[Numpy-discussion] reading 10 bit raw data into an array
Wed Aug 1 01:55:10 CDT 2007
I guess I will still have to pad my data to full bytes before reading it, correct?
Travis Oliphant <firstname.lastname@example.org> schrieb: Danny Chan wrote:
> Hi all!
> I'm trying to read a data file that contains a raw image file. Every
> pixel is assigned a value from 0 to 1023, and all pixels are stored from
> top left to bottom right pixel in binary format in this file. I know the
> width and the height of the image, so all that would be required is to
> read 10 bits at a time and store it these as an integer. I played around
> with the fromstring and fromfile function, and I read the documentation
> for dtype objects, but I'm still confused. It seems simple enough to
> read data in a format with a standard bitwidth, but how can I read data
> in a non-standard format. Can anyone help?
This kind of bit-manipulation must be done using bit operations on
standard size data types even in C. The file reading and writing
libraries use bytes as their common denominator.
I would read in the entire image into a numpy array of unsigned bytes
and then use slicing, masking, and bit-shifting to take 5 bytes at a
time and convert them to 4 values of a 16-bit unsigned image.
Basically, you would do something like
# read in entire image into 1-d unsigned byte array
# create 16-bit array of the correct 2-D size
# use flat indexing to store into the new array
# new.flat[::4] = old[::5] + bitwise_or(old[1::5], MASK1b) << SHIFT1b
# new.flat[1::4] = bitwise_or(old[1::5], MASK2a) << SHIFT2a
+ bitwise_or(old[2::5], MASK2b) << SHIFT2b
The exact MASKS and shifts to use is left as an exercise for the reader :-)
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