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 <matthew.brett@gmail.com>wrote:
Hi,
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
On Tue, Jul 26, 2011 at 5:11 PM, Craig Yoshioka <craigyk@me.com> wrote: 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 NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion