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test_ff.py
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"""
Created on 30 Jun 2015
@author: @willu47
"""
import numpy as np
from numpy.testing import assert_equal, assert_allclose
from SALib.sample.ff import sample, find_smallest, extend_bounds
from SALib.analyze.ff import analyze, interactions
def test_find_smallest():
""" """
num_vars = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 16, 17, 31, 32, 33]
expected = [0, 1, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6]
for x, y in zip(num_vars, expected):
actual = find_smallest(x)
assert_equal(actual, y)
def test_extend_bounds():
problem = {
"bounds": np.repeat([-1, 1], 12).reshape(2, 12).T,
"num_vars": 12,
"names": ["x" + str(x + 1) for x in range(12)],
}
actual = extend_bounds(problem)
expected = {
"names": [
"x1",
"x2",
"x3",
"x4",
"x5",
"x6",
"x7",
"x8",
"x9",
"x10",
"x11",
"x12",
"dummy_0",
"dummy_1",
"dummy_2",
"dummy_3",
],
"bounds": [
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([-1, 1]),
np.array([0, 1]),
np.array([0, 1]),
np.array([0, 1]),
np.array([0, 1]),
],
"num_vars": 16,
}
assert_equal(actual, expected)
def test_ff_sample():
problem = {
"bounds": [[0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]],
"num_vars": 4,
"names": ["x1", "x2", "x3", "x4"],
}
actual = sample(problem)
expected = np.array(
[
[1, 1, 1, 1],
[1, 0, 1, 0],
[1, 1, 0, 0],
[1, 0, 0, 1],
[0, 0, 0, 0],
[0, 1, 0, 1],
[0, 0, 1, 1],
[0, 1, 1, 0],
],
dtype=float,
)
assert_equal(actual, expected)
def test_ff_sample_scaled():
""" """
problem = {
"bounds": [[0.0, 2.5], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]],
"num_vars": 4,
"names": ["x1", "x2", "x3", "x4"],
}
actual = sample(problem)
expected = np.array(
[
[2.5, 1, 1, 1],
[2.5, 0, 1, 0],
[2.5, 1, 0, 0],
[2.5, 0, 0, 1],
[0, 0, 0, 0],
[0, 1, 0, 1],
[0, 0, 1, 1],
[0, 1, 1, 0],
],
dtype=float,
)
assert_equal(actual, expected)
def test_ff_analyze():
""" """
problem = {
"bounds": [[0.0, 2.5], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]],
"num_vars": 4,
"names": ["x1", "x2", "x3", "x4"],
}
X = np.array(
[
[1, 1, 1, 1],
[1, 0, 1, 0],
[1, 1, 0, 0],
[1, 0, 0, 1],
[0, 0, 0, 0],
[0, 1, 0, 1],
[0, 0, 1, 1],
[0, 1, 1, 0],
],
dtype=float,
)
Y = np.array([1.5, 1, 1.5, 1, 2, 2.5, 2, 2.5], dtype=float)
actual = analyze(problem, X, Y)
expected = {
"ME": np.array([-0.5, 0.25, 0.0, 0.0]),
"names": ["x1", "x2", "x3", "x4"],
}
assert_equal(actual, expected)
def test_ff_example():
""" """
problem = {
"bounds": np.repeat([-1, 1], 12).reshape(2, 12).T,
"num_vars": 12,
"names": ["x" + str(x + 1) for x in range(12)],
}
X = sample(problem)
Y = X[:, 0] + 2 * X[:, 1] + 3 * X[:, 2] + 4 * X[:, 6] * X[:, 11]
expected = np.array(
[
10,
-2,
4,
-8,
2,
6,
-4,
0,
2,
6,
-4,
0,
10,
-2,
4,
-8,
-2,
-6,
4,
0,
-10,
2,
-4,
8,
-10,
2,
-4,
8,
-2,
-6,
4,
0,
]
)
assert_equal(Y, expected)
Si = analyze(problem, X, Y)
expected = np.array([1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=float)
assert_equal(expected, Si["ME"])
def test_interactions_from_saltelli():
""" """
problem = {
"bounds": np.repeat([-1, 1], 12).reshape(2, 12).T,
"num_vars": 12,
"names": ["x" + str(x + 1) for x in range(12)],
}
X = sample(problem)
Y = np.array(
[
10,
-2,
4,
-8,
2,
6,
-4,
0,
2,
6,
-4,
0,
10,
-2,
4,
-8,
-2,
-6,
4,
0,
-10,
2,
-4,
8,
-10,
2,
-4,
8,
-2,
-6,
4,
0,
]
)
Si = analyze(problem, X, Y, second_order=True)
actual = Si["IE"]
expected = [
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
4.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
]
assert_equal(actual, expected)
def test_interactions():
""" """
problem = {
"bounds": [[0.0, 2.5], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]],
"num_vars": 4,
"names": ["x1", "x2", "x3", "x4"],
}
X = np.array(
[
[2.5, 1.0, 1.0, 1.0],
[2.5, 0, 1.0, 0],
[2.5, 1.0, 0, 0],
[2.5, 0, 0, 1.0],
[0, 0, 0, 0],
[0, 1.0, 0, 1.0],
[0, 0, 1.0, 1.0],
[0, 1.0, 1.0, 0],
],
dtype=float,
)
Y = X[:, 0] + (0.1 * X[:, 1]) + ((1.2 * X[:, 2]) * (1.3 + X[:, 3]))
ie_names, ie = interactions(problem, Y)
actual = ie
assert_allclose(actual, [0.3, 0, 0, 0, 0, 0.3], rtol=1e-4, atol=1e-4)