sample.txt

usage: job sample [-h]
                  [--lhs-criterion {center,c,maximin,m,centermaximin,cm,correlation,corr}]
                  [--lhs_iterations LHS_ITERATIONS] [-o OUT] [-N SIZE]
                  [--seed SEED] [--method {montecarlo,lhs}]
                  [NAME=DIST [NAME=DIST ...]]

Sample prior parameter distribution

optional arguments:
  -h, --help            show this help message and exit
  -o OUT, --out OUT     output parameter file
  -N SIZE, --size SIZE  Sample size
  --seed SEED           random seed, for reproducible results (default to
                        None)
  --method {montecarlo,lhs}
                        sampling method (default=lhs)

prior distribution of model parameters:
  NAME=DIST             Prior parameter defintion as NAME=SPEC. SPEC specifies
                        param values or distribution. Discrete parameter
                        values can be provided as a comma-separated list
                        `VALUE[,VALUE...]` or a range `START:STOP:N`. A
                        distribution is provided as `TYPE?ARG,ARG[,ARG,...]`.
                        Pre-defined `U?min,max` (uniform) and `N?mean,sd`
                        (normal) or any scipy.stats distribution as
                        TYPE?[SHP,]LOC,SCALE.

Latin hypercube sampling:
  --lhs-criterion {center,c,maximin,m,centermaximin,cm,correlation,corr}
                        randomized by default
  --lhs_iterations LHS_ITERATIONS