Heimdall.fe.Fe#
- class Heimdall.fe.Fe(data, vocab_size, embedding_parameters, d_embedding, pad_value=None, mask_value=None, drop_zeros=True, rng=0)[source]#
Bases:
ABCAbstraction for expression-based embedding.
- Parameters:
adata – input AnnData-formatted dataset, with gene names in the .var dataframe.
vocab_size (int) – total number of possible expression tokens and special tokens
d_embedding (int) – dimensionality of embedding for each expression entity
data (CellRepresentation)
embedding_parameters (DictConfig)
pad_value (int)
mask_value (int)
drop_zeros (bool)
Attributes
Methods
load_from_cache(expression_embeddings)Load processed values from cache.
Replace config placeholders with values after preprocessing.
preprocess_embeddings([float_dtype])Preprocess expression embeddings and store them for use during model inference.