issue_comments

Table actions

7 rows where user = 31700619 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 1

  • clausmichele · 7 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1103536849 https://github.com/pydata/xarray/issues/4196#issuecomment-1103536849 https://api.github.com/repos/pydata/xarray/issues/4196 IC_kwDOAMm_X85BxqLR clausmichele 31700619 2022-04-20T06:57:06Z 2022-04-20T06:57:06Z CONTRIBUTOR

@max-sixty the issue you have mentioned does not include an implementation of a convolution operator, or did I miss something? Could you please reopen this issue?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Convolution operation 650547452
677666962 https://github.com/pydata/xarray/issues/4300#issuecomment-677666962 https://api.github.com/repos/pydata/xarray/issues/4300 MDEyOklzc3VlQ29tbWVudDY3NzY2Njk2Mg== clausmichele 31700619 2020-08-20T13:32:33Z 2020-08-20T13:40:07Z CONTRIBUTOR

cheers @TomNicholas , that's helpful. :) I've started messing with the idea in this Gist if you want to have a look.

It's pretty hacky at the moment, but might be helpful as a testbed. (And a way of getting my head around how apply_ufunc would work in this context)

@AndrewWilliams3142 I've tried to extend this to a 3d matrix (timeseries of 2d matrices) using Dask, it seems to work! Have a look here https://gist.github.com/clausmichele/8350e1f7f15e6828f29579914276de71

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   General curve fitting method 671609109
670840367 https://github.com/pydata/xarray/issues/4196#issuecomment-670840367 https://api.github.com/repos/pydata/xarray/issues/4196 MDEyOklzc3VlQ29tbWVudDY3MDg0MDM2Nw== clausmichele 31700619 2020-08-08T07:45:26Z 2020-08-08T07:45:26Z CONTRIBUTOR

Could you please give an example on how to perform a 2d convolution with a 3x3 kernel?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Convolution operation 650547452
669065910 https://github.com/pydata/xarray/issues/4300#issuecomment-669065910 https://api.github.com/repos/pydata/xarray/issues/4300 MDEyOklzc3VlQ29tbWVudDY2OTA2NTkxMA== clausmichele 31700619 2020-08-05T08:44:06Z 2020-08-05T08:44:06Z CONTRIBUTOR

I am also trying to get similar results of scipy curve_fit with xarray and dask. Is there a workaround I can use to fit a sinusoidal function with the current functions/methods? This is the function I use to fit a seasonal trend with scipy: t = 365 def timeseries_function_season (x,a0,a1,a2): return a0+(a1*np.cos(2*np.pi/t*x)+a2*np.sin(2*np.pi/t*x)) timeseries_model_fit,pcov= curve_fit(timeseries_function_season,x,y)

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   General curve fitting method 671609109
630124227 https://github.com/pydata/xarray/issues/4072#issuecomment-630124227 https://api.github.com/repos/pydata/xarray/issues/4072 MDEyOklzc3VlQ29tbWVudDYzMDEyNDIyNw== clausmichele 31700619 2020-05-18T11:38:10Z 2020-05-18T11:38:10Z CONTRIBUTOR

@keewis yes you are right, but still a consistent ordering would be less confusing, including maybe also the Dimensions field. Now Dimensions shows first x and then y, even though the data itself has y,x ordering.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   [BUG] xr.concat inverts coordinates order 620009114
630026640 https://github.com/pydata/xarray/issues/3969#issuecomment-630026640 https://api.github.com/repos/pydata/xarray/issues/3969 MDEyOklzc3VlQ29tbWVudDYzMDAyNjY0MA== clausmichele 31700619 2020-05-18T08:25:31Z 2020-05-18T08:25:31Z CONTRIBUTOR

I've just noticed that using xr.concat inverts the coordinates order, I opened a new issue #4072 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   [BUG] xr.merge converts automatically variables into float64 599583548
628614247 https://github.com/pydata/xarray/issues/4059#issuecomment-628614247 https://api.github.com/repos/pydata/xarray/issues/4059 MDEyOklzc3VlQ29tbWVudDYyODYxNDI0Nw== clausmichele 31700619 2020-05-14T12:53:37Z 2020-05-14T12:53:37Z CONTRIBUTOR

Sure, should I use the master branch or the fix-docs?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Typo in Reading and writing files docs 617990073

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]);