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I was wondering if there is a package to plot a 2D representation of the outline of a human body? Being in 2D, plotting either the front/back/side at any one time would presumably be the easiest way to accomplish this. The output would be something similar to this (though this is not the best use of such a diagram):
Source: http://emj.bmj.com/content/20/5/434.full
Ideally, plotting a subset of data as is done for the world with map(regions="Australia") would be possible in the form body.map(regions="left.hand"). In that respect, would it be appropriate to base such a model on the maps package?
I just had a look on clker.com for vector body graphics, and if you search for 'body' you see a lot of possible SVG files you could read in and plot.
Then I spotted this one:
http://www.clker.com/clipart-29915.html
which also links to a lot of 'Derived cliparts' showing similar bodies with other parts outlines. It only seems to be the upper torso, but its a nicely-layered SVG file where all the bits could be drawable individually.
There's also plenty of outline body figures (including, I just found, the male figure that went on the Voyager or Pioneer space probe plaques!) and skeletons, including some very well labelled skeletons impressed.
Organising all this into some kind of "body.map" function should be possible - read in from SVG file, select components, plot - but requires some careful thinking and more specification according to requirements.
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I'm converting several SAS programs to R. Reading, data wrangling, and stats are straight forward enough. I'm at a point where I need to create the PDF. I need a lot of control over the format of the PDF and objects in the PDF (e.g. margins, fonts, tables (column widths, cell padding, border widths, cell background color, and alternating table row colors), plots (width, height, position on the page) and line spacing). I've converted a PDF page created from the SAS program to JPG:
In SAS, this is done using various options and procedures (proc gplot, proc report, ods text, and proc template). Can someone point me to the best approach for creating this type of PDF output using R?
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I have a large p (~20K) and small n (~500) problem. The first thing I was thinking is dimension reduction. After trying PCA, robust PCA, ICA, removing highly correlated features, I was thinking to use Random Projection. However, there is no simple R implementation of Random Projection.
I have found a few random projection R packages, like
MCLUST: https://cran.r-project.org/web/packages/mclust/index.html
RPEnsemble: https://cran.r-project.org/web/packages/RPEnsemble/index.html
But, it seems that they don't support random projection directly for dimension reduction. I have limited knowledge about random projection, but I found two functions in sklearn support this:
Gaussian random projection and Sparse random projection:
http://scikit-learn.org/stable/modules/random_projection.html
And it has pretty simple function interface.
Is that possible to implement random projection easily in R? Or, taking advantage of existing tools to do dimension reduction with Random Projection in R?
I concur that the RPEnsemble package doesn't seem to expose the low-level methods that would allow you to use only that feature in any convenient form.
I did however come across this R source code which seems fairly straight-forward and reasonably documented: R source code for random projections. This is part of the clusterv package and you can download it there.
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I am by no means a math person, but I am really trying to figure out how create a graphable function from some data plots I measure from a chemical titration. I have been trying to learn R and I would like to know if anyone can explain to me or point me to a guide to create a mathmatic function of the titration graph below.
Thanks in advance.
What you are looking for is a Interpolation. I'm not a R programmer, but I'll try to answer anyway.
Some of the more common ways to achieve this function you want is by Polynomial Interpolation which usually gives back a Nth degree polynomial function, where N is the number of data points minus one (1 point gives a constant, 2 points make a line, 3 makes a*x^2 + b*x + c and so on).
Other common alternatives I've learn are used in Computer Graphics are Splines, B-spline, Bézier curve and Hermite interpolation. Those make the curve smoother and good looking (I've told they originated in the car industry so they are less true to the data points).
TL;DR: I've found evidence that there is a implementation of spline in R from the question Interpolation in R which may lead you to your solution.
Hope you get to know better your tool and do a great work.
When doing this kind of work in Computer Science we call it Numerical Methods (at least here in my university), I've done some class and homework in this area while attending to the Numerical Methods Course (it can be found at github) but it's nothing worth noting.
I would add a lot of links to Wikipedia but StackOverflow didn't allow it.
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I am looking for an R implemention of the excellent Glicko-2 algorithm of Mark Glickman. Thusfar I found this one. Although this is a very nice piece of code I am particularly looking for a code that is able to deal with large data frames with match scores (meaning that it is capable of ranking all the players in the data frame in one go). A bit like the way the PlayerRatings package does the trick with e.g. Elo, Glicko. Unfortenately this package doesn't haven an implementation of the Glicko-2 algorithm.
Does anyone have an idea?
Glicko2 and few other algorithms are available in R package sport. Possible for two-player and multi-player matchups. Available on cran and github. Vignette included, standarized syntax, supported by C++.
Quick snippet
# install.packages("sport")
library(sport)
glicko2 <- glicko2_run(formula = rank|id ~ rider, data = gpheats)
# computation results
print(glicko2)
summary(glicko2)
tail(glicko2$r)
tail(glicko2$pairs)
If you had noticed the fine print at the bottom of Mark Glickman's page you would have seen (in tiny text admittedly)
PlayerRatings, an R package implementation of Glicko, as well as a
few other rating systems
with the link being: https://cran.r-project.org/web/packages/PlayerRatings/
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Suppose I have an Arabic character hand-drawn in Thuluth font, as in:
http://arabicletters.info/wp-content/uploads/1.jpg
I was thinking of a way I can recreate the same shape but at a much greater height, whilst leaving the other characteristics intact (stroke width, thickness, the relation of where the curving starts to happen to the height) which then got me curious about a way of finding its mathematical representation and play with it until I can get what I want or any other shape for that matter. Is there a math sub-specialty that can help with this? and for this particular problem, can it be solved using programs like Adobe Illustrator or AutoCAD?
Forgive the noobness.
I don't think deduce is the right word.
You can get what you want if you add sufficient points and do Bezier spline fits to match the letters.
There might be a way to automate the process of adding points, but the "sufficient" criterion is tricky. And then you'd have to tell how to connect points with splines.
Sounds like you're trying to reproduce optical character recognition in Arabic.