Changelog

Changelog#

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]#

Added#

  • DiagVI model (scviva.external.diagvi.DIAGVI), migrated from scvi-tools, for cross-modality alignment of paired spatial transcriptomics/proteomics data via a shared latent space with graph-guided and optimal-transport (Sinkhorn) losses; ships with two new tutorials (DiagVI_spatial_transcriptomics, DiagVI_spatial_proteomics). Its optional geomloss/torch-geometric dependencies are covered by the existing scviva-tools[spatial] extra.

  • Shared CyclicMultiDataLoader (scviva.model.utils._dataloaders), consolidating the near-identical cyclic-batch dataloader previously duplicated between GIMVI and DiagVI.

[0.1.6] - 2026-07-08#

Fixed#

  • Harreman: pandas 3.0 always-on copy-on-write broke three in-place mutation sites that relied on .values returning a writable view:

    • create_modules raised ValueError: underlying array is read-only on np.fill_diagonal; now forces a real copy via to_numpy(copy=True)

    • run_cell_communication_analysis hit the same fill_diagonal failure on the symmetric LC Z-score matrix; now mutates a copy and writes it back via .loc[:, :]

    • extract_lr_pairs raised ValueError: Length of indexer and values mismatch because pandas 3.0’s default Arrow-backed string dtype no longer allows storing variable-length arrays into single-element slots; ligand/receptor columns now use to_numpy(dtype=object, copy=True) to restore plain, guaranteed-writable object-array semantics

[0.1.5] - 2026-07-06#

Added#

  • Tangram model for mapping scRNA-seq to spatial transcriptomics (scviva.external.Tangram), a PyTorch reimplementation supporting “cells” and “constrained” cell-to-spot mapping modes

  • Harreman downstream tool for cell-cell communication and metabolic exchange analysis (scviva.tl.harreman, scviva.pl.harreman), integrating outputs from DestVI, ResolVI, and SCVIVA

  • SpatialPredictiveMixin: unified predictive mixin shared by ResolVI and SCVIVA, replacing the ResolVI-only ResolVIPredictiveMixin

  • scviva.tl/scviva.pl top-level namespace aliases, mirroring scanpy’s sc.tl/sc.pl convention

  • Dedicated CI job for optional/slow integration tests (real model training)

Changed#

  • Package renamed from spatialvi-tools to scviva-tools on PyPI (import name scviva unchanged); docs and install instructions updated accordingly

Fixed#

  • Tangram: gene-mismatch validation in setup_mudata, and get_mapper_matrix filtering under constrained=True

  • Harreman: import/namespace bugs from the initial port that made the package unimportable, plus a broken plotting accessor and a model-recognition constant typo

[0.1.3] - 2026-04-13#

Changed#

  • Cleanup: dropped dead code (MLflow/JAX settings, a stale config re-export, a trivial method alias, stale in-source dev comments) and simplified the lazy model map

  • Refactored SCVIVA’s predictive methods to share a common decoder helper, and tidied up several module-level imports; moved a few internal modules under utils/ for consistency with scvi-tools conventions

Fixed#

  • scikit-learn>=1.4 moved from test-only to core dependencies (required by SCVIVA/ResolVI at runtime); removed redundant anndata/scanpy test-extra pins

Documentation#

  • Added installation guide, FAQ, API reference stubs, developer/contributing guides, and user-guide background/use-case pages

[0.1.2] - 2026-04-12#

Fixed#

  • RNADeconv.__init__: read model_kwargs['ct_weight'] instead of the incorrect model_kwargs['ct_prop']; the mismatched key caused a KeyError whenever ct_weight was passed, making class-reweighted training unusable

  • JVAE.generative: replace y.type.squeeze(-1) with y.squeeze(-1).long() for the gene-label dispersion branch; y.type is Python’s built-in type() bound on the tensor object, so any run with dispersion='gene-label' crashed before reaching the one_hot encoding

  • Added regression tests for both fixes (all 78 tests pass)

[0.1.1] - 2026-04-12#

Added#

  • GIMVI model for joint imputation of missing genes across paired scRNA-seq and spatial transcriptomics data, based on :cite:p:Lopez19

  • Stereoscope model for probabilistic cell-type deconvolution of spatial transcriptomics spots (spatialvi.external.Stereoscope)

  • Tutorials: gimvi_tutorial, stereoscope_heart_LV_tutorial, cell2location_lymph_node_spatial_tutorial, and tangram_scvi_tools

  • Regression test suites for GIMVI and Stereoscope (upstream parity tests)

[0.1.0] - 2026-03-25#

Added#

  • Initial package with DestVI, ResolVI, and scVIVA models

  • SpatialBaseModel shared base infrastructure

  • SpatialNeighborhoodMixin for neighbor graph computation (squidpy + RAPIDS backends)

  • SpatialDeconvolutionMixin for cell-type deconvolution

  • SpatialData integration via setup_spatialdata() and from_spatialdata()

  • squidpy neighbor computation backend

  • RAPIDS acceleration backend (backend="rapids")

  • Custom AnnData fields: SpatialCoordsField, NeighborhoodGraphField