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Enable caching for just-in-time compiled functions. #25

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Merged
roytsmart merged 1 commit into from
Mar 31, 2025
Merged

Enable caching for just-in-time compiled functions. #25

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6 changes: 3 additions & 3 deletions ndfilters/_convolve.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,7 @@ def convolve(
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _convolve_1d(
array: np.ndarray,
kernel: np.ndarray,
Expand Down Expand Up @@ -196,7 +196,7 @@ def _convolve_1d(
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _convolve_2d(
array: np.ndarray,
kernel: np.ndarray,
Expand Down Expand Up @@ -254,7 +254,7 @@ def _convolve_2d(
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _convolve_3d(
array: np.ndarray,
kernel: np.ndarray,
Expand Down
6 changes: 3 additions & 3 deletions ndfilters/_generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,7 @@ def function(a: np.ndarray, args: tuple) -> float:
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _generic_filter_1d(
array: np.ndarray,
function: Callable[[np.ndarray, tuple], float],
Expand Down Expand Up @@ -187,7 +187,7 @@ def _generic_filter_1d(
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _generic_filter_2d(
array: np.ndarray,
function: Callable[[np.ndarray, tuple], float],
Expand Down Expand Up @@ -252,7 +252,7 @@ def _generic_filter_2d(
return result


@numba.njit(parallel=True)
@numba.njit(parallel=True, cache=True)
def _generic_filter_3d(
array: np.ndarray,
function: Callable[[np.ndarray, tuple], float],
Expand Down
4 changes: 2 additions & 2 deletions ndfilters/_indices.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
]


@numba.njit
@numba.njit(cache=True)
def rectify_index_lower(index: int, size: int, mode: str) -> int:
if mode == "mirror":
return -index
Expand All @@ -18,7 +18,7 @@ def rectify_index_lower(index: int, size: int, mode: str) -> int:
raise ValueError


@numba.njit
@numba.njit(cache=True)
def rectify_index_upper(index: int, size: int, mode: str) -> int:
if mode == "mirror":
return ~(index % size + 1)
Expand Down
2 changes: 1 addition & 1 deletion ndfilters/_mean.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def mean_filter(
)


@numba.njit
@numba.njit(cache=True)
def _mean(
array: np.ndarray,
args: tuple[float],
Expand Down
2 changes: 1 addition & 1 deletion ndfilters/_median.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def median_filter(
)


@numba.njit
@numba.njit(cache=True)
def _median(
array: np.ndarray,
args: tuple[float],
Expand Down
2 changes: 1 addition & 1 deletion ndfilters/_trimmed_mean.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,7 +75,7 @@ def trimmed_mean_filter(
)


@numba.njit
@numba.njit(cache=True)
def _trimmed_mean(
array: np.ndarray,
args: tuple[float],
Expand Down
2 changes: 1 addition & 1 deletion ndfilters/_variance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def variance_filter(
)


@numba.njit
@numba.njit(cache=True)
def _variance(
array: np.ndarray,
args: tuple[float],
Expand Down