From 51ae407526d968f617f6f65d71e22e8b1618e804 Mon Sep 17 00:00:00 2001
From: bleutner <benjamin.leutner@uni-wuerzburg.de>
Date: Thu, 6 Oct 2016 13:38:26 +0200
Subject: [PATCH] fix docu

---
 R/pifMatch.R    | 14 ++++++++------
 man/pifMatch.Rd | 14 ++++++++------
 2 files changed, 16 insertions(+), 12 deletions(-)

diff --git a/R/pifMatch.R b/R/pifMatch.R
index 45c0a00f..c0d57d27 100755
--- a/R/pifMatch.R
+++ b/R/pifMatch.R
@@ -30,7 +30,6 @@
 #' }
 #' @export 
 #' @examples 
-#' library(gridExtra)
 #' library(raster)
 #' 
 #' ## Import Landsat example data
@@ -41,17 +40,20 @@
 #' lsat_b <- log(lsat)  
 #' ## Run pifMatch and return similarity layer, invariant features mask and models
 #' lsat_b_adj <- pifMatch(lsat_b, lsat, returnPifMap = TRUE, returnSimMap = TRUE, returnModels = TRUE)
-#' grid.arrange(
-#' ggR(lsat_b_adj$simMap, geom_raster = TRUE) ,
-#' ggR(lsat_b_adj$pifMap),
-#' ncol=2)
 #' 
+#' ## Pixelwise similarity
+#' ggR(lsat_b_adj$simMap, geom_raster = TRUE)
+#' 
+#' ## Pesudo invariant feature mask 
+#' ggR(lsat_b_adj$pifMap)
+#' 
+#' ## Histograms of changes
 #' par(mfrow=c(1,3))
 #' hist(lsat_b[[1]], main = "lsat_b")
 #' hist(lsat[[1]], main = "reference")
 #' hist(lsat_b_adj$img[[1]], main = "lsat_b adjusted")
 #' 
-#' ## Model summary for first band 
+#' ## Model summary for first band
 #' summary(lsat_b_adj$models[[1]])
 pifMatch <- function(img, ref, method = "cor", quantile = 0.95, returnPifMap = TRUE, returnSimMap = TRUE, returnModels = FALSE){
 	if(nlayers(img)!=nlayers(ref) | nlayers(img) <= 1) stop("Both images need at least two corresponding bands and must have the same number of bands.", call.=FALSE)
diff --git a/man/pifMatch.Rd b/man/pifMatch.Rd
index c05c0236..102a2ec4 100644
--- a/man/pifMatch.Rd
+++ b/man/pifMatch.Rd
@@ -47,7 +47,6 @@ The threshold is defined as a similarity quantile. Setting \code{quantile=0.95}
 Model fitting is performed with simple linear models (\code{\link[stats]{lm}}); fitting one model per layer.
 }
 \examples{
-library(gridExtra)
 library(raster)
 
 ## Import Landsat example data
@@ -58,17 +57,20 @@ data(lsat)
 lsat_b <- log(lsat)  
 ## Run pifMatch and return similarity layer, invariant features mask and models
 lsat_b_adj <- pifMatch(lsat_b, lsat, returnPifMap = TRUE, returnSimMap = TRUE, returnModels = TRUE)
-grid.arrange(
-ggR(lsat_b_adj$simMap, geom_raster = TRUE) ,
-ggR(lsat_b_adj$pifMap),
-ncol=2)
 
+## Pixelwise similarity
+ggR(lsat_b_adj$simMap, geom_raster = TRUE)
+
+## Pesudo invariant feature mask 
+ggR(lsat_b_adj$pifMap)
+
+## Histograms of changes
 par(mfrow=c(1,3))
 hist(lsat_b[[1]], main = "lsat_b")
 hist(lsat[[1]], main = "reference")
 hist(lsat_b_adj$img[[1]], main = "lsat_b adjusted")
 
-## Model summary for first band 
+## Model summary for first band
 summary(lsat_b_adj$models[[1]])
 }