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Tools for sensitivity analysis. Contains Sobol, Morris, and FAST methods

Project description

## Sensitivity Analysis Library (SALib)

Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest.

**Documentation:** [ReadTheDocs](

**Requirements:** [NumPy](, [SciPy](, [matplotlib](

**Installation:** `pip install SALib` or `python install`

**Build Status:** [![Build Status](]( **Test Coverage:** [![Coverage Status](](

**Code Issues:** [![Code Issues](](

**SALib Paper:** [![status](](
Herman, J. and Usher, W. (2017) SALib: An open-source Python library for sensitivity analysis.
Journal of Open Source Software, 2(9).

**Methods included:**
* Sobol Sensitivity Analysis ([Sobol 2001](, [Saltelli 2002](, [Saltelli et al. 2010](
* Method of Morris, including groups and optimal trajectories ([Morris 1991](, [Campolongo et al. 2007](
* Fourier Amplitude Sensitivity Test (FAST) ([Cukier et al. 1973](, [Saltelli et al. 1999](
* Random Balance Designs - Fourier Amplitude Sensitivity Test (RBD-FAST)
([Tarantola et al. 2006](, [Plischke 2010](, [Tissot et al. 2012](
* Delta Moment-Independent Measure ([Borgonovo 2007](, [Plischke et al. 2013](
* Derivative-based Global Sensitivity Measure (DGSM) ([Sobol and Kucherenko 2009](
* Fractional Factorial Sensitivity Analysis ([Saltelli et al. 2008](

**Contributing:** see [here](

### Quick Start
from SALib.sample import saltelli
from SALib.analyze import sobol
from SALib.test_functions import Ishigami
import numpy as np

problem = {
'num_vars': 3,
'names': ['x1', 'x2', 'x3'],
'bounds': [[-np.pi, np.pi]]*3

# Generate samples
param_values = saltelli.sample(problem, 1000)

# Run model (example)
Y = Ishigami.evaluate(param_values)

# Perform analysis
Si = sobol.analyze(problem, Y, print_to_console=True)
# Returns a dictionary with keys 'S1', 'S1_conf', 'ST', and 'ST_conf'
# (first and total-order indices with bootstrap confidence intervals)

It's also possible to specify the parameter bounds in a file with 3 columns:
# name lower_bound upper_bound
P1 0.0 1.0
P2 0.0 5.0

Then the `problem` dictionary above can be created from the `read_param_file` function:
from SALib.util import read_param_file
problem = read_param_file('/path/to/file.txt')
# ... same as above

Lots of other options are included for parameter files, as well as a command-line interface. See the [advanced readme](

Also check out the [examples]( for a full description of options for each method.

### License
Copyright (C) 2018 Jon Herman, Will Usher, and others. Versions v0.5 and later are released under the [MIT license](

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