import_points

Imports points from file and computes statistics for them.

Topics

uncertainty_quantification, sampling

Specification

• Alias: None

• Arguments: None

Child Keywords:

Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
Required		import_points_file	File containing list of variable and response values to import for analysis.
Optional		variance_based_decomp	Computes Sobol’ main effects using a binned approach
Optional		std_regression_coeffs	Output Standardized Regression Coefficients and R^2 for samples
Optional		tolerance_intervals	Computes the double sided tolerance interval equivalent normal distribuion.
Optional		final_moments	Output moments of the specified type and include them within the set of final statistics.
Optional		response_levels	Values at which to estimate desired statistics for each response
Optional		probability_levels	Specify probability levels at which to estimate the corresponding response value
Optional		reliability_levels	Specify reliability levels at which the response values will be estimated
Optional		gen_reliability_levels	Specify generalized relability levels at which to estimate the corresponding response value
Optional		distribution	Selection of cumulative or complementary cumulative functions
Optional		model_pointer	Identifier for model block to be used by a method

Description

This method imports input-output points from a tabular file and computes statistics for them. Correlation coefficients and moments are always computed. More advanced statistics, e.g., for sensitivity or reliability analysis, can optionally be computed.

Default Behavior

By default, the import_points method operates on aleatory and epistemic uncertain variables. The types of variables can be restricted or expanded (to include design or state variables) through use of the active keyword in the variables block in the Dakota input file.

Expected Outputs

As a default, Dakota provides correlation analyses for imported points. Correlation tables are printed with the simple, partial, and rank correlations between inputs and outputs. These can be useful to get a quick sense of how correlated the inputs are to each other, and how correlated various outputs are to inputs. variance_based_decomp employs the binned Sobol’ index method [LM16] to compute first-order Sobol’ indices for the imported points.

Additional statistics can be computed from the imported points using the following keywords:

• response_levels

• reliability_levels

• probability_levels

• gen_reliability_levels

response_levels computes statistics at the specified response value. The other three allow the specification of the statistic value, and will estimate the corresponding response value.

distribution is used to specify whether the statistic values are from cumulative or complementary cumulative functions.

Expected HDF5 Output

If Dakota was built with HDF5 support and run with the hdf5 keyword, this method writes the following results to HDF5:

• When variance_based_decomp is enabled

  • Variance-Based Decomposition (Sobol’ Indices)

• For aleatory UQ studies

  • Probability Density

  • Level Mappings

  • Sampling Moments

  • Correlations

• For epistemic UQ studies

  • Extreme Responses

  • Correlations

Usage Tips

No error checking is done on the imported points, e.g., to confirm whether sample values fall within specified bounds in the variables block, or to confirm the adequacy of the sample for computing a requested statistic. Users should perform their own quality checks on their input-output points before employing this method.

Active Variables: By default import_points imports only uncertain variables, and treats any design or state variables as constants. However, if active all is specified, statistics such as correlation coefficients will be computed over all variables, including uncertain, design, and state. The other active options can enable statistics computation over other subsets of variables.

Examples

environment

method
  import_points
    import_points_file 'all_points.dat'
    variance_based_decomp

model
  single

variables
  active uncertain
  uniform_uncertain = 2
    descriptors  =   'input1'     'input2'
    lower_bounds =  -2.0     -2.0
    upper_bounds =   2.0      2.0
  continuous_state = 1
    descriptors =   'constant1'
    initial_state = 100

interface
  analysis_drivers 'text_book'
    fork

responses
  response_functions = 1
  no_gradients
  no_hessians

This example illustrates a basic import points Dakota input file.

• The tabular file to import is specified using import_points_file option.

• Values for all variables, including state variables, are imported.

• Statistics such as correlation coefficients and binned Sobol’ indices are only computed for the active variables.