Xarray/Dask Exception in cmip6_precip_analysis #7
Description
Xarray/dask are throwing a new error in this the cmip6_precip_analysis notebook.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-13-89aa342a55bc> in <module>
3 da = da.chunk({'lat': 1, 'lon': None, 'time': None})
4 return xr_histogram(da, bins, ['lon', 'time'], density=False)
----> 5 pr_3hr_hist = ds.pr.groupby('time.year').apply(func)
6 pr_3hr_hist
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/groupby.py in apply(self, func, shortcut, args, **kwargs)
572 applied = (maybe_wrap_array(arr, func(arr, *args, **kwargs))
573 for arr in grouped)
--> 574 return self._combine(applied, shortcut=shortcut)
575
576 def _combine(self, applied, restore_coord_dims=False, shortcut=False):
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/groupby.py in _combine(self, applied, restore_coord_dims, shortcut)
576 def _combine(self, applied, restore_coord_dims=False, shortcut=False):
577 """Recombine the applied objects like the original."""
--> 578 applied_example, applied = peek_at(applied)
579 coord, dim, positions = self._infer_concat_args(applied_example)
580 if shortcut:
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/utils.py in peek_at(iterable)
152 """
153 gen = iter(iterable)
--> 154 peek = next(gen)
155 return peek, itertools.chain([peek], gen)
156
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/groupby.py in <genexpr>(.0)
571 grouped = self._iter_grouped()
572 applied = (maybe_wrap_array(arr, func(arr, *args, **kwargs))
--> 573 for arr in grouped)
574 return self._combine(applied, shortcut=shortcut)
575
<ipython-input-13-89aa342a55bc> in func(da)
2 def func(da):
3 da = da.chunk({'lat': 1, 'lon': None, 'time': None})
----> 4 return xr_histogram(da, bins, ['lon', 'time'], density=False)
5 pr_3hr_hist = ds.pr.groupby('time.year').apply(func)
6 pr_3hr_hist
<ipython-input-12-9c2fe48cd1a0> in xr_histogram(data, bins, dims, **kwargs)
10 output_dtypes=['f8'],
11 output_sizes={output_dim_name: len(bins_c)},
---> 12 vectorize=True, dask='parallelized')
13 res[output_dim_name] = output_dim_name, bins_c
14 res[output_dim_name].attrs.update(data.attrs)
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/computation.py in apply_ufunc(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, *args)
967 join=join,
968 exclude_dims=exclude_dims,
--> 969 keep_attrs=keep_attrs)
970 elif any(isinstance(a, Variable) for a in args):
971 return variables_vfunc(*args)
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, *args)
215
216 data_vars = [getattr(a, 'variable', a) for a in args]
--> 217 result_var = func(*data_vars)
218
219 if signature.num_outputs > 1:
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/computation.py in apply_variable_ufunc(func, signature, exclude_dims, dask, output_dtypes, output_sizes, keep_attrs, *args)
562 raise ValueError('unknown setting for dask array handling in '
563 'apply_ufunc: {}'.format(dask))
--> 564 result_data = func(*input_data)
565
566 if signature.num_outputs == 1:
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/computation.py in func(*arrays)
556 return _apply_blockwise(
557 numpy_func, arrays, input_dims, output_dims,
--> 558 signature, output_dtypes, output_sizes)
559 elif dask == 'allowed':
560 pass
/srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/computation.py in _apply_blockwise(func, args, input_dims, output_dims, signature, output_dtypes, output_sizes)
658
659 return blockwise(func, out_ind, *blockwise_args, dtype=dtype,
--> 660 concatenate=True, new_axes=output_sizes)
661
662
/srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/blockwise.py in blockwise(func, out_ind, name, token, dtype, adjust_chunks, new_axes, align_arrays, concatenate, meta, *args, **kwargs)
231 from .utils import compute_meta
232
--> 233 meta = compute_meta(func, dtype, *args[::2], **kwargs)
234 if meta is not None:
235 return Array(graph, out, chunks, meta=meta)
/srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/utils.py in compute_meta(func, _dtype, *args, **kwargs)
118 # with np.vectorize, such as dask.array.routines._isnonzero_vec().
119 if isinstance(func, np.vectorize):
--> 120 meta = func(*args_meta)
121 else:
122 try:
/srv/conda/envs/notebook/lib/python3.7/site-packages/numpy/lib/function_base.py in __call__(self, *args, **kwargs)
2089 vargs.extend([kwargs[_n] for _n in names])
2090
-> 2091 return self._vectorize_call(func=func, args=vargs)
2092
2093 def _get_ufunc_and_otypes(self, func, args):
/srv/conda/envs/notebook/lib/python3.7/site-packages/numpy/lib/function_base.py in _vectorize_call(self, func, args)
2155 """Vectorized call to `func` over positional `args`."""
2156 if self.signature is not None:
-> 2157 res = self._vectorize_call_with_signature(func, args)
2158 elif not args:
2159 res = func()
/srv/conda/envs/notebook/lib/python3.7/site-packages/numpy/lib/function_base.py in _vectorize_call_with_signature(self, func, args)
2229 for dims in output_core_dims
2230 for dim in dims):
-> 2231 raise ValueError('cannot call `vectorize` with a signature '
2232 'including new output dimensions on size 0 '
2233 'inputs')
ValueError: cannot call `vectorize` with a signature including new output dimensions on size 0 inputs