Optimization

The files that help you setup an optimization problem. More...

Modules
	Package_Setups
	Individual package setups that help you interface with other codes.

Classes
class	SUAVE.Optimization.Nexus.Nexus
class	SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization

Functions
def	SUAVE.Optimization.carpet_plot.carpet_plot (problem, number_of_points, plot_obj=1, plot_const=0, sweep_index_0=0, sweep_index_1=1)
def	SUAVE.Optimization.helper_functions.set_values (dictionary, input_dictionary, converted_values, aliases)
def	SUAVE.Optimization.helper_functions.find_a_star (dictionary, string)
def	SUAVE.Optimization.helper_functions.scale_input_values (inputs, x)
def	SUAVE.Optimization.helper_functions.convert_values (inputs)
def	SUAVE.Optimization.helper_functions.get_values (dictionary, outputs, aliases)
def	SUAVE.Optimization.helper_functions.scale_obj_values (inputs, x)
def	SUAVE.Optimization.helper_functions.scale_const_values (inputs, x)
def	SUAVE.Optimization.helper_functions.scale_const_bnds (inputs)
def	SUAVE.Optimization.helper_functions.unscale_const_values (inputs, x)
def	SUAVE.Optimization.read_optimization_outputs.format_input_data (data)
def	SUAVE.Optimization.read_optimization_outputs.read_optimization_outputs (filename, base_inputs, constraint_inputs)
def	SUAVE.Optimization.write_optimization_outputs.write_optimization_outputs (nexus, filename)

Detailed Description

The files that help you setup an optimization problem.

Function Documentation

carpet_plot()

def SUAVE.Optimization.carpet_plot.carpet_plot	(		problem,
			number_of_points,
			plot_obj = 1,
			plot_const = 0,
			sweep_index_0 = 0,
			sweep_index_1 = 1
	)

Takes in an optimization problem and runs a carpet plot of the first 2 variables
    sweep_index_0, sweep_index_1 is index of variables you want to run carpet plot (i.e. sweep_index_0=0 means you want to sweep first variable, sweep_index_0 = 4 is the 5th variable)

    Assumptions:
    N/A

    Source:
    N/A

    Inputs:
    problem            [Nexus Class]
    number_of_points   [int]
    plot_obj           [int]
    plot_const         [int]
    sweep_index_0      [int]
    sweep_index_1      [int]
    
    Outputs:
    Beautiful Beautiful Plots!
        Outputs:
            inputs     [array]
            objective  [array]
            constraint [array]

    Properties Used:
    N/A

convert_values()

def SUAVE.Optimization.helper_functions.convert_values

(

inputs

)

Converts an inputs from an optimization into the right units

Assumptions:
Always multiply the units by 1!

Source:
N/A

Inputs:
inputs           [list]

Outputs:
converted_values [list of str]

Properties Used:
N/A

find_a_star()

def SUAVE.Optimization.helper_functions.find_a_star	(		dictionary,
			string
	)

Searches through a dictionary looking for an *

Assumptions:
There may or may not be an asterisk

Source:
N/A

Inputs:
dictionary       [Data()]
input_dictionary [Data()]
converted_values [Data()]
aliases          [list of str]

Outputs:
newstrings       [list of str]

Properties Used:
N/A

format_input_data()

def SUAVE.Optimization.read_optimization_outputs.format_input_data

(

data

)

Takes in a result from an optimization problem and 

    Assumptions:
    None

    Source:
    N/A

    Inputs:
    data

    Outputs:
    data_out

    Properties Used:
    None

get_values()

def SUAVE.Optimization.helper_functions.get_values	(		dictionary,
			outputs,
			aliases
	)

Retrieves values saved in a dictionary 

Assumptions:
N/A

Source:
N/A

Inputs:
dictionary       [Data()]
outputs          [Data()]
aliases          [list of str]

Outputs:
values           [float]

Properties Used:
N/A

read_optimization_outputs()

def SUAVE.Optimization.read_optimization_outputs.read_optimization_outputs	(		filename,
			base_inputs,
			constraint_inputs
	)

Reads in the outputs of an optimization problem

    Assumptions:
    None

    Source:
    N/A

    Inputs:
    filename          [str]
    base_inputs       [data]
    constraint_inputs [data]

    Outputs:
    iterations        [int]
    obj_values        [list]
    inputs            [array]
    constraints       [array]
    

    Properties Used:
    None

scale_const_bnds()

def SUAVE.Optimization.helper_functions.scale_const_bnds

(

inputs

)

Rescales constraint bounds based on Nexus inputs scale

Assumptions:
N/A

Source:
N/A

Inputs:
inputs           [Data()]

Outputs:
converted_values [array]

Properties Used:
N/A

scale_const_values()

def SUAVE.Optimization.helper_functions.scale_const_values	(		inputs,
			x
	)

Rescales constraint values based on Nexus inputs scale

Assumptions:
N/A

Source:
N/A

Inputs:
inputs          [Data()]
x               [array]

Outputs:
scaled          [array]

Properties Used:
N/A

scale_input_values()

def SUAVE.Optimization.helper_functions.scale_input_values	(		inputs,
			x
	)

Scales the values according to the a provided scale

Assumptions:


Source:
N/A

Inputs:
x                [array]         
inputs           [list]

Outputs:
inputs           [list]

Properties Used:
N/A

scale_obj_values()

def SUAVE.Optimization.helper_functions.scale_obj_values	(		inputs,
			x
	)

Rescales an objective based on Nexus inputs scale

Assumptions:
N/A

Source:
N/A

Inputs:
inputs          [Data()]
x               [float]

Outputs:
scaled          [float]

Properties Used:
N/A

set_values()

def SUAVE.Optimization.helper_functions.set_values	(		dictionary,
			input_dictionary,
			converted_values,
			aliases
	)

This method regresses through a dictionary to set the required values.
    dictionary is the base class that will be modified, input_dictionary is
    the set of inputs to be used, converted_values are values to be set in the
    base dictionary, and finally the aliases which are where in the dictionary
    the names link to

Assumptions:
N/A

Source:
N/A

Inputs:
dictionary       [Data()]
input_dictionary [Data()]
converted_values [Data()]
aliases          [list of str]

Outputs:
None

Properties Used:
N/A

unscale_const_values()

def SUAVE.Optimization.helper_functions.unscale_const_values	(		inputs,
			x
	)

Rescales values based on Nexus inputs scale

Assumptions:
N/A

Source:
N/A

Inputs:
inputs           [Data()]
x                [array]

Outputs:
scaled           [array]

Properties Used:
N/A

write_optimization_outputs()

def SUAVE.Optimization.write_optimization_outputs.write_optimization_outputs	(		nexus,
			filename
	)

Writes the optimization outputs to a file

Assumptions:
N/A

Source:
N/A

Inputs:
nexus            [nexus()]
filename         [str]

Outputs:
N/A

Properties Used:
N/A