glueviz 1.0.1+dfsg-2 source package in Ubuntu
Changelog
glueviz (1.0.1+dfsg-2) unstable; urgency=medium
* Drop obsolete dependency on jupyter_client (Closes: #999703)
* Bump Standards-Version to 4.6.0. No changes required.
* debian/copyright: Update copyright holder email and year for
debian/*.
* debian/glue: Bump dependency on glue core for load entrypoint.
-- Josue Ortega <email address hidden> Wed, 08 Dec 2021 22:01:09 -0600
Upload details
- Uploaded by:
- Debian Astronomy Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian Astronomy Maintainers
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section | |
|---|---|---|---|---|
| Mantic | release | universe | misc | |
| Lunar | release | universe | misc | |
| Kinetic | release | universe | misc | |
| Jammy | release | universe | misc |
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| glueviz_1.0.1+dfsg-2.dsc | 2.4 KiB | 0a990c0873e113a6b86a986ec9bc1915fe5e20f76e374beb094b018b6296e331 |
| glueviz_1.0.1+dfsg.orig.tar.gz | 22.2 MiB | 6efb4a093de49d0dcd803273ed13b625348b7557b25c633e55c28a2694b8245e |
| glueviz_1.0.1+dfsg-2.debian.tar.xz | 14.0 KiB | 548e1cd8677eb57c3af2719e0a01205c86a26d836fccc2b34e6ec5eeb7ab89bd |
Available diffs
- diff from 1.0.1+dfsg-1 to 1.0.1+dfsg-2 (1008 bytes)
No changes file available.
Binary packages built by this source
- glueviz: Linked data visualization
Glue is a Python project to link visualizations of scientific datasets across
many files. Some of its features are:
.
* Interactive, linked statistical graphics of multiple files.
* Support for many file formats including common image formats,
ascii tables, astronomical image and table formats (fits, vot, ipac), and
HDF5. Custom data loaders can also be easily added.
* Highly scriptable and extendable.
- python3-glue: Python 3 library for data interaction
python3-glue is a Python library for data interaction, it blurs the boundary
between GUI-centric and code-centric data exploration.
There are many ways to leverage Glue from Python. Among other things, you can
write code to do the following:
.
* Send data in the form of NumPy arrays or Pandas DataFrames to Glue for
exploration.
* Write startup scripts that automatically load and clean data,
before starting Glue.
* Write custom functions to parse files, and plug these functions into the
Glue GUI.
* Write custom functions to link datasets, and plug these into the Glue GUI.
* Create your own visualization modules.
