ufunc identity of -inf #7702
Comments
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Fyi the function already exists as np.logaddexp |
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I guess the question then becomes whether |
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@njsmith Wow, thanks, I had thought I checked well enough... ;) |
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@mhvk I don't necessarily agree: someone could be indexing a plain array to filter instead of using a ma, or someone could be initializing a result for a generic reduce where some of the loops are plain-old for loops (not over an array that actually exists) so you don't have to build the whole thing in memory. (The latter was my application.) It's a little more work to specialcase the first value even if I require it to exist. It does look like it might be more trouble / complication-adding than it's worth to add the ability to have an identity of -inf, but I think there is some utility to it. |
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Adding -inf from within numpy is reasonably easy, we recently added the -1, so you could find a template on how to do it. I would not mind if we had a way of defining the identity more specific, though. One could also think about an |
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If we want to allow arbitrary identity values, I think we should pull out There was another recent PR about identity at #8255 |
There didn't seem to be any value to a `assign_identity` function - all we actually care about is the value to assign. This also fixes numpy#8860 as a side-effect, and paves the way for: * easily adding more values (numpy#7702) * using the identity in more places (numpy#834)
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Many thanks, @eric-wieser |
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I'm afraid this is a way off from being merged since it would break the ufunc abi, so I'd prefer to leave this open. |
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Oops, I misread (I thought it was merged). Thanks all the same :) |
There didn't seem to be any value to a `assign_identity` function - all we actually care about is the value to assign. This also fixes numpy#8860 as a side-effect, and paves the way for: * easily adding more values (numpy#7702) * using the identity in more places (numpy#834)
I would like to write a function that, given
log(x)andlog(y), will computelog(x + y). The identity for this islog(0) = -inf. Currently, numpy only allows the values of 0, 1, -1, andNone, as far as I can tell. It would be nice for my purposes if -inf or an arbitrary value could be used.The text was updated successfully, but these errors were encountered: