event from the analysis manager\n fAOD = dynamic_cast(InputEvent());\n\n // check if there actually is an event\n if(!fAOD)\n ::Fatal(\"AliAnalysisTaskMyTask::UserExec\", \"No AOD event found, check the event handler.\");\n\nOnce we have access to our input event, we can e.g. loop over all the tracks that it contains, and store the pt of the tracks in our histogram:\n ...\n // let's loop over the tracks and fill our histogram\n\n // first we get the number of tracks\n int iTracks{fAOD->GetNumberOfTracks()};\n\n // and then loop over them\n for(int i{0}; i (fAOD->GetTrack(i));\n if(!track) continue;\n\n // here we do some track selection\n if(!track->TestFilterbit(128) continue;\n\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n // and save the data gathered in this iteration\n PostData(1, fOutputList);\n }\n\nTake a look at the code and make sure that you understand the logic of all the lines. In principle, this is all you need in an analysis task to run a small analysis. \nAlmost there: the AddTask macro\nThe last thing that we need to fully define our analysis task, is a small file, that we will call the AddTask macro, that instantiates our task (class), defines its in- and output, and connects it to the analysis manager. We will put this piece of code in an independent, third file, called AddMyTask.C. It is important, that this macro defines a function, in our case called AddMyTask, that returns a pointer to our analysis task. We need to follow this exact convention if we later on want to run our analysis in the automated LEGO train system. \nOur AddTask macro looks as follows:\nAliAnalysisTaskMyTask* AddMyTask(TString name = \"name\") {\n AliAnalysisManager *mgr = AliAnalysisManager::GetAnalysisManager();\n\n // resolve the name of the output file\n TString fileName = AliAnalysisManager::GetCommonFileName();\n fileName += \":MyTask\"; // create a subfolder in the file\n\n // now we create an instance of your task\n AliAnalysisTaskMyTask* task = new AliAnalysisTaskMyTask(name.Data()); \n\n // add your task to the manager\n mgr->AddTask(task);\n\n // connect the manager to your task\n mgr->ConnectInput(task,0,mgr->GetCommonInputContainer());\n // same for the output\n mgr->ConnectOutput(task,1,mgr->CreateContainer(\"MyOutputContainer\", TList::Class(), AliAnalysisManager::kOutputContainer, fileName.Data()));\n\n // important: return a pointer to your task\n return task;\n}\n\nAnd that's it - we now have our three files that contain a minimal analysis!\n"},"analysis/local.html":{"url":"analysis/local.html","title":"Running locally","keywords":"","body":"Running locally\nNow that we have seen how a task is built up, we will take a look at how you can run your analysis task. Basically, there are three options for running a task:\n\nRun on local data (i.e. some input files that are stored on your laptop)\n\nRun on GRID (either in test or full mode) yourself\n\nRun on GRID using the LEGO train system\n\n\nIn this section, we will take a look at option 1: how to run on data that you have stored locally, on your own computer. \n Please noteFor practical purposes it is (nearly) impossible to process a whole dataset locally on your laptop, but launching a local test provides you with an environment to test your analysis task!\n\nTo run a local analysis, we need to\n\nCompile our code, and\nLaunch our analysis\n\nSteering macros\nTo do so, we usually use another small macro, commonly referred to as a steering macro, which steers the analysis. This macro will \n\ncreate an analysis manager and data handler, \nwill define which data files to run on, \ncompile your code, and then \ninstruct the analysis manager to run your analysis. \n\nAn example of a steering macro to run the task AliAnalysisTaskMyTask on data that's stored on your laptop, looks as follows:\n void runAnalysis() {\n // header location\n gInterpreter->ProcessLine(\".include $ROOTSYS/include\");\n gInterpreter->ProcessLine(\".include $ALICE_ROOT/include\");\n\n // create the analysis manager\n AliAnalysisManager *mgr = new AliAnalysisManager(\"AnalysisMyTask\");\n AliAODInputHandler *aodH = new AliAODInputHandler();\n mgr->SetInputEventHandler(aodH);\n\n // compile the class (locally) with debug symbols\n gInterpreter->LoadMacro(\"AliAnalysisTaskMyTask.cxx++g\");\n\n // load the addtask macro and create the task\n AliAnalysisTaskMyTask *task = reinterpret_cast(gInterpreter->ExecuteMacro(\"AddMyTask.C\"));\n\n // if you want to run locally, we need to define some input\n TChain* chain = new TChain(\"aodTree\");\n chain->Add(\"/scratch/.../AliAOD.root\");\n\n // start the analysis locally\n mgr->StartAnalysis(\"local\", chain);\n }\n\nRead the above code snippet line-by-line, and try to understand the comments. \nRunning\nTo run your analysis, it will now suffice to type in a terminal (after sourcing the AliRoot environment): \naliroot runAnalysis.C\nThis will trigger executing of the steering macro, which will in turn launch the analysis. If all goes well, this minimal task should produce one histogram, which looks like\n\nTry for yourself?\nIf you want to try this for yourself, you can now go from steps 1 through 5 of the 'Analysis tutorial exercises'.\n"},"analysis/rungrid.html":{"url":"analysis/rungrid.html","title":"Running on Grid","keywords":"","body":"Running on Grid\nThe Worldwide LHC Computing Grid, usually simply referred to as Grid, is a global collaboration of computer centers. It has been up and running since 2002, to provide resources to store, distribute and analyze the petabytes of data that are generated by the LHC. \nOn the picture below, from http://alimonitor.cern.ch/map.jsp, you can see the distribution of computing centers that are working for the ALICE collaboration. We will the Grid to run your analysis on a larger scale than your laptop can provide. \n\nTo run your analysis on the Grid, all we need to do is expand our steering macro a little bit. In this section, we will explain how. \nConfiguring the AliEn plugin\nIn order to run your analysis transparently either on your local computer or on the Grid, we will use the AliEn plugin. The plugin hides a lot of complex operations that have to be performed in order to run your analysis on Grid, e.g.\n\nUsing all existing types of input data to be processed (root files, raw AliEn collections or XML collections) detecting their type automatically;\nGenerate XML collections corresponding to requested runs and/or data patterns;\nAutomatically detect presence of tags in input data and allow using tag-based cuts in a very simple way;\nAutomatically connect to AliEn (generate a token if needed)\nGenerate automatically: JDL, analysis macro to be run in grid, execution and validation scripts according a simple to understand user-driven configuration; \nCopy all needed files in user's AliEn space and submit the job automatically;\nStart an alien shell to allow inspecting the job status;\nDo automatic output merging and terminate the analysis tasks.\n\nThe implementation of the plugin is for the Alice Environment is provided in the class AliAnalysisAlien. In the following code snippet, you can an example of how the plugin is created. These lines would go into your runAnalysis.C steering macro. Read through the code and the comments, and make sure that you understand what happens in each line. \n // create an instance of the plugin\n AliAnalysisAlien *alienHandler = new AliAnalysisAlien();\n // if our class relies on code that has to be compiled, then we need to tell the Grid nodes\n // where the headers can be found\n alienHandler->AddIncludePath(\"-I. -I$ROOTSYS/include -I$ALICE_ROOT -I$ALICE_ROOT/include -I$ALICE_PHYSICS/include\");\n // here we tell which source files need to be copied to the Grid nodes\n alienHandler->SetAdditionalLibs(\"AliAnalysisTaskMyTask.cxx AliAnalysisTaskMyTask.h\");\n alienHandler->SetAnalysisSource(\"AliAnalysisTaskMyTask.cxx\");\n // here we specify which version of aliphysics will be used on the Grid nodes\n // only specificy the AliPhysics version, other dependencies (AliRoot, ROOT, etc)\n // will be resolved automatically\n alienHandler->SetAliPhysicsVersion(\"vAN-20160330-2\");\n // here we specify where the input data of our analysis is stored\n alienHandler->SetGridDataDir(\"/alice/data/2011/LHC11h_2\");\n // and here we specify a specific pattern of filenames\n alienHandler->SetDataPattern(\"*ESDs/pass2/AOD145/*AOD.root\");\n // here we set the run prefix: use '000' for data, or nothing for MC\n alienHandler->SetRunPrefix(\"000\");\n // specify the runnumber to be analyzed. you can call this function multiple times with \n // different runnumbers\n alienHandler->AddRunNumber(167813);\n\nSo far, we have defined the following things\n\nWhich input data has to be analyzed;\nWhich AliPhysics version has to be used;\nWhat kind of analysis sources have to be used.\n\nThese are options that you likely have to change very often. However, there are many more analysis details that we can provide:\n // number of files per subjob, this specifies how many input files\n // each Grid node will analyze. For slow analyses, you might want to \n // lower this number\n alienHandler->SetSplitMaxInputFileNumber(40);\n // the TTL is the 'time to live', which specifies how long a job can run, in seconds\n // the longer you make this time, the lower the jobs priority will be. However, if the job doesn't\n // finish within its TTL, it will be killed, so choose a reasonable number\n alienHandler->SetTTL(10000);\n // do you want to create a subfolder in which the output of each runnumber is stored? \n alienHandler->SetOutputToRunNo(kTRUE);\n // do you want to keep your jobs log files ? \n alienHandler->SetKeepLogs(kTRUE);\n // we can specify that we want to, later on, use Grid to also merge\n // our output. to enable this, we will set 'SetMergeViaJDL' to kTRUE\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1);\n // define the output folders, and give them a sensible name\n // jobs *cannot* overwrite output, so make sure that\n // folders with names as these do not yet exist in your AliEn space\n alienHandler->SetGridWorkingDir(\"myWorkingDir\");\n alienHandler->SetGridOutputDir(\"myOutputDir\");\n // lastly, we give names to the automatically generated analysis scripts\n alienHandler->SetJDLName(\"myTask.jdl\");\n alienHandler->SetExecutable(\"myTask.sh\");\n\nTest of full mode ?\nWe are nearly ready to launch our analysis on Grid. But before we go 'full blast' and use thousands of CPU's, we might want to do a test run to make sure that everything is configured correctly (and to make sure that we do not misuse ROOT's streamer, which will be covered in a later section). \nTo test your Grid analysis, we can specify to the plugin that we want to go for a test run, rather than launching a complete analysis. In the code snippet presented below, let's assume that the variable gridTest is set to kTRUE. As you can see, we specify to the plugin that we want to run in test mode. We also specify that we want to run over one test file (if you want to run over more test files, you can increase this number). \n // connect the alien plugin to the manager\n mgr->SetGridHandler(alienHandler);\n if(gridTest) {\n // speficy on how many files you want to run\n alienHandler->SetNtestFiles(1);\n // and launch the analysis\n alienHandler->SetRunMode(\"test\");\n mgr->StartAnalysis(\"grid\");\n } else {\n // else launch the full grid analysis\n alienHandler->SetRunMode(\"full\");\n mgr->StartAnalysis(\"grid\");\n }\n\nReady to go?\nWhen you run an analysis in test mode, a Grid environment is simulated locally for testing. Input data is downloaded from the file catalogue, following your configuration of the analysis plugin. After this, your analysis is executed. Running in test mode is an excellent way of convincing yourself that you have set up the plugin correctly. \nOnce your analysis test is finished, and you are convinced that your analysis output looks sane, you can submit your analysis to the Grid nodes. To do this, simply look at at the code snippet above, and assume that the variable gridTest is set to kFALSE. \n Create AliEn legacy token!Only ALICE members with a valid registration can submit jobs to the Grid and access the ALICE data. To identify yourself as an ALICE member, you will have to make sure that you have a valid token prior to launching your Grid jobs, be it in full or in test mode. If you are using AliEn legacy, then you need to obtain a token manually. If you are using JAliEn, then the token will be obtained automatically.\n$ alien-token-init \nif all is fine, you should be prompted for your password, and see something like\n => Trying to connect to Server [0] root://pcapiserv03.cern.ch:10000 as User \n ...\n Creating token ..................................... Done\n Your token is valid until: Thu Apr 7 15:23:52 2016\nafter this, you are good to go, and can launch your analysis by executing your steering macro\n$ aliroot runAnalysis.C \n\nMerging output on Grid\nYou can check the progress of the jobs that are running on Grid by going to (http://alimonitor.cern.ch/map.jsp)[http://alimonitor.cern.ch/map.jsp] and clicking on the tab My Jobs, at the top left of the page. When all your jobs are finished (we will later, in the section AliMonitor look at tracing your jobs in more detail), you are of course interested in looking at the output that they have produced. However, this output is stored as thousands of files, scattered over multiple job sites. To obtain one, single file as output of your analysis, we need to merge all these thousands of files. \nMerging via JDL\nThe easiest way to merge your output is using the MergeViaJDL option that the plugin provides. Using this option will allow you to submit special merging jobs, which run on the Grid nodes and merge your output files. To enable merging via JDL, you have to configure your plugin as follows, before you start your analysis:\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1); // just one step\n ....\n mgr->SetRunMode(\"full\");\n\nThis will prepare the plugin for writing merging jobs, when your analysis is done. \n More than on merging stage?By specifying\n alienHandler->SetMaxMergeStages(1);\n\nwe tell the plugin that all output files can be merged in one go. \nIf your output files are quite large, you might want to increase the number of merging stages by specifying a larger number here: this will tell the plugin that we want to merge in multiple, consecutive stages.\n\nWhen all your normal analysis jobs have finished, we want to launch the merging jobs to Grid. To do this, we again make a small modification to our steering macro, and change the run mode from full to terminate:\n alienHandler->SetMergeViaJDL(kTRUE);\n alienHandler->SetMaxMergeStages(1); // just one\n ....\n mgr->SetRunMode(\"terminate\");\n\nTo now launch the merging jobs, simply run\n$ aliroot runAnalysis.C\nagain. The merging jobs will be launched, and you can monitor their progress on via the 'Jobs' tab on http://alimonitor.cern.ch/map.jsp.\nWhen all your merging jobs have finished running, there is one step to be taken still, which is downloading the output of the merging jobs, so that you have your analysis output available on your laptop. This is done by again making a small change to your steering macro:\n alienHandler->SetMergeViaJDL(kFALSE);\n alienHandler->SetMaxMergeStages(1); // just one\n mgr->SetRunMode(\"terminate\");\n\nand running runAnalysis.C a final time. This will trigger downloading of the merged output files (the resulting files from the merging jobs) and a final 'local' merge of said files into one, single output file. When the process is done your high-statistics output files is ready - time to start writing a paper!\n Merging is 'dumb'Keep in mind: merging can be a memory-hungry process. During merging, all files that are to be merged are kept in random access memory. ROOT files tend to be heavily compressed when written to disk, so their size in RAM might be surprisingly large. \nWhen your output files are large, or if you have a large number of output files to be merged, you might need to merge in multiple stages, to avoid running out of RAM!\n\n"},"analysis/lego.html":{"url":"analysis/lego.html","title":"The LEGO train system","keywords":"","body":"The LEGO train system\nBy now, your code is running well on Grid, you're submitting and merging jobs like a seasoned professional. However, do you really want to \n\nStay up all night to resubmit jobs? \nRisk losing your code because it's not part of AliPhysics and your hard drive crashes? \n\nTo avoid these headaches, users are encouraged to run their jobs in a more automated and efficient way by using the LEGO framework. \n Why LEGO trains are crucialA train can easily contain multiple instances of your analysis, meaning you can run your default configuration and in addition multiple cut variations and other cross-checks. The success rate of the jobs is EXACTLY the same for each of your configurations, as they are all handled in parallel. This means that the all the configurations handle the exact same set of data.\nThis is in contrast to submitting your jobs one after each other (possibly running into quota problems) and having random job crashes, resulting in a situation where your default configuration and the variations did not handle exactly the same set of data.\n\nHow does it work\nThe LEGO framework is a tool to run and manage analysis trains on AliEn. It builds on existing infrastructure, the analysis framework, MonALISA and LPM. LEGO provides a web interface for users and operators which allows to:\n\nregister train wagons\nconfigure trains (handlers, wagons, input datasets, global Variables)\ntest the wagons and the train in a well-defined environment\nstudy the test results\nsubmit the train to the Grid\nstudy the resource consumption of the train for each wagon (CPU usage, virtual and resident memory) \n\n NoteThe fact that the trains run on the Grid, requires that all code is contained in an AliEn package. Therefore, the train uses the regularly deployed AliPhysics \"AN\" tags, so you will have to make sure that your analysis code is available in AliPhysics. \nWithin AliPhysics, your analysis code will be part of a shared library that contains many other analyses from your working group or analysis group. If you have never added a class to AliPhysics, ask your PWG or PAG coordinators for help.\n\nHow to access the LEGO train system\nThe LEGO train system can be accessed via (https://alimonitor.cern.ch/trains/)\n\nBy clicking on the top right 'help' tab, you will be guided to a webpage where it is explained in detail how you can join a LEGO train and perform a highly efficient analysis. \n Join the LEGO trains!Everyone is encouraged to use the LEGO train system for running analysis rather than running analysis by yourself on Grid. Not only will you benefit yourself, but by running trains that contain analyses of multiple users in one go, we conserve resources: the LEGO train has to only run on instance of AliPhysics to perform multiple analyses, and it has to only retrieve the input data once. \nAs a consequence: LEGO train jobs have higher priority in the job queues than user jobs! Furthermore, your analysis will always be reproducible, and you will receive a simple mail with a link to your final output file when your train run is done. So if you want to perform fast, safe, and efficient analysis: use the LEGO trains!\n\nHow to add your analysis task to the LEGO train system\nAs seen in the screenshot above, the train pages are grouped by PWG, collision system, and AOD or ESD data processing. Once you are in the correct train page:\n\nClick Add new wagon\nConfigure the wagon by either setting it up from scratch, or copying it from an existing wagon(available under advanced settings, and allows in addition to not only copy your own wagons, but also from any other user!)\nCheck that your macro is defined and configured correctly in the basic settings tab\nCheck the dependencies (if your dependency is not available you can just create another wagon and configure it accordingly then define it as a dependency for your own wagon)\nUse a unique filename for your wagon\nExpert mode: Add subwagons (easiest way to run multiple analysis with a single wagon)\nActivate your wagon for the dataset you want to process (if it is not available, ask an operator to add it)\nCheck the runlist of the dataset! (Do not blindly use the runlists which happen to be there, make sure proper QA is done such that only high quality runs are used for your analysis)\nAsk the train operators to start a train test for your activated wagons (each PAG and/or PWG has a different system, please ask the coordinators)\nCheck that the train test output is successful and take responsibility in debugging if there are problems\nIf all is ok, confirm with the train operator that the train can be started\n\nThis seems to be quite a long list, but once your wagons are set up it takes only a few minutes to get your analyses on the grid. You just need to wait for the email to announcing the completion of the run.\n"},"analysis/monalisa.html":{"url":"analysis/monalisa.html","title":"AliMonitor","keywords":"","body":"MonALISA - the ALICE Grid monitoring toolset\nALICE uses MonALISA (Monitoring Agents using a Large Integrated Services Architecture) for monitoring and control of its Gird operations. The AliMonitor webpage, that we have seen in previous sections, provides us with access to the MonALISA services. In this section, we will cover some of these services. \n VO registrationFor full access to all MonALISA serivces, make sure that you have a valid certificate and ALICE VO registration!\n\nRun numbers\nIn the previous section, we have seen that data that are stored are identified by their run number. If you want to look up which run numbers correspond to a given data taking period, go to ALIMONITOR and click on the tab 'Run Condition Table' (RCT). \n\nA large table is shown - you can select a data taking period from the drop down menu at the top left corner of the table. As soon as you select a data taking period, the corresponding list of run numbers is displayed in the table. \n\nTo ensure that detector systems that you need to use in your analysis were functioning properly, you can check quality flags for all detector subsystems in the columns on the right-hand side of the table. The number '1' means that data taking was successful; to only display run numbers for which data quality is guaranteed for a given sub detector, type a '1' in the field of the first row of the table that corresponds to said detector (see the circle on the top right of the above picture). \nIf you scroll down, to the bottom of the table, you will see a button labeled: 'Show list of runs'. Clicking this button will open a pop-up window which lists the run numbers that are displayed in the table as a list of comma separated numbers. You can now easily copy these numbers into your steering macro, and add these run numbers to the analysis plugin. \n Which data format to take?You might note that, for all runs, data is stored in two distinct formats\n\nAliESDs.root: event summary data\nAliAOD.root: analysis object data\nin various passes. \n\nESD files contain full information about events, AOD files contain a subset of information that has been selected for physics analysis. \n\nunless otherwise specified, use is discouraged as data are very\nlarge\nAOD files contain information necessary for physics analysis and is the preferred format\nAOD files contain pre filtered collections of tracks, to be selected via their\nfilterbit. Always apply a filterbit selection when running on AODs, to avoid double counting of tracks!\n\nWhen multiple passes are available for a data set, this means that the data has been reconstructed more than once, with slightly different approaches. As a rule-of-thumb: take the latest pass, but discuss this within your working group!\n\nAvailable packages\nThe AliMonitor webpage can be used to check which software packages are accessible on the Grid nodes. In the menu on the left-hand side of the page, click on 'Job information', then on 'User views', then on 'Grid packages'. A large table will load, if the CVMFS status is listed as 'available', a certain software package is available on Grid. If it's listed as n/a, it is (probably) archived, and cannot be selected for analysis. \nKeep in mind: when specifying a version of the software stack to be used, to only call โSetAliPhysicsVersion(โ..โ)โ in your steering macro. The right dependencies are automatically resolved. \n\nDaily tags (AN) of AliPhysics are a snapshot of all code that is in the central repository at 16h Geneva time. The daily tacks are usually available on Grid in about two hours after the tagging. \nRun quota - how many jobs can you run?\nWe have to share computing resources, so the number of jobs that you can run is not infinite. To check your quotas, which limit both how many jobs you can run, how much CPU hours they can consume, and how much diskspace your output files take up, click at the menu on the left-hand side of the AliMonotir page on 'Job information', then on 'User views' and then on 'Quotas. \n\nYou will see the five job activity quantifiers that apply for all users\n\nthe number of files that you have currently stored\nthe disk space that the files take up\nthe number of unfinished jobs that you have in the job queue\nthe running time of your jobs, integrated over the last 24 hours\nthe CPU cost of your jobs, integrated over the last 24 hours\n\nIf you are over (one of the) quota, i.e. one of the bars is completely red, you cannot submit jobs. In case of being over the file quota, you have to remove files from your alien space. Job quota just require a bit of waiting. \nBe patient, when you are over your quota. Not all quota are refreshed instantaneously, it can sometimes take up to 12 hours before your quota are refreshed. \n"},"analysis/oadb.html":{"url":"analysis/oadb.html","title":"Offline analysis database","keywords":"","body":"OADB and large shared files\nThe Offline Analysis Database (OADB) is a repository of relatively large configuration/calibration files that are used by the analysis framework, \ncontaining for example the 'TPC splines' with the parametrised dE/dx response of the TPC and calibration files for event plane calculation.\nThe data are generally stored in ROOT files, and the primary repository is on the CERN EOS file system, which is accessible from lxplus:\n/eos/experiment/alice/analysis-data\nWe have preserved the same directory structure found on AliPhysics, and the\nsame permissions: for instance, PWGLF is writable by all members of\nalice-svn-pwglf (whose members can be edited by the group conveners).\nUsing the OADB on the grid\nEvery day, in concomitance with the AliPhysics daily tag (at 4pm Geneva time),\nthis folder is snapshotted on CVMFS under the following path:\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD\ncarrying the same name as the corresponding AliPhysics tag. Moreover, at\nevery AliRoot/AliPhysics production release, we also snapshot at:\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01\nwhere the last component is the AliPhysics tag name.\nCVMFS brings the advantage to make data access from Grid jobs reliable and\nfaster due to caching (files unchanged in two different snapshots are not\ndownloaded twice).\nUsing the OADB on your local system\nIf your system is connected to the network, you can access the OADB via (x)rootd, but setting the ALICE_DATA environment variable\nexport ALICE_DATA=root://eospublic.cern.ch//eos/experiment/alice/analysis-data\n\nIf you want to have your OADB data locally, you can download it from lxplus:\nexport OADB_PATH=/path/to/my/local/oadb\nrsync -av --delete cern_user@lxplus.cern.ch:/eos/experiment/alice/analysis-data/ $OADB_PATH/\n\n\nTrailing slashes are important to rsync! Do not forget them!\n\nNote that the variable $OADB_PATH must be exported to the environment where\nyou run your local analysis in order to make it visible to the job.\nAccessing the OADB from code\nIn order to profit from the separate storage for large files we have created an\ninterface in AliRoot to allow transparent access to OADB files using a relative\npath. For instance, if you want to access the following large OADB data file:\nPWGLF/FORWARD/CORRECTIONS/data/fmd_corrections.root\nyou can do:\nTFile::Open(AliDataFile::GetFileNameOADB(\"PWGLF/FORWARD/CORRECTIONS/data/fmd_corrections.root\"))\n\nThe static function AliDataFile::GetFileNameOADB returns the first accessible\nfull URL of the OADB file by finding the first match from the following ordered\nlist of paths:\n\n$OADB_PATH/\n$ALICE_DATA/OADB/\n$ALICE_PHYSICS/OADB/\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01/OADB/ (for Grid jobs, or with CVMFS installed)\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD/OADB/ (for Grid jobs, or with CVMFS installed)\nroot://eospublic.cern.ch//eos/experiment/alice/analysis-data/OADB/\n\nThis means that for laptop analysis it will always be possible to access data\nfiles, somehow, and in a transparent fashion. \nNon-OADB data files\nThe same EOS path has also PWG-specific directories, outside the OADB one, for\nother analysis-specific data. The following interface can be used to access\nfiles from there:\nTFile::Open(AliDataFile::GetFileName(\"PWGMM/my_large_data.root\"))\n\n\nNote the difference between GetFileName() and GetFileNameOADB().\n\nIn this case, the file will be searched in the following locations in order:\n\n$ALICE_DATA/\n$ALICE_PHYSICS/\n/cvmfs/alice.cern.ch/data/prod/v5-XX-YY-01/ (for Grid jobs, or with CVMFS installed)\n/cvmfs/alice.cern.ch/data/analysis/YYYY/vAN-YYYYMMDD/ (for Grid jobs, or with CVMFS installed)\n\n"},"analysis/trouble.html":{"url":"analysis/trouble.html","title":"Troubleshooting","keywords":"","body":"Troubleshooting - when Grid does not do what you want it to do\nSometimes, running jobs does not go as smoothly as you would like it to go. In this section, we will cover some basic troubleshooting. \nFirst off all: be informed!\nGrid operations are complex. Often, job failures are a result of mistakes of users, but sometimes, certain Grid sites experience general problems. To quickly resolve these problems, it is important that we clearly communicate problems. To do so, ALICE makes extensive use of mailing lists. You can self-subscribe to mailing lists pertaining to Grid operations by surfing to e-groups.cern.ch . There, make sure that you are subscribed to\n\nalice-analysis-operations\nalice-project-analysis-task-force\nyour PAGโs mailing list\n\nALICE also employes a more professional bug and feature tracking suite, called JIRA, which you can access via\n\nhttps://alice.its.cern.ch/jira/projects/ALPHY\n\nTroubleshooting 101 - what should you do?\nSometimes, you will see mails such as\n `Dear experts,\n All my jobs are going into error. \n Could you check? Thanks!'\nbeing sent to the mailing lists. The experts can (and probably will) check, but you yourself should\nbe the first to take a look at why your job is not doing what you want it to do. The starting point is\n\nGo to โmy jobsโ on MonaLISA\nTake a look at the job trace and, if available, the stderr\nand stdout\n\nThe trace tells you exactly how your job was handled, from copying of files to Grid nodes, to executing the job, to checking if the expected output files were actually created. Stdout and stderr are the standard handles for the normal information and error information. Depending on whether or not the process actually ran, these files may or may not be available. \nIf you have checked your job's trace, stdout and stderr, and still cannot solve an issue, it is completely fine to write a mail to the mailing list. However, be complete in your message, specify what goes wrong, and provide some examples of job numbers. Do not kill your jobs! If the jobs are purged from the queue, debug information is lost. \nExample: validation error\nLet's take a look at an example of troubleshooting. We have some jobs running, and check their progress on MonALISA. Unfortunately, we see that all of our subjobs, corresponding to a given masterjob, go into the error state 'Validation error'\n\nThe first thing to do, is click on the masterjob number, to get a detailed overview of the subjobs. This table allows us access to the trace and log files\n\nClicking on 'log files' leads us to a page where we can consult the log files\n\nand by e.g. clicking on the 'stderr', we can check the error information of our job. \n\nMmm, so the job crashed with a segmentation violation, and if we remember correctly from our programming classes, we know that this points at illegal memory access ... so we had better go to our analysis code, and check our pointers ....\n Can you spot the mistake? Below, we see the UserCreateOutputObjects and a snippet of the UserExec() methods of the task that ran and segfaulted. What is wrong ? \n AliAnalysisTaskMyTask::UserCreateOutputObjects()\n {\n // create a new TList that OWNS its objects\n fOutputList = new TList();\n fOutputList->SetOwner(kTRUE);\n // add the list to our output file\n PostData(1,fOutputList);\n }\n ...\n AliAnalysisTaskMyTask::UserExec() {\n // called for each event\n ...\n fHistPt->Fill(track->Pt());\n\n Click to show answerClick to expandWe forgot to initialize the histogram that we try to fill: the pointer fHistPt has value NULL\n\nExample: execution error\nLet's take a look at another example. We are again running our jobs, but now we notice that subjobs of a given masterjob start to go into an 'Execution error' state. \n\nAgain, after clicking on the masterjob ID, the popup window of subjobs opens. If we hover with the mouse over the ID of a certain subjob, an graph of memory usage over time is shown. In this particular case, we clearly see that memory usage increases linearly over time\n\nLet's click on the trace of the subjob\n\nFrom the trace, we see that the job was killed because it used too much memory. The fact that we saw that the memory consumption increased linearly over time, probably means that there is a memory leak somewhere in our code ... better go back to the drawing board. \nWhat is the perfect workflow?\nBy now, we have seen that we can run our analysis\n\nlocally, on some data on our laptop\non Grid, either in test mode or full mode\non the LEGO trains\n\nEven though there is no perfect workflow, it is generally wise to\n\nDownload some AliAOD.root files to your computer\nDevelop your task\nTest locally (fast, no internet connection needed)\n\nWhen this goes well\n\nCheck in โtestโ grid mode. There are a few subtle differences\nbetween running LOCALLY and on GRID (covered in the next section)\n\nIf the code is robust:\n\nDonโt spend long nights (re)submitting jobs to GRID ...\n... rather get your code checked into AliPhysics\nAnd use the LEGO trains\n\n"},"analysis/streamer.html":{"url":"analysis/streamer.html","title":"The ROOT streamer","keywords":"","body":"The ROOT Streamer\nSometimes, mails like\n`Dear experts,\n my task worked fine but now \n on grid it does not. can you take a look ? '\nare sent on the mailing list. Some unexpected errors are caused by misuse of the ROOT streamer. The streamer has been mentioned a couple of times before now in other sections. So what is the โstreamer to begin with?\n\nThe ROOT streamer decomposes an object into its data members\n(serialization) and writes it to disk\n\nThis sounds more confusing than it is. Take a look at our class example from section 1\nclass Polygon\n{\n private:\n int width, height;\n}\n\nThe job of the streamer here would be, to save values of height and width, so that they can be written to disk. \nThe automatically generated streamer\nROOT automatically generates a steamer for us, if we instruct it to do so. Remember from the earlier sections, that we put the following lines in our task:\n // tell ROOT the class version\n ClassDef(AliAnalysisMyTask,1);\n };\n\nBy doing this, a streamer is constructed for us by invoking the ClassDef macro. \nCustomization\nROOT generates a streamer for us, but we have the task of customizing it. Customization means defining what data members should and should not be touched by the streamer. Customization is done in the header *.h) of a class, by giving specific instructions in the comments written after the declaration of data members (i.e. โ//โ). Let's take a look at this in practice. \nCustomizing: โmember persistenceโ\n\nPersistent Members (//) are โstreamedโ (copied/stored)\n class SomeClass : public TObject {\n private:\n Int_t fMinEta; // min eta value\n Int_t fMaxEta; // max eta value\n ...\n\n\nTransient Members (//!) are not streamed\n class SomeClass : public TObject {\n ...\n AliAODEvent* fAOD; //! current event\n TH1F* fHistPt; //! our histogram\n\n\n\nSo if we would write the object defined by the code snippets above to disk, the value of fMinEta and fMaxEta will be saved (//), but the values of fAOD and fHistPt will be ignored (//!).\nAdvanced use cases\nWe can customize the streamer in more sophisticated ways\n\nThe Pointer to Objects (//-$>$) calls streamer of the object\ndirectly\n class SomeClass : public TObject {\n private:\n TClonesArray *fTracks; //->\n ...\n\n\nVariable Length Array, (so that not just the pointer is copied)\n class SomeClass : public TObject {\n Int_t fNvertex;\n ...\n Float_t *fClosestDistance; //[fNvertex]\n\nAll this is explained in detail in 11.3 of the ROOT documentation https://root.cern.ch/root/htmldoc/guides/users-guide/ROOTUsersGuide.html\n\n\n Streamers and doxygenIn the second subsection of this tutorial, you saw that the streamer directives looked a bit different. This is, because we sometimes use member comments in header files for yet another purpose: creating automatic code documentation with Doxygen. Doxygen is a way of documenting your code inside the source code itself, by factoring special comments that will be ignored by the C++ compiler. \nDoxygen uses both //!\n\nPitfalls\nWe started this section out, by saying that the streamer definition can be a source of confusion. Why is this so? \nLet's start by realizing when the streamer definition is actually relevant: this is when objects are written to disk or copied. If you run your analysis locally, your analysis task is (probably) never copied or stored to disk, ergo the streamer information is never used and specifying // or //! are equivalent\nIf you run on Grid, or on the LEGO train system, the situation is different, and the following happens\n\nYour task is initialized locally and added to the analysis manager\nThe manager is stored locally in a .root file\nThis file is copied to grid nodes, invoking the streamer\nAt the grid node, a fresh instance of your task is created\nNon-persistent members are initialized to their default values found\nin the empty I/O constructor (remember that we said in Section 3: you always need to specify an empty I/O constructor for your classes!)\nPersistent members are read from the .root file\n\n Example 1 - 'unexpected' behaviorTake a look at the class below\n class SomeClass : public TObject \n Int_t fAbsEta; //!\n // setter\n SetAbsEta(Float_t eta) {fAbsEta = eta;}\n\n // ROOT IO constructor\n SomeClass::SomeClass() : \n fAbsEta(0) {;}\n\n\nIn your steering macro, you call\n SomeClass->SetAbsEta(3);\nYou now launch your analysis to run on the Grid. What is the value of fAbsEta when the analysis starts to run at a Grid node?\n Click to show answerClick to expandAfter copying (e.g. to grid) the value of fAbsEta = 0. The member is not persistent (//!), so after copying, the value of fAbsEta will be equal to its default value as specified in the I/O constructor of your class.\n\n Example 2 - expected behavior?Now take a look at a second, very similar class:\n class SomeClass : public TObject \n Int_t fAbsEta; //\n // setter\n SetAbsEta(Float_t eta) {fAbsEta = eta;}\n\n // ROOT IO constructor\n SomeClass::SomeClass() : \n fAbsEta(0) {;}\n\nAgain, we call\n SomeClass->SetAbsEta(3);\n\nAnd launch our analysis task on the Grid. What is the value of fAbsEta when your task starts to run on a Grid node? \n Click to show answerClick to expandAfter copying (e.g. to grid) fAbsEta = 3. The member is declared as persistent, so the value it has is retained. \n\nSo you see, that the streamer can have quite an important effect on your analysis!\nRuntime\nWhen you launch your analysis to Grid, it's important to realize that some methods of your analysis task are called on your laptop when you execute your steering macro, whereas other methods are only called on the Grid nodes. The execution on Grid is what we call runtime. \nLooking at the functions of our analysis task, we can e.g. say that \n // constructor: called locally\n AliAnalysisMyTask(const char*);\n\n // function called once at RUNTIME\n virtual void UserCreateOutputObjects();\n\n // functions for each event at RUNTIME\n virtual void UserExec(Option_t*);\n\nIt makes no sense to make data members that are initialized at runtime persistent. Therefore, as a rule-of-thumb, for all your output histograms, use the flag for non-persistence, i.e.\n TH1F* fHistPt; //! pt histo\n\nAutomatic Schema Evolution\nIf you develop your code, the layout of persistent members of your class probably changes, i.e.\nclass Polygon\n{\n private:\n int width;\n}\n\nwhich would take up 4 bytes, could change to \nclass Polygon\n{\n private:\n int width, height;\n}\n\nwhich would take up 8 bytes when written to disk. The ClassDef value of your class bookkeeps this evolution for ROOT and avoids compatibility problems such as\n `The StreamerInfo of class AliAnalysisTaskMyTask\n has the same version (=1) as the active class but a \n different checksum. Do not try to write, ..., \n the files will not be readable.'\nIf you commit your code to AliPhysics (or AliROOT), you should make sure to increment the ClassDef value when you change the list of persistent members, i.e. if we have a class\n class SomeClass : public TObject {\n private:\n Int_t fAbsEta; // min eta value\n ...\n ClassDef(SomeClass, 1);\n\nand we add a persistent member, we have to increment to ClassDef value\n class SomeClass : public TObject {\n private:\n Int_t fMinEta; // min eta value\n Int_t fMaxEta; // max eta value\n ...\n ClassDef(SomeClass, 2);\n\nIf the list of non-persistent members changes, e.g. when we change\n class SomeClass : public TObject {\n private:\n Int_t fAbsEta; //! min eta value\n ...\n ClassDef(SomeClass, 1);\n\ninto \n class SomeClass : public TObject {\n private:\n Int_t fMinEta; //! min eta value\n Int_t fMaxEta; //! max eta value\n ...\n ClassDef(SomeClass, 1);\n\nwe do not have to increment the ClassDef value, because the streamer definition of the class does not change. \n"},"analysis/destructor.html":{"url":"analysis/destructor.html","title":"Destructors","keywords":"","body":"Destructors\nWe are at the end of the manual for writing a task, but we forgot to implement one important aspect of our analysis task: the destructor, copy constructor and assignment operator. Out class dynamically allocates memory (use of the new), for example when we create our histograms\n\n // create our histo and add it to the list\n fHistPt = new TH1F(\"fHistPt\", \"fHistPt\", 100, 0, 100);\n\nThis has two implications:\n\nAfter usage, we are responsible for freeing the allocated memory\n(else itโs lost!)\n\nA bit more advanced: you might have to think about the copy constructor\nand assignment operator \n\n\nImplementing the destructor\nMemory allocated with new cannot be used again, unless it is realased by delete. Never deleting memory is called a memory leak. Leaks are bad: they waste resources and can crash your system, and for that reason, we should implement a destructor\nSuppose we have a constructor that looks like this\n MyClass::MyClass()\n {\n n = new int;\n p = new float;\n x = new float[5];\n }\n\nThe destructor should be\n MyClass::~MyClass()\n {\n delete n;\n delete p;\n delete[] x;\n }\n\nOur life is not so easy however: \n\nWe did not allocate memory in the class constructor but in\nUserCreateOutputObjects\n\nWe might want to free that memory, but what if\nUserCreateOutputObjects was not called? โif it hasnโt, freeing\nthe memory will cause serious problems (the infamous โglibc double\nfree or corruptionโ)\n\nTo avoid this, initialize our pointers to NULL in the member\ninitialization list\n ...\n AliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD(0), fOutputList(0), fHistPt(0)\n {\n // ROOT IO constructor, don't allocate memory here!\n }\n ...\n\n\nWith our pointers initialized to NULL, we can go ahead and write our\ndestructor\n\n AliAnalysisMyTask::~AliAnalysisMyTask()\n {\n if(fOutputList) delete fOutputList;\n }\n\n\nA little trick we applied is\nfOutputList->SetOwner(kTRUE);\nwhich tells the destructor of TList* to delete all objects added to\nit\n\nNote that fAOD is not deleted - this pointer points to memory that\nwas not allocated by our task\n\n\n new - deleteRule of thumb: all calls to new should be accompanied by a call to\ndelete somewhere in your code\n\nDestructors and PROOF\nIf you run on PROOF, your analysis class is not the owner of its output list. A little trick to avoid segmentation violations when running on PROOF is to write\n AliAnalysisMyTask::~AliAnalysisMyTask()\n {\n if(AliAnalysisManager::GetAnalysisManager()->GetAnalysisType()\n != AliAnalysisManager::kProofAnalysis) delete fOutputList;\n }\n\nThis only deletes the output list if youโre not running PROOF. \nCopy constructor and assignment operator\nSometimes in AliRoot code you see copy constructors and assignment operators (these two always go together). In principle, we donโt need them because our analysis class is never copied (apart from the streamer actions, which do not rely on these constructors). However, you might occasionally see compiler warnings such as\n warning: 'class AliAnalysisTaskMyTask' has pointer \n data members but does not override 'AliAnalysisTaskMyTask(const\n AliAnalysisTaskMyTask&)' or 'operator=(const AliAnalysisTaskMyTask&)' \n [-Weffc++]\"\nGenerally, these can be squashed by defining prototypes \n private:\n // not implemented\n AliAnalysisTaskMyTask(const AliAnalysisTaskMyTask&); \n AliAnalysisTaskMyTask& operator=(const AliAnalysisTaskMyTask&);\n\nDefining these functions as private implicates that we do not have provide an implementation. \nSo what does this mean, what are copy constructors and assignment operators, why do I need them, and how can I get them? If you are interested in this, keep reading. \nIn a nutshell:\n MyObject A; // initialization by default constructor\n MyObject B(A); // initialization by copy constructor\n MyObject C = A; // Also initialization by copy constructor\n B = C; // assignment by copy assignment operator\n\nThe copy constructor and assignment operator are automatically generated, but if your class has pointer members, they need to be customized (this is not a ROOT feature, just c++!). \nIf we wanted to implement our own copy constructor for our class, here is what it would look like\n AliAnalysisMyTask::AliAnalysisMyTask\n (const AliAnalysisMyTask& other) : AliAnalysisTaskSE(other),\n fOutputList(NULL), fHistPt(NULL)\n {\n if(other.fOutputList) fOutputList = (TList*)other.fOutputList->Clone();\n if(other.fHistPt) fHistPt = new TH1F(*other.fHistPt);\n }\n\n\nOperating on NULL pointers is not allowed and the code will crash if\nyou attempt to do that\n\nOperating on uninitialized pointers is undefined and much more\ndangerous\n\nThe TH1F and most ROOT histogram classes have public copy\nconstructors, so we can use them\n\nThe TList copy constructor is private, so we need to make a Clone of\nit instead\n\n\nThe assignment operator is very similar to the copy constructor, but it has the additional requirements for checking for self-assignment and returning a value. In our case, it could look like\n AliAnalysisMyTask& AliAnalysisMyTask::operator=\n (const AliAnalysisMyTask& other)\n {\n if(&other == this) return *this;\n outputlist = NULL;\n fHistPt = NULL;\n AliAnalysisTaskSE::operator=(other);\n if(other.fOutputList) fOutputList = (TList*)other.fOutputList->Clone();\n if(other.fHistPt) fHistPt = new TProfile(*other.fHistPt);\n return *this;\n }\n\n"},"analysis/":{"url":"analysis/","title":"Analysis tutorial exercises","keywords":"","body":"Writing a mini-analysis\nIn the following exercises, you will write a very small, but realistic, data analysis from the grounds up. The starting point is a minimal task that fills a histogram with a transverse momentum distribution. This task has already been written for you. As you go along, you will add code to this task, so that in the end, you can run a mini-analysis measuring the centrality dependence of charged pions production at mid-rapidity. \nThese exercises assume that you have read the previous section ('Writing an analysis task'). \nTo access ALICE data and run the analysis on the Grid, you will need to be an ALICE member (a CERN lightweight account does not suffice). When in doubt about this, ask your supervisor. \n"},"analysis/setup.html":{"url":"analysis/setup.html","title":"Step 1 - Setup the tutorial","keywords":"","body":"Obtain your source code\nThe starting point for these exercises is the analysis template called AliAnalysisTaskMyTask. To obtain the source code of this analysis, choose one of the following two options: \n\nClone the Git repository. Programmers use version control systems when developing their code. You will also use version control (in our case through Git) when you are contributing to the ALICE code base. So why not start with Git right now? You can clone the example task repository, which you can find it on here, by typing, in a terminal\n\ngit clone https://github.com/rbertens/ALICE_analysis_tutorial.git\n\nThis will clone the remote repository, so that you have access to a carbon copy of the full repository on your local computer. \n\nA more robust approach to working with Git, is creating a remote fork of a certain repository, and working on this fork. For this, you will need to open a GitHub [https://github.com/] account (which you will need in any case if you want to contribute to ALICE software). If you have a GitHub account, you create a fork of the example task repository by surfing here and clicking on fork at the top right of the screen. If you have forked the repository, you can proceed to cloning it on your laptop in the way as explained in option 1; this then allows you to develop the code, and push commits to your own fork\n\nWhichever approach you chose, the end result should be that you have stored these files on your laptop. One word of caution: the path in which you store these files cannot contain spaces! E.g. /home/my task/ will not work, use /home/my_task/ .\nA first look at your task\nAs a start, just take a look at code that makes up the task:\n\nAliAnalysisTaskMyTask.cxx\n\nAliAnalysisTaskMyTask.h\n\nAddMyTask.C\n\nrunAnalysis.C\n\n\nYou will see that the code is extensively documented. Can you tell\n\nwhich function is called for each event?\n\nwhere are the output histogram defined?\n\nwhere are the output histogram filled?\n\n\nRemember, that for now, the name โAliAnalysisTaskMyTaskโ doesnโt sound so bad, but when you develop a task โin real lifeโ, make sure to give it a meaningful name, that explains what the task is aimed at.\nObtain input data\nTo run your own analysis task, you will also need to download a file that contains reconstructed collisions. This input file is called AliAOD.root, short for Analysis Object Data. In the following steps, will assume that we are looking at Pb-Pb data that was taken in 2015. You can also choose to run on data from a different period or collision system. \nSource your environment\nWe will get the data form the ALICE file catalogue. To access the file catalogue, you will need to use xjalienfs or xalienfs packages and have a valid Grid certificate. This means that, at this point, we will assume that you have built all the ALICE software (see our build manual for that ).\nLoad your ALICE environment as explained here, e.g. by doing\nalienv enter AliPhysics::latest\nYou should see which module files are currently loaded, e.g.\n 1) BASE/1.0\n 2) AliEn-Runtime/v2-19-le-49\n 3) OpenSSL/v1.0.2o-9\n 4) Python-modules/1.0-11\n 5) XRootD/v4.11.1-14\n 6) ROOT/v6-18-04-alice2-1\n 7) boost/v1.70.0-6\n 8) cgal/4.6.3-5\n 9) fastjet/v3.2.1_1.024-alice3-21\n10) Vc/1.4.1-5\n11) xjalienfs/1.0.6-2\n12) JAliEn-ROOT/0.6.0-2\n13) AliRoot/master-1\n14) RooUnfold/V02-00-01-alice4-25\n15) treelite/a7a0839-2\n16) KFParticle/alice-v1.1-1-9\n17) AliPhysics/latest\n12) AliPhysics/latest\nUse alienv list to list loaded modules. Use exit to exit this environment.\nThe module xjalienfs is now available, which is what we will use to get our data. \nGet a valid token (optional)\n JAliEn tokensYou can skip this step if you are using JAliEn. JAliEn clients create the token automatically, but you can still run alien-token-init to refresh it manually.\n\nThe ALICE file catalogue is only accessible if you are an ALICE member. \nIf you are using AliEn-ROOT-Legacy or ROOT5, then you first need to authenticate yourself and obtain a token\nalien-token-init \nwhere username is your CERN username. You should be prompted to provide your PEM pass phrase, which is not the same as your CERN password unless you set them to be the same yourself. \nIf all goes well, you will see something like\n[AliPhysics/latest] ~/sw $> alien-token-init rbertens\n---------------------------------------------------------------\nSetting central config:\n===============================================================\nexport alien_API_SERVER_LIST=\"pcapiserv03.cern.ch:10000|pcapiserv08.cern.ch:10000|\"\nexport TERMINFO=/usr/share/terminfo\n===============================================================\n---------------------------------------------------------------\nSetting closest site to: CERN\n===============================================================\nUsing X509_CERT_DIR=/home/rbertens/sw/slc7_x86-64/AliEn-Runtime/v2-19-le-1/globus/share/certificates\n*********************************************************************************\nAttention: You don't have a valid grid proxy ( or less than 1 hour left ) - doing xrdgsiproxy init for you ...\n*********************************************************************************\nEnter PEM pass phrase:\n++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\nfile : /tmp/x509up_u1000\nissuer : /DC=ch/DC=cern/OU=Organic Units/OU=Users/CN=rbertens/CN=718303/CN=Redmer Alexander Bertens\nsubject : /DC=ch/DC=cern/OU=Organic Units/OU=Users/CN=rbertens/CN=718303/CN=Redmer Alexander Bertens/CN=708532894\npath length : 0\nbits : 512\ntime left : 12h:0m:0s\n++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n=> Trying to connect to Server [1] root://pcapiserv08.cern.ch:10000 as User rbertens \n/alice/cern.ch/user/a/alidaq/\n/alice/cern.ch/user/r/rbertens/\nYour identity: rbertens\nCreating token ..................................... Done\nYour token is valid until: Wed Nov 1 13:21:18 2017\nFor comparison, here is the output from the JAlien alien-token-init\n[AliPhysics/latest] ~ > alien-token-init\nINFO: JAliEn client automatically creates tokens, alien-token-init is deprecated\nDN >>> /C=ch/O=AliEn2/CN=Users/CN=nhardi/OU=nhardi\nISSUER >>> /C=ch/O=AliEn/CN=AliEn CA\nBEGIN >>> 2020-03-26 10:06:05\nEXPIRE >>> 2020-04-26 08:16:48\nOpen the AliEn shell\nYou can now enter the alice environment shell by typing\nalien.py\nOnce you type this command, a the alice environment shell is loaded, and you should see\n[AliPhysics/latest] ~ > alien.py\nWelcome to the ALICE GRID\nsupport mail: adrian.sevcenco@cern.ch\n\nAliEn[nhardi]:/alice/cern.ch/user/n/nhardi/ >\nThe AliEn legacy shell aliensh and JAliEn shell alien.py are very similar. The command prompt for aliensh shell looks like this:\n[AliPhysics/latest] ~/sw $> aliensh\n [ aliensh 1.0.140x (C) ARDA/Alice: Andreas.Joachim.Peters@cern.ch/Derek.Feichtinger@cern.ch]\naliensh:[alice] [1] /alice/cern.ch/user/r/rbertens/ >\nThis shell works a lot like a normal unix shell, but it is not - not all commands that you expect to find are defined. \nMove to the directory where the data we are looking for is stored\ncd /alice/data/2015/LHC15o/000246757/pass1/AOD/002/\nand copy the AliAOD.root file that is inside this folder to your local hard drive by doing\ncp AliAOD.root file:.\nNote the syntax of the copy command, here we tell to copy the remote file AliAOD.root to our own laptop by specifying file:. . \n JAliEn and AliEn shell documentationYou can find more information about the alien.py shell at jalien.docs.cern.ch. Reference documentation for the legacy AliEn shell is available at alien.web.cern.ch.\n\nTrouble ?\nIf for some reason this does not work for you - no fear. You can ask a colleague to provide a file for you, or send a mail to our mailing lists if you are having trouble with access.\n"},"analysis/running.html":{"url":"analysis/running.html","title":"Step 2 - Running the task","keywords":"","body":"Step 2 - Running the task\nIt is now time to run this simple analysis. To run the task, make sure that the ALICE environment is (still) sourced, and type\n$ aliroot runAnalysis.C\nin the folder where you have stored the analysis code. This command launches aliroot (the ALICE extension of the ROOT data analysis framework), and executes the macro โrunAnalysis.Cโ. The macro will\n\ncompile your analysis code\n\nadd your analysis task to the analysis manager\n\nrun the analysis over the input data file that you have provided\n\n\nAs the code starts running, the analysis manager prints some information to your screen, e.g.\n______________________________________________________________________________\n task: name ACTIVE=0 POST_LOOP=0\n INPUT #0: TChain [NO CONTAINER]\n OUTPUT #1: TList -> [MyOutputContainer]\n Container: MyOutputContainer DATA TYPE: TList\n = Filename: AnalysisResults.root folder: MyTask\nI-AliAnalysisManager::SetUseProgressBar: Progress bar enabled, updated every 25 events.\n ### NOTE: Debug level reset to 0 ###\n(class TClass*)0x37637e0\n===== RUNNING LOCAL ANALYSIS AnalysisTaskExample ON TREE aodTree\n(class TClass*)0x37637e0\nInitialization time: 2.69299 [sec]\nE-AliAnalysisManager::GetRunFromAlienPath: Invalid AliEn path string\nI-AliAODInputHandler::Notify: Moving to file AliAOD.root\nProocessing event [=====| ] 525 [ 50.92 %] TIME 00:00:08 ETA 00:00:08\nThis information is useful: you can see what kind of input and output your job is digesting - and, when something is wrong, you will get detailed information on what is going wrong. \nCaveats\nMake sure though, that the macro โknowsโ where you stored the AliAOD.root file on your laptop (if the AliAOD.root file is in a different folder than the analysis source code, open the runAnalysis.C file, and change the lines where the input file is accessed, just search for AliAOD.root ).\nBy default, the macro will run the task just on your laptop. Later on, weโll see how you can run your analysis on Grid.\nThere are some difference between interaction with ROOT5 and ROOT6; a quick ROOT5 to ROOT6 guide can be found here.\nTake a look at the output\nIf all goes well, your simple task runs over the input data, and fills one histogram with the distribution of transverse momentum of all charged particle tracks in all events. \nOnce the task is done running, take a look at the outputfile \nAnalysisResults.root\n that your analysis has generated. The easiest way to do so is to open a TBrowser (ROOTโs โgraphical user interfaceโ) while you are in (ali)root \nnew TBrowser\nand take a look at the distribution in the histogram. No idea how to use a TBrowser, or what a TBrowser even is? Donโt hesitate to ask, and take a look at the ROOT userโs guide.\n"},"analysis/modify.html":{"url":"analysis/modify.html","title":"Step 3 - Modify the task","keywords":"","body":"Step 3\nIf you managed to run the task, congratulations! This is step one towards becoming a professional physicist (no turning back from here ... ) If it didnโt work, ask for help. Also this is a very significant part of becoming a physicist ...\nAt this point, itโs time to expand our task a bit. What we will do is\n\nAdd some event selection criteria\n\nAdd some track selection criteria\n\n\nBut letโs not go too fast.\nThe event loop\nCollisions are referred to as โeventsโ. In our analysis task, the function \nAliAnalysisTaskSE::UserExec\nis called once for each event in the input data set. You never have to explicitly call this function yourself ! Remember, from programming 101 classes, the lecture about inheritance in C++? The UserExec function is called by a base class that you do not have to worry about. We will later see that this function is only called when an event passes your trigger selection. \nFun !\nItโs time to add some code to our task. First, create additional output histograms in which youโll store\n\nThe primary vertex positions along the beam line for all events\n\nJust like the example histogram fHistPt, you have to add these histograms as members of your class. So: create the pointers in the header file, remember to initialize the pointers in your class constructors, and donโt forget to create instances of the histograms in the UserCreateOutput method.\nOne of the trickiest things in programming can be finding out what methods to use out of millions of lines of code. To help you out, here's a line of code to obtain the vertex position along the beam line\nfloat vertexZ = fAOD->GetPrimaryVertex()->GetZ();\n\nYou can of course just copy-paste these lines into your task and hope that it works, but try to think of\n\ndo you understand the logic of these lines?\n\ncan you find out in which classes these methods are defined?\n\n\nTry to run the code again, after youโve added these histograms.\nAll set?\nItโs almost time to run the modified analysis. Not all collisions in the detector are actually usable for physics analysis. Events which happen very far from the center of the detector, for example, are usually not used for analysis (any idea why?). To make sure that we only look at high quality data, we do โevent selectionโ. Letโs add some event selection criteria to your task.\n\nModify the code such that only primary vertices are accepted within 10 cm of detector center. Such selections in the event sample or track sample are usually referred to as โcutsโ. \nGenerally, we want to see how much data we โthrow awayโ when applying a cut. How would you go about doing that?\n\nBesides rejecting data via cuts, we also make data selection while data taking, by โtriggeringโ: selecting collisions in which we expect certain processes to have occurred. You can check which triggers are selected in the AddMyTask.C macro , where we call\n task->SelectCollisionCandidates(AliVEvent::kAnyINT);\nAs you can see, trigger classes are defined in the class AliVEvent. A quick look into the source code of that classt tells us which triggers are available\n enum EOfflineTriggerTypes { \n kMB = BIT( 0), // Minimum bias trigger in PbPb 2010-11\n kINT1 = BIT( 0), // V0A | V0C | SPD minimum bias trigger\n kINT7 = BIT( 1), // V0AND minimum bias trigger\n kMUON = BIT( 2), // Single muon trigger in pp2010-11, INT1 suite\n kHighMult = BIT( 3), // High-multiplicity SPD trigger\n kHighMultSPD = BIT( 3), // High-multiplicity SPD trigger\n kEMC1 = BIT( 4), // EMCAL trigger in pp2011, INT1 suite\n kCINT5 = BIT( 5), // V0OR minimum bias trigger\n kINT5 = BIT( 5), // V0OR minimum bias trigger\n kCMUS5 = BIT( 6), // Single muon trigger, INT5 suite\n kMUSPB = BIT( 6), // Single muon trigger in PbPb 2011\n kINT7inMUON = BIT( 6), // INT7 in MUON or MUFAST cluster\n kMuonSingleHighPt7 = BIT( 7), // Single muon high-pt, INT7 suite\n kMUSH7 = BIT( 7), // Single muon high-pt, INT7 suite\n kMUSHPB = BIT( 7), // Single muon high-pt in PbPb 2011\n kMuonLikeLowPt7 = BIT( 8), // Like-sign dimuon low-pt, INT7 suite\n kMUL7 = BIT( 8), // Like-sign dimuon low-pt, INT7 suite\n kMuonLikePB = BIT( 8), // Like-sign dimuon low-pt in PbPb 2011\n kMuonUnlikeLowPt7 = BIT( 9), // Unlike-sign dimuon low-pt, INT7 suite\n kMUU7 = BIT( 9), // Unlike-sign dimuon low-pt, INT7 suite\n kMuonUnlikePB = BIT( 9), // Unlike-sign dimuon low-pt in PbPb 2011\n kEMC7 = BIT(10), // EMCAL/DCAL L0 trigger, INT7 suite\n kEMC8 = BIT(10), // EMCAL/DCAL L0 trigger, INT8 suite\n kMUS7 = BIT(11), // Single muon low-pt, INT7 suite\n kMuonSingleLowPt7 = BIT(11), // Single muon low-pt, INT7 suite\n kPHI1 = BIT(12), // PHOS L0 trigger in pp2011, INT1 suite\n kPHI7 = BIT(13), // PHOS trigger, INT7 suite\n kPHI8 = BIT(13), // PHOS trigger, INT8 suite\n kPHOSPb = BIT(13), // PHOS trigger in PbPb 2011\n kEMCEJE = BIT(14), // EMCAL/DCAL L1 jet trigger\n kEMCEGA = BIT(15), // EMCAL/DCAL L1 gamma trigger\n kHighMultV0 = BIT(16), // High-multiplicity V0 trigger\n kCentral = BIT(16), // Central trigger in PbPb 2011\n kSemiCentral = BIT(17), // Semicentral trigger in PbPb 2011\n kDG = BIT(18), // Double gap diffractive\n kDG5 = BIT(18), // Double gap diffractive\n kZED = BIT(19), // ZDC electromagnetic dissociation\n kSPI7 = BIT(20), // Power interaction trigger\n kSPI = BIT(20), // Power interaction trigger\n kINT8 = BIT(21), // 0TVX trigger\n kMuonSingleLowPt8 = BIT(22), // Single muon low-pt, INT8 suite\n kMuonSingleHighPt8 = BIT(23), // Single muon high-pt, INT8 suite\n kMuonLikeLowPt8 = BIT(24), // Like-sign dimuon low-pt, INT8 suite\n kMuonUnlikeLowPt8 = BIT(25), // Unlike-sign dimuon low-pt, INT8 suite\n kMuonUnlikeLowPt0 = BIT(26), // Unlike-sign dimuon low-pt, no additional L0 requirement\n kUserDefined = BIT(27), // Set when custom trigger classes are set in AliPhysicsSelection\n kTRD = BIT(28), // TRD trigger\n // Bits 29 and above are reserved for FLAGS\n kFastOnly = BIT(30), // The fast cluster fired. This bit is set in to addition another trigger bit, e.g. kMB\n kAny = 0xffffffff, // to accept any defined trigger\n kAnyINT = kMB | kINT7 | kINT5 | kINT8 | kSPI7 // to accept any interaction (aka minimum bias) trigger\n };\nbut that may be a bit cryptic .. We wonโt have time to cover triggers in detail, but if you have questions, ask - and if you do analysis - make sure that you are using the correct trigger configuration. \n"},"analysis/track.html":{"url":"analysis/track.html","title":"Step 4 -The track loop","keywords":"","body":"Step 4\nIn this exercise we are going to study the particles that are produced in each event. Out end goal is to identify charged pions, but first weโll familiarize ourselves with the analysis code some more.\n\nPlot the pseudorapidity and azimuthal distributions of the particles for all accepted events in a two-dimensional histogram\n\nMake sure that the axis have proper ranges (how large is the detector?) and a reasonable amount of bins\n\n\nIf youโve added this histogram, run the analysis, and look at the two dimensional histogram. Does the distribution make sense?\nTIP\nIf you have no idea how to extract information on tracks (like azimuthal angle, pseudorapidity, etc) from tracks, it can be useful to look in the source file of the track class to see if you find what you need. You can see that the track class if of type AliAODTrack. You can open the header file of that class AliAODTrack.h to see which methods are defined in this class, to give you a flavor\n\n // kinematics\n virtual Double_t OneOverPt() const { return (fMomentum[0] != 0.) ? 1./fMomentum[0] : -999.; }\n virtual Double_t Phi() const { return fMomentum[1]; }\n virtual Double_t Theta() const { return fMomentum[2]; }\n\n virtual Double_t Px() const { return fMomentum[0] * TMath::Cos(fMomentum[1]); }\n virtual Double_t Py() const { return fMomentum[0] * TMath::Sin(fMomentum[1]); }\n virtual Double_t Pz() const { return fMomentum[0] / TMath::Tan(fMomentum[2]); }\n virtual Double_t Pt() const { return fMomentum[0]; }\n virtual Double_t P() const { return TMath::Sqrt(Pt()*Pt()+Pz()*Pz()); }\n virtual Bool_t PxPyPz(Double_t p[3]) const { p[0] = Px(); p[1] = Py(); p[2] = Pz(); return kTRUE; }\n\n virtual Double_t Xv() const { return GetProdVertex() ? GetProdVertex()->GetX() : -999.; }\n virtual Double_t Yv() const { return GetProdVertex() ? GetProdVertex()->GetY() : -999.; }\n virtual Double_t Zv() const { return GetProdVertex() ? GetProdVertex()->GetZ() : -999.; }\n virtual Bool_t XvYvZv(Double_t x[3]) const { x[0] = Xv(); x[1] = Yv(); x[2] = Zv(); return kTRUE; }\nIt can be hard at first to find where members and methods are defined, and what the design of a software package is. An IDE might help you with that. \nTrack selection\nJust as some events are not of fit to do analysis with, some tracks are also not good for looking at certain observables. In addition to โevent cutsโ, we therefore have to apply โtrack cutsโ as well. In ALICE, we usually use a system of predefined track selection criteria, that are checked by reading the filterbit of a track. \n\nCheck in the code where the filterbit selection is done\n\nChange the filterbit selection from value 1 to 128 to 512\n\n\nHow does your eta, phi distribution change, if you run your task again with filterbit 512? What do you think is the cause of the difference? Keep in mind for later, that you will have to choose your filterbit selection wisely, different types of analyses need different track selections. Discuss with your colleagues, working group or supervisor to decide on what would be best for your analysis. \nTIP\n\nIf you ran your task again, you have - most likely - overwritten the output of the previous run, which makes it hard to compare the distributions obtained with the different filterbits - it can be useful to keep all output files you generate on a safe place on your hard drive\n\n... if you keep the files make sure that you will remember which event and track selections you used. In a few weeks, you have probably forgotten which filterbit was set for a certain output file. You can create readme files, or add a histogram as bookkeeping device.\n\n\n"},"analysis/pid.html":{"url":"analysis/pid.html","title":"Step 5 -Particle identification","keywords":"","body":"Step 5\nIn this section, weโll try to identify particles, by using the amount of energy they have lost per distance traveled in the Time Projection Chamber (TPC). Some specific technical information on how to implement this in your task is given at the end of this document, but general steps to follow are explained here. First, the goals. What we want to do is\n\nidentify pions\n\ncheck how โpureโ our pion sample is\n\n\nWeโll do this by looking at the TPC signal, and seeing how well this signal corresponds to the expected signal for a certain particle species. Look at the figure for clarification, you see lines (the expected signal a particle leaves in the TPC, โthe hypothesisโ) and in colors, the actual signals that were deposited.\n\nStart by storing the TPC signals for all charged particles in your events, in a two-dimensional histogram (such as shown in the figure). First follow the โtechnical stepsโ from Sec. 8, and then try to make such a plot.\nHint, you can get this information by doing\nfYour2DHistogram->Fill(track->P(), track->GetTPCsignal());\n\nIf your histogram is empty after running, try using Filterbit 1 rather than 128.\nAs a second step, you identify particles, and store only the TPC signal that corresponds to pions. \nBEFORE YOU START ...\nTo speed things up a bit, the code that you will need for this exercise is given and explained here. It is recommended to read the entire section prior to implementing the methods. \nTo identify particles, you will add an additional task to your analysis, the โPID responseโ task. This task makes sure that parametrizations that we use for e.g. specific energy loss in the TPC are loaded. To add this task to your analysis, open your runAnalysis.C macro, and add the following lines. Make sure that these lines are called before your own task is added to that analysis manager, your task will depend on this task:\n// load the macro and add the task\nTMacro PIDadd(gSystem->ExpandPathName(\"$ALICE_ROOT/ANALYSIS/macros/AddTaskPIDResponse.C\"));\nAliAnalysisTaskPIDResponse* PIDresponseTask = reinterpret_cast(PIDadd.Exec());\n\nthe above code snippet will work under ROOT6. If you are running ROOT5, the lines to use are a bit different:\ngROOT->LoadMacro(\"$ALICE_ROOT/ANALYSIS/macros/AddTaskPIDResponse.C\");\nAddTaskPIDResponse();\n\nAs a second step, youโll have to make some changed to the header of our analysis. First, youโll add another class member, which is a pointer to the AliPIDresponse object that weโll use in our class. To do this, remember how you added pointers to histograms earlier in this tutorial, so add\n\na forward declaration of the type, i.e. โclass AliPIDResponseโ\n\nthe pointer itself, i.e. โAliPIDResponse* fPIDResponse; //! pid response objectโ\n\n\nDonโt forget to add this new pointer fPIDResponse to the member initialization list in your class constructors (in the .cxx files)!\nAfter making changes to the header, you can add the actual identification routine. This will be done in the implementation of the class. You need to go through a few steps:\n\nRetrieve the AliPIDResponse object from the analysis manager;\n\nmake our poiter โfPIDResponseโ point to the AliPIDResponse object;\n\ninclude the header for the AliPIDResponse class, so that the compiler knows how it is defined\n\n\nThe code to do this might be a bit difficult to figure out by yourself, so itโs given here below\nAliAnalysisManager *man = AliAnalysisManager::GetAnalysisManager();\nif (man) {\n AliInputEventHandler* inputHandler = (AliInputEventHandler*)(man->GetInputEventHandler());\n if (inputHandler) fPIDResponse = inputHandler->GetPIDResponse();\n}\n\nDo you understand\n\nwhat happens in each line?\n\nin which function (UserCreateOutputObjects, UserExcec, Terminate, etc) to put this code?\n\n\nNow that weโve retrieved our PID response object, itโs time to use it. To extract information for different particle species, you can use the functions\ndouble kaonSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kKaon);\ndouble pionSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kPion);\ndouble protonSignal = fPIDResponse->NumberOfSigmasTPC(track, AliPID::kProton);\n\nWhat these functions return you, is a probability that a particle is of a certain type, expressed in standard deviations (ฯ\\sigmaฯ) . To identify a particle, weโll require that its PIDresponse signal lies withim 3 standard deviations of the expected signal. To check this, you can write a few lines such as\nif (std::abs(fPIDResponse->NumberOfSigmasTPC(track, AliPID::kPion)) \nPutting what you have read in practice\nUse the code snippets given in the above sections to implement your particle identification routines. If you are confident that can โisolateโ the pions, create new histograms to store the pionโs\n\ntransverse momentum\n\npseudorapidity\n\nazimuthal angle\n\n\nCentrality\nMost heavy-ion analyses report their results in intervals of collision centrality. In order to access collision centrality within your analysis, you will have to add yet another task to the chain of tasks that is called in your run macro. This third task also needs to be executed prior your own task (note, that the procedure for obtaining centrality for run 1 data can be different - when in doubt, ask your supervisor). The task, called AliMultSelectionTask, can be added to the manager using the following instructions:\n TMacro multSelection(gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/COMMON/MULTIPLICITY/macros/AddTaskMultSelection.C\"));\n AliMultSelectionTask* multSelectionTask = reinterpret_cast(multSelection.Exec());\n\nor, using the ROOT5 equivalent\n gROOT->LoadMacro(\"$ALICE_PHYSICS/OADB/COMMON/MULTIPLICITY/macros/AddTaskMultSelection.C\");\n AliMultSelectionTask* multSelectionTask = AddTaskMultSelection(kFALSE);\n\nTo access centrality within your analysis task, you need to obtain a pointer to the AliMultSelection object, and obtain the collision centrality through this object, e.g. by doing\n Float_t centrality(0);\n AliMultSelection *multSelection =static_cast(fAOD->FindListObject(\"MultSelection\"));\n if(multSelection) centrality = multSelection->GetMultiplicityPercentile(\"V0M\");\n\nUsing the above code snippets, can you select pions in 0-10% centrality, and 50-60% centrality? Does the number of pions change in the way you would expect them to change ?\n"},"analysis/MC.html":{"url":"analysis/MC.html","title":"Step 6 -Using Monte Carlo data","keywords":"","body":"Monte Carlo events\nA large fraction of our recorded data is accompanied by simulated events that we call Monte Carlo (MC) productions. Different MC generators, like PYTHIA, DPMJET, and HIJING are used to simulate collisions, after which a detector response is simulated using GEANT. \nThe main reason for analyzing MC events is that it enables the analyzer to calculate efficiency and acceptance corrections specific for their analysis, and study the difference between the true and reconstructed observables. So, in MC, we have by construction more information available. In MC, we can for example just ask the PDG code of the particles in the event, and then verify how well our data analysis performs. \nAccessing MC productions\nFirst, we have to download the MC data. Since we downloaded Pb-Pb data from the period LHC15o with run number 246757, we will download an AOD file from the same run of a MC that is anchored to this period; namely LHC16g1.\nalien.py\ncd /alice/sim/2016/LHC16g1/246757/AOD198/0002/\ncp alien://AliAOD.root file://AliAOD.root\n\n AliEn legacy shellIn case you are using AliEn legacy software please use aliensh instead of alien.py.\nThe syntax in aliensh is slightly different, you should use alien: and file: prefix. For example:\naliensh\ncp alien:AliAOD.root file:AliAOD.root\n\nIt might be useful to rename the file to AliAOD_MC.root to avoid confusion later on. If you do so, of course you have to change the name of the input data file that you specify in runAnalysis.C.\nNow if we don't do anything else and run the analysis, the MC data will be processed as if it was data, and should produce a similar output when compared to real data. But of course we want to and can do more!\nAccessing the MC information\nWe will add a few things to our code to be able to obtain information that is provided directly by the Monte Carlo generator itself (often referred to as 'true level' or 'generator level'). First, we add our new global variable to the header in the list of private objects:\nAliMCEvent* fMCEvent; //! corresponding MC event\n\nThen we add fMCEvent to the constructors\n...\nAliAnalysisTaskMyTask::AliAnalysisTaskMyTask() : AliAnalysisTaskSE(), \n fAOD(0), fMCEvent(0), fOutputList(0), fHistPt(0)\n{\n...\n\nand\n...\nAliAnalysisTaskMyTask::AliAnalysisTaskMyTask(const char* name) : AliAnalysisTaskSE(name),\n fAOD(0), fMCEvent(0), fOutputList(0), fHistPt(0)\n{\n...\n\nIn UserExec we can now use our new global variable to obtain the MC event through the MCEvent method\nfMCEvent = MCEvent();\n\nNow let's use the information by creating a new function that loops over the MC particles:\nin the header file we declare our new function ProcessMCParticles\nvoid ProcessMCParticles();\n\nThen we put the implementation in the .cxx file:\nvoid AliAnalysisTaskMyTask::ProcessMCParticles()\n{\n // process MC particles\n TClonesArray* AODMCTrackArray = dynamic_cast(fInputEvent->FindListObject(AliAODMCParticle::StdBranchName()));\n if (AODMCTrackArray == NULL) return;\n\n // Loop over all primary MC particle\n for(Long_t i = 0; i GetEntriesFast(); i++) {\n\n AliAODMCParticle* particle = static_cast(AODMCTrackArray->At(i));\n if (!particle) continue;\n cout GetPdgCode() \nFinally we call our newly created function in UserExec:\nif(fMCEvent) ProcessMCParticles();\n\nYou can run the code and enjoy the list of PDG code values of each particle in the MC event... although it might be more useful to fill a histogram with the values instead of printing them to the terminal.\n"},"analysis/grid.html":{"url":"analysis/grid.html","title":"Step 7 -Run your code on GRID","keywords":"","body":"Step 7\nIs your pion analysis running smoothly on your laptop? If yes, then it is time to 'scale things up' a bit. We will run your task on the Grid. \nThe macro\nrunAnalysis.C\nthat you used in the previous exercises already contains all the information that you need for running on the Grid. In fact, all that you have to do is open it, and make a minor change at the start of the macro\nvoid runAnalysis()\n{\n // set if you want to run the analysis locally (kTRUE), or on grid (kFALSE)\n Bool_t local = kFALSE;\n // if you run on grid, specify test mode (kTRUE) or full grid model (kFALSE)\n Bool_t gridTest = kTRUE;\nNote that we will first test if our code is actually 'grid compatible', by simulating a Grid node on our computer. Before you launch this test, browse through the runAnalysis.C macro and try to convince yourself of the fact that you understand the logic, and whether or not the configuration makes sense.\nRunning a Grid test\n AliEn-ROOT-Legacy tokens In case you are using AliEn-ROOT-Legacy, for instance with ROOT5, then you should first create an access token using command alien-token-init.\n\nIf you think everything is OK, and run the Grid test by simply launching the runAnalysis macro\naliroot runAnalysis.C\nYou will notice that the running time for the task is now probably a bit longer, as we have to wait for data to be retrieved. Does your analysis run fine? If it exits without problems, make sure to check your histograms and see if the output is as you expected it to be !\nLaunching your job on Grid\nIf the Grid test was successful, you can launch your analysis on Grid. Set the flag โgridTestโ in your macro to kFALSE,\nvoid runAnalysis()\n{\n // set if you want to run the analysis locally (kTRUE), or on grid (kFALSE)\n Bool_t local = kFALSE;\n // if you run on grid, specify test mode (kTRUE) or full grid model (kFALSE)\n Bool_t gridTest = kFALSE;\nand relaunch your analysis. \nMonitoring your jobs\nOnce you have submitted your job to Grid, you can track the progress at https://alimonitor.cern.ch/users/jobs.jsp. You will need your digital certificate to get access to the job pages!\nMerging your job's output\nOnce your jobs are all in done, it is time to merge the output files that were generated on the independent Grid nodes into one output file that is on your laptop. We will do this in two stages\n\nMerge all the output files that were generated by one masterjob into one output file that is still stored on the Grid\nMerge these 'master' output files into one output file on your laptop. \n\nNote that, since we only launched one masterjob, these two steps may seem a bit silly here. However, if you launch multiple masterjobs, this approach is very useful. \nMerging: step 1\nTo perform step 1 of the merging, open the runAnalysis.C macro again, and change the argument of SetRunMode() into terminate\nalienHandler->SetRunMode(\"terminate\")\nafter you have made this change, you have to launch your job again. The job that you are now launching is a merging job: an instruction send to the grid nodes to combine the independent AnalysisResults.root files of sub-jobs into one merged file per master-job. \nJust as with a normal job, you can monitor the progress of the merging job via https://alimonitor.cern.ch/users/jobs.jsp. \nMerging: step 2\nOnce the merging job is finished, you will need to retrieve the final output on your laptop. One more change to your runAnalysis.C macro needs to be made. Open the file, and set\nalienHandler->SetMergeViaJDL(kFALSE);\nThen, launch the macro again. If all goes well, it should proceed to merge the output of the merging jobs into one final output file on your laptop. \nHappy analyzing ! \n"},"analysis/bonus.html":{"url":"analysis/bonus.html","title":"Bonus content","keywords":"","body":"Bonus contents\nMinimal systematics\nAs you can see in the figure, the TPC signals of different particle species cross each other. In\nthese regions, it is difficult (or impossible) to identify particles. Because of this ambiguity,\nwe have to estimate what the uncertainty on our identification routine is.\n\nRun the main code multiple times, varying the number of standard deviations that you require the signal to be in from 3 to 4, and from 3 to 2.\n\nHow do your spectra change? Do these changes make sense to you?\n\n\nIf you are very enthusiastic,\n\nTry to estimate the systematic uncertainty that particle identification introduces to your measurement.\n\nMake it presentable\nBy now, you have made quite a few nice plots. Modify the code such that the labels, titles, markers, colors, legends of your plots look decent and presentable for fellow colleagues\n\nDid you know that you can use LaTeX in ROOT? This comes in handy when you are labeling axes, etc.\n\nStore one or two of your pictures. You can store them as ROOT files, macros, or as graphics.\nAlways use vector graphics (.ps, .pdf)!\n\nNever be afraid to make titles and axis labels larger, itโs better if things look a bit\n\"cartoonish\" than when half of the collaboration cannot read whatโs on your plots - especially\nwhen they are broadcast or projected\n\n\nIn practice, we usually donโt use the TBrowser for \"postprocessing\", but write dedicated code that opens our AnalysisResults.root files, does some final calculations, and makes our plot pretty.\n"},"analysis/hints.html":{"url":"analysis/hints.html","title":"Some hints","keywords":"","body":"AliRoot and AliPhysics documentations\nThe Doxygen documentation of AliROOT and AliPhysics is available here http://alidoc.cern.ch/ . It is generated daily.\nCleaning up and improving your code\n\nOne of the most important things you can do is make sure your code\nis readable\n\nThis means using whitespace freely, consistent indentation,\netc\n\nThis is valid C++ code:\n\n\n for(int i=0;i\nbut it looks bad\n\nThis is C++ code equivalent to that:\n\n for(int i=0; i\nand it looks much **better**\n\nThere are no wrongs or rights, but be consistent\n\nFault tolerance\n\nCheck e.g. the snippet\n\n for(Int_t i(0); i (fAOD->GetTrack(i));\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n\n\nWe can build in fault tolerance:\n\n for(Int_t i(0); i (fAOD->GetTrack(i));\n if(!track) continue;\n // fill our histogram\n fHistPt->Fill(track->Pt());\n }\n\n\nFinally, itโs a very good idea to comment your code\n\nComments improve readability and maintainability\n\nComments should be useful, though, and comments that are overly\nobvious can be avoided\n\n\n // no comment: bad\n a++;\n\n // pointless comment, also not so good\n\n a++; // adding 1 to a\n\n\n // descriptive comment, very good\n\n a++; // adding 1 to a to make a point during a tutorial\n\n\nItโs also a good idea to document your code as youโre writing it -\nyou will forget how it works and no-one will continue with\nuncommented tasks\n\n"},"analysis/ROOT5-to-6.html":{"url":"analysis/ROOT5-to-6.html","title":"Transition from ROOT5 to ROOT6","keywords":"","body":"Transition from ROOT5 to ROOT6\nROOT6 is similar to ROOT5: It comes with the same library of classes (base\nclasses, histogram classes like TH1, ...) which share the same interface as under\nROOT5. It provides a command line interface as ROOT5, and runs macros just\nlike under ROOT5. Therefore it is possible to build and run the ALICE\nsimulation, reconstruction and analysis framework under ROOT6. AliPhysics can be\nbuilt against ROOT6 in the following way:\naliBuild -z --defaults o2 build AliPhysics\n\nIf you have aliBuild v1.12.0 or later, you don't need to specify --defaults o2.\nFor classes in AliRoot or AliPhysics this transition is transparent. For code in\nmacros there are however a few difference. This page tries to summarize the\ndifferences in behaviour observed so far and gives some suggestions how to solve\nthese issues so work can go on smoothly under ROOT6.\nWhat is a just-in-time compiler?\nFor the command line interface and running macros ROOT5 uses CINT, which is an\ninterpreter for C/C++. An interpreter processes a macro line-by-line. It depends\non the implementation of the interpreter how C++ code will be handled and how\nclose the interpretation comes to the language standard. ROOT5 allows for some\ndeviations from the language standards, which means that some coding errors\nwhich would thrown by a compiler leading in a break of the compilation are still\ntolerated by ROOT5. Furthermore the standard library is not fully supported as\nits handling has to be implemented into the compiler. Macro can however also be\nrun in the compiled mode by ROOT5 (adding a \"+\" to the macro name). In this case\nROOT calls an external compiler to compile the macro to a library which is loaded\ninto ROOT. Once the macro runs in compiled mode it is expected to be fully\ncompatible with the C++ standard and coding error free as the compiler will not\ntolerate compiler errors.\nIn contrast to this ROOT6 uses a just-in-time compiler called cling. A\njust-in-time compiler translates each statement, no matter whether it is a single\ncommand or a complicated macro, into machine code as it would be a program and\nonly afterwards runs this piece of code. In order to translate code into machine\ncode the compiler must know how to translate every single line. Based on powerful\ncompiler library this means for ROOT6 that all macro must comply to 100% with\nthe C++ language standard, and exceptions will not be tolerated. Furthermore this\nalso means that all symbols and objects must be known at compile time. This has\nthree side effects:\n\nLoading Functions with gROOT->LoadMacro(...);: This function loads all\nfunctions it finds within the macro into ROOT during run time. For an interpreter\nthis is sufficient as the functions are used after they are loaded. However the\ncompiler must know all symbols used in a macro at compile time.\nLoading libraries with gSystem->Load(...);: Here we have the same problem:\nThe symbols in the libraries must be known before they are used.\nCompiling ALICE analysis tasks on the fly with gROOT->LoadMacro(\"...+\");:\nAs the analysis task compiled like this will be converted in a library it must be\nknow to the just-in-time compiler before.\n\nFor all three cases exist workarounds which will be discussed in the next\nsections. In general macros which were running under ROOT5 in the compiled mode\nwill also run under ROOT6. Macros which were running only in the interpreted\nmode might contain coding errors which were not handled by ROOT5 and might\ntherefore need fixes. However the just-in-time compiler will give precise error\nmessages leading exactly to the lines which need fixes.\nHow can I call macros inside macros?\nCalling macros inside macros is a bit tricky as the result of a macro will be\navailable only at runtime. There are however several workarounds which cover the \nmost common use cases:\n\nUsing ROOT's TMacro:\nTMacro is a wrapper class around the macro processing. It is constructed with\nthe macro path. The macro is run using TMacro::Exec. The result of\nTMacro::Exec() is a number representing an address in memory where to\nfind the resulting object. This has to be cast into a pointer to an object of\nthe expected type. Example:\nTMacro physseladd(gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/macros/AddTaskPhysicsSelection.C\"));\nAliPhysicsSelectionTask *physseltask = reinterpret_cast(physseladd.Exec());\n\nThe macro is still evaluated at runtime, however with the reinterpret_cast to\nAliPhysicsSelectionTask * we tell ROOT that the result of the macro\ninterpretation must be of type AliPhysicsSelectionTask *, so the type is known\nat compile time. TMacro::Exec optionally gets a string representation of the\nfunction arguments. This might be a bit complicated to handle, particularly if\nthe arguments are dynamic and change at run time. The method works both for\nROOT5 and ROOT6.\n\nUsing gROOT/gInterpreter->ProcessLine: \nMacro execution can be launched as well via gROOT->ProcessLine() /\ngInterpreter->ProcessLine(). As with TMacro this method is focused on running\na macro and not loading content from it. The ProcessLine method returns a\nlong number representing an address in memory where to find the output objects.\nThis number has to be cast to the expected output type using a\nreinterpret_cast in order to access the content of the output objects. The\nfollowing example runs the add macro for the physics selection task:\nAliPhysicsSelectionTask *physseltask = reinterpret_cast(gInterpreter->ProcessLine(Form(\".x %s\", gSystem->ExpandPathName(\"$ALICE_PHYSICS/OADB/macros/AddTaskPhysicsSelection.C\"))))\n\nAdding function arguments is possible here as well as a simple string\nrepresentation after the macro path, surrounded with (). This method also works\nboth under ROOT5 and ROOT6.\n\nIncluding macros:\nAs ROOT6 compiles the macro it is possible to include macros and treat them\nas if they were header files. In order for this to work it is essential to tell\nROOT before where to find the macro. This can be done using the preprocessor\nmacro R_ADD_INCLUDE_PATH(...). For the just-in-time compiler macros\nincluded will look as if they were part of the code itself. The following macro\nruns under ROOT6:\n#ifdef __CLING__\n// Tell ROOT where to find AliRoot headers\nR__ADD_INCLUDE_PATH($ALICE_ROOT)\n#include \n\n// Tell ROOT where to find AliPhysics headers\nR__ADD_INCLUDE_PATH($ALICE_PHYSICS)\n#include \n#endif\n\nvoid simpleaddtest(){\n AliAnalysisManager *mgr = new AliAnalysisManager;\n\n // Take function from macro AddESDHandler\n // no gROOT->LoadMacro for ROOT6\n AddESDHandler();\n\n AliPhysicsSelectionTask *test = AddTaskPhysicsSelection(kTRUE);\n\n mgr->InitAnalysis();\n mgr->PrintStatus();\n}\n\nIn particular when passing arguments to the macro (in the example above passing\nkTRUE to AddTaskPhysicsSelection) this method is very convenient. This method\nis specific to ROOT6. The part including macros has to be protected (see\nbelow).\n\n\nDo I need to include header files in my macros?\nROOT6 comes with a technique called pre-compiled header files. Header files\nfrom a certain library are compiled to a binary format by rootcling, the\nsuccessor of rootcint, and loaded into ROOT6 by an auto-loading mechanism\nsimilar to the rootmap mechanism. Once rootcling is invoked with the\nargument -rml name a .pcm-file is created containing the pre-compiled\nheaders. ROOT6 will search for .pcm-files in the LD_LIBRARY_PATH.\nThe following packages in ALICE provide .pcm support:\n\nAliRoot\nAliPhysics\nRooUnfold\nFairRoot\no2\n\nFor libraries providing .pcm-support NO headers should be included in macros.\nFor libraries handled by the user make sure to\n\nrun rootcling with the arguments -rmf for the .rootmap file\nand -rml for the .pcm file\nInstall both the .rootmap and the .pcm file of your library path in the \nlibrary location (usually PROJECT_PATH/lib)\n\nI get a huge amount of errors, and my macro doesn't run. What can I do?\nHere are few examples that commonly appear in user macros and which are tolerated by ROOT5 but not anymore by ROOT6:\n\nUndefined symbols:\nMaybe you have something like this in your code:\ntaskname = \"mytask\";\n\nThe variable taskname was not defined before. It was implicitly defined in ROOT5 as const char *. In ROOT6 this leads to the error\nerror: use of undeclared identifier 'taskname'\nThe variable taskname must be defined with a type before a value can be assigned. In this case the proper code would be\nconst char *taskname = \"mytask\";\n\nThanks to C++11 ROOT6 can also detect the type implicitly using the keyword\nauto. In this case the code looks the following:\nauto taskname = \"mytask\";\n\nThis will however not be transparent to ROOT5 as ROOT5 doesn't understand\nC++11.\nNote: On the command line ROOT6 automatically adds the auto keyword. The \nstatement above will be possible in the interpreted mode of ROOT6.\n\nMissing forward declarations\nConsider this macro:\nvoid fail_forward() {\n int result = test(2,4);\n printf(\"2 + 4 = %d\\n\", result);\n}\n\nint test(int a, int b) {\n return a + b;\n}\n\nUnder ROOT5 this macro will run, but under ROOT6 it will raise the following compiler error:\nerror: use of undeclared identifier 'test'\nThe function test is defined, but after it is used. In ROOT5 this is\nno problem: During interpretation the interpreter loads all functions. But\nunder ROOT6 the macro is compiled, and now the order matters: Functions need\nto be declared before they are used. Adding a forward declaration is \nsufficient in order to make the macro working. The following version of\nthe macro will run also under ROOT6:\nint test(int a, int b);\n\nvoid run_forward() {\n int result = test(2,4);\n printf(\"2 + 4 = %d\\n\", result);\n}\n\nint test(int a, int b) {\n return a + b;\n}\n\n\nHandling of pointer and objects:\nROOT5 does not enforce using the proper access operator for objects, pointers and\nreferences, but will allow the usage of the operator -> for\nreferences and the operator . for pointers. ROOT6 distinguishes\nbetween them, and consequently the proper access operator needs to be used.\nConsider the following macro:\nvoid fail_access(){\n TH1F *ptr = new TH1F(\"ptr\", \"ptr\", 1, 0., 1.);\n ptr.SetTitle(\"test1\");\n printf(\"Title 1: %s\\n\", ptr.GetTitle());\n\n TH1F obj(\"obj\", \"obj\", 1, 0., 1.);\n obj->SetTitle(\"test2\");\n printf(\"Title 2: %s\\n\", obj.GetTitle());\n}\n\nConsequently the wrong access operator is used. ROOT5 will warn about the\nincorrect access operator, but it will run the macro. Trying this under ROOT6\nends in the following errors:\n...: error: member reference type 'TH1F *' is a pointer; did you mean to use '->'?\nptr.SetTitle(\"test1\");\n ~~~^\n ->\n...: error: member reference type 'TH1F *' is a pointer; did you mean to use '->'?\n printf(\"Title 1: %s\\n\", ptr.GetTitle());\n ~~~^\n ->\n...: error: member reference type 'TH1F' is not a pointer; did you mean to use '.'?\n obj->SetTitle(\"test2\");\n ~~~^~\n .\n...: error: member reference type 'TH1F' is not a pointer; did you mean to use '.'?\n printf(\"Title 2: %s\\n\", obj->GetTitle());\n ~~~^~\n .\n\n\nI get a huge amount of unknown symbols from classes in AliRoot or AliPhysics? Do I still need to include header files?\nIn case the compilation of a macro under ROOT6 fails libraries and pre-compiled\nheaders from external packages are not loaded. The consequence is that ROOT6\ndoes not know about these classes and will raise errors about unknown symbols.\nOnce all the initial compiler errors are fixed (usually at the very top of\nthe error log), the next time the macros are compiled ROOT6 will also load the\nlibraries and .pch files from external libraries and the errors disappear. Header\nfrom ALICE libraries should NOT be included.\nHow do I distinguish between ROOT5 and ROOT6 in my macros?\nSometimes macros require different treatment for ROOT5 and ROOT6. It is then\nnecessary to know which ROOT version is used while the macro is running.\nROOT5 defines the preprocessor macro __CINT__, which can be used to check\nwhether one is in an interpreter session. In current (up to at least v6-12-04)\nhowever also ROOT6 exports __CINT__, so this macro cannot be used to\ndistinguish between ROOT versions.\nROOT6 in addition __CLING__ which is not present in ROOT5. The following lines \nindicate how to run ROOT5/ROOT6 specific code:\n#if defined(__CLING__)\n // ROOT6-specific code here ...\n#elif defined(__CINT__)\n // ROOT5-specific code here ...\n#endif\n\nI heard TF1 has changed fundamentally. Is there something to be aware of?\nTF1 is based on TFormula for the formula representation. TFormula got a heavy\nchange: In ROOT5 formulas were always interpreted on-the-fly. With ROOT6 they\nare compiled by the just-in-time compiler. While this leads to a significant\nspeedup in particular when the formula is evaluated multiple times (in fit\nprocedures for example) it comes on cost of breaking backward compatibility, for\nwhich reading TFormula/TF1 object created with ROOT6 with ROOT5 will lead to\nerrors. For what concerns TFormala a ROOT5-compatible version has been added to\nROOT6 as ROOT::v5::TFormula, however something similar does not exist for\nTF1. In order to read a TF1 object from a ROOT file under ROOT5 it has to be\ncreated under ROOT5.\nNow my macro finally works under ROOT6. Will it still work under ROOT5?\nIt depends whether the macro now contains something which ROOT5 does NOT\nunderstand.\n\nROOT6 is fully compatible with C++11. In ROOT5 C++11 support is not\nimplemented, but the standard C++98 is used. C++11-specific code will not\nbe understood.\nAll NEW features provided by ROOT6 are of course not ported to ROOT5.\nThis in particular affects:\nTTreeReader\nTProcPool\nTDataFrame\n...\n\n\nStandard library support in ROOT5, while it comes out-if-the-box in ROOT6.\nIf the macro should run under both ROOT versions consider ROOT containers\ninstead.\nIf your classes write stl-containers containing ROOT-objects to a ROOT-file \nthey must be declared to ROOT5 in your LinkDef.h file. Example:#pragma link C++ class std::vector+;\n\nFor ROOT6 this is not necessary.\n\n\n\n"},"rivet/rivet-tutorial.html":{"url":"rivet/rivet-tutorial.html","title":"Rivet","keywords":"","body":"Rivet in ALICE\nIn this tutorial, we will go through the ALICE documentation on Rivet. You can follow the examples yourself.\nFor past recorded tutorials on Rivet, follow the link to the Analysis tutorial: https://alice-analysis.web.cern.ch/content/tutorials.\n"},"rivet/getting-started.html":{"url":"rivet/getting-started.html","title":"Getting started with Rivet","keywords":"","body":"Getting started with Rivet\nOverview\nRivet (Robust Independent Validation of Experiment and Theory) is a generator-agnostic framework to replicate analyses performed on experimental data on the output of Monte Carlo event generators. The latter are interfaced through event records written in the HepMC format. Rivet reads these input data and reproduces the selected analysis as well as produces comparison plots to the published data.\nAnalyses for Rivet are implemented as plugins, the official ones being distributed together with Rivet. This design allows for the easy implementation and usage of new analysis even before they become official. Each plugin needs to contain the required information to reproduce the analysis, to produce the comparison plots, and the required references for documentation. The detailed content of a plugin is explained below.\nAnalysis plugin\nAn analysis plugin can be distributed with Rivet or added on-top of a Rivet installation (e.g. for local development). It always comprises the following elements:\n\nidentifier: __I (for older analyses the SPIRES ID was used)\ntitle\ndescription:\nshort summary of the analysis content collision system and energies \nreference to paper \nstatus: preliminary, unvalidated, validated, obsolete, \\dots\n\n\ncode:\ncode to reproduce the analysis on Monte Carlo output\n\n\ndata:\nmeasured data points and uncertainties\n\n\n\n"},"rivet/rivet-in-alice.html":{"url":"rivet/rivet-in-alice.html","title":"Using Rivet in ALICE","keywords":"","body":"Using Rivet in ALICE\nRivet has been integrated into the ALICE build system and is maintained there. Thus, it is also deployed to cvmfs, from where it can be used by Grid workernodes, interactive lxplus sessions, or other machines using software from cvmfs (e.g. CERN Linux desktops). It can also be installed locally using aliBuild. However, if you just get started and want to gain experience with Rivet, we recommend to use the cvmfs installation on lxplus, as this is maintained centrally and known to work (if it is not, please report!).\nUsing Rivet on lxplus\nIn order to use Rivet on lxplus, you just have to logon and use alienv to enter a shell with the proper environment loaded (same procedure as for AliPhysics):\nssh lxplus.cern.ch\nalienv enter Rivet\n\nYou can then check which packages and versions are loaded using:\nalienv list\n\nNow you have all the rivet tools (rivet, rivet-build, ...) available. To list the available analyses (those distributed with the used version of Rivet), you can use:\nrivet --list-analyses\nrivet --list-analyses ALICE_\n\nwhere the second command only lists analyses for ALICE publications. You can display the details of one of these analyses (here ALICE_2010_S8625980) using:\nrivet --show-analysis ALICE_2010_S8625980\n\nAssuming you have some output from a Monte Carlo generator in a HepMC file (e.g. /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc or see here for instructions on running MC generators), you can run an analysis (e.g. ALICE_2010_S8625980) on this input using:\nrivet -a ALICE_2010_S8625980 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\nwhere -a is used to specify the analysis you want to run (you can use any analysis that was distributed with Rivet). You can also list more than one analysis.\n BewareBeware the absence (!) of extension of your analysis name specified at the rivet command, i.e. no \"rivet -a ALICE_2010_S8625980.cc ...\". This would make your analysis not recognisable by Rivet, and it will complain so.\n\nThe command line above runs the analysis on the given input (~1000 generated events, here) and stores the produced output, typically histograms, in the file Rivet.yoda. Based on this yoda file, you can produce plots by running:\nrivet-mkhtml Rivet.yoda\n\nThis command puts the plots in the subdirectory rivet-plots/. The directory also contains an index.html, which you can open in a browser to look and navigate through the plots. If you have run Rivet on an lxplus node you probably must copy this directory to your local PC and then point your browser to the directory, i.e.\nscp -r lxplus.cern.ch:/rivet-plots /tmp/myRivetPlots\nopen /tmp/myRivetPlots/index.html (on Mac OS X, otherwise point browser to file:///tmp/myRivetPlots/index.html)\n\n N.B.If on lxplus you use a directory under /tmp you have to copy from the exact host you are working on instead of lxplus.cern.ch, e.g. lxplus012.cern.ch. You can get actual name of the hosting machine with hostname.\nWe recommend not to use direclty the directory /tmp to avoid clashes with other user. Please use /tmp/ to follow this tutorial even if stated differently.\n\nRunning Rivet together with a generator\nYou can use Rivet to run on the output of an arbitrary generator for which an interface to HepMC exists - e.g. those which have been integrated into the ALICE build system and are, thus, available on cvmfs or for local installation. There are two common options to run the generator and Rivet:\n\nintermediate file:\nrun generator writing to hepmc file\nrun Rivet reading from hepmc file (see example above)\n\n\nFIFO (first-in-first-out pipe, on Linux)\ncreate FIFO (NB: not possible on afs, need to use /tmp on lxplus)\nrun generator writing to FIFO (process won't finish)\nrun Rivet reading from FIFO\n\n\n\nThe latter option avoids writing a file to disk and is beneficial if the generator is fast. You can run a generator directly or use aligenmc after you have set it up with:\nalienv enter AliGenerators\n\nThen, you would have to do something like:\nmkfifo /tmp/$USER/fifo_$UID.hepmc\naligenmc -g pythia8 -E 7000 -N 10000 -o /tmp/$USER/fifo_$UID.hepmc &> /tmp/$USER/aligenmc_$UID.log &\nrivet -a ALICE_2010_S8625980 /tmp/$USER/fifo_$UID.hepmc\nrm /tmp/$USER/fifo_$UID.hepmc\n\n Notealigenmc is the script developed within ALICE that does the running of a chosen generator, with a dedicated configuration file, and writing the output to the specified file/FIFO.\nFor further instructions on how to run different generators, see:\n\naligenmc -h\nMC generator documentation\n\n\n Pythia8/Angantyraligenmc is not yet updated to generate heavy-ion collisions with the Pythia8/Angantyr model. In case you want to generate Pb-Pb collisions with Pythia8/Angantyr model you can \nrun-pythia -n 100 -e 2760 -o /tmp/$USER/fifo_$UID.hepmc -c \"Beams:idA 1000822080\" -c \"Beams:idB 1000822080\" -c \"HeavyIon:SigFitNGen = 0\" -c \"HeavyIon:SigFitDefPar = 12.32,1.63,0.19,0.0,0.0,0.0,0.0,0.0\" \n\nBeware that this line is valid only for Pb-Pb 2.76 TeV collisions. Should you need to change the collision energy (the the beams), make sure you run only the initial part\nrun-pythia -n 100 -e 2760 -o /tmp/$USER/fifo_$UID.hepmc -c \"Beams:idA 1000822080\" -c \"Beams:idB 1000822080\"\n\n\n"},"rivet/implementing-rivet-analysis.html":{"url":"rivet/implementing-rivet-analysis.html","title":"Implementing a Rivet analysis","keywords":"","body":"Implementing a Rivet analysis\nIn order to implement a new analysis, you can start from a template created by the Rivet tools. Best start in a new directory for the implementation and create the template therein:\nmkdir myRivet\ncd myRivet\nrivet-mkanalysis \n\nwhere ID specifies the identifier of the analysis. If you are aiming for an official analysis, you should use the proper identifier; if you are just testing, you can use essentially what you want. If you use an identifier referring to a published analysis, e.g. ALICE_2011_I1080735, you automatically get the reference data (taken from HepData) and the metadata (taken from spires/inspire) for this analysis.\nIn the next step, you \"just\" have to add the missing bits and pieces to the template. In more detail, the rivet-mkanalysis command will give you a bunch of files, amongst others a cc-file for the implementation of the analysis. This cc-file contains already the required class and the mandatory methods:\n\ninit\nanalyze\nfinalize\n\nwhich you still have to fill with useful content, of course. We will explain the required implementations in more details below, the template (for an assumed analysis ALICE_2016_test) contains:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/FinalState.hh\"\n#include \"Rivet/Projections/FastJets.hh\"\n#include \"Rivet/Projections/DressedLeptons.hh\"\n#include \"Rivet/Projections/MissingMomentum.hh\"\n#include \"Rivet/Projections/PromptFinalState.hh\"\n\nnamespace Rivet {\n\n\n /// @brief Add a short analysis description here\n class ALICE_2016_test : public Analysis {\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2016_test);\n\n\n /// @name Analysis methods\n ///@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Initialise and register projections\n\n // The basic final-state projection:\n // all final-state particles within\n // the given eta acceptance\n const FinalState fs(Cuts::abseta 20*GeV;\n DressedLeptons dressed_leps(photons, bare_leps, 0.1, lepton_cuts);\n declare(dressed_leps, \"leptons\");\n\n // Missing momentum\n declare(MissingMomentum(fs), \"MET\");\n\n // Book histograms\n // specify custom binning\n book(_h[\"XXXX\"], \"myh1\", 20, 0.0, 100.0);\n book(_h[\"YYYY\"], \"myh2\", logspace(20, 1e-2, 1e3));\n book(_h[\"ZZZZ\"], \"myh3\", {0.0, 1.0, 2.0, 4.0, 8.0, 16.0});\n // take binning from reference data using HEPData ID (digits in \"d01-x01-y01\" etc.)\n book(_h[\"AAAA\"], 1, 1, 1);\n book(_p[\"BBBB\"], 2, 1, 1);\n book(_c[\"CCCC\"], 3, 1, 1);\n\n }\n\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Retrieve dressed leptons, sorted by pT\n vector leptons = apply(event, \"leptons\").dressedLeptons();\n\n // Retrieve clustered jets, sorted by pT, with a minimum pT cut\n Jets jets = apply(event, \"jets\").jetsByPt(Cuts::pT > 30*GeV);\n\n // Remove all jets within dR 5*GeV && Cuts::abseta (event, \"MET\").missingPt() fill(bjets[0].pT()/GeV);\n\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n\n normalize(_h[\"XXXX\"]); // normalize to unity\n normalize(_h[\"YYYY\"], crossSection()/picobarn); // normalize to generated cross-section in fb (no cuts)\n scale(_h[\"ZZZZ\"], crossSection()/picobarn/sumW()); // norm to generated cross-section in pb (after cuts)\n\n }\n\n ///@}\n\n\n /// @name Histograms\n ///@{\n map _h;\n map _p;\n map _c;\n ///@}\n\n\n };\n\n\n DECLARE_RIVET_PLUGIN(ALICE_2016_test);\n\n}\n\nRivet usually does not use a separate header file for the implementation of the main class of the analysis (you can add further classes and headers if the analysis gets more complex). When extending the code for the Rivet plugin, be careful to follow Rivet coding conventions (which are different from the ALICE ones) such that the analysis can eventually be submitted to the Rivet team for integration into the official distribution.\nYou can already try and compile the plugin at this stage to make sure that the setup and preparations are correct:\nrivet-build RivetALICE_2016_test.so ALICE_2016_test.cc\n\nwhich builds the shared library RivetALICE_2016_test.so to be used by Rivet.\nRequired member variables and methods\nFor the plugin to do something useful, you need to add code in a few places. The basic steps are usually very straight-forward.\nmember variables\nYou can add member variables in the private section (below the Analysis methods section). They should follow the naming conventions of Rivet. This is the place where you add the pointers for histograms, profiles, etc. There are special Rivet structures for such pointers which should be used:\nHisto1DPtr _h_0000; // for a histogram\nProfile1DPtr _h_0001; // for a profile\n\nOf course, you can also add variables of your own, e.g. to define pt/rapidity ranges, jet radii, ...\ninit\nThe code in this method is run once at the beginning of the run. It is used to set up the analysis.\nHere, you have to book the histograms (using the previously added pointers). When implementing a published analysis, the preferred way to book the histograms is to let Rivet take the histogram details from the reference data:\nbook(_h_0000, \"d01-x01-y01\");\nbook(_h_0001, \"TMP/test\", refData(1, 1, 1));\n\nwhere d01-x01-y01 refers to the reference data (following HepData naming conventions for the histograms). If you don't have a reference histogram or you need to use a different binning, you can book a histogram as follows:\nbook(_hist, \"pt_h\", 10, 0., 20.);\n\nIn addition to the histogram bookings, you need to add all the projections required for the analysis. Rivet uses projections to extract (and re-use) observables from the final state, e.g. particles (after cuts), jets, .... E.g. for an analysis based on charged particles in the rapidity interval etamax, you would use:\n// need to #include \"Rivet/Projections/ChargedFinalState.hh\"\nconst ChargedFinalState cfs(Cuts::abseta \nFor an analysis based on jets you would use:\nconst FinalState fs_jet(Cuts::abseta \nFor an analysis based on primary particles according to the ALICE definition you would use:\n// need to #include \"Rivet/Projections/AliceCommon.hh\"\n// Charged, primary particles with |eta| 150 MeV\ndeclare(ALICE::PrimaryParticles(Cuts::abseta 150*MeV && Cuts::abscharge > 0), \"APRIM\");\n\nFor more details on possible projections, see the reference page\nanalyze\nThe code in this method is run for every event and is used for the actual (event-wise) analysis. The event for analysis is passed as parameter to the function. Commonly, you apply the projections, and fill some histograms:\nconst ALICE::PrimaryParticles & aprim = apply(event, \"APRIM\");\n\nfor (const Particle &p : aprim.particles()) {\n _h_0000->fill(p.pT()/GeV);\n}\n\nN.B.: Here, the iterations use C++11 constructs.\nfinalize\nThe code in this method is run once after the run. It is typically used for scaling and/or normalization of histograms. In order to normalize a histogram to the number of events, you can make use of Rivet helpers:\nscale(_h_0000, 1./sumOfWeights());\n\nwhere sumOfWeights() is provided by Rivet.\nexample analysis\nIn order to explain the required steps in a real life situation, we will go through the implementation for the analysis published as :\n\nMeasurement of pion, kaon and proton production in proton-proton collisions at sqrt(s) = 7 TeV\nALICE internal draft : ID-183,\njournal reference : Eur.Phys.J C75 (2015) no. 5, 226,\nInspire : ID-1357424,\narXiv : arXiv:1504.00024.\n\n\n\nThe content we now want to reproduce in Rivet is the following:\n\ntransverse momentum spectra of identified pions, kaons, protons\nparticle ratios: kaons / pions, protons / pions\nFor the implementation, you can to the ALICE Rivet reference page to look up the individual ingredients you might need for your analysis.\n\nNow, we go step by step.\nidentifier and template\nFirst, we need to find the identifier for the analysis we want to implement. The analysis was published in 2015 and has the inspire ID 1357424. Thus, the identifier is ALICE_2015_I1357424.\nNow, we can create the template structure (don't forget to load the environment for Rivet and to change to an appropriate directory):\nrivet-mkanalysis ALICE_2015_I1357424\n\nAs mentioned before, the analysis can already be compiled and run (even though it does nothing useful at this stage):\nrivet-build RivetALICE_2015_I1357424.so ALICE_2015_I1357424.cc\nrivet --pwd -a ALICE_2015_I1357424 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\ninitialisation (histograms and projections)\nFirst, we book the required histograms. We need one histogram for each of the pt spectra of pions, kaons, and protons. Eventually, we also want to plot the ratios of the spectra for which a different binning was used. Therefore, we need additional temporary histograms.\nSo, we add the required member variables (in the private section):\n // histograms for spectra\n Histo1DPtr _histPtPions;\n Histo1DPtr _histPtProtons;\n Histo1DPtr _histPtKaons;\n\n // temporary histograms for ratios\n Histo1DPtr _histPtPionsR1;\n Histo1DPtr _histPtPionsR2;\n Histo1DPtr _histPtProtonsR;\n Histo1DPtr _histPtKaonsR;\n\n // scatter plots for ratios\n Scatter2DPtr _histPtKtoPi;\n Scatter2DPtr _histPtPtoPi;\n\nThen, we add the booking of the histograms (in the init method):\n // plots from the paper\n book(_histPtPions , \"d01-x01-y01\"); // pions\n book(_histPtKaons , \"d01-x01-y02\"); // kaons\n book(_histPtProtons , \"d01-x01-y03\"); // protons\n book(_histPtKtoPi , \"d02-x01-y01\"); // K to pi ratio \n book(_histPtPtoPi , \"d03-x01-y01\"); // p to pi ratio\n\n // temp histos for ratios\n book(_histPtPionsR1 , \"TMP/pT_pi1\", refData(2, 1, 1)); // pi histo compatible with more restricted kaon binning\n book(_histPtPionsR2 , \"TMP/pT_pi2\", refData(3, 1, 1)); // pi histo compatible with more restricted proton binning\n book(_histPtKaonsR , \"TMP/pT_K\", refData(2, 1, 1)); // K histo with more restricted binning\n book(_histPtProtonsR , \"TMP/pT_p\", refData(3, 1, 1)); // p histo with more restricted binning\n\nNext, we book the projections for the identified particles (also in the init method):\n const ChargedFinalState cfs(Cuts::absrap \nHere, we use the charged final state (with a rapidity cut) and will deal with the particle identification directly in the analysis code.\n NoteThis example did not use the ALICE::PrimaryParticles projection because it was implemented before this projection was introduced in Rivet. The selection of primary particles according to the ALICE definition is therefore done by hand, by looking at the particle ancestors. The code below could in principle be simplified by removing the large set of if statements if the ALICE::PrimaryParticles projection is used\nconst ALICE::PrimaryParticles& aprim = apply(event, \"APRIM\");\nfor (const Particle& p : aprim.particles()) {\n ...\n}\n\nWe did not modify this tutorial to reflect the actual code for this analysis as in Rivet.\n\nanalysis\nHere, we just use the previously declared projection to loop over all the charged particles in the selected rapidity range and to fill the histograms. \nNote: We exclude feed-down from particles decaying weakly into ฯ, K, p:\n const ChargedFinalState& cfs = apply(event, \"CFS\");\n for (const Particle& p : cfs.particles()) {\n // protections against mc generators decaying long-lived particles\n if ( !(p.hasAncestor(310) || p.hasAncestor(-310) || // K0s\n p.hasAncestor(130) || p.hasAncestor(-130) || // K0l\n p.hasAncestor(3322) || p.hasAncestor(-3322) || // Xi0\n p.hasAncestor(3122) || p.hasAncestor(-3122) || // Lambda\n p.hasAncestor(3222) || p.hasAncestor(-3222) || // Sigma+/-\n p.hasAncestor(3312) || p.hasAncestor(-3312) || // Xi-/+ \n p.hasAncestor(3334) || p.hasAncestor(-3334) )) // Omega-/+ \n { \n switch (abs(p.pid())) {\n case 211: // pi+\n _histPtPions->fill(p.pT()/GeV);\n _histPtPionsR1->fill(p.pT()/GeV);\n _histPtPionsR2->fill(p.pT()/GeV);\n break;\n case 2212: // proton\n _histPtProtons->fill(p.pT()/GeV);\n _histPtProtonsR->fill(p.pT()/GeV);\n break;\n case 321: // K+\n _histPtKaons->fill(p.pT()/GeV);\n _histPtKaonsR->fill(p.pT()/GeV);\n break;\n } // particle switch\n } // primary pi, K, p only\n } // particle loop\n\nfinalise\nIn the end, we build the particle ratios to pions (K/ฯ and P/ฯ) and normalize the histograms in order to show 1/Nev dยฒN/dpt dy event-normalised spectra :\n divide(_histPtKaonsR, _histPtPionsR1, _histPtKtoPi);\n divide(_histPtProtonsR, _histPtPionsR2, _histPtPtoPi);\n\n scale(_histPtPions, 1./sumOfWeights());\n scale(_histPtProtons, 1./sumOfWeights());\n scale(_histPtKaons, 1./sumOfWeights());\n\ntry your new analysis\nNow, try and run the analysis on the test file:\nrivet-buildplugin Rivet_test.so ALICE_2015_I1357424.cc\nrivet --pwd -a ALICE_2015_I1357424 /eos/project/a/alipwgmm/rivet/hepmc/pythia6_pp7000.hepmc\n\nN.B.: Note the option --pwd which instructs Rivet to look for the specified analyses (also) in the current working directory.\nNext, create the plots and compare:\nrivet-mkhtml --pwd Rivet.yoda\n\n(if needed copy plots/ directory locally).\nIn case of problems, you can look at the reference implementation - but first try to sort it out yourself.\nexperiment with the analysis\nIn order to gather experience with programming Rivet plugins, it is good to experiment a bit. You can e.g. try to:\n\nreplace the projection to use particle identification\nmove the primary selection to a separate function\n...\n\n"},"rivet/hi-features.html":{"url":"rivet/hi-features.html","title":"Introduction to heavy-ion features","keywords":"","body":"Introduction to heavy-ion features\nSeveral heavy-ion features were added to the recent version of Rivet (2.7.x). The ones that will be used in this tutorial are described below. In order to get to know other, more advanced heavy-ion features go to this section.\nA lot of heavy-ion analyses require the calibration of some global event observable, e.g. centrality, thrust, etc. There might be multiple approaches on how to deal with this: using the calibration provided by the experiment together with the analysis, generating your own calibration files, or even using values provided by the generator. All mentioned solutions are already supported by Rivet. On top of that, the first two methods are supported in a form of a new kind of analyses, so called calibration analyses. They are 'dummy' analyses used to produce calibration plots that are afterwards used by the main analysis.\nCalibration analysis\nA calibration analysis is essential in case our generator does not provide some global event observable(s) required by the main analysis. Such a calibration analysis is similar to a regular one but instead of producing comparisons to the existing experimental data it produces distributions of different observables, such as impact parameter distribution. It should be pointed out that there might be multiple analyses using the same calibration analysis. An example of a calibration analysis producing a V0M multiplicity distribution and an impact parameter distribution is provided below:\n#include \n#include \n#include \n\nnamespace Rivet {\n\n /// Dummy analysis for centrality calibration in Pb-Pb at 5.02TeV\n ///\n /// @author Christian Holm Christensen \n class ALICE_2015_PBPBCentrality : public Analysis {\n public:\n\n /// Constructor \n ALICE_2015_PBPBCentrality()\n : Analysis(\"ALICE_2015_PBPBCentrality\")\n { }\n\n /// Initialize this analysis. \n void init() {\n ALICE::V0AndTrigger v0and;\n declare(v0and,\"V0-AND\");\n\n ALICE::V0MMultiplicity v0m;\n declare(v0m,\"V0M\");\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n book(_v0m, \"V0M\");\n book(_imp, \"V0M_IMP\",100,0,20);\n }\n\n\n /// Analyse a single event.\n void analyze(const Event& event) {\n // Get and fill in the impact parameter value if the information is valid.\n _imp->fill(apply(event, \"HepMC\").impact_parameter());\n\n // Check if we have any hit in either V0-A or -C. If not, the\n // event is not selected and we get out.\n if (!apply(event,\"V0-AND\")()) return;\n\n // Fill in the V0 multiplicity for this event\n _v0m->fill(apply(event,\"V0M\")());\n }\n\n\n /// Finalize this analysis\n void finalize() {\n _v0m->normalize();\n _imp->normalize();\n }\n\n /// The distribution of V0M multiplicity\n Histo1DPtr _v0m;\n /// The distribution of impact parameters\n Histo1DPtr _imp;\n\n };\n\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2015_PBPBCentrality);\n\n}\n\nThis calibration analysis can be run in the same way as any other analysis:\nrivet -a ALICE_2015_PBPBCentrality -o calibration.yoda /path/to/generator.hepmc\nThis will produce the calibration plots and save them to calibration.yoda to use in the future. Once this is done we can proceed to the next step.\nSelecting calibration method\nAny analysis can load yoda files from calibration analysis assuming it contains the necessary information about the calibration methods. Possible options that allow the selection of the calibratino method are the following:\n\nREF (default): get calibration histogram from reference data\nGEN: get generated calibration histogram\nIMP: get impact parameter calibration histogram\nUSR: get user-defined calibration histogram\nRAW: get generated centrality (available only with HepMC3)\n\nThe information about possible methods for a particular analysis is stored in the .info file of this analysis. An example of how an .info file may look like is provided below:\n[...]\nOptions:\n - cent=REF,GEN,IMP,USR\nBeams: [Pb, Pb] # PDG of lead ion\nEnergies: [574080] # This is _total_ energy of beams, so this becomes 208*2760=574080\n[...]\nPreloading calibration files\nIn order to run an analysis with preloading a calibration file one needs to use the '-p' flag (see rivet --help) to provide the path to the calibration .yoda file and choose a method of calibration by adding ':var=METHOD' after the name of the analysis. This will look something like that:\nrivet -a ALICE__I:cent=GEN -p /path/to/calibration.yoda /path/to/generator.hepmc\nThis means that Rivet will run our selected analysis with an option GEN (generated calibration histogram) for the centrality calibration using the plots stored in calibration.yoda file. In case of not specifying the calibration method, Rivet will try to access the reference calibration file - if it was not provided with the calibration analysis the run will fail. Next section will cover how to access and use the centrality value inside the main analysis.\nExtracting centrality\nPreloading and selecting the method of calibration of centrality gives us access to the centrality estimator inside our main analysis. This is done in the form of a special projection class CentralityProjection. It allows an analysis to cut on percentiles of single event quantities preloaded (or supplied by the experiment) from a histogram. In order to use it one needs to declare it in the init function:\nvoid init () {\n [...]\n // Declare centrality projection for centrality estimation\n const CentralityProjection cp = declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n [...]\n}\n\nThen, one can use it to extract centrality value in the analyze function like this:\nconst CentralityProjection& centrProj = apply(event, \"V0M\");\ndouble centr = centrProj();\n\nThis gives us a value of centrality as a percentage and it can be used to do whatever one wants to do with it: fill the histogram as a function of centrality, fill the histograms for different centrality ranges, remove events with particular centrality, etc. A full example of an analysis using centrality is provided below:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Tools/Cuts.hh\"\n#include \"Rivet/Projections/SingleValueProjection.hh\"\n#include \"Rivet/Tools/AliceCommon.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/HepMCHeavyIon.hh\"\n\nnamespace Rivet {\n\n /// @brief ALICE PbPb at 2.76 TeV multiplicity at mid-rapidity\n class ALICE_2010_I880049 : public Analysis { \n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2010_I880049);\n\n /// @name Analysis methods\n //@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Declare centrality projection\n declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n\n // Trigger projections\n declare(ChargedFinalState((Cuts::eta > 2.8 && Cuts::eta 0.1*GeV), \"VZERO1\");\n declare(ChargedFinalState((Cuts::eta > -3.7 && Cuts::eta 0.1*GeV), \"VZERO2\");\n declare(ChargedFinalState(Cuts::abseta 0.15*GeV),\n \"SPD\");\n\n // Charged, primary particles with |eta| 50 MeV\n declare(ALICE::PrimaryParticles(Cuts::abseta 50*MeV && Cuts::abscharge > 0), \"APRIM\");\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n // Histograms and variables initialization\n book(_histNchVsCentr, 1, 1, 1);\n book(_histNpartVsCentr, 1, 1, 2);\n\n }\n\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Charged, primary particles with at least pT = 50 MeV\n // in eta range of |eta| (event,\"APRIM\").particles();\n\n // Trigger projections\n const ChargedFinalState& vz1 =\n applyProjection(event,\"VZERO1\");\n const ChargedFinalState& vz2 =\n applyProjection(event,\"VZERO2\");\n const ChargedFinalState& spd =\n applyProjection(event,\"SPD\");\n int fwdTrig = (vz1.particles().size() > 0 ? 1 : 0);\n int bwdTrig = (vz2.particles().size() > 0 ? 1 : 0);\n int cTrig = (spd.particles().size() > 0 ? 1 : 0);\n\n if (fwdTrig + bwdTrig + cTrig (event, \"V0M\");\n double centr = centrProj();\n if (centr > 80) vetoEvent;\n // Calculate number of charged particles and fill histogram\n double nch = chargedParticles.size();\n _histNchVsCentr->fill(centr, nch);\n\n // Attempt to extract Npart form GenEvent.\n if (event.genEvent()->heavy_ion()) {\n const HepMCHeavyIon & hi = apply(event, \"HepMC\");\n _histNpartVsCentr->fill(centr, hi.Npart_proj() + hi.Npart_targ());\n }\n }\n\n\n /// Normalise histograms etc., after the run\n //void finalize() { }\n\n //@}\n\n\n private:\n\n /// @name Histograms\n //@{\n Profile1DPtr _histNchVsCentr;\n Profile1DPtr _histNpartVsCentr;\n //@}\n\n };\n\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2010_I880049);\n\n}\n\nRun an example\nWe can now try to run an aleady installed Rivet software with an already existing example analysis with an already existing .hepmc file and (optionally) .yoda calibration file. In order to do that follow the steps described below.\nLog in to your lxplus account (check that you have an access to lxplus here):\nssh @lxplus.cern.ch\nAfter logging in you can enter the environment as follows:\nalienv enter Rivet\nThis will load all the environment required for Rivet. The following command should prompt us that we are going to use Rivet version 3.1.1:\nrivet --version\nLet's create a directory for our results:\nmkdir /path/to/rivet-hi-tutorial\ncd /path/to/rivet-hi-tutorial\nNow, as an example we are going to use ALICE_2010_I880049 as our main analysis together with the calibration analysis ALICE_2015_PBPBCentrality. You can list available ALICE analyses and check that they are available to use by typing:\nrivet --list-analyses | grep ALICE_\nWe will use an already generated .hepmc file that contains some events from EPOS-LHC for Pb-Pb beam at 2.76 TeV, which corresponds to our analysis. This file is located here: /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nFirst, we need to run our calibration analysis. Let's assume that our output files will be saved as /path/to/rivet-hi-tutorial/calibration.yoda\nrivet -a ALICE_2015_PBPBCentrality -o /path/to/rivet-hi-tutorial/calibration.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nThis will produce our calibration plots (beware that this might take some time). In case of any problems with generating these plots you can use already generated ones from here: /eos/project/a/alipwgmm/rivet/yoda/calibration_epos_PbPb2760.yoda\nNext step is to run the main analysis. Let's choose for example generated V0M multiplicity distribution as calibration method. We will use the same .hepmc file as we used for calibration (it doesn't have to be the same) and run Rivet again:\nrivet -a ALICE_2010_I880049:cent=GEN -p /path/to/rivet-hi-tutorial/calibration.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nIn case you want to use an already generated calibration file instead, you can try:\nrivet -a ALICE_2010_I880049:cent=GEN -p /eos/project/a/alipwgmm/rivet/yoda/calibration_epos_PbPb2760.yoda /eos/project/a/alipwgmm/rivet/hepmc/epos_PbPb2760.hepmc\nAgain, this might take some time. After it's done, you can create the plots like that:\nrivet-mkhtml Rivet.yoda\n"},"rivet/reference-manual.html":{"url":"rivet/reference-manual.html","title":"Reference manual for Rivet in ALICE","keywords":"","body":"Reference manual for Rivet in ALICE\nBooking histograms/profiles\nThere are several ways to book a histogram:\n\ncorresponding to HepData_hist = bookHisto1D(\"d01-x01-y01\");\n\n\nre-using properties from HepData_hist = bookHisto1D(\"TMP/test\", refData(1, 1, 1));\n\n\nmanual_hist = bookHisto1D(\"pt_h\", 10, 0., 20., \"final state particles\", \"$p_\\\\perp$\", \"counts\");\n_prof = bookProfile1D(\"cos2phi_pt_h\", 10, 0., 20.);\n\n\n\nBooking projections\nparticle level\nIn order to select all final state particles in a given rapidity range:\n const FinalState fs(-_etamax, _etamax);\n addProjection(fs, \"FS\");\n\nor if you want to constrain to charged particles:\n const ChargedFinalState cfs(-_etamax, _etamax);\n addProjection(cfs, \"CFS\");\n\nYou can further add a minimum transverse momentum and particle identification:\n IdentifiedFinalState pionfs(-_etamax, _etamax, 0.*GeV);\n pionfs.acceptId(111);\n addProjection(pionfs, \"PIONFS\");\n\nderived projections\nYou can also add projections which are derived from a final state, e.g. for multiplicity:\n addProjection(Multiplicity(fs), \"Mult\");\n\nor for thrust:\n addProjection(Thrust(fs), \"Thrust\");\n\njets\nIn order to add a projection for jets, you first have to add (or re-use) a particle-level projection which serves as input to a jet finder. You can use the jet finders provided with the FastJet package.\n const FinalState fs_jet(-_etamax - _jet_r, _etamax + _jet_r);\n addProjection(fs_jet, \"FS_JET\");\n FastJets fj02(fs_jet, FastJets::ANTIKT, _jet_r);\n fj02.useInvisibles();\n addProjection(fj02, \"Jets02\");\n\nand more ...\nThe list of basic projections can be found under the Hepforge page for Rivet (see References).\nNormalisation\nYou can normalize a given histogram to unity:\n normalize(_h_sin2phi);\n\nYou can normalize to the number of events:\n scale(_h_stat, 1. / sumOfWeights());\n\nor to cross section:\n scale(_h_stat, crossSection() / sumOfWeights());\n\nYou might have to account for the considered phase space:\n const double fac = crossSection() / (millibarn * sumOfWeights() * 2 * pi * 2 * _etamax);\n scale(_h_pt_jet02, fac);\n\n"},"rivet/publishing-procedures.html":{"url":"rivet/publishing-procedures.html","title":"Procedures for publishing Rivet analyses","keywords":"","body":"Procedures for publishing Rivet analyses\nAs Rivet analyses will be published for the ALICE collaboration, they will have to undergo approval. The exact rules will still have to be defined, here we outline what we have in mind:\nValidation\nAll analyses contributed to Rivet must be shown to actually work by comparing to a (sufficiently large) Monte Carlo sample - this is also required by the Rivet author. For ALICE, we have to distinguish the cases of\n\nnew analysis\nRivet validation/approval can happen together with paper approval\n\n\nalready published analysis:\nneed to ensure to reproduce MC comparisons from published paper\nseparate validation/approval of Rivet analysis (t.b.d., could be by PB/PF)\n\n\n\nSubmission of analysis\nThe contributions to Rivet from the LHC experiments are organized through contact persons. For ALICE this is channeled through PAG-MC, i.e. after approval the analysis will be submitted centrally to the Rivet repository.\n"},"rivet/advanced-topics.html":{"url":"rivet/advanced-topics.html","title":"Advanced topics","keywords":"","body":"Advanced topics (installations)\nInstalling Rivet locally\nIf beyond CVMFS deployment (lxplus, Grid nodes), you wish to have your own environment lcoally, note that Rivet can be installed using aliBuild (analogous to AliPhysics). \nIt can be done :\n\nin your local computer natively (beware the difficulties associated with software dependencies...) \nunder alidock (a priori, smoother, but note the potential LaTeX dependencies of Rivet (See alidock/issue-145 to have custom docker image).\n\nAssuming you have followed the instructions to install AliPhysics in a repository ~/alice, you can run:\ncd ~/alice\naliBuild build Rivet\nThis will build and install Rivet as well as its dependencies (2019/10/18):\n\nPython-modules\nboost\nGMP\nCMake\nGSL\nYODA, histogramming\nMPFR\nHepMC, output format for generators, input for Rivet analysis\ncgal\nfastjet\nRivet\n\nSubsequently, you can setup the environment to use Rivet by:\nalienv enter Rivet/latest-ali-master\nThen, you can use Rivet in the same way as explained above for the installation from cvmfs. \nInstalling MC generators locally\nNote however that the above instructions just provide you with Rivet and Yoda basically but do not include the various generators themselves...\nUnder CVMFS, you will typically find generators that are centrally installed :\n\nAMPT, \nCRMC (= EPOS-LHC, 2012), \nDPMJET, \nEPOS-3.111 (2015), \nFONLL, \nHerwig-7, \nJETSCAPE-3\nJEWEL-2,\nPOWHEG, \n(Rivet-3.x),\nSHERPA-2, \nTherminator2, \n(aligenmc),\nPYTHIA-6.4, \nPYTHIA-8.2\n\nand several utilities coming along (Sacrifice for Pythia, ThePEG for Herwig, Agile for fortran MC, LHAPDF sets, ...).\nThe version of the generators as well as their dependencies naturally evolve with time and should normally be managed accordingly in ALICE.\nSuch MC generators available in ALICE are encompassed into the bundle AliGenerators.\nOne can find its constituents under https://alimonitor.cern.ch/packages, take for instance AliGenerators::v20190924-1.\nSuch a bundle can also be built locally with aliBuild and is managed via the recipealidist/aligenerators.sh and alidist/defaults-pwgmmtest.sh. Such a meta-recipe relies on the recipes of the individual generators alidist/[generator.sh].\ncd ~/alice\naliBuild build AliGenerators --debug --defaults generators -j 6\n"},"rivet/advanced-hi-features.html":{"url":"rivet/advanced-hi-features.html","title":"Advanced heavy-ion features","keywords":"","body":"Advanced heavy-ion feratures\nThis section covers more advanced heavy-ion features introduced in Rivet version 2.7.0+. It explains how event mixing is implemented in Rivet and how to use it, as well as it presents the idea of reentrant finalize for analyses which require more than one beam and/or energy within the same analysis.\nPlease follow the basic tutorial of implementing a Rivet analysis here and a section covering basic heavy-ion features here first before going into this section.\nPostprocessing with reentrant finalize\nPostprocessing is a method that enables to merge results coming from different Rivet runs. This is useful for analyses which require different beams and/or energies to obtain final results, but also is useful when one wants to simply increase the statistics by merging multiple runs for the same beam/energy. Note, that such an analysis must be implemented in a certain way to allow proper running for all modes, so one should take great care when writing it.\nIn case of running an analysis for different beams/energies, first step is to declare them in the .info file like this:\n[...]\nBeams: [[p, p], [Pb, Pb]]\n# This is _total_ energy of beams, so this becomes 208*2760=574080\nEnergies: [2760, 574080]\n[...]\nThen, inside the analysis' init function, one should declare objects for each beam/energy separately, e.g.:\nvoid init() {\n // Initialize PbPb objects\n book(_histNch, 1, 1, 1);\n book(_counterSOW, \"counter.pbpb\"); // Sum of weights counter for PbPb\n book(_counterNcoll, \"counter.ncoll\"); // Ncoll counter for PbPb\n // Initialize pp objects\n std::string namePP = _mkAxisCode(1, 1, 1) + \"-pp\";\n book(_histNchPP, namePP, refData(1, 1, 1));\n book(_counterSOWPP, \"counter.pp\"); // Sum of weights counter for pp\n // Book ratios, to be used in finalize\n book(_histRAA, 16, 1, 1);\n [...]\n}\n\nSill in the analyze method, one can check the beam type and assign the value to a variable (bool isHI, in this case) depending on the beam type\nconst ParticlePair& beam = beams();\nif (beam.first.pid() == PID::PROTON && beam.second.pid() == PID::PROTON) isHI = false;\nelse if (beam.first.pid() == PID::LEAD && beam.second.pid() == PID::LEAD) isHI = true;\nelse {\n MSG_ERROR(\"Beam error (found)!\");\n return;\n}\n\nIn the analyze method, one can then use the information gathered about the beam type to steer the analysis as required\nif (isHI) {\n const HepMC::HeavyIon* hi = event.genEvent()->heavy_ion();\n if (!hi.ok()) {\n MSG_WARNING(\"HEPMC Heavy ion container needed for this analysis, but not \"\n \"found for this event. Skipping.\");\n vetoEvent;\n }\n // process PbPb event, fill PbPb histograms\n}\nelse {\n // process pp event, fill pp histograms\n}\n\nFinally, the regular finalize method is called, but in case we have entries in the histograms for both beam types, we do an additional step of dividing them one by another to create R_AA plot:\nvoid finalize() {\n // Regular finalize, scaling, etc.\n [...]\n\n // Postprocessing of the histograms in case there are\n // entries in histograms for both beam types\n if (_histNchPP->numEntries() > 0 && _histNch->numEntries() > 0) {\n // Initialize and fill R_AA histograms\n divide(_histNch, _histNchPP, _histRAA);\n }\n}\n\nIn order to run an analysis in the postprocessing mode one should run an analysis for every beam/energy combination and then use the rivet-merge script with the output files from the previous runs provided as parameters (check rivet-merge --help):\nrivet-merge /path/to/result1.yoda /path/to/result2.yoda ...\nThis will use the RAW histograms from you output files (check that your .yoda files contain them, they contain results from the analysis before the final scaling in the finalize method), merge them, and call finalize part of the analysis again on the merged histograms. Now, as all the histograms will be available, the finalize method will (in our case) create and fill R_AA histograms and save them to the output .yoda file containing final results.\n BewareThere is no information about beam and energy when running rivet-merge script - this should be taken into account when implementing such an analysis. Also note, that an analysis with reentrant finalize should be validated to allow running in every mode, and so in the .info file it should be marked as: Status: REENTRANT\n\nA full example of an analysis with the reentrant finalize mode enabled is provided below:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/Beam.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Tools/Cuts.hh\"\n#include \"Rivet/Projections/SingleValueProjection.hh\"\n#include \"Rivet/Tools/AliceCommon.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/HepMCHeavyIon.hh\"\n\nnamespace Rivet {\n\n /// @brief ALICE PbPb at 2.76 TeV R_AA analysis.\n class ALICE_2012_I1127497 : public Analysis {\n\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2012_I1127497);\n\n /// @name Analysis methods\n //@{\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n // Access the HepMC heavy ion info\n declare(HepMCHeavyIon(), \"HepMC\");\n\n // Declare centrality projection\n declareCentrality(ALICE::V0MMultiplicity(),\n \"ALICE_2015_PBPBCentrality\", \"V0M\", \"V0M\");\n\n // Charged, primary particles with |eta| 150 MeV\n declare(ALICE::PrimaryParticles(Cuts::abseta 150*MeV && Cuts::abscharge > 0), \"APRIM\");\n\n // Loop over all histograms\n for (size_t ihist = 0; ihist (\"beam\",\"NONE\");\n if (beamOpt != \"NONE\") {\n MSG_WARNING(\"You are using a specified beam type, instead of using what\"\n \"is provided by the generator. \"\n \"Only do this if you are completely sure what you are doing.\");\n if (beamOpt==\"PP\") isHI = false;\n else if (beamOpt==\"HI\") isHI = true;\n else {\n MSG_ERROR(\"Beam error (option)!\");\n return;\n }\n }\n else {\n const ParticlePair& beam = beams();\n if (beam.first.pid() == PID::PROTON && beam.second.pid() == PID::PROTON) isHI = false;\n else if (beam.first.pid() == PID::LEAD && beam.second.pid() == PID::LEAD)\n isHI = true;\n else {\n MSG_ERROR(\"Beam error (found)!\");\n return;\n }\n }\n }\n\n /// Perform the per-event analysis\n void analyze(const Event& event) {\n\n // Charged, primary particles with at least pT = 150 MeV\n // in eta range of |eta| (event,\"APRIM\").particlesByPt();\n\n // Check type of event.\n if ( isHI ) {\n\n const HepMCHeavyIon & hi = apply(event, \"HepMC\");\n if (!hi.ok()) {\n MSG_WARNING(\"HEPMC Heavy ion container needed for this analysis, but not \"\n \"found for this event. Skipping.\");\n vetoEvent;\n }\n // Prepare centrality projection and value\n const CentralityProjection& centrProj =\n apply(event, \"V0M\");\n double centr = centrProj();\n // Veto event for too large centralities since those are not used\n // in the analysis at all\n if ((centr 80.)) vetoEvent;\n\n // Fill PbPb histograms and add weights based on centrality value\n for (size_t ihist = 0; ihist fill();\n _counterNcoll[ihist]->fill(hi.Ncoll());\n for (const Particle& p : chargedParticles) {\n double pT = p.pT()/GeV;\n if (pT binAt(pT).xMid();\n _histNch[PBPB][ihist]->fill(pT, 1/pTAtBinCenter);\n }\n }\n }\n }\n\n }\n else {\n\n // Fill all pp histograms and add weights\n for (size_t ihist = 0; ihist fill();\n for (const Particle& p : chargedParticles) {\n double pT = p.pT()/GeV;\n if (pT binAt(pT).xMid();\n _histNch[PP][ihist]->fill(pT, 1/pTAtBinCenter);\n }\n }\n }\n\n }\n\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n\n // Right scaling of the histograms with their individual weights.\n for (size_t itype = 0; itype sumW() > 0.) {\n scale(_histNch[itype][ihist],\n (1. / _counterSOW[itype][ihist]->sumW() / 2. / M_PI));\n }\n }\n }\n\n // Postprocessing of the histograms\n for (size_t ihist = 0; ihist numEntries() > 0 && _histNch[PBPB][ihist]->numEntries() > 0) {\n // Initialize and fill R_AA histograms\n divide(_histNch[PBPB][ihist], _histNch[PP][ihist], _histRAA[ihist]);\n // Scale by Ncoll. Unfortunately some generators does not provide\n // Ncoll value (eg. JEWEL), so the following scaling will be done\n // only if there are entries in the counters\n double ncoll = _counterNcoll[ihist]->sumW();\n double sow = _counterSOW[PBPB][ihist]->sumW();\n if (ncoll > 1e-6 && sow > 1e-6)\n _histRAA[ihist]->scaleY(1. / (ncoll / sow));\n\n }\n }\n\n }\n\n //@}\n\n private:\n\n bool isHI;\n static const int NHISTOS = 15;\n static const int EVENT_TYPES = 2;\n static const int PP = 0;\n static const int PBPB = 1;\n\n /// @name Histograms\n //@{\n Histo1DPtr _histNch[EVENT_TYPES][NHISTOS];\n CounterPtr _counterSOW[EVENT_TYPES][NHISTOS];\n CounterPtr _counterNcoll[NHISTOS];\n Scatter2DPtr _histRAA[NHISTOS];\n //@}\n\n std::vector> _centrRegions;\n\n };\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2012_I1127497);\n\n\n}\n\nEvent mixing\n WARNINGThis feature is still under development and its usage might change in the coming versions of Rivet. Description of this procedure was prepared for Rivet version 2.7.2.\n\nEvent mixing is a procedure that enables to project out an event mixed of several events. In Rivet it is implemented in a form of a projection class called EventMixingProjection. It is based on a mixing observable provided as an input to define what should qualify as a mixable event, where the mixing observable can be defined as number of final state particles, centrality, event plane angle, etc. It contains a buffer that is filled with events over the runtime. This buffer can be used within an analysis to perform required operations. A declaration of an event mixing projection looks like this:\nvoid init () {\n [...]\n // Charged final state to manage the mixing observable\n ChargedFinalState cfsMult(Cuts::abseta pTmin*GeV);\n addProjection(pp,\"APRIM\");\n // The event mixing projection\n declare(EventMixingFinalState(&cfsMult, pp, 5, 0, 100, 10),\"EVM\");\n\n [...]\n}\n\nIn this case the first parameter of the event mixing projection defines a mixing observable. The second parameter is used to project out an event that is added to the buffer. The other parameters are: number of events to mix, minimal and maximal value of the mixing observable, and number of bins for that observable (so that for each bin there is a separate buffer). One can use it in the analyze method like this:\nvoid analyze(const Event& event) {\n [...]\n const EventMixingFinalState& evm = applyProjection(event, \"EVM\");\n // Test if we have enough mixing events available to continue.\n if (!evm.hasMixingEvents()) return;\n // Loop over the particles in the mixing buffer\n for(const Particle& pMix : evm.particles()){\n [...]\n }\n [...]\n}\n\nThis enables to check if we already have enough events in our buffer (method hasMixingEvents will return false in case the number of events in the buffer is lower than requested) and gives us access to the mixing buffer within the analysis. Note, that in this case first few events will be skipped as we require our buffers to be filled before going further. Full example can be found here:\n// -*- C++ -*-\n#include \"Rivet/Analysis.hh\"\n#include \"Rivet/Projections/AliceCommon.hh\"\n#include \"Rivet/Projections/PrimaryParticles.hh\"\n#include \"Rivet/Projections/ChargedFinalState.hh\"\n#include \"Rivet/Projections/EventMixingFinalState.hh\"\nnamespace Rivet {\n\n\n /// @brief Correlations of identified particles in pp.\n /// Also showcasing use of EventMixingFinalState.\n\n class ALICE_2016_I1507157 : public Analysis {\n public:\n\n /// Constructor\n DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2016_I1507157);\n\n\n /// @name Analysis methods\n //@{\n\n /// @brief Calculate angular distance between particles.\n double phaseDif(double a1, double a2){\n double dif = a1 - a2;\n while (dif 3*M_PI/2)\n dif -= 2*M_PI;\n return dif;\n }\n\n\n /// Book histograms and initialise projections before the run\n void init() {\n\n double etamax = 0.8;\n double pTmin = 0.5; // GeV \n\n // Trigger\n declare(ALICE::V0AndTrigger(), \"V0-AND\");\n // Charged tracks used to manage the mixing observable.\n ChargedFinalState cfsMult(Cuts::abseta pTmin*GeV);\n addProjection(pp,\"APRIM\");\n\n // The event mixing projection\n declare(EventMixingFinalState(&cfsMult, pp, 5, 0, 100, 10),\"EVM\");\n // The particle pairs.\n pid = {{211, -211}, {321, -321}, {2212, -2212}, {3122, -3122}, {211, 211},\n {321, 321}, {2212, 2212}, {3122, 3122}, {2212, 3122}, {2212, -3122}};\n // The associated histograms in the data file.\n vector refdata = {\"d04-x01-y01\",\"d04-x01-y02\",\"d04-x01-y03\",\n \"d06-x01-y02\",\"d05-x01-y01\",\"d05-x01-y02\",\"d05-x01-y03\",\"d06-x01-y01\",\n \"d01-x01-y02\",\"d02-x01-y02\"};\n for (int i = 0, N = refdata.size(); i (event, \"V0-AND\")()) return;\n // The projections\n const PrimaryParticles& pp = \n applyProjection(event,\"APRIM\");\n const EventMixingFinalState& evm = \n applyProjection(event, \"EVM\");\n\n // Test if we have enough mixing events available to continue.\n if (!evm.hasMixingEvents()) return;\n\n for(const Particle& p1 : pp.particles()) {\n // Start by doing the signal distributions\n for(const Particle& p2 : pp.particles()) {\n if(isSame(p1,p2))\n continue;\n double dEta = abs(p1.eta() - p2.eta());\n double dPhi = phaseDif(p1.phi(), p2.phi());\n if(dEta 0);\n if (samesign && ((pid1 == p1.pid() && pid2 == p2.pid()) || \n (pid1 == -p1.pid() && pid2 == -p2.pid()))) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n if (!samesign && abs(pid1) == abs(pid2) &&\n pid1 == p1.pid() && pid2 == p2.pid()) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n if (!samesign && abs(pid1) != abs(pid2) && \n ( (pid1 == p1.pid() && pid2 == p2.pid()) ||\n (pid2 == p1.pid() && pid1 == p2.pid()) ) ) {\n signal[i]->fill(dPhi, weight);\n nsp[i] += 1.0;\n }\n }\n }\n }\n // Then do the background distribution\n for(const Particle& pMix : evm.particles()){\n double dEta = abs(p1.eta() - pMix.eta());\n double dPhi = phaseDif(p1.phi(), pMix.phi());\n if(dEta 0);\n if (samesign && ((pid1 == p1.pid() && pid2 == pMix.pid()) || \n (pid1 == -p1.pid() && pid2 == -pMix.pid()))) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n if (!samesign && abs(pid1) == abs(pid2) &&\n pid1 == p1.pid() && pid2 == pMix.pid()) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n if (!samesign && abs(pid1) != abs(pid2) && \n ( (pid1 == p1.pid() && pid2 == pMix.pid()) ||\n (pid2 == p1.pid() && pid1 == pMix.pid()) ) ) {\n background[i]->fill(dPhi, weight);\n nmp[i] += 1.0;\n }\n }\n }\n }\n }\n }\n\n\n /// Normalise histograms etc., after the run\n void finalize() {\n for (int i = 0, N = pid.size(); i scaleW(sc);\n divide(signal[i],background[i],ratio[i]);\n }\n }\n\n //@}\n\n\n /// @name Histograms\n //@{\n vector > pid;\n vector signal;\n vector background;\n vector ratio;\n vector nsp;\n vector nmp;\n\n //@}\n\n };\n\n // The hook for the plugin system\n DECLARE_RIVET_PLUGIN(ALICE_2016_I1507157);\n\n}\n\n"},"rivet/coding-conventions.html":{"url":"rivet/coding-conventions.html","title":"Coding conventions for Rivet plugins","keywords":"","body":"Coding conventions for Rivet plugins\nSome inventory is made in the Rivet webpage: Rivet - Coding Style\n BewareCoding conventions for Rivet plugins are different than those for AliRoot/AliPhysics!\n\n"},"rivet/references.html":{"url":"rivet/references.html","title":"References","keywords":"","body":"References\nRivet official\n\nRivet user manual: arXiv:1003:0694\n\nRivet wiki: writing an analysis\n\nRivet tutorial documentation (GitLab) GitLab:HepCedar-Tutorials\n\n\"Confronting Experimental Data with Heavy-Ion Models: Rivet for Heavy Ions\" arXiv:2001.10737\n\n\"Robust Independent Validation of Experiment and Theory: Rivet version 3\" arXiv:1912.05451\n\n\nALICE Rivet\n\nRivet & ALICE (conceptual overview) (2016) Jochen Klein : Indico.infn:10971\n\nALICE Rivet hackathon workshop 2020-11 : Indico.cern:969010\n\n\nALICE building framework\nalibuild primer\nalibuild reference\n"},"CONTRIBUTING.html":{"url":"CONTRIBUTING.html","title":"Contributing","keywords":"","body":"Welcome to the ALICE Analysis Tutorial documentation\n\nThis is a community-contributed place where we collect all our documentation. Every ALICE member can\ncontribute, and the Analysis Tutorial Committee will review every contribution.\nWhere can I see the documentation online?\nDocumentation is published on GitHub pages at the following address:\n\nhttps://alice-doc.github.io/alice-analysis-tutorial/\n\nHow can I contribute to the documentation?\nFirst off you need a GitHub account. Fork the\nalice-doc/alice-analysis-tutorial repository, then clone it to your\nlaptop:\ngit clone https://github.com//alice-analysis-tutorial\ncd alice-analysis-tutorial/\ngit remote add upstream https://github.com/alice-doc/alice-analysis-tutorial\n\nDocumentation is written in Markdown and it\nis generated using GitBook. You need to install GitBook first. GitBook\nis a NodeJS package, meaning that you need npm to install it. You can get npm easily.\nOn Ubuntu:\nsudo apt install npm\n\nOn macOS (assuming you have Homebrew):\nbrew install npm\n\nOn CentOS 7 (you need EPEL enabled):\nsudo yum install npm\n\nOnce npm is installed, you can install GitBook:\nsudo npm install -g gitbook-cli@2.3.0\n\nDo not use sudo on macOS.\nOnce GitBook is installed, you should find it in your $PATH, check it with:\ntype gitbook\n\nTo preview the documentation pages locally while you are editing them, move to the repository's root\ndirectory and run:\ncd alice-analysis-tutorial/\nmake serve\n\nThe command will not exit and a local website will be visible at the following address:\n\nhttp://localhost:4000\n\nThe website uses GitBook. Editing the pages using your favorite text\neditor: whenever you save, the page currently opened in your local preview will be refreshed\nautomatically.\nWhen you are happy with your modifications, commit them, push them to your repository and open a\npull request, for instance:\ngit commit -a -m 'I am happy with my doc'\ngit push origin\n\nthen navigate to your GitHub repository online to open a pull request.\n"}}}
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diff --git a/start/cert.html b/start/cert.html
index dc138a05..1d1342e1 100644
--- a/start/cert.html
+++ b/start/cert.html
@@ -246,6 +246,19 @@
+
+
+
either alienv or the alien-token-* commands available in case you have never done it.
The alien-token-init command will ask you for a password. This is the last password you have used
when you have converted your .p12 certificate into two .pem files.
-
Creating JAliEn and AliEn tokens
Note that the new JAliEn Grid clients automatically create tokens, while AliEn-ROOT-Legacy (ROOT5) requires running alien-token-init manually.
+
Creating JAliEn and AliEn tokens
Note that the new JAliEn Grid clients automatically create tokens, while AliEn-ROOT-Legacy (ROOT5) requires running alien-token-init manually.
There is alien-token-init for JAliEn, and you can use it to test your credentials or (re)create tokens manually.
@@ -969,7 +982,7 @@
No results matching "
var gitbook = gitbook || [];
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