@Robert, good point, always good to try out code before speculating on a thread. ;)
Here’s working code to do the averaging, though it’s not block-wise, you’ll have to add that on top with dask/util.apply_parallel. Note also that because of the C-order of numpy arrays, it’s much more efficient to think of axis 0 as the “vertical” axis, rather than axis 2. See http://scikit-image.org/docs/dev/user_guide/numpy_images.html#notes-on-array-order for more info. import numpy as np from skimage import util vol = np.linspace(1, 125, 125, dtype=np.int32).reshape(5, 5, 5) window_shape = (1, 3, 3) windows = util.view_as_windows(vol, window_shape) print(windows.shape) # (5, 3, 3, 1, 3, 3) averaged = np.mean(windows, axis=(3, 4, 5)) HTH! Juan. On 16 Sep 2017, 12:34 PM +1000, Robert Kern <robert.k...@gmail.com>, wrote: > On Sat, Sep 16, 2017 at 7:16 AM, Chris Barker - NOAA Federal > <chris.bar...@noaa.gov> wrote: > > > > No thoughts on optimizing memory, but that indexing error probably comes > > from np.mean producing float results. An astype call shoulder that work. > > Why? It's not being used as an index. It's being assigned into a float array. > > Rather, it's the slicing inside of `trace_block()` when it's being given > arrays as inputs for `x` and `y`. numpy simply doesn't support that because > in general the result wouldn't have a uniform shape. > > -- > Robert Kern > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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