From 0b535dfba7881ea46fabc835225df93abc6f3fca Mon Sep 17 00:00:00 2001
From: Andrew Herzing <andrew.herzing@nist.gov>
Date: Fri, 28 Jun 2024 10:16:39 -0400
Subject: [PATCH] Added docstrings for several functions

---
 tomotools/base.py  |  5 +----
 tomotools/recon.py | 32 ++++++++++++++++++++++++++++++++
 2 files changed, 33 insertions(+), 4 deletions(-)

diff --git a/tomotools/base.py b/tomotools/base.py
index 590a0318..931c7bfe 100644
--- a/tomotools/base.py
+++ b/tomotools/base.py
@@ -327,10 +327,7 @@ class TomoStack(CommonStack):
     """
 
     def plot_sinos(self, *args, **kwargs):
-        """
-        Plot the TomoStack in sinogram orientation.
-
-        """
+        """Plot the TomoStack in sinogram orientation."""
         self.swap_axes(1, 0).swap_axes(1, 2).plot(navigator='slider', *args, **kwargs)
         return
 
diff --git a/tomotools/recon.py b/tomotools/recon.py
index ffc90361..e607ba27 100644
--- a/tomotools/recon.py
+++ b/tomotools/recon.py
@@ -348,12 +348,44 @@ def run(stack, method, niterations=20, constrain=None, thresh=0, cuda=None, thic
 
 
 def dart_segment(rec, thresholds, gray_vals):
+    """
+    Segmentation step for DART Reconstruction.
+
+    Args
+    ----------
+    rec : NumPy array
+       Tomographic reconstruction.
+    thresholds : list or NumPy array
+        Threshold values for segmentation.
+    gray_vals : list or NumPy array
+        Grayscale values to assign the segmented regions.
+
+    Returns
+    ----------
+    segmented : NumPy array
+        Segmented version of the reconstruction.
+
+    """
     bins = np.digitize(rec, bins=thresholds, right=False)
     segmented = np.array(gray_vals)[bins]
     return segmented
 
 
 def get_dart_boundaries(segmented):
+    """
+    Boundary step for DART Reconstruction.
+
+    Args
+    ----------
+    segmented : NumPy array
+        Segmented reconstruction.
+
+    Returns
+    ----------
+    boundaries : NumPy array
+        Boundaries of the segmented reconstruction.
+
+    """
     kernel = np.array([[1, 1, 1],
                        [1, -8, 1],
                        [1, 1, 1]])