outcomes¶
Module for outcome classes
- class ema_workbench.em_framework.outcomes.AbstractOutcome(name, kind=0, variable_name=None, function=None, expected_range=None, shape=None)¶
Base Outcome class
- Parameters
name (str) – Name of the outcome.
kind ({INFO, MINIMZE, MAXIMIZE}, optional) –
variable_name (str, optional) – if the name of the outcome in the underlying model is different from the name of the outcome, you can supply the variable name as an optional argument, if not provided, defaults to name
function (callable, optional) – a callable to perform postprocessing on data retrieved from model
expected_range (2 tuple, optional) – expected min and max value for outcome, used by HyperVolume convergence metric
shape ({tuple, None} optional) –
- name¶
- Type
str
- kind¶
- Type
int
- variable_name¶
- Type
str
- function¶
- Type
callable
- shape¶
- Type
tuple
- abstract classmethod from_disk(filename, archive)¶
helper function for loading from disk
- Parameters
filename (str) –
archive (Tarfile) –
- abstract classmethod to_disk(values)¶
helper function for writing outcome to disk
- Parameters
values (obj) – data to store
- Return type
BytesIO
- class ema_workbench.em_framework.outcomes.ArrayOutcome(name, variable_name=None, function=None, expected_range=None, shape=None)¶
Array Outcome class for n-dimensional collections
- Parameters
name (str) – Name of the outcome.
variable_name (str, optional) – if the name of the outcome in the underlying model is different from the name of the outcome, you can supply the variable name as an optional argument, if not provided, defaults to name
function (callable, optional) – a callable to perform postprocessing on data retrieved from model
expected_range (2 tuple, optional) – expected min and max value for outcome, used by HyperVolume convergence metric
shape ({tuple, None}, optional) –
- name¶
- Type
str
- kind¶
- Type
int
- variable_name¶
- Type
str
- function¶
- Type
callable
- shape¶
- Type
tuple
- expected_range¶
- Type
tuple
- classmethod from_disk(filename, archive)¶
helper function for loading from disk
- Parameters
filename (str) –
archive (Tarfile) –
- classmethod to_disk(values)¶
helper function for writing outcome to disk
- Parameters
values (ND array) –
- Returns
BytesIO
filename
- class ema_workbench.em_framework.outcomes.Constraint(name, parameter_names=None, outcome_names=None, function=None)¶
Constraints class that can be used when defining constrained optimization problems.
- Parameters
name (str) –
parameter_names (str or collection of str) –
outcome_names (str or collection of str) –
function (callable) –
- name¶
- Type
str
- parameter_names¶
name(s) of the uncertain parameter(s) and/or lever parameter(s) to which the constraint applies
- Type
str, list of str
- outcome_names¶
name(s) of the outcome(s) to which the constraint applies
- Type
str, list of str
- function¶
The function should return the distance from the feasibility threshold, given the model outputs with a variable name. The distance should be 0 if the constraint is met.
- Type
callable
- class ema_workbench.em_framework.outcomes.ScalarOutcome(name, kind=0, variable_name=None, function=None, expected_range=None)¶
Scalar Outcome class
- Parameters
name (str) – Name of the outcome.
kind ({INFO, MINIMZE, MAXIMIZE}, optional) –
variable_name (str, optional) – if the name of the outcome in the underlying model is different from the name of the outcome, you can supply the variable name as an optional argument, if not provided, defaults to name
function (callable, optional) – a callable to perform post processing on data retrieved from model
expected_range (collection, optional) – expected min and max value for outcome, used by HyperVolume convergence metric
- name¶
- Type
str
- kind¶
- Type
int
- variable_name¶
- Type
str
- function¶
- Type
callable
- shape¶
- Type
tuple
- expected_range¶
- Type
tuple
- classmethod from_disk(filename, archive)¶
helper function for loading from disk
- Parameters
filename (str) –
archive (Tarfile) –
- classmethod to_disk(values)¶
helper function for writing outcome to disk
- Parameters
values (1D array) –
- Returns
BytesIO
filename
- class ema_workbench.em_framework.outcomes.TimeSeriesOutcome(name, variable_name=None, function=None, expected_range=None, shape=None)¶
TimeSeries Outcome class
- Parameters
name (str) – Name of the outcome.
variable_name (str, optional) – if the name of the outcome in the underlying model is different from the name of the outcome, you can supply the variable name as an optional argument, if not provided, defaults to name
function (callable, optional) – a callable to perform postprocessing on data retrieved from model
expected_range (2 tuple, optional) – expected min and max value for outcome, used by HyperVolume convergence metric
shape ({tuple, None}, optional) –
- name¶
- Type
str
- kind¶
- Type
int
- variable_name¶
- Type
str
- function¶
- Type
callable
- shape¶
- Type
tuple
- expected_range¶
- Type
tuple
- classmethod from_disk(filename, archive)¶
helper function for loading from disk
- Parameters
filename (str) –
archive (Tarfile) –
- classmethod to_disk(values)¶
helper function for writing outcome to disk
- Parameters
values (DataFrame) –
- Returns
StringIO
filename