=============== 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. .. code:: python 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 :code:`[ 0.31683154 0.44376306 0.01220312]`.