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- Implement interp for interpolating between chunks of data (dask) · 10 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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674321185 | https://github.com/pydata/xarray/pull/4155#issuecomment-674321185 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY3NDMyMTE4NQ== | fujiisoup 6815844 | 2020-08-15T00:30:21Z | 2020-08-15T00:30:21Z | MEMBER | @cyhsu Yes, because it is not yet released.
(I'm not sure when the next release will be, but maybe a few months later)
If you do |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
674305570 | https://github.com/pydata/xarray/pull/4155#issuecomment-674305570 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY3NDMwNTU3MA== | fujiisoup 6815844 | 2020-08-14T23:07:03Z | 2020-08-14T23:07:03Z | MEMBER | @cyhsu Yes, in the current master. |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
672348216 | https://github.com/pydata/xarray/pull/4155#issuecomment-672348216 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY3MjM0ODIxNg== | fujiisoup 6815844 | 2020-08-11T23:16:07Z | 2020-08-11T23:16:07Z | MEMBER | Thanks @pums974 :) |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
667412134 | https://github.com/pydata/xarray/pull/4155#issuecomment-667412134 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY2NzQxMjEzNA== | fujiisoup 6815844 | 2020-07-31T22:28:07Z | 2020-07-31T22:28:07Z | MEMBER | This PR looks good for me. Maybe we can wait for a few days in case anyone has some comments on it. If no comments, I'll merge this then. |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
666720655 | https://github.com/pydata/xarray/pull/4155#issuecomment-666720655 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY2NjcyMDY1NQ== | fujiisoup 6815844 | 2020-07-30T21:38:55Z | 2020-07-30T21:38:55Z | MEMBER | OK. If you have additional time, it would be nicer if you could add more comments on tests, like what is being tested there ;) |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
663788117 | https://github.com/pydata/xarray/pull/4155#issuecomment-663788117 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY2Mzc4ODExNw== | fujiisoup 6815844 | 2020-07-25T01:08:52Z | 2020-07-25T01:08:52Z | MEMBER | Thanks @pums974 for this update and sorry for my late response. It looks good but I'll take a deeper look in the next week. |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
651589183 | https://github.com/pydata/xarray/pull/4155#issuecomment-651589183 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY1MTU4OTE4Mw== | fujiisoup 6815844 | 2020-06-30T07:01:31Z | 2020-06-30T07:01:31Z | MEMBER |
Maybe we can support sequential interpolation only at this moment.
In this case,
|
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
650428037 | https://github.com/pydata/xarray/pull/4155#issuecomment-650428037 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY1MDQyODAzNw== | fujiisoup 6815844 | 2020-06-26T22:17:22Z | 2020-06-26T22:17:22Z | MEMBER |
OK.
Even so, I would suggest restructuring the code base;
maybe we can add an In missing.py, we can call this function. |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
649836609 | https://github.com/pydata/xarray/pull/4155#issuecomment-649836609 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY0OTgzNjYwOQ== | fujiisoup 6815844 | 2020-06-25T21:53:36Z | 2020-06-25T21:53:36Z | MEMBER | Also in my local environment, it gives
The full stack trace is ``` _________ test_interpolate_1d[1-y-cubic] ____________ method = 'cubic', dim = 'y', case = 1
xarray/tests/test_interp.py:86: xarray/testing.py:132: in compat_variable return a.dims == b.dims and (a._data is b._data or equiv(a.data, b.data)) xarray/testing.py:31: in _data_allclose_or_equiv return duck_array_ops.allclose_or_equiv(arr1, arr2, rtol=rtol, atol=atol) xarray/core/duck_array_ops.py:221: in allclose_or_equiv arr1 = np.array(arr1) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/array/core.py:1314: in array x = self.compute() ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/base.py:165: in compute (result,) = compute(self, traverse=False, kwargs) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/base.py:436: in compute results = schedule(dsk, keys, kwargs) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:527: in get_sync return get_async(apply_sync, 1, dsk, keys, kwargs) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:494: in get_async fire_task() ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:466: in fire_task callback=queue.put, ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:516: in apply_sync res = func(*args, kwds) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:227: in execute_task result = pack_exception(e, dumps) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/local.py:222: in execute_task result = _execute_task(task, data) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/core.py:119: in _execute_task return func(args2) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/optimization.py:982: in call return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/core.py:149: in get result = _execute_task(task, cache) ../../../anaconda3/envs/xarray/lib/python3.7/site-packages/dask/core.py:119: in _execute_task return func(args2) xarray/core/missing.py:830: in _dask_aware_interpnd return _interpnd(var, old_x, new_x, func, kwargs) xarray/core/missing.py:793: in _interpnd x, new_x = _floatize_x(x, new_x) xarray/core/missing.py:577: in _floatize_x if _contains_datetime_like_objects(x[i]): xarray/core/common.py:1595: in _contains_datetime_like_objects return is_np_datetime_like(var.dtype) or contains_cftime_datetimes(var) xarray/core/common.py:1588: in contains_cftime_datetimes return _contains_cftime_datetimes(var.data) array = <memory at 0x7f771d6daef0>
xarray/core/common.py:1574: AttributeError ``` |
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Implement interp for interpolating between chunks of data (dask) 638909879 | |
649827797 | https://github.com/pydata/xarray/pull/4155#issuecomment-649827797 | https://api.github.com/repos/pydata/xarray/issues/4155 | MDEyOklzc3VlQ29tbWVudDY0OTgyNzc5Nw== | fujiisoup 6815844 | 2020-06-25T21:30:17Z | 2020-06-25T21:30:17Z | MEMBER | Hi @pums974 Thanks for sending the PR. I'm working to review it, but it may take more time. A few comments;
Does it work with an unsorted destination?
e.g.,
I'm feeling that the basic algorithm, such as |
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Implement interp for interpolating between chunks of data (dask) 638909879 |
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