taucmdr.model.experiment module¶

Experiment data model.

An Experiment uniquely groups a Target, Application, and Measurement and will have zero or more Trial. There is one selected experiment per project. The selected experiment will be used for application compilation and trial visualization.

class taucmdr.model.experiment.Experiment(record)[source]¶

Bases: taucmdr.mvc.model.Model

Experiment data model.

associations = {'project': (<class 'taucmdr.model.project.Project'>, 'experiments'), 'trials': (<class 'taucmdr.model.trial.Trial'>, 'experiment')}¶

attributes = {'application': {'argparse': {'flags': ('--application',), 'metavar': '<name>'}, 'description': 'Application this experiment uses', 'model': <class 'taucmdr.model.application.Application'>, 'required': True}, 'measurement': {'argparse': {'flags': ('--measurement',), 'metavar': '<name>'}, 'description': 'Measurement parameters for this experiment', 'model': <class 'taucmdr.model.measurement.Measurement'>, 'required': True}, 'name': {'description': 'human-readable experiment name', 'primary_key': True, 'type': 'string', 'unique': True}, 'project': {'description': 'Project this experiment belongs to', 'model': <class 'taucmdr.model.project.Project'>, 'required': True, 'unique': True}, 'record_output': {'argparse': {'flags': ('--record-output',)}, 'default': False, 'description': 'Record application stdout', 'type': 'boolean'}, 'target': {'argparse': {'flags': ('--target',), 'metavar': '<name>'}, 'description': "The experiment's hardware/software configuration", 'model': <class 'taucmdr.model.target.Target'>, 'required': True}, 'tau_makefile': {'description': 'TAU Makefile used during this experiment, if any.', 'type': 'string'}, 'trials': {'collection': <class 'taucmdr.model.trial.Trial'>, 'description': 'Trials of this experiment', 'via': 'experiment'}}¶

configure()[source]¶

Sets up the Experiment for a new trial.

Installs or configures TAU and all its dependencies. After calling this function, the experiment is ready to operate on the user’s application.

Returns:	Object handle for the TAU installation.
Return type:	TauInstallation

classmethod controller(storage=<taucmdr.cf.storage.storage_dispatch.ProjectStorageDispatch object>)[source]¶

data_size()[source]¶

key_attribute = 'name'¶

managed_build(compiler_cmd, compiler_args)[source]¶

Uses this experiment to perform a build operation.

Checks that this experiment is compatible with the desired build operation, prepares the experiment, and performs the operation.

Parameters:	compiler_cmd (str) – The compiler command intercepted by TAU Commander. compiler_args (list) – Compiler command line arguments intercepted by TAU Commander.
Raises:	ConfigurationError – The experiment is not configured to perform the desired build.
Returns:	Build subprocess return code.
Return type:	int

managed_rewrite(rewrite_package, executable, inst_file)[source]¶

managed_run(launcher_cmd, application_cmds, description=None)[source]¶

Uses this experiment to run an application command.

Performs all relevant system preparation tasks to run the user’s application under the specified experimental configuration.

Parameters:	launcher_cmd (list) – Application launcher with command line arguments. application_cmds (list) – List of application executables with command line arguments (list of lists). description (str) – If not None, a description of the run.
Raises:	ConfigurationError – The experiment is not configured to perform the desired run.
Returns:	Application subprocess return code.
Return type:	int

name = 'Experiment'¶

next_trial_number()[source]¶

on_create()[source]¶

Callback to be invoked after a new data record is created.

on_delete()[source]¶

Callback to be invoked before a data record is deleted.

prefix¶

classmethod rebuild_required()[source]¶

Builds a string indicating if an application rebuild is required.

Rebuild information is taken from the ‘rebuild_required’ topic.

Returns:	String indicating why an application rebuild is required.
Return type:	str

references = {(<class 'taucmdr.model.trial.Trial'>, 'experiment'), (<class 'taucmdr.model.project.Project'>, 'experiment')}¶

classmethod select(name)[source]¶

Changes the selected experiment in the current project.

Raises:	ExperimentSelectionError – No experiment with the given name in the currently selected project.
Parameters:	name (str) – Name of the experiment to select.

trials(trial_numbers=None)[source]¶

Get a list of modeled trial records.

If bool(trial_numbers) is False, return the most recent trial. Otherwise return a list of Trial objects for the given trial numbers.

Parameters:	trial_numbers (list) – List of numbers of trials to retrieve.
Returns:	Modeled trial records.
Return type:	list
Raises:	ConfigurationError – Invalid trial number or no trials in selected experiment.

verify()[source]¶

Checks all components of the experiment for mutual compatibility.

class taucmdr.model.experiment.ExperimentController(model_cls, storage, context=None)[source]¶

Bases: taucmdr.mvc.controller.Controller

Experiment data controller.

_check_unique(data, match_any=False)[source]¶

Default match_any to False to prevent matches outside the selected project.

all(context=True)[source]¶

count()[source]¶

Return the number of records.

Returns:	Effectively len(self.all())
Return type:	int

create(data)[source]¶

Atomically store a new record and update associations.

Invokes the on_create callback after the data is recorded. If this callback raises an exception then the operation is reverted.

Parameters:	data (dict) – Data to record.
Returns:	The newly created data.
Return type:	Model

delete(keys)[source]¶

Delete recorded data and update associations.

The behavior depends on the type of keys:

• Record.ElementIdentifier: delete the record with that element identifier.
• dict: delete all records with attributes matching keys.
• list or tuple: delete all records matching the elements of keys.
• bool(keys) == False: raise ValueError.

Invokes the on_delete callback after the data is deleted. If this callback raises an exception then the operation is reverted.

Parameters:	keys (dict) – Attributes to match. keys – Fields or element identifiers to match.

exists(keys)[source]¶

Check if a record exists.

Parameters:	keys – See AbstractStorage.exists.
Returns:	True if a record matching keys exists, False otherwise.
Return type:	bool

one(keys, context=True)[source]¶

search(keys=None, context=True)[source]¶

unset(fields, keys)[source]¶

Unset recorded data fields and update associations.

The behavior depends on the type of keys:

• Record.ElementIdentifier: update the record with that element identifier.
• dict: update all records with attributes matching keys.
• list or tuple: apply update to all records matching the elements of keys.
• bool(keys) == False: raise ValueError.

Invokes the on_update callback after the data is modified. If this callback raises an exception then the operation is reverted.

Parameters:	fields (list) – Names of fields to unset. keys – Fields or element identifiers to match.

update(data, keys)[source]¶

Change recorded data and update associations.

The behavior depends on the type of keys:

• Record.ElementIdentifier: update the record with that element identifier.
• dict: update all records with attributes matching keys.
• list or tuple: apply update to all records matching the elements of keys.
• bool(keys) == False: raise ValueError.

Invokes the on_update callback after the data is modified. If this callback raises an exception then the operation is reverted.

Parameters:	data (dict) – New data for existing records. keys – Fields or element identifiers to match.

taucmdr.model.experiment.attributes()[source]¶