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Commit 31a90b8e authored by Maria Voigt's avatar Maria Voigt
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merging from laptop onto cluster

parents fd761e1c 697cf6eb
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......@@ -34,18 +34,18 @@ option_list <- list (
dest = "ESW_aerial",
type = "double",
help = "aerial effective strip width"),
make_option("--exclude-year", dest = "exclude_year", type = "integer",
default = NA, help = "year to exclude", metavar = "2015"),
make_option("--exclude-grid", dest = "exclude_grid", type = "integer",
default = NA, help = "index of grid-cells to exclude", metavar = "1"),
make_option("--exclude-random", dest = "exclude_random", type = "integer",
default = NA, help = "randomly excluding the percentage given",
metavar = "20"),
make_option("--include-aerial",
dest = "include_aerial", action="store_true",
default=FALSE, help="include aerial transects"),
make_option("--stability", action="store_true", default=FALSE,
help="do stability analysis"),
make_option("--exclude-year", dest = "exclude_year", type = "integer",
default = NA, help = "year to exclude", metavar = "2015"),
make_option("--exclude-grid", dest = "exclude_grid", type = "integer",
default = NA, help = "index of grid-cells to exclude", metavar = "1"),
make_option("--exclude-grid-random", dest = "exclude_grid_rand", type = "integer",
default = NA, help = "exclude the given percent randomly",
metavar = "10"),
make_option(c("-q", "--quiet"), dest = "verbose_script",
action = "store_false",
default = TRUE,
......@@ -98,8 +98,8 @@ if(is_verbose){print(paste("exclude year", exclude_year))}
exclude_grid <- options$exclude_grid
if(is_verbose){print(paste("exclude grid", exclude_grid))}
exclude_random <- options$exclude_random
if(is_verbose){print(paste("exclude random", exclude_random))}
exclude_grid_rand <- options$exclude_grid_rand
if(is_verbose){print(paste("exclude grid random", exclude_grid_rand))}
#---------#
# Globals #
......@@ -293,19 +293,19 @@ if (!is.na(exclude_grid)){
predictors_obs <- predictors_obs[predictors_obs$grid_id != exclude_grid, ]
}
if (!is.na(exclude_random)){
# choose X percent random grid_cells from all cells
# save them in predictors_excluded random and exclude them from the others
ids_to_exclude <- sample(predictors_obs$id,
size = nrow(predictors_obs)/100 * exclude_random,
if (!is.na(exclude_grid_rand)){
#bin_id --> randomly exclude percentage given in grid_rand
ids_to_exclude <- sample(predictors_obs$bin_id,
size = nrow(predictors_obs)/100 * exclude_grid_rand,
replace = FALSE)
predictors_excluded_random <- predictors_obs[predictors_obs$id %in% ids_to_exclude, ]
predictors_obs <- predictors_obs[!predictors_obs$id %in% ids_to_exclude, ]
predictors_excluded_grid_rand <- predictors_obs[predictors_obs$bin_id %in% ids_to_exclude, ]
predictors_obs <- predictors_obs[!predictors_obs$bin_id %in% ids_to_exclude, ]
}
# also we increase maxit for the two cases,
# because then slightly less data
if (is.na(exclude_grid) & is.na(exclude_year)){
if (is.na(exclude_grid) & is.na(exclude_year) & is.na(exclude_grid_rand)){
nr_maxit <- 250}else{
nr_maxit <- 500}
if(is_verbose){ print(paste("3. start making all_model_terms", Sys.time()))}
......@@ -402,7 +402,7 @@ if(is_verbose){print(paste("8. Start running models", Sys.time()))}
results_res <- foreach(i = 1:nrow(all_model_terms),
.combine = rbind) %dopar%{
# make results dataframe
if (is.na(exclude_year) & is.na(exclude_grid) & is.na(exclude_random)){
if (is.na(exclude_year) & is.na(exclude_grid) & is.na(exclude_grid_rand)){
result <- as.data.frame(matrix(NA, ncol = 3 *
length(model_terms) + 5,
nrow = 1))
......@@ -491,13 +491,14 @@ results_res <- foreach(i = 1:nrow(all_model_terms),
result[ , "R2_cross"] <- summary(cross_lm_grid)$r.squared
}
if (!is.na(exclude_random)){
predictors_excluded_random_pred <- predictors_excluded_random
predictors_excluded_random_pred$offset_term <- 0
prediction_transect_excluded_random <- predict.glm(res,
newdata = predictors_excluded_random,
if (!is.na(exclude_grid_rand)){
predictors_excluded_grid_pred <- predictors_excluded_grid_rand
predictors_excluded_grid_pred$offset_term <- 0
prediction_transect_excluded_grid <- predict.glm(res,
newdata = predictors_excluded_grid_rand,
type = "response")
cross_lm_random = lm(log(predictors_excluded_random$ou_dens+ 1) ~
cross_lm_random = lm(log(predictors_excluded_grid_rand$ou_dens+ 1) ~
log(prediction_transect_excluded_random + 1))
result[ , "R2_cross"] <- summary(cross_lm_random)$r.squared
......
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