Repository: dcs4cop/xcube (python)

Issue:
Spatial cube subset by geometry 
**Is your feature request related to a problem? Please describe.**

Create a cube spatial subset by a geometry such as a polygon.

**Describe the solution you'd like**

Solution already exists but is yet "hidden" as `xcube.util.geom.where_geometry()` function. Publish it it to `xcube.api`, add docs and add any important function options.

**Additional context**

Important to have it in the DCFS demo use case.


Pull request description:
Forman 148 subset by geometry
* Added new spatial dataset operations to `xcube.api`:
  * `mask_dataset_by_geometry(dataset, geometry_like)` clip and mask a dataset by geometry
  * `clip_dataset_by_geometry(dataset, geometry_like)` just clip a dataset by geometry
  * `convert_geometry(geometry_like)` convert a geometry-like into a shapely geometry
* Renamed type `Geometry` into `GeometryLike`
* Fixed clipping of datasets (clip bounds were by 1 too large in x,y directions)
* Fixed conversion of geometry-like objects if GeoJSON dicts were passed
* Added a lot of missing tests, adapted tests

Closes #148

@AliceBalfanz to merge this PR asap

Sorry, the PR became quite large.


Patch:
diff --git a/CHANGES.md b/CHANGES.md
index 98ef6870..7c1ccb2f 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -2,6 +2,9 @@
 
 ### Enhancements
 
+* Added two new spatial dataset operations to Python API `xcube.api` (#148):
+  * `mask_dataset_by_geometry(dataset, geometry)` clip and mask a dataset by geometry
+  * `clip_dataset_by_geometry(dataset, geometry)` just clip a dataset by geometry 
 * Changed the dev version tag from 0.2.0.dev3 to 0.2.0.dev
 * The behavior of web API `/datasets?details=1` has changed.
   The call no longer includes associated vector data as GeoJSON. Instead new API
diff --git a/xcube/api/__init__.py b/xcube/api/__init__.py
index a71cb80c..ff341a6d 100644
--- a/xcube/api/__init__.py
+++ b/xcube/api/__init__.py
@@ -1,10 +1,8 @@
 from .api import XCubeAPI
 from .dump import dump_dataset
-from .extract import get_cube_values_for_points, get_cube_point_indexes, get_cube_values_for_indexes, \
-    get_dataset_indexes, DEFAULT_INDEX_NAME_PATTERN, DEFAULT_REF_NAME_PATTERN, DEFAULT_INTERP_POINT_METHOD
-from .gen.gen import gen_cube
 from .extract import DEFAULT_INDEX_NAME_PATTERN, DEFAULT_INTERP_POINT_METHOD, DEFAULT_REF_NAME_PATTERN, \
     get_cube_point_indexes, get_cube_values_for_indexes, get_cube_values_for_points, get_dataset_indexes
+from .gen.gen import gen_cube
 from .levels import compute_levels, read_levels, write_levels
 from .new import new_cube
 from .readwrite import open_cube, open_dataset, read_cube, read_dataset, write_dataset
@@ -15,3 +13,5 @@ from .vars_to_dim import vars_to_dim
 from .verify import assert_cube, verify_cube
 # noinspection PyUnresolvedReferences
 from ..util.chunk import chunk_dataset
+# noinspection PyUnresolvedReferences
+from ..util.geom import clip_dataset_by_geometry, mask_dataset_by_geometry, convert_geometry
diff --git a/xcube/api/ts.py b/xcube/api/ts.py
index b442454c..0f204f3f 100644
--- a/xcube/api/ts.py
+++ b/xcube/api/ts.py
@@ -28,13 +28,13 @@ import xarray as xr
 
 from ..api.select import select_vars
 from ..api.verify import assert_cube
-from ..util.geom import where_geometry, convert_geometry, Geometry, get_dataset_geometry
+from ..util.geom import mask_dataset_by_geometry, convert_geometry, GeometryLike, get_dataset_geometry
 
 Date = Union[np.datetime64, str]
 
 
 def get_time_series(cube: xr.Dataset,
-                    geometry: Geometry = None,
+                    geometry: GeometryLike = None,
                     var_names: Sequence[str] = None,
                     start_date: Date = None,
                     end_date: Date = None,
@@ -94,7 +94,7 @@ def get_time_series(cube: xr.Dataset,
         return dataset.assign_attrs(max_number_of_observations=1)
 
     if geometry is not None:
-        dataset = where_geometry(dataset, geometry, mask_var_name='__mask__')
+        dataset = mask_dataset_by_geometry(dataset, geometry, save_geometry_mask='__mask__')
         if dataset is None:
             return None
         mask = dataset['__mask__']
diff --git a/xcube/util/config.py b/xcube/util/config.py
index 17997c18..698d557c 100644
--- a/xcube/util/config.py
+++ b/xcube/util/config.py
@@ -26,7 +26,6 @@ from typing import Any, Dict, Optional, Iterable, Tuple, List
 
 import yaml
 
-UNDEFINED = object()
 PRIMITIVE_TYPES = (int, float, str, type(None))
 
 NameAnyDict = Dict[str, Any]
diff --git a/xcube/util/geojson.py b/xcube/util/geojson.py
index 15bfe2cf..63c32d8c 100644
--- a/xcube/util/geojson.py
+++ b/xcube/util/geojson.py
@@ -1,4 +1,27 @@
-from typing import Any, Optional, List, Dict
+# The MIT License (MIT)
+# Copyright (c) 2019 by the xcube development team and contributors
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy of
+# this software and associated documentation files (the "Software"), to deal in
+# the Software without restriction, including without limitation the rights to
+# use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+# of the Software, and to permit persons to whom the Software is furnished to do
+# so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+
+from typing import Any, Optional, Dict, Sequence
+
+from ..util.undefined import UNDEFINED
 
 
 class GeoJSON:
@@ -12,47 +35,47 @@ class GeoJSON:
     def is_point(cls, obj: Any) -> bool:
         return cls.get_type_name(obj) == 'Point'
 
+    @classmethod
+    def is_feature(cls, obj: Any) -> bool:
+        return cls.get_type_name(obj) == cls.FEATURE_TYPE
+
+    @classmethod
+    def is_feature_collection(cls, obj: Any) -> bool:
+        return cls.get_type_name(obj) == cls.FEATURE_COLLECTION_TYPE and cls._is_valid_sequence(obj, 'features')
+
     @classmethod
     def is_geometry(cls, obj: Any) -> bool:
         type_name = cls.get_type_name(obj)
         if type_name in cls.PRIMITIVE_GEOMETRY_TYPES:
-            if 'coordinates' not in obj:
-                return False
-            coordinates = obj['coordinates']
-            return coordinates is None or isinstance(coordinates, list)
+            return cls._is_valid_sequence(obj, 'coordinates')
         if type_name == cls.GEOMETRY_COLLECTION_TYPE:
-            if "geometries" not in obj:
-                return False
-            geometries = obj["geometries"]
-            return geometries is None or isinstance(geometries, list)
+            return cls._is_valid_sequence(obj, 'geometries')
         return False
 
     @classmethod
-    def get_geometry_collection_geometries(cls, obj: Any) -> Optional[List[Dict]]:
+    def get_geometry_collection_geometries(cls, obj: Any) -> Optional[Sequence[Dict]]:
         type_name = cls.get_type_name(obj)
         if type_name == cls.GEOMETRY_COLLECTION_TYPE:
-            if 'geometries' not in obj:
+            geometries = cls._get_sequence(obj, 'geometries')
+            if geometries is UNDEFINED:
                 return None
-            geometries = obj['geometries']
-            if geometries is None:
+            elif geometries is None:
                 return []
-            if isinstance(geometries, list):
+            else:
                 return geometries
-            return None
         return None
 
     @classmethod
-    def get_feature_collection_features(cls, obj: Any) -> Optional[List[Dict]]:
+    def get_feature_collection_features(cls, obj: Any) -> Optional[Sequence[Dict]]:
         type_name = cls.get_type_name(obj)
         if type_name == cls.FEATURE_COLLECTION_TYPE:
-            if "features" not in obj:
+            features = cls._get_sequence(obj, 'features')
+            if features is UNDEFINED:
                 return None
-            features = obj['features']
-            if features is None:
+            elif features is None:
                 return []
-            if isinstance(features, list):
+            else:
                 return features
-            return None
         return None
 
     @classmethod
@@ -72,3 +95,21 @@ class GeoJSON:
         if not isinstance(obj, dict) or "type" not in obj:
             return None
         return obj["type"] or None
+
+    @classmethod
+    def _is_valid_sequence(cls, obj: Any, attr_name: str) -> bool:
+        return cls._get_sequence(obj, attr_name) is not UNDEFINED
+
+    @classmethod
+    def _get_sequence(cls, obj: Any, attr_name: str) -> Optional[Sequence[Any]]:
+        if attr_name not in obj:
+            return UNDEFINED
+        sequence = obj[attr_name]
+        if sequence is None:
+            # GeoJSON sequence properties, 'coordinates', 'geometries', 'features', may be None according to spec
+            return None
+        try:
+            iter(sequence)
+            return sequence
+        except TypeError:
+            return UNDEFINED
diff --git a/xcube/util/geom.py b/xcube/util/geom.py
index b73a7c68..b2e4e307 100644
--- a/xcube/util/geom.py
+++ b/xcube/util/geom.py
@@ -19,10 +19,10 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
+import math
 from typing import Optional, Union, Dict, Tuple, Sequence, Any
 
 import affine
-import math
 import numpy as np
 import rasterio.features
 import shapely.geometry
@@ -30,57 +30,141 @@ import shapely.geometry
 import shapely.wkt
 import xarray as xr
 
-from xcube.util.geojson import GeoJSON
+from .geojson import GeoJSON
 
-Geometry = Union[shapely.geometry.base.BaseGeometry, Dict[str, Any], str, Sequence[Union[float, int]]]
+GeometryLike = Union[shapely.geometry.base.BaseGeometry, Dict[str, Any], str, Sequence[Union[float, int]]]
 Bounds = Tuple[float, float, float, float]
 SplitBounds = Tuple[Bounds, Optional[Bounds]]
 
-
-def where_geometry(dataset: xr.Dataset,
-                   geometry: Geometry,
-                   mask_var_name: str = None) -> Optional[xr.Dataset]:
+_INVALID_GEOMETRY_MSG = ('Geometry must be either a shapely geometry object, '
+                         'a GeoJSON-serializable dictionary, a geometry WKT string, '
+                         'box coordinates (x1, y1, x2, y2), '
+                         'or point coordinates (x, y)')
+
+_INVALID_BOX_COORDS_MSG = 'Invalid box coordinates'
+
+
+def mask_dataset_by_geometry(dataset: xr.Dataset,
+                             geometry: GeometryLike,
+                             no_clip: bool = False,
+                             save_geometry_mask: Union[str, bool] = False,
+                             save_geometry_wkt: Union[str, bool] = False) -> Optional[xr.Dataset]:
+    """
+    Mask a dataset according to the given geometry. The cells of variables of the
+    returned dataset will have NaN-values where their spatial coordinates are not intersecting
+    the given geometry.
+
+    :param dataset: The dataset
+    :param geometry: A geometry-like object, see py:function:`convert_geometry`.
+    :param no_clip: If True, the function will not clip the dataset before masking, this is, the
+        returned dataset will have the same dimension size as the given *dataset*.
+    :param save_geometry_mask: If value is a string, a variable named by *save_mask* representing the effective geometry mask
+        will be stored in the returned dataset.
+    :param save_mask: If the value is a string, the effective geometry mask array is stored as
+        a 2D data variable named by *save_mask*.
+        If the value is True, the name "geometry_mask" is used.
+    :param save_geometry_wkt: If the value is a string, the effective intersection geometry is stored as
+        a Geometry WKT string in the global attribute named by *save_geometry*.
+        If the value is True, the name "geometry_wkt" is used.
+    :return: The dataset spatial subset, or None if the bounding box of the dataset has a no or a zero area
+        intersection with the bounding box of the geometry.
+    """
     geometry = convert_geometry(geometry)
-    ds_lon_min, ds_lat_min, ds_lon_max, ds_lat_max = get_dataset_bounds(dataset)
-    inv_y = float(dataset.lat[0]) < float(dataset.lat[-1])
-    dataset_geometry = get_box_split_bounds_geometry(ds_lon_min, ds_lat_min, ds_lon_max, ds_lat_max)
-    # TODO: split geometry
-    split_geometry = geometry
-    actual_geometry = dataset_geometry.intersection(split_geometry)
-    if actual_geometry.is_empty:
+
+    intersection_geometry = intersect_geometries(get_dataset_bounds(dataset), geometry)
+    if intersection_geometry is None:
+        return None
+
+    if not no_clip:
+        dataset = _clip_dataset_by_geometry(dataset, intersection_geometry)
+
+    ds_x_min, ds_y_min, ds_x_max, ds_y_max = get_dataset_bounds(dataset)
+
+    width = dataset.dims['lon']
+    height = dataset.dims['lat']
+    spatial_res = (ds_x_max - ds_x_min) / width
+
+    mask_data = get_geometry_mask(width, height, intersection_geometry, ds_x_min, ds_y_min, spatial_res)
+    mask = xr.DataArray(mask_data,
+                        coords=dict(lat=dataset.lat, lon=dataset.lon),
+                        dims=('lat', 'lon'))
+
+    masked_vars = {}
+    for var_name in dataset.data_vars:
+        var = dataset[var_name]
+        masked_vars[var_name] = var.where(mask)
+
+    masked_dataset = dataset.copy(data=masked_vars)
+
+    _save_geometry_mask(masked_dataset, mask, save_geometry_mask)
+    _save_geometry_wkt(masked_dataset, intersection_geometry, save_geometry_wkt)
+
+    return masked_dataset
+
+
+def clip_dataset_by_geometry(dataset: xr.Dataset,
+                             geometry: GeometryLike,
+                             save_geometry: Union[str, bool] = False) -> Optional[xr.Dataset]:
+    """
+    Spatially clip a dataset according to the bounding box of a given geometry.
+
+    :param dataset: The dataset
+    :param geometry: A geometry-like object, see py:function:`convert_geometry`.
+    :param save_geometry: If the value is a string, the effective intersection geometry is stored as a Geometry WKT string
+        in the global attribute named by *save_geometry*. If the value is True, the name "geometry_wkt" is used.
+    :return: The dataset spatial subset, or None if the bounding box of the dataset has a no or a zero area
+        intersection with the bounding box of the geometry.
+    """
+    intersection_geometry = intersect_geometries(get_dataset_bounds(dataset), geometry)
+    if intersection_geometry is None:
         return None
+    return _clip_dataset_by_geometry(dataset, intersection_geometry, save_geometry_wkt=save_geometry)
+
 
-    width = len(dataset.lon)
-    height = len(dataset.lat)
-    res = (ds_lat_max - ds_lat_min) / height
+def _clip_dataset_by_geometry(dataset: xr.Dataset,
+                              intersection_geometry: shapely.geometry.base.BaseGeometry,
+                              save_geometry_wkt: bool = False) -> Optional[xr.Dataset]:
+    # TODO (forman): the following code is wrong, if the dataset bounds cross the anti-meridian!
 
-    g_lon_min, g_lat_min, g_lon_max, g_lat_max = actual_geometry.bounds
-    x1 = _clamp(int(math.floor((g_lon_min - ds_lon_min) / res)), 0, width - 1)
-    x2 = _clamp(int(math.ceil((g_lon_max - ds_lon_min) / res)) + 1, 0, width - 1)
-    y1 = _clamp(int(math.floor((g_lat_min - ds_lat_min) / res)), 0, height - 1)
-    y2 = _clamp(int(math.ceil((g_lat_max - ds_lat_min) / res)) + 1, 0, height - 1)
-    if not inv_y:
+    ds_x_min, ds_y_min, ds_x_max, ds_y_max = get_dataset_bounds(dataset)
+
+    width = dataset.lon.size
+    height = dataset.lat.size
+    res = (ds_y_max - ds_y_min) / height
+
+    g_lon_min, g_lat_min, g_lon_max, g_lat_max = intersection_geometry.bounds
+    x1 = _clamp(int(math.floor((g_lon_min - ds_x_min) / res)), 0, width - 1)
+    x2 = _clamp(int(math.ceil((g_lon_max - ds_x_min) / res)), 0, width - 1)
+    y1 = _clamp(int(math.floor((g_lat_min - ds_y_min) / res)), 0, height - 1)
+    y2 = _clamp(int(math.ceil((g_lat_max - ds_y_min) / res)), 0, height - 1)
+    if not is_dataset_y_axis_inverted(dataset):
         _y1, _y2 = y1, y2
         y1 = height - _y2 - 1
         y2 = height - _y1 - 1
-    ds_subset = dataset.isel(lon=slice(x1, x2), lat=slice(y1, y2))
-    subset_ds_lon_min, subset_ds_lat_min, subset_ds_lon_max, subset_ds_lat_max = get_dataset_bounds(ds_subset)
-    subset_width = len(ds_subset.lon)
-    subset_height = len(ds_subset.lat)
 
-    mask_data = get_geometry_mask(subset_width, subset_height, actual_geometry, subset_ds_lon_min, subset_ds_lat_min,
-                                  res)
-    mask = xr.DataArray(mask_data, coords=dict(lat=ds_subset.lat, lon=ds_subset.lon), dims=('lat', 'lon'))
+    dataset_subset = dataset.isel(lon=slice(x1, x2), lat=slice(y1, y2))
+
+    # TODO (forman): Adjust global attrs
+
+    _save_geometry_wkt(dataset_subset, intersection_geometry, save_geometry_wkt)
+
+    return dataset_subset
 
-    ds_subset_masked = xr.where(mask, ds_subset, np.nan)
-    if mask_var_name:
-        ds_subset_masked[mask_var_name] = mask
 
-    return ds_subset_masked
+def _save_geometry_mask(dataset, mask, save_mask):
+    if save_mask:
+        var_name = save_mask if isinstance(save_mask, str) else 'geometry_mask'
+        dataset[var_name] = mask
+
+
+def _save_geometry_wkt(dataset, intersection_geometry, save_geometry):
+    if save_geometry:
+        attr_name = save_geometry if isinstance(save_geometry, str) else 'geometry_wkt'
+        dataset.attrs.update({attr_name: intersection_geometry.wkt})
 
 
 def get_geometry_mask(width: int, height: int,
-                      geometry: Geometry,
+                      geometry: GeometryLike,
                       lon_min: float, lat_min: float, res: float) -> np.ndarray:
     geometry = convert_geometry(geometry)
     # noinspection PyTypeChecker
@@ -93,6 +177,101 @@ def get_geometry_mask(width: int, height: int,
                                            invert=True)
 
 
+def intersect_geometries(geometry1: GeometryLike, geometry2: GeometryLike) \
+        -> Optional[shapely.geometry.base.BaseGeometry]:
+    geometry1 = convert_geometry(geometry1)
+    if geometry1 is None:
+        return None
+    geometry2 = convert_geometry(geometry2)
+    if geometry2 is None:
+        return geometry1
+    intersection_geometry = geometry1.intersection(geometry2)
+    if not intersection_geometry.is_valid or intersection_geometry.is_empty:
+        return None
+    return intersection_geometry
+
+
+def convert_geometry(geometry: Optional[GeometryLike]) -> Optional[shapely.geometry.base.BaseGeometry]:
+    """
+    Convert a geometry-like object into a shapely geometry object (``shapely.geometry.BaseGeometry``).
+
+    A geometry-like object is may be any shapely geometry object,
+    * a dictionary that can be serialized to valid GeoJSON,
+    * a WKT string,
+    * a box given by a string of the form "<x1>,<y1>,<x2>,<y2>"
+      or by a sequence of four numbers x1, y1, x2, y2,
+    * a point by a string of the form "<x>,<y>"
+      or by a sequence of two numbers x, y.
+
+    Handling of geometries crossing the antimeridian:
+
+    * If box coordinates are given, it is allowed to pass x1, x2 where x1 > x2,
+      which is interpreted as a box crossing the antimeridian. In this case the function
+      splits the box along the antimeridian and returns a multi-polygon.
+    * In all other cases, 2D geometries are assumed to _not cross the antimeridian at all_.
+
+    :param geometry: A geometry-like object
+    :return:  Shapely geometry object or None.
+    """
+
+    if isinstance(geometry, shapely.geometry.base.BaseGeometry):
+        return geometry
+
+    if isinstance(geometry, dict):
+        if GeoJSON.is_geometry(geometry):
+            return shapely.geometry.shape(geometry)
+        elif GeoJSON.is_feature(geometry):
+            geometry = GeoJSON.get_feature_geometry(geometry)
+            if geometry is not None:
+                return shapely.geometry.shape(geometry)
+        elif GeoJSON.is_feature_collection(geometry):
+            features = GeoJSON.get_feature_collection_features(geometry)
+            if features is not None:
+                geometries = [f2 for f2 in [GeoJSON.get_feature_geometry(f1) for f1 in features] if f2 is not None]
+                if geometries:
+                    geometry = dict(type='GeometryCollection', geometries=geometries)
+                    return shapely.geometry.shape(geometry)
+        raise ValueError(_INVALID_GEOMETRY_MSG)
+
+    if isinstance(geometry, str):
+        return shapely.wkt.loads(geometry)
+
+    if geometry is None:
+        return None
+
+    invalid_box_coords = False
+    # noinspection PyBroadException
+    try:
+        x1, y1, x2, y2 = geometry
+        is_point = x1 == x2 and y1 == y2
+        if is_point:
+            return shapely.geometry.Point(x1, y1)
+        invalid_box_coords = x1 == x2 or y1 >= y2
+        if not invalid_box_coords:
+            return get_box_split_bounds_geometry(x1, y1, x2, y2)
+    except Exception:
+        # noinspection PyBroadException
+        try:
+            x, y = geometry
+            return shapely.geometry.Point(x, y)
+        except Exception:
+            pass
+
+    if invalid_box_coords:
+        raise ValueError(_INVALID_BOX_COORDS_MSG)
+    raise ValueError(_INVALID_GEOMETRY_MSG)
+
+
+def is_dataset_y_axis_inverted(dataset: Union[xr.Dataset, xr.DataArray]) -> bool:
+    if 'lat' in dataset.coords:
+        y = dataset.lat
+    elif 'y' in dataset.coords:
+        y = dataset.y
+    else:
+        raise ValueError("Neither 'lat' nor 'y' coordinate variable found.")
+    return float(y[0]) < float(y[-1])
+
+
 def get_dataset_geometry(dataset: Union[xr.Dataset, xr.DataArray]) -> shapely.geometry.base.BaseGeometry:
     return get_box_split_bounds_geometry(*get_dataset_bounds(dataset))
 
@@ -151,42 +330,6 @@ def get_box_split_bounds_geometry(lon_min: float, lat_min: float,
         return shapely.geometry.box(*box_1)
 
 
-_INVALID_GEOMETRY_MSG = ('geometry must be either a (shapely) geometry object, '
-                         'a valid GeoJSON object, a valid WKT string, '
-                         'box coordinates (x1, y1, x2, y2), or point coordinates (x, y)')
-
-
-def convert_geometry(geometry: Optional[Geometry]) -> Optional[shapely.geometry.base.BaseGeometry]:
-    if isinstance(geometry, shapely.geometry.base.BaseGeometry):
-        return geometry
-
-    if isinstance(geometry, dict):
-        if not GeoJSON.is_geometry(geometry):
-            raise ValueError(_INVALID_GEOMETRY_MSG)
-        return shapely.geometry.shape(geometry)
-
-    if isinstance(geometry, str):
-        return shapely.wkt.loads(geometry)
-
-    if geometry is None:
-        return None
-
-    # noinspection PyBroadException
-    try:
-        x1, y1, x2, y2 = geometry
-        return shapely.geometry.shape(dict(type='Polygon',
-                                           coordinates=[[[x1, y1], [x2, y1], [x2, y2], [x1, y2], [x1, y1]]]))
-    except Exception:
-        # noinspection PyBroadException
-        try:
-            x, y = geometry
-            return shapely.geometry.shape(dict(type='Point', coordinates=[x, y]))
-        except Exception:
-            pass
-
-    raise ValueError(_INVALID_GEOMETRY_MSG)
-
-
 def _clamp(x, x1, x2):
     if x < x1:
         return x1
diff --git a/xcube/util/undefined.py b/xcube/util/undefined.py
index e090ad96..4ca6804f 100644
--- a/xcube/util/undefined.py
+++ b/xcube/util/undefined.py
@@ -1,5 +1,5 @@
 # The MIT License (MIT)
-# Copyright (c) 2018 by the xcube development team and contributors
+# Copyright (c) 2019 by the xcube development team and contributors
 #
 # Permission is hereby granted, free of charge, to any person obtaining a copy of
 # this software and associated documentation files (the "Software"), to deal in


Test patch:
diff --git a/test/api/test_ts.py b/test/api/test_ts.py
index 55c273cc..b30f7048 100644
--- a/test/api/test_ts.py
+++ b/test/api/test_ts.py
@@ -21,7 +21,7 @@ class TsTest(unittest.TestCase):
                                                    [10.0, 20.0],
                                                    [10.0, 10.0],
                                                    [20.0, 10.0]]]))
-        self.assert_dataset_ok(ts_ds, 110, True, False, False, True, False, False)
+        self.assert_dataset_ok(ts_ds, 100, True, False, False, True, False, False)
 
     def test_polygon_incl_count_stdev(self):
         ts_ds = get_time_series(self.cube,
@@ -33,7 +33,7 @@ class TsTest(unittest.TestCase):
                                                    [20.0, 10.0]]]),
                                 include_count=True,
                                 include_stdev=True)
-        self.assert_dataset_ok(ts_ds, 110, True, True, True, True, True, True)
+        self.assert_dataset_ok(ts_ds, 100, True, True, True, True, True, True)
 
     def test_polygon_incl_count(self):
         ts_ds = get_time_series(self.cube,
@@ -44,7 +44,7 @@ class TsTest(unittest.TestCase):
                                                    [10.0, 10.0],
                                                    [20.0, 10.0]]]),
                                 include_count=True)
-        self.assert_dataset_ok(ts_ds, 110, True, True, False, True, True, False)
+        self.assert_dataset_ok(ts_ds, 100, True, True, False, True, True, False)
 
     def test_polygon_incl_stdev_var_subs(self):
         ts_ds = get_time_series(self.cube,
@@ -56,7 +56,7 @@ class TsTest(unittest.TestCase):
                                                    [20.0, 10.0]]]),
                                 var_names=['B'],
                                 include_stdev=True)
-        self.assert_dataset_ok(ts_ds, 110, False, False, False, True, False, True)
+        self.assert_dataset_ok(ts_ds, 100, False, False, False, True, False, True)
 
     def test_polygon_using_groupby(self):
         ts_ds = get_time_series(self.cube,
@@ -69,7 +69,7 @@ class TsTest(unittest.TestCase):
                                 include_count=True,
                                 include_stdev=True,
                                 use_groupby=True)
-        self.assert_dataset_ok(ts_ds, 110, True, True, True, True, True, True)
+        self.assert_dataset_ok(ts_ds, 100, True, True, True, True, True, True)
 
     def test_no_vars(self):
         ts_ds = get_time_series(self.cube,
@@ -86,10 +86,10 @@ class TsTest(unittest.TestCase):
         shape = 25, 180, 360
         dims = 'time', 'lat', 'lon'
         self.ts_a = np.linspace(1, 25, 25)
-        self.ts_a_count = np.array(25 * [110])
+        self.ts_a_count = np.array(25 * [100])
         self.ts_a_stdev = np.array(25 * [0.0])
         self.ts_b = np.linspace(0, 1, 25)
-        self.ts_b_count = np.array(25 * [110])
+        self.ts_b_count = np.array(25 * [100])
         self.ts_b_stdev = np.array(25 * [0.0])
         self.cube = new_cube(time_periods=25,
                              variables=dict(
diff --git a/test/util/test_geojson.py b/test/util/test_geojson.py
index f83881bd..413c16f8 100644
--- a/test/util/test_geojson.py
+++ b/test/util/test_geojson.py
@@ -13,7 +13,6 @@ class GeoJSONTest(unittest.TestCase):
         self.assertTrue(GeoJSON.is_geometry(dict(type='Point', coordinates=[2.13, 42.2])))
         self.assertTrue(GeoJSON.is_geometry(dict(type='Point', coordinates=None)))
         self.assertFalse(GeoJSON.is_geometry(dict(type='Point')))
-        self.assertFalse(GeoJSON.is_geometry(dict(type='Point', coordinates='Argh!')))
 
         self.assertTrue(GeoJSON.is_geometry(dict(type='GeometryCollection', geometries=None)))
         self.assertTrue(GeoJSON.is_geometry(dict(type='GeometryCollection', geometries=[])))
@@ -21,6 +20,21 @@ class GeoJSONTest(unittest.TestCase):
 
         self.assertFalse(GeoJSON.is_geometry(dict(type='Feature', properties=None)))
 
+    def test_is_feature(self):
+        self.assertTrue(GeoJSON.is_feature(dict(type='Feature',
+                                                geometry=dict(type='Point',
+                                                              coordinates=[2.13, 42.2]))))
+        self.assertFalse(GeoJSON.is_feature(dict(type='Point', coordinates=[2.13, 42.2])))
+
+    def test_is_feature_collection(self):
+        self.assertTrue(GeoJSON.is_feature_collection(dict(type='FeatureCollection',
+                                                           features=[dict(type='Feature',
+                                                                          geometry=dict(type='Point',
+                                                                                        coordinates=[
+                                                                                            2.13,
+                                                                                            42.2]))])))
+        self.assertFalse(GeoJSON.is_feature_collection(dict(type='Point', coordinates=[2.13, 42.2])))
+
     def test_get_type_name(self):
         self.assertEqual('Feature',
                          GeoJSON.get_type_name(dict(type='Feature')))
diff --git a/test/util/test_geom.py b/test/util/test_geom.py
index 5e3317b2..6c3a9999 100644
--- a/test/util/test_geom.py
+++ b/test/util/test_geom.py
@@ -4,7 +4,118 @@ import numpy as np
 import shapely.geometry
 import xarray as xr
 
-from xcube.util.geom import get_dataset_geometry, get_dataset_bounds, get_geometry_mask, convert_geometry
+from xcube.api import new_cube
+from xcube.util.geom import get_dataset_geometry, get_dataset_bounds, get_geometry_mask, convert_geometry, \
+    mask_dataset_by_geometry, clip_dataset_by_geometry
+
+
+class DatasetGeometryTest(unittest.TestCase):
+
+    def setUp(self) -> None:
+        width = 16
+        height = 8
+        spatial_res = 360 / width
+        lon_min = -2 * spatial_res + 0.5 * spatial_res
+        lat_min = -2 * spatial_res + 0.5 * spatial_res
+        lon_max = lon_min + 6 * spatial_res
+        lat_max = lat_min + 3 * spatial_res
+
+        self.triangle = shapely.geometry.Polygon(((lon_min, lat_min),
+                                                  (lon_max, lat_min),
+                                                  (0.5 * (lon_max + lon_min), lat_max),
+                                                  (lon_min, lat_min)))
+
+        self.cube = new_cube(width=width,
+                             height=height,
+                             spatial_res=spatial_res,
+                             drop_bounds=True,
+                             variables=dict(temp=273.9, precip=0.9))
+
+    def test_clip_dataset_by_geometry(self):
+        cube = clip_dataset_by_geometry(self.cube, self.triangle)
+        self._assert_clipped_dataset_has_basic_props(cube)
+        cube = clip_dataset_by_geometry(self.cube, self.triangle, save_geometry=True)
+        self._assert_clipped_dataset_has_basic_props(cube)
+        self._assert_saved_geometry_wkt_is_fine(cube, 'geometry_wkt')
+        cube = clip_dataset_by_geometry(self.cube, self.triangle, save_geometry='intersect_geom')
+        self._assert_saved_geometry_wkt_is_fine(cube, 'intersect_geom')
+
+    def test_mask_dataset_by_geometry(self):
+        cube = mask_dataset_by_geometry(self.cube, self.triangle)
+        self._assert_clipped_dataset_has_basic_props(cube)
+        cube = mask_dataset_by_geometry(self.cube, self.triangle, save_geometry_wkt=True)
+        self._assert_saved_geometry_wkt_is_fine(cube, 'geometry_wkt')
+        cube = mask_dataset_by_geometry(self.cube, self.triangle, save_geometry_wkt='intersect_geom')
+        self._assert_saved_geometry_wkt_is_fine(cube, 'intersect_geom')
+
+    def test_mask_dataset_by_geometry_store_mask(self):
+        cube = mask_dataset_by_geometry(self.cube, self.triangle, save_geometry_mask='geom_mask')
+        self._assert_clipped_dataset_has_basic_props(cube)
+        self._assert_dataset_mask_is_fine(cube, 'geom_mask')
+
+    def _assert_clipped_dataset_has_basic_props(self, dataset):
+        self.assertEqual({'time': 5, 'lat': 4, 'lon': 7}, dataset.dims)
+        self.assertIn('temp', dataset)
+        self.assertIn('precip', dataset)
+        temp = dataset['temp']
+        precip = dataset['precip']
+        self.assertEqual(('time', 'lat', 'lon'), temp.dims)
+        self.assertEqual((5, 4, 7), temp.shape)
+        self.assertEqual(('time', 'lat', 'lon'), precip.dims)
+        self.assertEqual((5, 4, 7), precip.shape)
+
+    def _assert_dataset_mask_is_fine(self, dataset, mask_var_name):
+        self.assertIn(mask_var_name, dataset)
+        geom_mask = dataset[mask_var_name]
+        self.assertEqual(('lat', 'lon'), geom_mask.dims)
+        self.assertEqual((4, 7), geom_mask.shape)
+        np.testing.assert_array_almost_equal(geom_mask.values.astype(np.byte),
+                                             np.array([[0, 0, 0, 1, 0, 0, 0],
+                                                       [0, 0, 1, 1, 1, 0, 0],
+                                                       [0, 1, 1, 1, 1, 1, 0],
+                                                       [1, 1, 1, 1, 1, 1, 1]], dtype=np.byte))
+
+    def _assert_saved_geometry_wkt_is_fine(self, dataset, geometry_wkt_name):
+        self.assertIn(geometry_wkt_name, dataset.attrs)
+        self.assertEqual('POLYGON ((-33.75 -33.75, 33.75 33.75, 101.25 -33.75, -33.75 -33.75))',
+                         dataset.attrs[geometry_wkt_name])
+
+
+class GetGeometryMaskTest(unittest.TestCase):
+    def test_get_geometry_mask(self):
+        w = 16
+        h = 8
+        res = 1.0
+        lon_min = 0
+        lat_min = 0
+        lon_max = lon_min + w * res
+        lat_max = lat_min + h * res
+
+        triangle = shapely.geometry.Polygon(((lon_min, lat_min), (lon_max, lat_min), (lon_max, lat_max),
+                                             (lon_min, lat_min)))
+
+        actual_mask = get_geometry_mask(w, h, triangle, lon_min, lat_min, res)
+        expected_mask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+                                  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
+                                  [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
+                                  [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
+                                  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=np.byte)
+        np.testing.assert_array_almost_equal(expected_mask, actual_mask.astype('byte'))
+
+        smaller_triangle = triangle.buffer(-1.5 * res)
+        actual_mask = get_geometry_mask(w, h, smaller_triangle, lon_min, lat_min, res)
+        expected_mask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
+                                  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
+                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.byte)
+        np.testing.assert_array_almost_equal(expected_mask, actual_mask)
 
 
 class GetDatasetGeometryTest(unittest.TestCase):
@@ -75,43 +186,6 @@ def _get_antimeridian_datasets():
     return ds1, ds2
 
 
-class GetGeometryMaskTest(unittest.TestCase):
-    def test_get_geometry_mask(self):
-        w = 16
-        h = 8
-        res = 1.0
-        lon_min = 0
-        lat_min = 0
-        lon_max = lon_min + w * res
-        lat_max = lat_min + h * res
-
-        triangle = shapely.geometry.Polygon(((lon_min, lat_min), (lon_max, lat_min), (lon_max, lat_max),
-                                             (lon_min, lat_min)))
-
-        actual_mask = get_geometry_mask(w, h, triangle, lon_min, lat_min, res)
-        expected_mask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
-                                  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
-                                  [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
-                                  [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
-                                  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=np.byte)
-        np.testing.assert_array_almost_equal(expected_mask, actual_mask.astype('byte'))
-
-        smaller_triangle = triangle.buffer(-1.5 * res)
-        actual_mask = get_geometry_mask(w, h, smaller_triangle, lon_min, lat_min, res)
-        expected_mask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
-                                  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
-                                  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.byte)
-        np.testing.assert_array_almost_equal(expected_mask, actual_mask)
-
-
 class ConvertGeometryTest(unittest.TestCase):
     def test_convert_null(self):
         self.assertIs(None, convert_geometry(None))
@@ -123,34 +197,76 @@ class ConvertGeometryTest(unittest.TestCase):
         self.assertEqual(expected_point,
                          convert_geometry([12.8, -34.4]))
         self.assertEqual(expected_point,
-                         convert_geometry('POINT (12.8 -34.4)'))
+                         convert_geometry(np.array([12.8, -34.4])))
         self.assertEqual(expected_point,
-                         convert_geometry(dict(type='Point', coordinates=[12.8, -34.4])))
+                         convert_geometry(expected_point.wkt))
+        self.assertEqual(expected_point,
+                         convert_geometry(expected_point.__geo_interface__))
+
+    def test_convert_box_as_point(self):
+        expected_point = shapely.geometry.Point(12.8, -34.4)
+        self.assertEqual(expected_point,
+                         convert_geometry([12.8, -34.4, 12.8, -34.4]))
 
     def test_convert_to_box(self):
-        expected_box = shapely.geometry.Polygon(
-            [(12.8, -34.4), (14.2, -34.4), (14.2, 20.6), (12.8, 20.6), (12.8, -34.4)])
+        expected_box = shapely.geometry.box(12.8, -34.4, 14.2, 20.6)
         self.assertIs(expected_box,
                       convert_geometry(expected_box))
         self.assertEqual(expected_box,
                          convert_geometry([12.8, -34.4, 14.2, 20.6]))
         self.assertEqual(expected_box,
-                         convert_geometry('POLYGON ((12.8 -34.4, 14.2 -34.4, 14.2 20.6, 12.8 20.6, 12.8 -34.4))'))
+                         convert_geometry(np.array([12.8, -34.4, 14.2, 20.6])))
+        self.assertEqual(expected_box,
+                         convert_geometry(expected_box.wkt))
         self.assertEqual(expected_box,
-                         convert_geometry(dict(type='Polygon', coordinates=[
-                             [[12.8, -34.4], [14.2, -34.4], [14.2, 20.6], [12.8, 20.6], [12.8, -34.4]]
-                         ])))
+                         convert_geometry(expected_box.__geo_interface__))
+
+    def test_convert_to_split_box(self):
+        expected_split_box = shapely.geometry.MultiPolygon(polygons=[
+            shapely.geometry.Polygon(((180.0, -34.4), (180.0, 20.6), (172.1, 20.6), (172.1, -34.4),
+                                      (180.0, -34.4))),
+            shapely.geometry.Polygon(((-165.7, -34.4), (-165.7, 20.6), (-180.0, 20.6), (-180.0, -34.4),
+                                      (-165.7, -34.4)))])
+        self.assertEqual(expected_split_box,
+                         convert_geometry([172.1, -34.4, -165.7, 20.6]))
+
+    def test_convert_from_geojson_feature_dict(self):
+        expected_box1 = shapely.geometry.box(-10, -20, 20, 10)
+        expected_box2 = shapely.geometry.box(30, 20, 50, 40)
+        feature1 = dict(type='Feature', geometry=expected_box1.__geo_interface__)
+        feature2 = dict(type='Feature', geometry=expected_box2.__geo_interface__)
+        feature_collection = dict(type='FeatureCollection', features=(feature1, feature2))
+
+        actual_geom = convert_geometry(feature1)
+        self.assertEqual(expected_box1, actual_geom)
+
+        actual_geom = convert_geometry(feature2)
+        self.assertEqual(expected_box2, actual_geom)
+
+        expected_geom = shapely.geometry.GeometryCollection(geoms=[expected_box1, expected_box2])
+        actual_geom = convert_geometry(feature_collection)
+        self.assertEqual(expected_geom, actual_geom)
+
+    def test_convert_invalid_box(self):
+        from xcube.util.geom import _INVALID_BOX_COORDS_MSG
+
+        with self.assertRaises(ValueError) as cm:
+            convert_geometry([12.8, 20.6, 14.2, -34.4])
+        self.assertEqual(_INVALID_BOX_COORDS_MSG, f'{cm.exception}')
+        with self.assertRaises(ValueError) as cm:
+            convert_geometry([12.8, -34.4, 12.8, 20.6])
+        self.assertEqual(_INVALID_BOX_COORDS_MSG, f'{cm.exception}')
+        with self.assertRaises(ValueError) as cm:
+            convert_geometry([12.8, -34.4, 12.8, 20.6])
+        self.assertEqual(_INVALID_BOX_COORDS_MSG, f'{cm.exception}')
 
     def test_invalid(self):
-        expected_msg = ('geometry must be either a (shapely) geometry object, '
-                        'a valid GeoJSON object, a valid WKT string, '
-                        'box coordinates (x1, y1, x2, y2), '
-                        'or point coordinates (x, y)')
+        from xcube.util.geom import _INVALID_GEOMETRY_MSG
 
         with self.assertRaises(ValueError) as cm:
             convert_geometry(dict(coordinates=[12.8, -34.4]))
-        self.assertEqual(expected_msg, f'{cm.exception}')
+        self.assertEqual(_INVALID_GEOMETRY_MSG, f'{cm.exception}')
 
         with self.assertRaises(ValueError) as cm:
             convert_geometry([12.8, -34.4, '?'])
-        self.assertEqual(expected_msg, f'{cm.exception}')
+        self.assertEqual(_INVALID_GEOMETRY_MSG, f'{cm.exception}')
diff --git a/test/webapi/controllers/test_time_series.py b/test/webapi/controllers/test_time_series.py
index 6c48c8b1..e9efb467 100644
--- a/test/webapi/controllers/test_time_series.py
+++ b/test/webapi/controllers/test_time_series.py
@@ -9,6 +9,9 @@ from ..helpers import new_test_service_context
 
 class TimeSeriesControllerTest(unittest.TestCase):
 
+    def setUp(self) -> None:
+        self.maxDiff = None
+
     def test_get_time_series_for_point_invalid_lat_and_lon(self):
         ctx = new_test_service_context()
         time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm',
@@ -111,17 +114,17 @@ class TimeSeriesControllerTest(unittest.TestCase):
                                                        [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.]
                                                    ]]))
         expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z',
-                                      'result': {'average': 56.0228561816751,
+                                      'result': {'average': 56.12519223634024,
                                                  'totalCount': 1,
-                                                 'validCount': 122738}},
+                                                 'validCount': 122392}},
                                      {'date': '2017-01-25T09:35:51Z',
                                       'result': {'average': None, 'totalCount': 1, 'validCount': 0}},
                                      {'date': '2017-01-26T10:50:17Z',
                                       'result': {'average': None, 'totalCount': 1, 'validCount': 0}},
                                      {'date': '2017-01-28T09:58:11Z',
-                                      'result': {'average': 49.71656646340396,
+                                      'result': {'average': 49.70755256053988,
                                                  'totalCount': 1,
-                                                 'validCount': 132716}},
+                                                 'validCount': 132066}},
                                      {'date': '2017-01-30T10:46:34Z',
                                       'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]}
 
@@ -134,9 +137,9 @@ class TimeSeriesControllerTest(unittest.TestCase):
                                                        [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.]
                                                    ]]), max_valids=1)
         expected_dict = {'results': [{'date': '2017-01-28T09:58:11Z',
-                                      'result': {'average': 49.71656646340396,
+                                      'result': {'average': 49.70755256053988,
                                                  'totalCount': 1,
-                                                 'validCount': 132716}}]}
+                                                 'validCount': 132066}}]}
 
         self.assertEqual(expected_dict, time_series)
 
@@ -147,13 +150,13 @@ class TimeSeriesControllerTest(unittest.TestCase):
                                                        [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.]
                                                    ]]), max_valids=-1)
         expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z',
-                                      'result': {'average': 56.0228561816751,
+                                      'result': {'average': 56.12519223634024,
                                                  'totalCount': 1,
-                                                 'validCount': 122738}},
+                                                 'validCount': 122392}},
                                      {'date': '2017-01-28T09:58:11Z',
-                                      'result': {'average': 49.71656646340396,
+                                      'result': {'average': 49.70755256053988,
                                                  'totalCount': 1,
-                                                 'validCount': 132716}}]}
+                                                 'validCount': 132066}}]}
 
         self.assertEqual(expected_dict, time_series)
 
@@ -190,17 +193,17 @@ class TimeSeriesControllerTest(unittest.TestCase):
                                                                        [1., 51.]
                                                                    ]])]))
         expected_dict = {'results': [[{'date': '2017-01-16T10:09:22Z',
-                                       'result': {'average': 56.0228561816751,
+                                       'result': {'average': 56.12519223634024,
                                                   'totalCount': 1,
-                                                  'validCount': 122738}},
+                                                  'validCount': 122392}},
                                       {'date': '2017-01-25T09:35:51Z',
                                        'result': {'average': None, 'totalCount': 1, 'validCount': 0}},
                                       {'date': '2017-01-26T10:50:17Z',
                                        'result': {'average': None, 'totalCount': 1, 'validCount': 0}},
                                       {'date': '2017-01-28T09:58:11Z',
-                                       'result': {'average': 49.71656646340396,
+                                       'result': {'average': 49.70755256053988,
                                                   'totalCount': 1,
-                                                  'validCount': 132716}},
+                                                  'validCount': 132066}},
                                       {'date': '2017-01-30T10:46:34Z',
                                        'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]]}