- PLOT RESOLUTION ORIGIN GRAPHING PDF
- PLOT RESOLUTION ORIGIN GRAPHING PLUS
- PLOT RESOLUTION ORIGIN GRAPHING WINDOWS
Tessellation (i.e., you can safely re-model your kitchen floor with hexagonal-shaped tiles because you won't have any void space between the tiles when you are finished-not true for all other higher-n, n >= 7, polygons). Hexagon is the highest n-polygon that gives regular plane Inside that square is not everywhere equal) and Hexagons have nearest-neighbor symmetry (e.g., square bins don't,Į.g., the distance from a point on a square's border to a point Though less commonly used than e.g., circles, or squares, that hexagons are a better choice for the geometry of the binning container is intuitive:
PLOT RESOLUTION ORIGIN GRAPHING WINDOWS
So from a histogram, you can just count the number of points falling in each hexagon, discretiize the plotting region as a set of windows, assign each point to one of these windows finally, map the windows onto a color array, and you've got a hexbin diagram. If you're not familiar with this type of plot, it's just a bivariate histogram in which the xy-plane is tessellated by a regular grid of hexagons. This did not produce any errors but did not produce an output on Ubuntu even after changing around several parameters.In Matplotlib lexicon, i think you want a hexbin plot. Less successful test #6: plt.savefig('filename.pdf')Īnd then converting to jpeg on the command line: Less successful test #5: plt.savefig('filename.pdf')Īnd opening in GIMP, and exporting as a high quality png (increased the file size from ~100 KB to ~75 MB) Less successful test #4: plt.savefig('filename.pdf')Īnd then converting to png on the command line:Ĭonvert -density 300 filename.pdf filename.pngīut this is still too blurry when viewed close up. This also cannot be opened in powerpoint or Google Slides, with the same issue as above. Less successful test #3: plt.savefig('filename.svg')
PLOT RESOLUTION ORIGIN GRAPHING PLUS
This cannot be opened in Microsoft Office Professional Plus 2016 (so no powerpoint), same with Google Slides. Less successful test #2: plt.savefig('filename.pdf') Using a dpi value of up to 2000 still produced blurry images when viewed close up. This does save the image at a bit higher than the normal resolution, but it isn't high enough for publication or some presentations. Less successful test #1: plt.savefig('filename.png', dpi=300)
PLOT RESOLUTION ORIGIN GRAPHING PDF
OR simply opening the pdf and cropping to the image you need in adobe, saving as a png and importing the picture to powerpoint Pdftoppm -png -r 300 filename.pdf filename Plt.plot(WL, ABS, label='BN', color='red')Įxample graph of what I'm looking for: example graphįor future readers who found this question while trying to save high resolution images from matplotlib as I am, I have tried some of the answers above and elsewhere, and summed them up here.Īnd then converting this pdf to a png on the command line so you can use it in powerpoint:
Plt.plot(WL, T, label='BN', color='blue') WL, ABS, T = np.genfromtxt(fname, skip_header=1, unpack=True) # read file, skip header (1 line) and unpack into 3 variables # loop over all files in the current directory ending with. However, saving the picture by clicking right to the image gives very bad quality / low resolution images. I've used matplotlib for plotting some experimental results (discussed it in here: Looping over files and plotting.
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