Skip to main content

A package to solve the sum of min/max equations

Project description

Github All Releases Github All Releases Github All Releases Github All Releases
About:
solve-sum-minmax 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, say you want to solve this equation: min(400, 500x) + min(200, 500x) + min(0, 500x) = 700 with the assumption that x is within range (0, 1).
In Math, the rigorous way would require you to set up all possible conditions, which might result in huge computation. Currently, there aren't any available packages in Python that allows you to solve this kind of equation fastly and efficiently. Thus, this package is developed to fill the void and hopefully be of use to the broad population.


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 solve-sum-minmax

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

>>> from solve-sum-minmax 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 solve-sum-minmax 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.

Format guide:
Because the module depends heavily on regular expressions, please follow the guide on how to define your equations carefully, or the module might break.
In a nutshell, wrap the equation you want to solve in a string with the format similar to the example:

>>> eq = "20 + max(600*a, 400) + min(200*a, 500) + min(100, 300*a) + 50*a = 600"

Before we delve into explanations in details, let's define a few terms:

  • value_term: the value you want to solve your equation for, here it's 600.
  • minmax_term: it is what it means in English, for example, max(600*a, 400).
  • cons_var_term: terms with constants times variables, such as 50*a.

In brief, what you can do include:

  • put the variable either in the 1st or 2nd place inside the parenthesis, for example, either min(200, 300*a) or min(300*a, 200) is fine.
  • use min and max together in one equation.
  • use + and/or -.
  • have constants in front of min or max, such as 2*min(400, 400a).
  • have any space between each component.
  • have leading 0s before variable, such as min(0*a, 200).
  • have constants inside min or max, such as min(20, 30).

What you can't do include:

  • use == instead of =.
  • for the cons_var_term, have variables before constants, such as a*50 instead of 50*a.
  • missing any parenthesis.
  • use other operators instead of + or -.
  • missing any necessary * operator for each variable.
  • put any constants on the left-hand side of the equation. Do me a favor, if you have any constants, subtract it from the right-hand side and rearrange your terms before using the module.

Limitations:

  • Currently, the module only supports "a" as the variable.
  • Because the module heavily depends on regular expressions, the user needs to follow the format of the equation carefully, or the module might break.
  • The equation must be uni-variate, i.e., there can only be one independent variable.

Version history:

Version Core Ideas Return Rationals Return Intervals Error Handling
v0.0.1 numerical methods No No No
v0.0.2 numerical methods No No No
v0.0.3 combinations Yes No No
v0.0.4 intervals Yes Yes No
v0.1.0 intervals Yes Yes Yes

Contact:

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

solve_sum_minmax-0.1.1-py3-none-any.whl (8.9 kB view details)

Uploaded Python 3

File details

Details for the file solve_sum_minmax-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: solve_sum_minmax-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 8.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.9.2

File hashes

Hashes for solve_sum_minmax-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 666680ce9353e1bcbd25bbe92f11d77f7362a491f1049d42f617775530c8e5c0
MD5 432efab72ea0300cb373062253c70a1c
BLAKE2b-256 4b2c421a7a690ac3d5c25a407502a6f49e74e8ebc39790f3e8cddb7fe04a12b7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page