diff --git a/package/AUTHORS b/package/AUTHORS
index 35e4029f776..2cac431048e 100644
--- a/package/AUTHORS
+++ b/package/AUTHORS
@@ -236,6 +236,7 @@ Chronological list of authors
   2024
   - Aditya Keshari
   - Philipp Stärk
+  - SumairaAhmad
 
 External code
 -------------
diff --git a/package/CHANGELOG b/package/CHANGELOG
index b51a00014a9..9882e6f8a0a 100644
--- a/package/CHANGELOG
+++ b/package/CHANGELOG
@@ -62,7 +62,7 @@ Deprecations
 
 12/26/23 IAlibay, ianmkenney, PicoCentauri, pgbarletta, p-j-smith, 
          richardjgowers, lilyminium, ALescoulie, hmacdope, HeetVekariya, 
-         JoStoe, jennaswa, ljwoods2
+         JoStoe, jennaswa, ljwoods2, SumairaAhmad
 
  * 2.7.0
 
diff --git a/package/MDAnalysis/coordinates/timestep.pyx b/package/MDAnalysis/coordinates/timestep.pyx
index 09304ec85ee..f170059cddc 100644
--- a/package/MDAnalysis/coordinates/timestep.pyx
+++ b/package/MDAnalysis/coordinates/timestep.pyx
@@ -493,20 +493,31 @@ cdef class Timestep:
         vectors lengths followed by their respective angle, or as three
         triclinic vectors.
 
-          >>> ts.dimensions
-          array([ 13.,  14.,  15.,  90.,  90.,  90.], dtype=float32)
-          >>> ts.triclinic_dimensions
-          array([[ 13.,   0.,   0.],
-                 [  0.,  14.,   0.],
-                 [  0.,   0.,  15.]], dtype=float32)
+          .. testsetup::
+
+          >>> import MDAnalysis as mda
+          >>> from MDAnalysis.tests.datafiles import TPR, XTC
+          >>> import numpy as np
+          >>> u = mda.Universe(TPR, XTC)
+          >>> ts = u.trajectory[0] 
+               
+          .. doctest::
+                    
+          >>> print(np.round(ts.dimensions))
+          [80. 80. 80. 60. 60. 90.]
+          >>> print(np.round(ts.triclinic_dimensions))
+          [[80.  0.  0.]
+           [ 0. 80.  0.]
+           [40. 40. 57.]]
 
         Setting the attribute also works::
-
+          
+          .. doctest::
+          
           >>> ts.triclinic_dimensions = [[15, 0, 0], [5, 15, 0], [5, 5, 15]]
-          >>> ts.dimensions
-          array([ 15.        ,  15.81138802,  16.58312416,  67.58049774,
-                  72.45159912,  71.56504822], dtype=float32)
-
+          >>> print(np.round(ts.dimensions))
+          [15. 16. 17. 68. 72. 72.]
+          
         See Also
         --------
         :func:`MDAnalysis.lib.mdamath.triclinic_vectors`