[Neuroimaging] Thread-safe ArrayProxy/fileslice?

[paul mccarthy]

Howdy all,

Does anybody have experience accessing image data through the ArrayProxy
class (or functions in the fileslice module) in a multi-threaded
environment? I am visualising large 4D images which are kept on disk (via
my indexed_gzip module), and am having trouble when accessing the data from
multiple threads, as the seek/read pairs from different threads will
occasionally become intertwined with each other.


My hacky workaround is to patch the ArrayProxy.__getitem__ method, and add
a threading.Lock to each instance, as follows:


import threading

import nibabel            as nib
import nibabel.arrayproxy as ap

def ArrayProxy__getitem__(self, slc):

    if not hasattr(self, '_thread_lock'):
        return self.__real_getitem__(slc)

    self._thread_lock.acquire()

    try:
        return ap.ArrayProxy.__real_getitem__(self, slc)

    finally:
        self._thread_lock.release()

# Patch ArrayProxy.__getitem__
ap.ArrayProxy.__real_getitem__ = ap.ArrayProxy.__getitem__
ap.ArrayProxy.__getitem__      = ArrayProxy__getitem__


# Then add a lock to instances
# which need to be thread-safe
img = nib.load('MNI152_T1_2mm.nii.gz')
img.dataobj._thread_lock = threading.Lock()


This is the first thing I came up with, although I will probably end up
adding the lock to the fileobj, and patching the fileslice.fileslice
function instead. Unless there are any better ideas?

Cheers,

Paul
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