#IP-BEC

IP-BEC (IP stands for image processing) is a PyQt4 application to analyze absorption images of Bose-Einstein Condensates. It is GUI based, but all the image browsing, image processing and fitting subroutines are available as python modules which can be used for scripting. Some of the features implemented in the software include adding tags and comments to absorption images, fringe reduction using the eigen-face algorithm, correcting for saturation due to high probe intensity, fitting the 2D column density to various functions. Additional features are added via plugins, which themselves are python modules so that they can be reused in external scripts.

Requirements

IP-BEC is written in PyQt4 and uses pyqtgraph for plotting. Hence, it is completely cross-platform. It has been tested on Windows, Mac and Linux using python 2.7. The following python packages are required:

• PyQt4
• pyqtpgraph
• numpy
• pillow

Installation

pip install ipbec

If you wish to modify the code, download the package in a local directory and install it in develop mode.

cd path/to/installation
git clone https://github.com/shreyaspotnis/ipbec
cd ipbec
python setup.py develop

Running

Before running for the first time, you need to create an empty JSON database. Create a file with only

{}

in it. Then run ipbec:

python -m ipbec

Features

• Watches a directory and automatically updates as new images are acquired.
• Fitting to 2D distributions. Can easily add more fitting functions.
• Fringe reduction.
• Correction for probe detuning, high probe intensity, correction for non-resonant light.
• Extensible: support for plugins.
• Tagging of images.

Usage

IP-BEC works by watching a directory for new images. As absorption images are acquired, they are added to this directory. For IPBEC to work for your setup, two things need to be changed.

First, modify the function readImageFile in ipbec/clt/imtools.py so that it reads your image format of choice and converts it into a numpy array.

Second, modify the ImageList class in clt/ImageList.py to suit your file naming format. The way it's done currently is for every absorption image, two new images are added. The first is an absorption image, and the second is a reference image. The absorption image ends with 'Abs.tif' and the reference image ends with 'Ref.tif'. Check out /ipbec/testdata/test_images for some sample images.