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Wed Jan 16 00:05:16 2019

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QGIS Planet

On custom layout checks in QGIS 3.6, and how they can do your work for you!

Recently, we had the opportunity to implement an exciting new feature within QGIS. An enterprise with a large number of QGIS installs was looking for a way to control the outputs which staff were creating from the software, and enforce a set of predefined policies. The policies were designed to ensure that maps created in QGIS’ print layout designer would meet a set of minimum standards, e.g.:

  • Layouts must include a “Copyright 2019 by XXX” label somewhere on the page
  • All maps must have a linked scale bar
  • No layers from certain blacklisted sources (e.g. Google Maps tiles) are permitted
  • Required attribution text for other layers must be included somewhere on the layout

Instead of just making a set of written policies and hoping that staff correctly follow them, it was instead decided that the checks should be performed automatically by QGIS itself. If any of the checks failed (indicating that the map wasn’t complying to the policies), the layout export would be blocked and the user would be advised what they needed to change in their map to make it compliant.

The result of this work is a brand new API for implementing custom “validity checks” within QGIS. Out of the box, QGIS 3.6 ships with two in-built validity checks. These are:

  • A check to warn users when a layout includes a scale bar which isn’t linked to a map
  • A check to warn users if a map overview in a layout isn’t linked to a map (e.g. if the linked map has been deleted)

All QGIS 3.6 users will see a friendly warning if either of these conditions are met, advising them of the potential issue.

 

The exciting stuff comes in custom, in-house checks. These are written in PyQGIS, so they can be deployed through in-house plugins or startup scripts. Let’s explore some examples to see how these work.

A basic check looks something like this:

from qgis.core import check

@check.register(type=QgsAbstractValidityCheck.TypeLayoutCheck)
def my_layout_check(context, feedback):
  results = ...
  return results

Checks are created using the @check.register decorator. This takes a single argument, the check type. For now, only layout checks are implemented, so this should be set to QgsAbstractValidityCheck.TypeLayoutCheck. The check function is given two arguments, a QgsValidityCheckContext argument, and a feedback argument. We can safely ignore the feedback option for now, but the context argument is important. This context contains information useful for the check to run — in the case of layout checks, the context contains a reference to the layout being checked. The check function should return a list of QgsValidityCheckResult objects, or an empty list if the check was passed successfully with no warnings or errors.

Here’s a more complete example. This one throws a warning whenever a layout map item is set to the web mercator (EPSG:3875) projection:

@check.register(type=QgsAbstractValidityCheck.TypeLayoutCheck)
def layout_map_crs_choice_check(context, feedback):
  layout = context.layout
  results = []
  for i in layout.items():
    if isinstance(i, QgsLayoutItemMap) and i.crs().authid() == 'EPSG:3857':
      res = QgsValidityCheckResult()
      res.type = QgsValidityCheckResult.Warning
      res.title='Map projection is misleading'
      res.detailedDescription='The projection for the map item {} is set to Web Mercator (EPSG:3857) which misrepresents areas and shapes. Consider using an appropriate local projection instead.'.format(i.displayName())
      results.append(res)

  return results

Here, our check loops through all the items in the layout being tested, looking for QgsLayoutItemMap instances. It then checks the CRS for each map, and if that CRS is ‘EPSG:3857’, a warning result is returned. The warning includes a friendly message for users advising them why the check failed.

In this example our check is returning results with a QgsValidityCheckResult.Warning type. Warning results are shown to users, but they don’t prevent users from proceeding and continuing to export their layout.

Checks can also return “critical” results. If any critical results are obtained, then the actual export itself is blocked. The user is still shown the messages generated by the check so that they know how to resolve the issue, but they can’t proceed with the export until they’ve fixed their layout. Here’s an example of a check which returns critical results, preventing layout export if there’s no “Copyright 2019 North Road” labels included on their layout:

@check.register(type=QgsAbstractValidityCheck.TypeLayoutCheck)
def layout_map_crs_choice_check(context, feedback):
  layout = context.layout
  for i in layout.items():
    if isinstance(i, QgsLayoutItemLabel) and 'Copyright 2019 North Road' in i.currentText():
      return

  # did not find copyright text, block layout export
  res = QgsValidityCheckResult()
  res.type = QgsValidityCheckResult.Critical
  res.title = 'Missing copyright label'
  res.detailedDescription = 'Layout has no "Copyright" label. Please add a label containing the text "Copyright 2019 North Road".'
  return [res]

If we try to export a layout with the copyright notice, we now get this error:

Notice how the OK button is disabled, and users are forced to fix the error before they can export their layouts.

Here’s a final example. This one runs through all the layers included within maps in the layout, and if any of them come from a “blacklisted” source, the user is not permitted to proceed with the export:

@check.register(type=QgsAbstractValidityCheck.TypeLayoutCheck)
def layout_map_crs_choice_check(context, feedback):
  layout = context.layout
  for i in layout.items():
    if isinstance(i, QgsLayoutItemMap):
      for l in i.layersToRender():
        # check if layer source is blacklisted
        if 'mt1.google.com' in l.source():
          res = QgsValidityCheckResult()
          res.type = QgsValidityCheckResult.Critical
          res.title = 'Blacklisted layer source'
          res.detailedDescription = 'This layout includes a Google maps layer ("{}"), which is in violation of their Terms of Service.'.format(l.name())
          return [res]

Of course, all checks are run each time — so if a layout fails multiple checks, the user will see a summary of ALL failed checks, and can click on each in turn to see the detailed description of the failure.

So there we go — when QGIS 3.6 is released in late February 2019, you’ll  have access to this API and can start making QGIS automatically enforce your organisation policies for you! The really neat thing is that this doesn’t only apply to large organisations. Even if you’re a one-person shop using QGIS, you could write your own checks to  make QGIS “remind” you when you’ve forgotten to include something in your products. It’d even be possible to hook into one of the available Python spell checking libraries to write a spelling check! With any luck, this should lead to better quality outputs and less back and forth with your clients.

North Road are leading experts in customising the QGIS application for enterprise installs. If you’d like to discuss how you can deploy in-house customisation like this within your organisation, contact us for further details!

GRASS GIS 7.4.4 released: QGIS friendship release

We are pleased to announce the GRASS GIS 7.4.4 release

What’s new in a nutshell

The new update release GRASS GIS 7.4.4 is release with a few bugfixes and the addition of r.mapcalc.simple esp. for QGIS integration. An overview of the new features in the 7.4 release series is available at New Features in GRASS GIS 7.4.

As a stable release series, 7.4.x enjoys long-term support.

Binaries/Installer download:

Source code download:

More details:

See also our detailed announcement:

About GRASS GIS

The Geographic Resources Analysis Support System (https://grass.osgeo.org/), commonly referred to as GRASS GIS, is an Open Source Geographic Information System providing powerful raster, vector and geospatial processing capabilities in a single integrated software suite. GRASS GIS includes tools for spatial modeling, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It also provides the capability to produce sophisticated presentation graphics and hardcopy maps. GRASS GIS has been translated into about twenty languages and supports a huge array of data formats. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics. It is distributed freely under the terms of the GNU General Public License (GPL). GRASS GIS is a founding member of the Open Source Geospatial Foundation (OSGeo).

The GRASS Development Team, January 2019

The post GRASS GIS 7.4.4 released: QGIS friendship release appeared first on GFOSS Blog | GRASS GIS and OSGeo News.

PyQGIS101 part 10 published!

PyQGIS 101: Introduction to QGIS Python programming for non-programmers has now reached the part 10 milestone!

Beyond the obligatory Hello world! example, the contents so far include:

If you’ve been thinking about learning Python programming, but never got around to actually start doing it, give PyQGIS101 a try.

I’d like to thank everyone who has already provided feedback to the exercises. Every comment is important to help me understand the pain points of learning Python for QGIS.

I recently read an article – unfortunately I forgot to bookmark it and cannot locate it anymore – that described the problems with learning to program very well: in the beginning, it’s rather slow going, you don’t know the right terminology and therefore don’t know what to google for when you run into issues. But there comes this point, when you finally get it, when the terminology becomes clearer, when you start thinking “that might work” and it actually does! I hope that PyQGIS101 will be a help along the way.

QGIS and Call Before You Dig

Just released a new version of the KLIC viewer plugin for QGIS. This was neccesary because the format of the information received has changed a lot! Before it only included the information on pipelines in raster format. Now the information on pipelines delivered in XML can include information in vector format . The KLIC viewer … Continue reading QGIS and Call Before You Dig

Movement data in GIS #17: Spatial analysis of GeoPandas trajectories

In Movement data in GIS #16, I presented a new way to deal with trajectory data using GeoPandas and how to load the trajectory GeoDataframes as a QGIS layer. Following up on this initial experiment, I’ve now implemented a first version of an algorithm that performs a spatial analysis on my GeoPandas trajectories.

The first spatial analysis algorithm I’ve implemented is Clip trajectories by extent. Implementing this algorithm revealed a couple of pitfalls:

  • To achieve correct results, we need to compute spatial intersections between linear trajectory segments and the extent. Therefore, we need to convert our point GeoDataframe to a line GeoDataframe.
  • Based on the spatial intersection, we need to take care of computing the corresponding timestamps of the events when trajectories enter or leave the extent.
  • A trajectory can intersect the extent multiple times. Therefore, we cannot simply use the global minimum and maximum timestamp of intersecting segments.
  • GeoPandas provides spatial intersection functionality but if the trajectory contains consecutive rows without location change, these will result in zero length lines and those cause an empty intersection result.

So far, the clip result only contains the trajectory id plus a suffix indicating the sequence of the intersection segments for a specific trajectory (because one trajectory can intersect the extent multiple times). The following screenshot shows one highlighted trajectory that intersects the extent three times and the resulting clipped trajectories:

This algorithm together with the basic trajectory from points algorithm is now available in a Processing algorithm provider plugin called Processing Trajectory.

Note: This plugin depends on GeoPandas.

Note for Windows users: GeoPandas is not a standard package that is available in OSGeo4W, so you’ll have to install it manually. (For the necessary steps, see this answer on gis.stackexchange.com)

The implemented tests show how to use the Trajectory class independently of QGIS. So far, I’m only testing the spatial properties though:

def test_two_intersections_with_same_polygon(self):
    polygon = Polygon([(5,-5),(7,-5),(7,12),(5,12),(5,-5)])
    data = [{'id':1, 'geometry':Point(0,0), 't':datetime(2018,1,1,12,0,0)},
        {'id':1, 'geometry':Point(6,0), 't':datetime(2018,1,1,12,10,0)},
        {'id':1, 'geometry':Point(10,0), 't':datetime(2018,1,1,12,15,0)},
        {'id':1, 'geometry':Point(10,10), 't':datetime(2018,1,1,12,30,0)},
        {'id':1, 'geometry':Point(0,10), 't':datetime(2018,1,1,13,0,0)}]
    df = pd.DataFrame(data).set_index('t')
    geo_df = GeoDataFrame(df, crs={'init': '31256'})
    traj = Trajectory(1, geo_df)
    intersections = traj.intersection(polygon)
    result = []
    for x in intersections:
        result.append(x.to_linestring())
    expected_result = [LineString([(5,0),(6,0),(7,0)]), LineString([(7,10),(5,10)])]
    self.assertEqual(result, expected_result) 

One issue with implementing the algorithms as QGIS Processing tools in this way is that the tools are independent of one another. That means that each tool has to repeat the expensive step of creating the trajectory objects in memory. I’m not sure this can be solved.

TimeManager 3.0.2 released!

Bugfix release 3.0.2 fixes an issue where “accumulate features” was broken for timestamps with milliseconds.

If you like TimeManager, know your way around setting up Travis for testing QGIS plugins, and want to help improve TimeManager stability, please get in touch!

Thoughts on “FOSS4G/SOTM Oceania 2018”, and the PyQGIS API improvements which it caused

Last week the first official “FOSS4G/SOTM Oceania” conference was held at Melbourne University. This was a fantastic event, and there’s simply no way I can extend sufficient thanks to all the organisers and volunteers who put this event together. They did a brilliant job, and their efforts are even more impressive considering it was the inaugural event!

Upfront — this is not a recap of the conference (I’m sure someone else is working on a much more detailed write up of the event!), just some musings I’ve had following my experiences assisting Nathan Woodrow deliver an introductory Python for QGIS workshop he put together for the conference. In short, we both found that delivering this workshop to a group of PyQGIS newcomers was a great way for us to identify “pain points” in the PyQGIS API and areas where we need to improve. The good news is that as a direct result of the experiences during this workshop the API has been improved and streamlined! Let’s explore how:

Part of Nathan’s workshop (notes are available here) focused on a hands-on example of creating a custom QGIS “Processing” script. I’ve found that preparing workshops is guaranteed to expose a bunch of rare and tricky software bugs, and this was no exception! Unfortunately the workshop was scheduled just before the QGIS 3.4.2 patch release which fixed these bugs, but at least they’re fixed now and we can move on…

The bulk of Nathan’s example algorithm is contained within the following block (where “distance” is the length of line segments we want to chop our features up into):

for input_feature in enumerate(features):
    geom = feature.geometry().constGet()
    if isinstance(geom, QgsLineString):
        continue
    first_part = geom.geometryN(0)
    start = 0
    end = distance
    length = first_part.length()

    while start < length:
        new_geom = first_part.curveSubstring(start,end)

        output_feature = input_feature
        output_feature.setGeometry(QgsGeometry(new_geom))
        sink.addFeature(output_feature)

        start += distance
        end += distance

There’s a lot here, but really the guts of this algorithm breaks down to one line:

new_geom = first_part.curveSubstring(start,end)

Basically, a new geometry is created for each trimmed section in the output layer by calling the “curveSubstring” method on the input geometry and passing it a start and end distance along the input line. This returns the portion of that input LineString (or CircularString, or CompoundCurve) between those distances. The PyQGIS API nicely hides the details here – you can safely call this one method and be confident that regardless of the input geometry type the result will be correct.

Unfortunately, while calling the “curveSubstring” method is elegant, all the code surrounding this call is not so elegant. As a (mostly) full-time QGIS developer myself, I tend to look over oddities in the API. It’s easy to justify ugly API as just “how it’s always been”, and over time it’s natural to develop a type of blind spot to these issues.

Let’s start with the first ugly part of this code:

geom = input_feature.geometry().constGet()
if isinstance(geom, QgsLineString):
    continue
first_part = geom.geometryN(0)
# chop first_part into sections of desired length
...

This is rather… confusing… logic to follow. Here the script is fetching the geometry of the input feature, checking if it’s a LineString, and if it IS, then it skips that feature and continues to the next. Wait… what? It’s skipping features with LineString geometries?

Well, yes. The algorithm was written specifically for one workshop, which was using a MultiLineString layer as the demo layer. The script takes a huge shortcut here and says “if the input feature isn’t a MultiLineString, ignore it — we only know how to deal with multi-part geometries”. Immediately following this logic there’s a call to geometryN( 0 ), which returns just the first part of the MultiLineString geometry.

There’s two issues here — one is that the script just plain won’t work for LineString inputs, and the second is that it ignores everything BUT the first part in the geometry. While it would be possible to fix the script and add a check for the input geometry type, put in logic to loop over all the parts of a multi-part input, etc, that’s instantly going to add a LOT of complexity or duplicate code here.

Fortunately, this was the perfect excuse to improve the PyQGIS API itself so that this kind of operation is simpler in future! Nathan and I had a debrief/brainstorm after the workshop, and as a result a new “parts iterator” has been implemented and merged to QGIS master. It’ll be available from version 3.6 on. Using the new iterator, we can simplify the script:

geom = input_feature.geometry()
for part in geom.parts():
    # chop part into sections of desired length
    ...

Win! This is simultaneously more readable, more Pythonic, and automatically works for both LineString and MultiLineString inputs (and in the case of MultiLineStrings, we now correctly handle all parts).

Here’s another pain-point. Looking at the block:

new_geom = part.curveSubstring(start,end)
output_feature = input_feature
output_feature.setGeometry(QgsGeometry(new_geom))

At first glance this looks reasonable – we use curveSubstring to get the portion of the curve, then make a copy of the input_feature as output_feature (this ensures that the features output by the algorithm maintain all the attributes from the input features), and finally set the geometry of the output_feature to be the newly calculated curve portion. The ugliness here comes in this line:

output_feature.setGeometry(QgsGeometry(new_geom))

What’s that extra QgsGeometry(…) call doing here? Without getting too sidetracked into the QGIS geometry API internals, QgsFeature.setGeometry requires a QgsGeometry argument, not the QgsAbstractGeometry subclass which is returned by curveSubstring.

This is a prime example of a “paper-cut” style issue in the PyQGIS API. Experienced developers know and understand the reasons behind this, but for newcomers to PyQGIS, it’s an obscure complexity. Fortunately the solution here was simple — and after the workshop Nathan and I added a new overload to QgsFeature.setGeometry which accepts a QgsAbstractGeometry argument. So in QGIS 3.6 this line can be simplified to:

output_feature.setGeometry(new_geom)

Or, if you wanted to make things more concise, you could put the curveSubstring call directly in here:

output_feature = input_feature
output_feature.setGeometry(part.curveSubstring(start,end))

Let’s have a look at the simplified script for QGIS 3.6:

for input_feature in enumerate(features):
    geom = feature.geometry()
    for part in geom.parts():
        start = 0
        end = distance
        length = part.length()

        while start < length:
            output_feature = input_feature
            output_feature.setGeometry(part.curveSubstring(start,end))
            sink.addFeature(output_feature)

            start += distance
            end += distance

This is MUCH nicer, and will be much easier to explain in the next workshop! The good news is that Nathan has more niceness on the way which will further improve the process of writing QGIS Processing script algorithms. You can see some early prototypes of this work here:

So there we go. The process of writing and delivering a workshop helps to look past “API blind spots” and identify the ugly points and traps for those new to the API. As a direct result of this FOSS4G/SOTM Oceania 2018 Workshop, the QGIS 3.6 PyQGIS API will be easier to use, more readable, and less buggy! That’s a win all round!

Movement data in GIS #16: towards pure Python trajectories using GeoPandas

Many of my previous posts in this series [1][2][3] have relied on PostGIS for trajectory data handling. While I love PostGIS, it feels like overkill to require a database to analyze smaller movement datasets. Wouldn’t it be great to have a pure Python solution?

If we look into moving object data literature, beyond the “trajectories are points with timestamps” perspective, which is common in GIS, we also encounter the “trajectories are time series with coordinates” perspective. I don’t know about you, but if I hear “time series” and Python, I think Pandas! In the Python Data Science Handbook, Jake VanderPlas writes:

Pandas was developed in the context of financial modeling, so as you might expect, it contains a fairly extensive set of tools for working with dates, times, and time-indexed data.

Of course, time series are one thing, but spatial data handling is another. Lucky for us, this is where GeoPandas comes in. GeoPandas has been around for a while and version 0.4 has been released in June 2018. So far, I haven’t found examples that use GeoPandas to manage movement data, so I’ve set out to give it a shot. My trajectory class uses a GeoDataFrame df for data storage. For visualization purposes, it can be converted to a LineString:

import pandas as pd 
from geopandas import GeoDataFrame
from shapely.geometry import Point, LineString

class Trajectory():
    def __init__(self, id, df, id_col):
        self.id = id
        self.df = df    
        self.id_col = id_col
        
    def __str__(self):
        return "Trajectory {1} ({2} to {3}) | Size: {0}".format(
            self.df.geometry.count(), self.id, self.get_start_time(), 
            self.get_end_time())
        
    def get_start_time(self):
        return self.df.index.min()
        
    def get_end_time(self):
        return self.df.index.max()
        
    def to_linestring(self):
        return self.make_line(self.df)
        
    def make_line(self, df):
        if df.size > 1:
            return df.groupby(self.id_col)['geometry'].apply(
                lambda x: LineString(x.tolist())).values[0]
        else:
            raise RuntimeError('Dataframe needs at least two points to make line!')

    def get_position_at(self, t):
        try:
            return self.df.loc[t]['geometry'][0]
        except:
            return self.df.iloc[self.df.index.drop_duplicates().get_loc(
                t, method='nearest')]['geometry']

Of course, this class can be used in stand-alone Python scripts, but it can also be used in QGIS. The following script takes data from a QGIS point layer, creates a GeoDataFrame, and finally generates trajectories. These trajectories can then be added to the map as a line layer.

All we need to do to ensure that our data is ordered by time is to set the GeoDataFrame’s index to the time field. From then on, Pandas takes care of the time series aspects and we can access the index as shown in the Trajectory.get_position_at() function above.

# Get data from a point layer
l = iface.activeLayer()
time_field_name = 't'
trajectory_id_field = 'trajectory_id' 
names = [field.name() for field in l.fields()]
data = []
for feature in l.getFeatures():
    my_dict = {}
    for i, a in enumerate(feature.attributes()):
        my_dict[names[i]] = a
    x = feature.geometry().asPoint().x()
    y = feature.geometry().asPoint().y()
    my_dict['geometry']=Point((x,y))
    data.append(my_dict)

# Create a GeoDataFrame
df = pd.DataFrame(data).set_index(time_field_name)
crs = {'init': l.crs().geographicCrsAuthId()} 
geo_df = GeoDataFrame(df, crs=crs)
print(geo_df)

# Test if spatial functions work
print(geo_df.dissolve([True]*len(geo_df)).centroid)

# Create a QGIS layer for trajectory lines
vl = QgsVectorLayer("LineString", "trajectories", "memory")
vl.setCrs(l.crs()) # doesn't stop popup :(
pr = vl.dataProvider()
pr.addAttributes([QgsField("id", QVariant.String)])
vl.updateFields() 

df_by_id = dict(tuple(geo_df.groupby(trajectory_id_field)))
trajectories = {}
for key, value in df_by_id.items():
    traj = Trajectory(key, value, trajectory_id_field)
    trajectories[key] = traj
    line = QgsGeometry.fromWkt(traj.to_linestring().wkt)
    f = QgsFeature()
    f.setGeometry(line)
    f.setAttributes([key])
    pr.addFeature(f) 
print(trajectories[1])

vl.updateExtents() 
QgsProject.instance().addMapLayer(vl)

The following screenshot shows this script applied to a sample of the Geolife datasets containing 100 trajectories with a total of 236,776 points. On my notebook, the runtime is approx. 20 seconds.

So far, GeoPandas has proven to be a convenient way to handle time series with coordinates. Trying to implement some trajectory analysis tools will show if it is indeed a promising data structure for trajectories.

Visualize Postgres JSON data in QML widgets

As promised some time ago in “The new QML widgets in QGIS – When widgets get unbridled” we still owe you some fancy unicorns, but first let’s have a look at another nice feature that has been introduced in QGIS 3.4 LTR,  the reading of PostgreSQL JSON and JSONB types.
With JSON you have a lot of possibilities for storing unstructured data. In our case, it’s mainly interesting when the data are stored as an array or a JSON object. Let’s have a look at two examples.

Visualize Postgres JSON data with common widgets

With the usual QGIS widgets “List” and “Key/Value” you are able to display JSON arrays and simple JSON objects.

JSON array as List

[
    "European dark bee",
    "Carniolan honey bee",
    "Buckfast bee"
]

Simple JSON object as Key/Value

{
    "nomenclatura":"Apis mellifera mellifera",
    "name":"European dark bee",
    "link":"https://en.wikipedia.org/wiki/European_dark_bee"
}

Or of course both as plain text in the “Text Edit” widget:

Say hi to Postgres JSON in QML widget

Probably, your JSON data does not look really nice with the aforementioned widgets, luckily since QGIS 3.4, you are free to create your own QML widget. Since QGIS already loads the JSON data into structures that are supported by QML, we can use all the JSON data within the QML code.
Let’s assume you have the JSON array from above and you like the elegance of the blue of Jacques Majorelle. You create your personal list widget by adding the JSON field as an expression:

import QtQuick 2.0
Rectangle {
    width: 310; height: 250; color: "grey"
    Column {
        anchors.horizontalCenter: parent.horizontalCenter
        anchors.verticalCenter: parent.verticalCenter
        spacing: 5
        Repeater {
            model:expression.evaluate("\"jvalue\"")
            Rectangle {
                color: "#6050dc"
                width: 300; height: 50; radius: 10.0
                Text {
                    anchors.centerIn: parent
                    font.pointSize: 24
                    text: modelData
                }
            }
        }
    }
}

You will have your very personal list:

JSON also allows storing more complex data, like for example a list of objects. In that case, you will reach the limits of the common QGIS widgets.
Let’s assume you have a table looking like this:

nomenclatura name link
Apis mellifera mellifera European dark bee https://en.wikipedia.org/wiki/European_dark_bee
Apis mellifera carnica Carniolan honey bee https://en.wikipedia.org/wiki/Carniolan_honey_bee
Apis mellifera Buckfast bee https://en.wikipedia.org/wiki/Buckfast_bee

In JSON it would be stored like this:

[
    {"nomenclatura":"Apis mellifera mellifera","name":"European dark bee","link":"https://en.wikipedia.org/wiki/European_dark_bee"},
    {"nomenclatura":"Apis mellifera carnica","name":"Carniolan honey bee","link":"https://en.wikipedia.org/wiki/Carniolan_honey_bee"},
    {"nomenclatura":"Apis mellifera","name":"Buckfast bee","link":"https://en.wikipedia.org/wiki/Buckfast_bee"}
]

With the QML Widget you can use the QML TableView to visualize:

import QtQuick 2.0
import QtQuick.Controls 1.4
TableView {
    width: 600
    model: expression.evaluate("\"jvalue\"")
    TableViewColumn {
        role: "nomenclatura"
        title: "Nomenclature"
        width: 200
    }
    TableViewColumn {
        role: "name"
        title: "Name"
        width: 200
    }
    TableViewColumn {
        role: "link"
        title: "Wikipedia"
        width: 200
    }
}


Or, even more powerful, you can create your super individual table using the model and create each row by using a QML Repeater.
Additionally, you can use a lot of fancy stuff like:

  • mouse interaction
  • animation
  • opening an external link
  • … and so on


The QML code for that looks like this.

import QtQuick 2.0
Rectangle {
    width: 610; height: 500
    Column {
        anchors.horizontalCenter: parent.horizontalCenter
        anchors.verticalCenter: parent.verticalCenter
        Repeater {
            model: expression.evaluate("\"jvalue\"")
            Row {
                id: theRow
                height: mouseArea1.containsMouse || mouseArea2.containsMouse || mouseArea3.containsMouse ? 70 : 50;
                Rectangle { color: "lightblue";
                            border.width: 1
                            width: 150; height: parent.height
                            Text { anchors.centerIn: parent
                                   font.pointSize: 10; text: modelData.nomenclatura }
                            MouseArea {
                                id: mouseArea1
                                anchors.fill: parent
                                hoverEnabled: true
                            }
                }
                Rectangle { color: "lightgreen";
                            border.width: 1
                            width: 150; height: parent.height
                            Text { anchors.centerIn: parent
                                   font.pointSize: 10; text: modelData.name }
                            MouseArea {
                                id: mouseArea2
                                anchors.fill: parent
                                hoverEnabled: true
                            }
                }
                Rectangle {
                            id: linkField
                            color: "lightyellow";
                            border.width: 1
                            width: 300; height: parent.height
                            Text { anchors.centerIn: parent
                                   font.pointSize: 10; text: modelData.link }
                            MouseArea {
                                id: mouseArea3
                                anchors.fill: parent
                                hoverEnabled: true
                                onPressed: linkField.state = "PRESSED"
                                onReleased: linkField.state = "RELEASED"
                                onClicked: Qt.openUrlExternally(modelData.link)
                            }
                            states: [
                                State {
                                    name: "PRESSED"
                                    PropertyChanges { target: linkField; color: "green"}
                                },
                                State {
                                    name: "RELEASED"
                                    PropertyChanges { target: linkField; color: "lightyellow"}
                                }
                            ]
                            transitions: [
                                Transition {
                                    from: "PRESSED"
                                    to: "RELEASED"
                                    ColorAnimation { target: linkField; duration: 1000}
                                },
                                Transition {
                                    from: "RELEASED"
                                    to: "PRESSED"
                                    ColorAnimation { target: linkField; duration: 1000}
                                }
                            ]
                }
            }
        }
    }
}

And that’s it

I hope you liked reading and you will enjoy using it to make beautiful widgets and forms. If you have questions or inputs, feel free to add a comment.
… and in case you still asking where the promised unicorns are. Here’s is a super-fancy implementation 😉

My favorite new recipe in QGIS Map Design 2nd ed

If you follow me on Twitter, you have probably already heard that the ebook of “QGIS Map Design 2nd Edition” has now been published and we are expecting the print version to be up for sale later this month. Gretchen Peterson and I – together with our editor Gary Sherman (yes, that Gary Sherman!) – have been working hard to provide you with tons of new and improved map design workflows and many many completely new maps. By Gretchen’s count, this edition contains 23 new maps, so it’s very hard to pick a favorite!

Like the 1st edition, we provide increasingly advanced recipes in three chapters, each focusing on either layer styling, labeling, or creating print layouts. If I had to pick a favorite, I’d have to go with “Mastering Rotated Maps”, one of the advanced recipes in the print layouts chapter. It looks deceptively simple but it combines a variety of great QGIS features and clever ideas to design a map that provides information on multiple levels of detail. Besides the name inspiring rotated map items, this design combines

  • map overviews
  • map themes
  • graduated lines and polygons
  • a rotated north arrow
  • fancy leader lines

all in one:

“QGIS Map Design 2nd Edition” provides how-to instructions, as well as data and project files for each recipe. So you can jump right into it and work with the provided materials or apply the techniques to your own data.

The ebook is available at LocatePress.

(Nederlands) BGT Import plugin vernieuwd

Sorry, this entry is only available in the Dutch language

The new QML widgets in QGIS – When widgets get unbridled

Individuality is the definition of freedom. And freedom is the fundamental requirement of man’s mind. QGIS possibly cannot give you all the freedom you require in life. But at least a lot of freedom in how you manage your work. QGIS 3.4.0 LTR was released last week and it comes loaded with features supporting big freedom in the configuration of your projects.  Let’s focus on the QML Widget. QML is the smart casual look of widgets. With the help of some simple code, you will be able to visualize your data in the attribute form like never before. You can display beautiful charts, complex JSON data, and fancy colored unicorns. 

How it’s done

Let’s start with an example. In the Attribute Form configuration in the Layer Properties you have first to activate the drag and drop designer. Not only can you drag the field- and relation-items from the available widget list to the form layout list, but also a QML Widget. When you drop this item, it creates an “instance” of a QML Widget. This means, you can drag and drop as many QML Widgets as you like to have on your form and configure each of them individually.

QML (Qt Modelling Language) is a user interface specification and programming language. It allows developers and designers alike to create highly performant, fluidly animated and visually appealing applications. QML offers a highly readable, declarative, JSON-like syntax with support for imperative JavaScript expressions combined with dynamic property bindings. Source: Qt documentation

It’s a bit like an HTML page on the attribute form but very well integrated with Qt.
On dropping the item, the configuration dialog pops up. After closing you can come back to it by double-clicking the item in the form layout list, like you do it with containers and tabs. If your don’t know QML that much yet, the default snippets from the drop-down can create an example of a rectangle, a pie chart or a bar chart. This could help you to create your own widget. On the right you can see a preview of your widget in real time. There are powerful layout possibilities to design it according to your ideas. For more information about it see the QML layout part of the Qt documentation.

But a chart makes no sense if there is no data. Of course, you can enter the data directly into your QML code, but most likely you need the data of the features to be visualized. This brings us to expressions. You can use them like you are used to in Default Values, Constraints and Display Messages. You’ll find the well-known expression builder widget in this configuration as well.

Using expressions

So let’s assume we want to visualize who holds what share of a forest. These forests are owned by the country (national), the canton (cantonal) or private. To keep it simple we have three attributes for that: national_share,cantonal_share and private_share.
After creating the default pie chart you will find this snippet in the QML code text area:

PieSeries {
    id: pieSeries
    PieSlice { label: "First slice"; value: 25 }
    PieSlice { label: "Second slice"; value: 45 }
    PieSlice { label: "Third slice"; value: 30 }
}

Let’s set the field expressions into the PieSlice-values. Just select them in the expression widget and add them with the + into the chart.

As you can see the expressions in the code are wrapped inside expression.evaluate("<expression>"). This means there are no limits in using expressions.
You are open to use more complex expressions like e.g. for the title property of the pie chart:

title: expression.evaluate("CASE WHEN @layer_name LIKE \"forest\" THEN \"Forest\" ELSE @layer_name END")

Or in case the task with forest shares would be solved with relations to other layers by filling up a model with the children and the children’s share. This is possible by using expressions with the help of the expression functionrelation_aggregate.
More information about expressions can be found in the QGIS Documentation.
Back to our example. The result will look like this on the attribute form. It visualizes the share values in the pie chart.

The visualization is not (yet) updated in real time when the values change. But this would be a nice thing to have in the future… If you would like to support this, please contact us.

And that’s it

I hope you liked reading and you will enjoy using it to make beautiful widgets and forms. If you have questions or inputs, feel free to add a comment.
… and in case you still asking where the promised unicorns are. Well you have to wait for the part 2 of this article 😉
 

Add Realistic Mist and Fog to Topography in QGIS 3.2

I recently came across a great tutorial by in which he demonstrated how to create map of Switzerland in the style of Edward Imhof, the famed Swiss cartographer renowned for his hand painted maps of Switzerland and other mountainous regions of the world. John’s map used traditional hillshading, multidirectional hillshading and crucially, a translucent topographic layer that created a mist like appearance he likened to the sfumato technique used by painters since the Renascence.

I followed John’s tutorial in QGIS 3.2 and I was quite pleased with the initial result below. However, the process creating it is a bit too complicated for a tutorial so I set about simplifying the process and rather than imitating Imhof’s distinct style, my goal this time is realism.

The heart of the effect involves the very clever idea of using the topographic layer as a subtle opacity mask to simulate mist, fog and atmospheric haze. Have a look at the image below taken on March 17th, 2005 by NASA’s Terra satellite. This is the industrialised Po valley of northern Italy, surrounded by the Alps and Apennine Mountains that rise above the valley’s hazy pollution. The haze adds a sense of depth to the surrounding hills and mountains. It’s not uncommon to see fog and pollution in satellite imagery that gives way to the clear air in high mountains e.g. northern India and Nepal, China, Pakistan and India. Creating a similar mist effect in QGIS is actually quite simple.

First download topography for the Alps and Po region (a 68.55 Mb GeoTiff file derived from freely available EU-DEM data I resampled from 25 to 100m resolution). Next, make sure you have the plugin QuickMapServics (QMS) installed (menu Plugins – Manage and Install Plugins). This great plugin provides access to over 1000 basemaps.

Load the GeoTiff file into QGIS (Raster – Load) and rename the layer Hillshade. Right click the layer to open the Layer Properties window. In the Symbology panel, next to Render Type, choose Hillshade. Change the altitude to 35 degrees, Azimuth to 300 degrees and Z Factor of 1.5 (illuminating the landscape from the top left). Finally, change the Blending mode to Multiply. Click OK to close the dialogue.

To add the basemap layer, Esri World Imagery (Clarity), type “ESRI clarity” in the QMS search bar to find and add the basemap; Go to View – Panels and activate the QMS search bar if it isn’t initially visible. Make sure it’s the bottommost layer.

Oh, that’s a bit disappointing, we only increased the relief little a bit. It’s missing the vitally important mist layer.

To create mist, right click the Hillshade layer and choose Duplicate. Rename the new layer Mist and make sure it’s above the Hillshade layer. Now open the Layer Properties window of the layer, we’re going edit it’s attributes to make it look like mist.

Change the Render type to Singleband Pseudocolor and use 0 and 3000 for the min and max values (limiting maximum latitude of the mist to 3000 meters). Then open the colour ramp window by clicking on the Color ramp and enter these values:

  • Left Gradient – HSV 215 15 50 and 75% transparency
  • Right Gradient – HSV 215 15 50 and 0% transparency

Close the Color Ramp dialogue. In the Layer Properties window, and this is very important, change the Blending mode to Lighten. Click OK to close the Layer Properties window.

Wow, we have mist!

The mist effect looks great. It certainly adds a lot of realism to the topographic map, it now looks quite like NASA’s images. This is just a quick and basic map so there’s lots of scope to improve the effect. Play around with the colour of the mist layer and its opacity, or even brighten the Hillshade layer underneath. See what effects these changes have.

Here’s another example below. In this example I duplicated the hillshade layer and set the second hillshade layer to Multidirectional Hillshading (yes, QGIS 3.2 has Multidirectional Hillshading). I then adjusted the transparency of both hillshade layers so they blended together nicely. I then replaced the basemap with another duplicated topography layer that I coloured using the gradient sd-a (by Jim Mossman, 2005) using the cpt-city plugin. And lastly, I doubled the opacity of the mist layer turning it into a milky fog. I think it looks great!

What next? Well, there’s lots of possibilities. Perhaps download Martian topography and add mist to the bottom of Valles Marineris?

References:

Eduard Imhof – Biography

TV documentary about Eduard Imhof

The Map as an Artistic Territory: Relief Shading Works and Studies by Eduard Imhof

Haze in northern Italy – NASA Terra Satellite

Tzvetkov, J., 2018. Relief visualization techniques using free and open source GIS tools. Polish Cartographical Review, 50(2), pp.61-71.

Programme change…

See the Dutch website for more info on the programme.

Edit Features “In Place” crowdfund — made it to QGIS 3.4!

Well, thanks to the resounding success of our QGIS edit-in-place crowdfunding campaign, we’ve been frantically smashing away at our keyboards in an attempt to reward the QGIS community by sneaking this feature in a whole 4 months earlier than originally promised! And, we’re very proud to announce, that this exciting new feature has been implemented and will be included in the upcoming QGIS 3.4 release (due late October 2018). So go ahead — grab one of the nightly pre-release of QGIS 3.4 and checkout the results.

This wouldn’t have been possible without the rapid response to the campaign and the generosity of our wonderful backers:

(In addition to these backers, we’ve also received numerous anonymous donations to this feature from many other individuals — while we can’t list you all publicly, you’re also in our thanks!)

 

Keep an eye on this blog for other upcoming QGIS crowdfunding campaigns targeted at QGIS 3.6 and beyond… we’ve got lots more exciting work planned for these releases!

 

Dutch QGIS usergroup meeting

All presentations will be in Dutch. Please have a look at the Dutch version of this page to see more…

Edit Features “In Place” crowdfund — target reached!

Well, the final pledges have been tallied and we’re very proud to announce that our latest crowd funding campaign has been a roaring success!

We’ve been completely blown away by the response to this campaign. Thanks to some incredibly generous backers and donors, we’ve been able to hit the campaign target with plenty of time to spare. As a result, we’ll be pushing hard to reward the generosity of the community by trying to sneak this feature in for the upcoming QGIS 3.4 release (instead of the originally promised 3.6 release)! You can read more about what we’re adding at the campaign page.

We’d like to take this opportunity to extend our heartfelt thanks to all the backers who have pledged to support this project:

In addition to these backers, we’ve also received numerous anonymous donations to this feature from many other individuals — while we can’t list you all publicly, you’re also in our thanks!

Stay tuned for more updates to come as work proceeds on this feature…

QGIS speaks a lot of languages

QGIS is a real cosmopolitan. Born in Alaska sixteen years ago, it has spread all over the world since. Thanks to its open source mentality, it finds not only in economically strong countries big usergroups. No question, that beside all the developers, there is a bunch of brave translators giving everything to make and keep QGIS multilingual. It’s translated in over forty languages – even to Mandarin Chinese and Esperanto. Not only the application, but also its plugins.
And since the feature-loaded long term release 3.4.0 even the QGS-Projects themselves.  Thanks to the friendly support of QGIS Usergroup Switzerland and the QGEP Project.

How it comes

Plugins are often shipped with pre-configured project files. To provide them in the users individual language, you’ve been required to translate the project manually in the properties and store it separately. When you needed to change something, you have been coerced to update every single file. This is a big effort and fault-prone. So there appeared the idea to have translation files for each required language, and when the user opens the only one project, it will be translated to his specific language. And that’s, what this new functionality does.

How it’s done

Like QGIS and the plugins, the projects are translated with the Qt translation process. Means, it makes the translation according to a Qt Compiled Translation Source File (.qm file). When the user opens a project, QGIS checks for a .qm file laying in the same folder like the .qgs file, having the same name like the .qgs file and having the language-code as postfix of the users language (the language configured in the QGIS settings).
So when the user opens a project named “citybees.qgs” that is originally in English, but his QGIS language is German, it checks for a file named “citybees_de.qm”. The project’s layer names, field-aliases, container names and much more will be translated to German and the project will be automatically stored as “citybees_de.qgs”. So the user has his German project version and can use and edit it like he wishes. Super easy.

Start from the beginning

Swiss people love honey and so they are diligent beekeepers. So, let’s assume you want to provide a project about beekeeping in cities to your Swiss customers. Because in Switzerland people talk four different languages, you need to have the project multilingual in German, French and Italian. We skip Romansh, not because it’s less important or in the Romansh speaking parts are no cities, but because QGIS does not support Romansh (if you’ll propose this one day, you will have my vote).
Anyway. Let’s see what you have to do, to deliver the projects with the .qm file for German, French or Italian.

1. Create the project

You create your project about beekeeping and store it as “citybees.qgs”. You don’t have to care about languages at the moment. You name everything in your language. Assumed it’s English, you name the layers “apiary” and “area” and the fields “fid”, “bee-species”, “beekeeper” and so on.
On changes you will edit always this project and no translated projects.

2. Generate Ts File

In the project properties in the section General there is the part to generate a translation source file. First, you select the source language, to have this information in programs you’ll edit the file (like Qt Linguist or Transifex) afterwards. Per default the language of your QGIS is selected here.

When pressing Generate TS File you will find in your projects folder the new file “citybees.ts”.
But wait a minute, why are we generating a .ts file when we need a .qm file?
The .ts file is the translation source file and it’s the uncompiled .qm file. The .qm file contains compact binary format code Qt can make the translation of programs with, but you and your brave translator cannot read it. So you create a .ts file looking like this:

<!DOCTYPE TS>
<TS sourcelanguage="en_US">
 <context>
  <name>project:layers:apiary__offline__1f89f4fd_49da_4eb9_90b3_1f7b5e82840c</name>
  <message>
   <source>apiary</source>
   <translation type="unfinished"/>
  </message>
 </context>
 <context>
  <name>project:layers:apiary__offline__1f89f4fd_49da_4eb9_90b3_1f7b5e82840c:fieldaliases</name>
  <message>
   <source>fid</source>
   <translation type="unfinished"/>
  </message>
 </context>
 <context>
  <name>project:layers:apiary__offline__1f89f4fd_49da_4eb9_90b3_1f7b5e82840c:fieldaliases</name>
  <message>
   <source>bee_species</source>
   <translation type="unfinished"/>
  </message>
 </context>
 <context>
  <name>project:layers:apiary__offline__1f89f4fd_49da_4eb9_90b3_1f7b5e82840c:fieldaliases</name>
  <message>
   <source>beekeeper</source>
   <translation type="unfinished"/>
  </message>
 </context>
[...]

You see it’s simple XML code that contains mainly untranslated text in the <source> element and empty space for the translated text in the <translation> element.
You could enter your translations directly in this file using the text editor and then build the .qm file with the command lrelease, but it’s preferable to use tools like Qt Linguist orweb-based services like Transifex or Weblate.

3. Translate your File in Qt Linguist

You open Qt Linguist an you select the target language of the .qm file you want to build in the end. Let’s choose German.
The file opens and you see a list of entries described by the Context. The context is, where the strings are located in the QGIS project.

The string “beekeeper” stays in the context project:layers:apiary_1f7b5e82839c:fieldaliases and this means it’s a field or alias of the layer apiary_1f7b5e82839c in the project.
The translation is done simply over the graphical interface. To confirm your translation you can set the check mark.

4. Finally build your .qm file

You compile the translation – means build a .qm file – by simply select Release as… in the Qt Linguist and store it as “citybees_de.qm”.

And now your customer will be able to open your project in German 🙂

What’s translated

Most of the needed parameters like layer names and fields are translated. There could be still some strings in your use case that are not like for example action titles or labels. But the solution is designed, that it’s extendable for more project parameters (see the next chapter). So don’t worry if you will find parameters that cannot be translated yet. They possibly will be in the future.

Translatable strings:

  • layer names
  • layer group names
  • form attributes like tab titles and group box titles
  • relation names
  • field names and aliases
  • value relations

With field names and aliases it has a special behavior: while we should not translate the field names itself because they can be used as identification, the aliases are translated only. In case there is no alias in the original project, the translation of the field name would be written as an alias in the translated project. The field name stays the same. So you can just generate and translate without the fear of overwriting field names.

Content translation

There is a possibility to have a translation of the content as well. In particular using the value relation widget.
Let’s assume, you want to have the values in the field bee_species translated as well. Means the following bee species should be German:
– European dark bee
– Carniolan honey bee
– Buckfast bee

You can solve this by using the value relation widget. Means you create a non geometrical layer “beespecies” and enter the following values:

nomenclatura name_en name_de name_fr name_it
Apis mellifera mellifera European dark bee Dunkle Europäische Biene abeille noire ape nera
Apis mellifera carnica Carniolan honey bee Kärntner Biene abeille carniolienne ape carnica
Apis mellifera Buckfast bee Buckfastbiene abeille Buckfast ape Buckfast

And configure the field bee_species of apiary as value relation widget:

And now comes the magic:

When you create the .ts file it includes not only the field name bee_species but also the referenced value name_en:

 <context>
  <name>project:layers:apiary__offline__1f89f4fd_49da_4eb9_90b3_1f7b5e82840c:fields:bee_species:valuerelationvalue</name>
  <message>
   <source>name_en</source>
   <translation type="unfinished"/>
  </message>
 </context>

When you now “translate” the name_en to name_de the field is referenced to the German values of the entry:

Getting technical

Let’s have a quick look into the source code, shall we?

Generate Ts File

When you press the Generate Ts File button in the project properties, in the background happens the following:
First QGIS scans for the translatable strings in the currently loaded project and collects everything in a QgsTranslationContext object. This object contains the filename of the .ts file and all the collected translatable strings.
The strings are collected by firing a signal called requestForTranslatableObjects delivering the QgsTranslationContext. Every object that contains translatable strings connects a slot registering the strings in the received QgsTranslationContext:

void registerTranslatableObjects( QgsTranslationContext *translationContext )
{
  const QList<QgsLayerTreeLayer *> layers = mRootGroup->findLayers();
  for ( const QgsLayerTreeLayer *layer : layers )
  {
    translationContext->registerTranslation( QStringLiteral( "project:layers:%1" ).arg( layer->layerId() ), layer->name() );
[...]

This will be a growing list of strings as new features are added and missing bits are discovered.

Translate by QTranslator

The translation is made using the QTranslator. It’s loaded with the .qm file on reading the project and on loading of every single translatable string, it’s called to translate:

QString layername = mTranslator->translate( QStringLiteral( "project:layers:%1" ).arg( node.namedItem( QStringLiteral( "id" ) ).toElement().text() ), node.namedItem( QStringLiteral( "layername" ) ).toElement().text(), disambiguation, n );

That’s it

I hope you liked reading and if you have questions or inputs, feel free to add a comment.
Enjoy this cosmopolitious feature! 🙂

(Nederlands) 3 oktober QGIS gebruikersdag in Nieuwegein

Sorry, this entry is only available in the Dutch language

OpenCL acceleration now available in QGIS

What is OpenCL?

From https://en.wikipedia.org/wiki/OpenCL:

OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. OpenCL specifies programming languages (based on C99 and C++11) for programming these devices and application programming interfaces (APIs) to control the platform and execute programs on the compute devices. OpenCL provides a standard interface for parallel computing using task- and data-based parallelism.

Basically, you write a program and you execute it on a GPU (or, less frequently, on a CPU or on a DSP) taking advantage of the huge parallel programming capabilities of the modern graphic cards.

Depending on many different factors, the speed gain can vary to a great extent, but it is typically around one order of magnitude.

How QGIS benefits from OpenCL?

The work I’ve done consisted in integrating OpenCL support into QGIS and writing all the utilities to load, build and run OpenCL programs.

For now, I’ve ported the following QGIS core algorithms, all of them are availabe in processing:

  • slope
  • aspect
  • hillshade
  • ruggedness

Since the framework to support OpenCL is now in place, I think that more algorithms will be ported over the time.

During this development, even if was not in scope, the hillshade renderer has been optimized for speed and it can also benefit of OpenCL acceleration.

How to activate OpenCL support

OpenCL support is optional and opt-in, to use it, you need to activate it into the QGIS options dialog like shown in the screenshot below:

How much performance gain can I expect?

Well, YMMV, but here are some figures for a big DEM raster, low values mean faster execution.

GDAL means CPU execution using the GDAL processing algorithm.

How to install the OpenCL drivers?

Of course it depends on your specific hardware and on your O.S., AMD, NVidia and Intel have different distributions channels, in general the driver for your graphic card will also provide the OpenCL driver, if your GPU is compatible, if OpenCL is not available on your current machine, try to Google for OpenCL, your O.S. and graphic card.

If there is no OpenCL support for your graphic card, you might try to install a driver for your GPU (Intel for example provides them) and you will probably have a decent acceleration even if not as much as you can get on a real graphic card.

This fact worths some more explanation: you might ask your self why running and algorithm directly on the CPU and running it on the same CPU but using OpenCL would make any difference and the reason why it is generally faster by using OpenCL is that OpenCL will run the algorithm in parallel on all cores of your CPU, while a normal application (and QGIS does not make an exception here) will use a single core.

Credits

I started this work as a proof of concept in my spare time (that it is not much, lately) and when I realized that it was promising, I submitted a QGIS grant proposal in order to allocate some working time to port more algorithms, write tests and polish the implementation.

This work would not be possible without all the generous sponsors and donors that feed the QGIS grant program year after year, many thanks to the QGIS community for this amazing support!

Jürgen Fischer was as usual very helpful and took care of the windows builds, now available in OSGeo4W packages.

Nyall Dawson helped with the code review and with testing the implementation on different cards and machines.

Matthias Kuhn reviewed the code.

Even Rouault pointed me to some highly efficient GDAL algorithm optimizations that I’ve been able to integrate in QGIS.

 

 

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