Contents¶
Home¶
AlphaTwirl is a python library that loops over event data and summarizes them into multi-dimensional 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. Multi-dimensional 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¶
loop.Collector(resultsCombinationMethod[, …]) |
This class collects results, i.e., this class combines results of readers and deliver them. |
loop.CollectorComposite(*args, **kwargs) |
A composite of collectors. |
loop.EventLoop(build_events, reader[, name]) |
An event loop |
loop.EventLoopProgressReportWriter |
A progress report writer of an event loop |
loop.EventLoopRunner() |
This class runs instances of EventLoop and keeps the results. |
loop.EventsInDatasetReader(eventLoopRunner, …) |
This class manages objects involved in reading events in data sets. |
loop.MPEventLoopRunner(communicationChannel) |
This class (concurrently) runs instances of EventLoop. |
loop.ReaderComposite() |
A composite of event readers” |