units
equational-reasoning
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units | equational-reasoning | |
---|---|---|
1 | - | |
94 | 51 | |
- | - | |
5.3 | 5.8 | |
3 months ago | 4 months ago | |
Haskell | Haskell | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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units
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Frink is a programming language designed to make physical calculations simple
It seems to me that Haskell would be a great language for such a thing, ensuring correctness at compile time through the type system, e.g. using the units package https://hackage.haskell.org/package/units https://github.com/goldfirere/units/tree/master/units
It even has nice features like: "The laws of nature have dimensions, and they hold true regardless of the units used. For example, the gravitational force between two bodies is (gravitational constant) * (mass 1) * (mass 2) / (distance between body 1 and 2)^2, regardless of whether the distance is given in meters or feet or centimeters. In other words, every law of nature is unit-polymorphic."
"The units package supports unit-polymorphic programs ..."
equational-reasoning
We haven't tracked posts mentioning equational-reasoning yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
smtlib2 - SMTLib2 interface implementation for Haskell
continued-fractions - Haskell library for manipulating and evaluating continued fractions
polynomial - Haskell library for manipulating and evaluating polynomials
lambda-calculator - An introduction to the Lambda Calculus
uncertain - Manipulating numbers with inherent measurement/experimental uncertainty.
optimization - Some numerical optimization methods implemented in Haskell
monte-carlo - A Monte Carlo monad and transformer for Haskell.
nimber - Finite nimber arithmetic
dimensional - Dimensional library variant built on Data Kinds, Closed Type Families, TypeNats (GHC 7.8+).
cf - "Exact" real arithmetic for Haskell using continued fractions (Not formally proven correct)
matrix - A Haskell native implementation of matrices and their operations.
bayes-stack - Framework for Gibbs sampling of probabilistic models