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Data Acquisition and Experimental Analysis with Python

Project description

“PYDAQ”

PyPI version License python status contributors forks stars

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

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

Feature Description
Send Data (NIDAQ) This feature allows the user to send data through any NIDAQ board using a graphical user interface
Send Data (Arduino) This feature allows the user to send data through any Arduino board through a graphical user interface
Get Data (NIDAQ) Here the user is able to get data from a NIDAQ board, using any terminal configuration (Diff, RSE, NRSE), sample time and other parameters. Acquired data can also be saved and plot for further applications
Get Data (Arduino) Here the user is able to get data from an Arduino board, using several options. Acquired data can also be saved and plot for further applications
Step Response (NIDAQ) In this feature one can perform an automatic step response experiment using a NIDAQ board. Data genereted by the experiment can also be saved to be used in further applications, such as obtaining linear and nonlinear models from acquired data
Step Response (Arduino) In this feature one can perform an automatic step response experiment using an Arduino. Data genereted by the experiment can also be saved to be used in further applications, such as obtaining linear and nonlinear models from acquired data

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.

Project details


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