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pyDGS

a Python framework for wavelet-based digital grain size analysis

May - 2018 UPDATE: The online version of pyDGS has been retired. We encourage you to use it standalone as a pip module.

About

pyDGS is an open-source project dedicated to provide a Python framework to compute estimates of grain size distribution using the continuous wavelet transform method of Buscombe (2013) from an image of sediment where grains are clearly resolved. DOES NOT REQUIRE CALIBRATION

This program implements the algorithm of:

Buscombe, D. (2013) Transferable Wavelet Method for Grain-Size Distribution from Images of Sediment Surfaces and Thin Sections, and Other Natural Granular Patterns. Sedimentology 60, 1709-1732

Install:

From a shell with python and pip installed type the following:

python setup.py install
sudo python setup.py install
pip install pyDGS

Test:

You can run pyDGS tests using the following script:

python -c "import DGS; DGS.test.dotest()"

REQUIRED INPUTS:

image name e.g. '/home/sed_images/my_image.png'

OPTIONAL INPUTS

[default values][range of acceptable values]

OUTPUT FOR A SINGLE IMAGE FILE:

A dictionary objects containing the following key/value pairs:

Processing example on 1 image:

From a terminal with pyDGS already installed using pip:

$ python

Python 3.6.5 (default, Apr 11 2018, 10:42:01)
[GCC 4.2.1 Compatible Apple LLVM 9.1.0 (clang-902.0.39.1)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>

Then, once you’re in the python terminal (or as a separate .py file):

import DGS

image_file = '/home/sed_images/my_image.png'

density = 10 # process every 10 lines
resolution = 0.01 # mm/pixel
dofilter =1 # filter the image
notes = 8 # notes per octave
maxscale = 8 #Max scale as inverse fraction of data length
verbose = 1 # print stuff to screen
x = -0.5
dgs_stats = DGS.dgs(image_file, density, resolution, dofilter, maxscale, notes, verbose, x)

REQUIRED INPUTS:

simply a single file path

OPTIONAL INPUTS

[default values][range of acceptable values]

OUTPUT:

A dictionary objects containing the following key/value pairs:

PROCESSING NOTES:

Note that the larger the density parameter, the longer the execution time.

License:

GNU Lesser General Public License, Version 3
(http://www.gnu.org/copyleft/lesser.html)

This software is in the public domain because it contains materials that
originally came from the United States Geological Survey, an agency of the
United States Department of Interior. For more information, 
see the official USGS copyright policy at
http://www.usgs.gov/visual-id/credit_usgs.html#copyright
Any use of trade, product, or firm names is for descriptive purposes only 
and does not imply endorsement by the U.S. government.

Note for Windows Users

I recommend the Anaconda python distribution for Windows which includes all of the library dependencies required to run this program. Anaconda comes with a variety of IDEs and is pretty easy to use. To run the test images, launch the Anaconda command terminal and type:

pip install pyDGS
python -c "import DGS; DGS.test.dotest()"

Contributing & Credits

This program implements the algorithm of Buscombe, D. (2013) Transferable Wavelet Method for Grain-Size Distribution from Images of Sediment Surfaces and Thin Sections, and Other Natural Granular Patterns, Sedimentology 60, 1709 - 1732

Author: Daniel Buscombe
Northern Arizona University
Flagstaff, AZ 86001
daniel.buscombe@nau.edu

Revision: Dec 21, 2017
First Revision: January 18 2013

For more information visit https://github.com/dbuscombe-usgs/pyDGS

https://www.danielbuscombe.com/s/Buscombe_2013_sedimentology_101111-sed12049.pdf

Please contact: daniel.buscombe@nau.edu

to report bugs and discuss the code, algorithm, collaborations

For the latest code version please visit: https://github.com/dbuscombe-usgs

See also the project blog: http://dbuscombe-usgs.github.com/

Please download, try, report bugs, fork, modify, evaluate, discuss. Thanks for stopping by!