An alternative is to import vector graphics such as SVG or PS using the “grImport” package (Vignette). Suppose you have a postscript graphics named “candle.ps” (if you have an SVG graphics, then use e.g. Inkscape to convert SVG to PS), the following gives the desired plot:

## Read postscript
library(grImport)
PostScriptTrace("candle.ps")
ca = readPicture("candle.ps.xml")

## Set up some points and set background color
library(lattice)
library(grid)
N = 22; x = seq(9,N*10,9); y = rnorm(N, 40, 30)
trellis.par.set("background", list(col = "#380000"))

## Plot with lattice function
xyplot(y~x , xlim=c(0, 9*N + 5), ylim=c(20,100),
panel = function(x, y, ...) {
grid.symbols(ca, x, y, units = "native", size = unit(13, "mm"))})

The result could look like this:

Please note two things. First, postscript does not support transparency. It might be necessary that you replace transparent colors with solid colors using Inkscape, for example. Furthermore, grImport does not paint on the default “base” graphics system (functions like plot, hist), but only on the “grid” graphics system. Therefore we use “lattice” to produce graphics, as the package utilizes grid graphics. These slides from package creator Paul Murell are an helpful further reading.

As far as I know, there is only a single free app which you can just install and go: MapDroyd. After installing you select the regions for which you want offline maps. The program then downloads them automatically. The app uses its own format for Maps (MicroMap Format) optimized for mobile devices. Since it uses vectorized data the maps are not large. However, the program only shows the map – no navigation nor POIs. If you are willing to pay a few dollars, there is a version supporting navigation called NavDroyd.

If you want both for free, you should opt for OsmAnd. It provides navigation, search for addresses and POIs. The latter can be downloaded from within the program. The drawback is that you have to create the maps manually and load them on your android device beforehand (HowTo). You can use the free tool MobileAtlasCreator to do so. Also download this Java Library and store it in the same directory as the Creator. The program lets you select the area which you want the maps for as well as the source of the mapping data (OSM Mapnik recommended). Since it uses tiled images which have to be created for different zoom levels, maps tend to be much larger than for vectorized data.  I used zoom levels 0 to 16. Note that the size of zoom level 16 images is bigger than 0 to 15 together and that OsmAnd interpolates +2 zoomlevels from a smaller one. Do not forget to press Add Selection in the MobileAtlasCreator and to select Big Planet Tracks SQLite Format – it will save you huge amounts of effective space  on the SD card. Warning: Map download and creation will probably take up to some hours, depending on the map size.

There is one free App that can do above using vectorized maps, Navit, but it is not available on the market yet and must be inconveniently installed by hand (german instructions here).

Note: I will update this post after having used both tools abroad.

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• use a date-based directory structure for the experiments you perform
• keep a lab-notebook containing documentation and code for each experiment (How about Org-mode?)
• create generate scripts that work on original data and a general runner script for the complete experiment

His work flow is applies mostly to *nix enviroments. One thing I’d like to add: Use symbolic links! Due to huge amounts of data and backup strategies, it might be impractical to have all the project’s data in a single directory. Create subdirectories of your data and result directories according to the naming convention and link them to other network drives using the ‘ln -s’ command.

import sys, re
import csv
class CommentedFile:
    def __init__(self, f, commentstring="#"):
        self.f = f
        self.commentstring = commentstring
    def next(self):
        line = self.f.next()
        while line.startswith(self.commentstring):
            line = self.f.next()
        return line
    def __iter__(self):
        return self

tsv_file = csv.reader(CommentedFile(open("inputfile.txt", "rb")),
                      delimiter='\t')
for row in tsv_file:
    print row[2] # prints column 3 of each line

Auf Nachfrage bei Victorinox erhielt ich aber die Information das es in Europa ebenfalls vertrieben wird – nur mit leicht anderem Bedruck. Die Artikelnummer ist  5.2063.20. Ich habe es bereits gekauft und es macht einen guten Eindruck.