Fetch float16 and float128 with h5grove as binary using dtype=safe
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dtype=safedtype=safe
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| Infinity, |
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The maximum finite float128 value gets converted to float64 Infinity. I would have expected Numpy to clamp it to the maximum finite float64 value instead. 🤔
Now that I think of it, a similar thing happens with the smallest float128 value greater than 0 (the value of the float128_scalar dataset in the sample file) => h5grove sends 0 in float64 — not the smallest float64 value greater than 0, as I would have expected.
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The maximum finite float128 value gets converted to float64 Infinity
Sounds like a safe behaviour. It would be weird to convert a finite value to another while you know it's not the same value.
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It would be weird to convert a finite value to another while you know it's not the same value.
That's exactly what happens when you cast an int64 to int32, though. Obviously inf cannot be represented in int32, but still, in float, it's a special value... The rounding to 0 makes more sense in that regard.
I'm just asking in case the code in h5grove is wrong somehow — maybe the float128 are cast by Python before numpy can convert them properly, or something of the sort. 🤷
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Sorry, took a while to get back to this and I would need some context to refresh my mind. Why using |
No worries! There's no When fetching float16/128 datasets with |
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