differences for PR #338

07-thresholding.md

@@ -478,9 +478,7 @@ def measure_root_mass(filename, sigma=1.0):
 
     # determine root mass ratio
     root_pixels = np.count_nonzero(binary_mask)
-    w = binary_mask.shape[1]
-    h = binary_mask.shape[0]
-    density = root_pixels / (w * h)
+    density = root_pixels / binary_mask.size
 
     return density
 ```
@@ -499,11 +497,8 @@ Recall that in the `binary_mask`, every pixel has either a value of
 zero (black/background) or one (white/foreground).
 We want to count the number of white pixels,
 which can be accomplished with a call to the NumPy function `np.count_nonzero`.
-Then we determine the width and height of the image by using
-the elements of `binary_mask.shape`
-(that is, the dimensions of the NumPy array that stores the image).
 Finally, the density ratio is calculated by dividing the number of white pixels
-by the total number of pixels `w*h` in the image.
+by the total number of pixels `binary_mask.size` in the image.
 The function returns then root density of the image.
 
 We can call this function with any filename and
@@ -650,9 +645,7 @@ def enhanced_root_mass(filename, sigma):
 
     # determine root mass ratio
     root_pixels = np.count_nonzero(binary_mask)
-    w = binary_mask.shape[1]
-    h = binary_mask.shape[0]
-    density = root_pixels / (w * h)
+    density = root_pixels / binary_mask.size
 
     return density
 

LICENSE.md

@@ -69,11 +69,11 @@ SOFTWARE.
 ## Trademark
 
 "The Carpentries", "Software Carpentry", "Data Carpentry", and "Library
-Carpentry" and their respective logos are registered trademarks of
-[The Carpentries, Inc.][carpentries].
+Carpentry" and their respective logos are registered trademarks of [Community
+Initiatives][ci].
 
 [cc-by-human]: https://creativecommons.org/licenses/by/4.0/
 [cc-by-legal]: https://creativecommons.org/licenses/by/4.0/legalcode
 [mit-license]: https://opensource.org/licenses/mit-license.html
-[carpentries]: https://carpentries.org
+[ci]: https://communityin.org/
 [osi]: https://opensource.org

md5sum.txt

@@ -1,6 +1,6 @@
 "file" "checksum" "built" "date"
 "CODE_OF_CONDUCT.md" "c93c83c630db2fe2462240bf72552548" "site/built/CODE_OF_CONDUCT.md" "2023-04-25"
-"LICENSE.md" "e94126b93e27bae014999c2e84ee93f8" "site/built/LICENSE.md" "2025-02-04"
+"LICENSE.md" "b24ebbb41b14ca25cf6b8216dda83e5f" "site/built/LICENSE.md" "2025-02-05"
 "config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
 "index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
 "episodes/01-introduction.md" "4fe9db38f75f93b3ffbdb3115d36b802" "site/built/01-introduction.md" "2024-11-28"
@@ -9,7 +9,7 @@
 "episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
 "episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
 "episodes/06-blurring.md" "894ff33379584a8ee777f779564d5b01" "site/built/06-blurring.md" "2024-06-18"
-"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
+"episodes/07-thresholding.md" "512a1806b8061dded3a68871e7bcdfe9" "site/built/07-thresholding.md" "2025-02-05"
 "episodes/08-connected-components.md" "f599af69b770c7234a4e7d4a06a7f6dd" "site/built/08-connected-components.md" "2024-11-13"
 "episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
 "instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"