issue_comments: 305209648

Currently dask is an optional dependency for carry, which I would like to preserve if possible. I'll take a glance at the implementation shortly, but my guess is that we will indeed want to vendor the numpy version into xarray. On Wed, May 31, 2017 at 6:38 AM Peter Steinberg notifications@github.com wrote:

Hi @darothen https://github.com/darothen earthio is a recent experimental refactor of what was the elm.readers subpackage. elm - Ensemble Learning Models was developed with a Phase I NASA SBIR in 2016 and in part reflects our thinking in late 2015 when xarray was newer and we were planning the proposal. In the last ca. month we have started a Phase II of development on multi-model dask/xarray ML algorithms based on xarray, dask, scikit-learn and a Bokeh maps UI for tasks like land cover classification. I'll add you to elm and feel free to contact me at psteinberg [at] continuum [dot] io. We will do more promotion / blogs in the near term and also in about 12 months we will release a free/open collection of notebooks that form a "Machine Learning with Environmental Data" 3-day course.

Back to the subject matter of the thread.... I assigned this issue to myself. I'll wait to get started until after @shoyer https://github.com/shoyer comments on @laliberte https://github.com/laliberte 's question:

(1) replicate serial coarsen into xarray or (2) point to dask coarsen methods?

—

You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/pydata/xarray/issues/1192#issuecomment-305189172, or mute the thread https://github.com/notifications/unsubscribe-auth/ABKS1hU-F507Wp1-MMa_JXzyaNtxXYQvks5r_W1hgaJpZM4LaxU4 .