While most bugs and issues are managed using the astropy issue tracker, this document lists issues that are too difficult to fix, may require some intervention from the user to workaround, or are due to bugs in other projects or packages.
Quantities are subclassed from numpy’s ndarray and in some numpy operations (and in scipy operations using numpy internally) the subclass is ignored, which means that either a plain array is returned, or a Quantity without units. E.g.:
In : import astropy.units as u In : import numpy as np In : q = u.Quantity(np.arange(10.), u.m) In : np.dot(q,q) Out: 285.0 In : np.hstack((q,q)) Out: <Quantity [ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1., 2., 3., 4., 5., 6., 7., 8., 9.] (Unit not initialised)>
Work-arounds are available for some cases. For the above:
In : q.dot(q) Out: <Quantity 285.0 m2> In : u.Quantity([q, q]).flatten() Out: <Quantity [ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1., 2., 3., 4., 5., 6., 7., 8., 9.] m>
Displaying long docstrings that contain Unicode characters may fail on some platforms in the IPython console (prior to IPython version 0.13.2):
In : import astropy.units as u In : u.Angstrom? ERROR: UnicodeEncodeError: 'ascii' codec can't encode character u'\xe5' in position 184: ordinal not in range(128) [IPython.core.page]
This can be worked around by changing the default encoding to utf-8 by adding the following to your sitecustomize.py file:
import sys sys.setdefaultencoding('utf-8')
Note that in general, this is not recommended, because it can hide other Unicode encoding bugs in your application. However, in general if your application does not deal with text processing and you just want docstrings to work, this may be acceptable.
The IPython issue: https://github.com/ipython/ipython/pull/2738
On MacOS X, you may see the following error when running setup.py:
ValueError: unknown locale: UTF-8
This is due to the LC_CTYPE environment variable being incorrectly set to UTF-8 by default, which is not a valid locale setting. To fix this, set this environment variable, as well as the LANG and LC_ALL environment variables to e.g. en_US.UTF-8 using:
export LANG="en_US.UTF-8" export LC_ALL="en_US.UTF-8" export LC_CTYPE="en_US.UTF-8"
To avoid any issues in future, you should add this line to your ~/.bash_profile file.
To test these changes, open a new terminal and type locale, and you should see something like:
$ locale LANG="en_US.UTF-8" LC_COLLATE="en_US.UTF-8" LC_CTYPE="en_US.UTF-8" LC_MESSAGES="en_US.UTF-8" LC_MONETARY="en_US.UTF-8" LC_NUMERIC="en_US.UTF-8" LC_TIME="en_US.UTF-8" LC_ALL="en_US.UTF-8"
If so, you can go ahead and try running setup.py again (in the new terminal).
When converting floating point numbers to strings on Python 2.6 on a Microsoft Windows platform, some of the requested precision may be lost.
The easiest workaround is to install Python 2.7.
The Python issue: http://bugs.python.org/issue7117
When running the Astropy tests using astropy.test() in an IPython interpreter some of the tests in the astropy/tests/test_logger.py fail. This is due to mutually incompatible behaviors in IPython and py.test, and is not due to a problem with the test itself or the feature being tested.
On Hurd and possibly other platforms flush() on memory-mapped files is not implemented, so writing changes to a mmap’d FITS file may not be reliable and is thus disabled. Attempting to open a FITS file in writeable mode with mmap will result in a warning (and mmap will be disabled on the file automatically).
It is possible for installation of a new version of Astropy, or upgrading of an existing installation to crash due to not having permissions on the ~/.astropy/ directory (in your home directory) or some file or subdirectory in that directory. In particular this can occur if you installed Astropy as the root user (such as with sudo) at any point. This can manifest in several ways, but the most common is a traceback ending with ImportError: cannot import name config. To resolve this issue either run sudo chown -R <your_username> ~/.astropy or, if you don’t need anything in it you can blow it away with sudo rm -rf ~/.astropy.
See for example: https://github.com/astropy/astropy/issues/987
Colored printing of log messages and other colored text does work in Windows but only when running in the IPython console. Colors are not currently supported in the basic Python command-line interpreter on Windows.
In Python 3, prior to Numpy 1.6.2, there was a bug (in Numpy) that caused sorting of structured arrays to silently fail under certain circumstances (for example if the Table contains string columns) on MacOS X, Windows, and possibly other platforms other than Linux. Since Table.sort relies on Numpy to internally sort the data, it is also affected by this bug. If you are using Python 3, and need the sorting functionality for tables, we recommend updating to a more recent version of Numpy.
Upgrading Astropy in the anaconda python distribution using pip can result in a corrupted install with a mix of files from the old version and the new version. Anaconda users should update with conda update astropy. There may be a brief delay between the release of Astropy on PyPI and its release via the conda package manager; users can check the availability of new versions with conda search astropy.
Building may fail with warning messages such as:
unable to find 'pow' or 'sincos'
at the linking phase. Upgrading the OS packages for Python should fix the issue, though an immediate workaround is to edit the file:
and search for the line that adds the option -Wl,--no-undefined to the LDFLAGS variable and remove that option.
The remote data utilities in astropy.utils.data depend on the Python standard library shelve module, which in some cases depends on the standard library bsddb module. Some Python distributions, including but not limited to
are built without support for the bsddb module, resulting in an error such as:
ImportError: No module named _bsddb
One workaround is to install the bsddb3 module.
|||Continuum says this will be fixed in their next Python build.|
For Numpy 1.5, when reading an ASCII table that has integers which are too large to fit into the native C long int type for the machine, then the values get converted to float type with no warning. This is due to the behavior of numpy.array and cannot easily be worked around. We recommend that users upgrade to a newer version of Numpy. For Numpy >= 1.6 a warning is printed and the values are treated as strings to preserve all information.