diff --git a/src/mdevaluate/reader.py b/src/mdevaluate/reader.py
index 2f1bb72..e8f5ce0 100755
--- a/src/mdevaluate/reader.py
+++ b/src/mdevaluate/reader.py
@@ -187,35 +187,52 @@ def nojump_save_filename(reader: BaseReader):
         return full_path_fallback
 
 
-def parse_jumps(trajectory: Coordinates):
-    prev = trajectory[0].whole
+def parse_jumps(trajectory: Coordinates, whole: bool=True, fractional_inverted: bool=True):
+    if whole:
+        prev = trajectory[0].whole
+    else:
+        prev = trajectory[0]
     box = prev.box
+    if fractional_inverted:
+        s_prev = prev @ np.linalg.inv(box)
+
     SparseData = namedtuple("SparseData", ["data", "row", "col"])
     jump_data = (
         SparseData(data=array("b"), row=array("l"), col=array("l")),
         SparseData(data=array("b"), row=array("l"), col=array("l")),
         SparseData(data=array("b"), row=array("l"), col=array("l")),
     )
+
     for i, curr in enumerate(trajectory):
         if i % 500 == 0:
             logger.debug("Parse jumps Step: %d", i)
-        r3 = np.subtract(curr, prev)
-        delta_z = np.array(np.rint(np.divide(r3[:, 2], box[2][2])), dtype=np.int8)
-        r2 = np.subtract(
-            r3,
-            (np.rint(np.divide(r3[:, 2], box[2][2])))[:, np.newaxis]
-            * box[2][np.newaxis, :],
-            )
-        delta_y = np.array(np.rint(np.divide(r2[:, 1], box[1][1])), dtype=np.int8)
-        r1 = np.subtract(
-            r2,
-            (np.rint(np.divide(r2[:, 1], box[1][1])))[:, np.newaxis]
-            * box[1][np.newaxis, :],
-            )
-        delta_x = np.array(np.rint(np.divide(r1[:, 0], box[0][0])), dtype=np.int8)
-        delta = np.array([delta_x, delta_y, delta_z]).T
-        prev = curr
-        box = prev.box
+        if not fractional_inverted:
+            r3 = np.subtract(curr, prev)
+            delta_z = np.array(np.rint(np.divide(r3[:, 2], box[2][2])), dtype=np.int8)
+            r2 = np.subtract(
+                r3,
+                (np.rint(np.divide(r3[:, 2], box[2][2])))[:, np.newaxis]
+                * box[2][np.newaxis, :],
+                )
+            delta_y = np.array(np.rint(np.divide(r2[:, 1], box[1][1])), dtype=np.int8)
+            r1 = np.subtract(
+                r2,
+                (np.rint(np.divide(r2[:, 1], box[1][1])))[:, np.newaxis]
+                * box[1][np.newaxis, :],
+                )
+            delta_x = np.array(np.rint(np.divide(r1[:, 0], box[0][0])), dtype=np.int8)
+            delta = np.array([delta_x, delta_y, delta_z]).T
+            prev = curr
+            box = prev.box
+        else:
+            s_curr = curr @ np.linalg.inv(curr.box)
+
+            ds = s_curr - s_prev
+            delta = np.array(np.rint(ds), dtype=np.int8)
+
+            s_prev = s_curr
+
+
         for d in range(3):
             (col,) = np.where(delta[:, d] != 0)
             jump_data[d].col.extend(col)