I recommend testing your stuff with Plots... The overhead should be constant among backends, so you can use the same code to benchmark PyPlot, GR and Plotly/PlotlyJS. See the "backends" page of the Plots docs for more info. I recommend checking out master as there's been some good fixes/improvements since my last tag (I'll try to tag again today)
Also I'm hoping that there can be some hacking on the GLVisualize backend during JuliaCon! On Monday, June 13, 2016, Mauro <mauro...@runbox.com> wrote: > I also found that GR is a lot faster than PyPlot, so give that a try. > > On Mon, 2016-06-13 at 09:57, Andreas Lobinger <lobing...@gmail.com > <javascript:;>> wrote: > > Hello colleague, > > > > On Sunday, June 12, 2016 at 10:31:06 PM UTC+2, CrocoDuck O'Ducks wrote: > >> > >> Hi there! > >> > >> I have been experimenting a little with many plotting packages recently. > >> Being used to Matlab PyPlot seemed to work well for me... until this bug > >> <https://github.com/stevengj/PyPlot.jl/issues/209> I did not figure out > >> how to workaround. I often need to plot a lot of data. The fact is that > I > >> often work with sampled data, like audio. For example, I could have to > plot > >> 10 seconds of 192 kHz sampled audio. Even when PyPlot was working it was > >> hard to plot so many data: PyPlot was used to give up after few errors. > I > >> tried also other packages (Gadfly and few others) but seems like they > >> really struggle to plot so much stuff: they often kinda freeze. I am not > >> sure wether I am missing something or using the packages improperly or > the > >> packages are somewhat limited at this stage. I have resorted to export > the > >> data to .mat files and plot with matlab... > >> > >> My question is: how do you guys plot large data sets? Do you suggest a > >> plot package in particular? > >> > > > > I use some home-grown solutions and (still) Winston. I just tested > Plots.jl > > with GR backend and could plot 5e6 random lines. Maybe you look into > this. > > > > Wishing a happy day, > > Andreas >
