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SwissFEL DAQ Broker: SF-DAQ Component Overview

The SwissFEL DAQ Broker Component, (sf-daq_broker, serves as the primary user entry point into SF-DAQ (sf-daq). SF-DAQ consists of several integral components, including:

Components of SF-DAQ

  1. sf_daq_buffer

    Responsible for writing/reading to/from the DetectorBuffer for Jungfrau detectors.

  2. data_api

    Retrieves data from Data-/Image- buffers, catering to BS- and Camera sources respectively.

  3. epics-buffer

    Manages storing/retrieving Epics data.

Functionalities of sf-daq_broker

The sf-daq_broker offers a range of functionalities that include:

  1. Data Retrieval

    • Accesses data from various buffers: data, image, detector, and Epics.
  2. Data Validation

    • Ensures retrieved data aligns with requested parameters.
  3. Configuration of Epics Buffers

    • Facilitates individual Epics buffer configuration for each beamline.
  4. Detector Power-On and Configuration

    • Manages the activation and setup of detectors associated with a specific beamline.
  5. Pedestal (Dark Run) Operations

    • Handles pedestal data acquisition and processing procedures.
  6. Provides ZeroMQ streams

  7. Interface to DAP Configuration

    • Provides an interface to configure the Detector Analysis Pipeline(DAP).

The utilization of sf_daq_broker grants users access to a comprehensive suite of functionalities within SF-DAQ, empowering efficient data retrieval, configuration, and management for experiments conducted at SwissFEL.

Deployment

The current deployment of sf_daq_broker at SwissFEL is executed using ansible.

Communication with sf-daq_broker

Interaction with sf_daq_broker occurs through REST API calls, extensively detailed here.

Example1

A command-line example showcasing the usage of the broker to request data retrieval is daq_client.py. To execute, Python > 3.6 and standard packages (requests, os, json) are required. Utilizing the standard PSI Python environment suffices for this purpose:

$ module load psi-python39/2021.11 

$ python daq_client.py --help
usage: daq_client.py [-h] [-p PGROUP] [-c CHANNELS_FILE] [-e EPICS_FILE] [-f FILE_DETECTORS] [-r RATE_MULTIPLICATOR]
                     [-s SCAN_STEP_FILE] [--start_pulseid START_PULSEID] [--stop_pulseid STOP_PULSEID]

simple daq client example

optional arguments:
  -h, --help            show this help message and exit
  -p PGROUP, --pgroup PGROUP
                        pgroup, example p12345
  -c CHANNELS_FILE, --channels_file CHANNELS_FILE
                        TXT file with list channels
  -e EPICS_FILE, --epics_file EPICS_FILE
                        TXT file with list of epics channels to save
  -f FILE_DETECTORS, --file_detectors FILE_DETECTORS
                        JSON file with the detector list
  -r RATE_MULTIPLICATOR, --rate_multiplicator RATE_MULTIPLICATOR
                        rate multiplicator (1(default): 100Hz, 2: 50Hz,)
  -s SCAN_STEP_FILE, --scan_step_file SCAN_STEP_FILE
                        JSON file with the scan step information
  --start_pulseid START_PULSEID
                        start pulseid
  --stop_pulseid STOP_PULSEID
                        stop pulseid

Example2

Another example presents a more start/stop-oriented data acquisition process. Alongside daq_config.py, the script client_example.py is required to run this example.

. /opt/gfa/python 3.9 # this loads proper environment with pyepics in it
$ ipython

In [1]: import client_example as client                                                                                                
In [2]: daq_client = client.BrokerClient(pgroup="p12345")                                                                                     
In [3]: daq_client.configure(channels_file="channel_list", rate_multiplicator=2, detectors_file="jf_jf01.json")                              

In [4]: daq_client.run(1000)                                                                                                
[####################] 99% Run: 2
success: run number(request_id) is 2

Directory Structure

The structure where sf-daq stores data resides primarily in the /sf/{beamline}/data/{pgroup}/raw/ directory. This structure adheres to a specific format:

  • JF_pedestals/ Contains Jungfrau pedestal files, both in raw and converted formats, along with gainMaps files for experiment-utilized detectors.

  • runXXXX/ Corresponds to the run (or scan) directory. In cases where a "user_tag" is added, the directory is named runXXXX-{user_tag}/.

    • data/ Contains files formatted based on the sf-daq request.
    • meta/ Holds JSON files with the request details for each acquisition step and a scan.json file that encapsulates the entire run/scan information.
    • logs/ Houses log files from sf-daq writers, providing information regarding corresponding data retrieval actions.
    • raw_data/ (optional) Contains raw Jungfrau files, especially if different formats from raw files were requested by sf-daq.
    • aux/ (optional) Contains additional files.

File names within each acquisition step are prefixed with acqYYYY. to denote the acquisition step number. An example directory structure for a scan with multiple acquisition steps is provided below.

run0010/
├── data
│   ├── acq0001.BSDATA.h5
│   ├── acq0001.JF01T03V01.dap
│   ├── acq0001.JF01T03V01.h5
│   ├── acq0001.JF03T01V02.dap
│   ├── acq0001.JF03T01V02.h5
│   ├── acq0001.PVDATA.h5
│   ├── acq0002.BSDATA.h5
│   ├── acq0002.JF01T03V01.dap
│   ├── acq0002.JF01T03V01.h5
│   ├── acq0002.JF03T01V02.dap
│   ├── acq0002.JF03T01V02.h5
│   ├── acq0002.PVDATA.h5
├── logs
│   ├── acq0001.BSDATA.log
│   ├── acq0001.JF01T03V01.log
│   ├── acq0001.JF03T01V02.log
│   ├── acq0001.PVDATA.log
│   ├── acq0002.BSDATA.log
│   ├── acq0002.JF01T03V01.log
│   ├── acq0002.JF03T01V02.log
│   ├── acq0002.PVDATA.log
├── meta
│   ├── acq0001.json
│   ├── acq0002.json
│   └── scan.json
└── raw_data
    ├── acq0001.JF03T01V02.h5
    ├── acq0002.JF03T01V02.h5

Bookkeeping

Upon a successful request accepted by the broker, all parameters utilized are saved within a meta/ subdirectory related to the corresponding run/scan. These files are named acqYYYY.json.

For instance:

$ pwd
/sf/cristallina/data/p21528/raw/run0001/meta
$ ls
acq0001.json  acq0003.json  acq0005.json  acq0007.json  acq0009.json  acq0011.json  acq0013.json
acq0002.json  acq0004.json  acq0006.json  acq0008.json  acq0010.json  acq0012.json  scan.json
$ cat acq0010.json
{
  "pgroup": "p21528",
  "rate_multiplicator": 1,
  "append_user_tag_to_data_dir": false,
  "user_tag": "test",
  "run_number": 1,
  "start_pulseid": 18940426916,
  "stop_pulseid": 18940427116,
  "detectors": {
    "JF16T03V01": {}
  },
  "channels_list": [
    "SARFE10-PBPG050:PHOTON-ENERGY-PER-PULSE-AVG",
    "SARFE10-PBIG050-EVR0:CALCI",
    ...<skipped>...
    "SAROP31-PBPS149:YPOS",
    "SAR-CVME-TIFALL6:EvtSet"
  ],
  "pv_list": [
    "SARFE10-PBPG050:PHOTON-ENERGY-PER-PULSE-US",
    "SARFE10-PBPG050:PHOTON-ENERGY-PER-PULSE-DS",
    "SARFE10-OAPU044:MOTOR_X",
    ...<skipped>...
    "SAROP31-OKBH154:TX2.RBV"
  ],
  "beamline": "cristallina",
  "acquisition_number": 10,
  "request_time": "2023-09-05 15:28:24.291760",
  "unique_acquisition_run_number": 10
}

Additionally, logs within the logs/ directory capture the output of retrieve actions by corresponding writers:

$ pwd
/sf/cristallina/data/p21528/raw/run0001/logs
$ ls
acq0001.BSDATA.log      acq0004.JF16T03V01.log  acq0007.PVDATA.log      acq0011.BSDATA.log
...

$ cat acq0010.BSDATA.log 
Request for data3buffer : output_file /sf/cristallina/data/p21528/raw/run0001/data/acq0010.BSDATA.h5 from pulse_id 18940426916 to 18940427116
Sleeping for 59.997645139694214 seconds before continuing.
Starting payload.
Using data_api3 databuffer writer.
data api 3 reader 0.8.8
Data download and writing took 2.8266358375549316 seconds.
...<skipped>...
check SAROP31-PBPS149:YPOS number of pulse_id(unique) is different from expected : 181 vs 201
check SAR-CVME-TIFALL6:EvtSet not present in file
Check of data consistency took 0.017050504684448242 seconds.
Finished. Took 18.1561918258667 seconds to complete request.

$ cat acq0010.PVDATA.log 
[sf.cristallina.epics_writer] Processing of b4396eec-4156-4ad1-b2da-62d903405ace started in service sf.cristallina.epics_writer.
[sf.cristallina.epics_writer] Requesting file /sf/cristallina/data/p21528/raw/run0001/data/acq0010.PVDATA.h5 for pulse_id range 18940426916 to 18940427116 with 132 channels.
[sf.cristallina.epics_writer] Request b4396eec-4156-4ad1-b2da-62d903405ace completed in 0.29 seconds.
[sf.cristallina.epics_writer] Output file analysis:
    [SARFE10-PBPG050:PHOTON-ENERGY-PER-PULSE-US] Point count 3 (1[2)0)
    [SARFE10-PBPG050:PHOTON-ENERGY-PER-PULSE-DS] Point count 3 (1[2)0)
    [SARFE10-OAPU044:MOTOR_X] Point count 1 (1[0)0)
    ...<skipped>...
    [SAROP31-OKBH154:TX2.RBV] Point count 1 (1[0)0)

$ cat acq0010.JF16T03V01.log 
Request for detector_buffer : output_file /sf/cristallina/data/p21528/raw/run0001/data/acq0010.JF16T03V01.h5 from pulse_id 18940426916 to 18940427116
Sleeping for 9.99739956855774 seconds before continuing.
Starting payload.
Using detector retrieve writer.
Starting detector retrieve from buffer /home/dbe/bin/sf_writer /sf/cristallina/data/p21528/raw/run0001/data/acq0010.JF16T03V01.h5 /gpfs/photonics/swissfel/buffer/JF16T03V01 3 18940426916 18940427116 1 
Retrieve Time : 0.33776354789733887
Finished retrieve from the buffer
Finished. Took 0.3386099338531494 seconds to complete request.

These logs provide insights such as missing pulseid, incomplete data for certain sources, and details about the consistency of the acquired data.

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