issue_comments
5 rows where issue = 305373563 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Inconsistent type conversion when doing numpy.sum gvies different results · 5 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
585535983 | https://github.com/pydata/xarray/issues/1989#issuecomment-585535983 | https://api.github.com/repos/pydata/xarray/issues/1989 | MDEyOklzc3VlQ29tbWVudDU4NTUzNTk4Mw== | stale[bot] 26384082 | 2020-02-13T03:46:00Z | 2020-02-13T03:46:00Z | NONE | In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity If this issue remains relevant, please comment here or remove the |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Inconsistent type conversion when doing numpy.sum gvies different results 305373563 | |
373226888 | https://github.com/pydata/xarray/issues/1989#issuecomment-373226888 | https://api.github.com/repos/pydata/xarray/issues/1989 | MDEyOklzc3VlQ29tbWVudDM3MzIyNjg4OA== | fujiisoup 6815844 | 2018-03-15T01:10:37Z | 2018-03-15T01:15:33Z | MEMBER | I notice that bottleneck does the dtype conversion. I think in your environment bottleneck is installed. ```python In [9]: np.sum(a) # equivalent to a.sum(), using bottleneck Out[9]: <xarray.DataArray ()> array(499943.21875) In [10]: np.sum(a.data) # numpy native Out[10]: 499941.53 In [15]: bn.nansum(a.data) Out[15]: 499943.21875 In [11]: a.sum(dim=('x', 'y')) # multiple dims calls native np.sum Out[11]: <xarray.DataArray ()> array(499941.53, dtype=float32) ``` It might be an upstream issue. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Inconsistent type conversion when doing numpy.sum gvies different results 305373563 | |
373221321 | https://github.com/pydata/xarray/issues/1989#issuecomment-373221321 | https://api.github.com/repos/pydata/xarray/issues/1989 | MDEyOklzc3VlQ29tbWVudDM3MzIyMTMyMQ== | djhoese 1828519 | 2018-03-15T00:37:26Z | 2018-03-15T00:38:04Z | CONTRIBUTOR | @shoyer In my examples |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Inconsistent type conversion when doing numpy.sum gvies different results 305373563 | |
373221066 | https://github.com/pydata/xarray/issues/1989#issuecomment-373221066 | https://api.github.com/repos/pydata/xarray/issues/1989 | MDEyOklzc3VlQ29tbWVudDM3MzIyMTA2Ng== | shoyer 1217238 | 2018-03-15T00:36:02Z | 2018-03-15T00:36:02Z | MEMBER |
Yes, you're using a version of xarray prior to 0.10. What value are you using for Note that due to a quirk of NumPy, |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Inconsistent type conversion when doing numpy.sum gvies different results 305373563 | |
373219624 | https://github.com/pydata/xarray/issues/1989#issuecomment-373219624 | https://api.github.com/repos/pydata/xarray/issues/1989 | MDEyOklzc3VlQ29tbWVudDM3MzIxOTYyNA== | djhoese 1828519 | 2018-03-15T00:27:35Z | 2018-03-15T00:27:35Z | CONTRIBUTOR | Example: ``` import numpy as np import xarray as xr a = xr.DataArray(np.random.random((rows, cols)).astype(np.float32), dims=('y', 'x')) In [65]: np.sum(a).data Out[65]: array(499858.0625) In [66]: np.sum(a.data) Out[66]: 499855.19 In [67]: np.sum(a.data.astype(np.float64)) Out[67]: 499855.21635645436 In [68]: np.sum(a.data.astype(np.float32)) Out[68]: 499855.19 ``` I realized after making this example that nansum gives expected results: ``` a = xr.DataArray(np.random.random((rows, cols)).astype(np.float32), dims=('y', 'x')) In [83]: np.nansum(a.data) Out[83]: 500027.81 In [84]: np.nansum(a) Out[84]: 500027.81 In [85]: np.nansum(a.data.astype(np.float64)) Out[85]: 500027.77103802469 In [86]: np.nansum(a.astype(np.float64)) Out[86]: 500027.77103802469 ``` |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Inconsistent type conversion when doing numpy.sum gvies different results 305373563 |
Advanced export
JSON shape: default, array, newline-delimited, object
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]);
user 4