pept.tracking.Stack

class pept.tracking.Stack(sample_size=None, overlap=None)

Bases: pept.base.pipelines.Reducer

Stack iterables - for example a list[pept.LineData] into a single pept.LineData, a list[list] into a flattened list.

Reducer signature:

list[LineData] -> Stack.fit -> LineData
list[PointData] -> Stack.fit -> PointData

list[list[Any]] -> Stack.fit -> list[Any]
list[numpy.ndarray] -> Stack.fit -> numpy.ndarray

other -> Stack.fit -> other

Can optionally set a given sample_size and overlap. This is useful when collecting a list of processed samples back into a single object.

__init__(sample_size=None, overlap=None)

Methods

__init__([sample_size, overlap])
copy([deep])	Create a deep copy of an instance of this class, including all inner attributes.
fit(samples)
load(filepath)	Load a saved / pickled PEPTObject object from filepath.
save(filepath)	Save a PEPTObject instance as a binary pickle object.

fit(samples: collections.abc.Iterable)

copy(deep=True)

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

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")

Tracking Algorithms (pept.tracking) pept.tracking.SplitLabels