Don't set encoding attributes on bounds variables.

doc/whats-new.rst

@@ -33,6 +33,10 @@ Enhancements
 Bug fixes
 ~~~~~~~~~
 
+- Don't set attributes on bounds variables when writing to netCDF.
+  :py:meth:`xr.open_mfdataset` sets variable encodings to that of variables
+  in first file.(:issue:`2436`, :issue:`2921`)
+  By `Deepak Cherian <https://github.com/dcherian>`_.
 - indexing with an empty list creates an object with zero-length axis (:issue:`2882`)
   By `Mayeul d'Avezac <https://github.com/mdavezac>`_.
 - Return correct count for scalar datetime64 arrays (:issue:`2770`)

xarray/backends/api.py

@@ -724,6 +724,9 @@ def open_mfdataset(paths, chunks=None, concat_dim=_CONCAT_DIM_DEFAULT,
 
     combined._file_obj = _MultiFileCloser(file_objs)
     combined.attrs = datasets[0].attrs
+    for v in combined.variables:
+        if v in datasets[0]:
+            combined[v].encoding = datasets[0][v].encoding
     return combined
 
 

xarray/conventions.py

@@ -491,8 +491,6 @@ def cf_decoder(variables, attributes,
     """
     Decode a set of CF encoded variables and attributes.
 
-    See Also, decode_cf_variable
-
     Parameters
     ----------
     variables : dict
@@ -514,6 +512,10 @@ def cf_decoder(variables, attributes,
         A dictionary mapping from variable name to xarray.Variable objects.
     decoded_attributes : dict
         A dictionary mapping from attribute name to values.
+
+    See also
+    --------
+    decode_cf_variable
     """
     variables, attributes, _ = decode_cf_variables(
         variables, attributes, concat_characters, mask_and_scale, decode_times)
@@ -594,14 +596,12 @@ def encode_dataset_coordinates(dataset):
 
 def cf_encoder(variables, attributes):
     """
-    A function which takes a dicts of variables and attributes
-    and encodes them to conform to CF conventions as much
-    as possible.  This includes masking, scaling, character
-    array handling, and CF-time encoding.
-
-    Decode a set of CF encoded variables and attributes.
+    Encode a set of CF encoded variables and attributes.
+    Takes a dicts of variables and attributes and encodes them
+    to conform to CF conventions as much as possible.
+    This includes masking, scaling, character array handling,
+    and CF-time encoding.
 
-    See Also, decode_cf_variable
 
     Parameters
     ----------
@@ -617,8 +617,23 @@ def cf_encoder(variables, attributes):
     encoded_attributes : dict
         A dictionary mapping from attribute name to value
 
-    See also: encode_cf_variable
+    See also
+    --------
+    decode_cf_variable, encode_cf_variable
     """
     new_vars = OrderedDict((k, encode_cf_variable(v, name=k))
                            for k, v in variables.items())
+
+    # Remove attrs from bounds variables (issue #2921)
+    for var in new_vars.values():
+        bounds = var.attrs['bounds'] if 'bounds' in var.attrs else None
+        if bounds and bounds in new_vars:
+            # see http://cfconventions.org/cf-conventions/cf-conventions.html#cell-boundaries # noqa
+            for attr in ['units', 'standard_name', 'axis', 'positive',
+                         'calendar', 'long_name', 'leap_month', 'leap_year',
+                         'month_lengths']:
+                if attr in new_vars[bounds].attrs and attr in var.attrs:
+                    if new_vars[bounds].attrs[attr] == var.attrs[attr]:
+                        new_vars[bounds].attrs.pop(attr)
+
     return new_vars, attributes

xarray/tests/test_backends.py

@@ -2474,6 +2474,26 @@ def test_attrs_mfdataset(self):
                                       'no attribute'):
                         actual.test2
 
+    def test_encoding_mfdataset(self):
+        original = Dataset({'foo': ('t', np.random.randn(10)),
+                            't': ('t', pd.date_range(start='2010-01-01',
+                                                     periods=10,
+                                                     freq='1D'))})
+        original.t.encoding['units'] = 'days since 2010-01-01'
+
+        with create_tmp_file() as tmp1:
+            with create_tmp_file() as tmp2:
+                ds1 = original.isel(t=slice(5))
+                ds2 = original.isel(t=slice(5, 10))
+                ds1.t.encoding['units'] = 'days since 2010-01-01'
+                ds2.t.encoding['units'] = 'days since 2000-01-01'
+                ds1.to_netcdf(tmp1)
+                ds2.to_netcdf(tmp2)
+                with open_mfdataset([tmp1, tmp2]) as actual:
+                    assert actual.t.encoding['units'] == original.t.encoding['units']  # noqa
+                    assert actual.t.encoding['units'] == ds1.t.encoding['units']  # noqa
+                    assert actual.t.encoding['units'] != ds2.t.encoding['units']  # noqa
+
     def test_preprocess_mfdataset(self):
         original = Dataset({'foo': ('x', np.random.randn(10))})
         with create_tmp_file() as tmp:

xarray/tests/test_coding_times.py

@@ -5,11 +5,12 @@
 import pandas as pd
 import pytest
 
-from xarray import DataArray, Variable, coding, decode_cf
+from xarray import DataArray, Dataset, Variable, coding, decode_cf
+from xarray.backends.api import open_dataset, open_mfdataset
 from xarray.coding.times import (
     _import_cftime, cftime_to_nptime, decode_cf_datetime, encode_cf_datetime)
 from xarray.coding.variables import SerializationWarning
-from xarray.conventions import _update_bounds_attributes
+from xarray.conventions import _update_bounds_attributes, cf_encoder
 from xarray.core.common import contains_cftime_datetimes
 from xarray.testing import assert_equal
 
@@ -671,6 +672,41 @@ def test_decode_cf_time_bounds():
     _update_bounds_attributes(ds.variables)
 
 
+def test_encode_time_bounds():
+    # create time and time_bounds DataArrays for Jan-1850 and Feb-1850
+    time_bounds_vals = np.array([[0.0, 31.0], [31.0, 59.0]],
+                                dtype=np.int64)
+    time_vals = time_bounds_vals.mean(axis=1)
+
+    time_var = DataArray(time_vals, dims='time',
+                         coords={'time': time_vals})
+    time_bounds_var = DataArray(time_bounds_vals, dims=('time', 'd2'),
+                                coords={'time': time_vals})
+
+    # create Dataset of time and time_bounds
+    ds = Dataset(coords={'time': time_var},
+                 data_vars={'time_bounds': time_bounds_var})
+    ds.time.attrs = {'bounds': 'time_bounds', 'calendar': 'noleap',
+                     'units': 'days since 1850-01-01'}
+
+    # if time_bounds attrs are same as time attrs, pop them.
+    ds.time_bounds.attrs = {'calendar': 'noleap',
+                            'units': 'days since 1850-01-01'}
+    encoded, _ = cf_encoder({k: ds[k] for k in ds.variables},
+                            ds.attrs)
+    assert 'calendar' not in encoded['time_bounds'].attrs
+    assert 'units' not in encoded['time_bounds'].attrs
+
+    # for CF-noncompliant case of time_bounds attrs being different from
+    # time attrs; preserve them for faithful roundtrip
+    ds.time_bounds.attrs = {'calendar': 'noleap',
+                            'units': 'days since 1849-01-01'}
+    encoded, _ = cf_encoder({k: ds[k] for k in ds.variables},
+                            ds.attrs)
+    assert 'calendar' not in encoded['time_bounds'].attrs
+    assert encoded['time_bounds'].attrs['units'] == ds.time_bounds.attrs['units']  # noqa
+
+
 @pytest.fixture(params=_ALL_CALENDARS)
 def calendar(request):
     return request.param