Update FHD calculation and documentation

Change the term from Frequency Histogram Diversity to Foliage Height Diversity for clarity. Enhanced function documentation to better explain the input parameters and the output format while highlighting areas with no voxel returns resulting in NaN values.

pyforestscan/calculate.py

@@ -148,16 +148,20 @@ def calculate_pai(pad, min_height=1, max_height=None):
 
 def calculate_fhd(voxel_returns):
     """
-    Calculate the Frequency Histogram Diversity (FHD) for a given set of voxel returns.
+    Calculate the Foliage Height Diversity (FHD) for a given set of voxel returns.
 
-    This function computes the Frequency Histogram Diversity by calculating the entropy
-    of the voxel return proportions along the z-axis.
+    This function computes Foliage Height Diversity by calculating the entropy
+    of the voxel return proportions along the z-axis, which represents vertical structure
+    in the canopy.
 
     :param voxel_returns:
-        A numpy array of shape (x, y, z) representing voxel returns.
+        A numpy array of shape (x, y, z) representing voxel returns, where x and y are spatial
+        dimensions, and z represents height bins (or layers along the vertical axis).
 
     :return:
-        A numpy array of shape (x, y"""
+        A numpy array of shape (x, y) representing the FHD values for each (x, y) location.
+        Areas with no voxel returns will have NaN values.
+    """
     sum_counts = np.sum(voxel_returns, axis=2, keepdims=True)
 
     with np.errstate(divide='ignore', invalid='ignore'):