def test_list_input():
"""Indirectly test that flip works on lists as input"""
x, y = dg.figure2()
kl = KneeLocator(
x.tolist(), y.tolist(), S=1.0, curve="concave", interp_method="polynomial"
)
assert math.isclose(kl.knee, 0.22, rel_tol=0.05)
def test_concave_decreasing(interp_method):
"""test a concave decreasing function"""
x, y = dg.concave_decreasing()
kn = KneeLocator(
x, y, curve="concave", direction="decreasing", interp_method=interp_method
)
assert kn.knee == 7
def test_figure2(interp_method):
"""From the kneedle manuscript"""
x, y = dg.figure2()
kl = KneeLocator(x, y, S=1.0, curve="concave", interp_method=interp_method)
assert math.isclose(kl.knee, 0.22, rel_tol=0.05)
assert math.isclose(kl.elbow, 0.22, rel_tol=0.05)
assert math.isclose(kl.norm_elbow, kl.knee, rel_tol=0.05)
def test_convex_decreasing_bumpy(interp_method, expected):
"""test a bumpy convex decreasing function"""
x, y = dg.bumpy()
kl = KneeLocator(
x, y, curve="convex", direction="decreasing", interp_method=interp_method
)
assert kl.knee == expected
def test_convex_increasing_truncated(interp_method):
"""test a truncated convex increasing function"""
x, y = dg.convex_increasing()
kl = KneeLocator(
x[:-3] / 10, y[:-3] / 10, curve="convex", interp_method=interp_method
)
assert kl.knee == 0.4
def test_convex_decreasing(interp_method):
"""test a convex decreasing function"""
x, y = dg.convex_decreasing()
kl = KneeLocator(
x, y, curve="convex", direction="decreasing", interp_method=interp_method
)
assert kl.knee == 2
def test_plot_knee():
"""Test that plotting is functional"""
x, y = dg.figure2()
kl = KneeLocator(x, y, S=1.0, curve="concave", interp_method="interp1d")
num_figures_before = plt.gcf().number
kl.plot_knee()
num_figures_after = plt.gcf().number
assert num_figures_before < num_figures_after
def test_y():
"""Test the y value"""
x, y = dg.figure2()
kl = KneeLocator(x, y, S=1.0, curve="concave", interp_method="interp1d")
assert math.isclose(kl.knee_y, 1.897, rel_tol=0.03)
assert math.isclose(kl.all_knees_y[0], 1.897, rel_tol=0.03)
assert math.isclose(kl.norm_knee_y, 0.758, rel_tol=0.03)
assert math.isclose(kl.all_norm_knees_y[0], 0.758, rel_tol=0.03)
def test_convex_decreasing_truncated(interp_method):
"""test a truncated convex decreasing function"""
x, y = dg.convex_decreasing()
kl = KneeLocator(x[:-3] / 10,
y[:-3] / 10,
curve='convex',
direction='decreasing',
interp_method=interp_method)
assert kl.knee == 0.2
def test_find_shape():
"""Test that find_shape can detect the right shape of curve line"""
x, y = dg.concave_increasing()
direction, curve = find_shape(x, y)
assert direction == 'increasing'
assert curve == 'concave'
x, y = dg.concave_decreasing()
direction, curve = find_shape(x, y)
assert direction == 'decreasing'
assert curve == 'concave'
x, y = dg.convex_decreasing()
direction, curve = find_shape(x, y)
assert direction == 'decreasing'
assert curve == 'convex'
x, y = dg.convex_increasing()
direction, curve = find_shape(x, y)
assert direction == 'increasing'
assert curve == 'convex'
def test_concave_decreasing_truncated(interp_method):
"""test a truncated concave decreasing function"""
x, y = dg.concave_decreasing()
kl = KneeLocator(
x[:-3] / 10,
y[:-3] / 10,
curve="concave",
direction="decreasing",
interp_method=interp_method,
)
assert kl.knee == 0.4
def test_all_knees():
x, y = dg.bumpy()
kl = KneeLocator(x, y, curve='convex', direction='decreasing', online=True)
kl.all_elbows == set([41, 46, 53, 26, 31])
kl.all_norm_elbows == set([
0.2921348314606742,
0.348314606741573,
0.5955056179775281,
0.4606741573033708,
0.5168539325842696,
])
def test_NoisyGaussian():
"""From the Kneedle manuscript"""
x, y = dg.noisy_gaussian(mu=50, sigma=10, N=1000, seed=42)
kl = KneeLocator(
x,
y,
S=1.0,
curve="concave",
interp_method="polynomial",
polynomial_degree=11,
online=True,
)
assert math.isclose(kl.knee, 63.0, rel_tol=1e-02)
def test_all_knees():
x, y = dg.bumpy()
kl = KneeLocator(x, y, curve="convex", direction="decreasing", online=True)
assert np.isclose(sorted(kl.all_elbows), [26, 31, 41, 46, 53]).all()
assert np.isclose(
sorted(kl.all_norm_elbows),
[
0.2921348314606742,
0.348314606741573,
0.4606741573033708,
0.5168539325842696,
0.5955056179775281,
],
).all()
def test_NoisyGaussian(interp_method):
"""From the Kneedle manuscript"""
x, y = dg.noisy_gaussian(mu=50, sigma=10, N=10000)
kl = KneeLocator(x, y, S=1.0, curve='concave', interp_method=interp_method)
assert math.isclose(kl.knee, 60.5, rel_tol=7.0)
def test_NoisyGaussian():
"""From the Kneedle manuscript"""
DG = DataGenerator()
x, y = DG.noisy_gaussian(mu=50, sigma=10, N=10000)
kl = KneeLocator(x, y, S=1.0, curve='concave')
assert math.isclose(kl.knee, 60.5, rel_tol=7.0)
def test_figure2():
"""From the kneedle manuscript"""
DG = DataGenerator()
x, y = DG.figure2()
kl = KneeLocator(x, y, S=1.0, curve='concave')
assert math.isclose(kl.knee, 0.22, rel_tol=0.05)
def test_concave_increasing(interp_method):
"""test a concave increasing function"""
x, y = dg.concave_increasing()
kn = KneeLocator(x, y, curve='concave', interp_method=interp_method)
assert kn.knee == 2
def test_convex_increasing(interp_method):
"""test a convex increasing function"""
x, y = dg.convex_increasing()
kl = KneeLocator(x, y, curve='convex', interp_method=interp_method)
assert kl.knee == 7
def test_interp_method():
"""Test that the interp_method argument is valid."""
x, y = dg.figure2()
with pytest.raises(ValueError):
kl = KneeLocator(x, y, interp_method="not_a_method")