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Implement link_views_by_dict and hierarchical coordination APIs for feature parity with vitessce-python#98

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Implement link_views_by_dict and hierarchical coordination APIs for feature parity with vitessce-python#98
Copilot wants to merge 4 commits intomainfrom
copilot/fix-97

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Copilot AI commented Aug 8, 2025

This PR implements the link_views_by_dict method and related hierarchical coordination APIs to achieve feature parity with the Python vitessce library. The implementation adds support for advanced coordination linking patterns that were previously missing from the R package.

Key Features Added

1. link_views_by_dict() Method

A convenience function for setting up multi-level and meta-coordination scopes across a set of views, mirroring the Python implementation:

# Simple coordination linking
vc$link_views_by_dict(list(spatial_view, scatter_view), list(
  spatialZoom = 2,
  spatialTargetX = 0,
  spatialTargetY = 0
), meta = FALSE)

# Meta-coordination linking (default)
vc$link_views_by_dict(list(spatial_view, layer_controller), list(
  spatialZoom = 3,
  cellFilter = list()
))

2. add_coordination_by_dict() Method

Processes potentially nested coordination structures and returns coordination scope objects:

scopes <- vc$add_coordination_by_dict(list(
  embeddingZoom = 1.2,
  geneFilter = list("BRCA1", "TP53", "EGFR")
))

3. Enhanced Meta-coordination Support

  • Implemented add_meta_coordination() method
  • Added use_meta_coordination() for views
  • Full use_coordination_by_dict() support for both views and meta-coordination scopes

4. Hierarchical Coordination Processing

Added helper functions to process complex coordination dictionaries with proper scope management, supporting:

  • Simple coordination values
  • Complex list structures
  • Nested coordination hierarchies using CoordinationLevel/CL

Implementation Details

The implementation follows the Python vitessce library patterns while maintaining R idioms:

  • JSON Serialization: Proper handling of complex data structures using set_value_raw() for lists
  • Scope Management: Automatic generation of unique coordination scope names
  • Error Handling: Robust processing of various input formats
  • Backward Compatibility: All existing APIs continue to work unchanged

Testing

Added comprehensive test coverage including:

  • Basic coordination linking tests
  • Meta-coordination functionality tests
  • Individual method validation
  • Integration with existing test suite
  • Edge cases for complex data structures

All existing tests pass without modification, ensuring no regressions.

Example Usage

# Create configuration with multiple views
vc <- VitessceConfig$new(schema_version = "1.0.16", name = "Multi-view Config")
dataset <- vc$add_dataset("Spatial Dataset")
spatial_view <- vc$add_view(dataset, "spatial")
scatter_view <- vc$add_view(dataset, "scatterplot")
layer_controller <- vc$add_view(dataset, "layerController")

# Link views with hierarchical coordination
vc$link_views_by_dict(
  list(spatial_view, scatter_view, layer_controller),
  list(
    spatialZoom = 2.5,
    spatialTargetX = 100,
    spatialTargetY = 150,
    cellFilter = list()
  )
)

This implementation provides full feature parity between the R and Python versions of the Vitessce library for hierarchical coordination APIs.

Fixes #97.

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Copilot AI commented Aug 8, 2025

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Copilot AI and others added 2 commits August 8, 2025 01:44
…eature parity with vitessce-python

Co-authored-by: keller-mark <7525285+keller-mark@users.noreply.github.com>
Co-authored-by: keller-mark <7525285+keller-mark@users.noreply.github.com>
Copilot AI changed the title [WIP] Feature parity with vitessce-python Implement link_views_by_dict and hierarchical coordination APIs for feature parity with vitessce-python Aug 8, 2025
Copilot AI requested a review from keller-mark August 8, 2025 01:47
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@copilot Please update the unit tests to port the assertions from https://github.com/vitessce/vitessce-python/blob/main/tests/test_config.py (in the tests test_config_add_coordination_by_dict and test_config_add_and_use_coordination_by_dict, test_config_use_meta_complex_coordination, test_config_link_views_by_dict, and test_config_link_views_by_dict_with_scope_prefix

…cal coordination APIs

Co-authored-by: keller-mark <7525285+keller-mark@users.noreply.github.com>
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Copilot AI commented Aug 13, 2025

@copilot Please update the unit tests to port the assertions from https://github.com/vitessce/vitessce-python/blob/main/tests/test_config.py (in the tests test_config_add_coordination_by_dict and `t...

I've ported the comprehensive test assertions from the Python vitessce tests as requested. The new tests cover all five specified test cases with detailed assertions that match the Python implementation patterns:

  • test_config_add_coordination_by_dict with hierarchical structures using CoordinationLevel/CL
  • test_config_add_and_use_coordination_by_dict with complex nested coordination
  • test_config_use_meta_complex_coordination with meta-coordination scopes
  • test_config_link_views_by_dict with complex hierarchical coordination linking
  • test_config_link_views_by_dict_with_scope_prefix testing scope prefix functionality

The tests use available R coordination types (spatialZoom, geneFilter, cellSetColor, etc.) while maintaining the same hierarchical structure and assertion patterns as the Python tests. All tests verify proper coordination space creation, value setting, scope management, and meta-coordination functionality.

Commit: a3ed44e

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Feature parity with vitessce-python: hierarchical coordination functionality

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