The 'basis set' in DX is the "positions" component. You are close to what you need.
You need a 1-D (rank 1 shape 1) "positions". They can be simply 0..n-1, where n = number of items in (each of) your data array(s). This is what binds the other components together, in this case, just like an array index, but more generally, even if these were 3-D positions representing points in 3-D space, you would still associate your "data" components with the "positions". You can make this beast with Enumerate and Compute. Enumerate outputs a scalar array, Compute can make it 1-D vector (see below).
By virtue of associating the 4 data components (time is not special in DX) with the same positions, you 'relate' them as in a relational database, if you like to think of it that way. You have also guaranteed that each array has the same length and appears in the proper order, i.e., you've arranged it so that position 0 == time "0" (whatever actual time value that may be) == data0[0] == data1[0] == data2[0] (where "==" means "corresponds to" or "associates with"). So on up to position n-1 ==...data2[n-1]. These 5 components are bound into a Field because most DX modules like to work on Fields (because they know where things are stored, how they are associated, etc.).
So now it's trivial to Extract(data0) and Extract(data2) in parallel operations from the Field, Compute(float([a,b])) to make an array (of length n) of 2-vector floats [data0, data2]. These will become the new "positions" of the new Field that you will actually render. I like to do things the simple clean way, so trying to reinsert these over the old positions is not necessarily the best way to proceed. Instead, just send this 2-vector array into Construct's origin input. Viola, you get a new Field whose positions are your 2-vectors. You also get unnecessary (and sometimes annoying) line connections that join all these points in order, so I will often Remove("connections") right after Construct. Glyph, AutoColor, Image and you have a 2-d scatterplot. Add axes in Image. Any 2 of the 4 data components can be used. You can expand Compute to handle [a,b,c] and you get 3-d scatterplots. You can send any of the 4 data components (even if you've used them in positions) into the Construct "data" input to insert data onto each 2-vector position. Then AutoColor and Glyph will react to those data values (by default, Construct kicks out no data, so you have to put a "1" into "data" to avoid AutoColor bitching about the lack of data to color).
By the way, a scalar is not one-dimensional. It is zero-dimensional by definition. There is a precise meaning to 1-dimensional as you will find if you try to make a positions array with a scalar array. Doesn't work. You have to 'cast' it to 1-vector as follows: scalar input "a" -> Compute([a]). Further, positions MUST be float, thus the cast I did above for safety since one never knows what the 4 data input types are.
rank 0 = scalar (has no shape)
rank 1 = vector, now you must declare shape = n, where n = number of vector components (usually 1, 2, or 3, but DX has no known limit: I've worked with 57, and strings are character vectors that go to at least 1024)
rank 2 = tensor (read the manual)
On Jul 29, 2005, at 1:55 AM, Matt Genovese wrote:
Hello,
I am a little confused regarding the OpenDX data model, and would like to solicit input from those who understand it better than I.
My project is fairly simple: I am writing a C program to capture data as time progresses, and plot it in DX. There are one or more axes (sources of data values), and obviously the time-axis is another source of data (there can actually be multiple discrete time axes, but I'll keep it simple for now). Note that time does not progress at a constant rate.
The goal is to be able to plot any axis vs. a time axis. However, more generally, I'd like to be able to plot any axis vs. any other axiswhich is really a scatter plot. The points on the scatter plot are correlated (linked) by the discrete time which they were captured in the simulation.
I'd like to understand how to best assemble this into the DX data model. My attempt is to group all the axes under a DX Field. Each axis is essentially a DX Array of data, which is a component of the Field. However, does this allow me to formulate the time-based plots or scatter plots I am looking for? The Arrays I was building are scalar (rank 0) - just raw values (doubles) obtained over time...one for each axis. I am also confused as to the "rank" and "shape" parameters, and how they affect organization of the data in the Arrayso perhaps this is part of my problem.
So for example, my thinking is that if I had 3 data sources, and they're sampled over time, I have: 4 "axes" - 4 DX Arrays as components under 1 DX Field object. Three of the arrays are one-dimensional and contain the data values, and the fouth array is one-dimensional and contains the capture times for all points. Then the three data
