[yt-users] ANN: yt-3.2.2 release

Nathan Goldbaum nathan12343 at gmail.com
Fri Nov 13 14:34:08 PST 2015


We are proud to announce the release of yt 3.2.2!

yt (http://yt-project.org) is an open-source, community-developed toolkit
for
analysis and visualization of volumetric data of all types, with a
particular
emphasis on astrophysical and nuclear engineering simulations.

Version 3.2.2 is a regularly scheduled bugfix release including fixes for a
number of issues reported since the release of yt 3.2.1. This release also
supports matplotlib 1.5.x and NumPy 1.10.x.

The changes in this version are summarized below and include a number of
bugfixes, performance improvements, and documentation improvements.
We urge all users of version 3.2 and 3.2.1 to upgrade to yt 3.2.2
immediately.

Summary of changes
----------------------------

* Several fixes for units in the Tipsy frontend, including fixes for
incorrect units
  when data were loaded without a parameter file available, support for
Tipsy
  datasets converted from Gadget outputs, and support for tipsy auxiliary
files
  containing data for more particles than the default chunking size. See
  PR 1668 <https://bitbucket.org/yt_analysis/yt/pull-requests/1668>, PR 1735
<https://bitbucket.org/yt_analysis/yt/pull-requests/1735>, and PR 1787
<https://bitbucket.org/yt_analysis/yt/pull-requests/1787>.

* Added better documentation for answer testing. See PR 1742
<https://bitbucket.org/yt_analysis/yt/pull-requests/1742> and PR 1807
<https://bitbucket.org/yt_analysis/yt/pull-requests/1807>.

* Fixed a typo in the particle filter documentation. See PR 1744
<https://bitbucket.org/yt_analysis/yt/pull-requests/1744>.

* Avoid a test failure when running the unit tests in yt's default
configuration.
  See PR 1754 <https://bitbucket.org/yt_analysis/yt/pull-requests/1754>.

* Ensure grid patch objects have cell width metadata when needed.
  See PR 1756 <https://bitbucket.org/yt_analysis/yt/pull-requests/1756>.

* Ensure matplotlib axes and figure objects are always valid when modifying
a yt
  plot. See PR 1757 <http://17571668>.

* Fix a bug in the ARTIO frontend's implementation of
  "ds.index.get_smallest_dx()". See PR 1759
<https://bitbucket.org/yt_analysis/yt/pull-requests/1759>.

* Remove some dead code from the Chombo frontend. See PR 1761
<https://bitbucket.org/yt_analysis/yt/pull-requests/1761>.

* Adapt to API change in matplotlib 1.5.x. See PR 1752
<https://bitbucket.org/yt_analysis/yt/pull-requests/1752>.

* Use the effective redshift for calculating absorption spectra in the
LightRay
  analysis module. See PR 1758
<https://bitbucket.org/yt_analysis/yt/pull-requests/1758> and PR 1783
<https://bitbucket.org/yt_analysis/yt/pull-requests/1783>.

* Add support for more types of NMSU ART datasets. See PR 1764
<https://bitbucket.org/yt_analysis/yt/pull-requests/1764>.

* Fix test failures under Numpy 1.10 or newer. See PR 1697
<https://bitbucket.org/yt_analysis/yt/pull-requests/1697>, PR 1767
<https://bitbucket.org/yt_analysis/yt/pull-requests/1767> and
  P <https://bitbucket.org/yt_analysis/yt/pull-requests/1779>R 1779
<https://bitbucket.org/yt_analysis/yt/pull-requests/1779>.

* Avoid build failure in the check for openmp support. See PR 1768
<https://bitbucket.org/yt_analysis/yt/pull-requests/1768>.

* Ensure field dependencies are resulved when creating a smoothed particle
field.
  See PR 1772 <https://bitbucket.org/yt_analysis/yt/pull-requests/1758>.

* Fix a bug in the chombo frontend that prevented loading data with more
than
  10 particle fields. See PR 1780
<https://bitbucket.org/yt_analysis/yt/pull-requests/1758>.

* Minor performance optimization for the photon simulation analysis module.
  See PR 1766 <https://bitbucket.org/yt_analysis/yt/pull-requests/1766>.

* Fix loading Athena data under python3 when parameters are provided at
load time.
  See PR 1828 <https://bitbucket.org/yt_analysis/yt/pull-requests/1828>.

* Ensure Athena datasets have a `velocity_unit` attribute. See PR 1831
<https://bitbucket.org/yt_analysis/yt/pull-requests/1831>.

* Fix for loading GDF data in python3. See PR 1831
<https://bitbucket.org/yt_analysis/yt/pull-requests/1831>.

* Speedup for unit operations. See PR 1782
<https://bitbucket.org/yt_analysis/yt/pull-requests/1782>.

* Fix issues with SIMPUT files in the photon simulator analysis module.
  See PR 1790 <https://bitbucket.org/yt_analysis/yt/pull-requests/1790>.

* Ensure the x and y limits of PhasePlot instances are controllable via
  set_xlim and set_ylim. See PR 1821
<https://bitbucket.org/yt_analysis/yt/pull-requests/1821>.

* Fixing various issues in the Sunyaev-Zeldovich analysis module. See PR
1835 <https://bitbucket.org/yt_analysis/yt/pull-requests/1835>.

* Stop referring to a requirements file in the installation docs. See PR
1839 <https://bitbucket.org/yt_analysis/yt/pull-requests/1839>.

* Generate a nicer error message to work around bug in the nose testing
framework.
  See PR 1840 <https://bitbucket.org/yt_analysis/yt/pull-requests/1840>.

* Fix loading Gadget data in python3. See PR 1841
<https://bitbucket.org/yt_analysis/yt/pull-requests/1841>.

* Fix loading Tipsy data in python3. See PR 1842
<https://bitbucket.org/yt_analysis/yt/pull-requests/1842>.

* Pass bytes to FNV hashing algorithm, don't rely on python hashes. See PR
1845 <https://bitbucket.org/yt_analysis/yt/pull-requests/1845>.

* Fix bug in ray "dts" and "t" fields. See PR 1846
<https://bitbucket.org/yt_analysis/yt/pull-requests/1846/bugfix-fixing-bug-in-ray-dts-and-t-fields/diff>
.

* Make array_like_field return data with the same units as get_data. See PR
1847
<https://bitbucket.org/yt_analysis/yt/pull-requests/1847/bugfix-make-array_like_field-return-same/diff>
.

* Make default reult_id for parallel_objects more useful. See PR 1851
<https://bitbucket.org/yt_analysis/yt/pull-requests/1851/bugfix-make-default-result_id-for/diff>
.

* Update author name and e-mail metadata in setup.py. See PR 1854
<https://bitbucket.org/yt_analysis/yt/pull-requests/1854>.

Coming Soon!
-------------------

The next major release of yt will be version 3.3, which is slated to
include an
overhaul of the volume rendering system and support for analyzing and
visualizing unstructured mesh data. Some of this functionality is already
available
on the development branch of yt. We welcome feedback from early testers.

Standard Installation Methods
-----------------------------

As with previous releases, you can install yt from source using one of the
following methods.

1) From the install script (http://yt-project.org/#getyt ):

If you previously installed yt from the install script, you can update your
installation in-place using the following command:

# Update

$ yt update

If you are on the “stable” branch, updating will bring you from yt 3.2.1 or
3.2
to 3.2.2, whereas if you are on the development “yt” branch, only the
changes since your last update should be incorporated.

To install from scratch, do the following:

# Installation

$ wget http://bitbucket.org/yt_analysis/yt/raw/stable/doc/install_script.sh
$ bash install_script.sh

2) From pip (source or binary wheel, see below for more details):

# Installation

$ pip install yt

# Update

$ pip install -U yt

3) From the Anaconda Python Distribution
(https://store.continuum.io/cshop/anaconda/):

# Installation

$ conda install yt

# Update

$ conda update yt

Note that it might take up to a week for the conda package built by
Continuum
Analytics to be updated for yt 3.2.2.

Installing Binary Packages via pip

If you do not have compilers available, it is also possible to install
binary
packages (“wheels”) using pip on Windows and Mac OS X (64-bit only for
both). This has the advantage of not needing to install yt from source
using a
proper compiler setup, which has caused occasional problems on both of these
platforms and prevented us from installing yt easily on other Python
distributions.

Note that it may take several days for binary wheels for yt 3.2.2 to be
uploaded.

We have so far been able to install and run the binary distribution via pip
on
the following platforms and Python stacks:

Note that it might take a day or two for the pip wheels to be updated.

Windows x86_64:

Enthought Canopy Python (https://www.enthought.com/products/canopy/)
WinPython (http://winpython.sourceforge.net/)

Mac OS X x86_64:

Enthought Canopy Python (https://www.enthought.com/products/canopy/)
Homebrew Python (http://brew.sh/)
Python.org Python
Mac OS X’s system Python
MacPorts Python (https://www.macports.org/)

This is somewhat experimental, so other distributions may work (or not),
please
submit bug reports or successes to the mailing list or to the Bitbucket
issues
page (http://bitbucket.org/yt_analysis/yt/issues).

Both Python 2.7 and Python 3.4 are supported. The dependencies for
installing
yt via this method are the same as from source:

NumPy
h5py
HDF5
SymPy
Matplotlib
IPython (not required, but strongly recommended)

To install a new version of yt on one of these platforms, simply do

$ pip install yt

and you should get the binary distribution automatically. Also, if your
python
installation is system-wide (e.g., the Mac system Python) you might need to
run
pip with administrator privileges.

For more information, including more installation instructions, links to
community resources, and information on contributing to yt’s development,
please
see the yt homepage at http://yt-project.org and the documentation for yt-
3.2.2 at
http://yt-project.org/doc.

yt is the product of a large community of developers and users and we are
extraordinarily grateful for and proud of their contributions. Please
forward
this announcement on to any interested parties.

As always, if you have any questions, concerns, or run into any trouble
updating
please don't hesitate to send a message to the mailing list or stop by our
IRC
channel.

All the best,

Nathan Goldbaum,
on behalf of the yt development team
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