=============== Getting Started =============== Installing SALib ---------------- To install the latest stable version of SALib using pip, 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 python setup.py develop Installing Prerequisite Software -------------------------------- SALib requires `NumPy `_, `SciPy `_, and `matplotlib `_ installed on your computer. Using `pip `_, these libraries can be installed with the following command: :: pip install numpy pip install scipy pip install matplotlib The packages are normally included with most Python bundles, such as Anaconda and Canopy. In any case, they are installed automatically when using pip or setuptools to install SALib. Testing Installation -------------------- To test your installation of SALib, run the following command :: pytest Alternatively, if youâ€™d like also like a taste of what SALib provides, start a new interactive Python session and copy/paste the code below. .. code:: python from SALib.sample import saltelli from SALib.analyze import sobol 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 = saltelli.sample(problem, 1000) # Run model (example) Y = Ishigami.evaluate(param_values) # Perform analysis Si = sobol.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 :code:`[ 0.30644324 0.44776661 -0.00104936]`.