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.Rhistory

+devtools::create_description()
+usethis::use_description()
+library(rterahertz)
+library(rterahertz)
+?extrairematligne_even
+m <- matrix(0, nrow=10, ncol = 10)
+m_odd <- extrairematligne_odd
+m_odd <- extrairematligne_odd(m)
+?extrairematligne_odd
+?extrairematligne_even
+?extrairematligne_odd
+m_odd <- extrairematligne_odd(m)
+?extractematline_even
+m_odd <- extractematline_even(m)
+m_odd <- extractmatline_even(m)
+library(rterahertz)
+m_odd <- extractmatline_even(m)
+library(rterahertz)
+m_odd <- extractmatline_even(m)
+?extractmatline_even
+library(rterahertz)
+m_odd <- extractmatline_even(m)
+?rterahertz
+library(rterahertz)
+?extractmatline_even
+m_odd <- extractmatline_even(m)
+library(rterahertz)
+library(rterahertz)
+?extractmatline_even
+library(rterahertz)
+library(rterahertz)
+rnorm(10, mean = 0, sd = 1)
+matrix(rnorm(100, mean = 0, sd = 1), nrow = 10, ncol = 10)
+library(rterahertz)

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+#' Function for visualizing the THz image matrix using plotly
+#'
+#' @description A wrapper for plot_ly() function, useful for visualizing the THz matrix data quickly.
+#'
+#' @usage plotlyTHz(m)
+#'
+#' @param m THz matrix data, obtained through the THz scan
+#'
+#' @return An imaging of said matrix
+#'
+#' @examples
+#' m <- matrix(rnorm(100, mean = 0, sd = 1), nrow = 10, ncol = 10)
+#' plotlyTHz(m)
+
+plotlyTHz <- function(m){
+  
+  # m is the matrix of the data obtained through the THz imaging
+  
+  plotly::plot_ly(
+    
+    x = 1:ncol(m),
+    
+    y = 1:nrow(m),
+    
+    z = (as.matrix(m)), type = "heatmap"
+    
+  )
+  
+}
+
+#' Function for visualizing the THz image matrix using ggplot2
+#'
+#' @description A wrapper for ggplot() function, useful for visualizing the THz matrix data quickly.
+#'
+#' @usage plotTHz(m)
+#'
+#' @param m THz matrix data, obtained through the THz scan
+#'
+#' @return An imaging of said matrix
+#'
+#' @examples
+#' m <- matrix(rnorm(100, mean = 0, sd = 1), nrow = 10, ncol = 10)
+#' plotTHz(m)
+
+plotTHz <- function(m){
+  
+  #m is the matrix of the data obtained through the THz imaging
+  
+  m <- as.matrix(m)
+  
+  colnames(m) <- 1:ncol(m)
+  
+  row.names(m) <- 1:nrow(m)
+  
+  m <- reshape2::melt(m)
+  
+  names(m) <- c("Y","X","Val")
+  
+  m$Y <- as.numeric(m$Y)
+  
+  m$X <- as.numeric(m$X)
+  
+  ggplot2::ggplot(data = m, ggplot2::aes(x = X, y = Y, fill = Val))+
+    ggplot2::geom_tile()
+  
+}

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