I'd like to build a chart similar to:
Elevation over distance
This chart shows 3 things: elevation (y) distance (x) and colour represents the gradient change. How can I replicate this using D3.js?
You can check sample in the samples and pick something suitable for you depending on your requirement. But I'm suggesting something like this or this . First one does not give you color changing capability with it. You may need to read the documentation and find out. You can use the second one after reducing the width of bar to be very small. You may need to convert this to cater your data input method. I'm strongly suggesting you to go through the samples. As a help I'm posting few more samples you can customize.
Area Gradient fill
Applying a colour gradient to an area fill in d3.js
Related
I would like to density plot of some vectors (some realizations in probabilistic concept) and also their confidence interval in Matlab, enter image description herelike the figure I attached. The grey shadows are the data and the dashed lines are the confidence interval. Any suggestions?
Thanks a lot.
This can be done easily using Gramm toolbox avaialbale at https://github.com/piermorel/gramm/blob/master/README.md
The link also gives a minimal working example as well as information on more advanced control of the figure.
Has anyone added the ability to display values in a boxplot for dc.js?
Interesting answer given to this question related to matplotlib.
Adding a scatter of points to a boxplot using matplotlib
As it's currently implemented, the box plot will display any outliers as circles, and outliers are defined as the points which do not fall within the whiskers.
If you're willing to change the source, it's pretty easy to disable the whiskers and show all the data points.
You just need to change line 42:
var _whiskers = _whiskersIqr(_whiskerIqrFactor);
https://github.com/dc-js/dc.js/blob/356fccea3a1dbd49a76fb1841f280ffad87d725f/src/box-plot.js#L42
You could just set it to null, or add an accessor for whiskers. (There really should be one, looks like an oversight.)
It looks like this with no whiskers:
You'd have to dig a bit deeper and change the underlying d3-plugin if you want to display whiskers along with the data points.
I have the coordinate indicating the start of each letter within a word. I have set the plot function to make a red circle at that coordinate like so:
The problem is that the paper I am adding this image to has a structure of 2 columns per page. And when I add 2 of the above image to the same column, the circles become very small and difficult to notice.
I tried instead of circles to make triangles or pentagrams. I get the same result, they become too small to distinguish.
How can I make this more distinguishable? Especially when its printed in black and white.
You can change the marker size of the markers, and\or overlay two different markers one of the other. For example:
x=1:100;
y=rand(1,100);
plot(x,y); hold on
n=20:20:60;
plot(x(n),y(n),'r+','MarkerSize',30,'LineWidth',2);
plot(x(n),y(n),'ro','MarkerSize',15,'LineWidth',2);
There are many other degrees of freedom you can use to add \ change to this. It is a very basic question that you could have answered yourself if you read the documentation of plot in TMW website.
I need some advice about how to improve the visualization of cartographic information.
User can select different species and the webmapping app shows its geographical distribution (polygonal degree cells), each specie with a range of color (e.g darker orange color where we find more info, lighter orange where less info).
The problem is when more than one specie overlaps. What I am currently doing is just to calculate the additive color mix of two colors using http://www.xarg.org/project/jquery-color-plugin-xcolor/
As you can see in the image below, the resulting color where two species overlap (mixed blue and yellow) is not intuitive at all.
Someone has any idea or knows similar tools where to get inspiration? for creating the polygons I use d3.js, so if more complex SVG features have to be created I can give a try.
Some ideas I had are...
1) The more data on a polygon, the thicker the border (or each part of the border with its corresponding color)
2) add a label at the center of polygon saying how many species overlap.
3) Divide polygon in different parts, each one with corresponding species color.
thanks in advance,
Pere
My suggestion is something along the lines of option #3 that you listed, with a twist. Rather painting the entire cell with species colors, place a dot in each cell, one for each species. You can vary the color of each dot in the same way that you currently are: darker for more, ligher for less. This doesn't require you to blend colors, and it will expose more of your map to provide more context to the data. I'd try this approach with the border of the cell and without, and see which one works best.
Your visualization might also benefit from some interactivity. A tooltip providing more detailed information and perhaps a further breakdown of information could be displayed when the user hovers his mouse over each cell.
All of this is very subjective. However one thing's for sure: when you're dealing with multi-dimensional data as you are, the less you project dimensions down onto the same visual/perceptual axis, the better. I've seen some examples of "4-dimensional heatmaps" succeed in doing this (here's an example of visualizing latency on a heatmap, identifying different sources with different colors), but I don't think any attempt's made to combine colors.
My initial thoughts about what you are trying to create (a customized variant of a heat map for a slightly crowded data set, I believe:
One strategy is to employ a formula suggested for
n + 1
with regards to breaks in bin spacing. This causes me some concern regarding how many outliers your set has.
Equally-spaced breaks are ideal for compact data sets without
outliers. In many real data sets, especially proteomics data sets,
outliers can make this representation less effective.
One suggestion I have would be to consider the idea of adding some filters to your categories if you have not yet. This would allow slimming down the rendered data for faster reading by the user.
another solution would be to use something like (Comprehensive) R
or maybe even DanteR
Tutorial in displaying mass spectrometry-based proteomic data using heat maps
(Particularly worth noting I felt, was 'Color mapping'.)
I'm trying to build something like the Liquify filter in Photoshop. I've been reading through image distortion code but I'm struggling with finding out what will create similar effects. The closest reference I could find was the iWarp filter in Gimp but the code for that isn't commented at all.
I've also looked at places like ImageMagick but they don't have anything in this area
Any pointers or a description of algorithms would be greatly appreciated.
Excuse me if I make this sound a little simplistic, I'm not sure how much you know about gfx programming or even what techniques you're using (I'd do it with HLSL myself).
The way I would approach this problem is to generate a texture which contains offsets of x/y coordinates in the r/g channels. Then the output colour of a pixel would be:
Texture inputImage
Texture distortionMap
colour(x,y) = inputImage(x + distortionMap(x, y).R, y + distortionMap(x, y).G)
(To tell the truth this isn't quite right, using the colours as offsets directly means you can only represent positive vectors, it's simple enough to subtract 0.5 so that you can represent negative vectors)
Now the only problem that remains is how to generate this distortion map, which is a different question altogether (any image would generate a distortion of some kind, obviously, working on a proper liquify effect is quite complex and I'll leave it to someone more qualified).
I think liquefy works by altering a grid.
Imagine each pixel is defined by its location on the grid.
Now when the user clicks on a location and move the mouse he's changing the grid location.
The new grid is again projected into the 2D view able space of the user.
Check this tutorial about a way to implement the liquify filter with Javascript. Basically, in the tutorial, the effect is done transforming the pixel Cartesian coordinates (x, y) to Polar coordinates (r, α) and then applying Math.sqrt on r.