xarray.core.rolling.DatasetCoarsen#
- class xarray.core.rolling.DatasetCoarsen(obj, windows, boundary, side, coord_func)[source]#
- __init__(obj, windows, boundary, side, coord_func)[source]#
Moving window object.
- Parameters:
windows (mapping of hashable to
int
) – A mapping from the name of the dimension to create the rolling exponential window along (e.g. time) to the size of the moving window.boundary (
{"exact", "trim", "pad"}
) – If ‘exact’, a ValueError will be raised if dimension size is not a multiple of window size. If ‘trim’, the excess indexes are trimmed. If ‘pad’, NA will be padded.side (
'left'
or'right'
ormapping from dimension
to'left'
or'right'
)coord_func (
function (name)
ormapping from coordinate name
tofunction (name).
)
- Returns:
coarsen
Methods
__init__
(obj, windows, boundary, side, ...)Moving window object.
all
([keep_attrs])Reduce this DatasetCoarsen's data by applying all along some dimension(s).
any
([keep_attrs])Reduce this DatasetCoarsen's data by applying any along some dimension(s).
construct
([window_dim, keep_attrs])Convert this Coarsen object to a DataArray or Dataset, where the coarsening dimension is split or reshaped to two new dimensions.
count
([keep_attrs])Reduce this DatasetCoarsen's data by applying count along some dimension(s).
max
([keep_attrs])Reduce this DatasetCoarsen's data by applying max along some dimension(s).
mean
([keep_attrs])Reduce this DatasetCoarsen's data by applying mean along some dimension(s).
median
([keep_attrs])Reduce this DatasetCoarsen's data by applying median along some dimension(s).
min
([keep_attrs])Reduce this DatasetCoarsen's data by applying min along some dimension(s).
prod
([keep_attrs])Reduce this DatasetCoarsen's data by applying prod along some dimension(s).
reduce
(func[, keep_attrs])Reduce the items in this group by applying func along some dimension(s).
std
([keep_attrs])Reduce this DatasetCoarsen's data by applying std along some dimension(s).
sum
([keep_attrs])Reduce this DatasetCoarsen's data by applying sum along some dimension(s).
var
([keep_attrs])Reduce this DatasetCoarsen's data by applying var along some dimension(s).
Attributes