add new roadmap

ROADMAP.md

@@ -4,115 +4,16 @@ This file is for planning of new modules, features, and PRs that are needed the
 The roadmap is organized into phases, with each phase containing a set of PRs that build upon each other.
 The roadmap is intended to be a living document and may be updated as needed.
 
-## Scope for current release
+## Future Plans
 
-### In scope
-
-- [ ] Handcrafted featurization modules:
-  - [ ] volumesizeshape
-  - [ ] Colocalization
-  - [ ] Intensity
-  - [ ] Granularity
-  - [ ] Neighbors
-  - [ ] Texture
-- [ ] Featurization helper utilities needed by the modules
-- [ ] Full test suite with coverage gate (>=85%)
-- [ ] Sphinx documentation
-- [ ] Example notebooks for module usage
-- [ ] Our [RFC2119-specification](./docs/src/Feature_Naming_Convention.md) driven feature naming policy
-
-## Architecture and Product Decisions
-
-- [ ] Linux-first, CPU-only, low RAM usage for the current release.
-- [ ] File-format agnostic APIs operating on NumPy arrays.
-- [ ] Input contracts:
-  - [ ] Single-channel arrays: (z, y, x)
-  - [ ] Multi-channel arrays: (c, z, y, x)
-- [ ] Modules are intentionally small and composable for external parallel orchestration.
-
-## PR Plan
-
-### Phase 1: Foundation (PR 1-3)
-
-1. PR 1: Packaging and environment baseline
-
-- [x] Python package scaffold, uv dependency management, version metadata 0.0.1, lint/test tooling, CI skeleton.
-- [x] Linux support and CPU-only scope statements in metadata and docs.
-
-2. PR 2: Core data model and API contracts
-
-- [x] Canonical input contracts, loader interfaces, common error types.
-- [x] Return schema contract (required keys, types, deterministic ordering).
-
-3. PR 3: RFC2119 naming specification and validators
-
-- [x] Port and adapt naming conventions into this repository.
-- [x] Add runtime and CI naming validation helpers and conformance tests.
-
-### Phase 2: Feature modules and tests (PR 4-9)
-
-4. PR 4: volumesizeshape module and tests
-
-   - [x] Implement module
-
-1. PR 5: Colocalization module and tests
-
-   - [x] Implement module
-
-1. PR 6: Intensity module and tests
-
-   - [x] Implement module
-
-1. PR 7: Granularity module and tests
-
-   - [x] Implement module
-
-1. PR 8: Neighbors module and tests
-
-   - [x] Implement module
-
-1. PR 9: Texture module and tests
-
-   - [x] Implement module
-
-### Phase 3: Integration, docs, release (PR 10-13)
-
-10. PR 10: Integration matrix and parallelization guidance
-
-- [x] Cross-module integration tests and explicit non-goal docs for internal parallelization.
-
-11. PR 11: Example notebooks and public dataset references
-
-- [ ] One notebook per module plus one end-to-end chaining notebook.
-
-12. PR 12: Sphinx docs, logo, API docs
-
-- [ ] API pages, architecture and scope pages, docs build checks in CI.
-
-13. PR 13: Release v0.0.1 and publish workflow
-
-- [ ] Changelog, semantic tag, PyPI publish automation, README install updates.
-
-### Phase 4: Post-release improvements (PR 14+)
-
-14. Add the ability for loading of images from array instead of file
-    file paths for increased flexibility in data sources and testing.
-
-## Verification Gates
-
-- [x] Run full unit and integration tests on Linux with coverage >=85%.
-- [x] Run naming validation tests for all emitted feature names.
-- [ ] Build Sphinx docs in CI with warnings treated as errors.
-- [ ] Execute example notebooks in a clean environment.
-- [ ] Validate install/import from both wheel and sdist.
-- [ ] Perform release dry-run before publishing.
-
-## v0.0.2 Backlog (Planned)
-
-- [ ] Nucleocentric featurization.
+- [ ] Pick between pandas and polars for dataframe handling.
 - [ ] Optional mask output mode.
 - [ ] Expanded benchmark strategy.
-
-## v0.0.3 Backlog (Planned)
-
-- [ ] Potential Arrow Flight handoff experiments.
+- [ ] Cytomining V2 support.
+- [ ] Support for additional image formats (e.g., TIFF, JPEG, OME-arrow).
+- [ ] Support multi-channel image loading (lazily).
+- [ ] Support loading of shapes, vectors, outlines, and contours.
+- [ ] Integration with cloud storage solutions (e.g., AWS S3, Google Cloud Storage).
+- [ ] Support with DeepProfiler image handoff (thin arrow flight, but simplified for the use case of image handoff).
+- [ ] Support for additional feature extraction methods (e.g., mesh, graph-based features, point-clouds, polygons).
+- [ ] Feature-extraction time estimation and optimization.