HereditaryStratigraphicAssemblageSpecimen
- class HereditaryStratigraphicAssemblageSpecimen
Postprocessing representation of the differentia retained by an extant HereditaryStratigraphicColumn, indexed by deposition rank.
Differentia are stored using a nullable integer representation, which allows for inclusion of entries for all ranks retained by any specimen within the assemblage, even if that particualr rank is not retained by this specimen. This allows for more efficient comparisons between specimens, due to direct alignment.
See Also
- HereditaryStratigraphicSpecimen
Specimen representation that can contain only ranks retained by that specimen.
- HereditaryStratigraphicAssemblage
Gathers a collection of `HereditaryStratigraphicSpecimen`s and facilitates creation of corresponding aligned `HereditaryStratigraphicAssemblageSpecimen`s.
- __init__(stratum_differentia_series: Series[DataType(UInt64)], stratum_differentia_bit_width: int) None[source]
Initialize a HereditaryStratigraphicAssemblageSpecimen object with a (potentially sparse) sequence of rank-indexed differentia and a differentia bit width.
Methods
- GetData() Series[DataType(UInt64)][source]
Get the underlying Pandas Series containing differentia values indexed by rank.
Notes
This function directly returns the specimen’s underlying Series data, so mutation of the returned object will alter or invalidate this specimen.
- GetDifferentiaVals() ndarray[source]
Get the integer underlying values in the stored Pandas NullableInteger Series.
Returns
- differentianp.ndarray
A 1-dimensional NumPy integer ndarray containing differentia values, including garbage values where the underlying Series is null.
Notes
This function returns a direct view into the Series data, so no copy is made. Changes to the returned array will propagate to the Series object’s underlying values, and vice versa.
- GetNumDiscardedStrata() int[source]
How many deposited strata have been discarded?
Determined by number of generations elapsed and the configured column retention policy.
- GetNumStrataDeposited() int[source]
How many strata have been depostited on the column?
Note that a first stratum is deposited on the column during initialization.
- GetNumStrataRetained() int[source]
How many strata are currently stored within the column?
May be fewer than the number of strata deposited if strata have been discarded as part of the configured stratum retention policy.
- GetRankAtColumnIndex(index: int) int[source]
Map array position to generation of deposition.
What is the deposition rank of the stratum positioned at index i among retained strata? Index order is from most ancient (index 0) to most recent.
- GetRankIndex() ndarray[source]
Get the integer index in the stored Pandas Series, representing the ranks of stratum entries.
Returns
- ranksnp.ndarray
A numpy array containing ranks of differentia entries, including null entries for differentia that are not retained.
- GetStratumMask() ndarray[source]
Get a boolean mask indicating which entries in the stored Pandas NullableInteger Series are null.
I.e., which ranks does this specimen not retain differentia at?
Returns
- masknp.ndarray
A 1-dimensional boolean NumPy ndarray.
True values indicate nullness.
Notes
This function returns the underlying boolean mask used by the stored Pandas Series object to represent null values. This mask is a direct view into the Series data, so no copy is made. Changes to the mask will propagate to the store Series object, and vice versa.
- IterRankDifferentiaZip(copyable: bool = False) Iterator[Tuple[int, int]][source]
Iterate over ranks of retained strata and their differentia.
If copyable, return an iterator that can be copied to produce a new fully-independent iterator at the same position.
Equivalent to zip(specimen.IterRetainedRanks(), specimen.IterRetainedDifferentia()), but may be more efficient.
- IterRetainedDifferentia() Iterator[int][source]
Iterate over differentia of strata retained in the specimen.
Differentia yielded from most ancient to most recent.