update

QuartoBook/AquaFortR_Codes/conv2D.f90

@@ -2,7 +2,7 @@ subroutine conv2d_f(m, n, p, q, k, l, a, b, conv)
    implicit none
    integer                                :: m, n, p, q, k, l, i, j
    double precision, dimension(m, n)      :: a
-   double precision, dimension(p, q)      :: b, b_flipped
+   double precision, dimension(p, q)      :: b
    double precision, dimension(k, l)      :: conv
    !     dummy vars
    integer                               :: min_row_shift, min_col_shift
@@ -17,13 +17,6 @@ subroutine conv2d_f(m, n, p, q, k, l, a, b, conv)
    min_col_shift = -1*(q - 1)
    max_col_shift = n - 1
 
-   !   Flip the kernel i.e. B
-   b_flipped = 0.0
-   do i = 1, p
-      do j = 1, q
-         b_flipped(p - i + 1, q - j + 1) = b(i, j)
-      end do
-   end do
 
    !   Padded arrray
    rows_padded = abs(min_row_shift) + m + abs(max_row_shift)
@@ -42,7 +35,7 @@ subroutine conv2d_f(m, n, p, q, k, l, a, b, conv)
          iconv = irow + ((icol - 1)*k)
          icol2 = icol + q - 1
          irow2 = irow + p - 1
-         padded_b(irow:irow2, icol:icol2) = b_flipped
+         padded_b(irow:irow2, icol:icol2) = b(p:1:-1,q:1:-1)
          conv(irow, icol) = sum(padded_a*padded_b)
          padded_b = 0.0
       end do

QuartoBook/AquaFortR_Codes/conv2D_f.R

@@ -1,24 +1,28 @@
 conv2D_f0 <- function(a, b) {
+  require(dotCall64)
   dyn.load("AquaFortR_Codes/conv2D.so")
-
+
+  m <- nrow(a)
+  n <- ncol(b)
+
+  p <- nrow(b)
+  q <- ncol(b)
   # the full convolution matrix
-  conv_row <- nrow(a) + nrow(b) - 1
-  conv_col <- ncol(a) + ncol(b) - 1
-  conv <- matrix(1:c(conv_row * conv_col),
-    byrow = FALSE, ncol = conv_col
-  )
-
-  result <- .Fortran("conv2d_f",
-    m = as.integer(dim(a)[1]),
-    n = as.integer(dim(a)[2]),
-    p = as.integer(dim(b)[1]),
-    q = as.integer(dim(b)[2]),
-    k = as.integer(conv_row),
-    l = as.integer(conv_col),
-    a = as.double(a),
-    b = as.double(b),
-    conv = as.double(conv)
-  )$conv
-
-  return(matrix(result, nrow = conv_row, ncol = conv_col))
-}
+  conv_row <- m + p - 1
+  conv_col <- n + q - 1
+  conv <- matrix(0,
+                 ncol = conv_col,
+                 nrow = conv_row)
+
+  conv <- .C64("conv2d_f",
+               SIGNATURE = c(rep("integer",6),
+                             rep("double",3)),
+               INTENT = c(rep("r",8), "rw"),
+               m, n, p, q,
+               k = conv_row,
+               l = conv_col,
+               a = a, b = b,
+               conv = conv)$conv
+
+  return(conv)
+}

QuartoBook/_quarto.yml

@@ -34,6 +34,7 @@ book:
     - scripts.qmd
     - package.qmd
     - summary.qmd
+    - further_reading.qmd
     - references.qmd
   page-navigation: true
 

QuartoBook/further_reading.qmd

@@ -0,0 +1,23 @@
+# Further Reading 
+ * [Fortran and R – Speed Things Up](https://www.r-bloggers.com/2014/04/fortran-and-r-speed-things-up/) by Steve Pittard
+ * [The Need for Speed Part 1: Building an R Package with Fortran (or C)](https://www.r-bloggers.com/2018/12/the-need-for-speed-part-1-building-an-r-package-with-fortran-or-c/) by Avraham Adler
+ * [The Need for Speed Part 2: C++ vs. Fortran vs. C](https://www.avrahamadler.com/2018/12/23/the-need-for-speed-part-2-c-vs-fortran-vs-c/) by Avraham Adler
+ * [Writing R Extensions](https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Writing-R-Extensions) by R Core Team
+ * [Modern Fortran Tutorial](https://masuday.github.io/fortran_tutorial/index.html) by Yutaka Masuda
+ * [Extend R with Fortran](https://masuday.github.io/fortran_tutorial/r.html) by Yutaka Masuda
+ * [Advanced R](http://adv-r.had.co.nz/) by Hadley Wickham
+ * [Fortran 90 Tutorial](http://web.stanford.edu/class/me200c/tutorial_90/) by Stanford University
+ * [Fortran Libraries](https://fortranwiki.org/fortran/show/Libraries) by Fortran Wiki
+ * [Fortran Best Practices](https://fortran-lang.org/en/learn/best_practices/#fortran-best-practices) by Fortran Community
+ * [Fortran 90 Reference Card](https://web.pa.msu.edu/people/duxbury/courses/phy480/fortran90_refcard.pdf) by  Michael Goerz.
+ * [Hands-On Programming with R](https://rstudio-education.github.io/hopr/) by Garrett Grolemund
+ * [r-spatial](https://r-spatial.org/) by Edzer Pebesma, Marius Appel, and Daniel Nüst
+ * [Spatial Data Science](https://rspatial.org/index.html)
+ * [R for Data Science (2e)](https://r4ds.hadley.nz/) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund
+ * [Introduction to Environmental Data Science](https://bookdown.org/igisc/EnvDataSci/) by Jerry Davis
+
+<!-- https://cran.r-project.org/doc/manuals/r-release/R-exts.html#System-and-foreign-language-interfaces-1 -->
+
+<!-- Fortran is primarily intended for Fortran 77 code, and long precedes any support for Fortran 9x. Now current implementations of Fortran 9x support the Fortran 2003 module iso_c_binding, a better way to interface modern Fortran code to R is to use .C and write a C interface using use iso_c_binding.  -->
+
+<!-- The header files R_ext/BLAS.h, R_ext/Lapack.h and R_ext/Linpack.h contains declarations of the BLAS, LAPACK and LINPACK linear algebra functions included in R. -->

QuartoBook/index.qmd

@@ -2,11 +2,11 @@
 
  Welcome to the enlightening journey through the pages of **"AquaFortR: Streamlining 
  Atmospheric Science, Oceanography, Climate, and Water Research with Fortran-accelerated R"**. 
- In this book, you will gain invaluable insights into seamlessly integrating Fortran 
- into R scripts by harnessing the power of Fortran. You will acquire 
- invaluable insights into how to speed up your package using simple C and Fortran codes.
- Furthermore, you will accumulate tweaks to further accelerate your scripts or packages, 
- and further reading will prove to be both advantageous and highly beneficial for further 
+ In this book, you will gain invaluable insights into seamlessly speeding up R scripts 
+ by harnessing the power of Fortran. You will acquire 
+ essential perspectives into speeding up your package using simple C and Fortran codes.
+ Furthermore, you will accumulate tweaks to accelerate your scripts or packages, 
+ and supplementary reading will prove to be both advantageous and highly beneficial for further 
  optimization, and efficiency. 
 
  

QuartoBook/package.qmd

@@ -8,12 +8,12 @@ This chapter will focus on wrapping the developed routines from the previous cha
 <!-- https://www.mzes.uni-mannheim.de/socialsciencedatalab/article/r-package/ -->
 ## Developing AquaFortR Package 
 
-
-### R function 
-
 ### Fortran subroutine 
 
-- iso_c_binidng 
+iso_c_binidng
+<!-- -  https://gcc.gnu.org/onlinedocs/gfortran/Intrinsic-Types.html -->
+
+### R function 
 
 ### C funtions
  - C to Fortran