Fix map_blocks example (#4305)

TomAugspurger · web-flow · commit e1dafe676812 · 2020-08-03T20:38:50.000-07:00
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
@@ -3358,9 +3358,12 @@ def map_blocks(
         ...     clim = gb.mean(dim="time")
         ...     return gb - clim
         >>> time = xr.cftime_range("1990-01", "1992-01", freq="M")
+        >>> month = xr.DataArray(time.month, coords={"time": time}, dims=["time"])
         >>> np.random.seed(123)
         >>> array = xr.DataArray(
-        ...     np.random.rand(len(time)), dims="time", coords=[time]
+        ...     np.random.rand(len(time)),
+        ...     dims=["time"],
+        ...     coords={"time": time, "month": month},
         ... ).chunk()
         >>> array.map_blocks(calculate_anomaly, template=array).compute()
         <xarray.DataArray (time: 24)>
@@ -3371,21 +3374,19 @@ def map_blocks(
                 0.07673453,  0.22865714,  0.19063865, -0.0590131 ])
         Coordinates:
           * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+            month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
 
         Note that one must explicitly use ``args=[]`` and ``kwargs={}`` to pass arguments
         to the function being applied in ``xr.map_blocks()``:
 
         >>> array.map_blocks(
         ...     calculate_anomaly, kwargs={"groupby_type": "time.year"}, template=array,
-        ... )
+        ... )  # doctest: +ELLIPSIS
         <xarray.DataArray (time: 24)>
-        array([ 0.15361741, -0.25671244, -0.31600032,  0.008463  ,  0.1766172 ,
-               -0.11974531,  0.43791243,  0.14197797, -0.06191987, -0.15073425,
-               -0.19967375,  0.18619794, -0.05100474, -0.42989909, -0.09153273,
-                0.24841842, -0.30708526, -0.31412523,  0.04197439,  0.0422506 ,
-                0.14482397,  0.35985481,  0.23487834,  0.12144652])
+        dask.array<calculate_anomaly-...-<this, shape=(24,), dtype=float64, chunksize=(24,), chunktype=numpy.ndarray>
         Coordinates:
-            * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+          * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+            month    (time) int64 dask.array<chunksize=(24,), meta=np.ndarray>
         """
         from .parallel import map_blocks
 
@@ -3875,9 +3876,10 @@ def argmin(
         >>> array.isel(array.argmin(...))
         array(-1)
 
-        >>> array = xr.DataArray([[[3, 2, 1], [3, 1, 2], [2, 1, 3]],
-        ...                       [[1, 3, 2], [2, -5, 1], [2, 3, 1]]],
-        ...                      dims=("x", "y", "z"))
+        >>> array = xr.DataArray(
+        ...     [[[3, 2, 1], [3, 1, 2], [2, 1, 3]], [[1, 3, 2], [2, -5, 1], [2, 3, 1]]],
+        ...     dims=("x", "y", "z"),
+        ... )
         >>> array.min(dim="x")
         <xarray.DataArray (y: 3, z: 3)>
         array([[ 1,  2,  1],
@@ -3977,9 +3979,10 @@ def argmax(
         <xarray.DataArray ()>
         array(3)
 
-        >>> array = xr.DataArray([[[3, 2, 1], [3, 1, 2], [2, 1, 3]],
-        ...                       [[1, 3, 2], [2, 5, 1], [2, 3, 1]]],
-        ...                      dims=("x", "y", "z"))
+        >>> array = xr.DataArray(
+        ...     [[[3, 2, 1], [3, 1, 2], [2, 1, 3]], [[1, 3, 2], [2, 5, 1], [2, 3, 1]]],
+        ...     dims=("x", "y", "z"),
+        ... )
         >>> array.max(dim="x")
         <xarray.DataArray (y: 3, z: 3)>
         array([[3, 3, 2],
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
@@ -5817,35 +5817,36 @@ def map_blocks(
         ...     clim = gb.mean(dim="time")
         ...     return gb - clim
         >>> time = xr.cftime_range("1990-01", "1992-01", freq="M")
+        >>> month = xr.DataArray(time.month, coords={"time": time}, dims=["time"])
         >>> np.random.seed(123)
         >>> array = xr.DataArray(
-        ...     np.random.rand(len(time)), dims="time", coords=[time]
+        ...     np.random.rand(len(time)),
+        ...     dims=["time"],
+        ...     coords={"time": time, "month": month},
         ... ).chunk()
         >>> ds = xr.Dataset({"a": array})
         >>> ds.map_blocks(calculate_anomaly, template=ds).compute()
-        <xarray.DataArray (time: 24)>
-        array([ 0.12894847,  0.11323072, -0.0855964 , -0.09334032,  0.26848862,
-                0.12382735,  0.22460641,  0.07650108, -0.07673453, -0.22865714,
-               -0.19063865,  0.0590131 , -0.12894847, -0.11323072,  0.0855964 ,
-                0.09334032, -0.26848862, -0.12382735, -0.22460641, -0.07650108,
-                0.07673453,  0.22865714,  0.19063865, -0.0590131 ])
+        <xarray.Dataset>
+        Dimensions:  (time: 24)
         Coordinates:
           * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+            month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
+        Data variables:
+            a        (time) float64 0.1289 0.1132 -0.0856 ... 0.2287 0.1906 -0.05901
 
         Note that one must explicitly use ``args=[]`` and ``kwargs={}`` to pass arguments
         to the function being applied in ``xr.map_blocks()``:
 
         >>> ds.map_blocks(
         ...     calculate_anomaly, kwargs={"groupby_type": "time.year"}, template=ds,
         ... )
-        <xarray.DataArray (time: 24)>
-        array([ 0.15361741, -0.25671244, -0.31600032,  0.008463  ,  0.1766172 ,
-               -0.11974531,  0.43791243,  0.14197797, -0.06191987, -0.15073425,
-               -0.19967375,  0.18619794, -0.05100474, -0.42989909, -0.09153273,
-                0.24841842, -0.30708526, -0.31412523,  0.04197439,  0.0422506 ,
-                0.14482397,  0.35985481,  0.23487834,  0.12144652])
+        <xarray.Dataset>
+        Dimensions:  (time: 24)
         Coordinates:
-            * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+          * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+            month    (time) int64 dask.array<chunksize=(24,), meta=np.ndarray>
+        Data variables:
+            a        (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
         """
         from .parallel import map_blocks
 
diff --git a/xarray/core/parallel.py b/xarray/core/parallel.py
@@ -235,11 +235,14 @@ def map_blocks(
     ...     clim = gb.mean(dim="time")
     ...     return gb - clim
     >>> time = xr.cftime_range("1990-01", "1992-01", freq="M")
+    >>> month = xr.DataArray(time.month, coords={"time": time}, dims=["time"])
     >>> np.random.seed(123)
     >>> array = xr.DataArray(
-    ...     np.random.rand(len(time)), dims="time", coords=[time]
+    ...     np.random.rand(len(time)),
+    ...     dims=["time"],
+    ...     coords={"time": time, "month": month},
     ... ).chunk()
-    >>> xr.map_blocks(calculate_anomaly, array, template=array).compute()
+    >>> array.map_blocks(calculate_anomaly, template=array).compute()
     <xarray.DataArray (time: 24)>
     array([ 0.12894847,  0.11323072, -0.0855964 , -0.09334032,  0.26848862,
             0.12382735,  0.22460641,  0.07650108, -0.07673453, -0.22865714,
@@ -248,25 +251,20 @@ def map_blocks(
             0.07673453,  0.22865714,  0.19063865, -0.0590131 ])
     Coordinates:
       * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+        month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
 
     Note that one must explicitly use ``args=[]`` and ``kwargs={}`` to pass arguments
     to the function being applied in ``xr.map_blocks()``:
 
-    >>> xr.map_blocks(
-    ...     calculate_anomaly,
-    ...     array,
-    ...     kwargs={"groupby_type": "time.year"},
-    ...     template=array,
-    ... )
+    >>> array.map_blocks(
+    ...     calculate_anomaly, kwargs={"groupby_type": "time.year"}, template=array,
+    ... )  # doctest: +ELLIPSIS
     <xarray.DataArray (time: 24)>
-    array([ 0.15361741, -0.25671244, -0.31600032,  0.008463  ,  0.1766172 ,
-           -0.11974531,  0.43791243,  0.14197797, -0.06191987, -0.15073425,
-           -0.19967375,  0.18619794, -0.05100474, -0.42989909, -0.09153273,
-            0.24841842, -0.30708526, -0.31412523,  0.04197439,  0.0422506 ,
-            0.14482397,  0.35985481,  0.23487834,  0.12144652])
+    dask.array<calculate_anomaly-...-<this, shape=(24,), dtype=float64, chunksize=(24,), chunktype=numpy.ndarray>
     Coordinates:
-        * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
-    """
+      * time     (time) object 1990-01-31 00:00:00 ... 1991-12-31 00:00:00
+        month    (time) int64 dask.array<chunksize=(24,), meta=np.ndarray>
+     """
 
     def _wrapper(
         func: Callable,
