cf.RaggedContiguousArray

---

class cf.RaggedContiguousArray(compressed_array=None, shape=None, size=None, ndim=None, count_variable=None, source=None, copy=True)

Bases: cf.data.array.mixin.raggedarraymixin.RaggedArrayMixin, cf.data.array.mixin.arraymixin.ArrayMixin, cf.mixin_container.Container, cfdm.data.raggedcontiguousarray.RaggedContiguousArray

An underlying contiguous ragged array.

A collection of features stored using a contiguous ragged array combines all features along a single dimension (the “sample dimension”) such that each feature in the collection occupies a contiguous block.

The information needed to uncompress the data is stored in a “count variable” that gives the size of each block.

It is assumed that the compressed dimension is the left-most dimension in the compressed array.

See CF section 9 “Discrete Sampling Geometries”.

New in version 3.0.0.

Initialisation

Parameters

compressed_array: array_like

The compressed data.

shape: tuple

The shape of the uncompressed array.

count_variable: Count

The count variable required to uncompress the data, corresponding to a CF-netCDF count variable.

source: optional

Convert source, which can be any type of object, to a RaggedContiguousArray instance.

All other parameters, apart from copy, are ignored and their values are instead inferred from source by assuming that it has the RaggedContiguousArray API. Any parameters that can not be retrieved from source in this way are assumed to have their default value.

Note that if x is also a RaggedContiguousArray instance then cf.RaggedContiguousArray(source=x) is equivalent to x.copy().

New in version (cfdm): 1.10.0.0

copy: bool, optional

If True (the default) then deep copy the input parameters prior to initialisation. By default the parameters are not deep copied.

New in version (cfdm): 1.10.0.0

size: int

Deprecated at version 1.10.0.0. Ignored if set.

Number of elements in the uncompressed array.

ndim: int

Deprecated at version 1.10.0.0. Ignored if set.

The number of uncompressed array dimensions.

Methods

compressed_dimensions	Mapping of compressed to uncompressed dimensions.
conformed_data	The data as required by the decompression algorithm.
copy	Return a deep copy of the array.
get_calendar	The calendar of the array.
get_compressed_axes	Return axes that are compressed in the underlying array.
get_compressed_dimension	Returns the compressed dimension’s position in the array.
get_compression_type	Returns the array’s compression type.
get_count	Return the count variable for the compressed array.
cf.RaggedContiguousArray.get_filename'
get_filenames	Return the names of any files containing the compressed data.
get_index	Return the index variable for the compressed array.
get_Subarray	Return the Subarray class.
get_subspace	Return a subspace, defined by indices, of a numpy array.
get_units	The units of the array.
source	Return the underlying array object.
subarray_shapes	Create the subarray shapes along each uncompressed dimension.
subarrays	Return descriptors for every subarray.
to_dask_array	Convert the data to a dask array.
to_memory	Bring data on disk into memory.

Attributes

array	Returns a numpy array containing the uncompressed data.
compressed_array	Returns an independent numpy array with the compressed data.
dtype	Data-type of the uncompressed data.
ndim	Number of array dimensions.
shape	Shape of the uncompressed data.
size	Number of elements in the array.
Units	The cf.Units object containing the units of the array.