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0.1.7 — 2024-07-03

Chore

  • Update geopandas version ^1.0.0

Features

  • Add a new methods for clustering: cluster_cells, find_lisa_clusters, connected_components and label_connected_components. The cluster_cells works as a polished runner function to cluster spatially the cells of interest with local moran lisa analysis.

0.1.6 — 2024-04-11

Fixes

  • Fix a bug gdf_to_file. Failed when qupath data fields were added to gdf.
  • Remove matplotlib.cm.get_cmap function from source code. It was not used.

0.1.5 — 2024-02-28

Features

  • Add support for querying a WSI with bbox coords.
  • Add support for rasterizing a gdf into a instance or semantic segmentation mask
  • add support for intensity features

0.1.4 — 2024-02-05

Docs

  • Add cell clustering example
  • Add cell regionalization example
  • Add medial line extraction example

Features

  • Add medial line extraction funtion cellseg_gsontools.geometry.medial_lines. Extracts the medial lines using voronoi diagram.
  • Add perpendicular line extraction funtion cellseg_gsontools.geometry.perpendicular_lines. Extracts the perpendicular lines from a given line gdf.
  • Add num_processes arguments in local_character, local_distances, local_diversity and shape_metric functions.

0.1.3 — 2023-12-22

Breaking changes

  • The SpatialContext API now takes params: parallel and num_processes in the class constructor instead of the fit()-method.

Features

  • Added support for new backends (python libraries) to compute the spatial joins in the SpatialContext-classes. This allows for more efficient computation of the spatial joins especially for very large tissue areas.

  • Backends:

    • dask-geopandas
    • spatialpandas

  • Add h3 hexgrid support in grid fitting for spatial context classes

Performance

  • sjoin operations replaced with sindex ops. This makes subsetting 10-100x faster.

Docs

New documentation website: https://okunator.github.io/cellseg_gsontools/

0.1.2 — 2023-11-01

Deprecated

  • the Pipeline class was removed.

Features

  • Add local_distances function to compute the mean/median/sum of the distances between nodes in local neighborhoods

  • Add weights2gdf function to convert libpysal.weights.W into a gpd.GeoDataFrame with geometry column consisting of shapely.geometry.LineStrings

  • Add grid fitting to _SpatialContext classes. Allows a grid of patches to be overlayed on top of different context areas. The patch sizes and strides can be user defined.

  • Better looking links in _SpatialContext.plot(). Different link classes now represented with different colors.

  • Add grid_classify method to classify grids based on heuristics.

Performance

  • Support for parallel spatial context fitting: _SpatialContext.fit(parallel=True)

Fixes

  • Drop duplicates in context2gdf-class method

  • clarify the apply_gdf function api.

  • clarify the _SpatialContext api.

0.1.1 — 2023-10-13

Features

  • Add join predicate param for sjoin operation in get_objs_within function

Performance

  • Optimize spatial subsetting operations by getting rid of redundant operations in spatial context classes.

Perf

  • Parallelize and memory optimize AreaMerger.

Fixes

  • Simplify border_network computation and return only the node-node links that go accross the border.

  • Simplify weights plotting interfacee

  • Fix bug in interface and roi network fitting.

0.1.0-alpha.2 — 2023-09-15

Fixes

  • Set crs in _SpatialContext to avoid warnings

  • Unify the local_character and local_diversity function api.

Features

  • Add option to add multiple columns to local_diversity and local_character
  • add is_categorical helper func
  • Add hbdscan clustering method.
  • Add option to not fit graphs in .fit() method of _SpatialContext-classes

Chore

  • add scikit-learn (1.3.0) dependency
  • Update to latest geopandas (0.13) and shapely (> 2.0)

0.1.0 — 2023-06-28

First release

Features

  • Morphological, graph, and diversity feature extraction methods.
  • Parallelized dataframe operations via pandarallel.
  • Merging of adjacsent geojson annotations via the _BaseMerger classes.
  • Spatial context interface with _SpatialContext-classes to subset regions of the tissues with sophistication.
  • Summary features over the whole data via _Summary classes. Run summaries of the extracted features.
  • Simple pipeline interface with Pipeline-class to run analysis in parallel over samples.