Testing for conflicts#84
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ATP media update
biomass index
…ted in element uptake
mstemplate biomass
# Conflicts: # modelseedpy/core/msatpcorrection.py # modelseedpy/core/msmodel.py # modelseedpy/core/mstemplate.py # setup.py
…simulation, biochemistry, and gapfilling
- Implements expression-constrained flux balance analysis - Handles genome-to-model and type transformations automatically - Integrates with ExpressionActivationPkg for optimization - Includes comprehensive NumPy-style docstring with examples - Adds 12 unit tests covering all functionality and edge cases - Validates thresholds, conditions, and model compatibility - Related to PRD 0001 and task list tasks-0001
…hat lack all dependencies
Fixed issue where reaction expression values were blank when converting from gene-level to reaction-level expression. The problem occurred when expression data was loaded without a genome or when model gene IDs didn't match genome feature IDs. The original code only searched through the genome object, failing to find genes with different ID formats (e.g., model has ACIAD#### but expression has ACIAD_RS#####). Changes: - First attempt direct lookup in self.features by gene ID - Fall back to genome search (which supports aliases) if direct lookup fails - This allows matching when gene IDs are identical, even without a genome - Maintains backward compatibility with genome-based alias resolution Fixes blank reaction expression values in genome-to-model conversion. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
Integrates a new method to average expression data across replicates for each strain. This method: - Takes replicate columns (e.g., ACN2586_1, ACN2586_2) and averages them into single columns per strain - Properly uses MSCondition class instead of a fake ExpressionCondition - Returns a new MSExpression object with averaged data - Handles cases where replicates exist, single columns exist, or no data is found - Includes comprehensive logging and error handling This method is useful for preprocessing expression data before analysis.
…011CUoKZ7YGo72duYdrs7oTT Add average_expression_replicates method to MSExpression
…ance of claude web
…fixes to community and flexible biomass and thermo and adding features to msexpression
MSTemplateBuilder.from_dict() was silently dropping the drain_list from template JSON files, so template.drains stayed empty. This meant MSBuilder.build_drains() fell back to DEFAULT_SINKS and only created SK_ (sink) reactions, never DM_ (demand) reactions. Without DM_cpd11416_c0, cobrapy FBA returns 0 growth because the biomass compound (cpd11416) produced by bio1 has no outlet. Two fixes: 1. mstemplate.py: from_dict() now reads drain_list into builder.drains 2. msbuilder.py: build_demands() creates DM_ reactions for all drain compounds (previously required lower_bound < 0, but template drain_list entries use [0, 1000]) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Fix drain_list loading: create DM_ demand reactions during model build
…dd frontmatter - Replace 306-line obsolete CLAUDE.md with focused tier-split version - Remove non-home expert/dev skills (only universal + home-repo skills remain) - Retire: run_headless, free-agent, analyze-email, generate-tasks, create-prd, create-skill - Add YAML frontmatter (name, description, scope) to all surviving skills Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Convention pivot: .claude/commands/ is now runtime-only (gitignored, populated by `claude-skills sync`). Source-of-truth lives in agent-io/skills/.
…feature lookup
Two related changes that unblock the modelseed-api bulk-reconstruction
endpoint (Phase 3 per Chris Henry's PRD).
1. New factory: AnnotationOntology.from_prd_input(genome_id, annotations,
data_dir, translator, ...). Mirrors from_kbase_data but for inputs
whose ontology terms have NOT been pre-translated to ModelSEED
reaction IDs. The translator callable is injected so the factory
stays decoupled from any specific translation backend
(KBUtilLib.KBAnnotationUtils.translate_term_to_modelseed is the
canonical impl; tests use a small in-memory fake).
Input shape: {gene_id: {ontology_type: [{term, score}, ...]}}.
Synthesizes one AnnotationOntologyEvent per ontology type, keeps
priority-list logic untouched. Unmapped terms (translator returns
[]) are retained with an empty msrxns set - per PRD, unmapped genes
must never silently disappear.
2. Fix latent bug at msbuilder.py:789 in build_from_annotaton_ontology.
The line called anno_ont.get_feature(gene.id) but AnnotationOntology
has no such method (features are keyed in genes or cdss dicts). Any
call path that reached this line would AttributeError as soon as it
tried to attach evidence to a built reaction. Replaced with the
correct accessor: anno_ont.genes.get(gene.id) or anno_ont.cdss.get(gene.id).
9 unit tests cover both changes:
- 7 cases for from_prd_input (happy path, multi-gene/multi-ontology,
score recording, default score, unmapped retention, namespaced-term
passing, empty input)
- 2 regression tests for the msbuilder fix (one positive, one negative
lock to flag if get_feature is ever added back without reconciling
the msbuilder line)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…d-input feat(annoont): AnnotationOntology.from_prd_input + fix msbuilder get_feature lookup
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