The easiest way I&#39;ve found to create postscripts is the following, using the `setEPS()` command:

    setEPS()
    postscript(&quot;whatever.eps&quot;)
    plot(rnorm(100), main=&quot;Hey Some Data&quot;)
    dev.off()





If you are using `ggplot2` to generate a figure, then a `ggsave(file=&quot;name.eps&quot;)` will also work.

The `postscript()` device allows creation of EPS, but **only** if you change some of the default values. Read `?postscript` for the details.

Here is an example:

    postscript(&quot;foo.eps&quot;, horizontal = FALSE, onefile = FALSE, paper = &quot;special&quot;)
    plot(1:10)
    dev.off()



Another way is to use Cairographics-based SVG, PDF and PostScript Graphics Devices.
This way you don&#39;t need to `setEPS()`

    cairo_ps(&quot;image.eps&quot;)
    plot(1, 10)
    dev.off()

Yes, open a `postscript()` device with a filename ending in `.eps`, do your plot(s) and call `dev.off()`.  

I&#39;m really having a hard time understanding the difference between _procedural_ and _functional_ programming paradigms.

Here are the first two paragraphs from the Wikipedia entry on _functional programming_:

&gt; In computer science, functional
&gt; programming is a programming paradigm
&gt; that treats computation as the
&gt; evaluation of mathematical functions
&gt; and avoids state and mutable data. It
&gt; emphasizes the application of
&gt; functions, in contrast to the
&gt; imperative programming style, which
&gt; emphasizes changes in state.
&gt; Functional programming has its roots
&gt; in lambda calculus, a formal system
&gt; developed in the 1930s to investigate
&gt; function definition, function
&gt; application, and recursion. Many
&gt; functional programming languages can
&gt; be viewed as elaborations on the
&gt; lambda calculus.
&gt; 
&gt; In practice, the difference between a
&gt; mathematical function and the notion
&gt; of a &quot;function&quot; used in imperative
&gt; programming is that imperative
&gt; functions can have side effects,
&gt; changing the value of program state.
&gt; Because of this they lack referential
&gt; transparency, i.e. the same language
&gt; expression can result in different
&gt; values at different times depending on
&gt; the state of the executing program.
&gt; Conversely, in functional code, the
&gt; output value of a function depends
&gt; only on the arguments that are input
&gt; to the function, so calling a function
&gt; `f` twice with the same value for an
&gt; argument `x` will produce the same
&gt; result `f(x)` both times. Eliminating
&gt; side effects can make it much easier
&gt; to understand and predict the behavior
&gt; of a program, which is one of the key
&gt; motivations for the development of
&gt; functional programming.


In paragraph 2 where it says

&gt; Conversely, in functional code, the output value of a function depends only on the arguments that are input to the function, so calling a function `f` twice with the same value for an argument `x` will produce the same result `f(x)` both times.

Isn&#39;t that the same exact case for procedural programming?

What should one look for in procedural vs functional that stand out?

Truly understanding the difference between procedural and functional

When I try to upload a folder with subfolders to S3 through the AWS console, only the files are uploaded not the subfolders. 

You also can&#39;t select a folder. It always requires opening the folder first before you can select anything.

Is this even possible?

Upload folder with subfolders using S3 and the AWS console

How do I export a graph to an .eps format file? I typically export my graphs to a .pdf file (using the &#39;pdf&#39; function), and it works quite well. However, now I have to export to .eps files.

Export a graph to .eps file with R

<p>How do I export a graph to an .eps format file? I typically export my graphs to a .pdf file (using the 'pdf' function), and it works quite well. However, now I have to export to .eps files.</p>


When should one use a `data.frame`, and when is it better to use a `matrix`?

Both keep data in a rectangular format, so sometimes it&#39;s unclear.

Are there any general rules of thumb for when to use which data type?





Should I use a data.frame or a matrix?

I don&#39;t use ggplot2 that much, but today I thought I&#39;d give it a go on some graphs. But I can&#39;t figure out how to manually control colors in `geom_line()`

I&#39;m sure I&#39;m overlooking something simple, but here&#39;s my test code: 

    x &lt;- c(1:20, 1:20)
    variable &lt;- c(rep(&quot;y1&quot;, 20), rep(&quot;y2&quot;, 20) )
    value &lt;- c(rnorm(20), rnorm(20,.5) )
    
    df &lt;- data.frame(x, variable, value )
    
    d &lt;- ggplot(df, aes(x=x, y=value, group=variable, colour=variable ) ) + 
                geom_line(size=2)
    d

which gives me the expected output:


![enter image description here][1]

I thought all I had to do was something simple like:

    d +  scale_fill_manual(values=c(&quot;#CC6666&quot;, &quot;#9999CC&quot;))

But that changes nothing. What am I missing?


  [1]: http://i.stack.imgur.com/xN5gh.png

Changing line colors with ggplot()

I am running into issues trying to use large objects in R. For example:

    &gt; memory.limit(4000)
    &gt; a = matrix(NA, 1500000, 60)
    &gt; a = matrix(NA, 2500000, 60)
    &gt; a = matrix(NA, 3500000, 60)
    Error: cannot allocate vector of size 801.1 Mb
    &gt; a = matrix(NA, 2500000, 60)
    Error: cannot allocate vector of size 572.2 Mb # Can&#39;t go smaller anymore
    &gt; rm(list=ls(all=TRUE))
    &gt; a = matrix(NA, 3500000, 60) # Now it works
    &gt; b = matrix(NA, 3500000, 60)
    Error: cannot allocate vector of size 801.1 Mb # But that is all there is room for

I understand that this is related to the difficulty of obtaining contiguous blocks of memory (from [here][1]):

&gt; Error messages beginning cannot
&gt; allocate vector of size indicate a
&gt; failure to obtain memory, either
&gt; because the size exceeded the
&gt; address-space limit for a process or,
&gt; more likely, because the system was
&gt; unable to provide the memory. Note
&gt; that on a 32-bit build there may well
&gt; be enough free memory available, but
&gt; not a large enough contiguous block of
&gt; address space into which to map it.

How can I get around this? My main difficulty is that I get to a certain point in my script and R can&#39;t allocate 200-300 Mb for an object... I can&#39;t really pre-allocate the block because I need the memory for other processing. This happens even when I dilligently remove unneeded objects.

EDIT: Yes, sorry: Windows XP SP3, 4Gb RAM, R 2.12.0:

    &gt; sessionInfo()
    R version 2.12.0 (2010-10-15)
    Platform: i386-pc-mingw32/i386 (32-bit)
    
    locale:
    [1] LC_COLLATE=English_Caribbean.1252  LC_CTYPE=English_Caribbean.1252   
    [3] LC_MONETARY=English_Caribbean.1252 LC_NUMERIC=C                      
    [5] LC_TIME=English_Caribbean.1252    
    
    attached base packages:
    [1] stats     graphics  grDevices utils     datasets  methods   base
    
[1]: http://stat.ethz.ch/R-manual/R-patched/library/base/html/Memory-limits.html

R memory management / cannot allocate vector of size n Mb

Is there an equivalent method for plotting functions using `ggplot` to the `curve()` command employed in base graphics? I guess that the alternative would be to just create a vector of values of the function and plot a connected line, but I was hoping for something a bit more simple.

Thanks!

Plot a function with ggplot, equivalent of curve()

I have a question regarding the command plot().

Is there a way to fully eliminate the x-axis and replace it with own values? I know that I can get rid of the axis by doing

    plot(x,y, xaxt = &#39;n&#39;)
and then add an axis with

    axis(side = 1 etc.)

However, when I add the axis, obviously it still refers to the data plotted as &#39;x&#39;. 
I would only like to plot the &#39;y&#39;-values and add the x-axis my own in the sense of just &quot;drawing&quot; the x-axis with own values specified. Is there any way to do that?

The background of this question is that my two data frames differ in their length and therefore I cannot plot them.



Replace X-axis with own values

I was wondering about a quick to write implementation of a graph in c++. I need the data structure to be easy to manipulate and use graph algorithms(such as BFS,DFS, Kruskal, Dijkstra...).
I need this implementation for an algorithms Olympiad, so the easier to write the data structure the better.

Can you suggest such DS(main structs or classes and what will be in them). I know that an Adjacency list and Adjacency matrix are the main possibilities, but I mean a more detailed **code** sample.

For example I thought about this DS last time I had to implement a graph for DFS:

    struct Edge {
      int start;
      int end;
      struct Edge* nextEdge;
    }

and then used a array of size n containing in its i&#39;th place the Edge List(struct Edge) representing the edges starting in the i&#39;th node.

but when trying to DFS on this graph I had to write a 50 line code with about 10 while loops.

What &#39;good&#39; implementations are there?

Graph implementation C++

This question is about toolkits which draw graphs (those things composed of vertices and edges), not generic plots.

The tool must be able to get a set of vertices and edges, calculate their layout, and display them either using the canvas tag, or SVG, that is be compatible with HTML5.

Flash-based tools and java applets are out.

to serve as unified benchmark, please measure and report how long it takes for the toolkit to layout and draw a Barabasi-Albert graph with 100 vertices and 5 edges per node.

This python lybrary shows how to generate it and exports it to many formats:

http://networkx.lanl.gov/tutorial/tutorial.html#graph-generators-and-graph-operations

Please indicate browser and CPU.


What&#39;s the fastest, pure Javascript, Graph visualization toolkit?

I am using HighCharts for a line graph report. In this specific report I have been asked to Customize the colours of each series. The series will always stay the same. So for example:

John series: Blue dashed line
Mary series: Solid Red Line

Does anyone know how to accomplish this?

HighCharts : Is it possible to customize the colors of individual series?

I&#39;m looking for an interactive graphing library for Python. 

By &quot;[graph][1]&quot;, I meant a set of nodes connected by a set of vertices (not a plot of values over x-y axis, nor a grid of pixels).

By &quot;interactive&quot;, I meant I can drag-and-drop the nodes around and I need to be able to click on the nodes/vertices and have the library pass the nodes/vertices to my callbacks, which may add/remove nodes/vertices or display information (I cannot load the full graph at startup as the dataset is too large/complex; instead I&#39;ll be loading only the necessary slices of data depending on user inputs).

By Python, I meant the programming language [Python][2], the graphing library should have CPython binding. I have Python 2.7 and Python 3.1, but can downgrade to 2.6 if necessary. This language requirement is because the dataset I&#39;m working with only have Python binding.

The graphing library must support [directed graph](http://en.wikipedia.org/wiki/Directed_graph) and be able to layout the nodes automatically. I need to put labels on the nodes.

Preferably, the layouting algorithm should place adjacent nodes near each other. It should be able to handle from 100-1000 nodes and about 300-4000 vertices reasonably in my 4 year old laptop (I typically start with around 100 nodes, but the number might expand depending on user input). Preferably it should be a library with not too many dependencies (except perhaps for Gnome). Open source is preferred.

I have already written a simple prototype of my program using Tkinter Canvas, but I need a more serious graphing library to expand the program. I&#39;ve looked at graphviz and matplotlib, but apparently they&#39;re only for working with static graphs and apparently would need significant amount of work to do interactive manipulations (correct me if I&#39;m wrong, I&#39;ve only looked at them briefly). I&#39;ve also tried generating the graph to an SVG file and using Inkscape to view it, but it&#39;s too slow and takes too much memory and because of the sheer number of vertices it becomes a tangled mess.


  [1]: http://en.wikipedia.org/wiki/Graph_%28mathematics%29
  [2]: http://en.wikipedia.org/wiki/Python_%28programming_language%29

Is there an interactive graphing library for python

I&#39;m currently following Steve Yegge&#39;s advice on preparing for a technical programming interview: http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html

In his section on Graphs, he states:

&gt; There are three basic ways to
&gt; represent a graph in memory (objects
&gt; and pointers, matrix, and adjacency
&gt; list), and you should familiarize
&gt; yourself with each representation and
&gt; its pros and cons.

The pros and cons of matrix and adjacency list representations are described in CLRS, but I haven&#39;t been able to find a resource that compares these to an object representation. 

Just by thinking about it, I can infer some of this myself, but I&#39;d like to make sure I haven&#39;t missed something important. If someone could describe this comprehensively, or point me to a resource which does so, I would greatly appreciate it.


Content Type	Original Author	Original Content on Stackoverflow
Question	mStudent	View Question on Stackoverflow
Solution 1 - R	CompEcon	View Answer on Stackoverflow
Solution 2 - R	Maiasaura	View Answer on Stackoverflow
Solution 3 - R	Gavin Simpson	View Answer on Stackoverflow
Solution 4 - R	USER_1	View Answer on Stackoverflow
Solution 5 - R	Dirk Eddelbuettel	View Answer on Stackoverflow

Export a graph to .eps file with R

R Problem Overview

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Solution 1 - R

Solution 2 - R

Solution 3 - R

Solution 4 - R

Solution 5 - R

Upload folder with subfolders using S3 and the AWS console

Truly understanding the difference between procedural and functional

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