def test_pwl_avrg():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f1 = spk.PieceWiseLinFunc(x, y1, y2)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y1 = [0.5, 1.0, -0.25, 0.0, 1.5]
y2 = [0.8, 0.2, -1.0, 0.0, 2.0]
f2 = spk.PieceWiseLinFunc(x, y1, y2)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y1_expected = np.array([
1.5, 1.0 + 1.0 + 0.5 * 0.75, -0.5 + 1.0 - 0.8 * 0.25 / 1.25,
1.5 - 0.25, 0.75, 1.5 + 0.75 - 0.5 * 0.2 / 1.5
]) / 2
y2_expected = np.array([
0.8 + 1.0 + 0.5 * 0.75, 1.5 + 1.0 - 0.8 * 0.25 / 1.25, -0.4 + 0.2,
1.5 - 1.0, 0.75 - 0.5 * 0.2 / 1.5, 2.25
]) / 2
f1.add(f2)
f1.mul_scalar(0.5)
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y1, y1_expected, decimal=16)
assert_array_almost_equal(f1.y2, y2_expected, decimal=16)
def test_pwl_add():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
f1 = copy(f)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y1 = [0.5, 1.0, -0.25, 0.0, 1.5]
y2 = [0.8, 0.2, -1.0, 0.0, 2.0]
f2 = spk.PieceWiseLinFunc(x, y1, y2)
f1.add(f2)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y1_expected = [
1.5, 1.0 + 1.0 + 0.5 * 0.75, -0.5 + 1.0 - 0.8 * 0.25 / 1.25,
1.5 - 0.25, 0.75, 1.5 + 0.75 - 0.5 * 0.2 / 1.5
]
y2_expected = [
0.8 + 1.0 + 0.5 * 0.75, 1.5 + 1.0 - 0.8 * 0.25 / 1.25, -0.4 + 0.2,
1.5 - 1.0, 0.75 - 0.5 * 0.2 / 1.5, 2.25
]
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y1, y1_expected, decimal=16)
assert_array_almost_equal(f1.y2, y2_expected, decimal=16)
f2.add(f)
assert_array_almost_equal(f2.x, x_expected, decimal=16)
assert_array_almost_equal(f2.y1, y1_expected, decimal=16)
assert_array_almost_equal(f2.y2, y2_expected, decimal=16)
f1.add(f2)
# same x, but y doubled
assert_array_almost_equal(f1.x, f2.x, decimal=16)
assert_array_almost_equal(f1.y1, 2 * f2.y1, decimal=16)
assert_array_almost_equal(f1.y2, 2 * f2.y2, decimal=16)
def test_pwl():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
# function values
assert_equal(f(0.0), 1.0)
assert_equal(f(0.5), 1.25)
assert_equal(f(1.0), 0.5)
assert_equal(f(2.0), 1.1 / 2)
assert_equal(f(2.25), 1.5)
assert_equal(f(2.5), 2.25 / 2)
assert_equal(f(3.5), 0.75 - 0.5 * 1.0 / 1.5)
assert_equal(f(4.0), 0.25)
assert_array_equal(f(
[0.0, 0.5, 1.0, 2.0, 2.25, 2.5, 3.5,
4.0]), [1.0, 1.25, 0.5, 0.55, 1.5, 2.25 / 2, 0.75 - 0.5 / 1.5, 0.25])
xp, yp = f.get_plottable_data()
xp_expected = [0.0, 1.0, 1.0, 2.0, 2.0, 2.5, 2.5, 4.0]
yp_expected = [1.0, 1.5, -0.5, -0.4, 1.5, 1.5, 0.75, 0.25]
assert_array_almost_equal(xp, xp_expected, decimal=16)
assert_array_almost_equal(yp, yp_expected, decimal=16)
avrg_expected = (1.25 - 0.45 + 0.75 + 1.5 * 0.5) / 4.0
assert_almost_equal(f.avrg(), avrg_expected, decimal=16)
# interval averaging
a = f.avrg([0.5, 2.5])
assert_almost_equal(a, (1.375 * 0.5 - 0.45 + 0.75) / 2.0, decimal=16)
a = f.avrg([1.5, 3.5])
assert_almost_equal(a, (-0.425 * 0.5 + 0.75 +
(0.75 + 0.75 - 0.5 / 1.5) / 2) / 2.0,
decimal=16)
a = f.avrg((1.0, 3.5))
assert_almost_equal(a,
(-0.45 + 0.75 + (0.75 + 0.75 - 0.5 / 1.5) / 2) / 2.5,
decimal=16)
a = f.avrg([1.0, 4.0])
assert_almost_equal(a, (-0.45 + 0.75 + 1.5 * 0.5) / 3.0, decimal=16)
# interval between support points
a = f.avrg([1.1, 1.5])
assert_almost_equal(a, (-0.5 + 0.1 * 0.1 - 0.45) * 0.5, decimal=14)
# starting at a support point
a = f.avrg([1.0, 1.5])
assert_almost_equal(a, (-0.5 - 0.45) * 0.5, decimal=14)
# start and end at support point
a = f.avrg([1.0, 2.0])
assert_almost_equal(a, (-0.5 - 0.4) * 0.5, decimal=14)
# averaging over multiple intervals
a = f.avrg([(0.5, 1.5), (1.5, 2.5)])
assert_almost_equal(a, (1.375 * 0.5 - 0.45 + 0.75) / 2.0, decimal=16)
def test_pwl_mul():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
f.mul_scalar(1.5)
assert_array_almost_equal(f.x, x, decimal=16)
assert_array_almost_equal(f.y1, 1.5 * np.array(y1), decimal=16)
assert_array_almost_equal(f.y2, 1.5 * np.array(y2), decimal=16)
f.mul_scalar(1.0 / 5.0)
assert_array_almost_equal(f.y1, 1.5 / 5.0 * np.array(y1), decimal=16)
assert_array_almost_equal(f.y2, 1.5 / 5.0 * np.array(y2), decimal=16)