I am a novice QGis user, and I’m sure there is an easy way to do what I want, but I don’t have a clue as how to start. I downloaded a bunch of SRTM DEM sections and combined them into one raster layer. An image of my elevations and rivers is shown here.
The problem is that the area covered is all of eastern Europe, so it takes a long time to refresh whenever I pan around the map. Is there a way to speed this up?
I suppose that things would go faster had I not combined all the sections into one raster, but I want all the sections to have the same properties, and don’t want to have to change the properties for each segment one-at-a-time every time I change properties.
If someone could point me in the right direction on this that would be great!
There are several things you can do to increase your rendering performance, most of them under Settings -> Options -> Rendering:
You could use render caching to allow QGis to spare some computations when redrawing your rasters. You can also check render layers in parallel by using CPU cores to give the rendering more resources, as well as enable feature simplification for new layers. You can also uncheck the less jagged lines option to prevent the use of that extra performance it takes.
Another trick I usually do when moving around large maps and rasters is to uncheck the render option, move and pan around, and then check the render option back again on the desired region. This I found prevents unnecessary rendering when moving, panning and zooming repeated times. This is the render feature I was mentioning, you can find it in your bottom bar:
You can also check this related GIS Stackexchange question if you want to know more options.
Hope this helps.
Related
I understand it's often faster to pre-render graphics to an off-screen canvas. Is this the case for a shape as simple as a circle? Would it make a significant difference for rendering 100 circles at a game-like framerate? 50 circles? 25?
To break this into two slightly different problems, there are two aspects to what you're asking:
1) is drawing a shape off-screen and putting it on-screen faster
2) is drawing a shape one time and copying it to 100 different places faster than drawing a shape 100 times
The answer to the first one is "it depends".
That's a technique known as "buffering" and it's not really about speed.
The goal of buffering an image is to remove jerkiness from it.
If you drew everything on-screen, then as you loop through all of your objects and draw them, they're updating in real-time.
In the NES-days, that was normal, because there wasn't much room in memory, or much power to do anything about it, and because programmers didn't know much better, with the limited instructions they had to work with.
But that's not really the way games do things, these days.
Typically, they call all of the draw updates for one frame, then they take that whole frame as a finished image, and paste that whole thing on the screen.
The GPU (and GL/DirectX) takes care of this, by default, in a process called "double-buffering".
It's a double-buffer, because there's room for the "in-progress" buffer used for the updates, as well as the buffer that holds the final image from the last frame, that's being read by the monitor.
At the end of the frame processing, the buffers will "swap". The newly full frame will be sent to the monitor and the old frame will be overwritten with the new image data from the other draw calls.
Now, in HTML5, there isn't really access to the frame-buffer, so we do it ourselves; make every draw call to an offscreen canvas. When all of the updates are finished (the image is stable), then copy and paste that whole image to the onscreen canvas.
There is a large speed-optimization in here, called "blitting", which basically copies over only the parts that have changed, and reuses the old image.
There's a lot more to it than that, and there are a lot of caveats, these days, because of all of the special-effects we add, but there it is.
The second part of your question has to do with a concept called "instancing".
Instancing is similar to blitting, but while blitting is about only redrawing what's changed, instancing is about drawing the exact same thing several times in different places.
Say you're painting a forest in Photoshop.
You've got two options:
Draw every tree from scratch.
Draw one tree, copy it, paste it all over the image.
The downside of the second one is that each "instance" of the image looks exactly the same.
If your "template" image changes colour or takes damage, then all instances of the image do, too.
Also, if you had 87 different tree variations for an 8000 tree forest, making instances of them all would still be very fast, but it would take more memory, because you now need to save 87x more images than when it was just one tree, to reference on every draw call.
The upside is that it's still much, much faster.
To answer your specific question about X circles, versus instancing 1 circle:
Yes, it's still going to be a lot faster.
What a "lot" means, though, will change based on a lot of different things, because now you're talking about browsers on PCs.
How strong is the PC?
How good is the videocard?
How large is the canvas in software-pixels (not CSS pixels)?
How large are the circles? Do they have alpha-blending?
Is this written in WebGL or software?
If software is the canvas compositing in hardware mode?
For a typical PC, you should still be able to hit 60fps in Chrome, drawing 20 circles, I think (depending on what you're doing to them... ...just drawing them onscreen, every frame is simple), so in this case, the instances are still a "lot" faster, but it's not going to matter, because you've already passed the performance-ceiling of Canvas.
I don't know that the same would be true on phones/tablets, or battery-powered laptops/netbooks, though.
Yes, transferring from an offscreen canvas is faster than even primitive drawings like an arc-circle.
That's because the GPU just copies the pixels from the offscreen canvas (not much CPU effort required)
I'm toying around with d3.js and some other javascript libraries plotting geoJSON data in the browser. I've done some cool things with the data, but to give it a bit more context I want to lay it over a map that fills the browser (i'll probably make it opaque to not distract). I've spent a few hours with the google and bing API, which have great "zoom" options, but I want to specify how detailed the map becomes without further restricting how far I can zoom in. Is there a way to do this? I.e. I want to zoom further in and be able to pan around, without all of the side streets appearing-- maintaining the "main drags" of the city I'm working with.
I'm open to using different resources, but this is not a commercial product so I don't want to pay anything. As far as I know, the option for increasing and decreasing the detail/resolution of the pane is by increasing or decreasing the zoom variable. Thanks.
Edit: There really doesn't need to be much interaction with the map. This is kind of the intention http://www.caudillweb.com/temp/d3_choropleth.html, but since it will be at the city level, as you can see when you zoom in that far all sorts of different elements and side streets appear, taking away from the clean view at a more zoomed-out level and it begins to distract from the data.
I would like to draw a map of current temperatures (or air pressures, etc.) from many weather stations, with the underlying map still recognizable. the problem is easiest to think of as follows:
I have an array of spot measurements from irregularly spaced dots---think triples of GPS coordinates with one temperature value each. my stations can be very close to or very far apart from one another, and a user may want to zoom in or out. cold should be blue, warm should be red. Ideally, I would like to just pass the array, the color range, and have the rest be taken care of. I would prefer everything to be inside a web browser. The user needs to be able to zoom in, zoom out, move around, and get back to his current location.
I do not even know how to think about this problem. If a user has zoomed out enough, non-transparent dots could be so close as to obscure the terrain. However, zooming in, it would be nice to recognize the dot that is the station itself. This presumably requires some intelligence that realizes how many dots there are, e.g., relative to the density of the display? not sure.
I believe google maps charges for many API calls, so I would prefer using an open map and/or open API that can use different underlying maps. It does not have to be fancy. I don't care about directions, etc.---just a map that is recognizable at most zoom settings, with landmark and street names, and my nice temperature station overlay coloring, so that a user can visualize where it is cold and where it is warm.
(Stations come online and offline, but I don't need to update this more than once an hour. I can place the map measurements into a file that is URL web-accessible.)
is this an easy or a hard problem for the high-level web programmer?
/iaw
after looking around for a long time, I think the best way to do this is with html5 openlayers nexrad.
alas, the docs seem to be a mess. half the examples that I found did not seem to work. it's pretty hit-or-miss. similarly, the openlayers cookbook also seems to be outdated and has incorrect examples, but they did have a reasonably short example of such a nexrad map overlaid on the U.S., that one can further study.
I am trying to choose the right technology to use for updating a project that basically renders thousands of points in a zoomable, pannable graph. The current implementation, using Protovis, is underperformant. Check it out here:
http://www.planethunters.org/classify
There are about 2000 points when fully zoomed out. Try using the handles on the bottom to zoom in a bit, and drag it to pan around. You will see that it is quite choppy and your CPU usage probably goes up to 100% on one core unless you have a really fast computer. Each change to the focus area calls a redraw to protovis which is pretty darn slow and is worse with more points drawn.
I would like to make some updates to the interface as well as change the underlying visualization technology to be more responsive with animation and interaction. From the following article, it seems like the choice is between another SVG-based library, or a canvas-based one:
http://www.sitepoint.com/how-to-choose-between-canvas-and-svg/
d3.js, which grew out of Protovis, is SVG-based and is supposed to be better at rendering animations. However, I'm dubious as to how much better and what its performance ceiling is. For that reason, I'm also considering a more complete overhaul using a canvas-based library like KineticJS. However, before I get too far into using one approach or another, I'd like to hear from someone who has done a similar web application with this much data and get their opinion.
The most important thing is performance, with a secondary focus on ease of adding other interaction features and programming the animation. There will probably be no more than 2000 points at once, with those small error bars on each one. Zooming in, out, and panning around need to be smooth. If the most recent SVG libraries are decent at this, then perhaps the ease of using d3 will outweigh the increased setup for KineticJS, etc. But if there is a huge performance advantage to using a canvas, especially for people with slower computers, then I would definitely prefer to go that way.
Example of app made by the NYTimes that uses SVG, but still animates acceptably smoothly:
http://www.nytimes.com/interactive/2012/05/17/business/dealbook/how-the-facebook-offering-compares.html . If I can get that performance and not have to write my own canvas drawing code, I would probably go for SVG.
I noticed that some users have used a hybrid of d3.js manipulation combined with canvas rendering. However, I can't find much documentation about this online or get in contact with the OP of that post. If anyone has any experience doing this kind of DOM-to-Canvas (demo, code) implementation, I would like to hear from you as well. It seems to be a good hybrid of being able to manipulate data and having custom control over how to render it (and therefore performance), but I'm wondering if having to load everything into the DOM is still going to slow things down.
I know that there are some existing questions that are similar to this one, but none of them exactly ask the same thing. Thanks for your help.
Follow-up: the implementation I ended up using is at https://github.com/zooniverse/LightCurves
Fortunately, drawing 2000 circles is a pretty easy example to test. So here are four possible implementations, two each of Canvas and SVG:
Canvas geometric zooming
Canvas semantic zooming
SVG geometric zooming
SVG semantic zooming
These examples use D3's zoom behavior to implement zooming and panning. Aside from whether the circles are rendered in Canvas or SVG, the other major distinction is whether you use geometric or semantic zooming.
Geometric zooming means you apply a single transform to the entire viewport: when you zoom in, circles become bigger. Semantic zooming in contrast means you apply transforms to each circle individually: when you zoom in, the circles remain the same size but they spread out. Planethunters.org currently uses semantic zooming, but it might be useful to consider other cases.
Geometric zooming simplifies the implementation: you apply a translate and scale once, and then all the circles are re-rendered. The SVG implementation is particularly simple, updating a single "transform" attribute. The performance of both geometric zooming examples feels more than adequate. For semantic zooming, you'll notice that D3 is significantly faster than Protovis. This is because it's doing a lot less work for each zoom event. (The Protovis version has to recalculate all attributes on all elements.) The Canvas-based semantic zooming is a bit more zippy than SVG, but SVG semantic zooming still feels responsive.
Yet there is no magic bullet for performance, and these four possible approaches don't begin to cover the full space of possibilities. For example, you could combine geometric and semantic zooming, using the geometric approach for panning (updating the "transform" attribute) and only redrawing individual circles while zooming. You could probably even combine one or more of these techniques with CSS3 transforms to add some hardware acceleration (as in the hierarchical edge bundling example), although that can be tricky to implement and may introduce visual artifacts.
Still, my personal preference is to keep as much in SVG as possible, and use Canvas only for the "inner loop" when rendering is the bottleneck. SVG has so many conveniences for development—such as CSS, data-joins and the element inspector—that it is often premature optimization to start with Canvas. Combining Canvas with SVG, as in the Facebook IPO visualization you linked, is a flexible way to retain most of these conveniences while still eking out the best performance. I also used this technique in Cubism.js, where the special case of time-series visualization lends itself well to bitmap caching.
As these examples show, you can use D3 with Canvas, even though parts of D3 are SVG-specific. See also this force-directed graph and this collision detection example.
I think that in your case the decision between canvas and svg is not like a decision between »riding a Horse« or driving a »Porsche«. For me it is more like the decision about the cars color.
Let me explain:
Assuming that, based on the framework the operations
draw a star,
add a star and
remove a star
take linear time. So, if your decision of the framework was good it is a bit faster, otherwise a bit slower.
If you go on assuming that the framework is just fast, than it becomes totally obvious that the lack of performance is caused be the high amount of stars and handling them is something none of the frameworks can do for you, at least I do not know about this.
What I want to say is that the base of the problem leads to a basic problem of computational geometry, namely: range searching and another one of computer graphics: level of detail.
To solve your performance problem you need to implement a good preprocessor which is able to find very fast which stars to display and is perhaps able to cluster stars which are close together, depending on the zoom. The only thing that keeps your view vivid and fast is keeping the number of stars to draw as low possible.
As you stated, that the most important thing is performance, than I would tend to use canvas, because it works without DOM operations. It also offers the opportunity to use webGL, what increases graphic performance a lot.
BTW: did you check paper.js? It uses canvas, but emulates vector graphics.
PS: In this Book you can find a very detailed discussion about graphics on the web, the technologies, pros and cons of canvas, SVG and DHTML.
I recently worked on a near-realtime dashboard (refresh every 5 seconds) and chose to use charts that render using canvas.
We tried Highcharts(SVG based JavaScript Charting library) and CanvasJS(Canvas based JavaScript Charting library). Although Highcharts is a fantastic charting API and offers way more features we decided to use CanvasJS.
We needed to display at least 15 minutes of data per chart (with option to pick range of max two hours).
So for 15 minutes: 900 points(data point per second) x2(line and bar combination chart) x4 charts = 7200 points total.
Using chrome profiler, with CanvasJS the memory never went above 30MB while with Highcharts memory usage exceeded 600MB.
Also with refresh time of 5 seconds CanvasJS rendering was allot more responsive then Highcharts.
We used one timer (setInterval 5 seconds) to make 4 REST API calls to pull the data from back end server which connected to Elasticsearch. Each chart updated as data is received by JQuery.post().
That said for offline reports I would go with Highcharts since its more flexible API.
There's also Zing charts which claims to use either SVG or Canvas but haven't looked at them.
Canvas should be considered when performance is really critical. SVG for flexibility. Not that canvas frameworks aren't flexible, but it takes allot more work for canvas framework to get the same functionality as an svg framework.
Might also look into Meteor Charts, which is built on top of the uber fast KineticJS framework: http://meteorcharts.com/
I also found when we print to PDF a page with SVG graphics, the resulting PDF still contains a vector-based image, while if you print a page with Canvas graphics, the image in the resulting PDF file is rasterized.
I have a similar problem to this post. I need to display up to 1000 polygons on an embedded Google map. The polygons are in a SQL database, and I can render each one as a single KML file on the fly using a custom HttpHandler (in ASP.NET), like this http://alpha.foresttransparency.org/concession.1.kml .
Even on my (very fast) development machine, it takes a while to load up even a couple dozen shapes. So two questions, really:
What would be a good strategy for rendering these as markers instead of overlays once I'm beyond a certain zoom level?
Is there a publicly available algorithm for simplifying a polygon (reducing the number of points) so that I'm not showing more points than make sense at a certain zoom level?
For your second question: you need the Douglas-Peucker Generalization Algorithm
For your first question, could you calculate the area of a particular polygon, and relate each zoom level to a particular minimum area, so as you zoom in or out polygon's disappear and markers appear depending on the zoom level.
For the second question, I'd use Mark Bessey's suggestion.
I don't know much aobut KML, but I think the usual solution to question #2 involves iterating over the points, and deleting any line segments under a certain size. This will cause some "unfortunate" effects in some cases, but it's relatively fast and easy to do.
I would recommend 2 things:
- Calculate and combine polygons that are touching. This involves a LOT of processing and hard math, but I've done it so I know it's possible.
- Create your own overlay instead of using KML in PNG format, while you combine them in the previous suggestion. You'll have to create a LOT of PNGs but it is blazing fast on the client.
Good luck :)
I needed a solution to your #2 question a little bit ago and after looking at a few of the available line-simplification algorithms, I created my own.
The process is simple and it seems to work well, though it can be a bit slow if you don't implement it correctly:
P[0..n] is your array of points
Let T[n] be defined as the triangle formed by points P[n-1], P[n], P[n+1]
Max is the number of points you are trying to reduce this line to.
Calculate the area of every possible triangle T[1..n-1] in the set.
Choose the triangle T[i] with the smallest area
Remove the point P[i] to essentially flatten the triangle
Recalculate the area of the affected triangles T[n-1], T[n+1]
Go To Step #2 if the number of points > Max