I've managed to plot quite a few large datasets. GR through Plots.jl works 
very well for this. I tend to still prefer the defaults of PyPlot, but GR 
is just so much faster that I switch the backend whenever the amount of 
data gets unruly (larger than like 5-10GB, and it's worked to save a raster 
image from data larger than 40-50 GB). Plots + GR is a good combo.

On Wednesday, September 21, 2016 at 4:52:43 AM UTC-7, Igor wrote:
>
> Hello!
> did you managed to plot big data sets? You can try to use my small package 
> for this (  https://github.com/ig-or/qwtwplot.jl ) - it's very 
> interesting for me how it can handle big data sets.
>
> Best regards, Igor
>
>
> четверг, 16 июня 2016 г., 0:08:42 UTC+3 пользователь CrocoDuck O'Ducks 
> написал:
>>
>>
>> <https://lh3.googleusercontent.com/-8krr2WeB6rg/V2HDxDDxC2I/AAAAAAAAAHc/i9bcirHz4pgfCB14XpRB8dEKSUIbT7ZrQCLcB/s1600/10%2BkHz.png>
>>
>>
>> <https://lh3.googleusercontent.com/-bEY0cKEt1uc/V2HDtv11kEI/AAAAAAAAAHU/qcDhekOYjUsOsKoDJXnqPMuVCjZlFwuagCLcB/s1600/100%2BHz.png>
>> Hi, thank you very much, really appreciated. GR seems pretty much what I 
>> need. I like I can use Plots.jl with it. PlotlyJS.jl is very hot, I guess I 
>> will use it when I need interactivity. I will look into OpenGL related 
>> visualization tools for more advanced plots/renders.
>>
>> I just have a quick question. I just did a quick test with GR plotting 
>> two 1 second long sine waves sampled at 192 kHz, one of frequency 100 Hz 
>> and one of frequency 10 kHz. The 100 Hz looks fine but the 10 kHz plot has 
>> blank areas (see attached pictures). I guess it is due to the density of 
>> lines... probably solved by making the plot bigger?
>>
>>

Reply via email to