![]() ![]() When I first wrote this answer, I had used 10.csv generated with: i=0 plus a single outlier point outside of the line, on the top center of the plotĪnd the goal of this benchmark to find the point (5000000,20000000) on the graphical plot, and then determine the value of the third column from it, which is -1 in our test.a line with inclination 2 and 10 million points on it.The first few lines of 10m1.csv look like this:Īnd the very last one, the 10 million-first, is the outlier, and looks like: 5000000,20000000,-1 That problem can be represented by the following simplified test data: i=0 Įcho "$i,$((2 * i)),$((4 * i))" i=$((i + 1)) view all dimensions of the selected points (including at least X, Y and Z) to try and understand why they are outliers in the XY scatter.interactively select some interesting looking points from the plot with my mouse.do an XY scatter plot of multidimensional data, hopefully with Z as the point color.Inspired by the use case described at: I have benchmarked a few plotting programs with the exact same input files. The only trick will be to write the data into a file format that Paraview can easily read.Ī survey of open source interactive plotting software with a 10 million point scatter plot benchmark on Ubuntu They both are mainly for 3D data, but Paraview in particular does 2d as well, and is very interactive (and even has a Python scripting interface). Paraview is my personal favourite, and VisIt is another one. On the other hand, plotting-big-data is a pretty common task, and there are tools that are up for the job. I don't know of any python tools that will help you do this offhand. Now, if you want interactive, you're going to have to bin the data to plot, and zoom in on the fly. Gnuplot> plot 'bigdata.bin' binary format="%3float32" using 2:3 with dotsĪnd even Matplotlib can be made to behave with some caution (choosing a raster back end, and using pixels to mark points): #!/usr/bin/env pythonĭatatype=[('index',numpy.float32), ('floati',numpy.float32),ĭata = mmap(filename, datatype, 'r') Gnuplot has no trouble dealing with this: gnuplot> set term png This, I think is what is sinking matplotlib by default. The first thing to realize is that vector plots with glyphs at each point are going to be a disaster - for each of the 20 M points, most of which are going to overlap anyway, trying to render little crosses or circles or something is going to be a diaster, generating huge files and taking tonnes of time. Let's concentrate on non-interactive plots first. This generates a file of size ~229MB, which isn't all that big but you've expressed that you'd like to go to even larger files, so you'll hit memory limits eventually. Scipy.io.numpyio.fwrite(fd,data.size,data) Matplotlib has lots of options and the output is fine, but it's a huge memory hog and it fundamentally assumes your data is small. ![]() So your data isn't that big, and the fact that you're having trouble plotting it points to issues with the tools. Something like plt.swap_on_disk() could cache the stuff on my SSD ) Plt.plotfile(fname, cols=(0,1)) # index vs. Unpacked_file = unpack_set("test01.cfile", "test01.txt") # reformats output (precision configuration here) column to a variableīyte = f.read(4) # next row of the vector and read 1. column of the vectorįloatq = struct.unpack('f', byte) # write value of 2. column to a variableīyte = f.read(4) # read 2. column of the vectorįloati = struct.unpack('f', byte) # write value of 1. Output_filename = open(output_filename, 'wb')īyte = f.read(4) # read 1. Note: directly plotting with numpy results into shadowed functionsĭef unpack_set(input_filename, output_filename): Txt - index,in-phase,quadrature in plaintext import matplotlib.pyplot as pltĬfile - IEEE single-precision (4-byte) floats, IQ pairs, binary GNUplot fails, with a similar approach to the following. But I have no experience with other software. Is there any optimization potential to this, or another software/programming language (like R or so) which can handle larger data-sets? Actually I want much more data in my plots. I need the plot zoomable, and interactive. My framework (GNU Radio) saves the values (to avoid using too much disk space) in binary. Is there any solution to avoid that "shadowing" of my data-set?Ĭoncretely I deal with Digital Signal Processing and I have to use a high sample-rate. I have got a problem (with my RAM) here: it's not able to hold the data I want to plot. ![]()
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