launch_live¶
Module: run.launch_live¶
Script for running pyspace live controlling
 
A script for running pyspace live. The script contains a class to control the other related classes needed in the online mode, and several methods that are used for the general startup of the suite.
Inheritance diagram for pySPACE.run.launch_live:
 
Class Summary¶
| LiveController(parameters_[, live_processing]) | Controlling suite. | 
Function Summary¶
| parse_arguments() | Parses the command line arguments to create options object | 
| read_parameter_file(parameter_file_name) | Reads and interprets the given parameter file | 
| create_and_start_rpc_server(controller_instance) | Creates and starts the server for the remote procedure calls | 
| create_backup(liveControl, options) | Create backup files | 
Class¶
LiveController¶
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class pySPACE.run.launch_live.LiveController(parameters_, live_processing=None)[source]¶
- Bases: - object- Controlling suite. - This class provides a clean interface to the live environment. It provides contains objects of the classes that are used for the online mode and configures them as needed. - The controller uses the config-files for user related configuration, and additional parameter files for scenario/task specific parameterization. - Class Components Summary - adapt_classification_threshold([load_model])- Adapts classification threshold on a special function - convert_dict_to_defaultdict(dict_to_convert)- predict([load_model, online, remote])- Classifies new instances based on the trained pyspace flows - prewindowed_train()- Trains the pyspace flows which have been prewindowed using the prewindower - prewindowing([online])- Prewindows the pyspace flows on the data streamed from - record()- start_prewindowing([online])- Start the prewindowing process - stop_prediction()- stop_prewindowing()- Create pyspace live processing server - train()- Trains the pyspace flows on the data streamed from - 
prewindowing(online=True)[source]¶
- Prewindows the pyspace flows on the data streamed from an external EEG-Server 
 - 
prewindowed_train()[source]¶
- Trains the pyspace flows which have been prewindowed using the prewindower 
 - 
adapt_classification_threshold(load_model=True)[source]¶
- Adapts classification threshold on a special function 
 - 
predict(load_model=True, online=True, remote=False)[source]¶
- Classifies new instances based on the trained pyspace flows 
 - 
__weakref__¶
- list of weak references to the object (if defined) 
 
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