| 32 | | {{{#!python |
| 33 | | hello = lambda: "world" |
| | 34 | {{{ |
| | 35 | class AnalysisEvent(ROOT.TChain) |
| | 36 | | |
| | 37 | | __init__(self, inputFiles='', maxEvents=0) |
| | 38 | | Initialize the AnalysisEvent like a standard Event, plus additional features. |
| | 39 | | |
| | 40 | | addCollection(self, name, inputTag) |
| | 41 | | Register an event collection as used by the analysis. |
| | 42 | | Example: addCollection("myjets","jets") |
| | 43 | | Note that the direct access to the branch is still possible but unsafe. |
| | 44 | | |
| | 45 | | removeCollection(self, name) |
| | 46 | | Forget about the named event collection. |
| | 47 | | This method will delete both the product from the cache (if any) and the definition. |
| | 48 | | To simply clear the cache, use "del event.name" instead. |
| | 49 | | |
| | 50 | | getCollection(self, name) |
| | 51 | | Retrieve the event product or return the cached collection. |
| | 52 | | Note that the prefered way to get the collection is instead to access the "event.name" attribute. |
| | 53 | | |
| | 54 | | addProducer(self, name, producer, **kwargs) |
| | 55 | | Register a producer to create new high-level analysis objects. |
| | 56 | | |
| | 57 | | removeProducer(self, name) |
| | 58 | | Forget about the producer. |
| | 59 | | This method will delete both the product from the cache (if any) and the producer. |
| | 60 | | To simply clear the cache, use "del event.name" instead. |
| | 61 | | |
| | 62 | | addWeight(self, name, weightClass) |
| | 63 | | Declare a new class (engine) to compute the weights. |
| | 64 | | weightClass must have a weight() method returning a float. |
| | 65 | | |
| | 66 | | delWeight(self, name) |
| | 67 | | Remove one weight engine from the internal list. |
| | 68 | | |
| | 69 | | weight(self, weightList=None, **kwargs) |
| | 70 | | Return the event weight. Arguments: |
| | 71 | | * weightList is the list of engines to use, as a list of strings. |
| | 72 | | Default: all defined engines. |
| | 73 | | * the other named arguments are forwarded to the engines. |
| | 74 | | The output is the product of the selected individual weights. |
| | 75 | | |
| | 76 | | event(self) |
| | 77 | | Event number |
| | 78 | | |
| | 79 | | to(self, event) |
| | 80 | | Jump to some event |
| | 81 | | |
| | 82 | | (...) |
| 47 | | {{{#!python |
| 48 | | hello = lambda: "world" |
| | 96 | {{{ |
| | 97 | class BaseControlPlots |
| | 98 | | |
| | 99 | | __init__(self, dir=None, purpose='generic', dataset=None, mode='plots') |
| | 100 | | Initialize the ControlPlots, creating output file if needed. If no file is given, it means it is delegated. |
| | 101 | | |
| | 102 | | add(self, *args) |
| | 103 | | Add one item to the list of products. Arguments are as for TH1F. |
| | 104 | | |
| | 105 | | beginJob(self) |
| | 106 | | Declare histograms, and for derived classes instantiate handles. Must be overloaded. |
| | 107 | | |
| | 108 | | defineCategories(self, categories) |
| | 109 | | Define the categories, given a list of names. Only works for datasets |
| | 110 | | |
| | 111 | | endJob(self) |
| | 112 | | Save and close. |
| | 113 | | |
| | 114 | | fill(self, data, weight=1.0) |
| | 115 | | Fills whatever must be filled in |
| | 116 | | |
| | 117 | | process(self, event) |
| | 118 | | Process event data to extract histogrammables. Must be overloaded. |
| | 119 | | |
| | 120 | | processEvent(self, event, weight=1.0) |
| | 121 | | process event and fill histograms |
| | 122 | | |
| | 123 | | setCategories(self, categories) |
| | 124 | | Set the categories, given a list of booleans. Only works for datasets |
| | 125 | | |
| | 126 | | (...) |
| | 155 | {{{ |
| | 156 | FUNCTIONS |
| | 157 | eventCategory(event) |
| | 158 | Check analysis requirements for various steps |
| | 159 | and return a tuple of data used to decide |
| | 160 | to what category an event belong |
| | 161 | |
| | 162 | isInCategory(category, categoryData) |
| | 163 | Check if the event enters category X, given the tuple computed by eventCategory. |
| | 164 | |
| | 165 | DATA |
| | 166 | categoryNames = [ ] |
| | 167 | }}} |
| | 168 | }}} |
| | 169 | |
| | 170 | == Steering code and Configuration file == |
| | 171 | |
| | 172 | The framework is contained in python/DelphesAnalsys. No file in that directory should ever be modified. |
| | 173 | |
| | 174 | The main script is !ControlPlots. This is a single code to generate a full set of histograms for your analysis, organized in logical groups by !ControlPlot class and by category. The same code will generate a ntuple if the proper parameter is changed in the configuration file. Internally, !ControlPlots steers the user-defined codes: event selection and control plots. |
| | 175 | |
| | 176 | !DumpEventInfo is another script that will output all the information available on a given event. |
| | 177 | |
| | 178 | All that is configured through a simple configuration script. The script used is defined via the !DelphesAnalysisCfg environment variable, or optionally via the command line in the case of !ControlPlots. The config file is where the control plot class and event selection module are declared and where the event collections, producers and weights are set. |
| | 179 | |
| | 180 | {{{ |
| | 181 | #!div style="font-size: 80%" |
| 75 | | hello = lambda: "world" |
| 76 | | }}} |
| 77 | | }}} |
| 78 | | |
| 79 | | == Steering code and Configuration file == |
| 80 | | |
| 81 | | The framework is contained in python/DelphesAnalsys. No file in that directory should ever be modified. |
| 82 | | |
| 83 | | The main script is ControlPlots. |
| 84 | | |
| 85 | | DumpEventInfo is another script that will output all the information available on a given event. |
| 86 | | |
| 87 | | All that is configured through a simple configuration script. |
| | 183 | #configuration of the ControlPlot machinery |
| | 184 | |
| | 185 | from collections import namedtuple |
| | 186 | controlPlot = namedtuple("controlPlot", ["label","module","classname","kwargs"]) |
| | 187 | eventCollection = namedtuple("eventCollection",["label","collection"]) |
| | 188 | eventProducer = namedtuple("eventProducer", ["label","module","function","kwargs"]) |
| | 189 | eventWeight = namedtuple("eventWeight", ["label","module","classname","kwargs"]) |
| | 190 | |
| | 191 | class configuration: |
| | 192 | # default I/O |
| | 193 | defaultFilename = "controlPlots" |
| | 194 | RDSname = "rds_delphes" |
| | 195 | WSname = "workspace_ras" |
| | 196 | |
| | 197 | # mode: plots or dataset |
| | 198 | runningMode = "plots" |
| | 199 | |
| | 200 | # event selection class |
| | 201 | eventSelection = "" |
| | 202 | |
| | 203 | # control plot classes |
| | 204 | controlPlots = [ ] |
| | 205 | |
| | 206 | # event content: lists of eventCollection, eventProducer, and eventWeight objects respectively. |
| | 207 | eventCollections = [ ] |
| | 208 | eventProducers = [ ] |
| | 209 | eventWeights = [ ] |
| | 210 | |
| | 211 | class eventDumpConfig: |
| | 212 | # fine-tuning of the event content for display |
| | 213 | productsToPrint = [ ] # list of product to display (use the producer label) |
| | 214 | collectionsToHide = [ ] # collections used in the analysis but not printed (use the collection label) |
| | 215 | |
| | 216 | # import the actual implementation of the configuration |
| | 217 | import os |
| | 218 | theConfig = os.getenv("DelphesAnalysisCfg") |
| | 219 | if theConfig is not None: |
| | 220 | configImplementation = __import__(os.path.splitext(theConfig)[0]) |
| | 221 | configuration = configImplementation.configuration |
| | 222 | eventDumpConfig = configImplementation.eventDumpConfig |
| | 223 | }}} |
| | 224 | }}} |
| 91 | | what should be touched to implement an example? |
| 92 | | * config.py (name given as argument of ControlPlots or set as DelphesAnalysisCfg env var. |
| 93 | | * specific EventSelection class |
| 94 | | * specific controlPlots class(es) |
| 95 | | |
| 96 | | == Examples == |
| | 228 | In order to implement an analysis, one should |
| | 229 | * implement the specific control plot class(es), with the plots that you want to see. |
| | 230 | * implement an event selection module, with the cuts that should be applied. |
| | 231 | * declare everything in the configuration file (name given as argument of ControlPlots or set as DelphesAnalysisCfg env var). |
