Hi, Everybody!
Does anyone out there have a technique for getting the variance out of
a profile object? A profile object is good at getting <X> vs. B, I'd
then like to get < (X - <X>)^2 > vs B. Matt and I had spittballed the
possibility some time ago, but I was wondering if anyone out there had
successfully done it.
Thanks,
d.
--
Sent from my computer.
Hi guys,
I am very new to Ytini's mailing list, mailing lists as well as Houdini.
So please bear with me while I pick up the etiquette around this medium.
With that out of the way here's my first question:
After having succeeded installing Ytini for Houdini on a Mac OS X 10.14 I
would now like to achieve the same with my Houdini install on a Windows 10
OS.
I have tried to somewhat reproduce all steps described here
http://www.ytini.com/getstarted.html#collapseTwoOut (Houdini 17.5 Tested on
Mac OS X) on my Windows machine but wasn't surprised to learn that of
course Houdini could not find the ytini module when I tried to import it in
the python shell.
Is there somebody, that could point me . in the right direction of how to
install Ytini for Houdini on a Windows 10 OS environment?
Not afraid of reading so even hints a re more than welcome.
Many Thanks in advance
Ur4n
Folks,
I ran both HOP and Rockstar halo finders on the same ART simulations,
and the mass functions match very well (attached hmf_m.pdf file).
However, when I compare virial radii (attached hmf_r.pdf file), they
don't match. Even if I try rescaling the Rockstar virial radius by 1.5,
the match is much worse than for mass functions.
How are the 'virial_radius' fields defined for both halo finders?
This is a z=7 simulations, so all mass definitions are the same, Mvir =
M200m = M200c.
I also attach the script to plot virial radii if you want to check it,
although it is trivial.
Many thanks (as usual),
Nick
Hello All,
I am currently attempting to compare a catalog with Mvir and Rvir units of
Mpc/h and Kpc/h comoving to a catalog with Mpc and Kpc proper. I am
currently using yt version 3.5.1, which I just checked for updates.
When doing this conversion of units within yt, there appears to be a
problem where an amount of h*h is not handeled properly. I have included a
screenshot of a jupyter session that outlines the problem as well as a .py
and jupyter script so it can be tested.
The problem arises when I try to calculate delta_vir, which is the density
of a galaxy/ critical density. The correct value for both catalogs I am
comparing is around 170. When I use yt to calculate the critical density at
z = 2, it get the correct value, which I convert to Mpc*h*h//kpc/kpc/kpc to
match with my /h catalog. Then, when I divide the densities, even thought
their units are identical, their division is different than if just the
float values are divided, by an exact factor of h*h. I wonder if there is
something wrong with how I am initializing my values with the ytquantity,
or if there is something wrong going on in the code.
[image: Screen Shot 2019-07-31 at 2.36.01 PM.png]
I recently installed Anaconda3 with Python 3.7, as well as the latest yt 3.4.1. But when I ran my code, calculating the center of mass and angular momentum, an error saying:
count_values() got an unexpected keyword argument 'particle_type'
came up.
Is there anything I can do to fix it except installing an Anaconda with Python 3.6?
Dear yt developers,
I found that increasing number of CPU cores in a single node that have 16 cores and 16 additional hyper-threadings can dramatically deteriorate speed-up. figure [3] shows this result.
You may reproduce figure [3] by the following steps:
Running shell script [1] can automatically invoke yt script [2] and record elapsed time on files, called core_* [4].
[1] shell script:
http://paste.yt-project.org/show/150/
[2] yt script:
http://paste.yt-project.org/show/151/
[3] # of cores vs. elapsed time
http://i.imgur.com/mFk6lKu.png
[4] all scripts, data and log files:
http://use.yt/upload/d8efa692
Thanks for your help.
Rocky Tseng
Hi all,
With the merger today of https://github.com/yt-project/yt/pull/2163 ,
Python 2 support has been removed from the yt-4 branch. Those of you
using the master branch or any release will not be affected, but if
you're on yt-4, keep this in mind.
Best,
Matt
Hi yt,
When making projection plots of total gas density and cold gas density, averaged over the projection length (i.e. with a uniform weighting), and using cut_region() to filter out hot gas to make the cold gas plots, it appears that some areas in the cold gas plot have a higher density than the corresponding areas in the total gas plot, which shouldn't happen. If you look at the top-middle of the two plots (link below) and compare the densities, the cold gas appears to have a higher density there. The code is below:
(link to plots: https://drive.google.com/drive/folders/1UJ6fmKNFQzGr8cfjov5-GwOzfS8nt2e8?us…)
import yt
ds = yt.load("/tigress/cen/CZ15/redshift0100")
z = 0.62
# the box size is 120/0.7/(1+z) Mpc, where z is redshift
boxSize = 120e3/0.7/(1+z)
# virial radius in code units, r_v is virial radius in kpc
codeWidth = r_v / boxSize
center = [xCoord, yCoord, zCoord]
left_edge = [xCoord-2.1*codeWidth, yCoord-2.1*codeWidth, zCoord-2.1*codeWidth]
right_edge = [xCoord+2.1*codeWidth, yCoord+2.1*codeWidth, zCoord+2.1*codeWidth]
# want a box with full width about 4 times the virial radius
reg = ds.region(center, left_edge,right_edge)
# total gas plot
prj = yt.ProjectionPlot(ds, "x", "density", center=center, width=(4*r_v, 'kpc'),
data_source=reg, method='integrate', weight_field='ones')
u = 100 / 0.048
l = 0.07 / 0.048
prj.set_zlim('density', l,u)
prj.set_unit('density','mbd')
prj.set_cmap(field='density', cmap='CMRmap')
prj.show()
# cold gas plot
cold_reg = reg.cut_region(["obj['temperature'] < 1e5"])
prj = yt.ProjectionPlot(ds, "x", "density", center=center, width=(4*r_v, 'kpc'),
data_source=cold_reg, method='integrate', weight_field='ones')
prj.set_zlim('density', l,u)
prj.set_unit('density','mbd')
prj.set_cmap(field='density', cmap='CMRmap')
prj.show()
Thanks,
Andrew
Dear yt:
I am trying to plot streamlines using SlicePlot(x axis) and
annotate_streamlines (script below). The resulting image (google drive link
below) gives the orientation of streamlines along y axis. I would like to
have the streamlines orient along z-axis. I have tried switching the
variables on "SlicePlot" and "annotate_streamlines" but the streamlines
stays the same.
Can you give me any suggestions?
Thank you in advance
-----------------------------------
Image link
https://drive.google.com/open?id=0B4g8shg4DL7oak5PLWVVdG5UMHc
-----------------------------------
script
import yt
import numpy as np
import matplotlib.pylab as pl
import matplotlib
from yt.visualization.api import Streamlines
from yt.units import km
from mpl_toolkits.mplot3d import Axes3D
ms = 24000000
vector_max=ms-(ms/3)
ms1=ms-vector_max
dims = (200,200,200)
x =
np.genfromtxt("/work/jbi157/MODEL3/UPDATE_B/yo_n_t005.mtx",skip_header=2,usecols=1,
dtype="f8")
x = x.reshape((8000000, 3), order="F")
field1 = x[:,2].reshape(dims, order="F")
field2 = x[:,1].reshape(dims, order="F")
field3 = x[:,0].reshape(dims, order="F")
data = dict(field_x = field1,
field_y = field2,
field_z = field3)
bbox = np.array([[-100, 99], [-100, 99], [-100, 99]])
pf = yt.load_uniform_grid(data, dims, km, bbox=bbox, nprocs=1)
slc = yt.SlicePlot(pf, 0, ["field_z"], width=(200,'km'))
slc.set_cmap('field_z','B-W LINEAR_r')
#slc.set_log('field_z', True, linthresh=0.001)
slc.annotate_streamlines('field_z',
'field_y',factor=16,density=4,plot_args={'color':'blue'})
#slc.annotate_streamlines('field_y', 'field_z',factor=16,density=4)
slc.annotate_line((0.36, 0), (0.36, 1),
coord_system='axis',plot_args={'color':'white'})
slc.annotate_line((0.64, 0), (0.64, 1),
coord_system='axis',plot_args={'color':'white'})
# larger the value of factor lesser the quiver
#slc.annotate_quiver('field_y', 'field_z', factor=20, normalize=True)
#slc.annotate_line_integral_convolution('field_y', 'field_z',
lim=(0.30,0.70),cmap="YlGnBu",alpha=1,const_alpha=True)
slc.annotate_sphere([0.5, 0.5, 0.5], radius=(9,
'km'),circle_args={'color':'black'})
#slc.annotate_text((50,50),'t=0',coord_system='plot',text_args={'color':'black'})
slc.annotate_title("t=005, psi=30")
slc.hide_colorbar()
slc.save('plane_x_t_0005.png')
#slc.save('plane_x_t_0000.png', mpl_kwargs={'facecolor':'gray'})
On Thu, Jan 10, 2019 at 11:00 AM <yt-users-request(a)python.org> wrote:
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> Date: Thu, 10 Jan 2019 09:58:14 -0600
> From: Matthew Turk <matthewturk(a)gmail.com>
> Subject: [yt-users] ANN: yt dev workshop, March 4-6
> To: yt-dev(a)python.org, Discussion of the yt analysis package
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> Cc: "Campbell, Mary Terese" <mtc(a)illinois.edu>, Samantha Walkow
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*SK2*
*"**Claiming that something can move faster than light is a good
conversation-stopper in physics. People edge away from you in cocktail
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Hi All,
I could not find a solution for my issue in the archived threads so I am posting it here.
I use FLASH to run my MHD simulation and then use the output hdf5 plotfile to create and save a yt PhasePlot of number density and adiabatic index 'gamma' (user-defined fields) color-coded by the cell mass:
plot=yt.PhasePlot(my_sphere,"numdens","gamma",["cell_mass"])
plot.set_ylabel('$\gamma_{\mathrm{net}}$')
plot.set_xlabel('$n\,\,(\mathrm{cm^{-3}})$')
plot.set_ylim(1.3,1.7)
plot.set_log("gamma",False)
plot.set_font_size(20)
plot.set_minorticks('all','on')
plot.set_unit("cell_mass",'Msun')
plot.save("phaseplot_numgamma.pdf")
The axes labels are smaller than what I would like them to be. If I increase the font-size to a higher value (say, plot.set_font_size(30)), the axes labels are of the appropriate font size, but the x-axis tick labels also increase in size and overlap with the figure boundary. This might be because my tick labels have exponents (10^(11), 10^(12), etc.). Is there a way to only change the axes label size and not the tick label size while using yt?
Thanks in Advance,
Piyush Sharda