1. PyMoDAQ’s overview

overview

Fig. 1.1 PyMoDAQ control of an experimental setup using the Dashboard and a set of DAQ_Viewer and DAQ_Move modules

PyMoDAQ is an advanced user interface to control instruments (casually called Detectors) and actuators (sometimes called Moves for historical reasons). Each of these will have their own interface called DAQ Viewer and DAQ Move that are always the same (only some specifics about communication with the controller will differ), so that a PyMoDAQ’s user will always find a known environment independent of the kind of instruments it controls. These detectors and actuators are grouped together in the DashBoard and can then be controlled manually by the user: acquisition of images, spectra… for various positions of the actuators (see Fig. 1.1). The Dashboard has functionalities to fully configure all its detectors and actuators and save the configuration in a file that will, at startup, load and initialize all modules. Then Dashboard’s extensions can be used to perform advanced and automated tasks on the detectors and actuators (see Fig. 1.2):

  • The first of these extensions is called DAQ Scan and is used to perform automated and synchronized data acquisition as a function of multiple actuators positions. Many kind of scans are possible: 1Ds, 2Ds, NDs, set of points and many ways to perform each of these among which Adaptive scan modes have been recently developed (from version 2.0.1).

  • The second one is the DAQ Logger. It is a layer between all the detectors within the dashboard and various ways to log data acquired from these detectors. As of now, one can log to :

    • a local binary hdf5 file

    • a distant binary hdf5 file or same as hdf5 but on the cloud (see HSDS from the HDF group and the h5pyd package)

    • a local or distant SQL Database (such as PostgreSQL). The current advantage of this solution is to be able to access your data on the database from a web application such as Grafana. Soon a tutorial on this!!

  • Joystick control of the dashboard actuators (and eventually detectors).

  • PID closed loop interface

  • Direct code execution in a Console

overview

Fig. 1.2 PyMoDAQ’s Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.