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Add _assert_float function and refactor

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This commit is contained in:
Leonid Kostrykin
2024-03-04 17:28:19 +00:00
parent 5ce6045865
commit 7aebd26db4
1 changed files with 41 additions and 40 deletions
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lib/galaxy/tool_util/verify/asserts/image.py
+41 -40
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@@ -20,6 +20,30 @@ if TYPE_CHECKING:
import numpy.typing
def _assert_float(
actual: float,
label: str,
tolerance: Union[float, str],
expected: Optional[Union[float, str]] = None,
range_min: Optional[Union[float, str]] = None,
range_max: Optional[Union[float, str]] = None,
) -> None:
# Perform `tolerance` based check.
if expected is not None:
assert abs(actual - float(expected)) <= float(
tolerance
), f"Wrong {label}: {actual} (expected {expected} ±{tolerance})"
# Perform `range_min` based check.
if range_min is not None:
assert actual >= float(range_min), f"Wrong {label}: {actual} (must be {range_min} or larger)"
# Perform `range_max` based check.
if range_max is not None:
assert actual <= float(range_max), f"Wrong {label}: {actual} (must be {range_max} or smaller)"
def assert_image_has_metadata(
output_bytes: bytes,
width: Optional[Union[int, str]] = None,
@@ -75,27 +99,15 @@ def assert_image_has_intensities(
if channel is not None:
im_arr = im_arr[:, :, int(channel)]
# Perform `mean_intensity` assertion.
actual_mean_intensity = im_arr.mean()
if mean_intensity is not None:
mean_intensity = float(mean_intensity)
assert abs(actual_mean_intensity - mean_intensity) <= float(
eps
), f"Wrong mean intensity: {actual_mean_intensity} (expected {mean_intensity}, eps: {eps})"
# Perform `mean_intensity_min` assertion.
if mean_intensity_min is not None:
mean_intensity_min = float(mean_intensity_min)
assert (
actual_mean_intensity >= mean_intensity_min
), f"Wrong mean intensity: {actual_mean_intensity} (mean_intensity_min: {mean_intensity_min})"
# Perform `mean_intensity_max` assertion.
if mean_intensity_max is not None:
mean_intensity_max = float(mean_intensity_max)
assert (
actual_mean_intensity <= mean_intensity_max
), f"Wrong mean intensity: {actual_mean_intensity} (mean_intensity_max: {mean_intensity_max})"
# Perform `mean_intensity` assertions.
_assert_float(
actual=im_arr.mean(),
label="mean intensity",
tolerance=eps,
expected=mean_intensity,
range_min=mean_intensity_min,
range_max=mean_intensity_max,
)
# Perform `center_of_mass` assertion.
if center_of_mass is not None:
@@ -155,22 +167,11 @@ def assert_image_has_labels(
# Perform `mean_object_size` assertion.
actual_mean_object_size = sum((im_arr == label).sum() for label in labels) / len(labels)
if mean_object_size is not None:
expected_mean_object_size = float(mean_object_size)
assert abs(actual_mean_object_size - expected_mean_object_size) <= float(
eps
), f"Wrong mean object size: {actual_mean_object_size} (expected {expected_mean_object_size}, eps: {eps})"
# Perform `mean_object_size_min` assertion.
if mean_object_size_min is not None:
mean_object_size_min = float(mean_object_size_min)
assert (
actual_mean_object_size >= mean_object_size_min
), f"Wrong mean object size: {actual_mean_object_size} (mean_object_size_min: {mean_object_size_min})"
# Perform `mean_object_size_max` assertion.
if mean_object_size_max is not None:
mean_object_size_max = float(mean_object_size_max)
assert (
actual_mean_object_size <= mean_object_size_max
), f"Wrong mean object size: {actual_mean_object_size} (mean_object_size_max: {mean_object_size_max})"
_assert_float(
actual=actual_mean_object_size,
label="mean object size",
tolerance=eps,
expected=mean_object_size,
range_min=mean_object_size_min,
range_max=mean_object_size_max,
)