solveminmax is a Python module that allows you to solve a sum of min/max equations by taking advantage of the powerful sympy library.
For instance, you can solve min(400, 500x) + min(200, 500x) + min(0, 500x) = 700 with the assumption that x is within range (0, 1).

Documentation: https://hegelim.github.io/solveminmax/

Legacy Note:
From v0.1.0, the former module, solve-sum-minmax was renamed to solveminmax so that it follows the Python naming conventions.

Quick Start:
Let's say you want to solve the equation min(500, 600a) + max(400, 500a) = 500. However, solving it in Math means you would have to set up the conditions, then solve the check for each one of them, which sounds like a lot of work, especially for smart people like you who know how to take advantage of existing tools. So you ask yourself, "What if there is a library that lets me solve it like a piece of cake?" Well, there is a library for you now! First off, you need to install it via pip in your terminal like below:

pip install solveminmax

Or, you can directly clone the project in your local repo and install it using setup.py like below:

git clone https://github.com/Hegelim/solveminmax.git
python setup.py install

Then to solve your problem, simply type in these codes in your Python console:

>>> from solveminmax import solver
>>> eq = "min(500, 600*a) + max(400, 500*a) = 500"
>>> solver.auto_solve(eq, "a")
FiniteSet(1/6)

Whola! In fact, this is a pretty complex problem, but you just solved it with 3 lines of code. But hold on, what does it mean? Let's break it down: the core function auto_solve takes in two required parameters equation and var_name. equation takes in a string of the equation you want to solve and var_name lets you define your variable with flexibility, such as "a" or "x", although currently, it only supports "a". You can also pass in "low", "high", which lets you specify the range of your variable. Further details are included in the docstring if you are interested.

Perks:

• Fast: the module solves a set of complex min and max equations usually under 100 ms, depending on your hardware. For example, for an equation as complex as below, it takes 7 ms on average to give you a solution:

>>> from solveminmax import solver
>>> eq = "max(600*a, 400) + min(200*a, 500) + min(100, 300*a) + 50*a = 600"
>>> %timeit solver.auto_solve(eq, "a")
FiniteSet(4/11)
7.1 ms ± 225 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

• Accurate: it handles exact Rational numbers and intervals.

• Flexible：you have a lot of flexibility in defining your equation, see below.

• Versatile: start from v0.1.4, you can plot your equation and check your results visually. An example is:

>>> from solveminmax import plot
>>> eq = "-2*min(300, 400*a) = -600"
>>> plot.make_plot(eq, "a")

Version history:

For more information, check the documentation.

Contact:

• Email: yz4175@columbia.edu
• Collaboration: collaborations are welcomed, please email me if you are interested.