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simmla_w_mffifi's Introduction

SimMLA

Fourier optics simulation code for super-resolution microscopes utilizing dual microlens arrays.

License Information

© All rights reserved. ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE, Switzerland, Laboratory of Experimental Biophysics, 2016-2017

See the LICENSE file for more details.

Citing this Work

If you use SimMLA in your research, please cite the following paper in which this work was used:

K. M. Douglass, C. Sieben, A. Archetti, A. Lambert, and S. Manley, " Super-resolution imaging of multiple cells by optimized flat-field epi-illumination," Nature Photonics 10, 705-708, doi:10.1038/nphoton.2016.200 (2016)

http://www.nature.com/nphoton/journal/v10/n11/full/nphoton.2016.200.html

In addition if you use the mfFIFI extension, please cite:

Mahecic, D.; Gambarotto, D.; Douglass K.M.; Fortun, D.; Banterle, N.; Le Guennec, M.; Ibrahim, K.; Gonczy, P.; Hamel, V.; Guichard, P.; Manley, S. “Homogeneous multifocal excitation for high throughput superresolution imaging”. BioRxiv (2020). doi:2020.01.08.895565

Author

  • Kyle M. Douglass, kyle.m.douglass at gmail.com

Installation

SimMLA uses Python 3.5 and a few scientific libraries associated with it. The easiest way to install these libraries is through the Anaconda package manager.

After installing Anaconda, update the package manager in either the conda prompt or terminal with the command

conda update conda.

Once conda is updated, use the prompt/terminal to navigate to the folder containing the SimMLA directory. Enter the command

pip install -e SimMLA

to install SimMLA in development mode.

In case there are dependency issues, you can try installing a conda environment known to work with SimMLA. To do this, navigate to the SimMLA parent directory and run the command

conda env create -f environment.yml

Directions

SimMLA contains three modules that may be used in any Python 3.5 library:

  1. fftpack - Convenience routines for fast Fourier transforms
  2. fields - Used to generate coherent and partially coherent beams
  3. grids - Discrete grids for sampling fields

Examples of how to use the code may be found in the tests directory. Jupyter notebooks for generating the data in the publication's figures are in the publication_data directory.

simmla_w_mffifi's People

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