[yt-dev] [Bug] Halo Catalog units

Rasmi Elasmar re2300 at columbia.edu
Thu Jun 2 12:50:07 PDT 2016


Makes sense! PR submitted
<https://bitbucket.org/yt_analysis/yt/pull-requests/2208/added-halo-catalog-unit_registry-saving/diff>
-- let me know if that's good. Thanks for your help!

On Thu, Jun 2, 2016 at 3:15 PM, Nathan Goldbaum <nathan12343 at gmail.com>
wrote:

>
>
> On Thu, Jun 2, 2016 at 2:05 PM, Rasmi Elasmar <re2300 at columbia.edu> wrote:
>
>> Nathan,
>>
>> Sorry for the excess of questions. Should I implement the unit_registry
>> attr check here
>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/data_objects/static_output.py?at=yt&fileviewer=file-view-default#static_output.py-802>?
>> If so, how can I access the h5 dataset from there? If not, is here
>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/frontends/halo_catalog/data_structures.py?at=yt&fileviewer=file-view-default#data_structures.py-32>
>> better?
>>
>
> I would do it inside the `HaloCatalogDataset` class.
>
>
>> I don't know what the order of precedence is, so I don't want the
>> creation of the unit registry to be overwritten by the default one
>> _create_unit_registry call in the Dataset __init__. Is Particle File being
>> passed a Dataset that is already initiated with the default UnitRegistry?
>>
>
> You could add an implementation of _create_unit_regsitry to
> `HaloCatalogDataset` that supplements the implementation in the base class.
> First, call the superclass implementation, then if a registry is available
> in the output file, overwrite it inside `HaloCatalogDataset`. Something
> like this (using pseudocode here):
>
>     class HaloCatalogDataset(Dataset)
>
>     ... snip stuff that's already in this class ....
>
>         def _create_unit_registry(self):
>              super(HaloCatalogDataset, self)._create_unit_registry()
>              if registry in output_file:
>                   # replace the registry with what's in the output file
>
> -Nathan
>
>
>> On Thu, Jun 2, 2016 at 2:18 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>> wrote:
>>
>>>
>>>
>>> On Thu, Jun 2, 2016 at 1:16 PM, Rasmi Elasmar <re2300 at columbia.edu>
>>> wrote:
>>>
>>>> Hi Nathan,
>>>>
>>>> That approach sounds good. What do you think about this implementation?
>>>>
>>>>> import h5py
>>>>> import yt
>>>>
>>>>
>>>>
>>>> ds = yt.load('RD0009/RD0009')
>>>>> hc_file = h5py.File('halo_catalogs/catalog/catalog.0.h5')
>>>>
>>>>
>>>>
>>>> # Include unit_registry as an attribute
>>>>> hc_file.attrs['unit_registry'] = ds.unit_registry.to_json()
>>>>
>>>>
>>>>
>>>> # Or as a string dataset
>>>>> unit_registry_json = ds.unit_registry.to_json()
>>>>> str_type = h5py.special_dtype(vlen=str)
>>>>> unit_registry_h5 = hcfile.create_dataset('unit_registry_json',
>>>>> shape=(1,), dtype=str_type)
>>>>> unit_registry_h5[:] = unit_registry_json
>>>>
>>>>
>>>>
>>>> hc_file.close()
>>>>
>>>>
>>>>
>>>> # Regenerate unit_registry when loading the HaloCatalog?
>>>>> halos_ds = yt.load('halo_catalogs/catalog/catalog.0.h5')
>>>>> hc_file = h5py.File('halo_catalogs/catalog/catalog.0.h5')
>>>>> unit_registry_json = hc_file.attrs['unit_registry']
>>>>> halos_ds.unit_registry = yt.units.unit_registry.UnitRegistry.from_json(
>>>>> unit_registry_json)
>>>>
>>>>
>>>>
>>>> I'm not sure if including the unit_registry as an attribute or string
>>>> dataset is a better idea -- it seems to be an attribute in other parts
>>>> of the codebase
>>>> <https://bitbucket.org/yt_analysis/yt/src/c117d528f18ea412f8b80e8522a0595444e20ae8/yt/units/yt_array.py?at=yt&fileviewer=file-view-default#yt_array.py-796>
>>>> .
>>>>
>>>
>>> Either should be fine. I've actually been meaning to update the snippet
>>> you linked to use the JSON method, since pickles aren't portable across
>>> python versions, but we need to be careful to maintain backward
>>> compatibility with older files.
>>>
>>>
>>>>
>>>> Then, how do we get it to take the place of the halos_ds unit_registry?
>>>> Should this be done on creation in HaloCatalogDataset
>>>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/frontends/halo_catalog/data_structures.py?at=yt&fileviewer=file-view-default#data_structures.py-40>?
>>>> (i.e., check if the h5 file has a unit_registry attr, if so, load that, if
>>>> not use the current defaults?)
>>>>
>>>>
>>> Sounds good! Looking forward to the pull request that implements this.
>>>
>>>
>>>>
>>>> Thanks,
>>>>
>>>> Rasmi
>>>>
>>>> On Wed, Jun 1, 2016 at 1:01 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>>>> wrote:
>>>>
>>>>>
>>>>>
>>>>> On Wed, Jun 1, 2016 at 11:40 AM, Rasmi Elasmar <re2300 at columbia.edu>
>>>>> wrote:
>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> Greg and I found a bug involving halo catalog unit handling:
>>>>>>
>>>>>> >>> halo.quantities['particle_position_x']
>>>>>>> 0.495074982741 cm
>>>>>>> >>> halo.quantities['particle_position_x'].in_units('code_length')
>>>>>>> 0.495074982741 code_length
>>>>>>> >>> halo.quantities['particle_position_x'].in_units('cm')
>>>>>>> 0.495074982741 cm
>>>>>>> >>> ds.unit_registry['code_length']
>>>>>>> (9.195880139956267e+25, (length))
>>>>>>> >>> halos_ds.unit_registry['code_length']
>>>>>>> (1.0, (length))
>>>>>>
>>>>>>
>>>>>> The halos_ds mixes up cm and code_length units when the HaloCatalog
>>>>>> object is created from a saved halo catalog. The halo catalog values are
>>>>>> saved in code_length, but the HaloCatalog object assumes they are in cm.
>>>>>>
>>>>>> Here
>>>>>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/analysis_modules/halo_analysis/halo_catalog.py?at=yt&fileviewer=file-view-default#halo_catalog.py-453>
>>>>>> is where the code_length units are written out after halo-finding is done
>>>>>> (this is confirmed with an h5ls).
>>>>>> Here is where the halos_ds
>>>>>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/frontends/halo_catalog/data_structures.py?at=yt&fileviewer=file-view-default#data_structures.py-78> for
>>>>>> the HaloCatalog is created. The length unit is set in cm -- the catalog is
>>>>>> assumed to be in cgs.
>>>>>> The HaloCatalog fields
>>>>>> <https://bitbucket.org/yt_analysis/yt/src/b8a09cd382dd34f386ce3634e7f78df3f5d9401d/yt/frontends/halo_catalog/fields.py?at=yt&fileviewer=file-view-default#fields.py-21>
>>>>>> also assume cgs.
>>>>>>
>>>>>> In theory, the HaloCatalog could just parse the code_length units of
>>>>>> the halos_ds, but this isn't necessarily known at the time of creation, so
>>>>>> the ideal fix may be to save the halo catalog length units in cm instead of
>>>>>> in code_length. Then the assumptions that are made about length being in cm
>>>>>> when creating a HaloCatalog object from a halo catalog would be correct.
>>>>>> Any thoughts on this approach or other approaches?
>>>>>>
>>>>>>
>>>>> It would probably be better just to save the unit registry into the
>>>>> hdf5 file. You might find the UnitRegistry.to_json() and
>>>>> UnitRegistry.from_json() to be useful here - the json data could be saved
>>>>> in the HDF5 output file as a string dataset.
>>>>>
>>>>>
>>>>> https://bitbucket.org/yt_analysis/yt/src/yt/yt/units/unit_registry.py?at=yt&fileviewer=file-view-default#unit_registry.py-120
>>>>>
>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Rasmi
>>>>>>
>>>>>>
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