A question about the code for reading pseudopotentials

[A-006]

Describe the bug

in this expression,the pp.lchi[nw] - pp.jchi[nw] - 0.5,The result of this expression is always false. Should we calculate the absolute value of pp.lchi[nw] - pp.jchi[nw] to be around 0.5

Expected behavior

No response

To Reproduce

No response

Environment

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Additional Context

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[dyzheng]

@A-006 This code block try to dismiss SOC part of pseudopotential if the check of j == l + 0.5 or j == l - 0.5 fail, but there is a bug in it.
I'm interested that can you find a upf100 pseudopotential file with SOC but not comply with this j-l rule?

[A-006]

Thanks for your relpy,does it means that we can use the code as bellow
(abs(abs(pp.lchi[nw]-pp.jchi[nw])-0.5)<1e-7)
My understanding is that the rounding error range for single precision (float) is actually around 10e-7, while the rounding error range for double precision (double) is around 10e-14. Choosing a smaller range helps to reduce numerical errors？

I found it with TscanCode, which is a static code analysis tool. According to research on static code analysis, we can solve 30%-70% of the bugs in our program before we debug it when the problems happen. So, it's strongly recommended to use static code check tools. Actually, we can use three open-source code check tools: flawfinder, cppcheck, and TscanCode (most recommended!!!, [https://github.com/Tencent/TscanCode]

[mohanchen]

@A-006 This code block try to dismiss SOC part of pseudopotential if the check of j == l + 0.5 or j == l - 0.5 fail, but there is a bug in it. I'm interested that can you find a upf100 pseudopotential file with SOC but not comply with this j-l rule?

He has a background of computer science, he cannot understand your comment.