def test_pwc_integral():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f1 = spk.PieceWiseConstFunc(x, y)
# test full interval
full = 1.0 * 1.0 + 1.0 * -0.5 + 0.5 * 1.5 + 1.5 * 0.75
assert_equal(f1.integral(), full)
assert_equal(f1.integral((np.min(x), np.max(x))), full)
# test part interval, spanning an edge
assert_equal(f1.integral((0.5, 1.5)), 0.5 * 1.0 + 0.5 * -0.5)
# test part interval, just over two edges
assert_almost_equal(f1.integral((1.0 - 1e-16, 2 + 1e-16)),
1.0 * -0.5,
decimal=14)
# test part interval, between two edges
assert_equal(f1.integral((1.0, 2.0)), 1.0 * -0.5)
assert_equal(f1.integral((1.2, 1.7)), (1.7 - 1.2) * -0.5)
# test part interval, start to before and after edge
assert_equal(f1.integral((0.0, 0.7)), 0.7 * 1.0)
assert_equal(f1.integral((0.0, 1.1)), 1.0 * 1.0 + 0.1 * -0.5)
# test part interval, before and after edge till end
assert_equal(f1.integral((2.6, 4.0)), (4.0 - 2.6) * 0.75)
assert_equal(f1.integral((2.4, 4.0)), (2.5 - 2.4) * 1.5 + (4 - 2.5) * 0.75)
def test_pwc_avrg():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f1 = spk.PieceWiseConstFunc(x, y)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y = [0.5, 1.0, -0.25, 0.0, 1.5]
f2 = spk.PieceWiseConstFunc(x, y)
f1.add(f2)
f1.mul_scalar(0.5)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y_expected = [0.75, 1.0, 0.25, 0.625, 0.375, 1.125]
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y, y_expected, decimal=16)
def test_pwc():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
# function values
assert_equal(f(0.0), 1.0)
assert_equal(f(0.5), 1.0)
assert_equal(f(1.0), 0.25)
assert_equal(f(2.0), 0.5)
assert_equal(f(2.25), 1.5)
assert_equal(f(2.5), 2.25 / 2)
assert_equal(f(3.5), 0.75)
assert_equal(f(4.0), 0.75)
assert_array_equal(f([0.0, 0.5, 1.0, 2.0, 2.25, 2.5, 3.5, 4.0]),
[1.0, 1.0, 0.25, 0.5, 1.5, 2.25 / 2, 0.75, 0.75])
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, 1.0, -0.5, -0.5, 1.5, 1.5, 0.75, 0.75]
assert_array_almost_equal(xp, xp_expected, decimal=16)
assert_array_almost_equal(yp, yp_expected, decimal=16)
assert_almost_equal(f.avrg(), (1.0 - 0.5 + 0.5 * 1.5 + 1.5 * 0.75) / 4.0,
decimal=16)
# interval averaging
a = f.avrg([0.5, 3.5])
assert_almost_equal(a, (0.5 - 0.5 + 0.5 * 1.5 + 1.0 * 0.75) / 3.0,
decimal=16)
a = f.avrg([1.5, 3.5])
assert_almost_equal(a, (-0.5 * 0.5 + 0.5 * 1.5 + 1.0 * 0.75) / 2.0,
decimal=16)
a = f.avrg([1.0, 2.0])
assert_almost_equal(a, (1.0 * -0.5) / 1.0, decimal=16)
a = f.avrg([1.0, 3.5])
assert_almost_equal(a, (-0.5 * 1.0 + 0.5 * 1.5 + 1.0 * 0.75) / 2.5,
decimal=16)
a = f.avrg([1.0, 4.0])
assert_almost_equal(a, (-0.5 * 1.0 + 0.5 * 1.5 + 1.5 * 0.75) / 3.0,
decimal=16)
a = f.avrg([0.0, 2.2])
assert_almost_equal(a, (1.0 * 1.0 - 0.5 * 1.0 + 0.2 * 1.5) / 2.2,
decimal=15)
# averaging over multiple intervals
a = f.avrg([(0.5, 1.5), (1.5, 3.5)])
assert_almost_equal(a, (0.5 - 0.5 + 0.5 * 1.5 + 1.0 * 0.75) / 3.0,
decimal=16)
# averaging over multiple intervals
a = f.avrg([(0.5, 1.5), (2.2, 3.5)])
assert_almost_equal(a,
(0.5 * 1.0 - 0.5 * 0.5 + 0.3 * 1.5 + 1.0 * 0.75) / 2.3,
decimal=15)
def test_pwc_mul():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
f.mul_scalar(1.5)
assert_array_almost_equal(f.x, x, decimal=16)
assert_array_almost_equal(f.y, 1.5 * np.array(y), decimal=16)
f.mul_scalar(1.0 / 5.0)
assert_array_almost_equal(f.y, 1.5 / 5.0 * np.array(y), decimal=16)
def test_pwc_add():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
f1 = copy(f)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y = [0.5, 1.0, -0.25, 0.0, 1.5]
f2 = spk.PieceWiseConstFunc(x, y)
f1.add(f2)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y_expected = [1.5, 2.0, 0.5, 1.25, 0.75, 2.25]
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y, y_expected, decimal=16)
f2.add(f)
assert_array_almost_equal(f2.x, x_expected, decimal=16)
assert_array_almost_equal(f2.y, y_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.y, 2 * f2.y, decimal=16)
def test_pwc_integral_bad_bounds_oob_2():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f1 = spk.PieceWiseConstFunc(x, y)
f1.integral((-1, 3))
