spateo.digitization.borderline#
Written by @Jinerhal, adapted by @Xiaojieqiu.
Module Contents#
Functions#
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Identify the borderline at the interface of the source and target cell clusters. |
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Extend the borderline to either interior or exterior side to each create layer_num layers, and segment such |
- spateo.digitization.borderline.get_borderline(adata: spateo.digitization.utils.AnnData, cluster_key: str, source_clusters: int, target_clusters: int, bin_size: int = 1, spatial_key: str = 'spatial', borderline_key: str = 'borderline', k_size: int = 8, min_area: int = 30, dilate_k_size: int = 3) spateo.digitization.utils.np.ndarray[source]#
Identify the borderline at the interface of the source and target cell clusters.
The borderline will be identified by first retrieving the outline/contour formed by the source clusters, which will then be cleaned up to retrieve the borderline by masking with the expanded contours formed by the target clusters.
- Parameters:
- adata
The adata object to be used for identifying the borderline.
- cluster_key
The key name of the spatial cluster in adata.obs
- source_clusters
The source cluster(s) that will interface with the target clusters.
- target_clusters
The target cluster(s) that will interface with the source clusters.
- bin_size
The size of the binning.
- spatial_key
The key name of the spatial coordinates in adata.obs
- borderline_key
The key name in adata.obs that will be used to store the borderline.
- k_size
Kernel size of the elliptic structuring element.
- min_area
Minimal area threshold corresponding to the resulting contour(s).
- dilate_k_size
Kernel size of the cv2.dilate function.
- Returns:
- The matrix that stores the image information of the borderline between the source and target
cluster(s). Note that the adata object will also be updated with the boundary_line key that stores the information about whether the bucket is on the borderline.
- Return type:
borderline_img
- spateo.digitization.borderline.grid_borderline(adata: spateo.digitization.utils.AnnData, borderline_img: spateo.digitization.utils.np.ndarray, borderline_list: spateo.digitization.utils.List, layer_num: int = 3, column_num: int = 25, layer_width: int = 10, spatial_key: str = 'spatial', init: bool = False) None[source]#
- Extend the borderline to either interior or exterior side to each create layer_num layers, and segment such
layers to column_num columns.
- Parameters:
- adata
The adata object to be used for identifying the interior/exterior layers and columns.
- borderline_img
The matrix that stores the image information of the borderline between the source and target cluster(s).
- borderline_list
An order list of np.arrays of coordinates of the borderlines.
- layer_num
Number of layers to extend on either interior or exterior side.
- column_num
Number of columns to segment for each layer.
- layer_width
Layer/column boundary width. This only affects grid_label.
- spatial_key
The key name in adata.obsm of the spatial coordinates. Default to “spatial”. Passed to fill_grid_label function.
- init
Whether to generate (and potentially overwrite) the layer_label_key and column_label_key in fill_grid_label function.
- Returns:
layer_label_key: this key points to layer labels.
column_label_key: this key points to column labels.
- Return type:
Nothing but update the adata object with following keys in .obs