Comments (1)
JBGreisman
commented on September 24, 2024
Currently, rs.read_precognition() is written to only support .ii integrated intensity files and .hkl scaled/merged HKL files.
I agree that it makes sense to support CSV files without needing to go through a pandas.DataFrame because it is such a general / widely-used file format. This support can easily be added by wrapping a call to pd.read_csv() and adding an additional infer_dtypes boolean flag or something like that as you included.
For this specific case, it may be worth adding .spt files to the supported file formats in rs.read_precognition(). At the very least, I should update the docstring to specify the supported files.
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Related Issues (20)
- 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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