224 lines
8.8 KiB
Python
224 lines
8.8 KiB
Python
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import importlib.util
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from pathlib import Path
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import yaml
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from gfa_core.ppi_string_policy import (
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STRING_SPECIES_MAP,
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build_ppi_species_diagnostic,
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evaluate_string_mapping_quality,
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normalize_gene_ids_for_string,
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reference_protein_candidate_paths,
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recommended_string_reference_species,
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species_to_string_code,
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string_taxon_id,
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)
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REPO_ROOT = Path(__file__).resolve().parents[2]
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def load_ppi_skill_module():
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path = REPO_ROOT / "skills/ppi/run.py"
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spec = importlib.util.spec_from_file_location("ppi_skill_run", path)
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module = importlib.util.module_from_spec(spec)
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assert spec and spec.loader
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spec.loader.exec_module(module)
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return module
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def test_shared_species_policy_resolves_common_aliases_without_silent_ath():
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assert species_to_string_code("Os", fallback="") == "osa"
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assert species_to_string_code("rice", fallback="") == "osa"
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assert species_to_string_code("not_a_species", fallback="") == ""
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assert STRING_SPECIES_MAP["ath"] == "3702"
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assert STRING_SPECIES_MAP["osa"]
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def test_every_declared_string_species_code_resolves_to_itself():
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unresolved = {
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code: species_to_string_code(code, fallback="")
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for code in STRING_SPECIES_MAP
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if species_to_string_code(code, fallback="") != code
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}
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assert unresolved == {}
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assert {
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code: string_taxon_id(code, fallback="") for code in STRING_SPECIES_MAP
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} == STRING_SPECIES_MAP
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def test_shared_species_policy_resolves_spinacia_as_string_supported_near_reference():
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assert species_to_string_code("Spinacia oleracea", fallback="") == "soe"
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assert string_taxon_id("Spinacia oleracea", fallback="") == "3562"
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recommendations = recommended_string_reference_species("Ft")
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assert recommendations[0]["species_code"] == "soe"
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assert recommendations[0]["species_name"] == "Spinacia oleracea"
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assert recommendations[0]["taxon_id"] == "3562"
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assert recommendations[0]["relationship"] == "same_order_caryophyllales"
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def test_osa_transcript_ids_normalize_to_gene_locus_ids():
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assert normalize_gene_ids_for_string(["Os01t0810800-01", "Os02t0000100"], "osa") == [
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"Os01g0810800",
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"Os02g0000100",
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]
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def test_mapping_quality_small_families_require_all_ids_mapped():
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one_missing = evaluate_string_mapping_quality(input_count=2, mapped_count=1)
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assert one_missing["status"] == "failed"
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assert one_missing["issue_code"] == "ppi_string_id_mapping_low"
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all_mapped = evaluate_string_mapping_quality(input_count=2, mapped_count=2)
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assert all_mapped["status"] == "success"
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def test_mapping_quality_general_thresholds():
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low_rate = evaluate_string_mapping_quality(input_count=20, mapped_count=9)
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assert low_rate["status"] == "failed"
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enough = evaluate_string_mapping_quality(input_count=20, mapped_count=10)
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assert enough["status"] == "success"
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def test_target_unsupported_with_reference_pep_requires_separate_ortholog_stage():
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diagnostic = build_ppi_species_diagnostic(
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requested_ppi_species="auto",
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target_species="Ft",
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target_string_supported=False,
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reference_species="At",
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reference_data_source="/data/ref_genome/ath/Arabidopsis.pep.fa",
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ortholog_mapping_used=False,
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fallback_level="near_reference",
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fallback_reason="target_species_not_supported_by_string",
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)
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assert diagnostic["status"] == "failed"
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assert diagnostic["diagnostics"]["issue_code"] == "ppi_requires_ortholog_mapping"
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assert diagnostic["diagnostics"]["required_next_stage"] == "ortholog"
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assert diagnostic["parameters"]["ppi_species_resolution"]["selected_string_species"] == ""
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def test_target_unsupported_without_reference_data_requests_reference_input():
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diagnostic = build_ppi_species_diagnostic(
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requested_ppi_species="auto",
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target_species="Ft",
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target_string_supported=False,
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reference_species="",
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reference_data_source="",
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ortholog_mapping_used=False,
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fallback_level="reference_data_missing",
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fallback_reason="target_species_not_supported_by_string",
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)
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assert diagnostic["status"] == "failed"
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assert diagnostic["diagnostics"]["issue_code"] == "ppi_reference_data_missing"
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assert diagnostic["diagnostics"]["required_next_stage"] == "ortholog"
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actions = diagnostic["diagnostics"]["recommended_actions"]
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assert [action["id"] for action in actions] == [
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"upload_reference_protein",
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"prepare_reference_download",
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"explicit_arabidopsis_last_resort",
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]
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assert actions[-1]["requires_confirmation"] is True
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assert actions[-1]["risk"] == "low_confidence_model_reference"
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def test_reference_protein_candidates_include_data_ref_genome_roots():
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candidates = reference_protein_candidate_paths("At", roots=[Path("/data/ref_genome"), Path("/data")])
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as_text = [str(path) for path in candidates]
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assert "/data/ref_genome/At/At.pep.fasta" in as_text
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assert "/data/ref_genome/ath/ath.pep.fa" in as_text
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assert "/data/At/At.pep.fasta" in as_text
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def test_frontend_ppi_defaults_do_not_force_ath():
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html = (REPO_ROOT / "apps/web/vue3/index.html").read_text(encoding="utf-8")
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assert "ppiSpecies: 'auto'" in html
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assert "ppiSpecies = 'ath'" not in html
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assert "ppiSpecies || 'ath'" not in html
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assert "confirmParams.ppiSpecies || 'ath'" not in html
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assert "stageParams.ppiSpecies || confirmParams.ppiSpecies || 'ath'" not in html
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def test_ppi_skill_metadata_marks_plots_optional_and_string_png_default():
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config = yaml.safe_load((REPO_ROOT / "skills/ppi/config.yaml").read_text(encoding="utf-8"))
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files = config["output"]["files"]
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optional_files = config["output"].get("optional_files", [])
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assert "{prefix}.ppi_network.pdf" not in files
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assert "{prefix}.ppi_network.pdf" in optional_files
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assert "{prefix}.ppi_network.string.png" in optional_files
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skill_doc = (REPO_ROOT / "skills/ppi/SKILL.md").read_text(encoding="utf-8")
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assert "STRING PNG" in skill_doc
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assert "可选" in skill_doc
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def test_legacy_cli_and_skill_use_shared_species_policy():
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string_api = (REPO_ROOT / "apps/cli/string_api.py").read_text(encoding="utf-8")
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skill_run = (REPO_ROOT / "skills/ppi/run.py").read_text(encoding="utf-8")
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backend = (REPO_ROOT / "apps/web/pipeline_backend.py").read_text(encoding="utf-8")
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assert "from gfa_core.ppi_string_policy import STRING_SPECIES_MAP" in string_api
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assert "from gfa_core.ppi_string_policy import" in skill_run
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assert "STRING_SPECIES_MAP" in skill_run
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assert "from gfa_core.ppi_string_policy import" in backend
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assert "species_to_string_code as _shared_species_to_string_code" in backend
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assert 'f"{prefix}_id_resolution.tsv": f"{prefix}.ppi_id_resolution.tsv"' in backend
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def test_ppi_skill_writes_id_resolution_report_and_manifest_metrics(tmp_path):
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module = load_ppi_skill_module()
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gene_file = tmp_path / "genes.txt"
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gene_file.write_text("Os01t0810800-01\nOs02t0000100\n", encoding="utf-8")
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class FakeStringClient:
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species_id = "39947"
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def __init__(self):
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self.mapping_calls = []
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self.network_calls = []
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def get_string_ids(self, identifiers):
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self.mapping_calls.append(list(identifiers))
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selected = {
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"Os01g0810800": "39947.Os01g0810800",
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"Os02g0000100": "39947.Os02g0000100",
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}
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return [
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{
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"queryIndex": index,
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"queryItem": identifier,
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"stringId": selected[identifier],
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"preferredName": identifier,
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"ncbiTaxonId": 39947,
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}
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for index, identifier in enumerate(identifiers)
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if identifier in selected
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]
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def get_network(self, identifiers, required_score=200, network_type="functional"):
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self.network_calls.append((list(identifiers), required_score, network_type))
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return []
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client = FakeStringClient()
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result = module.PpiSkill(
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string_api_factory=lambda _species: client
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).run(
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gene_ids_file=gene_file,
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species="osa",
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prefix="Os.CrR",
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output_dir=tmp_path / "ppi",
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required_score=200,
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)
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id_report = tmp_path / "ppi" / "Os.CrR_id_resolution.tsv"
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assert id_report.exists()
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text = id_report.read_text(encoding="utf-8")
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assert "Os01t0810800-01\t\tOs01t0810800-01\t\tOs01g0810800" in text
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assert result["metrics"]["id_resolution"]["input_member_count"] == 2
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assert result["metrics"]["id_resolution"]["raw_resolved_query_count"] == 2
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assert result["metrics"]["id_resolution"]["resolved_member_count"] == 2
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assert client.network_calls == [
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(["39947.Os01g0810800", "39947.Os02g0000100"], 200, "functional")
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]
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assert "id_resolution" in result["artifacts"]
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