I'm trying to generate a Voronoi diagram for a set of latitude/longitude points.
var points = [["-87.63374","41.878723"],["-87.680622","41.829353"],["-87.631739","41.8768"],["-87.626149","41.884431"]] ;
var boundingRegion = d3.geom.polygon([
[-88, 41.7],
[-88, 42.3],
[-87.5, 42.3],
[-87.5, 41.7]
]);
var voronoi = d3.geom.voronoi(points).map(function(cell) {
return boundingRegion.clip(cell);
});
document.write("<pre>"+JSON.stringify(voronoi, null, ' ')+"</pre>");
I have a JSFiddle for that basic example here:
http://jsfiddle.net/ZzjpC/2/
I'm putting in 4 points and clipping them by using a simple rectangle.
The points are such that I should see at least one clipped vertex for each of the resulting Voronoi regions... the first one alone does not meet that.
When you plot them on a Google Map, the polygons intersect and are in total disarray.
If you look at http://jsfiddle.net/ZzjpC/3/, where the last point has been removed, everything looks fine.
So here's my question: is there something wrong with my set of points that is causing the Voronoi diagram generation to fail? Or is this a D3 bug and I should be telling those folks?
Turns out the problem was with the fact that my Voronoi sites (points) were arrays of strings instead of floats was the cause of the issue. My guess is that there was an addition taking place somewhere that was executed as a string concatenation instead and that broke things.
Converting the points to floats instead of strings fixed the problem.
Related
I have a GeoJSON file with small details and features that I want to render using D3. Unfortunately, important details are lost because D3
removes polygon coordinate pairs that are closely spaced.
I've set up a small example to show this. Both links use the exact same GeoJSON data, rendered with both D3-geo and mapbox through github.
Specifically, notice the two areas marked by the red circles.
https://bl.ocks.org/alvra/eebb06be793bc06ff3ae01e6945298b6
https://gist.github.com/alvra/eebb06be793bc06ff3ae01e6945298b6
The top one one marks a part of polygon that is rounded using many closely spaced coordinate pairs, but D3 removes most points and just draws a rough square end.
The lower red circle marks a tiny triangle that is removed altogether. The adjacent polygons should touch exactly, but are also affected by D3's loss of precision.
I haven't found any documentation about D3's coordinate precision or a (configurable) feature size limit.
I've tried decreasing D3-geo's EPSILON and related EPSILON2 values and that removes this problem (for me), although I'm sure even smaller features will still be affected.
Assuming this is related to the fact that D3 uses proper geodesics for polygon segments, while the other mapping libraries just draw straight lines (in the output coordinate space),
I was hoping that this process can only introduce new points.
I haven't been able to find other users experiencing similar problems with small features, although I'm surprised this has never come up before.
Does anyone have an idea about the proper way to deal with this?
Through epsilon, I've narrowed the problem down to this use of pointEqual(). This indicates the problem is with clipCircle considering closely spaced coordinates equal and removes them.
Indeed, if I disable circular clipping projection.clipAngle(null), the problem disappears.
On a shape from a logical image, I am trying to extract the field of view from any point inside the shape on matlab :
I tried something involving to test each line going through the point but it is really really long.(I hope to do it for each points of the shape or at least each point of it's contour wich is quite a few times)
I think a faster method would be working iteratively by the expansion of a disk from the considered point but I am not sure how to do it.
How can I find this field of view in an efficient way?
Any ideas or solution would be appreciated, thanks.
Here is a possible approach (the principle behind the function I wrote, available on Matlab Central):
I created this test image and an arbitrary point of view:
testscene=zeros(500);
testscene(80:120,80:120)=1;
testscene(200:250,400:450)=1;
testscene(380:450,200:270)=1;
viewpoint=[250, 300];
imsize=size(testscene); % checks the size of the image
It looks like this (the circle marks the view point I chose):
The next line computes the longest distance to the edge of the image from the viewpoint:
maxdist=max([norm(viewpoint), norm(viewpoint-[1 imsize(2)]), norm(viewpoint-[imsize(1) 1]), norm(viewpoint-imsize)]);
angles=1:360; % use smaller increment to increase resolution
Then generate a set of points uniformly distributed around the viewpoint.:
endpoints=bsxfun(#plus, maxdist*[cosd(angles)' sind(angles)'], viewpoint);
for k=1:numel(angles)
[CX,CY,C] = improfile(testscene,[viewpoint(1), endpoints(k,1)],[viewpoint(2), endpoints(k,2)]);
idx=find(C);
intersec(k,:)=[CX(idx(1)), CY(idx(1))];
end
What this does is drawing lines from the view point to each directions specified in the array angles and look for the position of the intersection with an obstacle or the edge of the image.
This should help visualizing the process:
Finally, let's use the built-in roipoly function to create a binary mask from a set of coordinates:
FieldofView = roipoly(testscene,intersec(:,1),intersec(:,2));
Here is how it looks like (obstacles in white, visible field in gray, viewpoint in red):
Trying to implement EKG style "heartbeat" chart from a design and I'm having a hard time getting D3 to draw a path like I need.
The design spec states that the graph needs to return to nuetral/zero point between each and every data point, and that the curved path from the zero point should be close to the data point itself and rise sharply. See the attached images below
Here is the design....
And here is my attempt to match the curve with dummy data (black circle data points)...
The graph has a time scale X axis and a linear Y axis that ranges from 0 to 2 (my data points are 0,1, or 2 respectively). The line is using 'monotone' interpolation which is the least terrible looking.
Question:
Is there a better way to get this appearance without dummy data points?
Question-behind-the-question:
What is the best way to get D3 draw a custom paths (e.g. from a function)?
Sub-question:
Why does the monotone interpolation curve the path inward so sharply between the last 2 data points?
Any help is appreciated! The designers and client won't budge on this one, so I have to get it as close possible :(
I got a data set that where each sample has a size (0-1000) and a value (grade 1-5). I want to visualise the data with circles of different sizes along a line (domain axis), much like:
http://www.nytimes.com/interactive/2013/05/25/sunday-review/corporate-taxes.html?_r=1&
(note that circles even with the same effective taxrate do not overlap)
Example data:
sample 1: size 300 value 3.2
sample 2: size 45 value 3.8
sample 3: size 4400 value 4.0
sample 5: size 233 value 0.2
sample 6: size 4000 value 4.2
How can the data above be visualised using circles on a line (size decides diameter, value decides approximate position on the line) so that circles do not overlap?
I've been looking at D3's packing layout, but from what I can tell it doesn't support this out of the box. Anyone got any ideas on how to approach this?
Oooh, this one was a puzzle...
If you look at the code for the NYTimes graphic, it uses pre-computed coordinates in the data file, so that's not much use.
However, there's an unused variable declaration at the top of the script that hints that the original version used d3.geom.quadtree to lay out the circles. The quadtree isn't actually a layout method; it is used to create a search tree of adjacent nodes, so that when you need to find a node in a given area you don't have to search through the whole set. Example here.
The quadtree can therefore be used to identify which of your datapoints might be overlapping each other on the x-axis. Then you have to figure out how much you need to offset them in order to avoid that overlap. The variable radii complicate both functions...
I've got a test case implemented here:
http://fiddle.jshell.net/6cW9u/5/
The packing algorithm isn't perfect: I always add new circles to the outside of existing circles, without testing whether they could possibly fit closer in, so sometimes you get significant extra whitespace when it is just the far edges of circles bumping into each other. (Run it a few times to get an idea of the possibilities -- note that I've got x-variables distributed as random normal and r-variables distributed as random uniform.) I also got a stack overflow on the recursive methods during one iteration with N=100 -- the random distribution clearly wasn't distributed well enough for the quadtree optimization.
But it's got the basic functionality. Leave a comment here if you can't follow the logic of my code comments.
--ABR
Update
New fiddle here: http://fiddle.jshell.net/6cW9u/8/
After a lot of re-arranging, I got the packing algorithm to search for gaps between existing bubbles. I've got the sort order switched (so that biggest circles get added first) to show off how little circles can get added in the gaps -- although as I mention in the code comments, this reduces the efficiency of the quadtree search.
Also added various decoration and transition so you can clearly see how the circles are being positioned, and set the r-scale to be square root, so the area (not radius) is proportional to the value in the data (which is more realistic, and what the O.P. asked for).
D3's packing layout is not the answer here. It places circles in a spiral fashion around the existing group. Here's me reverse-engineering the algorithm behind packing layout:
I would suggest a force layout-based approach. That way, you can give your nodes force towards a gravitational center, and then let gravity do its thing.
Force layouts (e.g. Clustered Force Layout I) are usually animations, so you'll want to apply a static force layout.
I've wrapped up this approach in an example block, which looks like this:
My code to calculate the minimum translation vector using the Separating Axis Theorem works perfectly well, except when one of the polygons is completely contained by another polygon. I have scoured the internet for the solution to this problem and everyone just seems to ignore it ( http://www.codezealot.org/archives/55#sat-contain talks about this, but doesn't give a full solution...)
The pictures below is a screenshot from my program illustrating the problem. The translucent blue triangle is the position of the rectangle before the MTV is applied, and the other triangle is with the MTV applied.
It seems to me that the link you shared does give a solution to this. In your MTV calculation, you have to test for complete containment in a projection and change the calculations accordingly. (The pseudocode is in reference to figure 9 on that page.) Perhaps if you post your code, we can comment on why it isn't working.