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Differences on datetime values appears after writing reindexed variable on netCDF file

See original GitHub issue

In my Dataset i’ve got a time serie coordinate who begins like this

<xarray.DataArray 'time' (time: 10)>
array(['2014-02-15T00:00:00.000000000+0100',
       '2014-02-15T18:10:00.000000000+0100',
       '2014-02-16T18:10:00.000000000+0100',
       '2014-02-17T18:10:00.000000000+0100',
       '2014-02-18T18:10:00.000000000+0100',
       '2014-02-19T18:10:00.000000000+0100',
       '2014-02-20T18:10:00.000000000+0100',
       '2014-02-21T18:10:00.000000000+0100',
       '2014-02-22T00:00:00.000000000+0100',
       '2014-02-23T00:00:00.000000000+0100'], dtype='datetime64[ns]')
Coordinates:
  * time     (time) datetime64[ns] 2014-02-14T23:00:00 2014-02-15T17:10:00 ...

And all is ok when I write and re-open the netdcdf file

Then i try to add to this dataset a reindexed variable like this

da["MeanRainfallHeigh"] = rain.reindex(time =da.time).fillna(0)

Everything is still good for the writing, but when I reopen the netcdf file, the time values are modified for the minutes part.

<xarray.DataArray 'time' (time: 10)>
array(['2014-02-15T00:00:00.000000000+0100',
       '2014-02-15T18:00:00.000000000+0100',
       '2014-02-16T18:00:00.000000000+0100',
       '2014-02-17T18:00:00.000000000+0100',
       '2014-02-18T18:00:00.000000000+0100',
       '2014-02-19T18:00:00.000000000+0100',
       '2014-02-20T18:00:00.000000000+0100',
       '2014-02-21T18:00:00.000000000+0100',
       '2014-02-22T00:00:00.000000000+0100',
       '2014-02-23T00:00:00.000000000+0100'], dtype='datetime64[ns]')
Coordinates:
  * time     (time) datetime64[ns] 2014-02-14T23:00:00 2014-02-15T17:00:00 ...

Thanks!

Issue Analytics

State:
Created 7 years ago
Comments:7 (5 by maintainers)

Top GitHub Comments

2reactions

NotSqrtcommented, Jan 23, 2018

FYI, merged.time.encoding = {} before calling to_netcdf seems to avoid the RuntimeWarning.

0reactions

NotSqrtcommented, Jan 18, 2018

There you go !

import numpy
import pandas
import tempfile
import warnings
import xarray


array1 = xarray.DataArray(
    numpy.random.rand(5),
    dims=['time'],
    coords={'time': pandas.to_datetime(['2018-01-01', '2018-01-01 00:01', '2018-01-01 00:02', '2018-01-01 00:03', '2018-01-01 00:04'])},
    name='foo'
)

array2 = xarray.DataArray(
    numpy.random.rand(5),
    dims=['time'],
    coords={'time': pandas.to_datetime(['2018-01-01 00:05', '2018-01-01 00:05:10', '2018-01-01 00:05:20', '2018-01-01 00:05:30', '2018-01-01 00:05:40'])},
    name='foo'
)

with tempfile.NamedTemporaryFile() as tmp:
    # save first array
    array1.to_netcdf(tmp.name)
    # reload it
    array1_reloaded = xarray.open_dataarray(tmp.name)

    # the time encoding stores minutes as int, so seconds won't be allowed at next call of to_netcdf
    assert array1_reloaded.time.encoding['dtype'] == numpy.int64
    assert array1_reloaded.time.encoding['units'] == 'minutes since 2018-01-01 00:00:00'

    merged = xarray.merge([array1_reloaded, array2])
    array1_reloaded.close()

    with warnings.catch_warnings():
        warnings.filterwarnings('error', category=RuntimeWarning)
        merged.to_netcdf(tmp.name)

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