Ignore coverage for numba-compiled functions

Author: tomwhite

setup.cfg

@@ -66,7 +66,7 @@ bgen =
 fail_under = 100
 
 [tool:pytest]
-addopts = --doctest-modules --ignore=validation
+addopts = --doctest-modules --ignore=validation --cov-fail-under=100
 norecursedirs = .eggs docs
 filterwarnings =
     error

sgkit/distance/metrics.py

@@ -16,7 +16,7 @@
     nopython=True,
     cache=True,
 )
-def correlation(x: ArrayLike, y: ArrayLike, out: ArrayLike) -> None:
+def correlation(x: ArrayLike, y: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Calculates the correlation between two vectors.
 
     Parameters
@@ -85,7 +85,7 @@ def correlation(x: ArrayLike, y: ArrayLike, out: ArrayLike) -> None:
     nopython=True,
     cache=True,
 )
-def euclidean(x: ArrayLike, y: ArrayLike, out: ArrayLike) -> None:
+def euclidean(x: ArrayLike, y: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Calculates the euclidean distance between two vectors.
 
     Parameters

sgkit/stats/aggregation.py

@@ -26,7 +26,9 @@
     nopython=True,
     cache=True,
 )
-def count_alleles(g: ArrayLike, _: ArrayLike, out: ArrayLike) -> None:
+def count_alleles(
+    g: ArrayLike, _: ArrayLike, out: ArrayLike
+) -> None:  # pragma: no cover
     """Generalized U-function for computing per sample allele counts.
 
     Parameters
@@ -66,7 +68,7 @@ def count_alleles(g: ArrayLike, _: ArrayLike, out: ArrayLike) -> None:
 )
 def _count_cohort_alleles(
     ac: ArrayLike, cohorts: ArrayLike, _: ArrayLike, out: ArrayLike
-) -> None:
+) -> None:  # pragma: no cover
     """Generalized U-function for computing per cohort allele counts.
 
     Parameters

sgkit/stats/popgen.py

@@ -123,7 +123,7 @@ def diversity(
 @guvectorize(  # type: ignore
     ["void(int64[:, :], float64[:,:])"], "(c, k)->(c,c)", nopython=True, cache=True
 )
-def _divergence(ac: ArrayLike, out: ArrayLike) -> None:
+def _divergence(ac: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Generalized U-function for computing divergence.
 
     Parameters
@@ -295,7 +295,7 @@ def divergence(
     nopython=True,
     cache=True,
 )
-def _Fst_Hudson(d: ArrayLike, out: ArrayLike) -> None:
+def _Fst_Hudson(d: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Generalized U-function for computing Fst using Hudson's estimator.
 
     Parameters
@@ -327,7 +327,7 @@ def _Fst_Hudson(d: ArrayLike, out: ArrayLike) -> None:
     nopython=True,
     cache=True,
 )
-def _Fst_Nei(d: ArrayLike, out: ArrayLike) -> None:
+def _Fst_Nei(d: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Generalized U-function for computing Fst using Nei's estimator.
 
     Parameters
@@ -587,7 +587,7 @@ def Tajimas_D(
     nopython=True,
     cache=True,
 )
-def _pbs(t: ArrayLike, out: ArrayLike) -> None:
+def _pbs(t: ArrayLike, out: ArrayLike) -> None:  # pragma: no cover
     """Generalized U-function for computing PBS."""
     out[:, :, :] = np.nan  # (cohorts, cohorts, cohorts)
     n_cohorts = t.shape[0]