def test_algorithm(autoplanner, session):
browser = Browser(session)
sample_composition = nx.DiGraph()
edges = [
("DTBA_backboneA_splitAMP", "pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
("T1MC_NatMX-Cassette_MCT2 (JV)",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
(
"BBUT_URA3.A.0_homology1_UTP1 (from genome)",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1",
),
("MCDT_URA3.A.1_homology2_DTBA",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
("DH5alpha", "pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
("TP-IRES-EGFP-TS", "pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
(
"BBUT_URA3.A.1_homology1_UTP1 (from_genome) (new fwd primer))",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1",
),
]
for n1, n2 in edges:
s1 = browser.find_by_name(n1)
s2 = browser.find_by_name(n2)
sample_composition.add_node(s1.id, sample=s1)
sample_composition.add_node(s2.id, sample=s2)
sample_composition.add_edge(s1.id, s2.id)
algorithm = NetworkOptimizer(browser, sample_composition,
autoplanner.template_graph)
algorithm.print_sample_composition()
algorithm.run(session.ObjectType.find_by_name("Plasmid Stock"))
def test_cache_where_name(session):
browser = Browser(session)
primers = browser.cached_where({"sample_type_id": 1}, "Sample")
primer1 = primers[0]
id1 = id(primer1)
primer2 = browser.find_by_name(primer1.name, "Sample", primary_key="id")
id2 = id(primer2)
assert id1 == id2
def test_get_sisters_for_run_gel(autoplan_model, session):
browser = Browser(session)
sample_composition = nx.DiGraph()
edges = [
# ('DTBA_backboneA_splitAMP', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
("T1MC_NatMX-Cassette_MCT2 (JV)",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
(
"BBUT_URA3.A.0_homology1_UTP1 (from genome)",
"pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1",
),
("DH5alpha", "pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1"),
("TP-IRES-EGFP-TS", "pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1")
# ('MCDT_URA3.A.1_homology2_DTBA', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
# ('BBUT_URA3.A.1_homology1_UTP1 (from_genome) (new fwd primer))', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1')
]
for n1, n2 in edges:
s1 = browser.find_by_name(n1)
s2 = browser.find_by_name(n2)
sample_composition.add_node(s1.id, sample=s1)
sample_composition.add_node(s2.id, sample=s2)
sample_composition.add_edge(s1.id, s2.id)
# s = production.Sample.find_by_name('MCDT-LEU-LEU.A.1_homology2_ampR-Split_A')
# sample_composition.add_node(s.id, sample=s)
# nx.draw(sample_composition)
network = NetworkOptimizer(browser, sample_composition,
autoplan_model.template_graph)
solution = network.run(
session.ObjectType.find_by_name("Plasmid Glycerol Stock"))
run_gels = []
for n, ndata in solution["graph"].iter_model_data(
model_class="AllowableFieldType"):
aft = ndata["model"]
if aft.field_type.operation_type.name == "Run Gel":
if aft.field_type.role == "input":
run_gels.append((n, ndata))
run_gels
sample_composition = nx.DiGraph()
edges = [
('DTBA_backboneA_splitAMP', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
('T1MC_NatMX-Cassette_MCT2 (JV)', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
('BBUT_URA3.A.0_homology1_UTP1 (from genome)', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
('DH5alpha', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
('TP-IRES-EGFP-TS', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1' ),
('MCDT_URA3.A.1_homology2_DTBA', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1'),
# ('pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1', 'CEN.PK2 - MAT alpha | his-pGRR-W5-W8-RGR-W36')
('BBUT_URA3.A.1_homology1_UTP1 (from_genome) (new fwd primer))', 'pyMOD-URA-URA3.A.1-pGPD-yeVenus-tCYC1')
]
for n1, n2 in edges:
s1 = browser.find_by_name(n1)
s2 = browser.find_by_name(n2)
sample_composition.add_node(s1.id, sample=s1)
sample_composition.add_node(s2.id, sample=s2)
sample_composition.add_edge(s1.id, s2.id)
# s = production.Sample.find_by_name('MCDT-LEU-LEU.A.1_homology2_ampR-Split_A')
# sample_composition.add_node(s.id, sample=s)
# nx.draw(sample_composition)
alg = NetworkOptimization(browser, sample_composition, ap.template_graph)
alg.set_verbose(True)
# alg.update_sample_composition
cost, paths, graph = alg.run(production.ObjectType.find_by_name('Plasmid Glycerol Stock'))