wrong time values in results from compute_mon_anomaly and compute_mon_climatology

[klindsay28]

The time values returned by compute_mon_anomaly and compute_mon_climatology are wrong.

The python code in the following file, which has a .txt suffix to enable me to attach it, exhibits the problem:
esmlab_compute_mon.py.txt

It uses the function dset from tests/conftest.py to create an example dataset, and then prints time from dset, and the datasets returned by compute_mon_anomaly and compute_mon_climatology.

print(ds.time) returns:

<xarray.DataArray 'time' (time: 24)>
array([ 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365, 396, 424,
455, 485, 516, 546, 577, 608, 638, 669, 699, 730])
Coordinates:

• time (time) int64 31 59 90 120 151 181 212 ... 577 608 638 669 699 730
  Attributes:
  units: days since 0001-01-01 00:00:00
  calendar: noleap
  bounds: time_bound

print(compute_mon_anomaly(ds).time) returns:

<xarray.DataArray 'time' (time: 24)>
array([-182.5, -182.5, -182.5, -182.5, -182.5, -182.5, -182.5, -182.5, -182.5,
-182.5, -182.5, -182.5, 182.5, 182.5, 182.5, 182.5, 182.5, 182.5,
182.5, 182.5, 182.5, 182.5, 182.5, 182.5])
Coordinates:

• time (time) float64 -182.5 -182.5 -182.5 -182.5 ... 182.5 182.5 182.5
  Attributes:
  units: days since 0001-01-01 00:00:00
  calendar: noleap
  bounds: time_bound

I expect this to report the same values as print(ds.time), and it does not.

print(compute_mon_climatology(ds).time) returns:

<xarray.DataArray 'time' (time: 12)>
array([213.5, 241.5, 272.5, 302.5, 333.5, 363.5, 394.5, 425.5, 455.5, 486.5,
516.5, 547.5])
Coordinates:

• time (time) float64 213.5 241.5 272.5 302.5 ... 455.5 486.5 516.5 547.5
  Attributes:
  long_name: time
  units: days since 0001-01-01 00:00:00
  bounds: time_bound

I expect this to report values corresponding to mid-Jan, mid-Feb, ..., and it does not.
I expect this to have the same calendar attribute that ds has, and it does not.

I am using the trunk of esmlab. conda list returns the following for xarray, numpy, and esmlab:

esmlab 2019.2.0+30.ged53a19 dev_0
numpy 1.15.4 py36h7e9f1db_0
numpy-base 1.15.4 py36hde5b4d6_0
xarray 0.11.3 pypi_0 pypi

[klindsay28]

FYI, the incorrect time values seem to have been introduced with #75. When I run the above code with 6e89f2a, right before #75, the reported time values are somewhat reasonable.
That said, even with that hash, the results have the following issues:

1. compute_mon_anomaly(ds).time is encoded, even though ds.time is not (this is what time_manager: returns ds with original time #75 was fixing)
2. compute_mon_climatology(ds).time doesn't have a calendar attribute, even though ds.time does
   @matt-long, could you take a look at this? It feels related to compute_ann_mean does not work if time is encoded #93, which was also introduced with time_manager: returns ds with original time #75.

[matt-long]

@klindsay28, I am looking at this now. I understand what's going on: we are retaining the original time coordinate in "undecoded form" (i.e. float) and doing computations on it. I think this is appropriate for operations like compute_ann_mean, but not appropriate for compute_mon_clim or compute_mon_anomaly.

I am thinking about how best to address the issue.

[klindsay28]

Are you saying that xarray operations on datasets are being applied to coordinate variables? If so, that sounds undesirable. Actually, it sounds so undesirable that I think I must be misunderstanding what you are saying. However, if I am right, is there a way to tell xarray not to do that.

[matt-long]

@klindsay28 I have a partial fix for this issue on my fork: https://github.com/matt-long/esmlab

Further work is required to clean things up and address #93. I addressed the first failure point there, but there's another error related to time_bound being decoded.

[klindsay28]

Thanks. I'm able to use your fork with just a couple of workarounds in my scripts.

[andersy005]

@klindsay28, feel free to close this in case #98 fixes this issue