issues

What is your issue?

I would like to create a PeriodicBoundaryIndex using the Explicit Indexes refactor. I want to do it first in 1D, then 2D, then maybe ND.

I'm thinking this would be useful for: 1) Geoscientists with periodic longitudes 2) Any scientists with periodic domains 3) Road-testing the refactor + how easy the documentation is to follow.

Eventually I think perhaps this index should live in xarray itself? As it's domain-agnostic, doesn't introduce extra dependencies, and could be a conceptually simple example of a custom index.

I had a first go, using the benbovy:add-set-xindex-and-drop-indexes branch, and reading the in-progress docs page. I got a bit stuck early on though.

@benbovy here's what I have so far:

```python import numpy as np import pandas as pd import xarray as xr from xarray.core.variable import Variable from xarray.core.indexes import PandasIndex, is_scalar

from typing import Union, Mapping, Any

class PeriodicBoundaryIndex(PandasIndex): """ An index representing any 1D periodic numberline.

Implementation subclasses a normal xarray PandasIndex object but intercepts indexer queries.
"""

def _periodic_subset(self, indxr: Union[int, slice, np.ndarray]) -> pd.Index:
    """Equivalent of __getitem__ for a pd.Index, but respects periodicity."""

    length = len(self)

    if isinstance(indxr, int):
        return self.index[indxr % length]
    elif isinstance(indxr, slice):
        raise NotImplementedError()
    elif isinstance(indxr, np.ndarray):
        raise NotImplementedError()
    else:
        raise TypeError

def isel(
    self, indexers: Mapping[Any, Union[int, slice, np.ndarray, Variable]]
) -> Union["PeriodicBoundaryIndex", None]:

    print("isel called")

    indxr = indexers[self.dim]
    if isinstance(indxr, Variable):
        if indxr.dims != (self.dim,):
            # can't preserve a index if result has new dimensions
            return None
        else:
            indxr = indxr.data
    if not isinstance(indxr, slice) and is_scalar(indxr):
        # scalar indexer: drop index
        return None

    subsetted_index = self._periodic_subset[indxr]
    return self._replace(subsetted_index)

```

```python airtemps = xr.tutorial.open_dataset("air_temperature")['air']

da = airtemps.drop_indexes("lon")

world = da.set_xindex("lon", index_cls=PeriodicBoundaryIndex) ```

Now selecting a value with isel inside the range works fine, giving the same result same as without my custom index. (The length of the example dataset along lon is 53.)

python world.isel(lon=45)

isel called <xarray.DataArray 'air' (time: 2920, lat: 25)> ...

But indexing with a lon value outside the range of the index data gives an IndexError, seemingly without consulting my new index object. It didn't even print "isel called" :confused: What should I have implemented that I didn't implement?

python world.isel(lon=55)

```python

IndexError Traceback (most recent call last) Input In [35], in <cell line: 1>() ----> 1 world.isel(lon=55)

File ~/Documents/Work/Code/xarray/xarray/core/dataarray.py:1297, in DataArray.isel(self, indexers, drop, missing_dims, **indexers_kwargs) 1292 return self._from_temp_dataset(ds) 1294 # Much faster algorithm for when all indexers are ints, slices, one-dimensional 1295 # lists, or zero or one-dimensional np.ndarray's -> 1297 variable = self._variable.isel(indexers, missing_dims=missing_dims) 1298 indexes, index_variables = isel_indexes(self.xindexes, indexers) 1300 coords = {}

File ~/Documents/Work/Code/xarray/xarray/core/variable.py:1233, in Variable.isel(self, indexers, missing_dims, **indexers_kwargs) 1230 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims) 1232 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims) -> 1233 return self[key]

File ~/Documents/Work/Code/xarray/xarray/core/variable.py:793, in Variable.getitem(self, key) 780 """Return a new Variable object whose contents are consistent with 781 getting the provided key from the underlying data. 782 (...) 790 array x.values directly. 791 """ 792 dims, indexer, new_order = self._broadcast_indexes(key) --> 793 data = as_indexable(self._data)[indexer] 794 if new_order: 795 data = np.moveaxis(data, range(len(new_order)), new_order)

File ~/Documents/Work/Code/xarray/xarray/core/indexing.py:657, in MemoryCachedArray.getitem(self, key) 656 def getitem(self, key): --> 657 return type(self)(_wrap_numpy_scalars(self.array[key]))

File ~/Documents/Work/Code/xarray/xarray/core/indexing.py:626, in CopyOnWriteArray.getitem(self, key) 625 def getitem(self, key): --> 626 return type(self)(_wrap_numpy_scalars(self.array[key]))

File ~/Documents/Work/Code/xarray/xarray/core/indexing.py:533, in LazilyIndexedArray.getitem(self, indexer) 531 array = LazilyVectorizedIndexedArray(self.array, self.key) 532 return array[indexer] --> 533 return type(self)(self.array, self._updated_key(indexer))

File ~/Documents/Work/Code/xarray/xarray/core/indexing.py:505, in LazilyIndexedArray._updated_key(self, new_key) 503 full_key.append(k) 504 else: --> 505 full_key.append(_index_indexer_1d(k, next(iter_new_key), size)) 506 full_key = tuple(full_key) 508 if all(isinstance(k, integer_types + (slice,)) for k in full_key):

File ~/Documents/Work/Code/xarray/xarray/core/indexing.py:278, in _index_indexer_1d(old_indexer, applied_indexer, size) 276 indexer = slice_slice(old_indexer, applied_indexer, size) 277 else: --> 278 indexer = _expand_slice(old_indexer, size)[applied_indexer] 279 else: 280 indexer = old_indexer[applied_indexer]

IndexError: index 55 is out of bounds for axis 0 with size 53 ```