Index

A

add_refinement() (pandakota.input.methods.LatinHypercubeSampling method) (pandakota.input.methods.Method method)

B

block_name (pandakota.input.variables.NormalUncertainVariable attribute) (pandakota.input.variables.StateVariable property) (pandakota.input.variables.UniformUncertainVariable attribute) (pandakota.input.variables.Variable attribute)

C

check_convergence_type() (pandakota.input.methods.JegaOptimize class method) check_crossover_type() (pandakota.input.methods.JegaOptimize class method) check_initialization_type() (pandakota.input.methods.JegaOptimize class method) check_merit_function() (pandakota.input.methods.OptppOptimize class method) check_mutation_type() (pandakota.input.methods.JegaOptimize class method) check_replacement_type() (pandakota.input.methods.JegaOptimize class method)

check_search_method() (pandakota.input.methods.OptppNewtonOptimize class method) ColinyCobylaOptimize (class in pandakota.input.methods) convergence_tolerance (pandakota.input.methods.Optimize property) convergence_types (pandakota.input.methods.JegaOptimize attribute) (pandakota.input.methods.MogaOptimize attribute) (pandakota.input.methods.SogaOptimize attribute) crossover_types (pandakota.input.methods.JegaOptimize attribute)

D

Derivatives (class in pandakota.input.derivatives)

dtype (pandakota.input.variables.Variable property)

E

element (pandakota.input.variables.Variable property)

F

fromVariable() (pandakota.input.variables.StateVariable class method)

function_key (pandakota.input.methods.Optimize attribute) (pandakota.input.methods.Sampling attribute)

G

gradient_type (pandakota.input.derivatives.Gradients property)

Gradients (class in pandakota.input.derivatives)

H

hessian_type (pandakota.input.derivatives.Hessians property)

Hessians (class in pandakota.input.derivatives)

I

initialization_types (pandakota.input.methods.JegaOptimize attribute)

J

JegaOptimize (class in pandakota.input.methods)

justify() (pandakota.input.variables.Variable method)

K

key (pandakota.input.derivatives.Derivatives attribute) (pandakota.input.derivatives.Gradients attribute) (pandakota.input.derivatives.Hessians attribute)

L

LatinHypercubeSampling (class in pandakota.input.methods)

lower (pandakota.input.variables.UniformUncertainVariable property)

M

max_function_evaluations (pandakota.input.methods.Optimize property) max_iterations (pandakota.input.methods.Optimize property) mean (pandakota.input.variables.NormalUncertainVariable property) merit_functions (pandakota.input.methods.OptppOptimize attribute) Method (class in pandakota.input.methods) min_boxsize_limit (pandakota.input.methods.NcsuDirectOptimize property) module pandakota.input.derivatives pandakota.input.methods pandakota.input.variables pandakota.reader pandakota.reader.output pandakota.reader.utils

MogaOptimize (class in pandakota.input.methods) MonteCarloSampling (class in pandakota.input.methods) mutation_types (pandakota.input.methods.JegaOptimize attribute)

N

NcsuDirectOptimize (class in pandakota.input.methods) NlpqlSqpOptimize (class in pandakota.input.methods)

nominal (pandakota.input.variables.StateVariable property) NormalUncertainVariable (class in pandakota.input.variables) nsamples (pandakota.input.methods.Sampling property)

O

Optimize (class in pandakota.input.methods) optimize_type (pandakota.input.methods.ColinyCobylaOptimize attribute) (pandakota.input.methods.JegaOptimize attribute) (pandakota.input.methods.MogaOptimize attribute) (pandakota.input.methods.NcsuDirectOptimize attribute) (pandakota.input.methods.NlpqlSqpOptimize attribute) (pandakota.input.methods.Optimize attribute) (pandakota.input.methods.OptppCgOptimize attribute) (pandakota.input.methods.OptppFdNewtonOptimize attribute) (pandakota.input.methods.OptppGNewtonOptimize attribute) (pandakota.input.methods.OptppNewtonOptimize attribute) (pandakota.input.methods.OptppOptimize attribute) (pandakota.input.methods.OptppPdsOptimize attribute) (pandakota.input.methods.OptppQNewtonOptimize attribute) (pandakota.input.methods.SogaOptimize attribute)

OptppCgOptimize (class in pandakota.input.methods) OptppFdNewtonOptimize (class in pandakota.input.methods) OptppGNewtonOptimize (class in pandakota.input.methods) OptppNewtonOptimize (class in pandakota.input.methods) OptppOptimize (class in pandakota.input.methods) OptppPdsOptimize (class in pandakota.input.methods) OptppQNewtonOptimize (class in pandakota.input.methods) order (pandakota.input.derivatives.Derivatives attribute) (pandakota.input.derivatives.Gradients attribute) (pandakota.input.derivatives.Hessians attribute)

P

pandakota.input.derivatives module pandakota.input.methods module pandakota.input.variables module pandakota.reader module

pandakota.reader.output module pandakota.reader.utils module population_size (pandakota.input.methods.JegaOptimize property) properties (pandakota.input.variables.StateVariable property)

R

read_confidence_intervals() (in module pandakota.reader.output) read_moment_statistics() (in module pandakota.reader.output) read_partial_matrix() (in module pandakota.reader.output) read_pearson_matrix() (in module pandakota.reader.output) read_spearman_matrix() (in module pandakota.reader.output) refinements (pandakota.input.methods.Method property) replacement_types (pandakota.input.methods.JegaOptimize attribute) (pandakota.input.methods.MogaOptimize attribute) (pandakota.input.methods.SogaOptimize attribute) requires_gradients (pandakota.input.methods.Method attribute) (pandakota.input.methods.OptppCgOptimize attribute) (pandakota.input.methods.OptppFdNewtonOptimize attribute) (pandakota.input.methods.OptppGNewtonOptimize attribute) (pandakota.input.methods.OptppNewtonOptimize attribute) (pandakota.input.methods.OptppQNewtonOptimize attribute)

requires_hessians (pandakota.input.methods.Method attribute) (pandakota.input.methods.OptppFdNewtonOptimize attribute) (pandakota.input.methods.OptppGNewtonOptimize attribute) (pandakota.input.methods.OptppNewtonOptimize attribute) (pandakota.input.methods.OptppQNewtonOptimize attribute)

S

sample_type (pandakota.input.methods.LatinHypercubeSampling attribute) (pandakota.input.methods.MonteCarloSampling attribute) (pandakota.input.methods.Sampling attribute) Sampling (class in pandakota.input.methods) search_methods (pandakota.input.methods.OptppNewtonOptimize attribute)

seed (pandakota.input.methods.JegaOptimize property) snip_text() (in module pandakota.reader.utils) SogaOptimize (class in pandakota.input.methods) solution_target (pandakota.input.methods.NcsuDirectOptimize property) StateVariable (class in pandakota.input.variables) string_to_stream() (in module pandakota.reader.utils)

T

to_string() (pandakota.input.derivatives.Derivatives method) (pandakota.input.derivatives.Gradients method) (pandakota.input.derivatives.Hessians method) (pandakota.input.methods.ColinyCobylaOptimize method) (pandakota.input.methods.JegaOptimize method) (pandakota.input.methods.Method method) (pandakota.input.methods.NcsuDirectOptimize method) (pandakota.input.methods.Optimize method) (pandakota.input.methods.OptppNewtonOptimize method) (pandakota.input.methods.OptppOptimize method) (pandakota.input.methods.OptppPdsOptimize method) (pandakota.input.methods.Sampling method)

type_rate_pairs (pandakota.input.methods.JegaOptimize attribute)

U

UniformUncertainVariable (class in pandakota.input.variables)

upper (pandakota.input.variables.UniformUncertainVariable property)

V

Variable (class in pandakota.input.variables)

volume_boxsize_limit (pandakota.input.methods.NcsuDirectOptimize property)