pept.tracking.SplitLabels#

class pept.tracking.SplitLabels(remove_labels=True, extract_lines=False, noise=False)[source]#

Bases: 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.attrs["_lines"] exists
PointData -> SplitLabels.fit_sample -> list[LineData]

The sample of data must have a column named exactly “label”. If remove_label = True (default), the “label” column is removed.

__init__(remove_labels=True, extract_lines=False, noise=False)[source]#

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: IterableSamples)[source]#

copy(deep=True)#: Create a deep copy of an instance of this class, including all inner attributes.

fit(samples, 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")