BLISS:

experiments control

of EBS beamlines

ISDD Seminar

16-10-2017

The BLISS core development team

A. Homs

E. Papillon

J. Bodera

C. Guilloud

J. Bodera

M. Guijarro

T. Coutinho

S. Petitdemange

V. Michel

BLISS =

BeamLine Instrumentation Support Software

Why BLISS ?

spec: 26 years driving experiments at ESRF

• Direct control of devices
  • easier to debug
  • restarting = reset
• Integrated tool
  • configuration
  • controllers for all kinds of devices
  • plotting
• Server mode to connect with external processes (GUI...)
• Commercial support

• Poor macro language
• No extensibility
• Single task operation
• Exclusive hardware control
• Per-session configuration, no sharing
• No built-in continuous scan framework
• Limited data management
• No code ownership, less freedom

spec: 26 years driving experiments at ESRF

The path to BLISS

BLISS Python library and tools

BLISS Python library and tools

Embed into any Python program

>>> from bliss.common.axis import Axis
>>> from bliss.controllers.motors import IcePAP
>>> iceid2322 = IcePAP.IcePAP("iceid2322",
                              {"host": "iceid2322"},
                              [("mbv4mot", Axis, { "address": 1, 
                                                   "steps_per_unit": 80,
                                                   "velocity": 125,
                                                   "acceleration": 500
                                              }
                              )], [])
>>> iceid2322.initialize()
>>> m = iceid2322.get_axis("mbv4mot")
>>> m.velocity()
125.0
>>> m.acceleration()
500.0
>>> m.position()
252.23750000000001
>>>

BLISS Python library and tools

Command Line Interface based on ptpython

matias@kashyyyk:~ % bliss -s test_session
test_session: Executing setup...
Initializing 'heater`
...
Initializing 's1hg`
Done.

>>> ascan(m1, 0, 10, 30, 0.1, diode, save=False)
Total 30 points, 3.0 seconds

Scan 4 Mon Sep 11 11:58:03 2017 <no file> test_session user = guijarro
ascan m1 0 10 30 0.1

  #  timestamp  m1  diode
  0  1.50512e+09   0  499.112
  1  1.50512e+09  0.345  500.799
...
 28  1.50512e+09  9.655  505.622
 29  1.50512e+09  10  499.883

BLISS Python library and tools

Configuration web application

BLISS Python library and tools

Graphical interface for users: interactive web shell

BLISS key concepts

All I/O based on gevent

cooperative multi-tasking

Direct hardware control

Distributed control ownership & shared state

Persistent settings

 cache

 Transient data store

Scan acquisition chain, represented as a tree

BLISS modular architecture

online data analysis

data visualisation

data archiving

Beacon:

services for BLISS

(presented by T. Coutinho)

Beacon static configuration service

Beacon server

.yml

Devices & sequences configuration in YAML format

Configuration web application DEMO

Beacon dynamic services

Beacon server,

services built on top of

BLISS Hardware Control

Direct hardware control

Demo: sensor with direct hardware control

• Acquisition chain
  • a tree with master & slave nodes
  • master triggers data acquisition
  • slave takes data
• AcquisitionMaster, AcquisitionDevice
  • wrappers around BLISS control objects
• Data writer
  • HDF5

Model for organizing acquired data

• Mirroring of the Acquisition Chain tree

  • each device in the chain has a name

  • each device define 1 or more 'AcquisitionChannel' objects

• Acquisition channels

  • must have a name, a type and a shape

• Metadata

  • scan_info dictionary ({ key: value, ... }) associated with scans

Online data publishing

• While a scan is running, data is published to the redis database provided by Beacon

  • scalar values are stored directly

  • bigger data (images, spectra) is just referenced

  • configurable time to live (TTL)

• Any external process can access redis data to perform online data analysis, for example

Online data publishing demo

Conclusion

Project state

• Current state of deployment
  • MX beamlines are already running BLISS
  • 3 more beamlines (Materials Science) for the end of the year
  • Full deployment in 2020
• Project is in active development
  • git repository

Conclusion

• Long term project for EBS beamlines
• Control paradigm: keep what works, add new concepts
• Python scanning framework
• Prepared for current and future challenges
  • scans with online feedback
  • data management
  • evolutive platform