# context("Running LIME")
# test_that("final gradient is below 0.001", {
# lh <- create_lh_list(vbk=0.21,
# linf=65,
# t0=-0.01,
# lwa=0.0245,
# lwb=2.79,
# S50=20,
# S95=26,
# selex_input="length",
# M50=34,
# M95=NULL,
# maturity_input="length",
# M=0.27,
# binwidth=1,
# CVlen=0.1,
# SigmaR=0.737,
# SigmaF=0.2,
# SigmaC=0.2,
# SigmaI=0.2,
# R0=1,
# qcoef=1e-5,
# start_ages=0,
# rho=0.43,
# nseasons=1)
# ## Demonstrate data generation option
# set.seed(143)
# true <- generate_data(modpath=NULL,
# data_avail="Index_Catch_LC",
# itervec=1,
# Fdynamics="Ramp",
# Rdynamics="AR",
# lh=lh,
# Nyears=20,
# Nyears_comp=10,
# comp_sample=200,
# init_depl=0.4)
# ## Data input components
# years <- true$years ## total years to model, can be 1:20 or 1998:2017
# LF <- true$LF ## length composition data, years along rows and length bin along columns. year names should match 'year' quantity, e.g. 11:20 or 2008:2017 (can be any years within years to model)
# C_t <- true$C_t ## (optional) catch data, with elements of vector named with the year observed, e.g. 1:20 or 1998:2017 (can be any years within years to model)
# I_t <- true$I_t ## (optional) abundance index, with elements of vector named with the year observed, e.g. 1:20 or 1998:2017 (can be any years within years to model)
# ## input data list
# data_LF <- list("years"=years, "LF"=LF) ## length comp only
# res <- run_LIME(modpath=NULL,
# lh=lh,
# input_data=data_LF,
# est_sigma="log_sigma_R",
# data_avail="LC")
# check <- res$df
# expect_false(all(is.na(Report)))
# expect_false(all(is.na(Sdreport)))
# expect_false(all(is.na(res$opt)))
# expect_true(max(abs(check[,1]))<0.001)
# })
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