xdas.coordinates.DenseCoordinate

class xdas.coordinates.DenseCoordinate(data=None, dim=None, dtype=None)

Coordinate backed by an explicit numpy array.

Suitable for irregularly-spaced or small axes where every value must be stored. Look-up is performed via a pandas.Index.

Parameters:

• data (array-like or None, optional) – 1-D array of coordinate values. None creates an empty coordinate.

• dim (str, optional) – Dimension name.

• dtype (dtype-like, optional) – Cast data to this dtype on construction.

__init__(data=None, dim=None, dtype=None)

Methods

__init__([data, dim, dtype])
concat(other)	Concatenate other DenseCoordinate values to this one.
copy([deep])	Return a copy of this coordinate.
equals(other)	Return True if other is a DenseCoordinate with identical values and dtype.
format_index(idx[, bounds])	Normalise integer index idx, handling negative indices and optional bounds checking.
from_block(start, size, step[, dim, dtype])	Build a DenseCoordinate from start + step * arange(size).
from_dataset(dataset, name)	Extract all coordinates from an xarray dataset variable name as plain arrays.
from_dict(dct)	Reconstruct a coordinate from the dict returned by to_dict().
get_availabilities()	Return a DataFrame containing information about the data availability.
get_discontinuities([tolerance])	Return a DataFrame containing information about the discontinuities.
get_div_points([tolerance])	Return sorted split-point indices where consecutive differences exceed tolerance.
get_indexer(value[, method])	Return the integer index (or indices) for value.
get_sampling_interval([cast])	Return the average sample spacing (end-to-end distance divided by N-1).
get_split_indices([kind, tolerance])	Return integer indices where this coordinate should be split.
is_monotonic_increasing()	Return True if all consecutive differences in this coordinate are positive.
isdefault()	Return True if this is a DefaultCoordinate (integer range).
isdense()	Return True (this is a DenseCoordinate).
isdim()	Return True if this coordinate is a dimensional coordinate in its parent container.
isinterp()	Return True if this is an InterpCoordinate (piecewise-linear).
issampled()	Return True if this is a SampledCoordinate (regularly sampled).
isscalar()	Return True if this is a ScalarCoordinate (non-dimensional).
isvalid(data)	Return True if data converts to a 1-D non-object numpy array.
simplify([tolerance])	Reduce tie-point count within tolerance.
slice_indexer([start, stop, step, endpoint])	Return an integer slice for label range [start, stop] via pandas.Index.
to_dataarray()	Convert this coordinate to a DataArray with a single dimension.
to_dataset(dataset, attrs)	Write this coordinate into an xarray dataset, updating attrs in place.
to_dict()	Serialise to {"dim": ..., "data": ..., "dtype": ...}.
to_index(item[, method, endpoint])	Convert a label-based selector to an integer index or slice.

Attributes

dtype	NumPy dtype of the underlying data array.
empty	True if the coordinate has zero length.
index	A pandas.Index view of the underlying data array.
name	The name under which this coordinate is stored in its parent container.
ndim	Number of dimensions of the underlying data array (always 1 for dimensional coords).
parent	The parent Coordinates container, or None if unattached.
shape	Shape tuple of the underlying data array.
values	Materialised numpy array of coordinate values.