How can I Read/Write multiple sequential Binary/Text data files

[Albert Tu]

Dear there,

We have an x-ray CT system. The acquisition computer acquires x-ray
projections and outputs multiple data files in binary format (2-byte
unsigned integer) such as projection0.raw , projection1.raw ,
projection2.raw ... up to projection500.r aw. Each file is
2*1024*768-byte big.

I would like to read those files and convert to ascii files in %5.0f/n
format as projection0.dat a ... projection500.d ata so that our
visualization software can undersatnd the projection images. I was
trying to do this conversion using Python. However, I had troubles
declaring the file names using the do-loop index. Anyone had previous
experience?

Thanks,
Albert

[Christos TZOTZIOY Georgiou]

On 10 Mar 2005 09:41:05 -0800, rumours say that "Albert Tu"
<sj*******@gmai l.com> might have written:

Dear there,

We have an x-ray CT system. The acquisition computer acquires x-ray
projections and outputs multiple data files in binary format (2-byte
unsigned integer) such as projection0.raw , projection1.raw ,
projection2.ra w ... up to projection500.r aw. Each file is
2*1024*768-byte big.

I would like to read those files and convert to ascii files in %5.0f/n
format as projection0.dat a ... projection500.d ata so that our
visualizatio n software can undersatnd the projection images. I was
trying to do this conversion using Python. However, I had troubles
declaring the file names using the do-loop index. Anyone had previous
experience?

Regular expressions could help, but if you *know* that these are the filenames,
you can (untested code):

PREFIX= "projection "
SUFFIX_I= ".raw"
SUFFIX_O= ".data"

import glob, struct

for filename in glob.glob("%s*% s" % (PREFIX, SUFFIX_I)):
number= filename[len(PREFIX):-len(SUFFIX_I)]
fpi= open(filename, "rb")
fpo= open("%s%s%s" % (PREFIX, number, SUFFIX_O), "w")
while 1:
datum= fpi.read(2)
if not datum: break
fpo.write("%5d\ n" % struct.unpack(" H", datum)) # check endianness!!!
fpi.close()
fpo.close()
--
TZOTZIOY, I speak England very best.
"Be strict when sending and tolerant when receiving." (from RFC1958)
I really should keep that in mind when talking with people, actually...

[John Machin]

On Thu, 10 Mar 2005 20:06:29 +0200, Christos "TZOTZIOY" Georgiou
<tz**@sil-tec.gr> wrote:

On 10 Mar 2005 09:41:05 -0800, rumours say that "Albert Tu"
<sj*******@gma il.com> might have written:

Dear there,

We have an x-ray CT system. The acquisition computer acquires x-ray
projections and outputs multiple data files in binary format (2-byte
unsigned integer) such as projection0.raw , projection1.raw ,
projection2.r aw ... up to projection500.r aw. Each file is
2*1024*768-byte big.

I would like to read those files and convert to ascii files in %5.0f/n
format as projection0.dat a ... projection500.d ata so that our
visualizati on software can undersatnd the projection images. I was
trying to do this conversion using Python. However, I had troubles
declaring the file names using the do-loop index. Anyone had previous
experience?
Regular expressions could help, but if you *know* that these are the filenames,
you can (untested code):

PREFIX= "projection "
SUFFIX_I= ".raw"
SUFFIX_O= ".data"

import glob, struct

import array

DIFFERENT_ENDIA N = True/False

for filename in glob.glob("%s*% s" % (PREFIX, SUFFIX_I)):
number= filename[len(PREFIX):-len(SUFFIX_I)]
fpi= open(filename, "rb")
fpo= open("%s%s%s" % (PREFIX, number, SUFFIX_O), "w")
while 1:
datum= fpi.read(2)
if not datum: break
fpo.write("%5d\ n" % struct.unpack(" H", datum)) # check endianness!!!
If the OP knows that each input file is small enough (1.5Mb each as
stated), then the agony of file.read(2) can be avoided by reading the
whole file in one hit. The agony of struct.unpack() on each datum can
be avoided by using the array module. E.g. replace the whole 'while'
loop by this:

ary = array.array('H' , fpi.read())
if DIFFERENT_ENDIA N:
ary.byteswap()
for datum in ary:
fpo.write("%5d\ n" % datum)

Even if the input files were too large to fit in memory, they could
still be processed fast enough by reading a big chunk at a time.

fpi.close()
fpo.close()

[Bengt Richter]

On 10 Mar 2005 09:41:05 -0800, "Albert Tu" <sj*******@gmai l.com> wrote:

Dear there,

We have an x-ray CT system. The acquisition computer acquires x-ray
projections and outputs multiple data files in binary format (2-byte
unsigned integer) such as projection0.raw , projection1.raw ,
projection2.ra w ... up to projection500.r aw. Each file is
2*1024*768-byte big.

I would like to read those files and convert to ascii files in %5.0f/n
format as projection0.dat a ... projection500.d ata so that our
visualizatio n software can undersatnd the projection images. I was Is there no chance of fixing the visualization software instead? The format seems
easy and efficient, and it seems a shame to make a redundant bloated copy
of the same info. What next? XML tags surrounding your ascii floats?

What platform are you on? What is the visualization software's method of
accessing data? Only files as you describe? Are you visualizing interactively,
or setting up batch processing?
trying to do this conversion using Python. However, I had troubles
declaring the file names using the do-loop index. Anyone had previous
experience?

Are you the same person who posted re this format some time ago?

Regards,
Bengt Richter