chore: bump version, add changelog, update deps and README

Author: okunator

CHANGELOG.md

@@ -2,6 +2,15 @@
 
 All notable changes to Histolytics will be documented in this file.
 
+## [0.2.0] - 2025-08-18
+### Added
+- Unify feature extraction API
+- Major performance improvements for functions in `stromal_feats` and `nuc_feats` modules
+- Add `textural_feats` for GLCM feature extraction. Uses skimage.
+- Add `manders_coloc_coeff`, `n_chrom_clumps` and `chrom_boundary_prop` feats to  `chromatin_feats`
+- Update documentation pages
+
+
 ## [0.1.1] - 2025-07-03
 
 ### Added

README.md

@@ -4,32 +4,51 @@
 
 **A Python library for scalable panoptic spatial analysis of histological WSIs**
 
-[![Github Test](https://img.shields.io/github/actions/workflow/status/HautaniemiLab/histolytics/tests.yml?label=tests)](https://github.com/HautaniemiLab/histolytics/blob/main/.github/workflows/tests.yml) [![License](https://img.shields.io/github/license/HautaniemiLab/histolytics)](https://github.com/HautaniemiLab/histolytics/blob/main/LICENSE) [![Python - Version](https://img.shields.io/pypi/pyversions/histolytics)](https://www.python.org/) [![Package - Version](https://img.shields.io/pypi/v/histolytics)](https://pypi.org/project/histolytics/)
-
+[![Github Test](https://img.shields.io/github/actions/workflow/status/HautaniemiLab/histolytics/tests.yml?label=tests)](https://github.com/HautaniemiLab/histolytics/blob/main/.github/workflows/tests.yml) [![License](https://img.shields.io/github/license/HautaniemiLab/histolytics)](https://github.com/HautaniemiLab/histolytics/blob/main/LICENSE) [![Python - Version](https://img.shields.io/pypi/pyversions/histolytics)](https://www.python.org/)
+[![Package - Version](https://img.shields.io/pypi/v/histolytics)](https://pypi.org/project/histolytics/) [![Model Checkpoints](https://img.shields.io/badge/%F0%9F%A4%97%20HF-Model%20Hub-yellow)](https://huggingface.co/histolytics-hub)
 </div>
 
 ## Introduction
 
-**histolytics** is a spatial analysis library for histological whole slide images (WSI) library built upon [`torch`](https://pytorch.org/), [`geopandas`](https://geopandas.org/en/stable/index.html) and [`libpysal`](https://pysal.org/libpysal/). The library contains multi-task encoder-decoder architectures for **panoptic segmentation** of WSIs into [`__geo_interface__`](https://gist.github.com/sgillies/2217756)-format and a wide array of spatial analysis tools for the resulting segmentation masks.
+**histolytics** is a spatial analysis library for histological whole slide images (WSI). Built upon [`torch`](https://pytorch.org/), [`geopandas`](https://geopandas.org/en/stable/index.html) and [`libpysal`](https://pysal.org/libpysal/), the library provides a comprehensive and scalable framework for **panoptic segmentation** and **interpretable panoptic spatial analysis** of routine histopathology slides.
+
 
-## Features 🌟
-- WSI-level panoptic segmentation
-- Several panoptic segmentation models for histological WSIs
+## Panoptic Segmentation Features 🌟
+- Fast WSI-level panoptic segmentation. See [example](https://hautaniemilab.github.io/histolytics/user_guide/seg/panoptic_segmentation/).
+- Low memory-footprint segmentation results with [`__geo_interface__`](https://gist.github.com/sgillies/2217756)-specification.
+- Multiple vectorized segmentation output formats (geojson/feather/parquet).
+- Several panoptic segmentation model architectures for histological WSIs with flexible backbone support: See [example](https://hautaniemilab.github.io/histolytics/user_guide/seg/backbones/)
 - Pre-trained models in model-hub. See: [histolytics-hub](https://huggingface.co/histolytics-hub)
-- Versatile spatial analysis tools for segmented WSIs
+
+## Spatial Analysis Features 📊
+- Fast Spatial Querying of WSI-scale panoptic segmentation maps. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/querying/)
+- Spatial indexing/partitioning for localized spatial statistics and analysis. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/partitioning/)
+- Graph-based neighborhood analysis for local cell neighborhoods. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/nhoods/)
+- Plotting utilities for spatial data visualization. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/legendgram/)
+- Spatial clustering and cluster centrography metrics. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/clustering/)
+- Large set of morphological, intensity, chromatin distribution, and textural features at nuclear level. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/nuclear_features/)
+- Large set of collagen fiber and intensity based features to characterize stroma and ECM. See [example](https://hautaniemilab.github.io/histolytics/user_guide/spatial/stromal_features/)
+
+## Example Workflows 🧪
+- Immuno-oncology Profiling:
+  - [Spatial Statistics of TILs](https://hautaniemilab.github.io/histolytics/user_guide/workflows/TIL_workflow/).
+  - [Profiling TLS and Lymphoid Aggregates](https://hautaniemilab.github.io/histolytics/user_guide/workflows/tls_lymphoid_aggregate/).
+- Nuclear Pleomorphism:
+  - [Nuclear Morphology Analysis](https://hautaniemilab.github.io/histolytics/user_guide/workflows/nuclear_morphology/).
+  - [Nuclear Chromatin Distribution Analysis](https://hautaniemilab.github.io/histolytics/user_guide/workflows/chromatin_patterns/).
+- TME Characterization:
+  - [Collagen Fiber Disorder Analysis](https://hautaniemilab.github.io/histolytics/user_guide/workflows/collagen_orientation/).
+  - [Characterization of Desmoplastic Stroma](https://hautaniemilab.github.io/histolytics/user_guide/workflows/clustering_desmoplasia/).
+- Nuclei Neighborhoods:
+  - [Tumor Cell Accessibility](https://hautaniemilab.github.io/histolytics/user_guide/workflows/tumor_cell_accessibility/).
+
 
 ## Installation 🛠️
 
 ```shell
 pip install histolytics
 ```
 
-## Getting started with Histolytics
-
-- [Segmentation Quick Start](https://hautaniemilab.github.io/histolytics/user_guide/seg/getting_started_seg/)
-- [API Reference](https://hautaniemilab.github.io/histolytics/api/)
-
-
 ## Models 🤖
 
 - Panoptic [HoVer-Net](https://www.sciencedirect.com/science/article/abs/pii/S1361841519301045)

mkdocs.yml

@@ -90,6 +90,7 @@ nav:
   - Home: index.md
   - Installation: installation.md
   - User Guide:
+    - Overview: user_guide/index.md
     - Segmentation:
       - Getting Started: user_guide/seg/getting_started_seg.md
       - Model Backbones: user_guide/seg/backbones.ipynb
@@ -108,12 +109,13 @@ nav:
       - Stromal Features: user_guide/spatial/stromal_features.ipynb
       - Medial Lines: user_guide/spatial/medial_lines.ipynb
     - WSI Analysis Workflows:
-      - Quantifying tumor-infiltrating lymphocytes (TILs): user_guide/spatial/indexing_partitioning.ipynb
-      - Quantifying Nuclear Chromatin Patterns: user_guide/spatial/chromatin_patterns.ipynb
-      - Clustering Desmoplastic Stroma: user_guide/spatial/clustering_desmoplasia.ipynb
-      - Tumor Cell Accessibility: user_guide/spatial/tumor_cell_accessibility.ipynb
-      - Collagen Orientation Disorder Quantification: user_guide/spatial/collagen_orientation.ipynb
-      - TLS and Lymphoid Aggregate Analysis: user_guide/spatial/tls_lymphoid_aggregate.ipynb
+      - Quantifying tumor-infiltrating lymphocytes (TILs): user_guide/workflows/TIL_workflow.ipynb
+      - TLS and Lymphoid Aggregate Analysis: user_guide/workflows/tls_lymphoid_aggregate.ipynb
+      - Quantifying Neoplastic Nuclear Chromatin Patterns: user_guide/workflows/chromatin_patterns.ipynb
+      - Quantifying Neoplastic Nuclear Morphology: user_guide/workflows/nuclear_morphology.ipynb
+      - Quantifying Neoplastic Cell Accessibility: user_guide/workflows/tumor_cell_accessibility.ipynb
+      - Clustering Desmoplastic Stroma: user_guide/workflows/clustering_desmoplasia.ipynb
+      - Collagen Orientation Disorder Quantification: user_guide/workflows/collagen_orientation.ipynb
   - API Reference:
     - Overview: api/index.md
     - data:

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "histolytics"
-version = "0.1.1"
+version = "0.2.0"
 description = "Panoptic Segmentation and WSI Spatial Analysis"
 readme = "README.md"
 license = { file = "LICENSE" }
@@ -18,8 +18,9 @@ classifiers = [
 requires-python = ">=3.10"
 dependencies = [
     "albumentations>=2.0.6",
-    "cellseg-models-pytorch>=0.1.26",
+    "cellseg-models-pytorch>=0.1.28",
     "cucim-cu12>=25.6.0",
+    "cuml-cu12>=25.6.0",
     "datasets>=3.6.0",
     "esda>=2.7.0",
     "geopandas>=1.0.1",
@@ -30,6 +31,7 @@ dependencies = [
     "networkx>=3.4.2",
     "pandarallel>=1.6.5",
     "quadbin>=0.2.2",
+    "scikit-image>=0.25.0",
     "torchdata>=0.11.0",
 ]
 

src/histolytics/__init__.py

@@ -1,3 +1,3 @@
-__version__ = "0.1.1"
+__version__ = "0.2.0"
 
 __all__ = ["__version__"]