Hello,
I hope this is the right mailings list for a numpy user questions, if
not, I'm sorry.
Im reading a binary file with numpy.fromfile()
The binary file is constructed with some integers for checking the
data for corruption.
This is how the binary file is constructed:
Timestamp [ 12 bytes]
[ 1 int ] check
[ 1 single ] Time stamp (single precision).
[ 1 int ] check
Data chunk [ 4*(no_sensor+2) bytes ]
[ 1 int ] check
[ no_sensor single ] Array of sensor readings (single precision).
[ 1 int ] check
The file continues this way
[ Timestamp ]
[ Data chunk ]
[ Timestamp ]
[ Data chunk ]
..
no_sensor is file dependend
int = 4 bytes
single = 4 bytes
This is my current procedure
f = open(file,'rb')
f.read(size_of_header) # The file contains a header, where fx. the
no_sensor can be read.
dt = np.dtype([('junk0', 'i4'),
('timestamp', 'f4'),
('junk1', 'i4'),
('junk2', 'i4'),
('sensors', ('f4',no_sensor)),
('junk3', 'i4')])
data = np.fromfile(f, dtype=dt)
Now the data is read in and I can access it, but I have the 'junk' in
the array, which annoys me.
Is there a way to remove the junk data, or skip it with fromfile ?
Another issue is that when accessing one sensor, I do it this way:
data['sensors'][:,0]
for the first sensor, would it be possible to just do:
data['sensors'][0] ?
Thank you!
Sincerely
Michael Klitgaard
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