That looks like it might be exactly what I'm hoping to do. Coming from a gnuplot background, I'm having a lot of trouble with the Gadlfy syntax, though. I can't seem to find any comprehensive documentation that lists all of the commands/options, and trying to understand it inductively from the minimal examples on the Gadfly site is frustrating. So far I haven't been able to make the contour plot that I'm hoping to make. Is there a resource you would recommend for learning Gadfly?
On Monday, May 16, 2016 at 11:56:14 AM UTC-4, Tom Breloff wrote: > > If your data is gridded (but just in vector form), then likely you could > just "zmat = reshape(z, numrows, numcols)" and then "contour(zmat)". > > On Mon, May 16, 2016 at 11:49 AM, <[email protected] <javascript:>> > wrote: > >> Yes, my data is gridded. And no, I don't plan to sample these density >> values later. I just want to plot it and see what it looks like :) I'm not >> sure how to reshape the data into a 2D array though, or how to make a >> contour plot from a dataset rather than from a function. Is there anything >> on this in the documentation? >> >> Thanks for your help, >> >> Amelia >> >> >> On Friday, May 13, 2016 at 8:30:36 PM UTC-4, Scott T wrote: >>> >>> Two key questions - is your data gridded? And do you plan to sample from >>> these density values later, or are you just wanting to plot it and see what >>> it looks like? >>> >>> If your data is gridded (your ~10000 lines cover every combination of x >>> and y values in the range that you are interested in), then you can use the >>> contour command in Gadfly, which is the volcano plot you described. You'll >>> first need to reshape the data so it's a 2D array: think of it as >>> displaying a 2D image, where the number at each point is the density. >>> However, for displaying this kind of data, I prefer heatmaps, and I don't >>> know if Gadfly supports those - you may have to look into the histogram2d >>> command. >>> >>> If it is not gridded (the x and y points don't have any particular >>> structure to them), it's still possible, but you have to choose a way to >>> decide how you want to turn it from unstructured data into a 2D image. The >>> histogram2d approach that Tom showed above is one option, where you treat >>> each density measurement as a weighted measurement in a histogram. But if >>> your data represents single measurements of a function that has meaningful >>> values away from those measured points, you probably want to interpolate >>> between those points. For this you can use a package like Dierckx, which >>> does interpolations on unstructured data. I also have some simple code that >>> does barycentric triangular interpolation between unstructured points, in >>> case you wanted to have a look at that. >>> >>> This may be overkill, however, if you just want to look at the data and >>> don't plan to interpolate or draw from those density values later. If >>> that's the case, the trisurface plot above might be just what you need for >>> showing you the shape of your density data. >>> >>> Whatever you choose, I can recommend Tom's Plots package as a nice >>> interface to the other plotting packages in Julia - it makes it easy to >>> switch between different plotting options like Gadfly and PyPlot depending >>> on what features they offer. >>> >>> Cheers, >>> Scott >>> >>> On Friday, 13 May 2016 15:34:19 UTC+1, [email protected] wrote: >>>> >>>> Dear Julia users, >>>> >>>> I have a rookie question about plotting in Gadfly. I have some density >>>> data in a plain-text file in the form of x y d, where d is the density at >>>> the point (x,y). I have about 10,000 lines of this data. I'm currently >>>> plotting old-school using gnuplot and since I don't like the looks of what >>>> I've been able to make, I'm hoping to be able to do something more elegant >>>> like Gadfly. I'm a relatively new Julia user as well. I like the "volcano" >>>> contour plot from the Gadfly documentation ( second plot from the top at >>>> http://dcjones.github.io/Gadfly.jl/geom_contour.html). I'm just not >>>> sure how to go about it. >>>> >>>> Has anyone done something like this before? I think it could be a >>>> really beautiful way to represent my data if I can get it to work. Any >>>> hints or suggestions would be greatly appreciated! >>>> >>>> Cheers, >>>> >>>> Amelia >>>> >>> >
