Enabling the suspend hotkey in KDE4

There are several reports of problems with the suspend hotkey on KDE4 [1] [2]. And there is even a bug report on that issue. Naturally, I wouldn’t write about this if I hadn’t experienced the same problem myself. I solved it by slightly modifiying the approach described at Linux Basement, avoiding the need to create a dedicated shell script somewhere.

This might not have been possible in KDE 4.2 (I haven’t verified), but it is in KDE SC 4.4. The Input Actions dialog (under System Settings) allows for the configuration of DBus calls from hotkeys. This was configured fast and works painless. I have exported the hotkey group and pasted the content below. To use it, save this as PowerManagement.khotkeys and import it in the Input Actions dialog.


Comment=Power management mappings of XF86 events
Name=Power Management


Comment=Enables suspend hotkey






ImportId=Power Management

WebDAV on Windows Vista & Windows 7

There are quite a number of tales of woe around that topic. I had to find that out when I experienced some trouble myself today. If you’re in the same situation skip right down to the last two lines of this posting, the stuff in between just details the problem to associate the solution to the problem for the search engines.

My intention was to connect to my freshly set up  WebDAV directory served by Apache. The setup on the server side was quite tedious as well, but as expected, there are countless howtos around and one just has to put the pieces together as usual. The real problem however arose, when I starry-eyed tried to connect to that online directory using Vista’s „Map Network Drive …“ dialog. After some steps into the wizard that always gave me the error popup saying „The folder you entered does not appear to be valid“.

Well that soon let me drop to the beloved command line. But using net use W: https://example.com/davroot was answered by „System error 67 has occurred“ and „The network name cannot be found“. Using net use W: \\example.com@SSL\davroot gave no improvement.

I will spare you my other trials and all the different possible solutions that can be found on the net (I even installed a Microsoft patch which didn’t change anything) and write down straight what solved the problem:

  1. Make sure the „WebClient“ service is running! (Type „services.msc“ into the search box in the start menu and hit enter.  Scroll down the WebClient and check.)
  2. Use „\\yourserver@SSL\DavWWWRoot\yourshare“ as the server address in the Folder field of the Map Network Drive dialog box. Do not forget the DavWWWRoot or the @SSL.  

Find overlapping polygons with Python

Yesterday I was confronted with a seemingly simple problem: how can one find out if the rectangles or, more general, polygons on a surface are overlapping or not? Surprisingly, because they have an amazing collection of tools, the matplotlib library used in this context to actually draw the rectangles, doesn’t seem to have this kind of functionality. Of course there are loads of examples on the web for 2D collision detection, but I couldn’t find one written in Python. But nevertheless, I found lecture notes on Robert Pless’s website, which taught me the quadrant method to check if one point lies inside a polygon. Then it is only a small step to find if polygons are intersecting.

After writing a Python module providing the functionality, it naturally turned out to be rather slow on big numbers of polygons to be checked. So I continued to write a function which checks which polygons in a given set are overlapping or touching. To use the resources on my machine efficiently, I made two versions of this later function: one for conservative, serial processing and a second which uses Parallel Python to distribute the workload among the CPUs found in the system.

If someone else needs this kind of functionaltiy as well or simply is interested in how I did it, here is the interesting part. The whole file with unit tests and documentation can be downloaded as well: polygons_overlapping.py

import pylab

class PolygonsTouching( Exception ):
    """ This exception is triggered when two polygons touch at one point.

    This is for internal use only and will be caught before returning.

    def __init__( self, x=0, y=0 ):
        self.x, self.y = x, y
    def __str__( self ):
        return 'The tested polygons at least touch each other at (%f,%f)'\
               % ( self.x, self.y )
    def shift( self, dx, dy ):
        self.x += dx
        self.y += dy

def pair_overlapping( polygon1, polygon2, digits = None ):
    """ Find out if polygons are overlapping or touching.

    The function makes use of the quadrant method to find out if a point is
    inside a given polygon.

    polygon1, polygon2 -- Two arrays of [x,y] pairs where the last and the
        first pair is the same, because the polygon has to be closed.
    digits -- The number of digits relevant for the decision between
        separate and touching or touching and overlapping

    Returns 0 if the given polygons are neither overlapping nor touching,
    returns 1 if they are not overlapping, but touching and
    returns 2 if they are overlapping


    def calc_walk_summand( r1, r2, digits = None ):
        """ Calculates the summand along one edge depending on axis crossings.

        Follows the edge between two points and checks if one or both axes are
        being crossed. If They are crossed in clockwise sense, it returns +1
        otherwise -1. Going through the origin raises the PolygonsTouching

        Returns one of -2, -1, 0, +1, +2 or raises PolygonsTouching

        x, y = 0, 1 # indices for better readability
        summand = 0 # the return value
        tx, ty = None, None # on division by zero, set parameters to None
        if r1[x] != r2[x]:
            ty = r1[x] / ( r1[x] - r2[x] ) # where it crosses the y axis
        if r1[y] != r2[y]:
            tx = r1[y] / ( r1[y] - r2[y] ) # where it crosses the x axis
        if tx == None: tx = ty
        if ty == None: ty = tx
        rsign = pylab.sign
        if digits != None:
            rsign = lambda x: pylab.sign( round( x, digits ) )
        sign_x = rsign( r1[x] + tx * ( r2[x] - r1[x] ) )
        sign_y = rsign( r1[y] + ty * ( r2[y] - r1[y] ) )
        if ( tx >= 0 ) and ( tx < 1 ):
            if ( sign_x == 0 ) and ( sign_y == 0 ):
                raise PolygonsTouching()
            summand += sign_x * pylab.sign( r2[y] - r1[y] )
        if ( ty >= 0 ) and ( ty < 1 ):
            if ( sign_x == 0 ) and ( sign_y == 0 ):
                raise PolygonsTouching()
            summand += sign_y * pylab.sign( r1[x] - r2[x] )
        return summand

    def current_and_next( iterable ):
        """ Returns an iterator for each element and its following element.

        iterator = iter( iterable )
        item = iterator.next()
        for next in iterator:
            yield ( item, next )
            item = next

    def point_in_polygon( xy, xyarray, digits = None ):
        """ Checks if a point lies inside a polygon using the quadrant method.

        This moves the given point to the origin and shifts the polygon
        accordingly. Then for each edge of the polygon, calc_walk_summand is
        called. If the sum of all returned values from these calls is +4 or -4,
        the point lies indeed inside the polygon. Otherwise, if a
        PolygonsTouching exception has been caught, the point lies on ond of
        the edges of the polygon.

        Returns the number of nodes of the polygon, if the point lies inside,
        otherwise 1 if the point lies on the polygon and if not, 0.

        moved = xyarray - xy # move currently checked point to the origin (0,0)
        touching = False # this is used only if no overlap is found
        walk_sum = 0
        for cnxy in current_and_next( moved ):
                walk_sum += calc_walk_summand( cnxy[0], cnxy[1], digits )
            except PolygonsTouching, (e):
                e.shift( *xy )
                touching = True
        if ( abs( walk_sum ) == 4 ):
            return len( xyarray )
        elif touching:
            return 1
            return 0

    def polygons_overlapping( p1, p2, digits = None ):
        """ Checks if one of the nodes of p1 lies inside p2.

        This repeatedly calls point_in_polygon for each point of polygon p1
        and immediately returns if it is the case, because then the polygons
        are obviously overlapping.

        Returns 2 for overlapping polygons, 1 for touching polygons and 0

        degree_of_contact = 0
        xyarrays = [ p1, p2 ]
        for xy in xyarrays[0]:
            degree_of_contact += point_in_polygon( xy, xyarrays[1], digits )
            if degree_of_contact >= len( xyarrays[1] ):
                return 2
        if degree_of_contact > 0:
            return 1
            return 0

    way1 = polygons_overlapping( polygon1, polygon2, digits )
    way2 = 0
    if way1 < 2: # Only if the polygons are not already found to be overlapping
        way2 = polygons_overlapping( polygon2, polygon1, digits )
    return max( way1, way2 )

def collection_overlapping_serial( polygons, digits = None ):
    """ Similar to the collection_overlapping function, but forces serial

    result = []
    pickle_polygons = [p.get_xy() for p in polygons]
    for i in xrange( len( polygons ) ):
        for j in xrange( i+1, len( polygons ) ):
            result.append( ( i, j, \
                pair_overlapping( pickle_polygons[i], pickle_polygons[j], \
                                  digits ) ) )
    return result

def __cop_bigger_job( polygons, index, digits = None ):
    """ This is a helper to efficiently distribute workload among processors.

    result = []
    for j in xrange( index + 1, len( polygons ) ):
        result.append( ( index, j, \
            pair_overlapping( polygons[index], polygons[j], digits ) ) )
    return result

def collection_overlapping_parallel( polygons, digits = None, \
        ncpus = 'autodetect' ):
    """ Like collection_overlapping, but forces parallel processing.

    This function crashes if Parallel Python is not found on the system.

    import pp
    ppservers = ()
    job_server = pp.Server( ncpus, ppservers=ppservers )
    pickle_polygons = [p.get_xy() for p in polygons]
    jobs = []
    for i in xrange( len( polygons ) ):
        job = job_server.submit( __cop_bigger_job, \
                                 ( pickle_polygons, i, digits, ), \
                                 ( pair_overlapping, PolygonsTouching, ), \
                                 ( "pylab", ) )
        jobs.append( job )
    result = []
    for job in jobs:
        result += job()
    return result

def collection_overlapping( polygons, digits = None ):
    """ Look for pair-wise overlaps in a given list of polygons.

    The function makes use of the quadrant method to find out if a point is
    inside a given polygon. It invokes the pair_overlapping function for each
    combination and produces and array of index pairs of these combinations
    together with the overlap number of that pair. The overlap number is 0 for
    no overlap, 1 for touching and 2 for overlapping polygons.

    This function automatically selects between a serial and a parallel
    implementation of the search depending on whether Parallel Python is
    installed and can be imported or not.

    polygons -- A list of arrays of [x,y] pairs where the last and the first
        pair of each array in the list is the same, because the polygons have
        to be closed.
    digits -- The number of digits relevant for the decision between
        separate and touching or touching and overlapping polygons.

    Returns a list of 3-tuples

        import pp # try if parallel python is installed
    except ImportError:
        return collection_overlapping_serial( polygons, digits )
        return collection_overlapping_parallel( polygons, digits )