adding verbose to print, so that script can be quiet

src/prediction/abundance_prediction.R

@@ -46,7 +46,9 @@ option_list <- list (
               dest = "year_to_predict",
               type = "integer",
               help = "year of the survey years (1994:2015) to predict abundance to",
-              metavar = "2015")
+              metavar = "2015"),
+  make_option(c("-v", "--verbose"), dest = "verbose_script", action = "store_true",
+              default = TRUE, help = "print all intermediate results")
 )
 
 options <- parse_args(OptionParser(option_list=option_list))
@@ -82,22 +84,30 @@ if (!(options$year_to_predict %in% year_to_predict_possibilities)) {
 }
 
 
+# is verbose?
+is_verbose <- options$verbose_script
 # input directory
+
+
 indir <- options$input_directory
-print(paste("indir", indir))
+if(is_verbose){print(paste("indir", indir))}
 
 # input directory
 indir_predictors <- options$pred_input_directory
-print(paste("indir_predictors", indir_predictors))
+if(is_verbose){print(paste("indir_predictors", indir_predictors))}
 
 # directory in which output is written
 outdir <- options$output_directory
-print(paste("outdir", outdir))
-
+if(is_verbose){print(paste("outdir", outdir))}
 
 year_to_predict <- as.numeric(options$year_to_predict )
-print(paste("year to predict " , year_to_predict))
+if(is_verbose){print(paste("year to predict " , year_to_predict))}
 
+
+exclude_year <- as.numeric(options$exclude_year)
+if(is_verbose){print(paste("exclude year", exclude_year))}
+
+if(is_verbose){print(paste(Sys.time(), "0. start run"))}
 #------------------------#
 # command line arguments #
 #------------------------#
@@ -113,11 +123,10 @@ crs_aea <- "+proj=aea +lat_1=7 +lat_2=-32 +lat_0=-15 +lon_0=125 +x_0=0
 #-------------------------------#
 # Load functions
 source(file.path(indir_fun, "generic/path.to.current.R"))
-print("function loaded")
 
 # Load coefficients and weights
 abundMod_results_path <- path.to.current(indir, "abundMod_results", "rds" )
-print(paste("this is abundMod_results_path:", abundMod_results_path))
+if(is_verbose){print(paste("this is abundMod_results_path:", abundMod_results_path))}
 abundMod_results <- readRDS(abundMod_results_path)
 # exclude the first column, which contains models, exclude the coefficient of the
 # autocorellation term and the weighted aic of the model
@@ -151,21 +160,20 @@ predictor_names <- predictor_names_coeffs[!grepl("I(*)", predictor_names_coeffs)
 #----------------------------#
 # Load and prepare estimates #
 #----------------------------#
-print(paste("these are predictor names: ", predictor_names))
+if(is_verbose){print(paste("these are predictor names: ", predictor_names))}
 predictors_path <- path.to.current(indir_predictors, paste0("predictors_abundance_",
                                                  year_to_predict),"rds")
-print(paste("this is predictors path", predictors_path))
+if(is_verbose){print(paste("this is predictors path", predictors_path))}
 predictors <- readRDS(predictors_path) %>%
  dplyr::filter(predictor %in% predictor_names) %>%
     dcast(id + z_year ~ predictor,  value.var = "scaled_value")
 
 predictors$year <- predictors$z_year
 predictors$z_year <- NULL
-str(predictors)
-
+if(is_verbose){str(predictors)}
 
+if(is_verbose){print(paste("this is nrow predictors", nrow(predictors)))}
 
-print(paste("this is nrow predictors", nrow(predictors)))
 #--------------------------#
 # PREDICTION FOR each year #
 #--------------------------#
@@ -188,7 +196,7 @@ names(predictor_estimates) <- c("intercept", predictor_names,
 # but takes a bit longer (52s, to 35s for 100 rows)
 ## PLUS PAY ATTENTION, IF PREDICTIONS NOT SAME NROW--> VALUES GET RECYCLED
 
-print(paste("1. start pred_per_cell", Sys.time()))
+if(is_verbose){print(paste("1. start pred_per_cell", Sys.time()))}
 pred_per_cell <- foreach(i = 1:nrow(predictor_estimates), .combine = c)  %dopar% {
 # pred_per_cell <- foreach(i = 1:100, .combine = c)  %dopar% {
 t_predictor_estimates <- t( predictor_estimates[i, ])
@@ -199,7 +207,7 @@ pred_estimates_sum <- apply(pred_estimates_wcoeffs, 1, sum)
 return(exp(pred_estimates_calc))
 }
 
-print(paste(Sys.time(), "2. finished dopar loop"))
+if(is_verbose){print(paste(Sys.time(), "2. finished dopar loop"))}
 
 # is this correct -> ????
 pred_per_cell <- as.data.frame(cbind(predictors$id, pred_per_cell))
@@ -208,14 +216,18 @@ names(pred_per_cell) <- c("id", "abundance_pred")
 # exclude NAN
 pred_per_cell <- pred_per_cell[!is.nan(pred_per_cell$abundance_pred), ]
 
+if (!is.na(exclude_year)){paste("year_to_exclude:", exclude_year)}
 
 print(paste(Sys.time(), "sum predicted for ", year_to_predict,
             sum(pred_per_cell$abundance_pred)))
-print(paste(Sys.time(), "range predicted for ", year_to_predict,
+print(paste(Sys.time(),
+            "range predicted for ", year_to_predict,
             range(pred_per_cell$abundance_pred)))
-print(paste(Sys.time(), "density predicted for ", year_to_predict,
+print(paste(Sys.time(),
+            "density predicted for ", year_to_predict,
             mean(pred_per_cell$abundance_pred)))
-print(paste(Sys.time(), "nr of values over 10 ", year_to_predict,
+print(paste(Sys.time(),
+            "nr of values over 10 ", year_to_predict,
             sum(pred_per_cell$abundance_pred > 10)))
 
 saveRDS(pred_per_cell,
@@ -229,7 +241,7 @@ save.image(file.path(outdir, "image_before_map.RData"))
 #-----------------------#
 # convert output to map #
 #-----------------------#
-print(paste(Sys.time(), "3. Start making map"))
+if(is_verbose){print(paste(Sys.time(), "3. Start making map"))}
 
 geography_grid_path <- path.to.current(indir_predictors,
                                        paste0("geography_", year_to_predict), "rds")
@@ -271,4 +283,4 @@ save.image(file.path(outdir, paste0("abundance_pred_image_", year_to_predict, "_
 
 
 
-print(paste(Sys.time(), "4. wrote results and done :-)"))
+if(is_verbose){print(paste(Sys.time(), "4. wrote results and done :-)"))}