scimilarity.anndata_data_models#

class scimilarity.anndata_data_models.MetricLearningDataModule(*args, **kwargs)[source]#

Bases: LightningDataModule

A class to encapsulate the anndata needed to train the model.

Parameters:

train_path (str) – Path to the training h5ad file.
val_path (str, optional, default: None) – Path to the validataion h5ad file.
obs_field (str, default: "celltype_name") – The obs key name containing celltype labels.
batch_size (int, default: 1000) – Batch size.
num_workers (int, default: 1) – The number of worker threads for dataloaders.
gene_order_file (str, optional) – Use a given gene order as described in the specified file rather than using the training dataset’s gene order. One gene symbol per line.

Examples

>>> datamodule = MetricLearningDataModule(
        batch_size=1000,
        num_workers=1,
        obs_field="celltype_name",
        train_path="train.h5ad",
    )

collate(batch)[source]#

Collate tensors.

Parameters:: batch – Batch to collate.
Returns:: A Tuple[torch.Tensor, torch.Tensor, list] containing information on the collated tensors.
Return type:: tuple

get_sampler_weights(labels, studies=None)[source]#

Get weighted random sampler.

Parameters:

dataset (scDataset) – Single cell dataset.
labels (list)
studies (list | None)

Returns:

A WeightedRandomSampler object.

Return type:

WeightedRandomSampler

subset_valid_terms(data)[source]#

Keep cells whose celltype labels have valid ontology id.

Parameters:: data (anndata.AnnData) – Annotated data to subset by valid ontology id.
Returns:: An object containing the data whose celltype labels have valid ontology id.
Return type:: anndata.AnnData

test_dataloader()[source]#

Load the test dataset.

Returns:: A DataLoader object containing the test dataset.
Return type:: DataLoader

train_dataloader()[source]#

Load the training dataset.

Returns:: A DataLoader object containing the training dataset.
Return type:: DataLoader

val_dataloader()[source]#

Load the validation dataset.

Returns:: A DataLoader object containing the validation dataset.
Return type:: DataLoader

class scimilarity.anndata_data_models.scDataset(X, Y, study=None)[source]#

Bases: Dataset

A class that represents a single cell dataset.

Parameters:

X (numpy.ndarray) – Gene expression vectors for every cell.
Y (numpy.ndarray) – Text labels for every cell.
study (numpy.ndarray) – The study identifier for every cell.