mesa.ecospatial.calculate_DPI
- mesa.ecospatial.calculate_DPI(spatial_data, scale, library_key, library_id, spatial_key, cluster_key, hotspot=True, p_value=0.01, mode='MoranI', restricted=False, **kwargs)
Calculate the Diversity Proximity Index (DPI) for specified samples within spatial data.
- Parameters:
spatial_data (Union[
ad.AnnData,pd.DataFrame]) – The spatial data to be analyzed. This can be an AnnData object or a pandas DataFrame.scale (float) – The scale factor used for generating patches within the spatial regions.
library_key (str) – Key in spatial_data that corresponds to library identifiers.
library_id (Union[tuple, list]) – A tuple or list of identifiers for the libraries to be processed.
spatial_key (Union[str, List[str]]) – Key(s) in spatial_data used to determine spatial coordinates.
cluster_key (str) – Key used to identify different clusters or types within spatial_data.
hotspot (bool, optional) – Specifies whether to identify diversity hotspots (True) or coldspots (False). Default is True.
p_value (float, optional) – The significance level used for hotspot or coldspot identification. Default is 0.01.
mode (str, optional) – Specifies the mode of spatial statistics to be used, such as ‘MoranI’. Default is ‘MoranI’.
restricted (bool, optional) – If set to True, restricts analysis to specific tissue regions. Default is False.
**kwargs – Additional keyword arguments for further customization of the diversity calculations.
- Returns:
A DataFrame where each index represents a library_id and the columns contain the calculated DPI for each sample.
- Return type: