Improve argument naming after group discussion

datacube/api/core.py

@@ -473,7 +473,7 @@ def product_data(*args, **kwargs):
         return Datacube.load_data(*args, **kwargs)
 
     @staticmethod
-    def load_data(sources, geobox, measurements, fuse_func=None, dask_chunks=None, ignore_errors=False):
+    def load_data(sources, geobox, measurements, fuse_func=None, dask_chunks=None, skip_broken_datasets=False):
         """
         Load data from :meth:`group_datasets` into an :class:`xarray.Dataset`.
 
@@ -505,7 +505,7 @@ def data_func(measurement):
                 data = numpy.full(sources.shape + geobox.shape, measurement['nodata'], dtype=measurement['dtype'])
                 for index, datasets in numpy.ndenumerate(sources.values):
                     _fuse_measurement(data[index], datasets, geobox, measurement, fuse_func=fuse_func,
-                                      ignore_errors=ignore_errors)
+                                      skip_broken_datasets=skip_broken_datasets)
                 return data
         else:
             def data_func(measurement):
@@ -562,15 +562,15 @@ def fuse_lazy(datasets, geobox, measurement, fuse_func=None, prepend_dims=0):
     return data.reshape(prepend_shape + geobox.shape)
 
 
-def _fuse_measurement(dest, datasets, geobox, measurement, ignore_errors=False, fuse_func=None):
+def _fuse_measurement(dest, datasets, geobox, measurement, skip_broken_datasets=False, fuse_func=None):
     reproject_and_fuse([DatasetSource(dataset, measurement['name']) for dataset in datasets],
                        dest,
                        geobox.affine,
                        geobox.crs,
                        dest.dtype.type(measurement['nodata']),
                        resampling=measurement.get('resampling_method', 'nearest'),
                        fuse_func=fuse_func,
-                       ignore_errors=ignore_errors)
+                       skip_broken_datasets=skip_broken_datasets)
 
 
 def get_bounds(datasets, crs):

datacube/api/grid_workflow.py

@@ -304,7 +304,7 @@ def list_tiles(self, cell_index=None, **query):
         return self.tile_sources(observations, query_group_by(**query))
 
     @staticmethod
-    def load(tile, measurements=None, dask_chunks=None, fuse_func=None, resampling=None, ignore_errors=False):
+    def load(tile, measurements=None, dask_chunks=None, fuse_func=None, resampling=None, skip_broken_datasets=False):
         """
         Load data for a cell/tile.
 
@@ -348,7 +348,7 @@ def load(tile, measurements=None, dask_chunks=None, fuse_func=None, resampling=N
         measurements = set_resampling_method(measurements, resampling)
 
         dataset = Datacube.load_data(tile.sources, tile.geobox, measurements.values(), dask_chunks=dask_chunks,
-                                     fuse_func=fuse_func, ignore_errors=ignore_errors)
+                                     fuse_func=fuse_func, skip_broken_datasets=skip_broken_datasets)
 
         return dataset
 

datacube/storage/storage.py

@@ -142,15 +142,15 @@ def ignore_if(ignore_errors):
 
 
 def reproject_and_fuse(sources, destination, dst_transform, dst_projection, dst_nodata,
-                       resampling='nearest', fuse_func=None, ignore_errors=False):
+                       resampling='nearest', fuse_func=None, skip_broken_datasets=False):
     """
     Reproject and fuse `sources` into a 2D numpy array `destination`.
 
     :param List[BaseRasterDataSource] sources: Data sources to open and read from
     :param numpy.ndarray destination: ndarray of appropriate size to read data into
     :type resampling: str
     :type fuse_func: callable or None
-    :param bool ignore_errors: Carry on in the face of adversity and failing reads.
+    :param bool skip_broken_datasets: Carry on in the face of adversity and failing reads.
     """
     assert len(destination.shape) == 2
 
@@ -169,14 +169,14 @@ def copyto_fuser(dest, src):
     if len(sources) == 0:
         return destination
     elif len(sources) == 1:
-        with ignore_if(ignore_errors):
+        with ignore_if(skip_broken_datasets):
             read_from_source(sources[0], destination, dst_transform, dst_nodata, dst_projection, resampling)
         return destination
     else:
         # Muitiple sources, we need to fuse them together into a single array
         buffer_ = numpy.empty(destination.shape, dtype=destination.dtype)
         for source in sources:
-            with ignore_if(ignore_errors):
+            with ignore_if(skip_broken_datasets):
                 read_from_source(source, buffer_, dst_transform, dst_nodata, dst_projection, resampling)
                 fuse_func(destination, buffer_)
 

tests/storage/test_storage.py

@@ -124,7 +124,7 @@ def test_read_from_broken_source():
 
     # Check can ignore errors
     reproject_and_fuse(sources, output_data, dst_transform=identity,
-                       dst_projection=crs, dst_nodata=no_data, ignore_errors=True)
+                       dst_projection=crs, dst_nodata=no_data, skip_broken_datasets=True)
 
     assert (output_data == [[2, 2], [2, 2]]).all()