Fix helper function and undo bad merge

xarray/core/groupby.py

@@ -258,9 +258,8 @@ def __init__(self, obj, group, squeeze=False, grouper=None, bins=None,
             if not index.is_monotonic:
                 # TODO: sort instead of raising an error
                 raise ValueError('index must be monotonic for resampling')
-            s = pd.Series(np.arange(index.size), index)
             full_index, first_items = self._get_index_and_items(
-                index, s, grouper)
+                index, grouper)
             sbins = first_items.values.astype(np.int64)
             group_indices = ([slice(i, j)
                               for i, j in zip(sbins[:-1], sbins[1:])] +
@@ -307,8 +306,9 @@ def __len__(self):
     def __iter__(self):
         return zip(self._unique_coord.values, self._iter_grouped())
 
-    def _get_index_and_items(self, index, s, grouper):
+    def _get_index_and_items(self, index, grouper):
         from .resample_cftime import CFTimeGrouper
+        s = pd.Series(np.arange(index.size), index)
         if isinstance(grouper, CFTimeGrouper):
             first_items = grouper.first_items(index)
             full_index = first_items.index

xarray/tests/test_formatting.py

@@ -1,8 +1,6 @@
 # -*- coding: utf-8 -*-
 from textwrap import dedent
 
-from textwrap import dedent
-
 import numpy as np
 import pandas as pd
 
@@ -191,73 +189,6 @@ def test_attribute_repr(self):
         assert '\n' not in newlines
         assert '\t' not in tabs
 
-    def test_diff_array_repr(self):
-        da_a = xr.DataArray(
-            np.array([[1, 2, 3], [4, 5, 6]], dtype='int64'),
-            dims=('x', 'y'),
-            coords={'x': np.array(['a', 'b'], dtype='U1'),
-                    'y': np.array([1, 2, 3], dtype='int64')},
-            attrs={'units': 'm', 'description': 'desc'})
-
-        da_b = xr.DataArray(
-            np.array([1, 2], dtype='int64'),
-            dims='x',
-            coords={'x': np.array(['a', 'c'], dtype='U1'),
-                    'label': ('x', np.array([1, 2], dtype='int64'))},
-            attrs={'units': 'kg'})
-
-        expected = dedent("""\
-        Left and right DataArray objects are not identical
-        Differing dimensions:
-            (x: 2, y: 3) != (x: 2)
-        Differing values:
-        L
-            array([[1, 2, 3],
-                   [4, 5, 6]], dtype=int64)
-        R
-            array([1, 2], dtype=int64)
-        Differing coordinates:
-        L * x        (x) <U1 'a' 'b'
-        R * x        (x) <U1 'a' 'c'
-        Coordinates only on the left object:
-          * y        (y) int64 1 2 3
-        Coordinates only on the right object:
-            label    (x) int64 1 2
-        Differing attributes:
-        L   units: m
-        R   units: kg
-        Attributes only on the left object:
-            description: desc""")
-
-        actual = formatting.diff_array_repr(da_a, da_b, 'identical')
-        try:
-            assert actual == expected
-        except AssertionError:
-            # depending on platform, dtype may not be shown in numpy array repr
-            assert actual == expected.replace(", dtype=int64", "")
-
-        va = xr.Variable('x', np.array([1, 2, 3], dtype='int64'),
-                         {'title': 'test Variable'})
-        vb = xr.Variable(('x', 'y'),
-                         np.array([[1, 2, 3], [4, 5, 6]], dtype='int64'))
-
-        expected = dedent("""\
-        Left and right Variable objects are not equal
-        Differing dimensions:
-            (x: 3) != (x: 2, y: 3)
-        Differing values:
-        L
-            array([1, 2, 3], dtype=int64)
-        R
-            array([[1, 2, 3],
-                   [4, 5, 6]], dtype=int64)""")
-
-        actual = formatting.diff_array_repr(va, vb, 'equals')
-        try:
-            assert actual == expected
-        except AssertionError:
-            assert actual == expected.replace(", dtype=int64", "")
-
     def test_diff_dataset_repr(self):
         ds_a = xr.Dataset(
             data_vars={