Contents¶
Home¶
AlphaTwirl is a python library that summarizes event data into multivariate categorical data as data frames. Event data, input to AlphaTwirl, are data with one entry (or row) for one event: for example, data in ROOT TTrees with one entry per collision event of an LHC experiment at CERN. Event data are often large—too large to be loaded in memory—because they have as many entries as events. Multivariate categorical data, the output of AlphaTwirl, have one row for one category. They are usually small—small enough to be loaded in memory—because they only have as many rows as categories. Users can, for example, import them as data frames into R and pandas, which usually load all data in memory, and can perform categorical data analyses with a rich set of data operations available in R and pandas.
API reference¶
binning¶
Binning ([boundaries, lows, ups, retvalue, …]) |
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Echo ([nextFunc, valid]) |
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Round ([width, aboundary, min, …]) |
Equal width binning |
RoundLog ([width, aboundary, min, …]) |
Binning with equal width in log scale |
loop¶
Collector (resultsCombinationMethod[, …]) |
This class collects results, i.e., this class combines results of readers and deliver them. |
CollectorComposite (**kwargs) |
A composite of collectors. |
CollectorDelegate (collector) |
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EventLoop (**kwargs) |
An event loop |
DatasetIntoEventBuildersSplitter (…[, …]) |
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EventDatasetReader (**kwargs) |
This class manages objects involved in reading events in data sets. |
EventLoopRunner () |
This class runs instances of EventLoop and keeps the results. |
MPEventLoopRunner (communicationChannel) |
This class (concurrently) runs instances of EventLoop. |
ReaderComposite ([readers]) |
A composite of event readers” |
NullCollector |
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ReaderComposite ([readers]) |
A composite of event readers” |
splitfuncs.create_files_start_length_list (files) |
determines how to split input data into chunks |
roottree¶
Branch (name, array, countarray) |
This class encloses an array.array object, which is typically used to set the address of a branch of a ROOT TTree. |
Events (tree[, maxEvents, start]) |
An iterative object for events. |
selection¶
build_selection (**kargs) |
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modules.All ([name, selections]) |
select events that meet all conditions |
modules.Any ([name, selections]) |
select events that meet any of the conditions |
modules.Not (selection[, name]) |
select events that do NOT pass the selection |
modules.AllwCount ([name, selections, collector]) |
select events that meet all conditions |
modules.AnywCount ([name, selections, collector]) |
select events that meet any of the conditions |
modules.NotwCount (selection[, name, collector]) |
select events that do NOT pass the selection |
modules.Count.Count ([selections]) |
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modules.LambdaStr.LambdaStr (lambda_str[, name]) |
select events to which a lambda returns True. |
summary¶
BackrefMultipleArrayReader (arrays, idxs_conf) |
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Count ([val, weight, contents]) |
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KeyValueComposer ([keyAttrNames, binnings, …]) |
This class composes keys and values for the event | ||
NextKeyComposer (binnings) |
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Reader (keyValComposer, summarizer[, …]) |
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Scan ([val, weight, contents]) |
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Sum ([val, weight, contents]) |
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Summarizer (Summary) |
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WeightCalculatorOne |
concurrently¶
CommunicationChannel (dropbox) |
A communication channel with workers in other processes. |
CommunicationChannel0 (**kwargs) |
A communication channel for the single process mode |
HTCondorJobSubmitter (**kwargs) |
A dispatcher that dispatches jobs to HTCondor |
MultiprocessingDropbox (**kwargs) |
A drop box for task packages. |
SubprocessRunner ([pipe]) |
An example dispatcher which runs tasks in subprocesses |
TaskPackage |
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TaskPackageDropbox (workingArea, dispatcher) |
A drop box for task packages. |
Worker |
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WorkingArea (**kwargs) |
A working area for tasks |