The interactive prompt offers a number of excellent opportunities for exploration of data. While there are challenges for repeatability, and some operations will be more challenging to operate in parallel, interactive prompts can be exceptionally useful for debugging, exploring, and tweaking plots.
You can start up an empty shell, with a handful of useful yt utilities (such as tab-completion and pre-imported modules) by executing:
The other option, which is shorthand for “iyt plus dataset loading” is to use
the command-line tool (see Command-Line Usage) with the
and to specify a dataset. For instance:
yt load cosmoSim_coolhdf5_chk_0026
yt load DD0030/DD0030
This will spawn
iyt, but the dataset given on the command line will
already be in the namespace as
ds. With interactive mode, you can use the
pylab module to interactively plot.
yt command-line tool allows you to access some of yt’s basic
functionality without opening a python interpreter. The tools is a collection of
subcommands. These can quickly making plots of slices and projections through a
dataset, updating yt’s codebase, print basic statistics about a dataset, launch
an IPython notebook session, and more. To get a quick list of what is
available, just type:
This will print the list of available subcommands,
help Print help message bootstrap_dev Bootstrap a yt development environment bugreport Report a bug in yt hub_register Register a user on the Hub: http://hub.yt-project.org/ hub_submit Submit a mercurial repository to the yt Hub (http://hub.yt-project.org/), creating a BitBucket repo in the process if necessary. instinfo Get some information about the yt installation version Get some information about the yt installation (this is an alias for instinfo). load Load a single dataset into an IPython instance mapserver Serve a plot in a GMaps-style interface pastebin Post a script to an anonymous pastebin pastebin_grab Print an online pastebin to STDOUT for local use. upload_notebook Upload an IPython notebook to hub.yt-project.org. plot Create a set of images rpdb Connect to a currently running (on localhost) rpd session. Commands run with --rpdb will trigger an rpdb session with any uncaught exceptions. notebook Run the IPython Notebook stats Print stats and max/min value of a given field (if requested), for one or more datasets (default field is Density) update Update the yt installation to the most recent version delete_image Delete image from imgur.com. upload_image Upload an image to imgur.com. Must be PNG.
To execute any such function, simply run:
Finally, to identify the options associated with any of these subcommand, run:
yt <subcommand> -h
First, we’ll discuss plotting from the command line, then we will give a brief
summary of the functionality provided by each command line subcommand. This
example uses the
DD0010/moving7_0010 dataset distributed in the yt
First let’s see what our options are for plotting:
$ yt plot --help
There are many! We can choose whether we want a slice (default) or a
-p), the field, the colormap, the center of the image, the
width and unit of width of the image, the limits, the weighting field for
projections, and on and on. By default the plotting command will execute the
same thing along all three axes, so keep that in mind if it takes three times
as long as you’d like! The center of a slice defaults to the center of
the domain, so let’s just give that a shot and see what it looks like:
$ yt plot DD0010/moving7_0010
Well, that looks pretty bad! What has happened here is that the center of the domain only has some minor shifts in density, so the plot is essentially incomprehensible. Let’s try it again, but instead of slicing, let’s project. This is a line integral through the domain, and for the density field this becomes a column density.:
$ yt plot -p DD0010/moving7_0010
Now that looks much better! Note that all three axes’ projections appear
nearly indistinguishable, because of how the two spheres are located in the
domain. We could center our domain on one of the spheres and take a slice, as
well. Now let’s see what the domain looks like with grids overlaid, using the
$ yt plot --show-grids -p DD0010/moving7_0010
We can now see all the grids in the field of view.
Help lists all of the various command-line options in yt.
Encountering a bug in your own code can be a big hassle, but it can be exponentially worse to find it in someone else’s. That’s why we tried to make it as easy as possible for users to report bugs they find in yt. After you go through the necessary channels to make sure you’re not just making a mistake (see What to do if you run into problems), you can submit bug reports using this nice utility.
This gives information about where your yt installation is, what version and changeset you’re using and more.
This will start the iyt interactive environment with your specified dataset already loaded. See Interactive Prompt for more details.
Ever wanted to interact with your data using the google maps interface? Now you can by using the yt mapserver. See Mapserver - A Google-Maps-like Interface to your Data for more details.
The pastebin is an online location where
you can anonymously post code snippets and error messages to share with
other users in a quick, informal way. It is often useful for debugging
code or co-developing. By running the
pastebin subcommand with a
text file, you send the contents of that file to an anonymous pastebin;
yt pastebin my_script.py
By running the
pastebin_grab subcommand with a pastebin number
(e.g. 1768), it will grab the contents of that pastebin
(e.g. the website http://paste.yt-project.org/show/1768 ) and send it to
STDOUT for local use. See Pastebin for more information.
yt pastebin_grab 1768
This command generates one or many simple plots for a single dataset.
By specifying the axis, center, width, etc. (run
yt help plot for
details), you can create slices and projections easily at the
This command will accept the filename of a
.ipynb file (generated from an
IPython notebook session) and upload it to the yt hub
<http://hub.yt-project.org/> where others will be able to view it, and
download it. This is an easy method for recording a sequence of commands,
their output, narrative information, and then sharing that with others. These
notebooks will be viewable online, and the appropriate URLs will be returned on
the command line.
Connect to a currently running (on localhost) rpd session.
Launches an IPython notebook server and prints out instructions on how to open an ssh tunnel to connect to the notebook server with a web browser. This is most useful when you want to run an IPython notebook using CPUs on a remote host.
This subcommand provides you with some basic statistics on a given dataset.
It provides you with the number of grids and cells in each level, the time
of the dataset, the resolution, and the maximum density in a variety of units.
It is tantamount to performing the
print_stats() inside of yt.
This subcommand updates the yt installation to the most recent version for
your repository (e.g. stable, 2.0, development, etc.). Adding the
flag will update the dependencies as well.
Images are often worth a thousand words, so when you’re trying to
share a piece of code that generates an image, or you’re trying to
debug image-generation scripts, it can be useful to send your
co-authors a link to the image. This subcommand makes such sharing
a breeze. By specifying the image to share,
uploads it anonymously to the website imgur.com and
provides you with a link to share with your collaborators. Note that the
image must be in the PNG format in order to use this function.