Porespy

🚀 New features
New visualization functions
- Added ``show_3D`` to visualization module. This function rotates the image along two axes and returns a 2D view from an angle for simple viewing with matplotlib's ``imshow``.

New filters
- Added ``trim_small_clusters``. This function allows the removal of all features small than a threshold size.
- Added ``hold_peaks`` function: This function finds the highest greyscale value along in each slice along a given axis.
- Added the ``prune_branches`` function. Given an image skeleton, this removes all dangling branches.

Improved generators
- Loosened tolerance for polydisperse generator test
- Switched default solver in sphere generator to bisection method
- Enhanced cylinders function to accept length argument

Minor changes
- Changed ``trim_disconnected_blobs`` to make a copy of input image
- Allowed get_border to optionally return indices as well as mask
- Cleaned many docstrings throughout package (need to install a spell checker on IDE!)

🐛 Bugfixes
- Fixed bug in snow_extraction that resulted in some negative throat lengths
- Fixed bug in ``trim_disconnected_blobs``. Note this bug was also impacting ``porosimetry`` when an inlet mask was provided.

This minor release is a major event in PoreSpy development. We have submitted our package to the Journal of Open Source Software, which will create an official DOI that users can refer to in any papers that use PoreSpy. Thanks to JOSS for being such an excellent and smoothly functioning journal, and thanks to all the contributors in the PMEAL group and elsewhere.

More preparations for JOSS release

At the time of this release there were only 7 open issues on the Github issue tracker, and most were feature requests. The following general areas were tackled:

- Enhanced documentation by adding extra citations to functions, fixing typos, improve the quality of figures throughout, added a contributor guide
- Added pseudo-manuscript to the package highlight the motivation for
- Improved test coverage, nearly 90%
- Moved all examples from a separate repo into a folder within the main package
- Fixed numerous bugs and instabilities
- Refactored the code in numerous locations (e.g. SNOW algorithms are now discrete functions that can be called individually)

This minor release adds a few components to the package that are necessary for the JOSS review, including a license (MIT) and a file called paper.md which gives a brief synopsis of the package.

This is the official release of PoreSpy Version 1.0. We've been working on this package for more than a year, adding new functions, fine tuning the old functions, and generally optimizing the organization of things. During this period, things have been breaking and changing, so we are happy to say that it is finally stable and ready for all to use.

- For information about what's in the package, refer to the [readme on Github](https://github.com/PMEAL/porespy/blob/dev/README.rst).

- For a gallery of examples showing how to use the package for various porous media related tasks, see the [examples folder](https://github.com/PMEAL/porespy/tree/dev/examples) containing Jupyter notebooks.

- Any questions about using the package, bug reports, feature requests, and suggestions, should be directed to the [Github Issues page](https://github.com/PMEAL/porespy/issues).

- Finally, we plan to submit a pseudo-paper to the [Journal of Open Source Software](https://joss.theoj.org/) so that users may reference the software in any publications that relies on it.

Thanks to all the members of the Porous Materials Engineering and Analysis Lab in the Department of Chemical Engineering at the University of Waterloo for their hard work on this:

TomTranter
mdrkok
ma-sadeghi
Zohaib-Atiq
magnaou
Ni2M
jgostick