From 9bea876fe57781e4632e71ad41d6bef7ec64d497 Mon Sep 17 00:00:00 2001
From: natejly <natejly@gmail.com>
Date: Thu, 16 May 2024 13:57:56 -0500
Subject: [PATCH] changed filter to mask_filter

---
 plantcv/plantcv/roi/__init__.py    |  4 ++--
 plantcv/plantcv/roi/roi_methods.py |  2 +-
 tests/plantcv/roi/test_roi.py      | 14 +++++++-------
 3 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/plantcv/plantcv/roi/__init__.py b/plantcv/plantcv/roi/__init__.py
index 72a26dad6..4cfa30705 100644
--- a/plantcv/plantcv/roi/__init__.py
+++ b/plantcv/plantcv/roi/__init__.py
@@ -5,9 +5,9 @@
 from plantcv.plantcv.roi.roi_methods import auto_grid
 from plantcv.plantcv.roi.roi_methods import multi
 from plantcv.plantcv.roi.roi_methods import custom
-from plantcv.plantcv.roi.roi_methods import filter
+from plantcv.plantcv.roi.roi_methods import mask_filter
 from plantcv.plantcv.roi.roi2mask import roi2mask
 from plantcv.plantcv.roi.quick_filter import quick_filter
 
 __all__ = ["circle", "ellipse", "from_binary_image", "rectangle", "auto_grid", "multi", "custom",
-           "filter", "roi2mask", "quick_filter"]
+           "mask_filter", "roi2mask", "quick_filter"]
diff --git a/plantcv/plantcv/roi/roi_methods.py b/plantcv/plantcv/roi/roi_methods.py
index 8148311f6..e034b7d99 100644
--- a/plantcv/plantcv/roi/roi_methods.py
+++ b/plantcv/plantcv/roi/roi_methods.py
@@ -425,7 +425,7 @@ def custom(img, vertices):
 
 
 # Filter a mask based on a region of interest
-def filter(mask, roi, roi_type="partial"):
+def mask_filter(mask, roi, roi_type="partial"):
     """Filter a mask using a region of interest. Connected regions of non-zero pixels outside the ROI turn to zero
 
     Inputs:
diff --git a/tests/plantcv/roi/test_roi.py b/tests/plantcv/roi/test_roi.py
index c643a069e..ebd87988c 100644
--- a/tests/plantcv/roi/test_roi.py
+++ b/tests/plantcv/roi/test_roi.py
@@ -2,7 +2,7 @@
 import cv2
 import numpy as np
 from plantcv.plantcv import Objects
-from plantcv.plantcv.roi import from_binary_image, rectangle, circle, ellipse, auto_grid, multi, custom, filter
+from plantcv.plantcv.roi import from_binary_image, rectangle, circle, ellipse, auto_grid, multi, custom, mask_filter
 
 
 def test_from_binary_image(roi_test_data):
@@ -247,7 +247,7 @@ def test_filter(mode, exp, test_data):
     roi = [np.array([[[150, 150]], [[150, 174]], [[249, 174]], [[249, 150]]], dtype=np.int32)]
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     roi_Obj = Objects(contours=[roi], hierarchy=[roi_str])
-    filtered_mask = filter(mask=mask, roi=roi_Obj, roi_type=mode)
+    filtered_mask = mask_filter(mask=mask, roi=roi_Obj, roi_type=mode)
     area = cv2.countNonZero(filtered_mask)
     # Assert that the contours were filtered as expected
     assert area == exp
@@ -264,7 +264,7 @@ def test_filter_multi(test_data):
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     # make a multi-ROI by repeating the same roi twice
     roi_Obj = Objects(contours=[roi, roi], hierarchy=[roi_str, roi_str])
-    filtered_mask = filter(mask=mask, roi=roi_Obj, roi_type="partial")
+    filtered_mask = mask_filter(mask=mask, roi=roi_Obj, roi_type="partial")
     area = cv2.countNonZero(filtered_mask)
     # Assert that the contours were filtered as expected
     assert area == 221
@@ -281,7 +281,7 @@ def test_filter_bad_input(test_data):
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     roi_Obj = Objects(contours=[roi], hierarchy=[roi_str])
     with pytest.raises(RuntimeError):
-        _ = filter(mask=mask, roi=roi_Obj, roi_type="cut")
+        _ = mask_filter(mask=mask, roi=roi_Obj, roi_type="cut")
 
 
 def test_filter_grayscale_input(test_data):
@@ -294,7 +294,7 @@ def test_filter_grayscale_input(test_data):
     roi = [np.array([[[150, 150]], [[150, 174]], [[249, 174]], [[249, 150]]], dtype=np.int32)]
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     roi_Obj = Objects(contours=[roi], hierarchy=[roi_str])
-    filtered_mask = filter(mask=mask, roi=roi_Obj, roi_type="partial")
+    filtered_mask = mask_filter(mask=mask, roi=roi_Obj, roi_type="partial")
     area = cv2.countNonZero(filtered_mask)
     # Assert that the contours were filtered as expected
     assert area == 221
@@ -310,7 +310,7 @@ def test_filter_no_overlap(test_data):
     roi = [np.array([[[0, 0]], [[0, 24]], [[24, 24]], [[24, 0]]], dtype=np.int32)]
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     roi_Obj = Objects(contours=[roi], hierarchy=[roi_str])
-    filtered_mask = filter(mask=mask, roi=roi_Obj, roi_type="partial")
+    filtered_mask = mask_filter(mask=mask, roi=roi_Obj, roi_type="partial")
     area = cv2.countNonZero(filtered_mask)
     # Assert that the contours were filtered as expected
     assert area == 0
@@ -334,7 +334,7 @@ def test_filter_nested():
     roi = [np.array([[[0, 0]], [[0, 99]], [[99, 99]], [[99, 0]]], dtype=np.int32)]
     roi_str = np.array([[[-1, -1, -1, -1]]], dtype=np.int32)
     roi_Obj = Objects(contours=[roi], hierarchy=[roi_str])
-    filtered_mask = filter(mask=mask, roi=roi_Obj, roi_type="largest")
+    filtered_mask = mask_filter(mask=mask, roi=roi_Obj, roi_type="largest")
     filtered_area = cv2.countNonZero(filtered_mask)
     assert area_pre == filtered_area
     assert area_total > filtered_area