rshkarin
quanfima
Python

Quanfima (Quantitative Analysis of Fibrous Materials)

Last updated Jan 7, 2026
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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')

thval = filters.thresholdotsu(img) imgseg = (img > thval).astype(np.uint8)

# estimate porosity pr = mrph.calcporosity(imgseg) for k,v in pr.items(): print 'Porosity ({}): {}'.format(k, v)

# prepare data and analyze fibers data, skeleton, skeletonthick = utils.preparedata(img_seg) cskel, fskel, omap, dmap, ovals, dvals = \ mrph.estimatefiberproperties(data, skeleton)

# plot results vis.plotorientationmap(omap, fskel, minlabel=u'0°', maxlabel=u'180°', figsize=(10,10), name='2d_polymer', output_dir='/path/to/output/dir') vis.plotdiametermap(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/2dpolymer_data.png :align: center .. image:: docs/source/static/2dpolymerorientationmap_600px.png :align: center .. image:: docs/source/static/2dpolymerdiametermap_600px.png :align: center

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