The current and future situation of the Midas analyzer is summarized in the
Midas code for accessing/gathering the hardware information into the Midas
Midas back end shared memory where the front end data are sent to.
Data logger collecting the midas events and storing them on a physical
logging device (Disk, Tape)
Midas client for event-by-event analysis. Incoming data can be either online
Subprocess interfacing external (remote) midas client to the centralized
data collection and database system.
Standalone physics data analyzer (CERN).
Standalone Physics data analyser (CERN).
This diagram represents the data path from the Frontend to the analyzer in
online and offline mode. Each data path is annoted with a circled number
discussed below. In all cases, the data will flow from the front end
application to the midas back end data buffers which reside in a specific
share memory for a given experiment.
(1): From the shared memory, the midas analyzer can request events directly
and process them for output to divers destination.
(2): The data logger is a specific application which stores all the data to
a storage media such as a disk or tape. This path is specific to the
creation of file.mid file format. The actual storage file in this .mid
format can be readout later on by the midas analyzer.
(3): The Midas analyzer has been developed originally for interfacing to the
PAW analyzer which uses its own shared memory segment for online display.
The analyzer can also save the data into a specific data format consistent
with PAW (HBOOK and Ntuples, extension .rz).
(4): Presently the data logger support a creation of the ROOT file format.
This file contains in the form of a Tree the midas event-by-event data. This
file is fully compatible with ROOT and therefore can be read out by the
standard ROOT application.
(5): Equivalent to the data logger, the analyzer receiving from the data
buffer or reading from a .mid file data can apply an event-by-event analysis
and on request produce a compliant ROOT file for further analysis. This
.root file can be composed of Trees as well as histograms.
(6): The possibility of ONLINE ROOT analysis has been implemented in a first
stage through the TMapFile (ROOT shared memory). While this configuration is
still in use an experiment, the intention is to deprecate it and replace it
with the data path (7).
(7): This path uses the network socket channel to transfer data out of the
analyzer to the ROOT environment. The current analyzer has a limited support
for ROOT analysis by only publishing on request the Midas analysis built in
histograms. No mean is yet implemented for Tree passing mechanism.
(8): The pass has not been yet investigated, but ROOT does provide
accessibility to external function calls which makes this option possible.
The ROOT framework will then perform dedicated event call to the main midas
data buffer using the standard midas communication scheme. The data format
translation from Midas banks to ROOT format will have to be taken care at
the user level in the ROOT environment.
Presently the Socket communication between Midas and ROOT (7) is under
revision by Stefan Ritt and René Brun. This revision will simplify the
remote access of an object such as an histogram. For the Tree itself, the
requirement would be to implement a "ring buffer" mechanism for remote tree
request. This is currently under discussion.
The path (8) has been suggested by Triumf to address small experiment setup
where only a single analyzer is required. This path minimize the DAQ
requirements by moving all the data analysis handling to the user.
The same ROOT analysis code would be applicable to a ONLINE as well as
- Necessity of publishing raw data through the network for every instance of
the remote analyzer.
- Result sharing of the analysis cannot be done yet in real time.
- No need of extra task for data translation (midas/root).
- Unique data unpacking code part of the user code.
- Less CPU requirement.
- The current necessity of the Midas shared memory for the midas analyzer to
run is a concern in particular for offline analysis where a priori no midas
- The handling of the run/analyzer parameters. Possible parameter extraction