landlab.data_record.aggregators

aggregate_items_as_count(ids, size=None)[source]

Count the number of time an id appears in an array.

Parameters:

  • ids (array_like of int) – An array of ids.

  • size (int, optional) – The size of the output array. This is useful if the ids array doesn’t contain all possible ids.

Returns:

The number of times each id appears.

Return type:

ndarray of int

Examples

>>> from landlab.data_record.aggregators import aggregate_items_as_count
>>> aggregate_items_as_count([1, 2, 3, 3, 1, 5])
array([0, 2, 1, 2, 0, 1])
>>> aggregate_items_as_count([1, 2, 3, 3, 1, 5], size=8)
array([0, 2, 1, 2, 0, 1, 0, 0])

Negative ids are ignored.

>>> aggregate_items_as_count([1, 2, 3, 3, -1, 5])
array([0, 1, 1, 2, 0, 1])
aggregate_items_as_mean(ids, values, weights=None, size=None)[source]

Find the mean of values associated with an id.

Parameters:

  • ids (array_like of int) – An array of ids.

  • values (array_like) – The value associated with the corresponding id in the id array.

  • size (int, optional) – The size of the output array. This is useful if the ids array doesn’t contain all possible ids.

  • weights (Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes] | None)

Returns:

The mean of the values at each id.

Return type:

ndarray of int

Examples

>>> from landlab.data_record.aggregators import aggregate_items_as_mean
>>> aggregate_items_as_mean([0, 0, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5])
array([1.5, 3. , 0. , 3. , 1. , 5. ])
>>> aggregate_items_as_mean([0, 0, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5], size=8)
array([1.5, 3. , 0. , 3. , 1. , 5. , 0. , 0. ])

Negative ids are ignored.

>>> aggregate_items_as_mean([0, -1, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5])
array([1., 3., 0., 3., 1., 5.])
aggregate_items_as_sum(ids, values, size=None)[source]

Find the sum of values associated with an id.

Parameters:

  • ids (array_like of int) – An array of ids.

  • values (array_like) – The value associated with the corresponding id in the id array.

  • size (int, optional) – The size of the output array. This is useful if the ids array doesn’t contain all possible ids.

Returns:

The sum of the values at each id.

Return type:

ndarray of int

Examples

>>> from landlab.data_record.aggregators import aggregate_items_as_sum
>>> aggregate_items_as_sum([0, 0, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5])
array([3., 3., 0., 3., 1., 5.])
>>> aggregate_items_as_sum([0, 0, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5], size=8)
array([3., 3., 0., 3., 1., 5., 0., 0.])

Negative ids are ignored.

>>> aggregate_items_as_sum([0, -1, 1, 3, 4, 5], [1, 2, 3, 3, 1, 5])
array([1., 3., 0., 3., 1., 5.])