Scikit-Fuzzy version 0.4.2

This minor point release brings forward compatibility with NetworkX 2.4, which removed some prior methods of interactive with directed graphs. The changes remain backward compatible.

Thanks to @wouter-vdb for the fixes contained herein.

The release is live on PyPi, installable via pip and will shortly be live on conda-forge.

Scikit-Fuzzy version 0.4.1

This minor point release brings a number of improvements, most importantly compatibility with Python 3.7. Also:

• The number of membership functions is no longer restricted in automf (#206)
• Improvements to the documentation, especially for Consequents

In addition to the source release here, 0.4.1 is now live on PyPi.

Install/upgrade with

pip install -U scikit-fuzzy

Scikit-Fuzzy version 0.4.0

This major point release brings bug fixes, efficiency improvements, and quality of life improvements.

• A bug was fixed in the lom/som methods; negative range now fully supported (#189)
• Significant efficiency gains by streamlined linear algebra (#187) (#156)
• Names of nodes in the control system graph can now be displayed (#166)
• Numerical improvement to cmeans for values of m close to 1.0 (#154)

In addition to the source release here, 0.4.0 is now live on PyPi.

Install/upgrade with

pip install -U scikit-fuzzy

Scikit-Fuzzy 0.3.1

This minor point release brings a significant new feature and minor fixes/compatibility enhancements:

Major feature:

• Arrays are now accepted as system inputs; all inputs must have the same shape. The output matches this shape. This is dramatically more computationally efficient for repeated runs on existing data - within the limits of your system memory. (see #141)

Major fix

• Fixed the mathematical definition of skfuzzy.gaussmf; this is a potentially breaking change but the results are now correct (see #147).

Minor fixes

• NetworkX 2.0 forward compatibility (see #149 and #150)
• Improve and harmonize the .view() methods in skfuzzy.control (see #142 and #148)
• Update examples to use the above

Scikit-Fuzzy 0.3

This major point release includes a number of improvements, primarily to the skfuzzy.control submodule. A significant bug was squashed, the entire system is markedly more performant, and users can now more intuitively control the aggregation method.

• Fixed a memory leak on repeated, cached simulations not entirely flushing the cache (#120)
• AND/OR aggregation methods are now directly exposed to the user (#126)
• np.interp is used under the hood, resulting in major performance improvements (#130)
• System visualization commands uniformly return both Matplotlib fig/axis objects, and better documented (#133/#136)

Thanks for using Scikit-Fuzzy, your reports keep making the package better!

Scikit-Fuzzy 0.2

This major point release brings many improvements to Scikit-Fuzzy, notably

• New fuzzy control system API
  • Explore the new features located in skfuzzy.control. Recommended import statement is import skfuzzy.control as ctrl - note these new classes are not brought into the main skfuzzy namespace, they live only in skfuzzy.control.
  • Designing complicated fuzzy control systems is now elegant, expressive, and Pythonic
  • Peruse the new examples (reworked tipping problem and an advanced system) in the gallery
• New, more accurate defuzzification calculations result in higher accuracy with even sparser systems
• Significantly improved documentation and test coverage.