Multi Dimensional Multiple Roots (Zero) Finding, sampled by a mesh
Multi Dimensional Multiple Roots (Zero) Finding, sampled by a mesh
mesh_roots( f, f.vectorized = FALSE, intervals, mesh = "seq", mesh.sizes = 11, maxerror_f = 1e-07, tol = .Machine$double.eps^0.25, ... )
f |
Function (one or more dimensions) to find roots of |
f.vectorized |
is f already vectorized ? (default: no) |
intervals |
bounds to inverse in, each column contains min and max of each dimension |
mesh |
function or "unif" or "seq" (default) to preform interval partition |
mesh.sizes |
number of parts for mesh (duplicate for each dimension if using "seq") |
maxerror_f |
the maximum error on f evaluation (iterates over uniroot to converge). |
tol |
the desired accuracy (convergence tolerance on f arg). |
... |
Other args for f |
matrix of x, so f(x)=0
mesh_roots(function(x) x-.51, intervals=rbind(0,1))
mesh_roots(function(x) sum(x)-.51, intervals=cbind(rbind(0,1),rbind(0,1)))
mesh_roots(sin,intervals=c(pi/2,5*pi/2))
mesh_roots(f = function(x) sin(pi*x[1])*sin(pi*x[2]),
intervals = matrix(c(1/2,5/2,1/2,5/2),nrow=2))
r = mesh_roots(function(x) (0.25+x[1])^2+(0.5+x[2])^2-.25,
intervals=matrix(c(-1,1,-1,1),nrow=2))
plot(r,xlim=c(-1,1),ylim=c(-1,1))
r = mesh_roots(function(x) (0.5+x[1])^2+(-0.5+x[2])^2+(0.+x[3])^2- .25,
mesh.sizes = 11,
intervals=matrix(c(-1,1,-1,1,-1,1),nrow=2))
scatterplot3d::scatterplot3d(r,xlim=c(-1,1),ylim=c(-1,1),zlim=c(-1,1))
mesh_roots(function(x)exp(x)-1,intervals=c(-1,2))
mesh_roots(function(x)exp(1000*x)-1,intervals=c(-1,2))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.