# ANN: Measurements.jl v0.4.0

**URL:** <https://discourse.julialang.org/t/ann-measurements-jl-v0-4-0/3397>\
**Category:** Community\
**Tags:** announcement, measurements\
**Created:** [April 27, 2017, 8:02am UTC](https://discourse.julialang.org/t/ann-measurements-jl-v0-4-0/3397 "2017-04-27T08:02:57Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![giordano](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/giordano/32/2166_2.png) [@giordano](https://discourse.julialang.org/u/giordano)\
**Post date:** [July 10, 2017, 9:36am UTC](https://discourse.julialang.org/t/ann-measurements-jl-v0-4-0/3397/2 "2017-07-10T09:36:59Z")

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A couple of days ago, I tagged a new minor version of [`Measurements.jl`](https://github.com/JuliaPhysics/Measurements.jl), `v0.5.0`. This is the list of changes:

> ### Breaking Changes

> - `isinteger` and `iszero` now check also that the uncertainty is zero.
> - Comparison between `Measurement` and `Real` with `==` now compares also the  
> uncertainty, so that the `Measurement` must have uncertainty equal to zero to  
> be equal to a real number.
> - Comparison between `Measurement` and `Irrational` with `==` now gives always  
> `false`, consistently with the rest of `Real` types.

> ### New Features

> - New mathematical operations supported: `sinpi`, `cospi`, `sinc`, `cosc`,  
> `asec`, `acsc`, `acot`, `asech`, `acsch`, `acoth`, `sincos` (the last one only  
> on Julia 0.7).
> - It is now possible to parse a string as a `Measurement{T}` with any  
> `T<:AbstractFloat` (not only `Measurement{Float64}`), as long as the parsing  
> method is able to digest the string. Tested with `T` equal to `Float16`,  
> `Float32`, `Float64`, and `BigFloat`.

There is also a change under the hood, not mentioned above, inspired by [this thread](https://discourse.julialang.org/t/trouble-with-measurements-jl-and-bessel-functions/4562): it is possible to [define a macro](https://discourse.julialang.org/t/trouble-with-measurements-jl-and-bessel-functions/4562/6) to numerically propagate the uncertainty of a complex-valued function of one complex argument, not supported out-of-the-box by the package (like complex special functions).

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