Comments (3)
This occurs because DataSet.stack_anomalous()
removes the suffixes from anomalous columns during this method. It then eventually calls ds["I"]
, which would ordinarily return a DataSeries
which has a from_friedel_dtype()
method. However, since there are now two columns with the label "I", this call now returns a DataSet
.
I'm considering this a bug, because it is certainly unexpected behavior. To resolve it, there are a few possible options in my mind:
- This behavior could be fixed by changing the column names later in the method. Although this would resolve this error, there would still be columns with the same name in the resulting
DataSet
. This will likely cause downstream problems. - One could raise a
ValueError
when this case is detected. This can then give a more sensible error message like "This operation will result in two or more columns with the same name" - We could do (2), but also add a
only_keep_friedels=True
flag that removes any non-Friedel columns with this operation. In the above example, this would drop the original "I" column, and output aDataSet
with an "I" column generated from "I(+)" and "I(-)".
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In the case of solution 2 (or perhaps 3 as well), I'd be happy to tackle this; it's similar to the change I made a little while back, and is still pretty fresh on my mind.
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Awesome -- sounds good! Kevin's example will also make a good template for writing a test. Reach out if you run into trouble.
I'm inclined to suggest starting with (2), because (3) can currently be implemented by the user by dropping desired columns.
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Related Issues (20)
- Cannot unstack_anomalous with other columns in index
- groupby apply drops cell and spacegroup HOT 2
- `stack_anomalous` inside `groupby` breaks `as_index=False` HOT 1
- Unstack anomalous taking into account Careless repeats HOT 10
- rs.utils.asu.in_asu() does not use the 'anomalous ASU' for stacked anomalous data. HOT 1
- function for cif file IO and possible support for multi-dataset files HOT 3
- `hkl_to_asu` does not annotate M/ISYM field correctly HOT 2
- support for read_precognition() for hkl without anomalous columns HOT 6
- unstack_anomalous makes data that phenix cannot interpret HOT 3
- API reference website display
- Return keys of dictionary in crystfel.py HOT 8
- add_rfree() does not consider Friedel mates HOT 2
- `rs.DataSet.reset_index()` call signature does not match pandas >1.5 HOT 1
- Used pandas.core.ops attribute does not appear to exist HOT 4
- A `rs.cifdump` utility? HOT 1
- No documentation of CrystFEL columns HOT 1
- mean_intensity_by_miller_index should use a grid HOT 1
- write_mtz SettingWithCopyWarning HOT 2
- Failure to correctly read Miller indices from cctbx-generated MTZ HOT 8
- RS requires set_index(["H","K","L"]) to create a multi_index using rs.DataSet HOT 5
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