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I think there is a lot of value to not having yt 3.0 be jarring to users when they are introduced to it. I think we are wrestling with a trade-off between drawing technical distinctions and not making for a difficult transition for the user, as well as those that work on this.
So far, yt does a pretty good job figuring out on its own the nature of the field that's being requested. I propose that we have both obj.fluid['whatever'] and obj.particles['whatever'] as means of explicitly stating the type of field being requested, but that we also allow for obj['whatever'] and let yt try to figure it out first. If yt can't figure out what type of field it's being asked to get, it can throw an exception and ask for specific direction.
Would this satisfy people?
On Mon, Feb 27, 2012 at 3:18 PM, Stephen Skory firstname.lastname@example.org wrote:
I've been thinking about things, and this actually dovetails onto Chris' comments as well, I think. The way I see it, in order to get to data from a dataset, here are the abstract levels yt goes through:
What we're struggling with is where to put level #3 in our syntax. As we currently have it, it's done at the finest level with the generalized dict access for a specific thing (dd["x"], dd["ParticleMass"], dd["DerivedField"]), and yt works out the rest. I don't know if I myself like this idea, but we might want to consider putting the Data Type specification up higher. For example we could have Data Type-specific data containers (dd_fluid = pf.h.all_data("fluid")). Or, I like this even less, but it's conceivable that there could be a Data Type-specific load (pf_parts = load("DD1234", "particles").
I'm not making any suggestions here, I just want to see if anyone sees any benefit from changing the level at which Data Type is specified? Feel free to say "no, stupidest idea since lawn darts." I'm not convinced it isn't.
-- Stephen Skory email@example.com http://stephenskory.com/ 510.621.3687 (google voice)
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