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This would be very useful for formats that don't need the full sample rate to save disk space and reduce risk of sample drops due to slow writes.
Not sure if this could be sorted simply in teh capture app with simple 2:1 decimation or if it requires extra filtering to avoid aliasing
The text was updated successfully, but these errors were encountered:
Here is a quick Python script you can use to see if simple decimation is viable:
#!/usr/bin/env python3 import sys import numpy as np BUF_SIZE = 1024*1024*10 while True: in_buf = sys.stdin.buffer.read(BUF_SIZE) if len(in_buf) == 0: break in_array = np.copy(np.frombuffer(in_buf, dtype=np.int16)) out_array = in_array[::2] sys.stdout.buffer.write(out_array.tobytes())
It uses 16-bit raw input and output, and drops every other pair of bytes.
Simple test to show functionality:
$ echo 'This is a test 1234567890' | python3 ./decimation_test.py Th ia st23670
Pipeline to decimate an LDS file:
$ ld-lds-converter -u -i test.lds | python3 decimation_test.py | ld-lds-converter -p -o test_decimated.lds $ ls -l total 29312 -rwxr-xr-x@ 1 warren staff 317 Sep 9 11:42 decimation_test.py -rw-r--r-- 1 warren staff 10000000 Sep 9 11:58 test.lds -rw-r--r-- 1 warren staff 5000000 Sep 9 11:58 test_decimated.lds
(10 MB decimated to 5 MB)
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This would be very useful for formats that don't need the full sample rate to save disk space and reduce risk of sample drops due to slow writes.
Not sure if this could be sorted simply in teh capture app with simple 2:1 decimation or if it requires extra filtering to avoid aliasing
The text was updated successfully, but these errors were encountered: