Seems interesting.
---------- Forwarded message ----------
From: Thomas Robitaille <thomas.robitaille(a)gmail.com>
Date: Wed, May 25, 2016 at 11:07 AM
Subject: [glue-viz-dev] ANN: glue-vispy-viewers v0.4 released!
To: glue-viz(a)googlegroups.com, glue-viz-dev(a)googlegroups.com
Hi everyone,
With the glue v0.8 release out of the door, we are happy to also let
you know that the plugin with the experimental 3D viewers for glue –
glue-vispy-viewers – also has a new release (v0.4).
Since the last time I advertised these plugins, there have been a
number of improvements, including:
The ability to select data in the 3D viewers
The ability to save and restore Glue sessions with 3D viewers
Optimizations of the panels on the left hand side of the application
for small screens
The ability to save static views of the 3D viewers to files
A toolbar icon to continuously rotate the view
A toolbar icon to record an animation to a GIF file (this requires the
imageio package to be installed)
A number of bug fixes that affected usability
The ability to switch between an orthogonal and perspective projection
This plugin can now be installed using Anaconda:
conda install -c conda-forge glue-vispy-viewers
or if you use pip:
pip install glue-vispy-viewers --upgrade --no-deps
Please note that the package should still be considered experimental.
If you run into any issues or have any requests, we would love to hear
from you - you can either send a message to the
glue-viz(a)googlegroups.com mailing list, or open an issue on GitHub in
the following repository:
https://github.com/glue-viz/glue-vispy-viewers/issues
Thanks!
Tom Robitaille and Penny Qian
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New issue 1223: annotate_mesh_lines and annotate_cell_edges should be combined.
https://bitbucket.org/yt_analysis/yt/issues/1223/annotate_mesh_lines-and
Andrew Myers:
Currently, these are two different plot callbacks that do similar things, but only work for certain dataset types. They should be combined into a single callback that does thing right thing under the hood.
Responsible: atmyers
New issue 1222: Many plot callbacks do not work with non-cartesian datasets
https://bitbucket.org/yt_analysis/yt/issues/1222/many-plot-callbacks-do-n...
John ZuHone:
A number of callbacks do not work properly with non-cartesian datasets:
* Anything that does vectors, i.e. `QuiverCallback`, `VelocityCallback`, `MagFieldCallback`, etc.
* Drawing grid or cell lines, i.e. `GridBoundaryCallback`, `CellEdgesCallback`
* Contouring
This will take a substantial, focused effort on the part of one or more people to get working properly.
I'm marking this 3.3 but I'm not sure if that's what we want or not. Open to having it pushed back.
New issue 1221: Improving docs for basic manipulation of halo catalogue data
https://bitbucket.org/yt_analysis/yt/issues/1221/improving-docs-for-basic...
Anonymous:
As a new user of yt, I've found it exceedingly hard to find just basic examples of manipulating the halo catalogues. A lot of the examples, whilst great, are designed for more advanced users who are interested in doing renderings, halo profiles etc. which are usually stage 3 or 4 for the entry level user. The only place I can find information about accessing the actual halo catalogue content (e.g. halo masses, positions etc. from Rockstar) is here:
http://yt-project.org/docs/dev/analyzing/analysis_modules/halo_transition...
This simple example is actually confusing in and of itself as it isn't clear if this is the masses of the particles in the halo or just the halo masses themselves. I thought there would be just a simple way to access the halo catalogue information (e.g. hc['Rvir']) without doing anything more sophisticated like masking/filtering. It would be great if some new docs could be added for just really fundamental manipulation of the data loaded from the halo finder output.
Responsible: yt_analysis
Hi all,
I'm trying to create two derived fields (one for stellar density, and one
for dark matter density) based on
<https://bitbucket.org/yt_analysis/yt/src/cee2a160c5351c376afea65bea346279...>
these
<https://bitbucket.org/yt_analysis/yt/src/cee2a160c5351c376afea65bea346279...>
from yt2. I'm running yt 3.2.3, and the star_density and dm_density fields
seem to have been removed. So far, the yt2 code has transferred fine, with
minimal changes:
- amrutils.CICDeposit_3() -> amrutils.CICDeposit.CICDeposit_3()
- np.float64(data['dx']) -> np.float64(np.ravel(data['dx'])[0]
- (data['dx'] appears to be a multidimensional array of all the same
values of dx, so I'm just taking the first one -- is there a
better way to
do this?)
Besides those two quirks, the code runs (I'm able to add a field using
ds.add_field), but I get an error when I try to access the data using
ds.all_data()['star_density'] (it seems now is when the field is actually
computed).
I get the following error:
> <ipython-input-5-1af8fbcb718a> in _spdensity(field, data)
> 1 def _spdensity(field, data):
> ----> 2 blank = np.zeros(data.ActiveDimensions, dtype='float64')
> 3 if data['particle_position_x'].size == 0: return blank
> 4 filter = data['creation_time'] > 0.0
> 5 if not filter.any(): return blank
> AttributeError: 'YTRegion' object has no attribute 'ActiveDimensions'
All the examples of ActiveDimensions that I saw in the docs and source
accessed ActiveDimensions as a property of some grid (i.e.
g.ActiveDimensions). Is there a simple way to access that from the
data/YTRegion object that I'm missing? I can access ds.index.grids and take
the first grid there, but ActiveDimensions differs across the grids (And
when I try to do this from within _spdensity, data doesn't have an
index.grids object, just fake_index (which can't access the grids)). Is
there something I'm missing?
Thanks,
Rasmi
Hi all,
I just opened a PR that moves our minimum supported h5py version to 2.4.0:
https://bitbucket.org/yt_analysis/yt/pull-requests/2188
See the pull request description for a justification and explanation. Since
this might be disruptive I wanted to raise this here to get people's
attention. If you have issues with this, please reply to this thread so we
can discuss the pros and cons.
-Nathan
Since we directly depend on sympy at a low level, this is something we need
to think about dealing with.
---------- Forwarded message ----------
From: Aaron Meurer <asmeurer(a)gmail.com>
Date: Thu, May 19, 2016 at 10:51 AM
Subject: [sympy] Feedback requested: The future of Python 2.7 support in
SymPy
To: "sympy(a)googlegroups.com" <sympy(a)googlegroups.com>
Hi all.
Some of us in the broader scientific Python community have been discussing
the future of Python 2 support for various libraries. As you may know,
Python 2.7 will cease to be supported by the core Python development team
in 2020, meaning all updates to it will cease, including security updates.
However, even though we are six major versions into Python 3, the larger
community as a whole is still slow on uptake for supporting it.
The proposal is for libraries to let the community know now when they plan
to drop Python 2.7 support, so that they will better prepared for it, and
hopefully so as an encouragement to start transitioning now, if they
haven't already.
*I propose that we put it on our roadmap to drop Python 2.7 support in
2019. *That is, the first release we do in 2019 will be the last to support
Python 2.7. This is consistent with what we've done so far, which is to
drop support for Python versions once they cease being supported by core
Python.
Other libraries, such as IPython and likely matplotlib, are also joining
together to sign a formal statement about this, which is drafted at
https://python3statement.github.io/.
Some libraries, such as IPython and matplotlib, are proposing to support a
patchfix branch for an older version that supports Python 2.7, but I am
opposed to any plan for SymPy that means supporting more than one version
at a time, as I don't think we have the development effort for it.
*I would like to hear feedback on this, both positive and negative. It
isn't an official decision yet, until the community agrees on it.*
Here is my rationale for doing this. I also plan to publish a blog post
about this soon, which goes into more detail:
As you also probably know, SymPy, like other Python libraries, has done
extra work to support Python 2 and 3 in the same codebase. While this work
is easier than it used to be, it does put a maintainence burden on SymPy,
and it prevents us from using language features which are Python 3-only.
One language feature in particular that I would love to be able to use in
SymPy is keyword-only arguments. This lets you write, for instance
def function(x, y, *, flag=False):
...
and then function(x, y, True) is a TypeError. Only function(x, y,
flag=True) will work. This future-proofs the API, e.g., you can easily
change it to function(x, y, z, *, flag=False) without any API breaks, and
it forces explicitness in keyword arguments. That's one example. There are
other Python 3-only features that we may or may not be able to make use of
as well (like function annotations).
And even without that, the maintenance burden of supporting both versions
is nontrivial. It means all developers have to know about the quirks of
Python 2 and 3, regardless of which one they use primarily. It means that
we always have to remember to add all the right compatibility imports at
the top of files, and avoid things which are one version-only. And it means
extra builds in the test matrix.
Aaron Meurer
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