diff --git a/audio_offset_finder/audio_offset_finder.py b/audio_offset_finder/audio_offset_finder.py
index c9ff31e..2ce81eb 100644
--- a/audio_offset_finder/audio_offset_finder.py
+++ b/audio_offset_finder/audio_offset_finder.py
@@ -161,7 +161,7 @@ def find_offset_between_buffers(buffer1, buffer2, fs, hop_length=128, win_length
     }
 
 
-# returns an array in which the first half represents an offset of mfcc2 within mfcc2,
+# returns an array in which the first half represents an offset of mfcc2 within mfcc1,
 # and the second half (accessed by negative indices) vice-versa.
 def cross_correlation(mfcc1, mfcc2, nframes):
     """Calculate the cross-correlation curve between two numpy arrays (assumed to be MFCCs).
@@ -179,15 +179,15 @@ def cross_correlation(mfcc1, mfcc2, nframes):
     -------
     A numpy array containing the cross-correlation of the two arrays for each possible offset between them.
     The zeroth element contains the cross-correlation with no offset.
-    The first half of the array (up to len(c)/2) contains offsets of mfcc2 within mfcc1.
-    The second half of the array contains offsets of mfcc1 within mfcc2.
-    This is done so that accessing the array with an index in the range -(len(c)/2) to (len(c)/2) will return
+    The first part of the array (with negative indices) contains offsets of mfcc1 within mfcc2.
+    The second half of the array (with positive indices) contains offsets of mfcc2 within mfcc1.
+    This is done so that accessing the array with an index in the range o_min to o_max will return
     an appropriate cross-correlation coefficient for that offset.
     """
     n1, mdim1 = mfcc1.shape
     n2, mdim2 = mfcc2.shape
-    o_min = nframes - min(n1, n2)
-    o_max = min(n1, n2) - nframes + 1
+    o_min = nframes - n2
+    o_max = n1 - nframes + 1
     n = o_max - o_min
     c = np.zeros(n)
     for k in range(o_min, 0):
diff --git a/audio_offset_finder/cli.py b/audio_offset_finder/cli.py
index d76f203..1c32dae 100644
--- a/audio_offset_finder/cli.py
+++ b/audio_offset_finder/cli.py
@@ -73,13 +73,12 @@ def main(argv):
         plot_results(args, results)
 
 
-# Re-order the cross-correlation array so that the zero offset is in the middle
-def reorder_correlations(cc):
+# Re-order the cross-correlation array so that the index of the earliest frame offset is at one end of the range
+def reorder_correlations(cc, earliest_frame_offset):
     from numpy import concatenate
 
     num_elements = len(cc)
-    centre_index = int(num_elements / 2)
-    return concatenate((cc[centre_index:], cc[:centre_index]))
+    return concatenate((cc[earliest_frame_offset:], cc[:earliest_frame_offset]))
 
 
 def plot_results(args, results):
@@ -88,7 +87,7 @@ def plot_results(args, results):
 
     cc = results["correlation"]
     cc_length = len(cc)
-    plot_data = reorder_correlations(cc)
+    plot_data = reorder_correlations(cc, results["earliest_frame_offset"])
 
     pyplot.figure(figsize=(15, 5))
     xaxis_range = range(results["earliest_frame_offset"], results["latest_frame_offset"])
diff --git a/requirements.txt b/requirements.txt
index b8c3944..dcfa3e3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
 librosa==0.10.2
 matplotlib==3.7.3
-numpy==1.22.0
+numpy==1.22.3
 pytest==6.2.5
 scipy==1.10.0
diff --git a/setup.cfg b/setup.cfg
index 7e0451f..ddcadf1 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -17,7 +17,7 @@ packages = find:
 install_requires =
   librosa >= 0.10.2
   matplotlib >= 3.7.3
-  numpy >= 1.22.0
+  numpy >= 1.22.3,<2
   scipy >= 1.10.0
 
 [options.extras_require]
diff --git a/tests/tool_test.py b/tests/tool_test.py
index 3b8d75b..e979486 100644
--- a/tests/tool_test.py
+++ b/tests/tool_test.py
@@ -26,10 +26,10 @@
 
 def test_reorder_correlations():
     input_array1 = np.array([0, 1, 2, 3])
-    np.testing.assert_array_equal(reorder_correlations(input_array1), np.array([2, 3, 0, 1]))
+    np.testing.assert_array_equal(reorder_correlations(input_array1, 2), np.array([2, 3, 0, 1]))
 
     input_array2 = np.array([0, 1, 2, 3, 4])
-    np.testing.assert_array_equal(reorder_correlations(input_array2), np.array([2, 3, 4, 0, 1]))
+    np.testing.assert_array_equal(reorder_correlations(input_array2, 2), np.array([2, 3, 4, 0, 1]))
 
 
 def test_tool():