plot dataset with 2D coordinate variables

I have an xarray dataset with the following structure:

<xarray.Dataset>
Dimensions:   (face: 13, i: 4320, j: 4320,  k: 90, time: 1)
Coordinates:
  * k         (k) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ...
  * j         (j) float64 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 ...
  * i         (i) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ...
  * face      (face) int64 0 1 2 3 4 5 6 7 8 9 10 11 12
    iter      (time) int64 487152
  * time      (time) int64 487152
    XC        (face, j, i) >f4 -114.932 -114.932 -114.932 -114.932 -114.932 ...
    YC        (face, j, i) >f4 -88.1771 -88.1801 -88.183 -88.1859 -88.1888 ...
    Z         (k) >f4 -0.5 -1.57 -2.79 -4.185 -5.78 -7.595 -9.66 -12.01 ...
Data variables:
    Theta     (time, k, face, j, i) >f4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...
    Salt      (time, k, face, j, i) >f4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...

This is an enormous dataset from a ocean simulation using a faceted curvilinear grid. The longitudes latitudes, and depths of the data are encoded by the variables ‘XC’ and ‘YC’.

I am trying, unsuccessfully, to use geoviews to visualize this data. Here is what I am doing:

import geoviews as gv
gvds_from_xr = gv.Dataset(ds, kdims=['XC', 'YC', 'Z', 'time'], vdims=['Theta', 'Salt'])
gvds_from_xr.to(gv.Image, ['XC', 'YC'])

This raises the error

ValueError: dimensions or multi-index levels ['Z'] do not exist

If I try

gvds_from_xr = gv.Dataset(ds, kdims=['XC', 'YC', 'k', 'time'], vdims=['Theta', 'Salt'])
gvds_from_xr.to(gv.Image, ['XC', 'YC'])

(replacing physical dimension ‘Z’ with logical dimension ‘k’) I get the following stack trace:

ValueErrorTraceback (most recent call last)
<ipython-input-27-02d44a5c1c08> in <module>()
      2 get_ipython().magic(u"time gvds_from_xr = gv.Dataset(ds, kdims=['XC', 'YC', 'k', 'time'], vdims=['Theta', 'Salt'])")
      3 print(gvds_from_xr)
----> 4 get_ipython().magic(u"time gvds_from_xr.to(gv.Image, ['XC', 'YC'])")

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/IPython/core/interactiveshell.pyc in magic(self, arg_s)
   2156         magic_name, _, magic_arg_s = arg_s.partition(' ')
   2157         magic_name = magic_name.lstrip(prefilter.ESC_MAGIC)
-> 2158         return self.run_line_magic(magic_name, magic_arg_s)
   2159 
   2160     #-------------------------------------------------------------------------

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/IPython/core/interactiveshell.pyc in run_line_magic(self, magic_name, line)
   2077                 kwargs['local_ns'] = sys._getframe(stack_depth).f_locals
   2078             with self.builtin_trap:
-> 2079                 result = fn(*args,**kwargs)
   2080             return result
   2081 

<decorator-gen-59> in time(self, line, cell, local_ns)

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/IPython/core/magic.pyc in <lambda>(f, *a, **k)
    186     # but it's overkill for just that one bit of state.
    187     def magic_deco(arg):
--> 188         call = lambda f, *a, **k: f(*a, **k)
    189 
    190         if callable(arg):

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/IPython/core/magics/execution.pyc in time(self, line, cell, local_ns)
   1174         if mode=='eval':
   1175             st = clock2()
-> 1176             out = eval(code, glob, local_ns)
   1177             end = clock2()
   1178         else:

<timed eval> in <module>()

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/geoviews/element/__init__.pyc in __call__(self, *args, **kwargs)
     24         if 'crs' not in kwargs and issubclass(group_type, _Element):
     25             kwargs['crs'] = self._element.crs
---> 26         return super(GeoConversion, self).__call__(*args, **kwargs)
     27 
     28     def linecontours(self, kdims=None, vdims=None, mdims=None, **kwargs):

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/data/__init__.pyc in __call__(self, new_type, kdims, vdims, mdims, sort, **kwargs)
     92             return element.sort() if sort else element
     93         group = selected.groupby(mdims, container_type=HoloMap,
---> 94                                  group_type=new_type, **params)
     95         if sort:
     96             return group.map(lambda x: x.sort(), [new_type])

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/data/__init__.pyc in groupby(self, dimensions, container_type, group_type, dynamic, **kwargs)
    409 
    410         return self.interface.groupby(self, dim_names, container_type,
--> 411                                       group_type, **kwargs)
    412 
    413     def __len__(self):

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/data/xarray.pyc in groupby(cls, dataset, dimensions, container_type, group_type, **kwargs)
    110             data = [(k, group_type(dataset.data.sel(**dict(zip(dimensions, k))),
    111                                    **group_kwargs))
--> 112                     for k in indexes]
    113 
    114         if issubclass(container_type, NdMapping):

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/geoviews/element/geo.pyc in __init__(self, data, **kwargs)
     83         elif crs:
     84             kwargs['crs'] = crs
---> 85         super(_Element, self).__init__(data, **kwargs)
     86 
     87 

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/element/raster.pyc in __init__(self, data, **params)
    657 
    658     def __init__(self, data, **params):
--> 659         super(GridImage, self).__init__(data, **params)
    660         (l, r), (b, t) = self.interface.range(self, 0), self.interface.range(self, 1)
    661         (ys, xs) = self.dimension_values(2, flat=False).shape

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/data/__init__.pyc in __init__(self, data, **kwargs)
    135                                            datatype=kwargs.get('datatype'))
    136         (data, self.interface, dims, extra_kws) = initialized
--> 137         super(Dataset, self).__init__(data, **dict(extra_kws, **dict(kwargs, **dims)))
    138         self.interface.validate(self)
    139 

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/dimension.pyc in __init__(self, data, **params)
    593                                   for d in params.pop(group)]
    594                 params[group] = dimensions
--> 595         super(Dimensioned, self).__init__(data, **params)
    596         self.ndims = len(self.kdims)
    597         cdims = [(d.name, val) for d, val in self.cdims.items()]

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/holoviews/core/dimension.pyc in __init__(self, data, id, **params)
    297             params['group'] = long_name
    298 
--> 299         super(LabelledData, self).__init__(**params)
    300         if not group_sanitizer.allowable(self.group):
    301             raise ValueError("Supplied group %r contains invalid characters." %

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/param/parameterized.pyc in __init__(self, **params)
   1039         self.__generate_name()
   1040 
-> 1041         self._setup_params(**params)
   1042         object_count += 1
   1043 

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/param/parameterized.pyc in override_initialization(parameterized_instance, *args, **kw)
    976         original_initialized=parameterized_instance.initialized
    977         parameterized_instance.initialized=False
--> 978         fn(parameterized_instance,*args,**kw)
    979         parameterized_instance.initialized=original_initialized
    980     return override_initialization

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/param/parameterized.pyc in _setup_params(self, **params)
   1439                 self.warning("Setting non-parameter attribute %s=%s using a mechanism intended only for parameters",name,val)
   1440             # i.e. if not desc it's setting an attribute in __dict__, not a Parameter
-> 1441             setattr(self,name,val)
   1442 
   1443 

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/param/__init__.pyc in __set__(self, obj, val)
   1151     def __set__(self,obj,val):
   1152         """Set to the given value, raising an exception if out of bounds."""
-> 1153         self._check_bounds(val)
   1154         super(List,self).__set__(obj,val)
   1155 

/home/rpa/.conda/envs/lagrangian_vorticity/lib/python2.7/site-packages/param/__init__.pyc in _check_bounds(self, val)
   1170             if min_length is not None and max_length is not None:
   1171                 if not (min_length <= l <= max_length):
-> 1172                     raise ValueError("%s: list length must be between %s and %s (inclusive)"%(self._attrib_name,min_length,max_length))
   1173             elif min_length is not None:
   1174                 if not min_length <= l:

ValueError: vdims: list length must be between 1 and 1 (inclusive)

Clearly I am doing something wrong, but I can’t figure out what.

Thanks for any help you can provide.

[philippjfr]

hv/gv.Dataset now natively understands datasets with multi-dimensional coordinates and they can now be plotted with a QuadMesh. Closing.

[philippjfr]

@rabernat We have now released both HoloViews 1.7.0 and GeoViews 1.2.0 and are now focusing on improving the documentation. Could you try updating to the latest versions using:

conda install -c ioam -c conda-forge holoviews geoviews

And report back if everything is working for you?