diff --git a/lib/galaxy/tool_util/verify/asserts/image.py b/lib/galaxy/tool_util/verify/asserts/image.py
index ff3c0899dcc..9f077900714 100644
--- a/lib/galaxy/tool_util/verify/asserts/image.py
+++ b/lib/galaxy/tool_util/verify/asserts/image.py
@@ -59,8 +59,10 @@ def assert_image_has_intensities(
output_bytes: bytes,
channel: Optional[Union[int, str]] = None,
mean_intensity: Optional[Union[float, str]] = None,
+ mean_intensity_min: Optional[Union[float, str]] = None,
+ mean_intensity_max: Optional[Union[float, str]] = None,
center_of_mass: Optional[Union[Tuple[float, float], str]] = None,
- eps: Union[float, str] = 1e-8,
+ eps: Union[float, str] = 0.01,
) -> None:
"""
Assert the image output has specific intensity content.
@@ -74,10 +76,26 @@ def assert_image_has_intensities(
im_arr = im_arr[:, :, int(channel)]
# Perform `mean_intensity` assertion.
+ actual_mean_intensity = im_arr.mean()
if mean_intensity is not None:
- actual = im_arr.mean()
- expected = float(mean_intensity)
- assert abs(actual - expected) <= float(eps), f"Wrong mean intensity: {actual} (expected {expected}, eps: {eps})"
+ 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 `center_of_mass` assertion.
if center_of_mass is not None:
@@ -86,19 +104,21 @@ def assert_image_has_intensities(
assert len(center_of_mass_parts) == 2
center_of_mass = (float(center_of_mass_parts[0]), float(center_of_mass_parts[1]))
assert len(center_of_mass) == 2, "center_of_mass must have two components"
- actual = _compute_center_of_mass(im_arr)
- distance = numpy.linalg.norm(numpy.subtract(center_of_mass, actual))
+ actual_center_of_mass = _compute_center_of_mass(im_arr)
+ distance = numpy.linalg.norm(numpy.subtract(center_of_mass, actual_center_of_mass))
assert distance <= float(
eps
- ), f"Wrong center of mass: {actual} (expected {center_of_mass}, distance: {distance}, eps: {eps})"
+ ), f"Wrong center of mass: {actual_center_of_mass} (expected {center_of_mass}, distance: {distance}, eps: {eps})"
def assert_image_has_labels(
output_bytes: bytes,
number_of_objects: Optional[Union[int, str]] = None,
mean_object_size: Optional[Union[float, str]] = None,
+ mean_object_size_min: Optional[Union[float, str]] = None,
+ mean_object_size_max: Optional[Union[float, str]] = None,
exclude_labels: Optional[Union[str, List[int]]] = None,
- eps: Union[float, str] = 1e-8,
+ eps: Union[float, str] = 0.01,
) -> None:
"""
Assert the image output has specific label content.
@@ -134,9 +154,23 @@ def assert_image_has_labels(
), f"Wrong number of objects: {actual_number_of_objects} (expected {expected_number_of_objects})"
# 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:
- actual_mean_object_size = sum((im_arr == label).sum() for label in labels) / len(labels)
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})"
diff --git a/lib/galaxy/tool_util/xsd/galaxy.xsd b/lib/galaxy/tool_util/xsd/galaxy.xsd
index 718892a12cf..73a3e7f3e1a 100644
--- a/lib/galaxy/tool_util/xsd/galaxy.xsd
+++ b/lib/galaxy/tool_util/xsd/galaxy.xsd
@@ -2798,19 +2798,29 @@ $attribute_list::5
The required mean value of the image intensities.
+
+
+ A lower bound of the required mean value of the image intensities.
+
+
+
+
+ An upper bound of the required mean value of the image intensities.
+
+
The required center of mass of the image intensities (horizontal and vertical coordinate, separated by a comma).
-
+
- The absolute tolerance to be used for the ``mean_intensity`` and ``center_of_mass`` assertions (defaults to ``1e-8``).
+ The absolute tolerance to be used for the ``mean_intensity`` and ``center_of_mass`` assertions (defaults to ``0.01``).
- Restricts the ``mean_intensity`` and ``center_of_mass`` assertions to a specific channel of the image (where the value ``0`` corresponds to the first image channel).
+ Restricts the ``mean_intensity``, ``mean_intensity_min``, ``mean_intensity_max``, and ``center_of_mass`` assertions to a specific channel of the image (where the value ``0`` corresponds to the first image channel).
@@ -2837,9 +2847,19 @@ $attribute_list::5
The required mean size of the objects in the image, where the size of an object is measured by the number of pixels. It is assumed that each individual object corresponds to a unique label.
-
+
- The absolute tolerance to be used for the ``mean_object_size`` assertion (defaults to ``1e-8``).
+ A lower bound of the required mean size of the objects in the image, where the size of an object is measured by the number of pixels. It is assumed that each individual object corresponds to a unique label.
+
+
+
+
+ An upper bound of the required mean size of the objects in the image, where the size of an object is measured by the number of pixels. It is assumed that each individual object corresponds to a unique label.
+
+
+
+
+ The absolute tolerance to be used for the ``mean_object_size`` assertion (defaults to 0.01).
diff --git a/test/functional/tools/validation_image.xml b/test/functional/tools/validation_image.xml
index 8789d9655bf..421736f36cc 100644
--- a/test/functional/tools/validation_image.xml
+++ b/test/functional/tools/validation_image.xml
@@ -15,7 +15,7 @@
@@ -47,6 +47,30 @@
+
+
+
+
+
+
+
+
+
+
+
+
@@ -83,5 +107,29 @@
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file