Tag Archives: Programming

Map Tiles with Python + GDAL

After getting GPSDrive running on OS X I started looking into different sources for maps. The GPSDrive wiki has a couple of interesting pages about this: one on creating maps and one on map sources. The second page pointed me to the LibreMap Project which has a complete collection of  USGS 1:24000 (large scale) topographic maps for the entire US. These files are distributed as high-resolution GeoTIFF files, along with world files, so the maps are fully geotagged. This means that they contain all of the information needed to generate GPSDrive-friendly map tiles, but GPSDrive will not read them directly. The creating maps page gives some (heavily out-of-date) advice on how to use the gdal_slice.sh script distributed with GPSDrive to create map tiles using the tools from GDAL. Sadly, this script is completely unusable on OS X, because of incompatibilities in the command line tools that are used by the shell script. After spending about five minutes trying to tune it to work with the tools that Apple ships, I completely gave up and looked into other approaches.

Luckily, I quickly found out that GDAL ships with Python bindings. I installed GDAL from source using the instructions from their wiki. To make sure it built with Python modules I ran ./configure –with-python. After that make and sudo make install ran without a hitch.

I then set about re-implementing gdal_slice.sh in Python. Once I got a handle on how to use the Python bindings it was fairly easy to write. You can find the script here.

Using gdal_slice.py is very similar to using gdal_slice.sh:

$ ./gdal_slice.py -h
Usage: gdal_slice.py [options] FILENAME

  -h, --help            show this help message and exit
  -o OVERLAP, --overlap=OVERLAP
                        percentage tiles will overlap. should be at least 20%
  -a, --add             write map info to map_koord.txt in current working
  -m, --map             use *_map folders for output; use if input image is
                        UTM. Default behavior
  -t, --topo            use *_top folders for output; use if input image is
                        not UTM
  -v, --verbose         enable debugging output

The biggest difference is that gdal_slice.py does not perform any format conversion; it will write maps to TIFF files. Although the file size is decidedly larger than that of PNGs, my version of GDAL is unable to create PNGs, and disk space is (fairly) cheap. If I’m motivated I’ll get around to adding a format option, at least to allow conversion to PNG.

Running gdal_slice.py filename.ext will create a folder named filename_map (or _top, if you use the -t flag) that contains a set of 1280×1024 TIFF files, as well as a map_koord_draft.txt file. Moving this folder into GPSDrive’s map directory, and merging filename_[map|top]/map_koord_draft.txt with map_koord.txt will make the new maps available to GPSDrive. Note that filename.ext must be in the current working directory, as the script handles filenames/paths somewhat naivëly.

So far I’ve only tested this with GeoTIFFs from LibreMaps, but it seems to work great, with the caveat that LibreMaps’ files include the borders of map, and my script doesn’t do any cropping, so you see borders if you’re near the edges of quads. This doesn’t bother me terribly much, but you may need to turn mapsets on and off in the Map Control dialog to see the appropriate images.

Update 7-14-11: I’ve modified the script with an additional flag (-a) that will automatically merge the generated map_koords file with map_koord.txt in the current working directory. This means that if you run the script from inside .gpsdrive/maps with the -a flag the generated tiles will be automatically added to GPSDrive’s database. The script avoids creating duplicate entries in map_koord.txt, as well as alphabetizing all entries.

I’ve modified the documentation here, as well as the links, to reference the latest version.

Sign your email like Randall Waterhouse

Neal Stephenson’s novel Cryptonomicon is a fascinating book; I’m re-reading it for the umpteenth time and loving it every bit as much as when I first read it in 7th grade. One thing that caught my attention on this reading (especially in light of my recent GPS post) is the way that one of the main characters, Randall Lawrence Waterhouse, signs his email:

Randall Lawrence Waterhouse

Current meatspace coordinates, hot from the GPS receiver card in my laptop:

8 degrees, 52.33 minutes N latitude 117 degrees, 42.75 minutes E longitude

Nearest geographical feature: Palawan, the Philippines

(from http://www.euskalnet.net/larraorma/crypto/slide51.html)

Using GPSd’s python bindings, and the free, CC-licenced RESTful API from GeoNames.org, I wrote a short python script that will produce a similar output:

Seth Just

Current meatspace coordinates, hot from the GPS receiver card in my laptop:

41.751 N latitude, 111.807 W longitude

Nearest geographical feature: Logan Canyon, Utah, United States

The core of the script is two functions — one that gets GPS coordinates from GPSd, and a second that does a lookup for geographical features (mountains, canyons, islands, etc) on GeoNames.org. For more details, see the final section of this post.

Using gpssig.py

To use gpssig.py, first download it from here, and change the extension to .py.

In order to be useful as an email signature, I had to produce output in HTML format, which allows almost any mail client to use the output as a signature. I’ve gone through the effort of setting it up with the two clients I use the most: Mozilla Thunderbird and Apple’s Mail.app. Of these two, Thunderbird has documented support for HTML signatures (see here for details), and should be the most like other email clients. This script has been tested on Mac OS X Snow Leopard, and should run on Linux without problems (although I haven’t tried it on versions of python higher than 2.6.1).

Using gpssig.py takes two steps: first configure your Mail client to take a signature from a file, and then configure gpssig.py to run automatically to update that file.

Thunderbird is relatively easy to set up with an HTML signature. Because it only supports one signature per account, you simply need to tell it to draw that signature from a file. Under each account’s settings there’s an option to “Attach the signature from a file” (see here for a detailed howto). I chose to use ~/.signature.html, but you can use any file you’d like to, just remember the location you choose.

Mail.app is a more finicky beast — although the script supports it, I recommend using Thunderbird, mainly because Mail only refreshes its signatures from files on every launch, whereas Thunderbird will read the file each time you compose a message. However, if that limitation is acceptable (if you don’t move very much, perhaps), it will work just fine. The main issue with Mail.app is that it doesn’t store signatures in an HTML file, but instead in the proprietary .webarchive format. These files can be found in ~/Library/Mail/Signatures. To use gpssig.py with Mail, you need to follow steps 4&5 from http://bytes.com/topic/macosx/insights/825900-setup-html-signatures-apple-mail-mail-app. First create a new signature (under Preferences->Signatures). This will create a new file in the signature folder — take note of the file name. You will use this file name to configure gpssig.py.

gpssig.py is configured with command line options:

Usage: gpssig.py [options] NAME FILENAME
Note: NAME should be enclosed in quotes, unless it contains no spaces.

  -h, --help   show this help message and exit
  --no-gps     don't attempt to get coordinates from GPS
  -a, --amail  generate files for Apple's Mail.app (.webarchive)
  --lat=LAT    default latitude, if GPS is unavailable
  --lon=LON    default longitude, if GPS is unavailable

The simplest way to use it is manually — simply running it whenever you want to update your signature. For example, I use ./gpssig.py –lat=41.752 –lon=-111.793 ‘Seth Just’ ~/.signature.html to generate a signature for Thunderbird.

If you want to make this automatic, you’ll need to have the script run automatically. On OS X you’ll need to use launchd, while on linux you need cron. Both of these make setting up repeating actions very easy — see here for information on launchd and here for information on cron.

Sadly I haven’t yet figured out a way to run the script whenever you write an email — if I figure it out, I’ll be sure to post something.

The Script

gpssig.py is built around three major functions — one gets coordinates from GPSd, one gets geographical feature information from

The function I use to get GPS information is a bit hacky — there doesn’t seem to be terribly much documentation on GPSd’s python bindings, so I made do with what I could figure out:

class NoGPSError (Exception): pass

def get_lat_lon():
  # GPSd Python bindings
  import gps

  # Create GPS object
  session = gps.gps()

  # Set GPS object as an iterator over reports from GPSd

  # Loop until we get a report with lat and lon. The limit of 5 loops should be more than enough -- my gps never takes more than three when it has a lock
  i = 0
  while (1):
      lat, lon = session.data['lat'], session.data['lon']
      if (i > 5): raise NoGPSError 
      i += 1

  return lat, lon

The other function is more straightforward — it makes two http requests to GeoNames.org to get the nearest geographical feature and locality. It then combines those responses in a way that should provide a good response almost anywhere in the world (provided that GeoNames has good, local data). I’ve tested it with a variety of coordinates (provided by http://www.getlatlon.com/), and the responses seem to be pretty good.

def get_geo_string(lat, lon):
  # Modules for REST/XML request from GeoNames
  import urllib
  from xml.etree import ElementTree as ET
  # Request the name of the nearest geographical feature
  placename = ET.parse(
      urllib.urlopen("http://api.geonames.org/findNearby?lat=" + str(lat) + "&lng=" + str(lon) + "&featureClass=T&username=sethjust")
  subdiv = ET.parse(
      urllib.urlopen("http://api.geonames.org/countrySubdivision?lat=" + str(lat) + "&lng=" + str(lon) + "&username=sethjust")
  # Format and return place, region, country
    country = subdiv.getiterator("countryName")[0].text
      country = placename.getiterator("countryName")[0].text
      country = ''
    region = subdiv.getiterator("adminName1")[0].text
    region = ''
    name = placename.getiterator("name")[0].text
    name = ''
  if country:
    if region:
      if name:
        result = "%s, %s, %s" % (name, region, country)
        result = "%s, %s" % (region, country)
      if name:
        result = "%s, %s" % (name, country)
        result = country
    result = "unknown"
  return result

Finally, the main method of the program parses arguments, determines what coordinates to use, gets the geographical feature string, and then generates the proper HTML and copies it into the correct place.

if (__name__ == "__main__"):
  # Parse command line options
  from optparse import OptionParser
  parser = OptionParser("Usage: %prog [options] NAME FILENAME\nNote: NAME should be enclosed in quotes, unless it contains no spaces.")
  parser.add_option("--no-gps", action="store_true", dest="nogps", default=False, help="don't attempt to get coordinates from GPS")
  parser.add_option("-a", "--amail", action="store_true", dest="amail", default=False, help="generate files for Apple's Mail.app (.webarchive)")
  parser.add_option("--lat", action="store", type="float", dest="lat", help="default latitude, if GPS is unavailable")
  parser.add_option("--lon", action="store", type="float", dest="lon", help="default longitude, if GPS is unavailable")

  options, args = parser.parse_args()
  try: assert(len(args) == 2)
  except AssertionError:
    print "You must provide NAME FILENAME\n"

  try: assert(((options.lat!=None) & (options.lon!=None)) | ((options.lat==None) & (options.lon==None)))
  except AssertionError:
    print "You must provide both lat and lon arguments\n"

  # Modules for creating signature file
  import tempfile, os

    if (options.nogps): raise NoGPSError
    lat, lon = get_lat_lon()
    print "Got %f, %f from gps" % (lat, lon)
  except NoGPSError:
    if (not options.nogps): print "Failed to get coordinates from GPS"
      assert((options.lat!=None) & (options.lon!=None))
    except AssertionError:
      print "No default coordinates provided; exiting"
    lat, lon = options.lat, options.lon
    print "Using %f, %f as coordinates" % (lat, lon)

  geostring = get_geo_string(lat, lon)

  lac, loc = 'N', 'E'
  if lat \n

") file.write(args[0]) file.write("


") file.write("Current meatspace coordinates, hot from the GPS receiver card in my laptop:") file.write("


") file.write("%.3f %s latitude, %.3f %s longitude" % (lat, lac, lon, loc)) file.write("


") file.write("Nearest geographical feature: " + geostring) file.write("

\n") file.write("\n") file.flush() if (options.amail): os.system("textutil -convert webarchive -output " + args[1] + " " + file.name) else: os.system("cp " + file.name + " " + args[1])

RGB LED Sun with Rainbowduino

So my current project (outside of massive amounts of school work) is building a large, bright, RGB LED display for my college’s weekend-long end-of-year party. I’ve got three of these strips from DealExtreme, which have 30 RGB LEDs in separable strips of three LEDs. That makes for a total of 30 RGB dots, which is presents no problem for a Rainbowduino.

My goal for this post is to record my process in putting this project together. I’m nowhere near done at the moment, but I’ll keep updating it as I go.


The plan for this project came together slowly – I knew that I wanted to make a large RGB LED display, and I had already bought one light strip to play with a year or so ago. I’m not sure how the Rainbowduino came across my radar, but it seemed perfect, because it could drive up to 64 RGB LEDs simultaneously, so could support up to 6 strips. However, the funding for the project chose to use 3, and I felt that that was more than enough to get the effect I was shooting for.

Because the strips run at 12 volts, and are each rated for 6 amps, I decided to use a spare PC power supply to provide power because it supplies a well-regulated voltage and plenty of current.

Finally, the Rainbowduino can operate in one of three ways: standalone mode, serial mode, or I2C mode. The second and third allow you to stream patterns to the Rainbowduino from another microcontroller or computer. However, I want this sun to stand on its own, so I’m planning on having it run in standalone mode. This means I’ll need a way of programming it with whatever patterns I want it to use. The Rainbowduino has a 6-pin ICSP plug, which will work perfectly with the AVR programmer I already have, Lady Ada’s UsbTinyISP.


To prepare for putting the whole display together, I wanted to test my LEDs, power supply and control board. I used an RGB driver based on a Teensy 2.0, a few FETs and a wall-wart (which I know works well with these strips) as a simple tester for the LEDs, and found no problems. The power supply also checked out, I took apart a single 4-pin plug to get the +12V and GND wires and checked the voltage with a multimeter. The reading was good and steady, but attaching it to the Rainbowduino caused one of the power-filtering capacitors to explode (which was unexpected, given the board is rated for 12V), but removing the damaged cap fixed the problem, and soon I had it powered up and lighting LEDs. I also connected the UsbTinyISP and used Avrdude to ensure I could program the Rainbowduino. (As an aside, the Avrdude part name for the ATMEGA328P is ‘m328p’, which took me way too long to figure out).

At this point I felt comfortable that I had everything I needed to put the display together (except for some sort of mounting board. However, the end of the weekend was drawing to a close, so I had to wait to get more done.

Steeling Myself

Before I prepared to cut my 3 strips into 30 smaller ones, and soldered 4 wires to each one, I decided to get a picture of what the final wiring would look like. This was a job for Cadsoft’s Eagle, the defacto-standard for making schematics and PCB layouts. Even though I’m planning on laying out the display by hand, with wires, I felt that having a reference for wiring the matrix would be worthwhile. I built a schematic to show the control layout for the LEDs, as a matrix, which is what the Rainbowduino is designed to drive. I then built a layout based on the schematic that corresponds (roughly, and not to scale) to how I’m planning to arrange the LED strips, although the footprints of all the parts are completely arbitrary. However, the pin layout of the headers on either side match the layout of those on the Rainbowduino, which will make it helpful when it comes time to connect all 120 wires.


Update, May 2: I’ve now finished wiring the matrix: I attached all of the strips to a piece of foamcore board using their adhesive backing and soldered all of the connections. Everything worked on the first try, and I flashed the code (rainbowduino_v1_0_4) from here. The demo patterns looked amazing, but sadly, shortly after powering it up (before Icould even get a video), something stopped working. Not only were the patterns not being displayed, but I couldn’t get my programmer to connect to the rainbowduino! Luckily, I emailed SeeedStudio, and one of their very helpful employe has promised me that a replacement is already on the way. Hopefully it arrives before the fifth, when I was hoping to set up the display on campus. Until it arrives, and I can replace the defective board on the display, enjoy the only two photos I took while it was working (before I flashed the new firmware onto it).

Final words

Despite the setback with my Rainbowduino, I went ahead with getting the display ready for this weekend, where (hopefully) it will be sitting in a central place, entertaining people with colorful patterns. To do this, I used a large zip-tie to strap the ATX power supply to the back of the piece of foamcore board, and used some more zip ties to position all of the wires out of sight, as well as to securely fasten the two wires running 12V to the display. All in all it looks good, and I’m excited to load some exciting patters onto it once my new control board arrives.

Also, this post is still in progress — check back soon for updates! Apologies for the lack of photos, they should be coming soon.

Perl Snippets

I’ve been getting into a mood lately that makes me fiddle around with fun Perl stuff, but sadly school’s picking up to the point that writing anything up isn’t going to happen. However, I have a couple short scripts that I’m just dying to share.

Just Another Perl Hacker

I figured that it was about time in my hacking career (read: I was bored enough) that I should make a japh script. After a couple attempts I came up with this:

 	for (map{ord($_)-33}split ''){

print "\n";

                   /|                        |\
      !            ; :                        : :
                  | Y,                      ,P |
     !             |  Yb.        __        ,dP  |
                  l\  YMMb,_ _,/  \,_ _,dMMP  /f
  !                 j;  `YMMP'  `--'  `YMMP'  ;j
                   : \   YP`-._    _.-'YP   / ;
  !            !      \ `\,  _,\_    _/,_  ,/' /
                     `,_,   \`o>  


I'll let you go ahead and figure it out on your own. It's not super-hard, but it's fun.


In another fit of boredom I decided that it was finally time to create a mandelbrot set renderer. I originally tried to make one of these in basic, long before I had the math to do so. I was proud that I got the real axis to render, and figured it was time to complexify it. To keep things simple I decided to make it render an ASCII-art version of the set that would fit in a terminal window. The output looks like this:


The code's far from polished and not what I like to publish, but it's a fun thing to look at and offers you some neat abilities to poke things around and fix some pesky problems that just need clear thinking applied to them. It's available here.

Genetic Algorithms in Perl

Inspired by recent genetic algorithms floating around, I decided to try my hand at implementing one in perl. I’d thought for a long time that it would be quite difficult, but really it’s quite easy. My biggest hangup was dealing with data structures, but once I did that, it turns out that all you really need is a few functions:

  • A fitness function, that determines which individuals are most fit to reproduce
  • A mutate function, that will add random chance into each generation
  • A breed function that allows the best individuals to reproduce.

I ended up implementing a very simple algorithm, but it’s fairly fast and very generic – it can be easily adapted to just about any task. Sadly, I have no fascinating application just yet, but if I stumble across one, I’ll be sure to post about it.

After the jump, I’ll put up some of the code I used and a link to the script, all for your viewing pleasure.
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