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feat: add probe-specific logic to Primer3 #48
feat: add probe-specific logic to Primer3 #48
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## em_feat_add_Probe_object #48 +/- ##
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- Coverage 97.05% 96.60% -0.45%
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Files 25 26 +1
Lines 1664 1739 +75
Branches 317 337 +20
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+ Hits 1615 1680 +65
- Misses 26 31 +5
- Partials 23 28 +5 ☔ View full report in Codecov by Sentry. |
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@dataclass(frozen=True, init=True, kw_only=True, slots=True) | ||
class Probe(Primer, Metric["Probe"]): |
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issue Per discussion on the working group call today, we are going to add these fields directly to Primer
(and maybe rename the class to Oligo
or similar)
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I should have documented this because I just bumped up against why I defaulted them both to None
in the first place-- if you specify the default weights for either task, then Primer3 uses those weights as part of your scoring function, and it will complain if the corresponding params are not there, because it has no delta-off-optimal to score.
"""Stores task-specific characteristics for designing an internal hybridization probe.""" | ||
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@classmethod | ||
def _to_input_tags(cls, target: Span, design_region: Span) -> dict[Primer3InputTag, Any]: |
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question Does the task require either the target
or design_region
? How does primer3
know the range of valid locations for the probe?
else: | ||
if self.primer_weights is None: | ||
object.__setattr__(self, "primer_weights", PrimerAndAmpliconWeights()) | ||
elif self.task.requires_probe_params: |
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question Is it ever possible for a task to require both probe and primer params?
If so, you may want to consider checking both and then reporting all collected errors. But if they're mutually exclusive it's unnecessary
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