Index error while running the first temporal update step in MiniAn

[AlbertFok]

Hi,

My error log looks like this:

IndexError                                Traceback (most recent call last)
File <timed exec>:1

File ~\minian\minian\cnmf.py:858, in update_temporal(A, C, b, f, Y, YrA, noise_freq, p, add_lag, jac_thres, sparse_penal, bseg, med_wd, zero_thres, max_iters, use_smooth, normalize, warm_start, post_scal, scs_fallback, concurrent_update)
    856     YrA = compute_trace(Y, A, b, C, f).persist()
    857 Ymask = (YrA > 0).any("frame").compute()
--> 858 A, C, YrA = A.sel(unit_id=Ymask), C.sel(unit_id=Ymask), YrA.sel(unit_id=Ymask)
    859 print("grouping overlaping units")
    860 A_sps = (A.data.map_blocks(sparse.COO) > 0).compute().astype(np.float32)

File ~\.conda\envs\minian\lib\site-packages\xarray\core\dataarray.py:1202, in DataArray.sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
   1121 def sel(
   1122     self,
   1123     indexers: Mapping[Hashable, Any] = None,
   (...)
   1127     **indexers_kwargs: Any,
   1128 ) -> "DataArray":
   1129     """Return a new DataArray whose data is given by selecting index
   1130     labels along the specified dimension(s).
   1131 
   (...)
   1200 
   1201     """
-> 1202     ds = self._to_temp_dataset().sel(
   1203         indexers=indexers,
   1204         drop=drop,
   1205         method=method,
   1206         tolerance=tolerance,
   1207         **indexers_kwargs,
   1208     )
   1209     return self._from_temp_dataset(ds)

File ~\.conda\envs\minian\lib\site-packages\xarray\core\dataset.py:2185, in Dataset.sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
   2181 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "sel")
   2182 pos_indexers, new_indexes = remap_label_indexers(
   2183     self, indexers=indexers, method=method, tolerance=tolerance
   2184 )
-> 2185 result = self.isel(indexers=pos_indexers, drop=drop)
   2186 return result._overwrite_indexes(new_indexes)

File ~\.conda\envs\minian\lib\site-packages\xarray\core\dataset.py:2032, in Dataset.isel(self, indexers, drop, missing_dims, **indexers_kwargs)
   2030 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "isel")
   2031 if any(is_fancy_indexer(idx) for idx in indexers.values()):
-> 2032     return self._isel_fancy(indexers, drop=drop, missing_dims=missing_dims)
   2034 # Much faster algorithm for when all indexers are ints, slices, one-dimensional
   2035 # lists, or zero or one-dimensional np.ndarray's
   2036 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)

File ~\.conda\envs\minian\lib\site-packages\xarray\core\dataset.py:2090, in Dataset._isel_fancy(self, indexers, drop, missing_dims)
   2087     continue  # drop this variable
   2089 if name in self.indexes:
-> 2090     new_var, new_index = isel_variable_and_index(
   2091         name, var, self.indexes[name], var_indexers
   2092     )
   2093     if new_index is not None:
   2094         indexes[name] = new_index

File ~\.conda\envs\minian\lib\site-packages\xarray\core\indexes.py:106, in isel_variable_and_index(name, variable, index, indexers)
    101 if len(variable.dims) > 1:
    102     raise NotImplementedError(
    103         "indexing multi-dimensional variable with indexes is not supported yet"
    104     )
--> 106 new_variable = variable.isel(indexers)
    108 if new_variable.dims != (name,):
    109     # can't preserve a index if result has new dimensions
    110     return new_variable, None

File ~\.conda\envs\minian\lib\site-packages\xarray\core\variable.py:1120, in Variable.isel(self, indexers, missing_dims, **indexers_kwargs)
   1117 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)
   1119 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims)
-> 1120 return self[key]

File ~\.conda\envs\minian\lib\site-packages\xarray\core\variable.py:768, in Variable.__getitem__(self, key)
    755 def __getitem__(self: VariableType, key) -> VariableType:
    756     """Return a new Variable object whose contents are consistent with
    757     getting the provided key from the underlying data.
    758 
   (...)
    766     array `x.values` directly.
    767     """
--> 768     dims, indexer, new_order = self._broadcast_indexes(key)
    769     data = as_indexable(self._data)[indexer]
    770     if new_order:

File ~\.conda\envs\minian\lib\site-packages\xarray\core\variable.py:609, in Variable._broadcast_indexes(self, key)
    606 if all(isinstance(k, BASIC_INDEXING_TYPES) for k in key):
    607     return self._broadcast_indexes_basic(key)
--> 609 self._validate_indexers(key)
    610 # Detect it can be mapped as an outer indexer
    611 # If all key is unlabeled, or
    612 # key can be mapped as an OuterIndexer.
    613 if all(not isinstance(k, Variable) for k in key):

File ~\.conda\envs\minian\lib\site-packages\xarray\core\variable.py:652, in Variable._validate_indexers(self, key)
    650 if k.dtype.kind == "b":
    651     if self.shape[self.get_axis_num(dim)] != len(k):
--> 652         raise IndexError(
    653             "Boolean array size {:d} is used to index array "
    654             "with shape {:s}.".format(len(k), str(self.shape))
    655         )
    656     if k.ndim > 1:
    657         raise IndexError(
    658             "{}-dimensional boolean indexing is "
    659             "not supported. ".format(k.ndim)
    660         )

IndexError: Boolean array size 10 is used to index array with shape (820,).

I don't know what it means or how to fix it. I greatly appreciate your help.