This program makes initial models using a (kind of) stochastic gradient descent approach. It is recommended that the box size of particles is around 100. 
	[prog] --ptcls <particle stack> 

Option Type Description
--version None show program's version number and exit
--path str Path to write initial model output. Default is initmodel_XX
--ptcls str Class average or particles input.
--sym str Specify symmetry - choices are: c<n>, d<n>, h<n>, tet, oct, icos
--batchsize int Batch size of stochastic gradient desent. N particles are randomly selected to generate an initial model at each step.
--niter int Number of iterations
--ntry int The number of different initial models to generate in search of a good one
--learnrate float Learning rate. i.e. how much the initial model changes toward the gradient direction in each iteration. Range from 0.0~1.0. Default is 0.3
--lrdecay float Learning rate multiplier after each iteration.
--addnoise float Add noise on particles at each iteration. Stablize convergence for some reason.
--shrink int shrinking factor
--setsf str
--ref str
--writetmp None Write output for each iteration
--fullcov None Assume the input particles covers most of the orientation of the model. This gives better performance when the model is relatively feature-less, but is more likely to fail when there are incorrect particles in the input.
--threads int threads
--verbose, -v int Verbose
--targetres float Target resolution