dopes 2025.0.2

Data analysis and operation software

Description

Data analysis and Operation Software (DOpeS) provides a set of tools for

1. the analysis of data coming from lab equipment such as Raman spectrometer, white-light interferometer, semiconductor analyzer, ...
2. the control of lab equipment such as multimeter, source measurement units, pressure generator, climatic chamber, monochromator, ...

Structure

• data_analysis for the analysis of lab equipment:
  • Data processing function such as baseline removal, interpolation, filtering, ...
  • File handling to read data files and writting processed data in files
  • Specific functions to analyse measurements such as Raman specroscopy, white-light interferometer, semiconductor analyzer, ...
  • Modeling of electronic device and material such as diode and MOS transistor
• equipment_control for the control of various lab equipment:
  • Digital multimeter (DMM) DMM7510, DMM6500 and K2000
  • Source Measurement Unit (SMU) K2400 and K2450
  • Semiconductor analyser HP4145 and K4200
  • Monochromator CM110
  • Pressure generator and monitor KAL100
  • Climatic chamber SH242 (sh242.py)
  • ...

Requirements

DOpeS is made from functions, classes and scripts based on Python programming lanquage. The following packages are required for the data analysis and the equipment control:

• Numpy for the data handling and processing
• SciPy for the data processing tools such as interpolation and filtering (only for data_analysis part)
• Pyvisa for the communication with equipment (only for equipment_control part)
• Pyserial for the serial communication with equipment (only for equipment_control part)

Installation

DOpeS is easily installed through the Python Index Package (PyPI) available at dopes :

pip install dopes

If you want to keep track of the latest versions, you can download the gitlab repository and keep it synchronized with the gitlab project: To download it, you just have to type the following command in a terminal:

git clone https://forge.uclouvain.be/LocLahaye/dopes.git

To update it with the gitlab project, you can type:

cd path/to/dopes
git pull

Usage

DOpeS is built as a set of python classes and functions. To use it, you only have to create a python script in you favorite IDE and import the dopes package installed through the Python Index Package (PyPI).

A global import can be made to import all the functionnalities:

import dopes

The various tools can also bee specifically accessed as any python package:

import dopes.equipment_control.equipment as eq
import dopes.equipment_control.k2400 as k2400
import dopes.data_analysis.raman as ram

If the package has been locallly downloaded on your laptop with git command or not, the path to DOpeS folder has to be added at the beginning of the script:

import sys
sys.path.insert(1, '/path/to/dopes')

The various tools can then be accessed as any python package and class:

import equipment_control.equipment as eq
import equipment_control.k2400 as k2400
import data_analysis.raman as ram

Lots of examples for the data analysis and equipment control can be found in the examples folder ("examples/data_analysis/" and "/examplesequipment_control"). Furthermore, an markdown (.md) or html (.html) documentation can be found in the "doc/" folder with a description of all classes and functions present in the software.

Support and contributing

We welcome any feedback on issue, missing operation or equipment but also idea for further improvements.

Authors and acknowledgment

The initial idea of this project has been thought by Loïc Lahaye and Nicolas Roisin.

License

DOpeS © 2025 by Loïc Lahaye and Nicolas Roisin is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International ( CC BY-NC-SA 4.0)

Project status

Still alive