restore RNG state after generating random numbers

[m-bossart]

For generating datasets from PSID simulations it is useful to rely on a seed and random number generator to randomly select a perturbation. Currently, it is not possible to evaluate the same set of randomly selected perturbations for systems of different size (# of states) because of the call to the random number generator within a PSID simulation. This PR will reset the state of the random number generator so the state is not changed during a simulation.

[github-actions]

Performance Results

Version	Precompile Time
Main	4.553962067
This Branch	4.770556177

Version	Run Time
Main-Build ResidualModel	11.410039083
Main-Execute ResidualModel	30.330661418
Main-Build MassMatrixModel	0.995980207
Main-Execute MassMatrixModel	303.916684105
This Branch-Build ResidualModel	11.396617335
This Branch-Execute ResidualModel	30.338091671
This Branch-Build MassMatrixModel	0.995813355
This Branch-Execute MassMatrixModel	287.937015293

ResidualModel and MassMatrixModel performance results should be compared between versions and not between models due to the execution order of the tests

[codecov]

Codecov Report

Merging #353 (ad99c83) into main (a51524d) will decrease coverage by 0.07%.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #353      +/-   ##
==========================================
- Coverage   87.29%   87.23%   -0.07%     
==========================================
  Files          65       65              
  Lines        8986     8990       +4     
==========================================
- Hits         7844     7842       -2     
- Misses       1142     1148       +6     

Flag	Coverage Δ
unittests	87.23% <100.00%> (-0.07%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files Changed	Coverage Δ
src/base/jacobian.jl	96.00% <100.00%> (+0.22%)	⬆️

... and 2 files with indirect coverage changes

[jd-lara]

This shouldn't affect the results of the simulation. Can you explain better what you are seeing that this PR is supposed to correct?

[m-bossart]

I would like these two to give the same result:

Random.seed!(1)
print(rand())

Random.seed!(1)
Simulation(MassMatrixModel, sys, pwd(), (0.0,1.0)
print(rand())