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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1050937380 | I_kwDOAMm_X84-pAgk | 5975 | Typing of dim in concat.py does not include Hashable | LunarLanding 4441338 | closed | 0 | 2 | 2021-11-11T12:38:44Z | 2022-05-17T20:53:07Z | 2022-05-17T20:53:07Z | NONE | Arent' dims supposed to be any Hashable? In other xarray methods they generally are. |
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| 869786882 | MDU6SXNzdWU4Njk3ODY4ODI= | 5228 | sel(dim=slice(a,b,c)) only accepts integers for c, uses c as isel does | LunarLanding 4441338 | closed | 0 | 1 | 2021-04-28T10:22:40Z | 2021-04-28T10:47:00Z | 2021-04-28T10:46:59Z | NONE | Trying to slice with sel using label delta values as interval, i.e. What happened: The label delta value is not accepted. What you expected to happen:
Selecting c-spaced samples from the DataArray Minimal Complete Verifiable Example: ```python dim0_n = 100 d = xr.DataArray(np.arange(dim0_n),coords={'dim0':np.linspace(0,1,num=dim0_n)},dims=('dim0',)) d.sel(dim0=slice(None,None,0.1)) expected 0,10,20,...,90instead get a TypeError: 'float' object cannot be interpreted as an integer(full traceback below)``` Full traceback``` TypeError Traceback (most recent call last) <ipython-input-43-9eb3e3c8bbe4> in <module> 1 dim0_n = 100 2 d = xr.DataArray(np.arange(dim0_n),coords={'dim0':np.linspace(0,1,num=dim0_n)},dims=('dim0',)) ----> 3 d.sel(dim0=slice(None,None,0.1)) 4 # expected 0,10,20,...,90 5 # instead get a TypeError (traceback below) ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 1252 Dimensions without coordinates: points 1253 """ -> 1254 ds = self._to_temp_dataset().sel( 1255 indexers=indexers, 1256 drop=drop, ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 2231 self, indexers=indexers, method=method, tolerance=tolerance 2232 ) -> 2233 result = self.isel(indexers=pos_indexers, drop=drop) 2234 return result._overwrite_indexes(new_indexes) 2235 ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataset.py in isel(self, indexers, drop, missing_dims, **indexers_kwargs) 2093 var_indexers = {k: v for k, v in indexers.items() if k in var_value.dims} 2094 if var_indexers: -> 2095 var_value = var_value.isel(var_indexers) 2096 if drop and var_value.ndim == 0 and var_name in coord_names: 2097 coord_names.remove(var_name) ~/miniconda3/lib/python3.9/site-packages/xarray/core/variable.py in isel(self, indexers, missing_dims, **indexers_kwargs) 1164 1165 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims) -> 1166 return self[key] 1167 1168 def squeeze(self, dim=None): ~/miniconda3/lib/python3.9/site-packages/xarray/core/variable.py in __getitem__(self, key) 808 array `x.values` directly. 809 """ --> 810 dims, indexer, new_order = self._broadcast_indexes(key) 811 data = as_indexable(self._data)[indexer] 812 if new_order: ~/miniconda3/lib/python3.9/site-packages/xarray/core/variable.py in _broadcast_indexes(self, key) 647 648 if all(isinstance(k, BASIC_INDEXING_TYPES) for k in key): --> 649 return self._broadcast_indexes_basic(key) 650 651 self._validate_indexers(key) ~/miniconda3/lib/python3.9/site-packages/xarray/core/variable.py in _broadcast_indexes_basic(self, key) 675 dim for k, dim in zip(key, self.dims) if not isinstance(k, integer_types) 676 ) --> 677 return dims, BasicIndexer(key), None 678 679 def _validate_indexers(self, key): ~/miniconda3/lib/python3.9/site-packages/xarray/core/indexing.py in __init__(self, key) 382 k = int(k) 383 elif isinstance(k, slice): --> 384 k = as_integer_slice(k) 385 else: 386 raise TypeError( ~/miniconda3/lib/python3.9/site-packages/xarray/core/indexing.py in as_integer_slice(value) 359 start = as_integer_or_none(value.start) 360 stop = as_integer_or_none(value.stop) --> 361 step = as_integer_or_none(value.step) 362 return slice(start, stop, step) 363 ~/miniconda3/lib/python3.9/site-packages/xarray/core/indexing.py in as_integer_or_none(value) 353 354 def as_integer_or_none(value): --> 355 return None if value is None else operator.index(value) 356 357 TypeError: 'float' object cannot be interpreted as an integer ``` Anything else we need to know?: I think a warning in the documentation would be nice. It happened that I was giving integer values to c and xarray was subsetting datasets in an entirely different way that the one intended. It took noticing a downstream effect to find this behavior. Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.9.2 | packaged by conda-forge | (default, Feb 21 2021, 05:02:46) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.11.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: None LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.17.0 pandas: 1.2.4 numpy: 1.20.2 scipy: 1.6.2 netCDF4: 1.5.6 pydap: None h5netcdf: 0.11.0 h5py: 3.1.0 Nio: None zarr: 2.8.1 cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2021.04.1 distributed: 2021.04.1 matplotlib: 3.3.4 cartopy: None seaborn: 0.11.1 numbagg: None pint: None setuptools: 51.0.0.post20201207 pip: 21.1 conda: 4.10.1 pytest: None IPython: 7.22.0 sphinx: None |
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| 831148018 | MDU6SXNzdWU4MzExNDgwMTg= | 5034 | output_dtypes needs to be a tuple, not a sequence | LunarLanding 4441338 | closed | 0 | 4 | 2021-03-14T12:47:49Z | 2021-04-19T19:33:14Z | 2021-04-19T19:33:14Z | NONE | If a sequence, I get MVE ( WIP, will finish later ) ``` p,v are chunked in 'time'M is a positive integermsd_w_one_mol takes two args, has two outputsm,w = xr.apply_ufunc( msd_w_one_mol, p,v, input_core_dims=[('time','spatial'),('time',)], output_core_dims=[('interval',),('interval',)], vectorize=True, dask='parallelized', dask_gufunc_kwargs={ 'output_sizes':{'interval':M}, 'allow_rechunk':True, 'meta':(np.empty((M,),dtype=p.dtype),np.empty((M,),dtype=np.min_scalar_type(M)))'output_dtypes':[p.dtype,np.min_scalar_type(M)],) ``` Stack Trace: ``` ValueError Traceback (most recent call last) ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/gufunc.py in apply_gufunc(func, signature, args, kwargs) 429 try: --> 430 tmp = blockwise( # First try to compute meta 431 func, loop_output_dims, arginds, concatenate=True, **kwargs ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/blockwise.py in blockwise(func, out_ind, name, token, dtype, adjust_chunks, new_axes, align_arrays, concatenate, meta, args, kwargs) 278 --> 279 meta = compute_meta(func, dtype, args[::2], **kwargs) 280 return new_da_object(graph, out, chunks, meta=meta, dtype=dtype) ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/utils.py in compute_meta(func, _dtype, args, kwargs) 138 if isinstance(func, np.vectorize): --> 139 meta = func(args_meta) 140 else: ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/numpy/lib/function_base.py in call(self, args, *kwargs) 2112 -> 2113 return self._vectorize_call(func=func, args=vargs) 2114 ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/numpy/lib/function_base.py in _vectorize_call(self, func, args) 2186 if self.signature is not None: -> 2187 res = self._vectorize_call_with_signature(func, args) 2188 elif not args: ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/numpy/lib/function_base.py in _vectorize_call_with_signature(self, func, args)
2260 for dim in dims):
-> 2261 raise ValueError('cannot call ValueError: cannot call During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) <ipython-input-119-a2a3ac7df12d> in <module> ----> 1 m,w = xr.apply_ufunc( 2 msd_w_one_mol, 3 p,v, 4 input_core_dims=[('time','spatial'),('time',)], 5 output_core_dims=[('interval',),('interval',)], ~/dotfiles/conda/base/.conda/lib/python3.8/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, meta, dask_gufunc_kwargs, args) 1126 # feed DataArray apply_variable_ufunc through apply_dataarray_vfunc 1127 elif any(isinstance(a, DataArray) for a in args): -> 1128 return apply_dataarray_vfunc( 1129 variables_vfunc, 1130 args, ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/xarray/core/computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, args) 269 270 data_vars = [getattr(a, "variable", a) for a in args] --> 271 result_var = func(data_vars) 272 273 if signature.num_outputs > 1: ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/xarray/core/computation.py in apply_variable_ufunc(func, signature, exclude_dims, dask, output_dtypes, vectorize, keep_attrs, dask_gufunc_kwargs, args) 722 ) 723 --> 724 result_data = func(input_data) 725 726 if signature.num_outputs == 1: ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/xarray/core/computation.py in func(*arrays) 690 import dask.array as da 691 --> 692 res = da.apply_gufunc( 693 numpy_func, 694 signature.to_gufunc_string(exclude_dims), ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/gufunc.py in apply_gufunc(func, signature, args, *kwargs) 441 ) 442 else: --> 443 meta = tuple( 444 meta_from_array(sample, dtype=odt) 445 for ocd, odt in zip((output_coredimss,), (output_dtypes,)) ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/gufunc.py in <genexpr>(.0) 442 else: 443 meta = tuple( --> 444 meta_from_array(sample, dtype=odt) 445 for ocd, odt in zip((output_coredimss,), (output_dtypes,)) 446 ) ~/dotfiles/conda/base/.conda/lib/python3.8/site-packages/dask/array/utils.py in meta_from_array(x, ndim, dtype) 104 meta = np.array(meta) 105 --> 106 if dtype and meta.dtype != dtype: 107 try: 108 meta = meta.astype(dtype) TypeError: Field elements must be 2- or 3-tuples, got 'dtype('float64')' ``` Preliminary investigation using %debug: ```
ipdb> print(dtype) [dtype('float64'), dtype('uint16')] ipdb> print(meta.dtype) float64 ipdb> print(dtype) [dtype('float64'), dtype('uint16')] ``` |
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completed | xarray 13221727 | issue |
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