Hello list, I just started R today and tried something quite simple. I wanted to create a colored plot and eventually after hours of fiddling around got it working. However, my solution seems very suboptimal and I'd really appreciate your hints on how to improve. I believe that R already offers many functions I coded (e.g. distance between two vectors, vector length, vector normalization and so on). I generally didn't even figure out how to create a simple vector or how to extract a row from a matrix so the result is a vector (to get scalars, I use the "sum" functions, which is an incredibly ugly workaround). To sum the problem up: one has a binary star system with a large star (e.g. red giant) and a small star (e.g. white dwarf). Gravitation between them is directly proportional to the mass and indirectly proportional to the square of the distance. If correctly plotted, one should be able to see the inner lagrange point L1 which is the point where the gravitational potentials of the stars "cancel out", e.g. an object would not be attracted to any star. Well, enough background information, here's my rookie code - please feel free to comment on anything :-) Kind regards, Johannes star1center = vector("numeric", 2) star1center[1] = -0.5 star1center[2] = 0 star1mass = 30 star2center = vector("numeric", 2) star2center[1] = 0.5 star2center[2] = 0 star2mass = 1 sqr = function(x) { return(x * x) } distance = function(a, b) { return(sqrt(sqr(a[1] - b[1]) + sqr(a[2] - b[2]))) } len = function(x) { return(sqrt(sqr(x[1]) + sqr(x[2]))) } norm = function(x) { return(x / len(x)) } gravitation = function(invecx, invecy) { invec = vector("numeric", 2) invec[1] = invecx invec[2] = invecy vec1 = star1mass * norm(star1center - invec) / sqr(distance(invec, star1center)) vec2 = star2mass * norm(star2center - invec) / sqr(distance(invec, star2center)) return(len(vec1 + vec2)) } vmin = -1 vmax = 1 step = 0.1 vals = ((vmax - vmin) / step) + 1 xvals = seq(vmin, vmax, step) yvals = seq(vmin, vmax, step) a = expand.grid(seq(vmin, vmax, step), seq(vmin, vmax, step)) b = matrix(seq(1, vals*vals), vals) for (x in 1:vals) { for (y in 1:vals) { b[x, y] = gravitation(sum(a[x,][1]), sum(a[y,][1])) } } filled.contour(xvals, yvals, z = b, color = heat.colors, ylim = c(-1, 1), xlim = c(-1, 1), zlim = c(0, 100), nlevels = 100)
> -----Original Message----- > From: r-help-bounces at r-project.org > [mailto:r-help-bounces at r-project.org] On Behalf Of Johannes Bauer > Sent: Monday, October 20, 2008 10:42 AM > To: r-help at r-project.org > Subject: [R] R Newbie Question > > Hello list, > > I just started R today and tried something quite simple. I wanted to > create a colored plot and eventually after hours of fiddling > around got > it working. However, my solution seems very suboptimal and I'd really > appreciate your hints on how to improve. I believe that R > already offers > many functions I coded (e.g. distance between two vectors, vector > length, vector normalization and so on). I generally didn't > even figure > out how to create a simple vectorSee ?c (i.e. type "?c" without quotes at R prompt) star1center = c(-0.5, 0) or how to extract a row> from a matrix > so the result is a vector (to get scalars, I use the "sum" functions, > which is an incredibly ugly workaround).In your code a[] is not a matrix, it is a data frame. However, you should be able to index it just like you would a matrix. For your code, b[x, y] = gravitation(a[x,1], a[y,1]) Without the need for the sum() function.> > To sum the problem up: one has a binary star system with a large star > (e.g. red giant) and a small star (e.g. white dwarf). Gravitation > between them is directly proportional to the mass and indirectly > proportional to the square of the distance. If correctly plotted, one > should be able to see the inner lagrange point L1 which is the point > where the gravitational potentials of the stars "cancel out", e.g. an > object would not be attracted to any star. Well, enough background > information, here's my rookie code - please feel free to comment on > anything :-) > > Kind regards, > Johannes > > ><<<snip>>> I have edited your code to simplify some of your functions and use vectorized computations. I'm sure others could provide even more optimized code. I will leave it to others to respond concerning already written functions for norm, len, etc. You could try using the various search functions with key terms (like distance) to see what may be available. star1center = c(-0.5, 0) star1mass = 30 star2center = c(0.5, 0) star2mass = 1 sqr = function(x) { return(x * x) } distance = function(a, b) { return(sum((a-b)^2)^0.5) } len = function(x) { return(sum(x^2)^0.5) } norm = function(x) { return(x / len(x)) } gravitation = function(invecx, invecy) { invec = c(invecx, invecy) vec1 = star1mass * norm(star1center - invec) / sqr(distance(invec,star1center)) vec2 = star2mass * norm(star2center - invec) / sqr(distance(invec,star2center)) return(len(vec1 + vec2)) } vmin = -1 vmax = 1 step = 0.1 vals = ((vmax - vmin) / step) + 1 xvals = seq(vmin, vmax, step) yvals = seq(vmin, vmax, step) a = expand.grid(seq(vmin, vmax, step), seq(vmin, vmax, step)) b = matrix(seq(1, vals*vals), vals) for (x in 1:vals) { for (y in 1:vals) { b[x, y] = gravitation(a[x,1], a[y,1]) } } filled.contour(xvals, yvals, z = b, color = heat.colors, ylim = c(-1, 1), xlim = c(-1, 1), zlim = c(0, 100), nlevels = 100) Hope this is helpful, Dan Daniel J. Nordlund Washington State Department of Social and Health Services Planning, Performance, and Accountability Research and Data Analysis Division Olympia, WA 98504-5204
tIs a bit neater to create list objects for each of star1 and star2 and then, since the various functions are not used outside of gravitation stick them right in gravitation. Also we can use distance for len as well by giving it a default second arg of 0 and sqr does not seem to do much so we can eliminate that too. Making the vec computation a function eliminates some redundant code and using outer eliminates the two loops. star1 <- list(mass = 30, center = c(-0.5, 0)) star2 <- list(mass = 1, center = c(0.5, 0)) gravitation2 <- function(v1, v2) { distance <- function(a, b = 0) sqrt(sum((a-b)^2)) norm <- function(x) x/distance(x) vec <- function(x) with(x, mass * norm(center - v) / distance(v, center)^2) v <- c(v1, v2) distance(vec(star1) + vec(star2)) } xvals2 <- yvals2 <- seq(vmin, vmax, step) b2 <- outer(xvals, yvals, Vectorize(gravitation2)) On Mon, Oct 20, 2008 at 1:41 PM, Johannes Bauer <dfnsonfsduifb at gmx.de> wrote:> Hello list, > > I just started R today and tried something quite simple. I wanted to > create a colored plot and eventually after hours of fiddling around got > it working. However, my solution seems very suboptimal and I'd really > appreciate your hints on how to improve. I believe that R already offers > many functions I coded (e.g. distance between two vectors, vector > length, vector normalization and so on). I generally didn't even figure > out how to create a simple vector or how to extract a row from a matrix > so the result is a vector (to get scalars, I use the "sum" functions, > which is an incredibly ugly workaround). > > To sum the problem up: one has a binary star system with a large star > (e.g. red giant) and a small star (e.g. white dwarf). Gravitation > between them is directly proportional to the mass and indirectly > proportional to the square of the distance. If correctly plotted, one > should be able to see the inner lagrange point L1 which is the point > where the gravitational potentials of the stars "cancel out", e.g. an > object would not be attracted to any star. Well, enough background > information, here's my rookie code - please feel free to comment on > anything :-) > > Kind regards, > Johannes > > > > star1center = vector("numeric", 2) > star1center[1] = -0.5 > star1center[2] = 0 > star1mass = 30 > > star2center = vector("numeric", 2) > star2center[1] = 0.5 > star2center[2] = 0 > star2mass = 1 > > sqr = function(x) { > return(x * x) > } > > distance = function(a, b) { > return(sqrt(sqr(a[1] - b[1]) + sqr(a[2] - b[2]))) > } > > len = function(x) { > return(sqrt(sqr(x[1]) + sqr(x[2]))) > } > > norm = function(x) { > return(x / len(x)) > } > > gravitation = function(invecx, invecy) { > invec = vector("numeric", 2) > invec[1] = invecx > invec[2] = invecy > vec1 = star1mass * norm(star1center - invec) / sqr(distance(invec, > star1center)) > vec2 = star2mass * norm(star2center - invec) / sqr(distance(invec, > star2center)) > return(len(vec1 + vec2)) > } > > vmin = -1 > vmax = 1 > step = 0.1 > vals = ((vmax - vmin) / step) + 1 > > xvals = seq(vmin, vmax, step) > yvals = seq(vmin, vmax, step) > > a = expand.grid(seq(vmin, vmax, step), seq(vmin, vmax, step)) > b = matrix(seq(1, vals*vals), vals) > > for (x in 1:vals) { > for (y in 1:vals) { > b[x, y] = gravitation(sum(a[x,][1]), sum(a[y,][1])) > } > } > filled.contour(xvals, yvals, z = b, color = heat.colors, ylim = c(-1, > 1), xlim = c(-1, 1), zlim = c(0, 100), nlevels = 100) > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
Maybe Matching Threads
- Turning a logical vector into its indices without losing its length
- Round Robin trafic shapping
- What is the fastest way to see what are in an RData file?
- [PATCH 00/15] clk/tegra: improve code and add DFS support
- PATCH [xenconsoled]: makes pty slave raw early