sainsc.LazyKDE.assign_celltype
==============================

.. py:method:: sainsc.LazyKDE.assign_celltype(signatures, *, log = False, chunk = (500, 500))

   Calculate the cosine similarity with known cell-type signatures.

   For each bead calculate the cosine similarity with a set of cell-type signatures.
   The cell-type with highest score will be assigned to the corresponding bead.

   :param signatures: DataFrame of cell-type signatures. Columns are cell-types and index are genes.
   :type signatures: pandas.DataFrame
   :param log: Whether to log transform the KDE when calculating the cosine similarity.
               This is useful if the gene signatures are derived from log-transformed data.
   :type log: bool
   :param chunk: Size of the chunks for processing. Larger chunks require more memory but
                 have less duplicated computation.
   :type chunk: tuple[int, int]

   :raises ValueError: If not all genes of the `signatures` are available.
   :raises ValueError: If `self.kernel` is not set.
   :raises ValueError: If `chunk` is smaller than the shape of `self.kernel`.