Skip to main content

Data analysis and operation software

Project description

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 by downloading the repository on you computer. If you want to keep track of the latest develepments, 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 insert the path to DOpeS folder at the beginning:

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 ("data_analysis/examples/" and "equipment_control/examples"). Furthermore, an 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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dopes-2025.0.1.tar.gz (86.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dopes-2025.0.1-py3-none-any.whl (43.7 kB view details)

Uploaded Python 3

File details

Details for the file dopes-2025.0.1.tar.gz.

File metadata

  • Download URL: dopes-2025.0.1.tar.gz
  • Upload date:
  • Size: 86.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.5

File hashes

Hashes for dopes-2025.0.1.tar.gz
Algorithm Hash digest
SHA256 3dc4cf1b6866ec6a85fac0a0d10b17278ce3ab087cc2eec776a38e13507a8d28
MD5 2a78f4ce27a70a5315759d264535dbbf
BLAKE2b-256 18f288929c8c21c4cc55626398ec310955ed91d3f0a9274f4a9ba4566098f2ef

See more details on using hashes here.

File details

Details for the file dopes-2025.0.1-py3-none-any.whl.

File metadata

  • Download URL: dopes-2025.0.1-py3-none-any.whl
  • Upload date:
  • Size: 43.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.5

File hashes

Hashes for dopes-2025.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 838e894676d5c7ab2bcf94207835f7b93bd28df7ffb77c4c308c8bf54d97895b
MD5 364df95858a9e9210a5efdcd73a646ed
BLAKE2b-256 33caf306f2a110fd3557a04e087075851ffb28a2fda31025bffd0e15bbe49173

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page