Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/rshkarin/quanfima

Quanfima (Quantitative Analysis of Fibrous Materials)
https://github.com/rshkarin/quanfima

data-analysis material-science morphological-analysis volumetric-data

Last synced: 2 months ago
JSON representation

Quanfima (Quantitative Analysis of Fibrous Materials)

Lists

README 

        
.. image:: docs/source/_static/logo.png

    :align: left

    

-----------



.. image:: https://travis-ci.org/rshkarin/quanfima.svg?branch=master 

    :target: https://travis-ci.org/rshkarin/quanfima 

    

.. image:: https://readthedocs.org/projects/quanfima/badge/?version=latest 

    :target: http://quanfima.readthedocs.io/en/latest/?badge=latest 

    :alt: Documentation Status

    

.. image:: https://zenodo.org/badge/127795855.svg

   :target: https://zenodo.org/badge/latestdoi/127795855



*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