gs_Coordinate

Inheritance diagram of gspy.src.classes.data.xarray_gs.Coordinate
class gspy.src.classes.data.xarray_gs.Coordinate.Coordinate(xarray_obj)

Accessor to xarray.DataArray to define a Coordinate.

Checks necessary metadata to satisfy the CF convention, and allows use with GIS software. Handles both arbitrary coordinates and standard coordinates defined as x, y, z, or t used within NetCDF files. Standard coordinates have extra checks on the metadata.

See also

Coordinate.from_dict

For instantiation

Coordinate.from_values

For instantiation

static check_is_projected(name, is_projected)

Checks for a projected standard coordinate x or y

Parameters:

  • name (str) – Name of the coordinate

  • is_projected (bool) – Is the coordinate projected or not

Returns:

out

Return type:

str

static check_standard_coordinates(name, **kwargs)

If this is a standard coordinate do some extra checks on metadata.

Parameters:

  • axis (int, optional) – Axis this Coordinate belongs to .

  • positive (str, optional) – “up” or “down”. Only used if name == ‘z’.

  • datum (str, optional) – Datum. Only used if name == ‘z’ or ‘t’.

classmethod from_dict(name, is_projected=False, is_dimension=False, **kwargs)

Specifically generates a coordinate/dimension from a dict.

Automatically checks/generates required Coordinate metadata and bounds. If the coordinate is a “standard coordinate” i.e. (‘x’, ‘y’, ‘z’, ‘t’), extra checks on metadata are performed.

Parameters:

  • name (str) – The name of the coordinate to attach

  • is_projected (bool) – If the coordinate is projected, the standard_name metadata entry needs to change

  • is_dimension (bool) – If the coordinate is a coordinate-dimension defines its dims as itself

  • centers (array_like, optional) –

    • Explicit definition of Coordinate center values. Used for non-uniformly distanced center values.

    • Has shape (size of dimension, ) defining the center values of each “cell”

  • increment (scalar, optional) – Increment of the Coordinate centers. Only used if centers is None.

  • length (int, optional) – Size of the Coordinate centers. Only used if centers is None.

  • origin (scalar, optional) – Lower limit of the Coordinate centers. Only used if centers is None.

See also

DataArray.DataArray.from_values

For GS standard metadata keywords

Coordinate.check_standard_coordinates

For extra keywords when name in (‘x’, ‘y’, ‘z’, ‘t’)

Example

>>> depth_dict = {"standard_name": "depth",
>>>               "long_name": "Depth below earth's surface DTM",
>>>               "units": "m",
>>>               "null_value": "not_defined",
>>>               "centers" : [2.5, 7.5, 20.0]}
>>> Coordinate.from_dict('depth', **depth_dict)
classmethod from_values(name, values, is_projected=False, is_dimension=False, **kwargs)

Generate a Coordinate from an array of values.

Parameters:

  • name (str) – The name of the coordinate to attach

  • is_projected (bool) – If the coordinate is projected, the standard_name metadata entry needs to change

  • is_dimension (bool) – If the coordinate is a coordinate-dimension defines its dims as itself.

  • centers (array_like, optional) – Explicit definition of Coordinate center values. Used for non-uniformly distanced center values. Has shape (size of dimension, ) defining the center values of each “cell”

  • increment (scalar, optional) – Increment of the Coordinate centers. Only used if centers is None.

  • length (int, optional) – Size of the Coordinate centers. Only used if centers is None.

  • origin (scalar, optional) – Lower limit of the Coordinate centers. Only used if centers is None.

See also

DataArray.DataArray.from_values

For GS convention metadata keywords

Coordinate.check_standard_coordinates

For extra keywords when creating a standard coordinate

Example

>>> depth_dict = {"standard_name": "depth",
>>>               "long_name": "Depth below earth's surface DTM",
>>>               "units": "m",
>>>               "null_value": "not_defined",
>>>               "centers" : [2.5, 7.5, 20.0]}
>>> Coordinate.from_dict('depth', np.r_[2.5, 7.5, 20.0], **depth_dict)