pasteur.table.SeqTransformerWrapper

class pasteur.table.SeqTransformerWrapper(modules, parent=None, seq=None, ctx=None, seq_col=None, ctx_to_ref=None, order=None, max_len=None, first_seq_ref_itself=False, ref=None, **kwargs)

Attributes

deterministic	For a given output, the input is the same.
lossless	The decoded output equals the input.
name
stateful	Transformer fits variables.
mode

Methods

fit(table, data, ref, ids[, seq_val, seq])	Fits to the provided data
fit_transform(table, data[, ref, ids, ...])
get_attributes()
get_factory(*args, **kwargs)	Returns a factory that registers this module to the system.
get_seq_value()
reduce(other)
reverse(data, ctx, ref, ids)	When reversing, the data column contains encoded data, whereas the ref column contains decoded/original data.
transform(data, ref, ids[, seq])

deterministic = True

For a given output, the input is the same.

fit(table, data, ref, ids, seq_val=None, seq=None)

Fits to the provided data

Return type:

tuple[SeqValue, Series] | None

fit_transform(table, data, ref=None, ids=None, seq_val=None, seq=None)

Return type:

tuple[DataFrame, dict[str, DataFrame]] | tuple[DataFrame, dict[str, DataFrame], Series]

get_attributes()

Return type:

tuple[Mapping[str | tuple[str, ...], Attribute], dict[str, Mapping[str | tuple[str, ...], Attribute]]]

classmethod get_factory(*args, **kwargs)

Returns a factory that registers this module to the system.

Any *args and **kwargs passed to this function will be saved and passed to the module’s __init__() method when calling build().

get_seq_value()

Return type:

SeqValue | None

lossless = True

The decoded output equals the input.

mode: Literal['dual', 'single', 'notrn']

name: str = 'seq'

reduce(other)

reverse(data, ctx, ref, ids)

When reversing, the data column contains encoded data, whereas the ref column contains decoded/original data. Therefore, the referred columns have to be decoded first.

Return type:

DataFrame

stateful = False

Transformer fits variables.

transform(data, ref, ids, seq=None)

Return type:

tuple[DataFrame, dict[str, DataFrame]] | tuple[DataFrame, dict[str, DataFrame], Series]