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Spectroscopy in Python built on Pandas.

Project description

.. image:: skspec/data/coverimage.png
:height: 100px
:width: 200 px
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scikit-spectra: Tools for explorative spectroscopy


The current documentation (and in-a-pinch test suite) is a series of example notebooks
(`iPython Notebook`_), which cover most of the basics. These have been linked below:

.. _`iPython Notebook`:

- **Getting Started**:
- `TimeSpectra tutorial (part 1)`_
- `TimeSpectra tutorial (part 2)`_
- `Sampling and Selecting Data`_

- `Intro to Plotting`_
- `Intro to 2D and 3D Plots`_
- `Interactive Plots with Plotly`_

Don't forget that `pandas itself has a rich plotting api`_. Use **** to retrieve the DataFrame or Series from the skspec object.

.. _`pandas itself has a rich plotting api` :

- `Bundled Datasets`_
- `IO: Importing and Exporting`_
- `Intro to Multiple Datasets (StackSpec)`_

.. _`Sampling and Selecting Data` :
.. _`IO: Importing and Exporting` :
.. _`Intro to Plotting` :
.. _`Intro to 2D and 3D Plots` :
.. _`Interactive Plots with Plotly` :
.. _`Bundled Datasets` :
.. _`Intro to Multiple Datasets (StackSpec)` :
.. _`TimeSpectra tutorial (part 1)` :
.. _`TimeSpectra tutorial (part 2)` :

- Correlation spectral data with electron microscopy

- `Custom units`_
- `Custom units with convertable representations (inch --> foot --> meter)`_

.. _`Custom units` :
.. _`Custom units with convertable representations (inch --> foot --> meter)` :

- Two Dimensional Correlation Spectroscopy (see `Noda/Ozaki`_)
- Sizing Gold Nanoparticles through UVVis Spectra

- `Matplotlib Color Maps`_

.. _`Matplotlib Color Maps` :
.. _`Noda/Ozaki` :

Legacy documentation_ is generously hosted by github_.

.. _github:

.. _documentation:


3-Clause Revised BSD_

.. _BSD :


In its current state, skspec requires following dependencies:

**pandas (0.14 or greater)**, **scipy**

.. _scipy:

I would recommend using `Enthought Canopy`_ and its excellent
the package manager. ``skspec`` is also
registered on PyPi_.

.. _PyPi :

.. _`Enthought Canopy` :

Pip Install

Make sure you have pip installed:

sudo apt-get install python-pip


pip install scikit-spectra

To install all of the dependencies, download ``skspec`` from github, navigate
to the base directory and type:

pip install -r requirements.txt

Installation from source

In the ``skspec`` base directory run:

python install

The developmental version can be cloned from github:

git clone

This will not install any dependencies.

Download the source_ and run::

python install

This should install to your systems default Python path. If your default Python path is not found, or you have multiple Python distributions,
install to an arbitrary directory using the home keyword option::

python install

.. _source:

To install all of the dependencies (pandas, scipy and their various dependencies), download ``skspec`` from github, navigate
to the base directory and type:

pip install -r requirements.txt

Testing Installation

Open a Python shell and run the following::

from skspec import *

from import *

This should result in no errors.

Have a feature request, or want to report a bug? Please fill out a github
issue_ with the appropriate label.

.. _issue :

History and Background

``skspec`` originally began at the George Washington University in an
effort to develop exploratory visualization techniques with UVVis
data, particularly the output of fiberoptic/nanotechnology research.

The decision to officialy package these nascent tools was made for the following

1. To faciliate easier sharing and better organization between collaborators.
2. To document the progress and functionalities of the toolset.
3. To broadcast the toolkit to the community, and hopefully to merge with other Python spectroscopy packages.

In regard to the final point, ``skspec`` is not an attempt to be the de-facto spectroscopy
toolkit in Python; rather, it is a domain-specific wrapper for pandas. It should be quite extensible
to other spectroscopy domains, where it may perform a supporting or ancillary role. It is our
hope that in the future, other internal GWU tools for fiber optics design and nanomaterial plasmonics,
combined with this package, may form the basis for a crude nano-optics Python package.

Related Libraries
Interested in the Python ecosystem? Check out some of these related libraries:

- NumPy_ (Fundamental vectorized numerics in Python)
- SciPy_ (Collection of core, numpy-based scientific libraries)
- matplotlib_ (De facto static plotting in Python)
- pandas_ (R on steroids)
- plotly_ (Interactive/cloud plotting)

.. _NumPy:
.. _pandas:
.. _SciPy:
.. _matplotlib :
.. _plotly :

About the Author

I'm a PhD student at GWU (check me out on researchgate_, Linkedin_ or twitter_ (@hughesadam87))
and former Enthought intern. I work in biomolecule sensing and nanophotonics.
Like any PhD student, my time is stretched across many projects. As such,
the ``skspec`` source code may is messy in places, and a test suite has
yet to be developed. Developing the iPython notebook tutorials
alongside the code helped served as a basic regression test platform.

.. _researchgate :
.. _Linkedin :*1_*1_*1_*1_*1_*1_*1_*1_*1_*1_*1&trk=spm_pic
.. _twitter :

Thank you countless developers who have patiently answered hundreds of
my questions on too many mailing lists and sites to list.

Thank you `Zhaowen Liu`_ for all of your help with this project, our
other projects and for your unwaivering encouragement (and for the panda).

.. _`Zhaowen Liu` :

Project details

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