Fixed issues with irregular xarray shape (#4188)

holoviews/core/data/xarray.py

@@ -52,29 +52,13 @@ def packed(cls, dataset):
     @classmethod
     def shape(cls, dataset, gridded=False):
         if cls.packed(dataset):
-            shape = dataset.data.shape[:-1]
-            if gridded:
-                return shape
-            else:
-                return (np.product(shape, dtype=np.intp), len(dataset.dimensions()))
+            array = dataset.data[..., 0]
         else:
             array = dataset.data[dataset.vdims[0].name]
-        if not any(cls.irregular(dataset, kd) for kd in dataset.kdims):
-            names = [kd.name for kd in dataset.kdims
-                     if kd.name in array.dims][::-1]
-            if not all(d in names for d in array.dims):
-                array = np.squeeze(array)
-            if len(names) > 1:
-                try:
-                    array = array.transpose(*names, transpose_coords=False)
-                except:
-                    array = array.transpose(*names) # Handle old xarray
-        shape = array.shape
-        if gridded:
-            return shape
-        else:
-            return (np.product(shape, dtype=np.intp), len(dataset.dimensions()))
-
+        if not gridded:
+            return (np.product(array.shape, dtype=np.intp), len(dataset.dimensions()))
+        shape_map = dict(zip(array.dims, array.shape))
+        return tuple(shape_map.get(kd.name, np.nan) for kd in dataset.kdims[::-1])
 
     @classmethod
     def init(cls, eltype, data, kdims, vdims):
@@ -342,8 +326,7 @@ def coords(cls, dataset, dimension, ordered=False, expanded=False, edges=False):
 
         if dim in dataset.kdims:
             idx = dataset.get_dimension_index(dim)
-            isedges = (dim in dataset.kdims and len(shape) == dataset.ndims
-                       and len(data) == (shape[dataset.ndims-idx-1]+1))
+            isedges = (len(shape) == dataset.ndims and len(data) == (shape[dataset.ndims-idx-1]+1))
         else:
             isedges = False
         if edges and not isedges:

holoviews/tests/core/data/testxarrayinterface.py

@@ -5,6 +5,7 @@
 import numpy as np
 
 try:
+    import pandas as pd
     import xarray as xr
 except:
     raise SkipTest("Could not import xarray, skipping XArrayInterface tests.")
@@ -45,6 +46,29 @@ def get_irregular_dataarray(self, invert_y=True):
         return da.assign_coords(**{'xc': xr.DataArray(xs, dims=('y','x')),
                                    'yc': xr.DataArray(ys, dims=('y','x')),})
 
+    def get_multi_dim_irregular_dataset(self):
+        temp = 15 + 8 * np.random.randn(2, 2, 4, 3)
+        precip = 10 * np.random.rand(2, 2, 4, 3)
+        lon = [[-99.83, -99.32], [-99.79, -99.23]]
+        lat = [[42.25, 42.21], [42.63, 42.59]]
+        return xr.Dataset({'temperature': (['x', 'y', 'z', 'time'],  temp),
+                         'precipitation': (['x', 'y', 'z', 'time'], precip)},
+                        coords={'lon': (['x', 'y'], lon),
+                                'lat': (['x', 'y'], lat),
+                                'z': np.arange(4),
+                                'time': pd.date_range('2014-09-06', periods=3),
+                                'reference_time': pd.Timestamp('2014-09-05')})
+
+    def test_xarray_dataset_irregular_shape(self):
+        ds = Dataset(self.get_multi_dim_irregular_dataset())
+        shape = ds.interface.shape(ds, gridded=True)
+        self.assertEqual(shape, (np.nan, np.nan, 3, 4))
+
+    def test_xarray_irregular_dataset_values(self):
+        ds = Dataset(self.get_multi_dim_irregular_dataset())
+        values = ds.dimension_values('z', expanded=False)
+        self.assertEqual(values, np.array([0, 1, 2, 3]))
+
     def test_xarray_dataset_with_scalar_dim_canonicalize(self):
         xs = [0, 1]
         ys = [0.1, 0.2, 0.3]