some minor edits

1 files changed, 7 insertions, 22 deletions

diff --git a/my_functions.py b/my_functions.py
index 1f76b82..49dc87d 100644
--- a/my_functions.py
+++ b/my_functions.py
@@ -94,28 +94,13 @@ def calc_translation_matrix(x_translation, y_translation, z_translation):
 
 ##############################################################
 # interpolate function
-# used to find a value in an inte
-rval with the specified mode.
+# used to find a value in an interval with the specified mode.
 # So that it is clear that the values are points that have 2
 # coordinates I will treat the input as they are (x,y) points
 # the function will either return m_x or m_y depending on
-# which of the middle point value
-
-s is provided to the function
+# which of the middle point values is provided to the function
 # (set None to the variable going to be returned by the 
-# function). Smooth will use the Cubic Hermite Spline 
-# interpolation method and will be the one using the point's
-# derivatives/tangent.
-#
-# IMPORTANT (FOR SMOOTH INTERPOLA
-TION):
-#
-# As I don't really have information on how to define
-# tangent-out or tangent in/out interpolation (as JAE has
-# already done those calculations) I will use the same 
-# interpolation method to both tangent-out or tangent in/out
-# CSV files. If someone knows about this better please open
-# an issue on blenxy's repository
+# function). Only linear interpolation is supported for now.
 #
 # l_x (float) --> left point X axis component
 # l_y (float) --> left point Y axis component
@@ -124,7 +109,6 @@ TION):
 # m_x (float) --> middle point X axis component
 # m_y (float) --> middle point Y axis component
 # interp_type (string) --> "linear" for linear interpolation
-#                          "smooth" for smooth interpolation
 ##############################################################
 def interpolate(l_x, l_y, r_x, r_y, m_x, m_y, interp_type):
 #
@@ -141,16 +125,17 @@ def interpolate(l_x, l_y, r_x, r_y, m_x, m_y, interp_type):
   ###############################
   # m_x is the one to be returned
   if (m_x == None):
+    
+    # linear interpolation
     if (interp_type == "linear"):
       m_x = (((r_x - l_x) / (r_y - l_y)) * (m_y - r_y)) + r_x
       result = m_x
       
-    else: # interpolation type is "smooth"
-            
-      
   ###############################
   # m_y is the one to be returned
   if (m_y == None):
+    
+    # linear interpolation
     if (interp_type == "linear"):
       m_y = (((r_y - l_y) / (r_x - l_x)) * (m_x - r_x)) + r_y
       result = m_y