README

The GenTex or general texture analysis package provides a suite of routines that combines standard texture analysis methods and entropy/statistical complexity analysis methods.

What is this repository for?

GenTex provides a number of the standard algorithms required for generating complexity/texture measure estimates from multimodal imaging data. These include:

1. Generation of multidimensional feature spaces from multimodal 'image' data (i.e. multiple 'co-registered' 1,2,3, or 4 dimensional data sets, e.g. multiple 'co-registered' time series, multimodal image data, space/time data..) via the use of a set of image templates, including:

   • single voxels
   • linear sequences in cardinal directions (ref.)
   • notches in cardinal directions (ref.)
   • light cones in cardinal directions and 45 degree angles (ref.)

2. Clustering methods for generating discrete ('grey') levels from the constructed feature space (the levels are then typically mapped to the original image space at the anchor points of the templates)

3. Building co-occurrence matrices from a discrete level 'image' or a pair of discrete level 'images', where the discrete level 'images' are typically generated via feature space clustering of the original multimodal data sets (time series, images, space/time data...)

4. Estimation of various complexity/texture measures from the co-occurrence matrices. (Haralick measures and epsilon machine related quantities) such as:

   • CM Entropy
   • EM Entropy
   • Statistical Complexity
   • Energy Uniformity
   • Maximum Probability
   • Contrast
   • Inverse Difference Moment
   • Correlation
   • Probability of Run Length
   • Epsilon Machine Run Length
   • Run Length Asymmetry
   • Homogeneity
   • Cluster Tendency
   • Multifractal Spectrum Energy Range
   • Multifractal Spectrum Entropy Range

References:

• K. Young, Y. Chen, J. Kornak, G. B. Matson, N. Schuff, 'Summarizing complexity in high dimensions', Phys Rev Lett. (2005) Mar 11;94(9):098701.

• C. R. Shalizi and J. P. Crutchfield, 'Computational Mechanics: Pattern and Prediction, Structure and Simplicity', Journal of Statistical Physics 104 (2001) 819--881.

• K. Young and J. P. Crutchfield, 'Fluctuation Spectroscopy', Chaos, Solitons, and Fractals 4 (1993) 5-39.

• J. P. Crutchfield and K. Young, 'Computation at the Onset of Chaos', in Entropy, Complexity, and Physics of Information, W. Zurek, editor, SFI Studies in the Sciences of Complexity, VIII, Addison-Wesley, Reading, Massachusetts (1990) 223-269.

• C. R. Shalizi and J. P. Crutchfield, 'Computational Mechanics: Pattern and Prediction, Structure and Simplicity', Journal of Statistical Physics 104 (2001) 819--881.

How do I get set up?

• Compile the C-library from the gentex subdirectory.

python setup.py build_ext -i

• Run test.py to check if GenTex is running.

python ./test.py

• Have a pick at test_texture_measure() function in test.py to get started and write your own scripts.

Requirements

• Python 3.x or superior
• Numpy
• Scipy

Who do I talk to?

This module was developed by Karl Young and, to minor extend, by Nicolas Pannetier and Norbert Schuff.

License

GenTex is licensed under the terms of the BSD license. Please see the License file in the GenTex distribution