yt is 2024极速赛车168开奖记录查询 168极速赛车开奖官网视频 168官方开奖官网直播 1分钟极速彩票赛车官网网址 75秒赛车最新开奖号码 极速体彩赛车168开奖官网直播 168官方开奖记录一分钟 在线计划 大数据分析软件.
yt supports structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles. Focused on driving physically-meaningful inquiry, yt has been applied in domains such as astrophysics, seismology, nuclear engineering, molecular dynamics, and oceanography. Composed of a friendly community of users and developers, we want to make it easy to use and develop — we'd love it if you got involved!
import yt
ds = yt.load_sample("IsolatedGalaxy")
ds.r[0.45:0.55,:,:].sum("cell_mass").in_units("Mjup")
9.98537989593e+12 Mjup
import yt
ds = yt.load_sample("IsolatedGalaxy")
def thermal_energy_dens(field, data):
return (3/2)*data['gas', 'number_density'] * data['gas', 'kT']
ds.add_field(("gas", "thermal_energy_density"), units="erg/cm**3",
function=thermal_energy_dens, sampling_type="cell")
ad = ds.all_data()
ad.mean("thermal_energy_density", "z", weight="density").plot()
import yt
ds = yt.load("GasSloshing/sloshing_nomag2_hdf5_plt_cnt_0150",
unit_system="imperial")
slc = yt.SlicePlot(ds, 'z', "temperature", width=(600,"kpc"))
import yt
ds = yt.load_sample("IsolatedGalaxy")
sp = ds.sphere([0.5, 0.5, 0.5], (8, "kpc"))
sp.save_as_dataset("my_sphere.h5", ["density", "particle_mass"])
ds2 = yt.load("my_sphere.h5")
print (ds2.data["particle_mass"].to("Msun"))
[ 213975.58440381
213975.58440381
213975.58440381
...,
102714.05991054
102857.70970906
102981.94762343] Msun
import yt
ds = yt.load_sample("snapshot_033")
ds.r[(12.4, 'Mpc'),:,:].plot(("gas", "density"))
import yt
ds = yt.load_sample("D9p_500")
p = yt.ProjectionPlot(ds, "y", "density")
import yt
ds = yt.load_sample("IsolatedGalaxy")
yt.interactive_render(ds)
import yt
ds = yt.load_sample("snipshot_399_z000p000")
ad = ds.all_data()
yt.ProfilePlot(ad, ("PartType0", "density"),
("PartType0", "temperature"),
weight_field = ("PartType0", "particle_mass")).save()
import yt
ds = yt.load_sample("HiresIsolatedGalaxy")
ad = ds.all_data()
yt.PhasePlot(ad, "density", "temperature", "cell_mass",
weight_field=None).save()
import yt
ds = yt.load_sample("Enzo_64/DD0043/data0043")
ds.r[:].min(), ds.r[:].max()
(3.81289338015e-32 g/cm**3,
6.27892369905e-27 g/cm**3)
import yt
ds = yt.load_sample("output_00080")
ds.r[(10.0, "Mpc"):(20.0, "Mpc"),
(30.0, "Mpc"):(40.0, "Mpc"),
(50.0, "Mpc"):(60.0, "Mpc")].mean("temperature", weight="density")
296317.62046 K
import yt
ds = yt.load_sample("IsolatedGalaxy")
loc1 = ds.r[:].argmax("temperature")
loc2 = ds.r[:].argmax("density")
ray = ds.ray(loc1, loc2)
ray["velocity_magnitude"].in_units("cm/s")
YTArray([ 22921344.10593038,
24626806.46165072,
24759784.32406003,
26583519.63858156,
27331481.53657745,
27728742.61474814,
28734604.40420894,
30188600.75890669,
30989266.0493723 ,
31197303.98155414,
...
10846216.93678336,
12222078.64819527]) cm/s
Learn: getting started.
To get started using yt 最新免费计划记录,查询结果 to explore data, we provide resources including documentation, workshop material, and even a fully-executable quick start guide demonstrating many of yt's capabilities.
But if you just want to dive in and start using yt, we have a long list of recipes demonstrating how to do various tasks in yt. We even have sample datasets from all of our supported codes on which you can test these recipes. While yt should just work with your data, here are some instructions on loading in datasets from our supported codes and formats.
Community: yt's best 168开奖现场官方网站下载.
yt is a friendly community. We like hearing about fun things you have done with the code, and we're happy to help you out if you have a question or some trouble. You can join us in IRC, on the mailing lists, and if you'd like, you can check out how to develop, too.
If you've got some code to share, or scripts that you'd like to share, start up a repo on GitHub or Bitbucket or share them on our pastebin. If you have any trouble, drop by the mailing list and we'll be happy to help out.
Participatory development.
幸运飞飞开奖官方现场168飞艇记录结果官方网站-168飞艇官方数据 easiest way is to Fork us on GitHub, check out the developer guide, and stop by the development mailing list. yt is released under the modified BSD License.
There are lots of fun projects to work on, along with some open issues, and we'd particularly like if you'd help out by adding support for a a new data format or if you'd like to help out by shoring up support for a semi-supported output format.
Get yt: 极速赛车官方开奖查询结果记录2024.
yt is built on a stack of completely free and libre open source software, with no proprietary dependencies and is distributed to both the conda and PyPi package repositories for easy installation. For a full description of how to install, including selecting optional dependencies and installing from source, see the main documentation.
If you use yt in a publication, we request that you please consider citing our method paper (BibTeX).
Get yt: using 极速168赛车视频官网直播.
If you use the anaconda python distribution or use conda to manage python packages, you can install the latest stable version of yt with the following command:
Or a nightly development build:
Get yt: 168一分钟官方开奖历史记录 pip.
You can also can install the latest stable version of yt via pip with:
See here for more details on 168极速在线赛车号码查询直播官方网站.