Similar to what Matthew said, I often find that it's cleaner to make a
seperate class with a "data" (or somesuch) property that lazily loads the
numpy array.
For example, something like:
class DataFormat(object):
def __init__(self, filename):
self.filename = filename
for key, value in self._read_header().iteritems():
setattr(self, key, value)
@property
def data(self):
try:
return self._data
except AttributeError:
self._data = self._read_data()
return self._data
Hope that helps,
-Joe
On Tue, Jul 26, 2011 at 4:15 PM, Matthew Brett <[email protected]>wrote:
> Hi,
>
> On Tue, Jul 26, 2011 at 5:11 PM, Craig Yoshioka <[email protected]> wrote:
> > I want to subclass ndarray to create a class for image and volume data,
> and when referencing a file I'd like to have it load the data only when
> accessed. That way the class can be used to quickly set and manipulate
> header values, and won't load data unless necessary. What is the best way
> to do this? Are there any hooks I can use to load the data when an array's
> values are first accessed or manipulated? I tried some trickery with
> __array_interface__ but couldn't get it to work very well. Should I just
> use a memmapped array, and give up on a purely 'lazy' approach?
>
> What kind of images are you loading? We do lazy loading in nibabel,
> for medical image type formats:
>
> http://nipy.sourceforge.net/nibabel/
>
> - but our images _have_ arrays and headers, rather than (appearing to
> be) arrays. Thus something like:
>
> import nibabel as nib
>
> img = nib.load('my_image.img')
> # data not loaded at this point
> data = img.get_data()
> # data loaded now. Maybe memmapped if the format allows
>
> If you think you might have similar needs, I'd be very happy to help
> you get going in nibabel...
>
> Best,
>
> Matthew
> _______________________________________________
> NumPy-Discussion mailing list
> [email protected]
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
_______________________________________________
NumPy-Discussion mailing list
[email protected]
http://mail.scipy.org/mailman/listinfo/numpy-discussion
