# cf.GatheredArray¶

class cf.GatheredArray(compressed_array=None, shape=None, size=None, ndim=None, compressed_dimension=None, list_variable=None)[source]

Bases: cf.data.abstract.compressedarray.CompressedArray, cfdm.data.gatheredarray.GatheredArray

An underlying gathered array.

Compression by gathering combines axes of a multidimensional array into a new, discrete axis whilst omitting the missing values and thus reducing the number of values that need to be stored.

The information needed to uncompress the data is stored in a “list variable” that gives the indices of the required points.

New in version 3.0.0.

Initialization

Parameters: compressed_array: Data The compressed array. shape: tuple The uncompressed array dimension sizes. size: int Number of elements in the uncompressed array. ndim: int The number of uncompressed array dimensions compressed_dimension: int The position of the compressed dimension in the compressed array. list_variable: List The “list variable” required to uncompress the data, identical to the data of a CF-netCDF list variable.

## Inspection¶

Methods

 get_compressed_axes Return axes that are compressed in the underlying array. get_compressed_dimension Return the position of the compressed dimension in the compressed array. get_compression_type The type of compression that has been applied to the underlying array. get_list Return the list variable for a compressed array. get_subspace Return a subspace, defined by indices, of a numpy array. source TODO Return the underlying array object.

Attributes

 array Return an independent numpy array containing the uncompressed data. compressed_array Return an independent numpy array containing the compressed data. dtype Data-type of the data elements. ndim The number of dimensions of the uncompressed data. shape Shape of the uncompressed data. size Number of elements in the uncompressed data.

## Miscellaneous¶

Methods

 copy Return a deep copy of the array. get_subspace Return a subspace, defined by indices, of a numpy array. to_memory TODO