SALib.util package

Submodules

• SALib.util.problem module
  • ProblemSpec
    • ProblemSpec.samples
    • ProblemSpec.results
    • ProblemSpec.analysis
    • ProblemSpec.analysis
    • ProblemSpec.analyze()
    • ProblemSpec.analyze_parallel()
    • ProblemSpec.evaluate()
    • ProblemSpec.evaluate_distributed()
    • ProblemSpec.evaluate_parallel()
    • ProblemSpec.heatmap()
    • ProblemSpec.plot()
    • ProblemSpec.results
    • ProblemSpec.sample()
    • ProblemSpec.samples
    • ProblemSpec.set_results()
    • ProblemSpec.set_samples()
    • ProblemSpec.to_df()
• SALib.util.results module
  • ResultDict
    • ResultDict.plot()
    • ResultDict.to_df()
• SALib.util.util_funcs module
  • avail_approaches()
  • handle_seed()
  • read_param_file()

Module contents

A set of utility functions

SALib.util.avail_approaches(pkg)

Create list of available modules.

Parameters:

pkg (module) – module to inspect

Returns:

method – A list of available submodules

Return type:

list

SALib.util.handle_seed(seed: Generator | BitGenerator | SeedSequence | int | Sequence[int] | None) → Generator

Set (or create) a random number generator.

SALib.util.read_param_file(filename, delimiter=None)

Unpacks a parameter file into a dictionary

Reads a parameter file of format:

Param1,0,1,Group1,dist1
Param2,0,1,Group2,dist2
Param3,0,1,Group3,dist3

(Group and Dist columns are optional)

Returns a dictionary containing:

• names - the names of the parameters

• bounds - a list of lists of lower and upper bounds

• num_vars - a scalar indicating the number of variables

  (the length of names)

• groups - a list of group names (strings) for each variable

• dists - a list of distributions for the problem,

  None if not specified or all uniform

Parameters:

• filename (str) – The path to the parameter file

• delimiter (str, default=None) – The delimiter used in the file to distinguish between columns

SALib.util.scale_samples(params: ndarray, problem: Dict)

Scale samples based on specified distribution (defaulting to uniform).

Adds an entry to the problem specification to indicate samples have been scaled to maintain backwards compatibility (sample_scaled).

Parameters:

• params (np.ndarray,) – numpy array of dimensions num_params-by-\(N\), where \(N\) is the number of samples

• problem (dictionary,) – SALib problem specification

Return type:

np.ndarray, scaled samples