Fix "Chunksize cannot exceed dimension size"

doc/whats-new.rst

@@ -49,6 +49,8 @@ Bug fixes
 
 - Fixed ``apply_ufunc`` with ``dask='parallelized'`` for scalar arguments
   (:issue:`1697`).
+- Fix "Chunksize cannot exceed dimension size" error when writing netCDF4 files
+  loaded from disk (:issue:`1225`).
   By `Stephan Hoyer <https://github.com/shoyer>`_.
 
 Testing

xarray/backends/netCDF4_.py

@@ -147,7 +147,11 @@ def _force_native_endianness(var):
 
 
 def _extract_nc4_variable_encoding(variable, raise_on_invalid=False,
-                                   lsd_okay=True, backend='netCDF4'):
+                                   lsd_okay=True, backend='netCDF4',
+                                   unlimited_dims=None):
+    if unlimited_dims is None:
+        unlimited_dims = ()
+
     encoding = variable.encoding.copy()
 
     safe_to_drop = set(['source', 'original_shape'])
@@ -156,10 +160,17 @@ def _extract_nc4_variable_encoding(variable, raise_on_invalid=False,
     if lsd_okay:
         valid_encodings.add('least_significant_digit')
 
-    if (encoding.get('chunksizes') is not None and
-            (encoding.get('original_shape', variable.shape) !=
-                variable.shape) and not raise_on_invalid):
-        del encoding['chunksizes']
+    if not raise_on_invalid and encoding.get('chunksizes') is not None:
+        # It's possible to get encoded chunksizes larger than a dimension size
+        # if the original file had an unlimited dimension. This is problematic
+        # if the new file no longer has an unlimited dimension.
+        chunksizes = encoding['chunksizes']
+        chunks_too_big = any(
+            c > d and dim not in unlimited_dims
+            for c, d, dim in zip(chunksizes, variable.shape, variable.dims))
+        changed_shape = encoding.get('original_shape') != variable.shape
+        if chunks_too_big or changed_shape:
+            del encoding['chunksizes']
 
     for k in safe_to_drop:
         if k in encoding:
@@ -346,7 +357,8 @@ def prepare_variable(self, name, variable, check_encoding=False,
                 'NC_CHAR type.' % name)
 
         encoding = _extract_nc4_variable_encoding(
-            variable, raise_on_invalid=check_encoding)
+            variable, raise_on_invalid=check_encoding,
+            unlimited_dims=unlimited_dims)
         nc4_var = self.ds.createVariable(
             varname=name,
             datatype=datatype,

xarray/tests/test_backends.py

@@ -909,6 +909,21 @@ def test_compression_encoding(self):
         with self.roundtrip(expected) as actual:
             self.assertDatasetEqual(expected, actual)
 
+    def test_encoding_chunksizes_unlimited(self):
+        # regression test for GH1225
+        ds = Dataset({'x': [1, 2, 3], 'y': ('x', [2, 3, 4])})
+        ds.variables['x'].encoding = {
+            'zlib': False,
+            'shuffle': False,
+            'complevel': 0,
+            'fletcher32': False,
+            'contiguous': False,
+            'chunksizes': (2 ** 20,),
+            'original_shape': (3,),
+        }
+        with self.roundtrip(ds) as actual:
+            self.assertDatasetEqual(ds, actual)
+
     def test_mask_and_scale(self):
         with create_tmp_file() as tmp_file:
             with nc4.Dataset(tmp_file, mode='w') as nc:
@@ -1230,6 +1245,7 @@ def test_encoding_unlimited_dims(self):
                             save_kwargs=dict(unlimited_dims=['y'])) as actual:
             self.assertEqual(actual.encoding['unlimited_dims'], set('y'))
             self.assertDatasetEqual(ds, actual)
+
         ds.encoding = {'unlimited_dims': ['y']}
         with self.roundtrip(ds) as actual:
             self.assertEqual(actual.encoding['unlimited_dims'], set('y'))