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 setup.py install
Herman, J. and Usher, W. (2017) SALib: An opensource 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)

Delta MomentIndependent Measure (Borgonovo 2007, Plischke et al. 2013)

Derivativebased 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, calc_second_order=True)
# Run model (example)
Y = Ishigami.evaluate(param_values)
# Perform analysis
Si = sobol.analyze(problem, Y, print_to_console=False)
# Returns a dictionary with keys 'S1', 'S1_conf', 'ST', and 'ST_conf'
# (first and totalorder indices with bootstrap confidence intervals)
Itâ€™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
...etc.
Then the problem
dictionary above can be created from the read_param_file
function:
python
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 commandline interface. See the advanced readme.
Also check out the examples for a full description of options for each method.
License
Copyright (C) 2017 Jon Herman, Will Usher, and others. Versions v0.5 and later are released under the MIT license.