===============
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 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.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]`.