Bug: Energy scan requires hinting during loadRun #193
Description
Following up from updates made in PR #179. Scan ID 93983 is an energy scan (single image per energy) and loads fine with dims=["energy"] hinted but throws an error without hinting.
scan = loader.loadRun(run=93983).unstack('system')
Error:
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[10], line 1
----> 1 scan = loader.loadRun(run=93983).unstack('system')
2 scan
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\PyHyperScattering\SST1RSoXSDB.py:740, in SST1RSoXSDB.loadRun(self, run, dims, coords, return_dataset, useMonitorShutterThinning)
737 dims_to_join.append(val)
738 dim_names_to_join.append(key)
--> 740 index = pd.MultiIndex.from_arrays(dims_to_join, names=dim_names_to_join)
741 # handle the edge case of a partly-finished scan
742 if len(index) != len(data["time"]):
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\pandas\core\indexes\multi.py:533, in MultiIndex.from_arrays(cls, arrays, sortorder, names)
530 if len(arrays[i]) != len(arrays[i - 1]):
531 raise ValueError("all arrays must be same length")
--> 533 codes, levels = factorize_from_iterables(arrays)
534 if names is lib.no_default:
535 names = [getattr(arr, "name", None) for arr in arrays]
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\pandas\core\arrays\categorical.py:3069, in factorize_from_iterables(iterables)
3065 if len(iterables) == 0:
3066 # For consistency, it should return two empty lists.
3067 return [], []
-> 3069 codes, categories = zip(*(factorize_from_iterable(it) for it in iterables))
3070 return list(codes), list(categories)
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\pandas\core\arrays\categorical.py:3069, in <genexpr>(.0)
3065 if len(iterables) == 0:
3066 # For consistency, it should return two empty lists.
3067 return [], []
-> 3069 codes, categories = zip(*(factorize_from_iterable(it) for it in iterables))
3070 return list(codes), list(categories)
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\pandas\core\arrays\categorical.py:3042, in factorize_from_iterable(values)
3037 codes = values.codes
3038 else:
3039 # The value of ordered is irrelevant since we don't use cat as such,
3040 # but only the resulting categories, the order of which is independent
3041 # from ordered. Set ordered to False as default. See GH #15457
-> 3042 cat = Categorical(values, ordered=False)
3043 categories = cat.categories
3044 codes = cat.codes
File ~\Anaconda3\envs\20250331_1\Lib\site-packages\pandas\core\arrays\categorical.py:425, in Categorical.__init__(self, values, categories, ordered, dtype, fastpath, copy)
422 elif isinstance(values, np.ndarray):
423 if values.ndim > 1:
424 # preempt sanitize_array from raising ValueError
--> 425 raise NotImplementedError(
426 "> 1 ndim Categorical are not supported at this time"
427 )
428 values = sanitize_array(values, None)
429 else:
430 # i.e. must be a list
NotImplementedError: > 1 ndim Categorical are not supported at this time