Measurements.jl
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Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical inte...
Currently, there is some LOVELY integration and fluidity between `Plots.jl` and this package. I guess this is acomplished by exporting a plotting-recipe for measurements. If I am not mistaken, Makie...
I need think more about this, but this doesn't look good at all performance-wise. Before PR: ``` julia> @benchmark measurement(1, 2,) BenchmarkTools.Trial: 10000 samples with 999 evaluations. Range (min …...
For some engineering applications, it is very helpful to use uniform distributions rather than Gaussian distributions. Examples include statistical geometric tolerance stacks, round-off noise in signal processing, and worst-case timing...
I'm happy to submit a pull request on this, I just want to confirm that the package devs are happy with this suggestion: add a ribbon option for the plot...
We could make `Measurement` type abstract, and define two concrete types, `IndependentMeasurement` and `DependentMeasurement` (the latter may be an [abuse of language](https://en.wikipedia.org/wiki/Abuse_of_language) but gives the idea): ``` julia abstract Measurement{T
Forgive me for etiquette and formatting issues, this is my first *real* github issue post. Further, if this wasn't the appropriate place to post problems like this, please let me...
Are you planning to support asymmetric errors like `2.0 + 0.1 - 0.05`?
Hi, thanks for this great package! I'm seeing some strange behavior with broadcasting. It's easy enough to work around, but still seems worth noting: ```julia julia> (zeros(3) .± 1) .±...
My main motivation behind this is that [MonteCarloMeasurements.jl](https://github.com/baggepinnen/MonteCarloMeasurements.jl) already overloads these, so I believe this would make for better interchangeability between both approaches. Personally, I also find them more convenient...