def test_topo_sort(self, session):
canvas = Planner(session)
ops = canvas.chain(
"Assemble Plasmid",
"Transform Cells",
"Plate Transformed Cells",
"Check Plate",
category="Cloning",
)
ops[-1].x = 500
for _ in range(3):
canvas.chain(ops[-1], ("E Coli Lysate", "Cloning"), "E Coli Colony PCR")
lysate = canvas.get_op_by_name("E Coli Lysate")
pcr = canvas.get_op_by_name("E Coli Colony PCR")
canvas.layout.ops_to_subgraph(pcr).translate(100, 100)
assert not canvas.layout.ops_to_subgraph(lysate).midpoint()[0] == ops[-1].x
assert (
not canvas.layout.ops_to_subgraph(lysate).midpoint()[0]
== canvas.layout.ops_to_subgraph(pcr).midpoint()[0]
)
canvas.layout.topo_sort()
assert canvas.layout.ops_to_subgraph(lysate).midpoint()[0] == ops[-1].x
assert (
canvas.layout.ops_to_subgraph(lysate).midpoint()[0]
== canvas.layout.ops_to_subgraph(pcr).midpoint()[0]
)
def test_align_x_with_predecessors(self, session):
canvas = Planner(session)
ops = canvas.chain(
"Assemble Plasmid",
"Transform Cells",
"Plate Transformed Cells",
"Check Plate",
category="Cloning",
)
new_ops = canvas.get_op_by_name("E Coli Lysate")
print(len(new_ops))
for _ in range(3):
print("created")
canvas.chain(ops[-1], "E Coli Lysate", category="Cloning")
new_ops = canvas.get_op_by_name("E Coli Lysate")
print(len(new_ops))
new_ops[0].x = 0
new_ops[1].x = 100
new_ops[2].x = 150
ops_layout = canvas.layout.ops_to_subgraph(ops)
new_op_layout = canvas.layout.ops_to_subgraph(new_ops)
midpoint = new_op_layout.midpoint()
assert midpoint[0] == 75, "should be midpoint between 0 and 150"
assert midpoint[0] != ops_layout.midpoint()[0]
new_op_layout.align_x_midpoints_to(ops_layout)
for op in new_op_layout.operations:
print(op.rid)
print(op.x)
print()
assert new_op_layout.midpoint()[0] == ops_layout.midpoint()[0]
def test_optimize3(self, session):
"""Here we setup two operations chains of 5.
6 of these operations will be mergable (10 to 7). We also add
additional operations to one of the Miniprep operations. We
should end up with 9 operations after the optimization.
Additionally, the merged Miniprep should have a single output
with 3 wires.
"""
with session.with_cache() as sess:
canvas = Planner(sess)
q = self.sql({
"object_type_id":
sess.ObjectType.find_by_name("E coli Plate of Plasmid").id,
"location":
self.Not("deleted"),
})
item = sess.Item.one(query=q)
assert item
chain = [
"Check Plate",
"Make Overnight Suspension",
"Make Miniprep",
"Yeast Transformation",
"Yeast Overnight Suspension",
]
ops = canvas.chain(*chain)
canvas.set_field_value_and_propogate(ops[0].inputs[0],
sample=item.sample)
canvas.set_to_available_item(ops[0].inputs[0])
ops[-1].tagged = "YES"
ops = canvas.chain(*chain)
canvas.set_field_value_and_propogate(ops[0].inputs[0],
sample=item.sample)
canvas.set_to_available_item(ops[0].inputs[0])
canvas.chain(ops[2], "Yeast Transformation")
canvas.chain(ops[2], "Make PCR Fragment")
assert len(canvas.plan.operations) == 12
assert len(canvas.get_outgoing_wires(ops[2].outputs[0])) == 3
canvas.optimize()
assert len(canvas.plan.operations) == 9
assert len(canvas.get_outgoing_wires(ops[2].outputs[0])) == 4
for yt in canvas.get_op_by_name("Yeast Transformation"):
print(yt.inputs[0].name)
assert len(canvas.get_incoming_wires(yt.inputs[0]))
def test_optimize_case5_array_inputs_merge_missing_samples(self, session):
with session.with_cache() as sess:
canvas = Planner(sess)
canvas.logger.set_level("DEBUG")
q = self.sql({
"object_type_id":
sess.ObjectType.find_by_name("Fragment Stock").id,
"location":
self.Not("deleted"),
})
primers = sess.Sample.last(
4,
query={
"sample_type_id": sess.SampleType.find_by_name("Primer").id
})
fragments = sess.Sample.last(
4,
query={
"sample_type_id":
sess.SampleType.find_by_name("Fragment").id
})
plasmids = sess.Sample.last(
3,
query={
"sample_type_id":
sess.SampleType.find_by_name("Plasmid").id
})
subchain = [
"Make PCR Fragment",
"Run Gel",
"Extract Gel Slice",
"Purify Gel Slice",
]
ops1 = canvas.chain(*(subchain + ["Assemble Plasmid"]))
ops2 = canvas.chain(*(subchain + ops1[-1:]))
ops3 = canvas.chain(*(subchain + ["Assemble Plasmid"]))
ops4 = canvas.chain(*(subchain + ops3[-1:]))
ops5 = canvas.chain(*(subchain + ["Assemble Plasmid"]))
ops6 = canvas.chain(*(subchain + ops5[-1:]))
ops7 = canvas.chain(*(subchain + ops5[-1:]))
ops8 = canvas.chain(*(subchain + ops5[-1:]))
ops9 = canvas.chain(*(subchain + ops5[-1:]))
for op in canvas.get_op_by_name("Run Gel"):
pour_gel = canvas.chain("Pour Gel", op)[0]
# pour_gels = [op for op in canvas.operations if
# op.operation_type.name == 'Pour Gel']
# print([op.outputs[0].sample for op in pour_gels])
# chain1 using primer1
canvas.set_field_value_and_propogate(ops1[0].outputs[0],
sample=fragments[0])
# chain2 using primer2
canvas.set_field_value_and_propogate(ops2[0].outputs[0],
sample=fragments[1])
# chain3 using primer2
canvas.set_field_value_and_propogate(ops3[0].outputs[0],
sample=fragments[1])
# chain4 using primer1
canvas.set_field_value_and_propogate(ops4[0].outputs[0],
sample=fragments[0])
canvas.set_field_value_and_propogate(ops6[0].outputs[0],
sample=fragments[1])
canvas.set_field_value_and_propogate(ops7[0].outputs[0],
sample=fragments[1])
def pcr(op, p1, p2, t):
canvas.set_field_value(op.input("Forward Primer"), sample=p1)
canvas.set_field_value(op.input("Reverse Primer"), sample=p2)
canvas.set_field_value(op.input("Template"), sample=t)
pcr(ops1[0], primers[0], primers[1], plasmids[0])
pcr(ops2[0], primers[2], primers[3], plasmids[1])
pcr(ops4[0], primers[0], primers[1], plasmids[0])
pcr(ops3[0], primers[2], primers[3], plasmids[1])
canvas.set_field_value(ops1[-1].outputs[0], sample=plasmids[2])
canvas.set_field_value(ops3[-1].outputs[0], sample=plasmids[2])
op_types = sorted(
[op.operation_type.name for op in canvas.operations])
print(op_types)
canvas.optimize(merge_missing_samples=True)
op_types = sorted(
[op.operation_type.name for op in canvas.operations])
print(op_types)
assert len(canvas.get_op_by_name("Assemble Plasmid")) == 2
assert len(canvas.get_op_by_name("Pour Gel")) == 4
for op in canvas.get_op_by_name("Assemble Plasmid"):
assert len({fv.child_sample_id for fv in op.inputs}) == 2
assert len(op.inputs) in [5, 2]
