quanfima 0.1a3
The package for morphological analysis and visualization of fibrous materials.
License: MIT
Requires Python: >=2.6,<3
Keywords: biomaterials fiber analysis material science visualization

.. image:: docs/source/_static/logo.png
    :align: left

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    :target: https://travis-ci.org/rshkarin/quanfima 

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*Quanfima* (**qu**\ antitative **an**\ alysis of **fi**\ brous **ma**\ terials)
is a collection of useful functions for morphological analysis and visualization
of 2D/3D data from various areas of material science. The aim is to simplify
the analysis process by providing functionality for frequently required tasks
in the same place.

More examples of usage you can find in the documentation.

- Analysis of fibrous structures by tensor-based method in 2D / 3D datasets.
- Estimation of structure diameters in 2D / 3D by a ray-casting method.
- Counting of particles in 2D / 3D datasets and providing a detailed report in
  pandas.DataFrame format.
- Calculation of porosity measure for each material in 2D / 3D datasets.
- Visualization in 2D / 3D using matplotlib, visvis packages.

Installation
------------

The easiest way to install the latest version is by using pip::

    $ pip install quanfima

You may also use Git to clone the repository and install it manually::

    $ git clone https://github.com/rshkarin/quanfima.git
    $ cd quanfima
    $ python setup.py install

Usage
-----
Open a grayscale image, perform segmentation, estimate porosity, analyze fiber
orientation and diameters, and plot the results.

.. code-block:: python

  import numpy as np
  from skimage import io, filters
  from quanfima import morphology as mrph
  from quanfima import visualization as vis
  from quanfima import utils

  img = io.imread('../data/polymer_slice.tif')

  th_val = filters.threshold_otsu(img)
  img_seg = (img > th_val).astype(np.uint8)

  # estimate porosity
  pr = mrph.calc_porosity(img_seg)
  for k,v in pr.items():
    print 'Porosity ({}): {}'.format(k, v)

  # prepare data and analyze fibers
  data, skeleton, skeleton_thick = utils.prepare_data(img_seg)
  cskel, fskel, omap, dmap, ovals, dvals = \
                      mrph.estimate_fiber_properties(data, skeleton)

  # plot results
  vis.plot_orientation_map(omap, fskel, min_label=u'0°', max_label=u'180°',
                           figsize=(10,10),
                           name='2d_polymer',
                           output_dir='/path/to/output/dir')
  vis.plot_diameter_map(dmap, cskel, figsize=(10,10), cmap='gist_rainbow',
                        name='2d_polymer',
                        output_dir='/path/to/output/dir')

.. code-block:: python

  >> Porosity (Material 1): 0.845488888889

.. image:: docs/source/_static/2d_polymer_data.png
    :align: center

.. image:: docs/source/_static/2d_polymer_orientation_map_600px.png
    :align: center

.. image:: docs/source/_static/2d_polymer_diameter_map_600px.png
    :align: center