def test_loss_curve_computation(self):
loss_ratio_curve = shapes.Curve([(0.1, 1.0), (0.2, 2.0), (0.3, 3.0)])
loss_curve = common.compute_loss_curve(loss_ratio_curve, ASSET_VALUE)
self.assertEqual(shapes.Curve([(0.1 * ASSET_VALUE, 1.0),
(0.2 * ASSET_VALUE, 2.0), (0.3 * ASSET_VALUE, 3.0)]),
loss_curve)
def test_loss_curve_computation(self):
loss_ratio_curve = shapes.Curve([(0.1, 1.0), (0.2, 2.0), (0.3, 3.0)])
loss_curve = common.compute_loss_curve(loss_ratio_curve, ASSET_VALUE)
self.assertEqual(shapes.Curve([(0.1 * ASSET_VALUE, 1.0),
(0.2 * ASSET_VALUE, 2.0), (0.3 * ASSET_VALUE, 3.0)]),
loss_curve)
def compute_loss_curve(self, point, loss_ratio_curve, asset):
"""
Computes the loss ratio and store it in kvs to provide
data to the @output decorator which does the serialization
in the RiskJobMixin, more details inside
openquake.risk.job.RiskJobMixin -- for details see
RiskJobMixin._write_output_for_block and the output decorator
:param point: the point of the grid we want to compute
:type point: :py:class:`openquake.shapes.GridPoint`
:param loss_ratio_curve: the loss ratio curve
:type loss_ratio_curve: :py:class `openquake.shapes.Curve`
:param asset: the asset for which to compute the loss curve
:type asset: :py:class:`dict` as provided by
:py:class:`openquake.parser.exposure.ExposurePortfolioFile`
"""
loss_curve = compute_loss_curve(loss_ratio_curve, asset['assetValue'])
loss_key = kvs.tokens.loss_curve_key(self.job_id, point.row,
point.column, asset['assetID'])
kvs.set(loss_key, loss_curve.to_json())
def compute_loss_curve(self, point, loss_ratio_curve, asset):
"""
Computes the loss ratio and store it in kvs to provide
data to the @output decorator which does the serialization
in the RiskJobMixin, more details inside
openquake.risk.job.RiskJobMixin -- for details see
RiskJobMixin._write_output_for_block and the output decorator
:param point: the point of the grid we want to compute
:type point: :py:class:`openquake.shapes.GridPoint`
:param loss_ratio_curve: the loss ratio curve
:type loss_ratio_curve: :py:class `openquake.shapes.Curve`
:param asset: the asset for which to compute the loss curve
:type asset: :py:class:`dict` as provided by
:py:class:`openquake.parser.exposure.ExposurePortfolioFile`
"""
loss_curve = compute_loss_curve(loss_ratio_curve, asset['assetValue'])
loss_key = kvs.tokens.loss_curve_key(self.job_id, point.row,
point.column, asset['assetID'])
kvs.set(loss_key, loss_curve.to_json())
def test_a_loss_curve_is_not_defined_when_the_asset_is_invalid(self):
self.assertEqual(common.compute_loss_curve(
shapes.Curve([(0.1, 1.0), (0.2, 2.0), (0.3, 3.0)]),
INVALID_ASSET_VALUE),
shapes.EMPTY_CURVE)
def test_empty_loss_curve(self):
self.assertEqual(common.compute_loss_curve(shapes.EMPTY_CURVE, None),
shapes.EMPTY_CURVE)
def test_a_loss_curve_is_not_defined_when_the_asset_is_invalid(self):
self.assertEqual(common.compute_loss_curve(
shapes.Curve([(0.1, 1.0), (0.2, 2.0), (0.3, 3.0)]),
INVALID_ASSET_VALUE),
shapes.EMPTY_CURVE)
def test_empty_loss_curve(self):
self.assertEqual(common.compute_loss_curve(shapes.EMPTY_CURVE, None),
shapes.EMPTY_CURVE)