html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/1863#issuecomment-362462705,https://api.github.com/repos/pydata/xarray/issues/1863,362462705,MDEyOklzc3VlQ29tbWVudDM2MjQ2MjcwNQ==,1217238,2018-02-02T02:01:43Z,2018-02-02T02:01:43Z,MEMBER,"Nice, thank you @j08lue for tracking this down and adding tests!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,292231408
https://github.com/pydata/xarray/pull/1863#issuecomment-361091073,https://api.github.com/repos/pydata/xarray/issues/1863,361091073,MDEyOklzc3VlQ29tbWVudDM2MTA5MTA3Mw==,3404817,2018-01-28T19:59:23Z,2018-01-28T19:59:23Z,CONTRIBUTOR,"> Store _NS_PER_TIME_DELTA values as int, then numpy will do the casting.

Haha, OK, this is actually what you implemented in https://github.com/pydata/xarray/commit/50b0a69a7aa0fb7ac3afb28e7bd971cf08055f99:

https://github.com/pydata/xarray/blob/50b0a69a7aa0fb7ac3afb28e7bd971cf08055f99/xarray/coding/times.py#L32-L37

So that is why it works now.

Case closed, I guess.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,292231408
https://github.com/pydata/xarray/pull/1863#issuecomment-361089977,https://api.github.com/repos/pydata/xarray/issues/1863,361089977,MDEyOklzc3VlQ29tbWVudDM2MTA4OTk3Nw==,3404817,2018-01-28T19:45:49Z,2018-01-28T19:48:09Z,CONTRIBUTOR,"I believe the issue originates in these lines:

https://github.com/pydata/xarray/blob/ac854f081d4b57d292755d3aff1476f8e2e2da11/xarray/conventions.py#L174-L175

where we multiply the `num_dates` with some `float` value and then cast to `int64`. 

If `num_dates` is `float32`, numpy keeps `float32` when multiplying with e.g. 1e9 and that somehow introduces an error. Here is a stripped version of the above:

```python
flat_num_dates = np.arange(100).astype('float32')
n = 1e9
roundtripped = (flat_num_dates * n).astype(np.int64) / n
assert np.all(flat_num_dates == roundtripped)
```

By the way, the factor has to be large, like `1e9`. E.g. `1e6` (`'ms since ...'`) won't give the error.

The weird thing is that the corresponding code in the current `master` is identical:

https://github.com/pydata/xarray/blob/50b0a69a7aa0fb7ac3afb28e7bd971cf08055f99/xarray/coding/times.py#L151-L152

I will look into why the result is still different from `v0.10.0`.

Also, if this really is the origin of the error, there are two easy ways to avoid this:

1. Cast `flat_num_dates` to `float64`: `(flat_num_dates.astype(np.float64) * n).astype(np.int64)`
2. Store `_NS_PER_TIME_DELTA` values as `int`, then `numpy` will do the casting.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,292231408
https://github.com/pydata/xarray/pull/1863#issuecomment-361089805,https://api.github.com/repos/pydata/xarray/issues/1863,361089805,MDEyOklzc3VlQ29tbWVudDM2MTA4OTgwNQ==,3404817,2018-01-28T19:43:21Z,2018-01-28T19:43:21Z,CONTRIBUTOR,"For comparison, I added the same test to the `0.10.0` version in https://github.com/j08lue/xarray/tree/0p10-f4-time-decode, where it fails:

```
pytest -v xarray\tests\test_conventions.py

...

>               self.assertArrayEqual(expected, actual_cmp)
E               AssertionError:
E               Arrays are not equal
E
E               (mismatch 90.0%)
E                x: array([datetime.datetime(2000, 1, 1, 0, 0),
E                      datetime.datetime(2000, 1, 2, 0, 0),
E                      datetime.datetime(2000, 1, 3, 0, 0),...
E                y: array(['2000-01-01T00:00:00.000000', '2000-01-02T00:00:00.003211',
E                      '2000-01-03T00:00:00.006422', '2000-01-04T00:00:00.001245',
E                      '2000-01-05T00:00:00.012845', '2000-01-06T00:00:00.024444',...
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,292231408