Solve the equation system \(Ax = b\), given the coefficient matrix
\(A\) and right-hand side vector \(b\), using gaussianElimination
.
Display the solutions using showEqn
.
Arguments
- A,
the matrix of coefficients of a system of linear equations
- b,
the vector of constants on the right hand side of the equations. The default is a vector of zeros, giving the homogeneous equations \(Ax = 0\).
- vars
a numeric or character vector of names of the variables. If supplied, the length must be equal to the number of unknowns in the equations. The default is
paste0("x", 1:ncol(A)
.- verbose,
logical; show the steps of the Gaussian elimination algorithm?
- simplify
logical; try to simplify the equations?
- fractions
logical; express numbers as rational fractions, using the
fractions
function; if you require greater accuracy, you can set thecycles
(default 10) and/ormax.denominator
(default 2000) arguments tofractions
as a global option, e.g.,options(fractions=list(cycles=100, max.denominator=10^4))
.- ...,
arguments to be passed to
gaussianElimination
andshowEqn
Value
the function is used primarily for its side effect of printing the solution in a readable form, but it invisibly returns the solution as a character vector
Details
This function mimics the base function solve
when supplied with two arguments,
(A, b)
, but gives a prettier result, as a set of equations for the solution. The call
solve(A)
with a single argument overloads this, returning the inverse of the matrix A
.
For that sense, use the function inv
instead.
Examples
A1 <- matrix(c(2, 1, -1,
-3, -1, 2,
-2, 1, 2), 3, 3, byrow=TRUE)
b1 <- c(8, -11, -3)
Solve(A1, b1) # unique solution
#> x1 = 2
#> x2 = 3
#> x3 = -1
A2 <- matrix(1:9, 3, 3)
b2 <- 1:3
Solve(A2, b2, fractions=TRUE) # underdetermined
#> x1 - 1*x3 = 1
#> x2 + 2*x3 = 0
#> 0 = 0
b3 <- c(1, 2, 4)
Solve(A2, b3, fractions=TRUE) # overdetermined
#> x1 - 1*x3 = 5/3
#> x2 + 2*x3 = -1/6
#> 0 = -1/2