sierra.core.pipeline.stage4.intra_exp_graph_generator

Classes for generating graphs within a single Experiment.

• BatchIntraExpGraphGenerator: Undocumented.

• IntraExpGraphGenerator: Generates graphs from Averaged .csv files for a single experiment.

• LinegraphsGenerator: Generates linegraphs from Averaged .csv files within an experiment.

• HeatmapsGenerator: Generates heatmaps from Averaged .csv files for a single experiment.

class sierra.core.pipeline.stage4.intra_exp_graph_generator.BatchIntraExpGraphGenerator(cmdopts: Dict[str, Any])

Inheritance

__call__(main_config: Dict[str, Any], controller_config: Dict[str, Any], LN_config: Dict[str, Any], HM_config: Dict[str, Any], criteria: IConcreteBatchCriteria) → None

Generate all intra-experiment graphs for a Batch Experiment.

Parameters:

• main_config – Parsed dictionary of main YAML configuration

• controller_config – Parsed dictionary of controller YAML configuration.

• LN_config – Parsed dictionary of intra-experiment linegraph configuration.

• HM_config – Parsed dictionary of intra-experiment heatmap configuration.

• criteria – The Batch Criteria used for the batch experiment.

__dict__ = mappingproxy({'__module__': 'sierra.core.pipeline.stage4.intra_exp_graph_generator', '__init__': <function BatchIntraExpGraphGenerator.__init__>, '__call__': <function BatchIntraExpGraphGenerator.__call__>, '__dict__': <attribute '__dict__' of 'BatchIntraExpGraphGenerator' objects>, '__weakref__': <attribute '__weakref__' of 'BatchIntraExpGraphGenerator' objects>, '__doc__': None, '__annotations__': {}})

__doc__ = None

__init__(cmdopts: Dict[str, Any]) → None

__module__ = 'sierra.core.pipeline.stage4.intra_exp_graph_generator'

__weakref__

list of weak references to the object (if defined)

class sierra.core.pipeline.stage4.intra_exp_graph_generator.IntraExpGraphGenerator(main_config: Dict[str, Any], controller_config: Dict[str, Any], LN_config: Dict[str, Any], HM_config: Dict[str, Any], cmdopts: Dict[str, Any])

Generates graphs from Averaged .csv files for a single experiment.

Which graphs are generated is controlled by YAML configuration files parsed in PipelineStage4.

This class can be extended/overriden using a Project hook. See SIERRA Hooks for details.

cmdopts

Dictionary of parsed cmdline attributes.

main_config

Parsed dictionary of main YAML configuration

controller_config

Parsed dictionary of controller YAML configuration.

LN_config

Parsed dictionary of intra-experiment linegraph configuration.

HM_config

Parsed dictionary of intra-experiment heatmap configuration.

criteria

The Batch Criteria used for the batch experiment.

logger

The handle to the logger for this class. If you extend this class, you should save/restore this variable in tandem with overriding it in order to get logging messages have unique logger names between this class and your derived class, in order to reduce confusion.

Inheritance

__call__(criteria: IConcreteBatchCriteria) → None

Generate graphs.

Performs the following steps:

# . LinegraphsGenerator

to generate linegraphs for each experiment in the batch.

# . HeatmapsGenerator

to generate heatmaps for each experiment in the batch.

__dict__ = mappingproxy({'__module__': 'sierra.core.pipeline.stage4.intra_exp_graph_generator', '__doc__': 'Generates graphs from :term:`Averaged .csv` files for a single experiment.\n\n    Which graphs are generated is controlled by YAML configuration files parsed\n    in :class:`~sierra.core.pipeline.stage4.pipeline_stage4.PipelineStage4`.\n\n    This class can be extended/overriden using a :term:`Project` hook. See\n    :ref:`ln-sierra-tutorials-project-hooks` for details.\n\n    Attributes:\n\n        cmdopts: Dictionary of parsed cmdline attributes.\n\n        main_config: Parsed dictionary of main YAML configuration\n\n        controller_config: Parsed dictionary of controller YAML\n                           configuration.\n\n        LN_config: Parsed dictionary of intra-experiment linegraph\n                   configuration.\n\n        HM_config: Parsed dictionary of intra-experiment heatmap\n                   configuration.\n\n        criteria:  The :term:`Batch Criteria` used for the batch\n                   experiment.\n\n        logger: The handle to the logger for this class. If you extend this\n               class, you should save/restore this variable in tandem with\n               overriding it in order to get logging messages have unique logger\n               names between this class and your derived class, in order to\n               reduce confusion.\n\n    ', '__init__': <function IntraExpGraphGenerator.__init__>, '__call__': <function IntraExpGraphGenerator.__call__>, 'generate': <function IntraExpGraphGenerator.generate>, 'calc_targets': <function IntraExpGraphGenerator.calc_targets>, '__dict__': <attribute '__dict__' of 'IntraExpGraphGenerator' objects>, '__weakref__': <attribute '__weakref__' of 'IntraExpGraphGenerator' objects>, '__annotations__': {}})

__doc__ = 'Generates graphs from :term:`Averaged .csv` files for a single experiment.\n\n    Which graphs are generated is controlled by YAML configuration files parsed\n    in :class:`~sierra.core.pipeline.stage4.pipeline_stage4.PipelineStage4`.\n\n    This class can be extended/overriden using a :term:`Project` hook. See\n    :ref:`ln-sierra-tutorials-project-hooks` for details.\n\n    Attributes:\n\n        cmdopts: Dictionary of parsed cmdline attributes.\n\n        main_config: Parsed dictionary of main YAML configuration\n\n        controller_config: Parsed dictionary of controller YAML\n                           configuration.\n\n        LN_config: Parsed dictionary of intra-experiment linegraph\n                   configuration.\n\n        HM_config: Parsed dictionary of intra-experiment heatmap\n                   configuration.\n\n        criteria:  The :term:`Batch Criteria` used for the batch\n                   experiment.\n\n        logger: The handle to the logger for this class. If you extend this\n               class, you should save/restore this variable in tandem with\n               overriding it in order to get logging messages have unique logger\n               names between this class and your derived class, in order to\n               reduce confusion.\n\n    '

__init__(main_config: Dict[str, Any], controller_config: Dict[str, Any], LN_config: Dict[str, Any], HM_config: Dict[str, Any], cmdopts: Dict[str, Any]) → None

__module__ = 'sierra.core.pipeline.stage4.intra_exp_graph_generator'

__weakref__

list of weak references to the object (if defined)

calc_targets() → Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]

Calculate what intra-experiment graphs should be generated.

Uses YAML configuration for controller and intra-experiment graphs. Returns a tuple of dictionaries: (intra-experiment linegraphs, intra-experiment heatmaps) defined what graphs to generate. The enabled graphs exist in their YAML respective YAML configuration and are enabled by the YAML configuration for the selected controller.

generate(LN_targets: List[Dict[str, Any]], HM_targets: List[Dict[str, Any]])

class sierra.core.pipeline.stage4.intra_exp_graph_generator.LinegraphsGenerator(cmdopts: Dict[str, Any], targets: List[Dict[str, Any]])

Generates linegraphs from Averaged .csv files within an experiment.

Inheritance

__dict__ = mappingproxy({'__module__': 'sierra.core.pipeline.stage4.intra_exp_graph_generator', '__doc__': '\n    Generates linegraphs from :term:`Averaged .csv` files within an experiment.\n    ', '__init__': <function LinegraphsGenerator.__init__>, 'generate': <function LinegraphsGenerator.generate>, '__dict__': <attribute '__dict__' of 'LinegraphsGenerator' objects>, '__weakref__': <attribute '__weakref__' of 'LinegraphsGenerator' objects>, '__annotations__': {}})

__doc__ = '\n    Generates linegraphs from :term:`Averaged .csv` files within an experiment.\n    '

__init__(cmdopts: Dict[str, Any], targets: List[Dict[str, Any]]) → None

__module__ = 'sierra.core.pipeline.stage4.intra_exp_graph_generator'

__weakref__

list of weak references to the object (if defined)

generate() → None

class sierra.core.pipeline.stage4.intra_exp_graph_generator.HeatmapsGenerator(cmdopts: Dict[str, Any], targets: List[Dict[str, Any]])

Generates heatmaps from Averaged .csv files for a single experiment.

Inheritance

__dict__ = mappingproxy({'__module__': 'sierra.core.pipeline.stage4.intra_exp_graph_generator', '__doc__': '\n    Generates heatmaps from :term:`Averaged .csv` files for a single experiment.\n    ', '__init__': <function HeatmapsGenerator.__init__>, 'generate': <function HeatmapsGenerator.generate>, '__dict__': <attribute '__dict__' of 'HeatmapsGenerator' objects>, '__weakref__': <attribute '__weakref__' of 'HeatmapsGenerator' objects>, '__annotations__': {}})

__doc__ = '\n    Generates heatmaps from :term:`Averaged .csv` files for a single experiment.\n    '

__init__(cmdopts: Dict[str, Any], targets: List[Dict[str, Any]]) → None

__module__ = 'sierra.core.pipeline.stage4.intra_exp_graph_generator'

__weakref__

list of weak references to the object (if defined)

generate() → None