Incomplete documentation of options

[jeffedstrom]

First off, thank you for your efforts with this and sharing the code. The base report is very good and a great tool in my tool box as a cyber security leader.

I am struggling to understand all the command switch or threat nodes I can populate. The example code:

import pyfair

Create using LEF (PERT), PL, (PERT), and SL (constant)

model1 = pyfair.FairModel(name="Regular Model 1", n_simulations=10_000)
model1.input_data('Loss Event Frequency', low=20, mode=100, high=900)
model1.input_data('Primary Loss', low=3_000_000, mode=3_500_000, high=5_000_000)
model1.input_data('Secondary Loss', constant=3_500_000)
model1.calculate_all()

Create another model using LEF (Normal) and LM (PERT)

model2 = pyfair.FairModel(name="Regular Model 2", n_simulations=10_000)
model2.input_data('Loss Event Frequency', mean=.3, stdev=.1)
model2.input_data('Loss Magnitude', low=2_000_000_000, mode=3_000_000_000, high=5_000_000_000)
model2.calculate_all()

Create metamodel by combining 1 and 2

mm = pyfair.FairMetaModel(name='My Meta Model!', models=[model1, model2])
mm.calculate_all()

Create report comparing 2 vs metamodel.

fsr = pyfair.FairSimpleReport([model1, mm])
fsr.to_html('output.html')

only gives you R, LEF, LM, PL, SL. How does one populate/call the others? Do you have an example code snippet that populates all of the sub items ?

[gitgitwhat]

I have to agree on the incompleteness (or at least my understanding) of the docs.

For example, the gamma/lambda parameter is mentioned in passing in the docs but don't make any mention on the scale. In one example it is set to 90 but if you look at the code, the default value is 4. So an explanation on how to use that effectively would be great.

It'd also be nice if all of the input/output functions were documented. For example, if you want to set parameters that require matrices like SLEF and SLEM then it appears like you need to use the input_multi_data function instead of just input_data but that's not discussed in the docs. You need to dig through the code to find an example.

Otherwise, great library. Thanks for your work on this.