0.75 to 0.95 vs.0.75 to 0.9 is strictly my transcription bug, not being careful enough.
In general I wasn’t auditing the code from the Jonas Moss comment, I just stepped through looking at the functionality. I should’ve been more careful, if I was going to make a claim about the conversion factor.
You’re kinda right about the question “if it’s a constant number of lines written exactly once, does it really count as boilerplate?” I can see how it feels a little dishonest of me to imply that the ratio is really 15:1. The example I was thinking of was the Biological Anchors Report (“Ajeya’s Timeilnes”), those notebooks have lots of LOC in hidden cells, but the relative cost of those goes down as the length of the report goes up. All that considered, I could be updated to the idea that the boilerplate point is moot for power users (who are probably able and willing to provide that boilerplate once per file), but I would still be excited about what is opened up for more casual users.
You’re right that, or your comment is suggesting to me indirectly that, squiggle, having not yet provided a way to give non-default quantiles with the to syntax, hasn’t done anything to show that it’d really beat hand-crafted python functions, to accomplish this.
Re the underlying squiggle notebook concerning GiveDirectly and so on, I’ve flagged your comment to Sam (it’s something else I haven’t taken a close look at).
Thanks for the flag! I might not be understanding correctly, but I don’t think there’s a problem here with the actual underlying code just my explanation of it (we all hate magic numbers). Which is very fair enough, the notebook is much too dense for my liking. It’s still a work in progress!
I agree! The Squiggle team is looking to create different quantiles for different distributions. I’ve needed them on several occasions. You can check out the discussion on GitHub here. It’s on my todo list.
Thanks!
0.75 to 0.95vs.0.75 to 0.9is strictly my transcription bug, not being careful enough.In general I wasn’t auditing the code from the Jonas Moss comment, I just stepped through looking at the functionality. I should’ve been more careful, if I was going to make a claim about the conversion factor.
You’re kinda right about the question “if it’s a constant number of lines written exactly once, does it really count as boilerplate?” I can see how it feels a little dishonest of me to imply that the ratio is really 15:1. The example I was thinking of was the Biological Anchors Report (“Ajeya’s Timeilnes”), those notebooks have lots of LOC in hidden cells, but the relative cost of those goes down as the length of the report goes up. All that considered, I could be updated to the idea that the boilerplate point is moot for power users (who are probably able and willing to provide that boilerplate once per file), but I would still be excited about what is opened up for more casual users.
You’re right that, or your comment is suggesting to me indirectly that, squiggle, having not yet provided a way to give non-default quantiles with the
tosyntax, hasn’t done anything to show that it’d really beat hand-crafted python functions, to accomplish this.Re the underlying squiggle notebook concerning GiveDirectly and so on, I’ve flagged your comment to Sam (it’s something else I haven’t taken a close look at).
Thanks for the flag!
I might not be understanding correctly, but I don’t think there’s a problem here with the actual underlying code just my explanation of it (we all hate magic numbers). Which is very fair enough, the notebook is much too dense for my liking. It’s still a work in progress!
I agree! The Squiggle team is looking to create different quantiles for different distributions. I’ve needed them on several occasions. You can check out the discussion on GitHub here. It’s on my todo list.
Just letting you know that you seem to have double-pasted the 3rd bullet point.
oof, good catch, fixed.