Add runtime user-supplied relative secondary and absolute factor options to placalc + add tests for Post Loss Amplifcation components

[hchagani-oasislmf]

Add runtime user-supplied relative, secondary factor option to placalc

An optional, relative flat-factor can be specified by the user and applied to all loss factors with the command line argument -f. For example, to apply a relative secondary factor of 0.8 the following can be entered:

$ placalc -f 0.8 < gulcalc_output.bin > placalc_output.bin

The relative secondary factor must lie within the range [0, 1] and is applied to the deviation of the factor from 1. For example:

event_id	factor from model	relative factor from user	applied factor
1	1.10	0.8	1.08
2	1.20	0.8	1.16
3	1.00	0.8	1.00
4	0.90	0.8	0.92

Add runtime user-supplied absolute, uniform factor option to placalc

Alternatively, an absolute, uniform post loss amplification/reduction factor can be applied to all losses by the user with the command line argument -F. For example, to specify a uniform factor of 0.8 across all losses, the following can be entered:

$ placalc -F 0.8 < gulcalc_output.bin > placalc_output.bin

If specified, the loss factors from the model (those in lossfactors.bin) are ignored. This factor must be positive and is applied uniformly across all losses. For example:

event_id	factor from model	uniform factor from user	applied factor
1	1.10	0.8	0.8
2	1.20	0.8	0.8
3	1.00	0.8	0.8
4	0.90	0.8	0.8

The absolute, uniform factor is incompatible with the relative, secondary factor given above. Therefore, if both are given by the user, a warning is issued and the relative, secondary factor is ignored:

$ placalc -f 0.8 -F 0.8 < gulcalc_output.bin > placalc_output
WARNING: Relative secondary and absolute factors are incompatible
INFO: Ignoring relative secondary factor

Add tests for Post Loss Amplification (PLA) components

Acceptance tests for placalc, amplificationstobin, amplificationstocsv, lossfactorstobin and lossfactorstocsv have been included.

[hchagani-oasislmf]

Hi @johcarter. When you get the chance, would you mind checking the output for placalc makes sense? It looks good to me but it would be good to get a second pair of eyes on it. I've updated the acceptance tests to include placalc.

[hchagani-oasislmf]

Hi @johcarter. As discussed, I've added the option to specify an absolute, uniform factor across the losses. Would you mind taking another look when convenient please?

[hchagani-oasislmf]

Passes all tests: numbers look good within floating point errors. Ready to merge.