pycotools3.tasks.Reports

class pycotools3.tasks.Reports(model, **kwargs)

Creates reports in copasi output specification section. Which report is controlled by the report_type key word. The following are valid types of report:

Report Types	Description
time_course	Report definition for collection of time course data.
parameter_estimation	Collect parameter estimates from parameter estimations run from the parameter estimation task
multi_parameter_estimation	Collect parameter estimation data from parameter estimations run from the scan task with copasi’s repeat feature
profile_likelihood	Collect both the parameter being scanned value and the parameter estimates

Here are the keyword arguments accepted by the Reports class.

Args:

Returns:

__init__(model, **kwargs)

A class for configuring reports :param model: Model to add report configuration to :type model: model.Model :param **kwargs: Arguments for report

Methods

__init__(model, **kwargs)	A class for configuring reports :param model: Model to add report configuration to :type model: model.Model :param **kwargs: Arguments for report
check_integrity(allowed, given)	Method to raise an error when a wrong kwarg is passed to a subclass
clear_all_reports()	Having multile reports defined at once can be really annoying and give you unexpected results.
convert_bool_to_numeric(dct)	CopasiML uses 1’s and 0’s for True or False in some but not all places.
convert_bool_to_numeric2()	CopasiML uses 1’s and 0’s for True or False in some but not all places.
get_component(model, component, string)	Get component called string from model
get_variable_from_string(m, v[, glob])	Use model entity name to get the pycotools3 variable
multi_parameter_estimation()	Define a parameter estimation report and include the progression of the parameter estimation (function evaluations).
parameter_estimation()	Define a parameter estimation report and include the progression of the parameter estimation (function evaluations).
profile_likelihood()	Create report of a parameter and best value for a parameter estimation for profile likelihoods
read_model(m)	param m:
remove_report(report_name)	remove report called report_name
run()	Execute code that builds the report defined by the kwargs
scan()	creates a report to collect scan time course results.
sensitivity()
timecourse()	creates a report to collect time course results.
update_properties(kwargs)	method for updating properties from kwargs

Attributes

schema

clear_all_reports()

Having multile reports defined at once can be really annoying and give you unexpected results. Use this function to remove all reports before defining a new one to ensure you only have one active report any once. :return:

Args:

Returns:

multi_parameter_estimation()

Define a parameter estimation report and include the progression of the parameter estimation (function evaluations). Defaults to including all metabolites, global variables and local variables with the RSS best value These can be over-ridden with the global_quantities, LocalParameters and metabolites keywords.

Args:

Returns:

parameter_estimation()

Define a parameter estimation report and include the progression of the parameter estimation (function evaluations). Defaults to including all metabolites, global variables and local variables with the RSS best value These can be over-ridden with the global_quantities, LocalParameters and metabolites keywords.

Args:

Returns:

profile_likelihood()

Create report of a parameter and best value for a parameter estimation for profile likelihoods

Args:

Returns:

remove_report(report_name)

remove report called report_name

Parameters:report_name – return: pycotools3.model.Model Returns:pycotools3.model.Model

run()

Execute code that builds the report defined by the kwargs

scan()

creates a report to collect scan time course results.

By default all species and all global quantities are used with Time on the left most column. This behavior can be overwritten by passing lists of metabolites to the metabolites keyword or global quantities to the global quantities keyword

Args:

Returns:

sensitivity()

timecourse()

creates a report to collect time course results.

By default all species and all global quantities are used with Time on the left most column. This behavior can be overwritten by passing lists of metabolites to the metabolites keyword or global quantities to the global quantities keyword

Args:

Returns: