[yt-dev] [Bug] Halo Catalog units

Thu Jun 2 12:05:36 PDT 2016

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 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?

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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>>>>
>>>>
>>>
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