daplis-rtp 1.1.2

Data Analysis Package for LInoSpad - Real-Time Plotting

Data Analysis Package for LInoSpad - Real-Time Plotting (DAPLIS-RTP).

Package with an application for real-time plotting of sensor population for LinoSPAD2. A spin-off of the main data analysis package daplis

Full documentation (including all docstrings) can be found here.

Introduction

The main purpose of this application is real-time plotting of LinoSPAD2 sensor population for easier alignment: introducing the changes into the setup, one can see the results instantly using this application. Given the detector data acquisition is running and once a path to where data files should be saved to is provided, the program constantly checks for the latest saved file, then unpacks the data, and plots it as a number of photons detected in each pixel.

Additionally, a separate tab for checking the data quality by looking at the distribution of timestamps across the whole acquisition cycle is provided: if the distribution is uniform, the data is ok. The third tab can be used for plotting the number of photons from two pixels vs the data file as two curves with primary application in Mach-Zehnder interferometer setup.

This repo was separated from the main library of scripts for LinoSPAD2 data analysis. The reason is that the app requires its own 'main.py' to run and having it as a standalone makes it quite easy to generate an executable with pyinstaller.

Installation and how to run the application

To start using the package, one can download the whole repo. The 'main.py' serves as the main hub for starting the app. "requirements.txt" lists all packages required for this project to run. One can create an environment for this project either using conda or install the necessary packages using pip (for creating virtual environments using pip see this).

Using pip, one can check if the virtualenv package is installed in the current python environment:

pip show virtualenv

or install it directly using:

pip install virtualenv

To create a new environment (it is highly recommended to keep the virtual environments in a separate folder), run the following:

py -m venv PATH/TO/NEW/ENVIRONMENT

E.g., for creating a 'daplis-rtp' environment, one can run (on Windows):

py -m venv C:/Users/USERNAME/venvs/daplis-rtp

To activate the environment, run (on Windows):

PATH/TO/NEW/ENVIRONMENT/Scripts/activate

or, on Linux:

source PATH/TO/NEW/ENVIRONMENT/bin/activate

There, the package can be installed from PyPI:

pip install daplis-rtp

The application can be run from the command line or terminal via

daplis-rtp

Installation: using source code

Alternatively, one can run the application using the source code. To do it this way, first, create a virtual environment for the package by running the following set of commands (on Windows):

pip install virtualenv
py -m venv NEW_ENVIRONMENT_NAME
PATH/TO/NEW_ENVIRONMENT_NAME/Scripts/activate

Then, download the zip with the source code of this package from github, extract and change directory to the folder with the code. There, first install the required packages ("requirements.txt"), and, finally, install the package itself locally.

cd PATH/TO/THIS/PACKAGE
pip install -r requirements.txt
pip install -e .

Finally, to run the app, run the 'main.py' script.

Executable from the source code using pyinstaller

On Windows, to create an executable, one can do the following: first, a separate virtual environment is highly recommended for a faster and smoother experience with the app, as pyinstaller packs everything it finds in the virtual environment; using pip:

pip install virtualenv
py -m venv PATH/TO/NEW_ENVIRONMENT_NAME
PATH/TO/NEW_ENVIRONMENT_NAME/Scripts/activate

where the last command activates the environment. Here, all the necessary packages along with the app package itself should be installed. To do this, run from the environment (given the package was downloaded):

cd PATH/TO/THIS/PACKAGE
pip install -r requirements.txt
pip install -e .

where the latter command installs the package itself in the environment. To create the executable, pyinstaller should be installed, too:

pip install pyinstaller

Then, given the current directory is set to where the package is, run

pyinstaller --clean --onedir --noconsole main.py

which packs everything in the package for the "main.exe" executable for the app. Options '--onedir' for installing everything into a single directory and '--noconsole' for running the app without a console are recommended.

Dark theme app (Windows)

For dark theme enthusiasts, there is an option to run the app in dark mode (tested on Windows only). To do that, in the environment where the app is running, install qdarkstyle

pip install qdarkstyle

or, using conda

conda install qdarkstyle -c conda-forge

Then, in the 'main.py', import (uncomment) qdarkstyle and uncomment the 5th line in the following code block

if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = MainWindow()
    # For dark theme
    # app.setStyleSheet(qdarkstyle.load_stylesheet())
    window.show()
    app.exec()

that will run the app in dark mode. To apply dark theme for the matplotlib canvases as well, uncomment the

plt.style.use("dark_background")

in the 'plot_figure.py' and 'plot_figure_MZI.py'.

How to contribute

This repo consists of two branches: 'main' serves as the release version of the package, tested, and proved to be functional and ready to use, while the 'develop' branch serves as the main hub for testing new stuff. To contribute, the best way would be to fork the 'develop' branch and submit via pull requests. Everyone willing to contribute is kindly asked to follow the PEP 8 and PEP 257 conventions.

License and contact info

This package is available under the MIT license. See LICENSE for more information. If you'd like to contact me, the author, feel free to write at [e-mail].