def _convert_pes_to_pos(hazard_curve, imls): """ For each IML (Intensity Measure Level) given compute the PoOs (Probability of Occurence) from the PoEs (Probability of Exceendance) defined in the given hazard curve. """ return collect(loop(_compute_pes_from_imls(hazard_curve, imls), lambda x, y: subtract(array(x), array(y))))
def _generate_curve(losses, probs_of_exceedance): """Generate a loss ratio (or loss) curve, given a set of losses and corresponding PoEs (Probabilities of Exceedance). This function is intended to be used internally. """ mean_losses = collect(loop(losses, lambda x, y: mean([x, y]))) return shapes.Curve(zip(mean_losses, probs_of_exceedance))
def _convert_pes_to_pos(hazard_curve, imls): """ For each IML (Intensity Measure Level) given compute the PoOs (Probability of Occurence) from the PoEs (Probability of Exceendance) defined in the given hazard curve. """ return collect( loop(_compute_pes_from_imls(hazard_curve, imls), lambda x, y: subtract(array(x), array(y))))
def _compute_imls(vuln_function): """ Computes Intensity Measure Levels considering the highest/lowest values a special case """ imls = vuln_function.imls # "special" cases for lowest part and highest part of the curve lowest_curve_value = imls[0] - ((imls[1] - imls[0]) / 2) highest_curve_value = imls[-1] + ((imls[-1] - imls[-2]) / 2) between_curve_values = collect(loop(imls, lambda x, y: mean([x, y]))) return [lowest_curve_value] + between_curve_values + [highest_curve_value]
def _split_loss_ratios(loss_ratios, steps=None): """Split the loss ratios, producing a new set of loss ratios. Keyword arguments: steps -- the number of steps we make to go from one loss ratio to the next. For example, if we have [1.0, 2.0]: steps = 1 produces [1.0, 2.0] steps = 2 produces [1.0, 1.5, 2.0] steps = 3 produces [1.0, 1.33, 1.66, 2.0] """ if steps is None: steps = STEPS_PER_INTERVAL splitted_ratios = set() for interval in loop(array(loss_ratios), linspace, steps + 1): splitted_ratios.update(interval) return array(sorted(splitted_ratios))
def _compute_imls(vuln_function): """ Compute the mean IMLs (Intensity Measure Level) for the given vulnerability function. """ imls = vuln_function.imls # "special" cases for lowest part and highest part of the curve lowest_curve_value = imls[0] - ((imls[1] - imls[0]) / 2) # if the calculated lowest_curve_value goes < 0 we have to force the 0 # IMLs have to be >= 0 if lowest_curve_value < 0: lowest_curve_value = 0 highest_curve_value = imls[-1] + ((imls[-1] - imls[-2]) / 2) between_curve_values = collect(loop(imls, lambda x, y: mean([x, y]))) return [lowest_curve_value] + between_curve_values + [highest_curve_value]
def _convert_pes_to_pos(hazard_curve, imls): """ Computes the probability occurences from the probability exceedances """ return collect(loop(_compute_pes_from_imls(hazard_curve, imls), lambda x, y: subtract(array(x), array(y))))