rex.external.rexarray.RexArrayWrapper

class RexArrayWrapper(variable_name, datastore, dtype, shape, meta_index=-1, coord_index=-1, scale_factor=1, adder=0)[source]

Bases: BackendArray

rexarray implementation of a BackendArray

Parameters:

variable_name (str) – Name of variable associated with data.
datastore (RexStore) – Open RexStore instance that can be used to retrieve the data.
dtype (str | obj) – Data type.
shape (tuple) – Tuple representing data shape.
meta_index (int, default=-1) – Index value specifying wether variable came from meta. If this value is positive, the variable is assumed to originate from the meta. In this case, the value should represent the index in the meta records array corresponding to the variable. If negative, then this input is ignored. By default, -1.
coord_index (int, default=-1) – Index value specifying wether variable came from coordinates dataset. If this value is positive, the variable is assumed to originate from coordinates. In this case, the value should represent the last index in the coordinates array corresponding to the variable (typically 0 for latitude, 1 for longitude). If negative, then this input is ignored. By default, -1.
scale_factor (int | float, default=1) – Optional rex-style scaling factor. By default, 1.
adder (int | float, default=0) – Optional rex-style adder. By default, 0.

Methods

`get_array`([needs_lock])	Get array of data for variable
`get_duck_array`([dtype])

Attributes

`datastore`
`dtype`
`shape`
`variable_name`
`meta_index`
`coord_index`
`scale_factor`
`adder`
`ndim`	Number of array dimensions.
`size`	Number of elements in the array.

get_array(needs_lock=True)[source]

Get array of data for variable

Parameters:: needs_lock (bool, optional) – Flag indicating wether a lock should be acquired before reading the data array (e.g. if a write operation is necessary). By default, True.
Returns:: array-like – Array of data. Could be lazy-loaded like an h5py.Dataset instance.

property ndim: int: Number of array dimensions.

See also

numpy.ndarray.ndim

property size: int

Number of elements in the array.

Equal to np.prod(a.shape), i.e., the product of the array’s dimensions.