issue_comments

Table actions

4 rows where issue = 96211612 and user = 1217238 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

  • shoyer · 4 ✖

issue 1

  • API for multi-dimensional resampling/regridding · 4 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
349016244 https://github.com/pydata/xarray/issues/486#issuecomment-349016244 https://api.github.com/repos/pydata/xarray/issues/486 MDEyOklzc3VlQ29tbWVudDM0OTAxNjI0NA== shoyer 1217238 2017-12-04T16:27:51Z 2017-12-04T16:27:51Z MEMBER

For nearest-neighbor style resampling, we already have support for 1-dimensional resampling in .reindex()/.sel(). It would feel pretty natural to add support for N-dimensional resampling, too, if those lookups can use an index of some sort (i.e., a KDTree) to do things efficiently.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   API for multi-dimensional resampling/regridding 96211612
348163073 https://github.com/pydata/xarray/issues/486#issuecomment-348163073 https://api.github.com/repos/pydata/xarray/issues/486 MDEyOklzc3VlQ29tbWVudDM0ODE2MzA3Mw== shoyer 1217238 2017-11-30T11:34:19Z 2017-11-30T11:34:19Z MEMBER

@mraspaud of pyresample expressed interest to me offline about bringing some of pyresample's resampling features into xarray -- welcome to the conversation!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   API for multi-dimensional resampling/regridding 96211612
272585787 https://github.com/pydata/xarray/issues/486#issuecomment-272585787 https://api.github.com/repos/pydata/xarray/issues/486 MDEyOklzc3VlQ29tbWVudDI3MjU4NTc4Nw== shoyer 1217238 2017-01-14T00:43:35Z 2017-01-14T00:43:35Z MEMBER

Is there a style guide that I can/should follow? Something like this: https://google.github.io/styleguide/pyguide.html? Does it or something else define naming conventions?

It's pretty standard to follow Python's PEP8 with NumPy-style docstrings.

I generally like the Google style guide, too, but it leans towards being overly strict -- sometimes it's OK to be more relaxed (e.g., it's rules for valid import statements). Also, the public facing version has gotten out of date (I think there are plans to update it).

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   API for multi-dimensional resampling/regridding 96211612
123405417 https://github.com/pydata/xarray/issues/486#issuecomment-123405417 https://api.github.com/repos/pydata/xarray/issues/486 MDEyOklzc3VlQ29tbWVudDEyMzQwNTQxNw== shoyer 1217238 2015-07-21T17:10:34Z 2015-07-21T17:10:34Z MEMBER

Indeed, SciPy's ndimage.interpolation.zoom would probably be more appropriate (and faster) for regular grids.

Xray currently doesn't have any built-in support for handling projected data, but basic selection and regridding (from explicit arrays of 2D coordinates) seems in scope for the project.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   API for multi-dimensional resampling/regridding 96211612

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);