PAME 0.3.2

GUI for modeling nanoparticles on optical fiber with mixing/shell-filling models

PAME: Plasmonic Assay Modeling Environment

Graphical Python application for simulating plasmonic biosensors, particularly fiberoptic biosensors with nanoparticles.

Check out the PAME preprint.

Tutorials

IPython Notebooks

Some of these are traditional tutorials, others are examples of analyzed data from our lab.

• Simultation Parsing Tutorial

• Gold Nanoparticle Self-Assembly Compared to Experimental Data

  • Experimental datasets are preloaded in scikit-spectra library

• Simulating a Refractometer

• Protein binding to gold nanoparticle film

• Gold and Silver Nanoparticle Combined Layer 1

• Gold and Silver Nanoparticle Combined Layer 2

Screencasts

Tutorials are cumulative (eg screencast 2 picks up where 1 ends).

PAME’s tutorials are a series of screencasts.

• Screencast 1: Introduction to PAME- Anti-reflective coatings

• Screencast 2: Introduction to Nanoparticles

• Screencast 3: Nanoparticle film with silica shell

• Screencast 4: Nanoparticle film with protein shell

• Screencast 5: Intro to Fiberoptic Dip Sesnosr

• Screencast 6: Multiplexed Dip Sensor with Gold and Silver Nanoparticles

• Screencast 7: Gold Nanoparticle Fiber Dip Sensor Simulation

• Screencast 8: Dip Sensor with Organosilane Layer

Installation

Binaries (ie .exe one-click use files) are under development, but for now, PAME must be installed as a python library and launched through the command line. Anyone interested in helping to develop binaries, please contact.

PAME makes heavy use of the SciPy Stack (numpy, ipython etc…), and so it has a lot of dependencies. Instead of using a bare python distribution, I’d recommend using a scientific python distribution that comes pre-loaded with the SciPy Stack (eg canopy or conda) or want to install PAME into a clean environment (this is suggested), see the Conda installation directions. Otherwise, you can use pip install as usual.

PyPI

Since PAME requires many dependencies, this may upgrade numpy, scipy, ipython and other core scipy libraries.

To install from pip

pip install PAME

If this gives you an error (maybe for this reason), do the following.

Download the PAME sourcecode as a zipfile and unzip. cd into the unzipped directory

cd /path/to/PAME

Install from source

python setup.py install

Install the dependencies from pip

pip install -r requirements.txt

You also may need to install the QT backend <http://pyqt.sourceforge.net/Docs/PyQt4/installation.html> if it’s not already configured.

Conda

I use anaconda because it has an excellent virtual environment manager. The advantage is here you can installed a clean working environment only for PAME without altering any of your other packages. For a tutorial on conda virtual environments, check this out. To configure a PAME environment in anaconda, first install anaconda and then do the following:

1. Create a clean virtual environment (mine is named PAMEvenv)

   conda create -n PAMEvenv anaconda

This installs several required scientific packages including numpy, pandas and ipython.

2. Activate the environment

   source activate PAMEvenv

3. Install pame (download pame source code and unzip, then navigate into directory)

   cd /path/to/PAMEdirectory python setup.py install

4. Conda install/upgrade dependencies

   conda install traits traitsui mayavi chaco mpmath PIL

5. To deactivate the virtual environment

   source deactivate

Dependencies

The full list of PAME’s dependencies is in the requirements.txt file. You also may need to install the QT backend <http://pyqt.sourceforge.net/Docs/PyQt4/installation.html>.

Support

Questions? Interested in developing? Message: [e-mail], or contact me directly ([e-mail], @hughesadam87)

Web Utilitiles

PAME doesn’t run in the browser. Check out these related tools that do!

• Mie-coefficients

• Film Metrics (Thin Film Solver)

• Mie with shells and other tools

License

3-Clause Revised BSD