Merge pull request #61 from blowekamp/restore_clamp

Restore clamping for the computed visual min max range.

pytools/workflow_functions.py

@@ -28,6 +28,7 @@
 def visual_min_max(
     input_image: Union[Path, str],
     mad_scale: float,
+    clamp: bool = True,
 ) -> Dict[str, int]:
     """Reads a path to an input_image file or a directory of zarr array to estimate minimum and maximum ranges to be
     used for visualization of the data set in Neuroglancer.
@@ -43,6 +44,9 @@ def visual_min_max(
     :param mad_scale: The scale factor for the robust median absolute deviation (MAD) about the median to produce the
         "minimum and maximum range."
 
+    :param clamp: If True then the minimum and maximum range will be clamped to the computed floor and limit values.
+
+
     :returns: The resulting dictionary will contain the following data elements with integer values as strings:
        - "neuroglancerPrecomputedMin"
        - "neuroglancerPrecomputedMax"
@@ -77,6 +81,10 @@ def visual_min_max(
 
     floor_limit = weighted_quantile(mids, quantiles=[0.0, 1.0], sample_weight=h, values_sorted=True)
 
+    if clamp:
+        logger.debug(f"clamping min_max: {min_max} to floor_limit: {floor_limit}")
+        min_max = (max(min_max[0], floor_limit[0]), min(min_max[1], floor_limit[1]))
+
     output = {
         "neuroglancerPrecomputedMin": str(math.floor(min_max[0])),
         "neuroglancerPrecomputedMax": str(math.ceil(min_max[1])),

test/test_histogram.py

@@ -76,18 +76,20 @@ def test_histogram_robust_stats():
 
 
 @pytest.mark.parametrize(
-    "image_mrc,expected_min, expected_max, expected_floor, expected_limit",
+    "image_mrc,expected_min, expected_max, expected_floor, expected_limit, clamp",
     [
-        (sitk.sitkUInt8, 0, 0, 0, 0),
-        (sitk.sitkUInt16, 0, 0, 0, 0),
-        ("uint16_uniform", 8191, 57344, 0, 65535),
-        ("float32_uniform", 0, 1, 0, 1),
-        ("uint8_bimodal", -64, 319, 0, 255),
+        (sitk.sitkUInt8, 0, 0, 0, 0, False),
+        (sitk.sitkUInt16, 0, 0, 0, 0, False),
+        ("uint16_uniform", 8191, 57344, 0, 65535, False),
+        ("uint16_uniform", 8191, 57344, 0, 65535, True),
+        ("float32_uniform", 0, 1, 0, 1, False),
+        ("uint8_bimodal", -64, 319, 0, 255, False),
+        ("uint8_bimodal", 0, 255, 0, 255, True),
     ],
     indirect=["image_mrc"],
 )
-def test_build_histogram_main(image_mrc, expected_min, expected_max, expected_floor, expected_limit):
-    res = pytools.visual_min_max(Path(image_mrc), mad_scale=1.5)
+def test_build_histogram_main(image_mrc, expected_min, expected_max, expected_floor, expected_limit, clamp):
+    res = pytools.visual_min_max(Path(image_mrc), mad_scale=1.5, clamp=clamp)
 
     assert "neuroglancerPrecomputedMin" in res
     assert "neuroglancerPrecomputedMax" in res