PYDAQ - Data Acquisition and Experimental Analysis with Python

Using Python for applications with experimental data (Arduino and NIDAQ boards)

This package was firstly designed to use experimental device for data acquisition and signal generator, when performing different experiment, such as a step-response test.

Despite this, one can use PYDAQ to acquire and send a signal from any system, using different boards (check jupyter notebook examples folder), through a Graphical User Interface or via command line. In this sense the user is capable to generate a customized signal which can be easily applied to a system.

It is noteworthy that this application makes data acquisition and empirical experiments simpler, faster and easier. This is relevant when the user needs empirical data to construct black box linear and nonlinear models, commomly used in research projects in forecasting and model-based control schemes.

The code provided here allows user to save acquired data in .dat files in a path specified by the user (or at Desktop, if no path is provided), as well as send a user-defined data, which can be any nonlinear input signal (you are strongly advised to check the )

In what follows you will find

• Installation and Requirements
• Quick view and Main features
• Using Graphical User Interfaces
• Screenshots

Installation and Requirements

The fastest way to install PYDAQ is using pip:

pip install pydaq

NOTE: In this version of pydaq (0.0.3), (NI-DAQmx drivers) must be installed, even if the user is only using Arduino Boards. This issue will be addressed in future versions, allowing Arduino users to use PYDAQ without having to install NI-DAQmx drivers.

PYDAQ requires:

• Installed driver of the board used (Arduino or National Instruments NIDAQ)
• nidaqmx (>=0.6.5) for data acquisition from National Instruments Boards
• matplotlib (>=3.5.3) as a visualization tool
• numpy (>=1.22.3) to process data
• PySimpleGUI (>=4.60.3) as a Graphical User Interface
• PyQt5 as a backend for PySimpleGui
• pyserial (>=3.5) to manage data to/from Arduino

Quick view and Main features

Using GUIs (more details in documentation and jupyter notebook examples):

Data acquisition (NIDAQ):

from pydaq.get_data import Get_data
g = Get_data()
g.get_data_nidaq_gui()

Data acquisition (Arduino):

from pydaq.get_data import Get_data
g = Get_data()
g.get_data_arduino_gui()

Sending data (NIDAQ):

from pydaq.send_data import Send_data
s = Send_data()
s.send_data_nidaq_gui()

Sending data (Arduino):

from pydaq.send_data import Send_data
s = Send_data()
s.send_data_arduino_gui()

Step response (NIDAQ):

from pydaq.step_response import Step_response
s = Step_response()
s.step_response_nidaq_gui()

Step response (Arduino):

from pydaq.step_response import Step_response
s = Step_response()
s.step_response_arduino_gui()

Screnshots

Graphical User Interfaces - NIDAQ

Graphical User Interfaces - Arduino

Acquired/Sending data and step response - NIDAQ and Arduino

Data in .dat format

Contributing

You are more than welcome to make your contribution and submit a pull request. To contribute, read this guide.

CITATION

If you are using PYDAQ on your project, you can cite us as following:

• 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}
}