Comments (8)
dennisbrookner
commented on June 12, 2024
2
Just created a fresh conda environment with rs 0.9.3, and it works now. Not sure if the fresh environment or the update is what fixed it, but in either case, thanks!
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JBGreisman
commented on June 12, 2024
1
This seems likely to be a local environment issue, but I pushed a new PyPI release (0.9.3) so that all of the examples are consistent with the latest version available through pip install
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JBGreisman
commented on June 12, 2024
Based on the error traceback, it appears that the spacegroup attribute was not set when you loaded HEWL_unmerged.mtz. That is certainly strange, but do you mind confirming the hewl DataSet instance has all the expected fields?
Regarding the second part, rs.algorithms.merge() was added relatively recently and I haven't yet made an official PyPI release. I will do so shortly.
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JBGreisman
commented on June 12, 2024
I'm not quite able to reproduce the error locally with regard to the HEWL_unmerged.mtz:
> pwd
/Users/jgreisman/Documents/Hekstra_Lab/github/reciprocalspaceship/docs/examples
> rs.mtzdump data/HEWL_unmerged.mtz --embed
Spacegroup: P43212
Extended Hermann-Mauguin name: P 43 21 2
Unit cell dimensions: 79.344 79.344 37.810 90.000 90.000 90.000
mtz.head():
BATCH I SIGI PARTIAL
H K L
0 0 4 137 696.5212 87.83294 False
4 520 710.6812 88.107025 False
4 856 672.05634 87.75671 False
4 1239 642.47485 87.90302 False
4 2160 655.71783 87.74394 False
mtz.describe():
BATCH I SIGI
count 816804.000 816804.000 816804.000
mean 1720.375 606.572 82.154
std 1082.828 829.815 106.452
min 1.000 -12.324 0.192
25% 720.000 85.008 14.543
50% 2001.000 275.463 38.605
75% 2720.000 777.393 104.605
max 3439.000 9844.659 783.325
mtz.dtypes:
BATCH Batch
I Intensity
SIGI Stddev
PARTIAL bool
dtype: object
Python 3.8.5 (default, Sep 4 2020, 02:22:02)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.19.0 -- An enhanced Interactive Python. Type '?' for help.
rs.DataSet stored as mtz
In [1]: rs.algorithms.merge(mtz)
Out[1]:
IMEAN SIGIMEAN I(+) SIGI(+) I(-) SIGI(-) N(+) N(-)
H K L
0 0 4 661.29987 21.953098 661.29987 21.953098 661.29987 21.953098 16 16
8 3229.6492 105.980934 3229.6492 105.980934 3229.6492 105.980934 16 16
12 1361.8672 43.06085 1361.8672 43.06085 1361.8672 43.06085 16 16
16 4124.393 196.89108 4124.393 196.89108 4124.393 196.89108 8 8
1 0 1 559.3369 8.626299 559.3369 8.626299 559.3369 8.626299 64 64
... ... ... ... ... ... ... ... ...
14 11 20 35.6825 8.251703 NaN NaN 35.6825 8.251703 0 2
10 20 52.386147 10.075351 NaN NaN 52.386147 10.075351 0 2
9 20 122.96966 13.823673 NaN NaN 122.96966 13.823673 0 3
8 20 149.46716 13.995815 NaN NaN 149.46716 13.995815 0 4
11 7 20 25.917196 8.322451 NaN NaN 25.917196 8.322451 0 2
[12542 rows x 8 columns]
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dennisbrookner
commented on June 12, 2024
Both in jupyter and in terminal/IPython, the dataset does appear to have space group assigned. Here's what I just did, analogous to your example:
> pwd
/Users/dennisbrookner/crystallography/reciprocalspaceship/docs/examples
> rs.mtzdump data/HEWL_unmerged.mtz --embed
Spacegroup: P43212
Extended Hermann-Mauguin name: P 43 21 2
Unit cell dimensions: 79.344 79.344 37.810 90.000 90.000 90.000
mtz.head():
BATCH I SIGI PARTIAL
H K L
0 0 4 137 696.5212 87.83294 False
4 520 710.6812 88.107025 False
4 856 672.05634 87.75671 False
4 1239 642.47485 87.90302 False
4 2160 655.71783 87.74394 False
mtz.describe():
BATCH I SIGI
count 816804.000 816804.000 816804.000
mean 1720.375 606.572 82.154
std 1082.828 829.815 106.452
min 1.000 -12.324 0.192
25% 720.000 85.008 14.543
50% 2001.000 275.463 38.605
75% 2720.000 777.393 104.605
max 3439.000 9844.659 783.325
mtz.dtypes:
BATCH Batch
I Intensity
SIGI Stddev
PARTIAL bool
dtype: object
Python 3.8.5 | packaged by conda-forge | (default, Jul 31 2020, 02:18:36)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.19.0 -- An enhanced Interactive Python. Type '?' for help.
rs.DataSet stored as mtz
In [1]: rs.algorithms.merge(mtz)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/commandline/mtzdump.py in <module>
----> 1 rs.algorithms.merge(mtz)
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/algorithms/merge.py in merge(dataset, intensity_key, sigma_key, sort)
38
39 # Reshape anomalous data and use to compute IMEAN / SIGIMEAN
---> 40 result = result.unstack_anomalous()
41 result.loc[:, ["N(+)", "N(-)"]] = result[["N(+)", "N(-)"]].fillna(0).astype("I")
42 result["IMEAN"] = result[["wI(+)", "wI(-)"]].sum(axis=1) / result[["w(+)", "w(-)"]].sum(axis=1).astype("Intensity")
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/dataset.py in wrapped(ds, *args, **kwargs)
56 names = ds.index.names
57 ds = ds._index_from_names([None], inplace=True)
---> 58 result = f(ds, *args, **kwargs)
59 result = result._index_from_names(names, inplace=True)
60 ds = ds._index_from_names(names, inplace=True)
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/dataset.py in unstack_anomalous(self, columns, suffixes)
876 # Separate DataSet into Friedel(+) and Friedel(-)
877 columns = set(columns).union(set(["H", "K", "L"]))
--> 878 dataset = self.hkl_to_asu()
879 if "PARTIAL" in columns: columns.remove("PARTIAL")
880 for column in columns:
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/dataset.py in wrapped(ds, *args, **kwargs)
37 return f(ds, *args, **kwargs)
38 else:
---> 39 return f(ds.copy(), *args, **kwargs)
40 else:
41 raise KeyError(f'"inplace" not found in local variables of @inplacemethod decorated function {f} '
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/dataset.py in wrapped(ds, *args, **kwargs)
56 names = ds.index.names
57 ds = ds._index_from_names([None], inplace=True)
---> 58 result = f(ds, *args, **kwargs)
59 result = result._index_from_names(names, inplace=True)
60 ds = ds._index_from_names(names, inplace=True)
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/dataset.py in hkl_to_asu(self, inplace, anomalous)
975 hkls = dataset.get_hkls()
976 compressed_hkls, inverse = np.unique(hkls, axis=0, return_inverse=True)
--> 977 asu_hkls, isym, phi_coeff, phi_shift = hkl_to_asu(
978 compressed_hkls,
979 dataset.spacegroup,
~/miniconda3/envs/rs/lib/python3.8/site-packages/reciprocalspaceship-0.9.2-py3.8.egg/reciprocalspaceship/utils/asu.py in hkl_to_asu(H, spacegroup, return_phase_shifts)
82 an array length n containing phase shifts in degrees
83 """
---> 84 basis_op = spacegroup.basisop
85 group_ops = spacegroup.operations()
86 num_ops = len(group_ops)
AttributeError: 'NoneType' object has no attribute 'basisop'
In [2]: mtz.spacegroup
Out[2]: <gemmi.SpaceGroup("P 43 21 2")>
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JBGreisman
commented on June 12, 2024
What's your pandas version?
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dennisbrookner
commented on June 12, 2024
I have pandas 1.1.0. I'll uninstall and re-pip install, and see if that fixes it.
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JBGreisman
commented on June 12, 2024
Let me know if that works -- depending on the situation in that environment it also may be worth starting from a clean conda environment. That will at least make it easier for me to reproduce any issues on my end.
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Related Issues (20)
- Missing function call signature from Jedi-VIM autocomplete library HOT 3
- provide seed for reproducible creation of Rfree flags HOT 2
- Resolving indexing ambiguities when comparing datasets HOT 12
- Add `sample_rate` or `resolution_cutoff` options for `to_reciprocalgrid` HOT 5
- rs.DataSet.assign_resolution_bins ought to return bin edges HOT 1
- 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 6
- 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
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