yorick-mira 1.1.0+git20170124.3bd1c3~dfsg1-2 source package in Ubuntu
Changelog
yorick-mira (1.1.0+git20170124.3bd1c3~dfsg1-2) unstable; urgency=low
* Bug fix: "ymira crashes when trying to fit several wavelengths"
(Closes: #856835).
-- Thibaut Paumard <email address hidden> Sun, 05 Mar 2017 11:43:23 +0100
Upload details
- Uploaded by:
- Debian Astronomy Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian Astronomy Maintainers
- Architectures:
- all
- Section:
- science
- Urgency:
- Low Urgency
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Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| yorick-mira_1.1.0+git20170124.3bd1c3~dfsg1-2.dsc | 2.2 KiB | 3129a92ec08701239627b8ef988ba643a860b514150f27600d27c23378b0db58 |
| yorick-mira_1.1.0+git20170124.3bd1c3~dfsg1.orig.tar.xz | 256.8 KiB | d765bd4819d130983f72f8483283922dd068359298eb898735bbf8bb99440a3f |
| yorick-mira_1.1.0+git20170124.3bd1c3~dfsg1-2.debian.tar.xz | 8.2 KiB | ff57b0da222d091c3515748985af4ac78b58e9bb2c79a9eee4fe11087cb7205f |
Available diffs
No changes file available.
Binary packages built by this source
- yorick-mira: optical interferometry image reconstruction within Yorick
MiRA is an algorithm for image reconstruction from data provided by
optical interferometers. It is written in the Yorick language and
operated through the Yorick interpreter.
.
MiRA won the 2008' Interferometric Imaging Beauty Contest organized
by International Astronomical Union (IAU) to compare the image
synthesis algorithms designed for optical interferometry. In a
nutshell, MiRA proceeds by direct minimization of a penalized
likelihood. This penalty is the sum of two terms: a likelihood term
(typically a χ2) which enforces agreement of the model with the data,
plus a regularization term to account for priors. The priors are
required to lever the many degeneracies due to the sparseness of the
spatial frequency sampling. MiRA implements many different
regularizations (quadratic or edge-preserving smoothness, total
variation, maximum entropy, etc.) and let the user defines his own
priors. The likelihood penalty is modular and designed to account for
available data of any kind (complex visibilities, powerspectra and/or
closure phase). One of the strength of MiRA is that it is purely
based on an inverse problem approach and can therefore cope with
incomplete data set; for instance, MiRA can build an image without
any Fourier phase information. Input data must be in OI-FITS format.
