QuantEcon/QuantEcon.jl

Use `StableRNGs` in tests

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#275 建立於 2022年7月5日

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描述

@oyamad asked me to expand my comment in #274 into an issue. Here it is.

A lot of tests currently depend on outcomes of simulations. In order to get reproducible results, the tests set seeds. However the random number streams are not guaranteed to be the same across Julia versions. This led to the problem visible in #274: a test suddenly broke on Julia 1.7 and above.

In order to avoid this one can use the package https://github.com/JuliaRandom/StableRNGs.jl, which guarantees reproducible streams of random numbers across Julia versions.

I am afraid that this would require rewriting some of the functionality of this package to accept an RNG as in

rng = StableRNG(seed::Integer) # random number generator object
rand(rng, X)

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領域
testing
議題類型
test
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
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清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
Julia basicsFamiliarity with RNG in JuliaUnderstanding of test setup
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
65
研究方向
First, review the test files in the repository (likely under a `test/` directory) to find instances where `rand` is called with a seed. Then, import the `StableRNGs` package and modify each test to create a `StableRNG` object and pass it to `rand`. Ensure that the changes do not alter the expected test outcomes. Check the linked issue #274 for context on the Julia version compatibility issue.