oasislmf.pytools.gul.core

This file contains the core mathematical functions used in gulpy.

Functions

get_gul(bin_from, bin_to, bin_mean, prob_from, ...)	Compute the ground-up loss using linear or quadratic interpolaiton if necessary.
setmaxloss(losses)	Set maximum losses.
split_tiv_classic(gulitems, tiv)	Split the total insured value (TIV). If the total loss of all the items
split_tiv_multiplicative(gulitems, tiv)	Split the total insured value (TIV) using a multiplicative formula for the
compute_mean_loss(tiv, prob_to, bin_mean, bin_count, ...)	Compute the mean ground-up loss and some properties.

Module Contents

oasislmf.pytools.gul.core.get_gul(bin_from, bin_to, bin_mean, prob_from, prob_to, rval, tiv)

Compute the ground-up loss using linear or quadratic interpolaiton if necessary.

Args:

bin_from (oasis_float): bin minimum damage. bin_to (oasis_float): bin maximum damage. bin_mean (oasis_float): bin mean damage (interpolation column in damagebins file). prob_from (oasis_float): bin minimum probability prob_to (oasis_float): bin maximum probability rval (float64): the random cdf value. tiv (oasis_float): total insured value.

Returns:

float64: the computed ground-up loss

oasislmf.pytools.gul.core.setmaxloss(losses)

Set maximum losses. For each sample idx, find the maximum loss across all items and set to zero all the losses smaller than the maximum loss. If the maximum loss occurs in N items, then set the loss in all these items as the maximum loss divided by N.

Args:

losses (numpy.array[oasis_float]): losses for all item_ids and sample idx.

Returns:

numpy.array[oasis_float]: losses for all item_ids and sample idx.

oasislmf.pytools.gul.core.split_tiv_classic(gulitems, tiv)

Split the total insured value (TIV). If the total loss of all the items in gulitems exceeds the total insured value, re-scale the losses in the same proportion to the losses.

Args:

gulitems (numpy.array[oasis_float]): array containing losses of all items. tiv (oasis_float): total insured value.

oasislmf.pytools.gul.core.split_tiv_multiplicative(gulitems, tiv)

Split the total insured value (TIV) using a multiplicative formula for the total loss as tiv * (1 - (1-A)*(1-B)*(1-C)…), where A, B, C are damage ratios computed as the ratio between a sub-peril loss and the tiv. Sub-peril losses in gulitems are always back-allocated proportionally to the losses.

Args:

gulitems (numpy.array[oasis_float]): array containing losses of all items. tiv (oasis_float): total insured value.

oasislmf.pytools.gul.core.compute_mean_loss(tiv, prob_to, bin_mean, bin_count, max_damage_bin_to)

Compute the mean ground-up loss and some properties.

Args:

tiv (oasis_float): total insured value. prob_to (numpy.array[oasis_float]): bin maximum probability bin_mean (numpy.array[oasis_float]): bin mean damage (interpolation column in damagebins file). bin_count (int): number of bins. max_damage_bin_to (oasis_float): maximum damage value (i.e., bin_to of the last damage bin).

Returns:

float64, float64, float64, float64: mean ground-up loss, standard deviation of the ground-up loss,

chance of loss, maximum loss