Getting Started#

Installing SALib#

To install the latest stable version of SALib via pip from PyPI. together with all the dependencies, run the following command:

pip install SALib

To install the latest development version of SALib, run the following commands. Note that the development version may be unstable and include bugs. We encourage users use the latest stable version.

git clone
cd SALib
pip install .

Installing Prerequisite Software#

Core dependencies include: - NumPy - SciPy - pandas - matplotlib

These should be installed automatically alongside SALib but otherwise they can be installed with the following command:

pip install numpy scipy pandas matplotlib

The packages are normally included with most Python bundles, such as Anaconda and Canopy.

Testing Installation#

To test your installation of SALib, run the following command


Alternatively, if you’d like also like a taste of what SALib provides, start a new interactive Python session and copy/paste the code below.

from SALib.analyze.sobol import analyze
from SALib.sample.sobol import sample
from SALib.test_functions import Ishigami
import numpy as np

# Define the model inputs
problem = {
    'num_vars': 3,
    'names': ['x1', 'x2', 'x3'],
    'bounds': [[-3.14159265359, 3.14159265359],
               [-3.14159265359, 3.14159265359],
               [-3.14159265359, 3.14159265359]]

# Generate samples
param_values = sample(problem, 1024)

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

# Perform analysis
Si = analyze(problem, Y, print_to_console=True)

# Print the first-order sensitivity indices

If installed correctly, the last line above will print three values, similar to [ 0.31683154 0.44376306 0.01220312].