From 619198a1201d39bcb3d80d54ac355ace0c20aecf Mon Sep 17 00:00:00 2001
From: Maria Voigt <maria.voigt@idiv.de>
Date: Sun, 26 Nov 2017 19:43:35 +0100
Subject: [PATCH] some cosmetic fixes
---
src/prediction/abundance_prediction.R | 13 ++-----------
1 file changed, 2 insertions(+), 11 deletions(-)
diff --git a/src/prediction/abundance_prediction.R b/src/prediction/abundance_prediction.R
index a2fa220..a7c43fe 100644
--- a/src/prediction/abundance_prediction.R
+++ b/src/prediction/abundance_prediction.R
@@ -116,7 +116,7 @@ exclude_year <- as.numeric(options$exclude_year)
if(is_verbose){print(paste("exclude year", exclude_year))}
focal_change_predictor <- as.numeric(options$focal_change_predictor)
-if(is_verbose){print(paste("focal_change_predictor", focal_change_predictor))}
+if(is_verbose){print(paste("focal_change_predictor", focal_change_predictor))}
if(is_verbose){print(paste(Sys.time(), "0. start run"))}
#------------------------#
@@ -162,17 +162,9 @@ coeffs[is.na(coeffs) == T] <- 0
# Load estimates for observation and grid
# these are the predictors that will be used in the prediction
-# THEY MUST BE IN THE ORDER IN WHICH THEY APPEAR IN THE COEFFICIENTS
-# CODE THIS
# here only separate after first _
predictor_names_coeffs <- gsub("coeff_","", names(coeffs))
-#UNDERSTAND HERE WHAT IS HAPPENING
-#interaction_terms_names <- predictor_names_coeffs[predictor_names_coeffs %in%
-# paste0("year:", predictor_names_coeffs)]
-#interaction_terms_names <- gsub("year:", "", interaction_terms_names)
-#quadratic_terms_names <- predictor_names_coeffs[predictor_names_coeffs %in%
-# paste0("I(", predictor_names_coeffs, "^2)")]
-#quadratic_terms_names <- gsub("I\\(|\\^2\\)", "", quadratic_terms_names )
+
quadratic_terms_names <- c("rain_dry")
predictor_names_coeffs <- predictor_names_coeffs[predictor_names_coeffs != "(Intercept)"]
@@ -287,7 +279,6 @@ names(predictor_estimates) <- c("intercept", predictor_names,
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, ])
pred_estimates_wcoeffs <- data.frame(mapply(`*`, coeffs, t_predictor_estimates, SIMPLIFY = F))
pred_estimates_sum <- apply(pred_estimates_wcoeffs, 1, sum)
--
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