diff --git a/test/fft.py b/test/fft.py
deleted file mode 100755
index e38a21c..0000000
--- a/test/fft.py
+++ /dev/null
@@ -1,12 +0,0 @@
-#!/bin/env python3
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-data = []
-
-with open("test", "rb") as f:
-  data = np.fromfile(f, dtype=np.int16)
-
-plt.psd(data, Fs=1e6)
-plt.show()
diff --git a/test/sync/correlation.png b/test/sync/correlation.png
new file mode 100644
index 0000000..34d1dc1
Binary files /dev/null and b/test/sync/correlation.png differ
diff --git a/test/sync/difference-of-channels-1.png b/test/sync/difference-of-channels-1.png
new file mode 100644
index 0000000..0b27a5d
Binary files /dev/null and b/test/sync/difference-of-channels-1.png differ
diff --git a/test/sync/difference-of-channels-2.png b/test/sync/difference-of-channels-2.png
new file mode 100644
index 0000000..2d4521b
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diff --git a/test/sync/sync.py b/test/sync/sync.py
new file mode 100644
index 0000000..e6f35d5
--- /dev/null
+++ b/test/sync/sync.py
@@ -0,0 +1,32 @@
+# this script helps to verify if the 2 channels of
+# the picoscope are sampled synchronously (as stated in the datasheet)
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+# the input is the same square wave on both channels
+# stored as an array of pairs of float32-s
+data = np.fromfile("sync_test.bin", dtype=np.float32)
+
+# if the i and q channels are perfectly indetical and in sync
+# their difference should be const 0
+diff = data[0::2] - data[1::2]
+plt.plot(diff[:10000], label="I - Q")
+plt.title("Difference of channels")
+plt.legend()
+plt.show()
+# this is not exactly the case, channel b seems to be
+# a higher value at the changes in the signal
+# maybe the two channels are sampled synchronously
+# but with a small delay (less than a sample length)
+
+# if the signals are sampled with 
+plt.figure()
+corr = np.correlate(data[0::2][:10000], data[1::2][:10000], mode="full")
+print(f"Index of maximum (starting from 0, to 10000):", np.argmax(corr))
+# 9999 -> index of last element in the array -> complete overlap without offset
+plt.plot(corr)
+plt.title("Correlation")
+plt.show()
+# the maximum of the correlation is when the two signals perfectly overlap without
+# and offset, this means that they are sampled at the same time
\ No newline at end of file
diff --git a/test/view.py b/test/view.py
deleted file mode 100755
index 4726c1b..0000000
--- a/test/view.py
+++ /dev/null
@@ -1,12 +0,0 @@
-#!/bin/env python3
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-data = []
-
-with open("test", "rb") as f:
-  data = np.fromfile(f, dtype=np.int16)
-
-plt.plot(data[:10000])
-plt.show()
\ No newline at end of file