issue_comments

Closing. Please feel free to reopen this if you have an API suggestion.

On Apr 21 2018 10:17 PM, Keisuke Fujii wrote:

How about reset_index? python array.stack(z=('x', 'y')).reset_index('z')

Before I left work for the weekend I had tried array.stack(z=('x', 'y')), but I had not come across reset_index yet. I will give that a try ASAP.

EBo --

How about reset_index? python array.stack(z=('x', 'y')).reset_index('z')

Thank you rabernat . I just tried:

``` array.stack(z=('x', 'y')) X

<xarray.DataArray (band: 3, z: 1647861)> dask.array<shape=(3, 1647861), dtype=float64, chunksize=(1, 1647861)> Coordinates: * band (band) int64 1 2 3 * z (z) MultiIndex - x (z) float64 1.939e+05 1.939e+05 1.939e+05 1.939e+05 1.939e+05 ... - y (z) float64 4.986e+06 4.985e+06 4.985e+06 4.984e+06 4.984e+06 ... nX = client.compute(X) ``` and got the following error:

/home/jldavid3/anaconda3/envs/pangeo/lib/python3.6/site-packages/distributed/worker.py:741: UserWarning: Large object of size 6.61 MB detected in task graph: ([[["('reshape-33c73e5277bff381fea27bc752d60c16', ... e, None), None) Consider scattering large objects ahead of time with client.scatter to reduce scheduler burden and keep data on workers

future = client.submit(func, big_data)    # bad

big_future = client.scatter(big_data)     # good
future = client.submit(func, big_future)  # good

% (format_bytes(len(b)), s)) distributed.worker - WARNING - Compute Failed Function: _dask_finalize args: ([[[array([[ 1.11333953, 0.15302669, 2.30724196, ..., -0.49583333, -0.31415252, 0.17898109]])], [array([[ 0.2049355 , 1.32097473, -1.11873895, ..., -0.10651731, 0.69806911, 1.34692913]])], [array([[ 0.59425151, -0.52178773, 0.80188672, ..., -0.83324054, -0.54774213, -0.15842612]])]]], <function Dataset._dask_postcompute at 0x7fbaded21158>, ([(False, 'band', <xarray.IndexVariable 'band' (band: 3)> array([1, 2, 3])), (False, 'z', <xarray.IndexVariable 'z' (z: 1647861)> array([(193899.75, 4985847.0), (193899.75, 4985391.0), (193899.75, 4984935.0), ..., (805851.75, 4427703.0), (805851.75, 4427247.0), (805851.75, 4426791.0)], dtype=object)), (True, <this-array>, (<function Variable._dask_finalize at 0x7fbadee159d8>, (<function finalize at 0x7fbaf986e8c8>, (), ('band', 'z'), OrderedDict(), None)))], {'z', 'band'}, {'band': 3, 'z': 1647861}, None, None, None), None) kwargs: {} Exception: KeyError(<this-array>,)

distributed.scheduler - ERROR - error from worker inproc://169.154.136.32/2193/2: <this-array>

Do you have any suggestions? I will read up more on stack later to see what else I can learn, but do you have any suggestions? I figure I probably am missing an argument or got something out of order.

Thanks again.

I think you are looking for stack:

http://xarray.pydata.org/en/stable/reshaping.html#stack-and-unstack

On Tue, Apr 17, 2018 at 1:01 PM, John (EBo) David notifications@github.com wrote:

I got a version of TomAugspurger's Spectral Clustering modified to work with GeoTIFFs http://localhost:8839/notebooks/geo-spectral- geotiff-da.ipynb, and I have been working to modify it to run using xarrays http://localhost:8839/notebooks/geo-spectral-geotiff-xa.ipynb.

I'm currently stuck on getting the xarray flattened/reduced. I keep getting errors similar to: "TypeError: 'axis' is an invalid keyword argument for this function" no matter what I have tried. I need to find some way to change the array into nbands x (1 x N). I have not been able to figure out how to do this via the examples or docs I've read.

Suggestions? Also if you have other suggestions on how to clean up either example let me know.

Also, these are using publicly available data and will be free to post some place if desired.

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