Merge branch 'release/v0.2.0'

.travis.yml

@@ -4,3 +4,10 @@ sudo: required
 # System dependencies for building
 r_binary_packages:
  - testthat
+
+r_github_packages:
+ - jimhester/covr
+
+after_success:
+ - Rscript -e 'covr::coveralls()'
+

DESCRIPTION

@@ -1,10 +1,13 @@
 Package: cmna
 Type: Package
 Title: Computational Methods for Numerical Analysis
-Version: 0.1.2
-Date: 2016-02-04
-Author: "James P. Howard, II" <jh@jameshoward.us>
-Maintainer: "James P. Howard, II" <jh@jameshoward.us>
+Version: 0.2.0
+Date: 2016-09-17
+Authors@R: person(given = "James P.", family = "Howard, II",
+		          email = "jh@jameshoward.us", role = c("aut", "cre"))
+URL: https://jameshoward.us/cmna/,
+    https://github.com/howardjp/cmna
+BugReports: https://github.com/howardjp/cmna/issues
 Description: Provides the source and examples for James P. Howard, II, 
              "Computational Methods for Numerical Analysis with R," 
 			 <https://jameshoward.us/cmna>, a forthcoming book on

R/bisection.R

@@ -59,9 +59,10 @@ bisection <- function(f, a, b, tol = 1e-3, m = 100) {
 
     while (abs(b - a) > tol) {
         iter <- iter + 1
-        if (iter > m)
+        if (iter > m) {
+            warning("maximum number of iterations exceeded")
             break
-
+        }
         xmid <- (a + b) / 2
         ymid <-  f(xmid)
         if (f.a * ymid > 0) {

R/cholesky.R

@@ -49,7 +49,6 @@ choleskymatrix <- function(m) {
     count.rows <- nrow(m)
     count.cols <- ncol(m)
 
-
     L = diag(0, count.rows)
     for(i in 1:count.rows) {
         for(k in 1:i) {

R/gdls.R

@@ -58,8 +58,10 @@ gdls <- function(A, b, alpha = 0.05, tol = 1e-6, m = 1e5) {
     oldtheta = theta + 10 * tol
 
     while(vecnorm(oldtheta - theta) > tol) {
-        if((iter <- iter + 1) > m)
+        if((iter <- iter + 1) > m) {
+            warning("maximum number of iterations exceeded")
             return(theta)
+        }
         e <- (A %*% theta - b)
         d <- (t(A) %*% e) / length(b)
         oldtheta <- theta

R/goldsect.R

@@ -64,8 +64,10 @@ goldsectmin <- function(f, a, b, tol = 1e-3, m = 100) {
 
     while (abs(b - a) > tol) {
         iter <- iter + 1
-        if (iter > m)
+        if (iter > m) {
+            warning("maximum number of iterations exceeded")
             break
+        }
 
         if(f(a.star) < f(b.star)) {
             b <- b.star
@@ -92,8 +94,10 @@ goldsectmax <- function(f, a, b, tol = 1e-3, m = 100) {
 
     while (abs(b - a) > tol) {
         iter <- iter + 1
-        if (iter > m)
+        if (iter > m) {
+            warning("maximum number of iterations exceeded")
             break
+        }
 
         if(f(a.star) > f(b.star)) {
             b <- b.star

R/horner.R

@@ -33,12 +33,12 @@
 #' Use Horner's rule to evaluate a polynomial
 #'
 #' @param x a vector of x values to evaluate the polynomial
-#' @param betas vector of coefficients of x
+#' @param coefs vector of coefficients of x
 #'
 #' @details
 #' This function implements Horner's rule for fast polynomial
 #' evaluation.  The implementation expects \code{x} to be a vector of x
-#' values at which to evaluate the polynomial. The parameter \code{betas}
+#' values at which to evaluate the polynomial. The parameter \code{coefs}
 #' is a vector of coefficients of \emph{x}.  The vector order is such
 #' that the first element is the constant term, the second element is
 #' the coefficient of \emph{x}, the so forth to the highest degreed
@@ -68,45 +68,45 @@
 #' rhorner(x, b)
 
 #' @export
-horner <- function(x, betas) {
+horner <- function(x, coefs) {
     y <- rep(0, length(x))
 
-    for(i in length(betas):1)
-        y <- betas[i] + x * y
+    for(i in length(coefs):1)
+        y <- coefs[i] + x * y
 
     return(y)
 }
 
 #' @rdname horner
 #' @export
-rhorner <- function(x, betas) {
-    n <- length(betas)
+rhorner <- function(x, coefs) {
+    n <- length(coefs)
 
     if(n == 1)
-        return(betas)
+        return(coefs)
 
-    return(betas[1] + x * rhorner(x, betas[2:n]))
+    return(coefs[1] + x * rhorner(x, coefs[2:n]))
 }
 
 #' @rdname horner
 #' @export
-naivepoly <- function(x, betas) {
+naivepoly <- function(x, coefs) {
     y <- rep(0, length(x))
 
-    for(i in 1:length(betas))
-        y <- y + betas[i] * (x ^ (i - 1))
+    for(i in 1:length(coefs))
+        y <- y + coefs[i] * (x ^ (i - 1))
 
     return(y)
 }
 
 #' @rdname horner
 #' @export
-betterpoly <- function(x, betas) {
+betterpoly <- function(x, coefs) {
     y <- rep(0, length(x))
     cached.x <- 1
 
-    for(i in 1:length(betas)) {
-        y <- y + betas[i] * cached.x
+    for(i in 1:length(coefs)) {
+        y <- y + coefs[i] * cached.x
         cached.x <- cached.x * x
     }
 

R/iterativematrix.R

@@ -71,13 +71,17 @@ jacobi <- function(A, b, tol = 10e-7, maxiter = 100) {
     x <- rep(0, n)
     newx <- rep(tol, n)
 
-    while(vecnorm(newx - x) > tol & iter < maxiter) {
+    while(vecnorm(newx - x) > tol) {
+        if(maxiter > iter) {
+            warning("maximum number of iterations exceeded")
+            break
+        }
         x <- newx
         newx <- Dinv %*% (b - R %*% x)
         iter <- iter + 1
     }
 
-    return(as.vector(x))
+    return(as.vector(newx))
 }
 
 #' @rdname iterativematrix
@@ -94,13 +98,17 @@ gaussseidel <- function(A, b, tol = 10e-7, maxiter = 100) {
     x <- rep(0, n)
     newx <- rep(tol * 10, n)
 
-    while(vecnorm(newx - x) > tol & iter < maxiter) {
+    while(vecnorm(newx - x) > tol) {
+        if(maxiter > iter) {
+            warning("maximum number of iterations exceeded")
+            break
+        }
         x <- newx
         newx <- Linv %*% (b - U %*% x)
         iter <- iter + 1
     }
 
-    return(as.vector(x))
+    return(as.vector(newx))
 }
 
 #' @rdname iterativematrix
@@ -113,8 +121,12 @@ cgmmatrix <- function(A, b, tol = 10e-7, maxiter = 100) {
     newx <- rep(tol * 10, n)
 
     p <- r <- b - A %*% x
-    while(vecnorm(r) > tol & iter < maxiter) {
-        a <- as.numeric((t(r) %*% r) / t(p) %*% A %*% p)
+    while(vecnorm(r) > tol) {
+        if(maxiter > iter) {
+            warning("maximum number of iterations exceeded")
+            break
+        }
+		a <- as.numeric((t(r) %*% r) / t(p) %*% A %*% p)
         newx <- x + a * p
         newr <- r - a * A %*% p
         beta <- as.numeric(t(newr) %*% newr / (t(r) %*% r))

R/naivediv.R

@@ -63,7 +63,7 @@ naivediv <- function(m, n) {
         r <- r - n
     }
 
-    return(list(quot = quot, r = r))
+    return(list(quotient = quot, remainder = r))
 }
 
 #' @rdname division
@@ -84,5 +84,5 @@ longdiv <- function(m, n) {
         }
     }
 
-    return(list(quot = quot, r = r))
+    return(list(quotient = quot, remainder = r))
 }

R/naivesum.R

@@ -49,12 +49,12 @@
 #' @family intro
 #'
 #' @examples
-#' l <- 1:10^6
-#' n <- sample(l, 1)
-#' bound <- sample(l, 2)
-#' bound.u <- max(bound) - 10^6 / 2
-#' bound.l <- min(bound) - 10^6 / 2
-#' x <- runif(n, bound.l, bound.u)
+#' k <- 1:10^6
+#' n <- sample(k, 1)
+#' bound <- sample(k, 2)
+#' bound.upper <- max(bound) - 10^6 / 2
+#' bound.lower <- min(bound) - 10^6 / 2
+#' x <- runif(n, bound.lower, bound.upper)
 #' naivesum(x)
 #' kahansum(x)
 #' pwisesum(x)

R/polyinterp.R

@@ -54,10 +54,10 @@ polyinterp <- function(x, y) {
     vandermonde <- rep(1, length(x))
     for(i in 1:n) {
         xi <- x^i
-        vandermonde <- cbind(xi, vandermonde)
+        vandermonde <- cbind(vandermonde, xi)
     }
     beta <- solve(vandermonde, y)
 
     names(beta) <- NULL
-    return(rev(beta))
+    return(beta)
 }

R/tridiagmatrix.R

@@ -29,9 +29,9 @@
 #' @description
 #' use the tridiagonal matrix algorithm to solve a tridiagonal matrix
 #'
-#' @param d vector of entries on the main diagonal
-#' @param l vector of entries below the main diagonal
-#' @param u vector of entries above the main diagonal
+#' @param D vector of entries on the main diagonal
+#' @param L vector of entries below the main diagonal
+#' @param U vector of entries above the main diagonal
 #' @param b vector of the right-hand side of the linear system
 #'
 #' @details
@@ -43,26 +43,26 @@
 #' @family linear
 #'
 #' @export
-tridiagmatrix <- function(l, d, u, b) {
-    n <- length(d)
-    l <- c(NA, l)
+tridiagmatrix <- function(L, D, U, b) {
+    n <- length(D)
+    L <- c(NA, L)
 
     ##  The forward sweep
-    u[1] <- u[1] / d[1]
-    b[1] <- b[1] / d[1]
+    U[1] <- U[1] / D[1]
+    b[1] <- b[1] / D[1]
     for(i in 2:(n - 1)) {
-        u[i] <- u[i] / (d[i] - l[i] * u[i - 1])
-        b[i] <- (b[i] - l[i] * b[i - 1]) /
-            (d[i] - l[i] * u[i - 1])
+        U[i] <- U[i] / (D[i] - L[i] * U[i - 1])
+        b[i] <- (b[i] - L[i] * b[i - 1]) /
+            (D[i] - L[i] * U[i - 1])
     }
-    b[n] <- (b[n] - l[n] * b[n - 1]) /
-        (d[n] - l[n] * u[n - 1])
+    b[n] <- (b[n] - L[n] * b[n - 1]) /
+        (D[n] - L[n] * U[n - 1])
 
     ##  The backward sweep
     x <- rep.int(0, n)
     x[n] <- b[n]
     for(i in (n - 1):1)
-        x[i] <- b[i] - u[i] * x[i + 1]
+        x[i] <- b[i] - U[i] * x[i + 1]
 
     return(x)
 }

README.md

@@ -1,6 +1,8 @@
-# CMNA
+# Computational Methods for Numerical Analysis
 
 [![Build Status](https://travis-ci.org/howardjp/cmna.svg?branch=master,osx)](https://travis-ci.org/howardjp/cmna)
+[![Coverage Status](https://coveralls.io/repos/howardjp/cmna/badge.svg?branch=master&service=github)](https://coveralls.io/github/howardjp/cmna?branch=master)
+[![Downloads from the RStudio CRAN mirror](http://cranlogs.r-pkg.org/badges/cmna)](http://cran.rstudio.com/package=cmna)
 
 This is the R package to support _Computational Methods for Numerical
 Analysis with R_ by James P. Howard, II.  This book is scheduled for
@@ -104,7 +106,7 @@ numerical analysis algorithms in pure R.
   * Initial Value Problems
     * Euler Method (euler)
 	* Midpoint Method (midptivp)
-	* Fouth-Order Runge-Kutta (rungekitta4)
+	* Fouth-Order Runge-Kutta (rungekutta4)
     * Adams-Bashforth (adamsbashforth)
   * Systems of Differential Equations
     * Euler Method (eulersys)
@@ -124,6 +126,7 @@ numerical analysis algorithms in pure R.
 * Use [Git Flow](http://nvie.com/posts/a-successful-git-branching-model/)
 * Write unit tests using [testthat](https://github.com/hadley/testthat)
 * Document functions using [roxygen2](https://github.com/yihui/roxygen2)
+* Use [ZenHub](https://www.zenhub.com/) for project management on GitHub
 
 ## For more information