issue_comments: 259792002

I wanted to be sure that IO works well with the scipy engine, but I get this error below. Does that look familiar to you?

``` python import xarray as xr ds = xr.open_dataset('/home/mowglie/Downloads/rasm.nc') ds.Tair.encoding['dtype'] = 'float32' ds.to_netcdf('/home/mowglie/rasm.nc', format='NETCDF3_CLASSIC', engine='scipy')

---

ValueError Traceback (most recent call last) /home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/backends/api.py in to_netcdf(dataset, path, mode, format, group, engine, writer, encoding) 353 try: --> 354 dataset.dump_to_store(store, sync=sync, encoding=encoding) 355 if isinstance(path, BytesIO):

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/core/dataset.py in dump_to_store(self, store, encoder, sync, encoding) 729 if sync: --> 730 store.sync() 731

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/backends/scipy_.py in sync(self) 147 super(ScipyDataStore, self).sync() --> 148 self.ds.flush() 149

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in flush(self) 388 if hasattr(self, 'mode') and self.mode in 'wa': --> 389 self._write() 390 sync = flush

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write(self) 400 self._write_gatt_array() --> 401 self._write_var_array() 402

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write_var_array(self) 448 for name in variables: --> 449 self._write_var_metadata(name) 450 # Now that we have the metadata, we know the vsize of

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write_var_metadata(self, name) 466 for dimname in var.dimensions: --> 467 dimid = self._dims.index(dimname) 468 self._pack_int(dimid)

ValueError: '2' is not in list

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last) <ipython-input-22-4077b7ef5b8c> in <module>() 2 ds = xr.open_dataset('/home/mowglie/Downloads/rasm.nc') 3 ds.Tair.encoding['dtype'] = 'float32' ----> 4 ds.to_netcdf('/home/mowglie/rasm.nc', format='NETCDF3_CLASSIC', engine='scipy')

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/core/dataset.py in to_netcdf(self, path, mode, format, group, engine, encoding) 780 from ..backends.api import to_netcdf 781 return to_netcdf(self, path, mode, format=format, group=group, --> 782 engine=engine, encoding=encoding) 783 784 dump = utils.function_alias(to_netcdf, 'dump')

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/backends/api.py in to_netcdf(dataset, path, mode, format, group, engine, writer, encoding) 357 finally: 358 if sync: --> 359 store.close() 360 361 if not sync:

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/xarray/backends/scipy_.py in close(self) 149 150 def close(self): --> 151 self.ds.close() 152 153 def exit(self, type, value, tb):

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in close(self) 277 if not self.fp.closed: 278 try: --> 279 self.flush() 280 finally: 281 self.variables = {}

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in flush(self) 387 """ 388 if hasattr(self, 'mode') and self.mode in 'wa': --> 389 self._write() 390 sync = flush 391

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write(self) 399 self._write_dim_array() 400 self._write_gatt_array() --> 401 self._write_var_array() 402 403 def _write_numrecs(self):

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write_var_array(self) 447 # Set the metadata for all variables. 448 for name in variables: --> 449 self._write_var_metadata(name) 450 # Now that we have the metadata, we know the vsize of 451 # each record variable, so we can calculate recsize.

/home/mowglie/.bin/conda/envs/climate/lib/python3.5/site-packages/scipy/io/netcdf.py in _write_var_metadata(self, name) 465 self._pack_int(len(var.dimensions)) 466 for dimname in var.dimensions: --> 467 dimid = self._dims.index(dimname) 468 self._pack_int(dimid) 469

ValueError: '2' is not in list ```