def test_ordinate_diffs(self):
hazard_curve = Curve(
[(0.01, 0.99), (0.08, 0.96), (0.17, 0.89), (0.26, 0.82), (0.36, 0.70), (0.55, 0.40), (0.70, 0.01)]
)
expected_pos = [0.0673, 0.1336, 0.2931, 0.4689]
pes = [0.05, 0.15, 0.3, 0.5, 0.7]
self.assertTrue(allclose(expected_pos, hazard_curve.ordinate_diffs(pes), atol=0.00005))
def test_clip_low_imls_many_values(self):
"""
Test :py:method:`openquake.risklib.range.Curve.range_clip` to
ensure that low values are clipped to the lowest valid value in the
IML range.
"""
expected_imls = numpy.array([0.005, 0.005, 0.005])
test_input = [0.0049, 0.00001, 0.002]
numpy.testing.assert_allclose(
expected_imls, Curve.range_clip(test_input, self.TEST_IMLS))
# same test, except with a numpy.array-type input:
numpy.testing.assert_allclose(
expected_imls,
Curve.range_clip(numpy.array(test_input), self.TEST_IMLS))
def test_clip_imls_with_many_normal_values(self):
"""
Test :py:method:`openquake.risklib.range.Curve.range_clip` to
ensure that normal values (values within the defined IML range) are not
changed.
"""
valid_imls = [0.005, 0.0269, 0.0051, 0.0268]
expected_result = numpy.array(valid_imls)
numpy.testing.assert_allclose(
expected_result,
Curve.range_clip(valid_imls, self.TEST_IMLS))
# same test, except with numpy.array-type input:
numpy.testing.assert_allclose(
expected_result,
Curve.range_clip(numpy.array(valid_imls), self.TEST_IMLS))
def test_clip_high_iml_values(self):
"""
Test :py:method:`openquake.risklib.range.Curve.range_clip` to
ensure that the high values are clipped to the highest valid value in
the IML range.
"""
self.assertEqual(0.0269, Curve.range_clip(0.027, self.TEST_IMLS))
def test_clip_low_iml_values(self):
"""
Test :py:method:`openquake.risklib.range.Curve.range_clip` to
ensure that low values are clipped to the lowest valid value in the
IML range.
"""
self.assertEqual(0.005, Curve.range_clip(0.0049, self.TEST_IMLS))
def test_compute_loss_ratio_curve(self):
hazard_curve = [
(0.01, 0.99), (0.08, 0.96),
(0.17, 0.89), (0.26, 0.82),
(0.36, 0.70), (0.55, 0.40),
(0.70, 0.01)]
imls = [0.1, 0.2, 0.4, 0.6]
covs = [0.5, 0.3, 0.2, 0.1]
loss_ratios = [0.05, 0.08, 0.2, 0.4]
vulnerability_function = scientific.VulnerabilityFunction(
imls, loss_ratios, covs, "LN")
# pre computed values just use one intermediate
# values between the imls, so steps=2
lrem = [[1., 1., 1., 1.],
[8.90868149e-01, 9.99932030e-01, 1., 1.],
[4.06642478e-01, 9.27063668e-01, 1., 1.],
[2.14297309e-01, 7.12442306e-01, 9.99999988e-01, 1.],
[1.09131851e-01, 4.41652761e-01, 9.99997019e-01, 1.],
[7.84971008e-03, 2.00321301e-02, 9.55620783e-01, 1.],
[7.59869969e-04, 5.41393717e-04, 4.60560758e-01, 1.],
[2.79797605e-05, 1.66547090e-06, 1.59210054e-02,
9.97702369e-01],
[1.75697664e-06, 9.04938835e-09, 1.59710253e-04,
4.80110732e-01],
[2.89163471e-09, 2.43138842e-14, 6.60395072e-11,
7.56938368e-09],
[2.38464803e-11, 0., 1.11022302e-16, 0.]]
loss_ratio_curve = scientific.classical(
vulnerability_function, lrem, hazard_curve, 2)
expected_curve = Curve([
(0.0, 0.96), (0.025, 0.96),
(0.05, 0.91), (0.065, 0.87),
(0.08, 0.83), (0.14, 0.75),
(0.2, 0.60), (0.3, 0.47),
(0.4, 0.23), (0.7, 0.00),
(1.0, 0.00)])
for x_value in expected_curve.abscissae:
numpy.testing.assert_allclose(
expected_curve.ordinate_for(x_value),
loss_ratio_curve.ordinate_for(x_value), atol=0.005)
def test_clip_iml_with_normal_value(self):
"""
Test :py:method:`openquake.risklib.range.Curve.range_clip` to
ensure that normal values (values within the defined IML range) are not
changed.
"""
valid_imls = numpy.array([0.005, 0.0051, 0.0268, 0.0269])
for i in valid_imls:
self.assertEqual(i, Curve.range_clip(i, valid_imls))
def test_can_construct_with_unordered_values(self):
curve = Curve([(0.5, 1.0), (0.4, 2.0), (0.3, 2.0)])
self.assertEqual(1.0, curve.ordinate_for(0.5))
self.assertEqual(2.0, curve.ordinate_for(0.4))
self.assertEqual(2.0, curve.ordinate_for(0.3))
def test_can_pickle(self):
curve = Curve([(0.5, 1.0), (0.4, 2.0), (0.3, 2.0)])
curve.ordinate_for(0.35)
curve.abscissa_for(1.35)
self.assertEqual(pickle.loads(pickle.dumps(curve)), curve)
