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# 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 https://github.com/SALib/SALib.git
    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

    pytest

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
    print(Si['S1'])

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