Added more descriptive error message if indexing with all False bool …

Changelog

@@ -2,6 +2,9 @@
 ==========================
  * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
    underlying netcdf4 supports setting the HDF5 alignment.
+ * Slicing multi-dimensional variables with an all False boolean index array
+   now returns an empty numpy array (instead of raising an exception - issue #1197).
+   Behavior now consistent with numpy slicing.
 
  version 1.6.1 (tag v1.6.1rel)
 ==============================

src/netCDF4/_netCDF4.pyx

@@ -4953,7 +4953,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
         # put_ind for this dimension is set to -1 by _StartCountStride.
         squeeze = data.ndim * [slice(None),]
         for i,n in enumerate(put_ind.shape[:-1]):
-            if n == 1 and put_ind[...,i].ravel()[0] == -1:
+            if n == 1 and put_ind.size > 0 and put_ind[...,i].ravel()[0] == -1:
                 squeeze[i] = 0
 
         # Reshape the arrays so we can iterate over them.

src/netCDF4/utils.py

@@ -238,6 +238,10 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             unlim = False
         # convert boolean index to integer array.
         if np.iterable(ea) and ea.dtype.kind =='b':
+            # check that boolean array is not all False.
+            if not ea.any():
+                msg='Boolean index array is all False. Empty array will be returned.'
+                warnings.warn(msg)
             # check that boolean array not too long
             if not unlim and shape[i] != len(ea):
                 msg="""
@@ -457,7 +461,7 @@ def _out_array_shape(count):
     out = []
 
     for i, n in enumerate(s):
-        if n == 1:
+        if n == 1 and count.size > 0:
             c = count[..., i].ravel()[0] # All elements should be identical.
             out.append(c)
         else:

test/tst_fancyslicing.py

@@ -142,6 +142,11 @@ def test_get(self):
 
         assert_array_equal(v[0], self.data[0])
 
+        # slicing with all False booleans (PR #1197)
+        iby[:] = False
+        data = v[ibx,iby,ibz]
+        assert(data.size == 0)
+
         f.close()
 
     def test_set(self):