time_series_sink

Module: missions.nodes.sink.time_series_sink

Gather all time series objects that are passed through

Author:Jan Hendrik Metzen (jhm@informatik.uni-bremen.de)
Created:2008/11/28

Inheritance diagram for pySPACE.missions.nodes.sink.time_series_sink:

Inheritance diagram of pySPACE.missions.nodes.sink.time_series_sink

TimeSeriesSinkNode

class pySPACE.missions.nodes.sink.time_series_sink.TimeSeriesSinkNode(sort_string=None, merge=False, **kwargs)[source]

Bases: pySPACE.missions.nodes.base_node.BaseNode

Collect all time series objects in a collection

Parameters

sort_string:

A lambda function string that is passed to the TimeSeriesDataset and evaluated before the data is stored.

(optional, default: None)
max_num_stored_objects:
 

Number of maximal stored time series objects. Can be used if only a part of a dataset should be exported, e.g. for size purposes in debugging. Applies to train and test set separately.

(optional, default: numpy.inf)
merge:

Can be set to true if the use wants to get one timeseries containing the entier input data

(optional, default: False)

Exemplary Call

- 
    node: Time_Series_Sink
Author:

Jan Hendrik Metzen (jhm@informatik.uni-bremen.de)
Created:

2008/11/28
LastChange:

2011/04/13 Anett Seeland (anett.seeland@dfki.de)
POSSIBLE NODE NAMES:
 
  • TimeSeriesSinkNode
  • TimeSeriesSink
  • Time_Series_Sink
POSSIBLE INPUT TYPES:
 
  • TimeSeries

Class Components Summary

_get_train_set(use_test_data) Returns the data that can be used for training
_train(data, label)
get_result_dataset() Return the result
input_types
is_supervised() Returns whether this node requires supervised training
is_trainable() Returns whether this node is trainable.
merge_time_series(input_collection) Merges all timeseries of the input_collection to one big timeseries
process_current_split() Compute the results of this sink node for the current split of the data
reset() Reset the state of the object to the clean state it had after its
input_types = ['TimeSeries']
__init__(sort_string=None, merge=False, **kwargs)[source]
reset()[source]

Reset the state of the object to the clean state it had after its initialization

is_trainable()[source]

Returns whether this node is trainable.

_get_train_set(use_test_data)[source]

Returns the data that can be used for training

is_supervised()[source]

Returns whether this node requires supervised training

_train(data, label)[source]
process_current_split()[source]

Compute the results of this sink node for the current split of the data into train and test data

merge_time_series(input_collection)[source]

Merges all timeseries of the input_collection to one big timeseries

get_result_dataset()[source]

Return the result