[yt-dev] YT field detection

[Douglas Harvey Rudd]

Hi Matt,

Okay, I'll try to add it to camera.py and tack it on my bugfix PR.  I tried my original suggestion, naming the field ( field[0], "temp_weightfield" ) but that created ("d","temp_weightfield") in at least one test that passed in "density" rather than a tuple.

Douglas Rudd
Scientific Computing Consultant
Research Computing Center
drudd at uchicago.edu



On Aug 30, 2014, at 7:09 AM, Matthew Turk <matthewturk at gmail.com> wrote:

> Hi Doug,
> 
> Thanks for going through and looking into this.
> 
> On Fri, Aug 29, 2014 at 3:07 PM, Douglas Harvey Rudd <drudd at uchicago.edu> wrote:
>> Hi all
>> 
>> I have a set of fixes for Issue #887 (field detection). Most apply without breaking any tests, but to address all of the problems in that issue I need to add a check to YTDataContainer._determine_fields that doesn't allow a field to be added if it doesn't exist in field_list or derived_field_list.
> 
> That sounds good to me.
> 
>> 
>> This fixes my bug, but breaks a test based on code in yt/visualization/volume_rendering/camera.py which adds a field "temp_weightfield" (not a tuple!).
> 
> Whoops, that should be a tuple!  :)  Does it use ds.add_field?  That
> should ensure it gets added to the derived_field_list.
> 
>> 
>> When this field is passed to _determine_fields, _get_field_info first guesses at ("gas","temp_weightfield"), but since that doesn't exist in field_info, it replaces it with ("index","temp_weightfield"), which I don't see as being any better.
> 
> I would slightly prefer "index" over "gas" just because "index"
> indicates it's an internal field.
> 
>> 
>> There are several places where the syntax _get_field_info(*field) is used, which will break when field is a string, not a tuple.  Should I fix camera.py to use an explicit fluid type?  If so, what?  I've tried to use the fluid type of the input field, but that apparently is also not always a tuple.
> 
> I think fixing camera.py is good, and I would go with "index".
> 
>> 
>> e.g.
>>        fields = [field]
>>        if self.weight is not None:
>>            self.weightfield = (field[0], "temp_weightfield")
>>            # This is a temporary field, which we will remove at the end.
>>            def _make_wf(f, w):
>>                def temp_weightfield(a, b):
>>                    tr = b[f].astype("float64") * b[w]
>>                    return b.apply_units(tr, a.units)
>>                    return tr
>>                return temp_weightfield
>>            ds.field_info.add_field(self.weightfield,
>>                function=_make_wf(self.field, self.weight))
>>            # Now we have to tell the dataset to add it and to calculate
>>            # its dependencies..
>>            deps, _ = ds.field_info.check_derived_fields([self.weightfield])
>>            ds.field_dependencies.update(deps)
>>            fields = [self.weightfield, self.weight]
>> 
>> Douglas Rudd
>> Scientific Computing Consultant
>> Research Computing Center
>> drudd at uchicago.edu
>> 
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