Hello,
I am new to yt and I am interesting in plotting a volume rendering with output file from enzo cosmology simulation.
For the time being, I get to plot a box ; here's the result :
I would like now to plot borders of this box too like on this image :
Here's the yt script I use :

from yt.mods import * from yt.utilities.amr_kdtree.api import AMRKDTree from time import time import matplotlib.colorbar as cb
# Load up your dataset num='70' pf = load('RD00'+num+'/RedshiftOutput00'+num) c = [0.5]*3 # Center L = [1.0,1.0,1.0] # Viewpoint W = na.sqrt(3) # Width N = 768 # Pixels (512^2) up = [0.,0.,1.] # Get density min, max # These might take a long time, so I'd suggest handcoding mi, ma so # that you don't have to find the maxima and minima each time you # test. Note that mi, ma, should be a log value since we are # rendering the log of density. mi, ma = pf.h.all_data().quantities['Extrema']('Density')[0] mi, ma = na.log10(mi), na.log10(ma) print mi, ma #mi, ma = 31.0, 26.0 # Construct transfer function, pad the TF space by a bit so that # gaussians sampling the data range don't hit the edge. tf = ColorTransferFunction((mi10, ma+10), nbins=1024) # Sample transfer function with 20 gaussians. Use col_bounds keyword # to restrict color mapping to true data range. tf.add_layers(20, w=0.001, col_bounds=(mi,ma),colormap='jet') # Create the camera object cam = pf.h.camera(c, L, W, (N,N), transfer_function=tf, north_vector=up, no_ghost=True) cam.snapshot("volume_rendered%s.png" % num, clip_ratio=8.0)

Is there an option for 'camera" or "snapshot" which allows to add the borders for this box ?
Any help would be really appreciated.
Hi Henry,
Welcome to yt!
Thanks for bringing this up. I've had some code lying around uncommitted for quite some time that allows for this type of annotation of the grids/domains, and this has motivated me to revive it and push it along. I currently have a pull request open to incorporate these changes, and they will likely be accepted soon ( https://bitbucket.org/yt_analysis/yt/pullrequest/406/drawdomainboundarya... ).
Once it is accepted, you should be able to update (to the development brach), and do: im = cam.snapshot("volume_rendered%s.png" % num) cam.draw_domain(im) write_bitmap(im, 'volume_rendered%s_with_domain.png" % num)
Once the functionality is added, I will send an email to the users list announcing it as a feature and asking for folks to test it out.
Best, Sam
On Tue, Jan 22, 2013 at 6:29 AM, henry wasker henry.wasker@gmail.comwrote:
Hello,
I am new to yt and I am interesting in plotting a volume rendering with output file from enzo cosmology simulation.
For the time being, I get to plot a box ; here's the result :
I would like now to plot borders of this box too like on this image :
Here's the yt script I use :
from yt.mods import * from yt.utilities.amr_kdtree.api import AMRKDTree from time import time import matplotlib.colorbar as cb
# Load up your dataset num='70' pf = load('RD00'+num+'/RedshiftOutput00'+num) c = [0.5]*3 # Center L = [1.0,1.0,1.0] # Viewpoint W = na.sqrt(3) # Width N = 768 # Pixels (512^2) up = [0.,0.,1.] # Get density min, max # These might take a long time, so I'd suggest handcoding mi, ma so # that you don't have to find the maxima and minima each time you # test. Note that mi, ma, should be a log value since we are # rendering the log of density. mi, ma = pf.h.all_data().quantities['Extrema']('Density')[0] mi, ma = na.log10(mi), na.log10(ma) print mi, ma #mi, ma = 31.0, 26.0 # Construct transfer function, pad the TF space by a bit so that # gaussians sampling the data range don't hit the edge. tf = ColorTransferFunction((mi10, ma+10), nbins=1024) # Sample transfer function with 20 gaussians. Use col_bounds keyword # to restrict color mapping to true data range. tf.add_layers(20, w=0.001, col_bounds=(mi,ma),colormap='jet') # Create the camera object cam = pf.h.camera(c, L, W, (N,N), transfer_function=tf, north_vector=up, no_ghost=True) cam.snapshot("volume_rendered%s.png" % num, clip_ratio=8.0)
Is there an option for 'camera" or "snapshot" which allows to add the borders for this box ?
Any help would be really appreciated.
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participants (2)

henry wasker

Sam Skillman