elphick.mass_composition.mc_xarray.MassCompositionAccessor

class elphick.mass_composition.mc_xarray.MassCompositionAccessor(xarray_obj)[source]

__init__(xarray_obj)[source]

MassComposition xarray Accessor

Parameters:: xarray_obj (Dataset) –

Methods

`__init__`(xarray_obj)	MassComposition xarray Accessor
`add`(other)	Add two objects
`aggregate`([group_var, group_bins, ...])	Calculate the weight average of this dataset.
`column_map`()
`composition_to_mass`()	Transform composition to mass
`cumulate`(direction)	Cumulate along the dims
`data`()
`div`(other)	Divide self by the supplied object
`mass_to_composition`()	Transform mass to composition.
`mul`(value)	Multiply self and retain attrs
`rename`(new_name)
`split`(fraction)	Split the object by mass
`split_by_partition`(partition_definition)	Partition the object along a given dimension.
`sub`(other)	Subtract the supplied object from self
`to_dataframe`([original_column_names, ds])	rtype: `DataFrame`

Attributes

`composition_context`
`name`

add(other)[source]

Add two objects

Perform the addition with the mass-composition variables only and then append any attribute variables.

Parameters:: other (Dataset) – object to add to self
Return type:: Dataset

Returns:

aggregate(group_var=None, group_bins=None, as_dataframe=False, original_column_names=False, column_formats=None)[source]

Calculate the weight average of this dataset.

Parameters:

group_var (Optional[str]) – Optional grouping variable
group_bins (Union[int, Iterable, None]) – Optional bins to apply to the group_var
as_dataframe (bool) – If True return a pd.DataFrame
original_column_names (bool) – If True, and as_dataframe is True, will return with the original column names.
column_formats (Optional[Dict]) – If not None, and as_dataframe is True, will format the dataframe per the dict.

Return type:

Union[Dataset, DataFrame]

Returns:

composition_to_mass()[source]

Transform composition to mass

Return type:: Dataset
Returns:

cumulate(direction)[source]

Cumulate along the dims

Expected use case is only for Datasets that have been reduced to 1D.

Parameters:: direction (str) – ‘ascending’|’descending’
Return type:: Dataset

Returns:

div(other)[source]

Divide self by the supplied object

Perform the division with the mass-composition variables only and then append any attribute variables. :type other: Dataset :param other: denominator object, self will be divided by this object

Returns:

Return type:: Dataset

mass_to_composition()[source]

Transform mass to composition.

Return type:: Dataset
Returns:

mul(value)[source]

Multiply self and retain attrs

Multiply the mass-composition variables only by the value then append any attribute variables. NOTE: does not multiply two objects together. Used for separation (partition) operations.

Parameters:: value (Union[float, ndarray]) – the multiplier, a scalr or array of floats.
Return type:: Dataset

Returns:

split(fraction)[source]

Split the object by mass

A simple mass split maintaining the same composition

Parameters:: fraction (float) – A constant in the range [0.0, 1.0]
Return type:: Tuple[Dataset, Dataset]
Returns:: tuple of two datasets, the first with the mass fraction specified, the other the complement

split_by_partition(partition_definition)[source]

Partition the object along a given dimension.

This method applies the defined partition resulting in two new objects.