pydaq 0.0.7

Data Acquisition and Experimental Analysis with Python

PYDAQ - Data Acquisition and Experimental Analysis with Python (www.pydaq.org)

PYDAQ is a Python package for data acquisition, signal generation, system identification, digital filtering, and real-time control using Arduino and NI-DAQ devices.

It provides a unified graphical interface, command-line tools, and Jupyter notebook examples for laboratory experiments, rapid prototyping, teaching, and research workflows.

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Capabilities

PYDAQ supports the following experimental workflows:

Capability	Description
Data acquisition	Acquire, plot, and save experimental data from Arduino or NI-DAQ boards
Signal generation	Send user-defined input signals, including nonlinear excitation signals
Step-response experiments	Run automatic step-response tests and save the resulting data
PRBS-based experiments	Generate excitation signals for system identification workflows
System identification	Estimate linear and nonlinear black-box models from experimental data using SysIdentPy
Digital filtering	Apply FIR and IIR filters directly to acquired data in real time
PID control	Run real-time or simulated P, PI, PD, and PID control with Ziegler-Nichols tuning
LQR control	Simulate or implement Linear Quadratic Regulator control for state-space systems
Multi-channel workflows	Work with multiple Arduino or NI-DAQ channels
Benchmarking	Estimate the maximum reliable sampling frequency supported by the local system

Further details about benchmarking are available in the benchmarking documentation.

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Installation

Install PYDAQ with pip:

pip install pydaq

Main dependencies include numpy, scipy, matplotlib, pyserial, nidaqmx, PySide6, sysidentpy, bitarray, and packaging. Specific dependency versions are defined in the project configuration files.

Hardware notes:

• Arduino workflows do not require NI-DAQmx drivers.
• NI-DAQ workflows require the NI-DAQmx drivers.

PYDAQ is tested up to Python 3.14. It may run on newer versions, but without guarantees.

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Graphical user interface

All main workflows are available from a single graphical interface.

Launch the GUI with:

from pydaq.pydaq_global import PydaqGui

PydaqGui()

More details are available in the documentation and in the Jupyter notebook examples.

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Screenshots

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Contributing

Contributions are welcome. Please read the contribution guide before submitting a pull request.

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Citation

This is the seminal publication of the PYDAQ project and should be cited in any work that uses PYDAQ.

• Martins, S. A. M. (2023). PYDAQ: Data Acquisition and Experimental Analysis with Python. Journal of Open Source Software, 8(92), 5662. https://doi.org/10.21105/joss.05662

@article{Martins_PYDAQ_Data_Acquisition_2023,
  author  = {Martins, Samir Angelo Milani},
  doi     = {10.21105/joss.05662},
  journal = {Journal of Open Source Software},
  month   = dec,
  number  = {92},
  pages   = {5662},
  title   = {{PYDAQ: Data Acquisition and Experimental Analysis with Python}},
  url     = {https://joss.theoj.org/papers/10.21105/joss.05662},
  volume  = {8},
  year    = {2023}
}

Additional related publications are available in the papers directory.