homology.PersDiag

class homology.PersDiag(birth_index, death_index, birth_value, death_value, mergetree)

Persistence Diagrams and related merge-tree information. Sometimes known as barcodes.

A PersDiag consists of a pandas.DataFrame of birth and death values (sorted by length), along with the tree and forest for range and domain inclusion.

You should not call this directly — instead use the constructor on your homology.SimplicialComplex or ‘timeseries.Signal` object.

The input parameters are of the form that comes from persistence.dim0.unionfind or similar

Parameters:

birth_index : list_like

death_index : list_like

birth_value : list_like

death_value : list_like

mergetree : dict

See also

homology.dim0.unionfind()

Notes

Users should never call this directly — instead use the constructor on your homology.SimplicialComplex or timeseries.Signal object.

Attributes:

diagram : pandas.DataFrame

A DataFrame showing all of the birth/death information. It has columns birth_index, death_index, birth, death, and pers

lefts : pandas.Series

rights : pandas.Series

domains : dict

bartree : dict

bartree_parents : dict

forest : dict

forest_parents : dict

mergetree : dict

PersDiag.bin(width[, underflow, overflow, …])	Count bins on the transformed persistence diagram.
PersDiag.bin_bot(width[, underflow, overflow])
PersDiag.bin_diag(width[, underflow, overflow])
PersDiag.bin_len(width[, underflow, overflow])
PersDiag.bin_top(width[, underflow, overflow])
PersDiag.clip(beta)	clip the barcode below beta.
PersDiag.grab(n)	clip the barcode, using only the top n entries.
PersDiag.plot(canvas[, transform, bins, title])	Plot the persistence diagram using matplotlib or bokeh.
PersDiag.syzygy(powers)	compute the syzygy coordinate of my barcode.
PersDiag.transform([transform, points])	Produce an array of points, obtained by transforming the persistence diagram.