From QGIS 1.8 and onwards the Plugin Installer plugin will no longer include the option to add the 3rd party repositories.  This was by design and intended to move people over to using the official plugin repository at http://plugins.qgis.org/ so we can provide a richer experience and keep everything in one place.

If you have plugins that are still not on the official repository then I would strongly recommend that you migrate them as a lot of new 1.8 users will be missing out on your great work.

Something that I need to do now and then is generate points along a line at supplied distance.  I had never really looked into doing it in QGIS until this question poped up on gis.stackexchange.com.  This is a quick blog post because I thought it was a pretty handy little thing to do.

In the development version there is a new method on QgsGeometry called interpolate. This method takes a distance and returns a point along a line at that distance. Perfect! We can then just wrap this in a loop and generate a point increasing the distance as we move along

from qgis.core import (QgsFeature, QgsGeometry,
                       QgsVectorLayer, QgsMapLayerRegistry,
                       QgsField)
from PyQt4.QtCore import QVariant
from qgis.utils import iface

def createPointsAt(distance, geom):
    length = geom.length()
    currentdistance = distance
    feats = []

    while currentdistance < length:
        # Get a point along the line at the current distance
        point = geom.interpolate(currentdistance)
        # Create a new QgsFeature and assign it the new geometry
        fet = QgsFeature()
        fet.setAttributeMap( { 0 : currentdistance } )
        fet.setGeometry(point)
        feats.append(fet)
        # Increase the distance
        currentdistance = currentdistance + distance

    return feats

def pointsAlongLine(distance):
    # Create a new memory layer and add a distance attribute
    vl = QgsVectorLayer("Point", "distance nodes", "memory")
    pr = vl.dataProvider()
    pr.addAttributes( [ QgsField("distance", QVariant.Int) ] )
    layer = iface.mapCanvas().currentLayer()
    # Loop though all the selected features
    for feature in layer.selectedFeatures():
        geom = feature.geometry()
        features = createPointsAt(distance, geom)
        pr.addFeatures(features)
        vl.updateExtents()

    QgsMapLayerRegistry.instance().addMapLayer(vl)

The above code might look a bit scary at first if you have never done any Python/pyqgis but hopefully the comments will ease the pain a little. The main bit is the createPointsAt function.

Cool! If we want to use this we can just stick it in a file in the .qgis/python folder (lets call it pointtools.py) and then run import pointtools in the python console.

So lets have a go. First select some objects then run the following in the Python Console

import pointtools
pointtools.pointsAlongLine(40)

That will generate a point every 40 meters along then selected lines

Distance nodes along line in qgis-dev

To generate nodes along different lines, select the new features, then call pointtools.pointsAlongLine(40) in the Python console.

Simple as that!

(Who knows, someone (maybe me) might even add this as a core object function in QGIS in the future)

Sourcepole bietet Grundlagen- und Aufbau-Kurse für den Betrieb von Geodaten-Infrastrukturen auf der Basis von PostgreSQL/PostGIS und Quantum GIS an. Detaillierte Informationen zu den Kursen, die im Herbst 2012 stattfinden, entnehmen Sie bitte dem Kursprogramm. Die Anmeldung ist ab sofort online möglich. Wir freuen uns darauf Sie in Zürich begüssen zu können.

During the Zurich QGIS hackfest we had some extended discussions about migrating our documentation away from LaTeX to sphinx because the latter offers a more approachable syntax for casual documentation writers and has good support for internationalisation via gettext. This week I am going to our first 2012 QGIS hackfest (to be held in Lyon,... Read more »

During the Zurich QGIS hackfest we had some extended discussions about migrating our documentation away from LaTeX to sphinx because the latter offers a more approachable syntax for casual documentation writers and has good support for internationalisation via gettext. This week I am going to our first 2012 QGIS hackfest (to be held in Lyon, France) and we will be spending some time and effort to move forward with the migration to sphinx. In order to get familiar with sphinx, I have slowly been moving my own documentation work from txt2tags (which I love for its simplicity, but it is not great for complex documents that need interdocument references) to sphinx (which is a little more complex but has many more bells and whistles). Sphinx provides a number of themes 'out of the box'  for generated html content, but I don't really like any of them much and I want my stuff to look a little more unique. So I have dipped my toes a little into the waters of sphinx theme creation. This weekend I decided to make my efforts public. There are still a number of layout issues I want to address (mainly in the TOC sidebar), and I want to add some more explicit markup for various sphinx constructs, but what I have is already usable and hopefully interesting for others to try out. Here is a little screenshot of what the theme looks like:

You can download the theme from its github project page (https://github.com/timlinux/linfiniti-sphinx-theme)  - the accompanying README should give you enough info to get started with it. I am hoping that we can use a variant of this theme for the QGIS project documentation too. I look forward to any patches to make the theme better any of you html/css gurus out there may have to offer!

Gary Sherman has just published a new Python plugin for QGIS that I think people will find very handy, I know I will.  The plugin allows you to run Python scripts inside QGIS for tasks that don’t really require, or warrant, a whole plugin.

Go check out Gray’s post about the new plugin at http://spatialgalaxy.net/2012/01/29/script-runner-a-plugin-to-run-python-scripts-in-qgis/

The new plugin can be installed via the Plugin Installer using the “runner” or “script”.  The Plugin Installer is another one of my favorite plugins for QGIS, being able to push out a new plugin and know that everyone can get it is a good feeling :)

Following up on my last post, Running Scripts in the Python Console, I created a plugin to simplify running scripts:

The Script Runner plugin allows you to add your scripts to a list so they are readily available. You can then run them to automate QGIS tasks and have full access to the PyQGIS API. In addition, you can view information about the classes, methods, and functions in your module as well as browse the source:

In order for your script to work with ScriptRunner it has to implement a single function as an entry point. Here is some additional information from the Help tab of the plugin:

Requirements

In order for Script Runner to execute your script you must define a run_script function that accepts a single argument. This is the standard entry point used by Script Runner. A reference to the qgis.utils.iface object will be passed to your run_script function. You don’t have to use the iface object in your script but your run_script function must accept it as an argument.

Here is an example of a simple run_script function:

    def run_script(iface):
        ldr = Loader(iface)
        ldr.load_shapefiles('/vmap0_shapefiles')

In this example, the run_script creates an instance (ldr) of a class named Loader that is defined in the same source file. It then calls a method in the Loader class named load_shapefiles to do something useful—in this case, load all the shapefiles in a specified directory.

Alternatively, you could choose not to use classes and just do everything within the run_script function, including having it call functions in the same script or others you might import. The important thing is to be sure you have defined a run_script function. If not, Script Runner won’t load your script.

Working with Scripts

To run a script, you must add it to Script Runner using the Add Script tool on the toolbar. This will add it to a list in the left panel. This list of scripts is persisted between uses of QGIS. You can remove a script using the Remove Script tool. This just removes it from the list; it does nothing to the script file on disk.

Once you have a script loaded, you can click the Script Info tool to populate the Info and Source tabs in the panel on the right. The Info tab contains the docstring from your module and then a list of the classes, methods, and functions found in the script. Having a proper docstring at the head of your script will help you determine the puprose of script.

You can view the source of the script on the Source tab. This allows you to quickly confirm that you are using the right script and it does what you think it will.

Installing the Plugin

To install the plugin:

1. Open the Python plugin installer: Plugins->Fetch Python Plugins
2. Check to see if you have the new Official repository in your list of plugins by clicking on Repositories tab. The URL is http://plugins.qgis.org/plugins/plugins.xml.
3. If you have it, skip to step 5. If the new repository isn’t in the list, add it by clicking the Add button. Give it a name and insert the URL http://plugins.qgis.org/plugins/plugins.xml
4. Click on the Plugins tab
5. Enter scriptrunner in the Filter box
6. Select the ScriptRunner plugin and click Install

ScriptRunner adds an entry to the Plugins menu as well as a tool on the Plugins toolbar: . Click it and you are off and running.

The QGIS Python console is great for doing one-off tasks or experimenting with the API. Sometimes you might want to automate a task using a script, and do it without writing a full blown plugin. Currently QGIS does not have a way to load an arbitrary Python script and run it¹. Until it does, this post illustrates a way you can create a script and run it from the console.

There are a couple of requirements to run a script in the console:

1. The script must be in your PYTHONPATH
2. Just like a QGIS plugin, the script needs a reference to qgis.utils.iface

Setting up the Environment

By default, the Python path includes the .qgis/python directory. The location depends on your platform:

• Windows: in your home directory under .qgis\python. For example, C:\Documents and Settings\gsherman\.qgis\python
• Linux and OS X: $HOME/.qgis/python

To see what is in your PYTHONPATH you can do the following in QGIS Python console:

import sys
sys.path

While you could use the .qgis\python directory for your custom scripts, a better way is to create a directory specifically for that purpose and add that directory to the PYTHONPATH environment variable. On Windows you can do this using the Environment Variables page in your system properties:

On Linux or OS X, you can add it to your .bash_profile, .profile, or other login script in your home directory:

export PYTHONPATH=$PYTHONPATH:/home/gsherman/qgis_scripts

Writing the Script

With the environment set, we can create scripts to automate QGIS tasks and run them from the console. For this example, we will use a simple script to load all shapefiles in a specified directory. There are a couple of ways to do this:

1. Write a simple script with a function that accepts qgis.utils.iface as an argument, along with a path to the shapefiles
2. Create a Python class that uses an __init__ method to store a reference to the iface object and then add methods to do the work

We will use the latter approach because it is more flexible and allows us to initialize once and then call methods without having to pass the iface object each time.

The script looks like this:

#!/usr/bin/env Python
"""Load all shapefiles in a given directory.
  This script (loader.py) runs from the QGIS Python console.
  From the console, use:
    from loader import Loader
    ldr = Loader(qgis.utils.iface)
    ldr.load_shapefiles('/my/path/to/shapefile/directory')
 
  """
from glob import glob
from os import path
 
class Loader:
    def __init__(self, iface):
        """Initialize using the qgis.utils.iface 
        object passed from the console.
 
        """
        self.iface = iface
 
    def load_shapefiles(self, shp_path):
        """Load all shapefiles found in shp_path"""
        print "Loading shapes from %s" % path.join(shp_path, "*.shp")
        shps = glob(path.join(shp_path, "*.shp"))
        for shp in shps:
            (shpdir, shpfile) = path.split(shp)
            self.iface.addVectorLayer(shp, shpfile, 'ogr' )

Running the Script

To open the console use the Plugins->Python Console menu item.

The comment at the head of the script explains how to use it.

First we import the Loader class from the script file (named loader.py). This script resides in the qgis_scripts directory that is our PYTHONPATH.

from loader import Loader

We then create an instance of Loader, passing it the reference to the iface object:

ldr = Loader(qgis.utils.iface)

This creates the Loader object and calls the __init__ method to initialize things.

Once we have an instance of Loader we can load all the shapefiles in a directory by calling the load_shapefiles method, passing it the full path to the directory containing the shapefiles:

ldr.load_shapefiles('/home/gsherman/qgis_sample_data/vmap0_shapefiles')

The load_shapefiles method uses the path to get a list of all the shapefiles and then adds them to QGIS using addVectorLayer.

Here is the result, rendered in the random colors and order that the shapefiles were loaded:

Some Notes

• When testing a script in the console you may need to reload it as you make changes. This can be done using reload and the name of the module. In our example, reload(loader) does the trick.
• You can add more methods to your class to do additional tasks
• You can create a “driver” script that accepts the iface object and then initializes additional classes to do more complex tasks

1. I have plans on the drawing board to implement this feature.

This week we look at the OpenLayers plugin for QGIS. This plugin allows you to add a number of image services to your map canvas:

• Google
• Physical
• Streets
• Hybrid
• Satellite
• OpenStreetMap
• Yahoo
• Street
• Hybrid
• Satellite
• Bing
• Road
• Aerial
• Aerial with labels

Installing the Plugin

The OpenLayers plugin is installed like all other Python plugins. From the the Plugins menu in QGIS, choose Fetch Python Plugins. This brings up the plugin installer. To find the plugin, enter openlayers in the Filter box, then select OpenLayers Plugin from the list. Once it’s highlighted, click the Install plugin button. This will download the plugin from the repository, install it, and load it into QGIS.

Using the Plugin

The OpenLayers Plugin uses your view extent to fetch the data from the service you choose. For this reason you should load at least one of your own layers first. Since each of the services are expecting a request in latitude/longitude your layer either has to be geographic or you must enable on the fly projection.

To add one of the services you have two choices; you can pick the service from the Plugins->OpenLayers plugin menu or you can use the OpenLayers Overview. The Overview opens a new panel that allows you to choose a service from a drop-down list. Click the Enable map checkbox to enable the drop-down list and preview the service you want to add. If you are happy with what you see, you can add it to the map by clicking the Add map button.

In the screenshot below we have enabled the Overview panel, added the world boundaries layer¹, zoomed to an area of interest, and added the Google terrain (physical) data:

You can add as many services as you want, previewing them using the OpenLayers Overview panel.

¹ You can get the world boundaries layer from the Geospatial Desktop sample data set.

This week we take a look at a how to plot a terrain profile using the Profile plugin. The plugin can be used with any raster format supported by QGIS. You can can display profiles from up to three rasters at once, allowing you to compare the results. To illustrate, we’ll create a simple profile using a DEM of a 1:63,360 quadrangle in Alaska.

Installing the Plugin

The Profile plugin is installed like all other Python plugins. From the the Plugins menu in QGIS, choose Fetch Python Plugins. This brings up the plugin installer. To find the plugin, enter profile in the Filter box, then select Profile from the list. Once it’s highlighted, click the Install plugin button. This will download the plugin from the repository, install it, and load it into QGIS.¹

Using the Plugin

Here we have loaded the DEM as well as a raster (DRG) of the topography for the same quadrangle and zoomed in a bit to an area of interest:

The yellow line has been added to indicate where we will take the profile. While the Profile plugin allows you to interactively select the profile line it doesn’t display the line on the map.

To create a profile, first make sure the raster you want to profile is selected in the layer list, then activate the plugin from the Plugins toolbar by clicking on it. The cursor becomes a cross that you use to create the profile line: click at the start point, move to the end and click again. Once you have created the profile line, the plugin pops up the result:

The profile is taken from the northeast towards the southwest, based on where we clicked first. You can change the exaggeration of the profile by using the slider on the left. The X axis shows the distance along the profile line in map units and the Y axis shows the cell values from the raster—in this case, elevation in meters.

You can save the result as a PDF or SVG using the buttons at the bottom of the dialog.

The Statistics tab displays some information for the raster layer and the profile line:

If we had additional rasters loaded, we could use the Setup tab to add them to the profile analysis. This would display the results using the colors specified for each layer and we could compare them on the Profile tab.

This is just one of several QGIS plugins that deal with profiles. You can check out the rest of them using the Python Plugin installer.

1 The Profile plugin requires the Python module for QWT5. If you don’t have this installed, a warning will be displayed during the installation process.

This week we highlight the Points to Paths plugin, a handy way to convert a series of points into line features. This plugin lets you “connect the dots” based on an common attribute and a sequence field. The attribute field determines which points should be grouped together into a line. The sequence field determines the order in which the points will connected. The output from this plugin is a shapefile.

Let’s take a look at some example data. Here we have some fictional wildlife tracking data for two moose. The tracking data is in shapefile format, but you can use any vector format supported by QGIS. The tracking data is symbolized by our two animals: Moose1 and Moose2:

The moose_tracks layer has an animal tracking id field (animal_tid) and a sequence field (id). This is all we need to convert the individual observations into a line feature that represents the animals path.

Installing the Plugin

The Points to Paths plugin is installed like all other Python plugins. From the the Plugins menu in QGIS, choose Fetch Python Plugins. This brings up the plugin installer. To find the plugin, enter points to in the Filter box, then select Points to Paths from the list. Once it’s highlighted, click the Install plugin button. This will download the plugin from the repository, install it, and load it into QGIS.

Using the Plugin

Let’s convert the tracking data to paths. To get started, choose Plugins->Points to Paths from the menu or click on the Points to Paths tool on the Plugin toolbar. This brings up the PointsToPaths dialog box where we specify the paramaters needed to create the paths. Below is the completed dialog for our moose tracks:

The first drop-down box contains a list of the vector layers loaded in QGIS—in our case we have just one: moose_tracks. For the group field drop-down we chose the field that contains the tracking identifier for each animal. This determines which points will be selected and grouped to form an individual line. The point order field drop-down specifies the field that contains the ordering for the observations. In this case, the id field is incremented with each observation and can be used to construct the paths. We don’t have a date/time field in this data, but your observations may be sequenced in this way. The Python date format field allows you to specify a format string so the plugin can determine how to sequence your points based on date/time.

The last thing we need to specify is the output shapefile. You can do this by typing in the full path to a new shapefile or by using the Browse button.

With these options set, clicking the OK button will create the new shapefile containing the paths created from our point observations. Once the shapefile is created, the plugin gives you the option to add the new shapefile directly to QGIS.

The Result

The result of our simple example are shown below:

We symbolized the individual tracks using the Categorized renderer on the Style tab of the vector properties dialog. You can see we now have a track for each animal. The attribute table created by the plugin contains the following fields:

• group – the name of the animal taken from the field we chose as the group field
• begin – the value of the first point order field used to create the path
• end – the value of the last point order field used to create the path

In our data, group contains the animal name, begin the value of the lowest id field for animal, and end contains the greatest id value. In a more typical data set, begin and end would contain the start and end date/time values for the observation. Labeling the observation points with our sequence field or date/time values would allow us to determine the direction of movement.

If you have point data that represent a movement of an object, this plugin is a great way to convert it into a path that can be used for visualization, analysis, or map composition.

QGIS has a lot of plugins, including over 180 that have been contributed by users. If you aren’t using plugins, you are missing out on a lot that QGIS has to offer. I’m starting what I hope to be a regular feature: Plugin of the Week. This week we’ll take a look at Time Manager.

Time Manager lets you browse spatial data that has a temporal component. Essentially this includes anything that changes location through time. Examples include:

• Wildlife tracking
• Vehicles
• Storm centers
• QGIS users

Data Preparation

Expanding on our last post about QGIS Users Around the World, we’ll use Time Manager to watch access to the QGIS Python plugin repository through time. If you refer to the previous post, you’ll see that all the IP addresses contacting the repository were extracted from the web server log and geocoded to get the approximate geographic coordinates. To use Time Manager all we need is the time for each access to the repository.

A important part (for our purpose) of the web server log entry looks like this:

66.58.228.196 - - [23/Oct/2011:21:17:54 +0000] "GET /repo/contributed HTTP/1.1" 200 256

Time Manager supports date/time in the following formats:

• YYYY-MM-DD HH:MM:SS
• YYYY-MM-DD HH:MM
• YYYY-MM-DD

As you can see, this doesn’t work with the format in the web server log.

The geocoding process created a file containing IP address, country, city (where available), latitude and longitude. This file is used to create a Python dictionary to look up locations by IP address. Using this file and a bit of Python, the web server log entries were converted into a CSV file containing:

ip,date_time,country,latitude,longitude
66.58.228.196,2011-10-23 21:13:53,United States,61.2149,-149.258
66.58.228.196,2011-10-23 21:14:22,United States,61.2149,-149.258
66.58.228.196,2011-10-23 21:17:54,United States,61.2149,-149.258
66.58.228.196,2011-10-23 21:18:04,United States,61.2149,-149.258
...


The CSV file was first converted to a shapefile using the QGIS Delimited Text plugin. Performance with Time Manager was somewhat slow using a shapefile containing 134,171 locations. The shapefile was imported into a SpatiaLite database (you can do this using ogr2ogr or the SpatiaLite GUI).

Using Time Manager

To display the progression of access to the repository (and thus users of QGIS), we first have to have the Time Manager plugin installed.^[1] Once installed, we enable it using the Plugin Manger.

As you can see from the screenshot above, Time Manager installs a new panel in QGIS that sits below the map canvas. You can set a number of options by clicking Settings; the most important being the layer to use in the visualization. For the QGIS users, we use the time_manager_req layer that was created from the web server logs. With the location and date/time data in the proper format, you can click the “Play” button to start the display. For each time interval, the plugin selects the appropriate entries and displays a frame for the duration specified in the settings.

You can use the time slider to move around or move the time interval forward or backward using the buttons on each end of the slider.

A really nice feature is the ability to export to video. At present this saves a PNG file and world file for each time interval. You can then use another software package to combine these to create a video animation of the time sequence. Once solution is to use mencoder^[1]:

mencoder "mf://*.PNG" -mf fps=10 -o output.avi -ovc lavc -lavcopts vcodec=mpeg4

Putting all this together gives us the following visualization of QGIS user activity from October 23 through December 19, 2011:

QGIS User Activity

You can see the “wave” of activity progress from east to west as the daylight hours come and go.

Summary

If you have spatial data with a date or time component, the Time Manager plugin provides a convenient way to visualize the temporal relationships.

[1]http://www.geofrogger.net/trac/wiki

One of the difficult things to track in the open source world is the number of people who actually use your software. In the proprietary commercial world you have licenses, invoices, and so forth. In the case of QGIS, we can track the total number of downloads from qgis.org, but this doesn’t represent the total installed base. It is impossible to accurately determine the actual number of people using QGIS, but we can get an approximation of the number and where they are in the world.

The analysis was done using the log files from the QGIS contributed repository:

• The IP address of each entry that retrieved the plugin list from the server represents one or more users—these IPs were collected into a unique list
• Using a Python script, each IP address in the log was geocoded to get the approximate latitude and longitude of the user
• The IP address, country, latitude, and longitude were written to a CSV file
• The CSV file was converted to a Spatialite layer to create the map of users

The map represents 35,603 unique IP addresses of users that accessed the repository between October 23, 2011 and December 17, 2011.

The geocoding process varies in precision—some IPs are located to the city level while others only return a general location for the country.

Some assumptions and observations:

• Most (maybe all) users make use of Python plugins and therefore access the contributed repository at some point
• Country-level points (blue) on the map represent more than one user
• Some points represent organizations that use a single IP for all users accessing the Internet. These points will represent more than one user
• Some users may access the repository from more than one IP address

So how many people use QGIS? At the very minimum, 35,000. We know that the downloads of just the Windows version exceeded 100,000. Given that there are 7,183 IP addresses that are generalized to a country location, we can safely assume that the number of actual users is much higher than that.

Considering the number of points that represent an organization and those that represent a country location, I think we can safely assume that the number of QGIS users easily exceeds 100,000 worldwide.

The Plugin Builder allows you to quickly create a skeleton Python plugin by generating all that boring boilerplate that every plugin requires.

Here is a short video showing how to create, compile, and install a new plugin.

For more information, see QGIS Workshop Documentation and the PyQGIS Cookbook.

For a current project (using django), I wanted to get a dynamically generated image from a remote map server and return the image to the django view as an object (as opposed to returning a URL as a string).

Here's how it's done (logic derived from this code snippet):

import urllib
import urllib2
import mimetypes

def serveMapImage( theArea ):
  # omitted: procedure to define the variable zoomExtents
  # from user-specified, database-derived variable theArea
  URI = "http://example.com/mapofsouthafrica-" + zoomExtents
  contents = urllib2.urlopen(URI).read()
  mimetype = mimetypes.guess_type(URI)
  response = HttpResponse(contents, mimetype=mimetype)

  return response

For a current project (using django), I wanted to get a dynamically generated image from a remote map server and return the image to the django view as an object (as opposed to returning a URL as a string).

Here's how it's done (logic derived from this code snippet):

import urllib
import urllib2
import mimetypes

def serveMapImage( theArea ):
  # omitted: procedure to define the variable zoomExtents
  # from user-specified, database-derived variable theArea
  URI = "http://example.com/mapofsouthafrica-" + zoomExtents
  contents = urllib2.urlopen(URI).read()
  mimetype = mimetypes.guess_type(URI)
  response = HttpResponse(contents, mimetype=mimetype)

  return response

The other day I posted an entry about using MapInfo with Python and Qt (see http://woostuff.wordpress.com/2011/03/05/mapinfo-map-control-into-qt-python-form/), one big thing that I missed was support for callbacks, which if you want to do anything related to integrated mapping is a must for map tool support.

Turns out it is pretty easy, and today I worked out how.

You will need to create a class in python that looks something like this:

class Callback():
    _public_methods_ = ['SetStatusText']
    _reg_progid_ = "MapInfo.PythonCallback"
    _reg_clsid_ = "{14EF8D30-8B00-4B14-8891-36B8EF6D51FD}"
    def SetStatusText(self,status):
        print status

This will be our callback object that we will need to create for MapInfo.

First I will explain what some of the funny stuff is:

• _public_methods_ is a Python array of all the methods that you would like to expose to COM eg MapInfo in this case. This attribute is a must for creating a COM object.
• _reg_progid_ is the name of your COM application or object.  This can be anything you would like.
• _reg_clsid_ is the GUID, or unique id, for the object or app.  Do not use the one I have, call the following in a Python shell to create your own.

           import pythoncom
           pythoncom.CreateGuid()
           

• SetStatusText is the MapInfo callback method that is called when the status bar changes in MapInfo.

In order to use the class as a COM object we have two more steps to complete, one is registering the COM object and the other is creating it.

First, in oder to register the object we call the following code from our main Python method:

if __name__ == "__main__":
    print "Registering COM server..."
    import win32com.server.register
    win32com.server.register.UseCommandLine(Callback)
    main()

This will register the COM object which will mean it can then be creating for use by MapInfo.

In order to create our callback in Python we call:

callback = win32com.client.Dispatch("MapInfo.PythonCallback")

and set it as our callback object for MapInfo:

mapinfo.SetCallback(callback)

So after all that the final code looks like this:

def main():
    from PyQt4.QtCore import *
    from PyQt4.QtGui import *
    from win32com.client import Dispatch
    import sys

    app = QApplication(sys.argv)
    app.setAttribute(Qt.AA_NativeWindows,True)
    wnd = QMainWindow()
    wnd.resize(400, 400)
    widget = QWidget()
    wnd.setCentralWidget(widget)
    wnd.show()

    handle = int(widget.winId())
    mapinfo = Dispatch("MapInfo.Application")
    callback = win32com.client.Dispatch("MapInfo.PythonCallback")
    mapinfo.SetCallback(callback)
    mapinfo.do('Set Next Document Parent %s Style 1' % handle)
    mapinfo.do('Open Table "D:\GIS\MAPS\Property.TAB"')
    mapinfo.do('Map from Property')

    app.exec_()

class Callback():
    """ Callback class for MapInfo """
    _public_methods_ = ['SetStatusText']
    _reg_progid_ = "MapInfo.PythonCallback"
    _reg_clsid_ = "{14EF8D30-8B00-4B14-8891-36B8EF6D51FD}"
    def SetStatusText(self,status):
        print status

if __name__ == "__main__":
    print "Registering COM server..."
    import win32com.server.register
    win32com.server.register.UseCommandLine(Callback)
    main()

and the result is a map window and information printed to the console.

Information from MapInfo callback

I think Python could be a good language to prototype MapInfo based app, or even build a whole app itself. If you do end up making something of it let me know I am quite interested with what people could come up with.

EDIT:  If you are having trouble opening MS SQL 2008 in QGIS I will have a blog post coming explaining how to correct it. Or you can read the comments between TheGeoist and I below which will have the answer.

Just a quick tip.

Thanks to GDAL/OGR 1.8 QGIS can now open MS SQL Server 2008 spatial tables via the OGR MSSQLSpatial driver.

First you must be running a version of QGIS that is using GDAL/OGR 1.8.  Opening the QGIS about page will tell you if it is supported.

Need version 1.8 or higher

As I am writing this on my Ubuntu install I only have version 1.6.3 but the latest dev version of QGIS (upcoming 1.7 release) for Windows in the OSGeo4W installer is complied with version 1.8.

Now open the python console in QGIS and type the following:

uri = "MSSQL:server={serverName};database={databaseName};tables={tableName};trusted_connection=yes"
qgis.utils.iface.addVectorLayer(uri,'{yourLayerNameHere}','ogr')

Replacing {serverName} with your server name, if installed on your local machine you can use localhost; {databaseName} with the name of the database with the tables;{tableName} with the table to open; {yourLayerNameHere} with the name you would like the layer to have in the map legend.

After that you should see your MS SQL Spatial table displayed in QGIS, with editing support.

At the moment there is no nice interface in QGIS to open MS SQL tables like there is for PostGIS, although that might be a good plugin project for someone to work on.

Tonight for a bit of fun, or shits and jiggles as we say here, I thought I would try and embed a MapInfo map control into a Qt python widget (although I should be studying, but it’s Saturday night) .

Turns out it is pretty easy!

pls send me teh codez? OK here you go.

from PyQt4.QtCore import *
from PyQt4.QtGui import *
from win32com.client import Dispatch
import sys

app = QApplication(sys.argv)
app.setAttribute(Qt.AA_NativeWindows,True)
wnd = QMainWindow()
wnd.resize(400, 400)
widget = QWidget()
wnd.setCentralWidget(widget)
wnd.show()

handle = int(widget.winId())
mapinfo = Dispatch("MapInfo.Application")
mapinfo.do('Set Next Document Parent %s Style 1' % handle)
mapinfo.do('Open Table "D:\GIS\MAPS\Property.TAB"')
mapinfo.do('Map from Property')

app.exec_()

The above code will load MapInfo and open the property layer into the Qt Widget control, with the result below.

MapInfo map in python Qt based form

So this means you don’t “always” have to write your MapInfo based apps in C# or C++; of course I already knew this as anything that can use OLE and provide a native window handle to MapInfo will work, I just never tried it.

One of the cool things I love about QGIS is finding stuff that you didn’t know it could do, well not just itself but plugins that you didn’t know about.

Today my discovery was in how to generate contour lines from a point layer.

1. First install the contour plugin for qgis via the plugin installer.  Just search for “contour”
2. Once installed open a vector point layer in QGIS.  Make sure the point layer has a field that you can use for elevation.
   

   One I prepared earlier

3. Then select from the menu: Plugins->Contour->Contour
4. Fill in the information
   

   Details form (The above setting will generate 0.5m contours)

5. Press OK
6. Results
   

   Results from plugin

7. Profit??

The resulting contours will have a field that contains the label and z value for each contour line, you can then just label or color them how you wish.

Note:  There is a bug with QGIS memory layers where the fields don’t  show up in dropdown or attribute browsers, a simple fix is just to make the layer editable and then non editable then the fields will be there.

The contour layer is a QGIS memory layer so remember to save it to disk eg a shapefile before you close you will loose your new fancy contour layer.

Happy mapping :)