New issue 1315: Place for domain-specific fields in the field documentation
https://bitbucket.org/yt_analysis/yt/issues/1315/place-for-domain-specific-…
Nathan Goldbaum:
Right now most of this sort of documentation lives in the analysis modules. We'd like to split off most of the analysis modules into their own packages but one or two will stay in the main yt package because all they do is add a few fields. We should move the documentation for these analysis modules into the field documentation.
Hi all,
Would anyone be interested in putting together some project ideas for
google summer of code?
OpenAstronomy will likely be applying to be an umbrella org and they've
asked me to indicate whether we'd like to participate again this year. Last
year we didn't end up getting many applications, so we should try to think
hard about writing good project ideas. We could also think about applying
under the NumFocus org instead of OpenAstronomy, since yt is increasingly
not only for astronomical simulation data.
Applications are due Feb 9, so please try to get back to me either here or
off-list so I can let the OpenAstronomy organizers know. If there's enough
interest I'll try to put together a video call so we can discuss our
portion of the application process.
-Nathan
Hi
Organizations can start submitting applications for Google Summer of Code
2017 on January 19 (and the deadline is February 9)
https://developers.google.com/open-source/gsoc/timeline?hl=en
NumFOCUS will be applying again this year. If you want to work with us
please let me know and if you apply as an organization yourself or under a
different umbrella organization please tell me as well. If you participate
with us it would be great if you start to add possible projects to the
ideas page on github soon. We some general information for mentors on
github.
https://github.com/numfocus/gsoc/blob/master/CONTRIBUTING-mentors.md
We also have a template for ideas that might help. It lists the things
Google likes to see.
https://github.com/numfocus/gsoc/blob/master/2017/ideas-list-skeleton.md
In case you participated in earlier years with NumFOCUS there are some
small changes this year. Raniere won't be the admin this year. Instead I'm
going to be the admin. We are also planning to include two explicit rules
when a student should be failed, they have to communicate regularly and
commit code into your development branch at the end of the summer.
best, Max
New issue 1311: [Ramses] add possibility to force cosmological
https://bitbucket.org/yt_analysis/yt/issues/1311/ramses-add-possibility-to-…
Corentin Cadiou:
Regarding discussions on pull request 2491, it would be great to be able to tell yt whether a simulation is a cosmological one by implementing an extra `force_cosmological` flag into the RAMSES data loader.
The code would override any detection of the nature of the simulation using the value given in the flag. This can be useful for some cosmological simulations running down to `z<0` with `H0=1` that are detected as non-cosmological ones.
New issue 1310: YTBoundsDefinitionError
https://bitbucket.org/yt_analysis/yt/issues/1310/ytboundsdefinitionerror
Corentin Cadiou:
HI,
I am doing a SlicePlot of a deposit field using the following code: `p = yt.SlicePlot(ds, 'z', ('deposit', 'all_cic'))`.
If I do the slice in the `x` or `y` directions, it works fine. But if I slice in the `z` direction, I get:
```
#!python
---------------------------------------------------------------------------
YTBoundsDefinitionError Traceback (most recent call last)
<ipython-input-11-d477c9a88f02> in <module>()
----> 1 p = yt.SlicePlot(ds, 'z', ('deposit', 'all_cic'))
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/visualization/plot_window.pyc
in SlicePlot(ds, normal, fields, axis, *args, **kwargs)
1999 del kwargs['north_vector']
2000
-> 2001 return AxisAlignedSlicePlot(ds, normal, fields, *args, **kwargs)
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/visualization/plot_window.pyc
in __init__(self, ds, axis, fields, center, width, axes_unit, origin, right_handed, fontsize, field_parameters, window_
size, aspect, data_source)
1324 slc = ds.slice(axis, center[axis], field_parameters=field_parameters,
1325 center=center, data_source=data_source)
-> 1326 slc.get_data(fields)
1327 validate_mesh_fields(slc, fields)
1328 PWViewerMPL.__init__(self, slc, bounds, origin=origin,
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in get_data(self, fields)
1331
1332 fields_to_generate += gen_fluids + gen_particles
-> 1333 self._generate_fields(fields_to_generate)
1334 for field in list(self.field_data.keys()):
1335 if field not in ofields:
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in _generate_fields(self, fields_to_generate)
1351 fi = self.ds._get_field_info(*field)
1352 try:
-> 1353 fd = self._generate_field(field)
1354 if fd is None:
1355 raise RuntimeError
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in _generate_field(self, field)
316 tr = self._generate_particle_field(field)
317 else:
--> 318 tr = self._generate_fluid_field(field)
319 if tr is None:
320 raise YTCouldNotGenerateField(field, self.ds)
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in _generate_fluid_field(self, field)
334 finfo.check_available(gen_obj)
335 except NeedsGridType as ngt_exception:
--> 336 rv = self._generate_spatial_fluid(field, ngt_exception.ghost_zones)
337 else:
338 rv = finfo(gen_obj)
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in _generate_spatial_fluid(self, field, ngz)
354 o = self._current_chunk.objs[0]
355 with o._activate_cache():
--> 356 ind += o.select(self.selector, self[field], rv, ind)
357 else:
358 chunks = self.index._chunk(self, "spatial", ngz = ngz)
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.p
yc in __getitem__(self, key)
279 return self.field_data[f]
280 else:
--> 281 self.get_data(f)
282 # fi.units is the unit expression string. We depend on the registry
283 # hanging off the dataset to define this unit object.
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.pyc in get_data(self, fields)
1331
1332 fields_to_generate += gen_fluids + gen_particles
-> 1333 self._generate_fields(fields_to_generate)
1334 for field in list(self.field_data.keys()):
1335 if field not in ofields:
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.pyc in _generate_fields(self, fields_to_generate)
1351 fi = self.ds._get_field_info(*field)
1352 try:
-> 1353 fd = self._generate_field(field)
1354 if fd is None:
1355 raise RuntimeError
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.pyc in _generate_field(self, field)
316 tr = self._generate_particle_field(field)
317 else:
--> 318 tr = self._generate_fluid_field(field)
319 if tr is None:
320 raise YTCouldNotGenerateField(field, self.ds)
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/data_containers.pyc in _generate_fluid_field(self, field)
336 rv = self._generate_spatial_fluid(field, ngt_exception.ghost_zones)
337 else:
--> 338 rv = finfo(gen_obj)
339 return rv
340
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/fields/derived_field.pyc in __call__(self, data)
218 "for %s" % (self.name,))
219 with self.unit_registry(data):
--> 220 dd = self._function(self, data)
221 for field_name in data.keys():
222 if field_name not in original_fields:
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/fields/particle_fields.pyc in particle_cic(field, data)
141 def particle_cic(field, data):
142 pos = data[ptype, coord_name]
--> 143 d = data.deposit(pos, [data[ptype, mass_name]], method = "cic")
144 d = data.apply_units(d, data[ptype, mass_name].units)
145 d /= data["index", "cell_volume"]
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/data_objects/octree_subset.pyc in deposit(self, positions, fields, method, kernel_name)
184 # We allocate number of zones, not number of octs
185 op = cls(nvals, kernel_name)
--> 186 op.initialize()
187 mylog.debug("Depositing %s (%s^3) particles into %s Octs",
188 positions.shape[0], positions.shape[0]**0.3333333, nvals[-1])
/home/cadiou/anaconda2/lib/python2.7/site-packages/yt-3.4.dev0-py2.7-linux-x86_64.egg/yt/geometry/particle_deposit.pyx in yt.geometry.particle_deposit.CICDeposit.initialize (yt/geometry/particle_deposit.c:8068)()
332 if not all(_ > 1 for _ in self.nvals):
333 from yt.utilities.exceptions import YTBoundsDefinitionError
--> 334 raise YTBoundsDefinitionError(
335 "CIC requires minimum of 2 zones in all dimensions",
336 self.nvals)
YTBoundsDefinitionError: This operation has encountered a bounds error: CIC requires minimum of 2 zones in all dimensions Specified bounds are (2, 2, 2, 1)
```
I am using the yt 3.4-dev version.
New issue 1309: passing in a data object to OffAxisProjectionDummyDataSource
https://bitbucket.org/yt_analysis/yt/issues/1309/passing-in-a-data-object-to
Hui Li:
Currently, OffAxisProjection can only analyze all_data() object. Would you please add a feature so that we can have the freedom to pass any 3D data object to this function as a "data_source" argument.
Hi all,
I just rolled out new version of hub.yt. Most notable changes:
* girder API was upgraded to 2.1.0.
* hub can now spawn different containers.
The latter is probably the most interesting feature. Before the update,
all you could do with the data was launching jupyter notebook that had
the proper files mounted. Right now when you try to run the notebook,
you'll be instead asked about your preferred "frontend" to expose the
data with.
Currently available frontends are: Jupyter Notebook and Jupyter Lab.
I know it's not really much of a choice, but it merely serves as a proof
of concept. The bottom line is: if you have a specific software that
you'd like to run with the data hosted on hub.yt, we can make that happen!
As always, if you notice anything not working, please let me know.
Cheers,
Kacper
