pept.tracking.SplitLabels

class pept.tracking.SplitLabels(remove_labels=True, extract_lines=False, noise=False)

Bases: pept.base.pipelines.Filter

Split a sample of data into unique label values, optionally removing noise and extracting _lines attributes.

Filter signature:

# `extract_lines` = False (default)
LineData -> SplitLabels.fit_sample -> list[LineData]
PointData -> SplitLabels.fit_sample -> list[PointData]

# `extract_lines` = True and PointData.lines exists
PointData -> SplitLabels.fit_sample -> list[LineData]

The sample of data must have a column named exactly “label”. The filter normally removes the “label” column in the output (if remove_label = True).

__init__(remove_labels=True, extract_lines=False, noise=False)

Methods

__init__([remove_labels, extract_lines, noise])
copy([deep])	Create a deep copy of an instance of this class, including all inner attributes.
fit(samples[, executor, max_workers, verbose])	Apply self.fit_sample (implemented by subclasses) according to the execution policy.
fit_sample(sample)
load(filepath)	Load a saved / pickled PEPTObject object from filepath.
save(filepath)	Save a PEPTObject instance as a binary pickle object.

fit_sample(sample: pept.base.iterable_samples.IterableSamples)

copy(deep=True)

Create a deep copy of an instance of this class, including all inner attributes.

fit(samples: collections.abc.Iterable, executor='joblib', max_workers=None, verbose=True)

Apply self.fit_sample (implemented by subclasses) according to the execution policy. Simply return a list of processed samples. If you need a reduction step (e.g. stack all processed samples), apply it in the subclass.

static load(filepath)

Load a saved / pickled PEPTObject object from filepath.

Most often the full object state was saved using the .save method.

Parameters

filepathfilename or file handle

If filepath is a path (rather than file handle), it is relative to where python is called.

Returns

pept.PEPTObject subclass instance

The loaded object.

Examples

Save a LineData instance, then load it back:

>>> lines = pept.LineData([[1, 2, 3, 4, 5, 6, 7]])
>>> lines.save("lines.pickle")

>>> lines_reloaded = pept.LineData.load("lines.pickle")

save(filepath)

Save a PEPTObject instance as a binary pickle object.

Saves the full object state, including inner attributes, in a portable binary format. Load back the object using the load method.

Parameters

filepathfilename or file handle

If filepath is a path (rather than file handle), it is relative to where python is called.

Examples

Save a LineData instance, then load it back:

>>> lines = pept.LineData([[1, 2, 3, 4, 5, 6, 7]])
>>> lines.save("lines.pickle")

>>> lines_reloaded = pept.LineData.load("lines.pickle")

pept.tracking.Stack pept.tracking.SplitAll