fetch

Fetch data from AnnData, flexibly.

fetch

Given, adata and a key that points to a specific matrix stored in adata, return the data, formatted either as np.ndarray or torch.Tensor. If formatted as torch.Tensor, device may be specified based on available devices.

Uses the class: adata_query._core.AnnDataFetcher.

data = fetch(
    adata: anndata.AnnData,
    key: str,
    groupby: Optional[str] = None,
    torch: bool = False,
    device: torch.device = autodevice.AutoDevice(),
    as_dict: bool = True,
    *args,
    **kwargs,
)

Parameters

adata (anndata.AnnData)

• Annotated single-cell data object. See anndata.AnnData

key (str)

• Key to access a matrix in adata. For example, if you wanted to access adata.obsm['X_pca'], you would pass: "X_pca".

groupby (Optional[str]) = None

• Optionally, one may choose to group data according to a cell-specific annotation in adata.obs. This would invoke returning data as List

torch (bool) = False

• Boolean indicator of whether data should be formatted as torch.Tensor. If False (default), data is formatted as np.ndarray.

device (torch.device) = autodevice.AutoDevice()

• Should torch=True, the device ("cpu", "cuda:N", "mps:N") may be set. The default value, autodevice.AutoDevice() will indicate the use of GPU, if available.

as_dict (bool) =True

• Only relevant when groupby is not None. Boolean indicator to return data in a Dict where the key for each value corresponds to the respective groupby value. If False, returns List.

Returns

data(Union[torch.Tensor, np.ndarray, List[Union[torch.Tensor, np.ndarray]], Dict[Union[str, int], Union[torch.Tensor, np.ndarray]])

• Formatted data as np.ndarray or torch.Tensor. If torch=True the torch.Tensor is allocated to the device indicated by the device argument. If groupby is passed, returned as Dict[Union[str, int], np.ndarray] or Dict[Union[str, int]. torch.Tensor]. If groupby is passed and as_dict = False, returns List[np.ndarray] or List[tobrch.Tensor].

Source code: GitHub.com/mvinyard/AnnDataQuery/adata_query/_core/_fetcher.py