Introduction

What is Pyacq?

Pyacq is an open-source system for distributed data acquisition and stream processing. Its functionality is organized into nodes that individually handle acquisition, filtering, visualization, and recording. Nodes are created on demand and connected to form a graph of data streams. Nodes may be created and connected within a single thread, or distributed across multiple threads, processes, and hosts.

_images/example_node_graph.svg

An example setup for a neurophysiology experiment.

The figure above shows an example use case: two data acquisition devices–a camera and an electrode array recorded through an ADC–stream data simultaneously to storage. The electrode data is passed through an online spike-sorting analyzer whose output is also stored. Finally, the camera’s video feed and the online analysis are streamed to a graphical interface that displays data as it is acquired. The nodes in the graph may run together on a single machine or distributed across a network.

The simplified example below gives a brief overview of the code needed to create part of the graph shown above:

import pyacq

# Connect to a remote host and create a new process there
manager = pyacq.create_manager('rpc')
worker_host = manager.add_host('tcp://10.0.0.103:5678')
worker = worker_host.create_nodegroup()

# Create nodes for data acquisition, analysis, storage, and display
device = manager.create_node('NiDAQmx')
analyzer = manager.create_node('Spikesorter', host=worker)
recorder = manager.create_node('HDF5Recorder', host=worker)
viewer = manager.create_node('QOscilloscope')

# Connect all nodes together
analyzer.input.connect(device.output)
recorder.input.connect(analyzer.output)
viewer.input.connect(analyzer.output)

# Begin acquiring and streaming data
manager.start_all()

License

Pyacq is supported by the French National Center for Scientific Research (CNRS) and the Lyon Neuroscience Research Center (CRNL). It is distributed under the BSD 3-clause license.

Architecture

Pyacq consists of 1) a collection of nodes with various capabilities for acquisition, processing, and visualization, and 2) a set of core tools that facilitate distributed control and data streaming.

Pyacq is built on several open-source tools including Python 3, numpy for data handling, ZeroMQ for interprocess and network communication, and PyQt for graphical user interface.

Overview of node types

Acquisition Processing Visualization
PyAudio Triggering Oscilloscope
Webcam (libav, imageio) Filtering Wavelet spectrogram
BrainAmp   Video display
Emotiv    
OpenBCI    

Installation

  • Pyacq requires Python 3; support for Python 2 is not planned.

  • Several packages are required, but most can be installed with pip:

    $ pip install pyzmq pytest numpy scipy pyqtgraph vispy colorama msgpack-python pyaudio blosc

  • One final dependency, PyQt4, cannot be installed with pip. Linux distributions typically provide this package. OSX users can get PyQt4 (and most other dependencies) using the Anaconda Python distribution. Windows users can also use Anaconda or download PyQt4 directly from the Riverbank Computing website.

  • To install Pyacq, use the standard distutils approach:

    $ python setup.py install