Skip to main content
# SNClassifying_Pre-alpha
Supernovae classifying and redshifting software: development stage


1. How to install:

Install tensorflow (https://www.tensorflow.org/versions/r0.11/get_started/os_setup.html#download-and-setup).
Run GUI/main.py
Once open, type in a known redshift
Browse for any single spectrum FITS, ASCII, dat, or two-column text file.
Click any of the best matches to view the continuum-subtracted binned spectra.
If the input spectrum is too noisy, increase the smoothing level, and click 'Re-fit with priors'


2. Dependencies:
python2.7 (unconfirmed python3)
numpy
scipy
PyQt4
tensorflow

3. How to raise issues:

4. Examples

5. API Usage
Notes:
Current version requires an input redshift (inaccurate results if redshift is unknown)

Metadata

Release files for deepstars 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for deepstars 0.1.0
File Size Uploaded Provenance
deepstars-0.1.0.tar.gz 2.9 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for deepstars 0.1.0
File Interpreter ABI Platform
deepstars-0.1.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 7.0 kB

Release files / deepstars-0.1.0.tar.gz

Download URL deepstars-0.1.0.tar.gz
Size 2.9 kB
Tags Source
SHA-256 checksum
How to use checksums
fa2d6284a6cd7f1726a7abbff1b473d84035d10972cf909e1cc40f8e7b83c10a
BLAKE2b-256 checksum
How to use checksums
0427978041d3caee572a32007e6314f28b560f917b84783d8ebb0f7012f93011
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / deepstars-0.1.0-py2.py3-none-any.whl

Download URL deepstars-0.1.0-py2.py3-none-any.whl
Size 4.1 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
8ed25ae6fc4a7ee9b64ed37aed0446717dae572a25f6cbd53b3f0fca301e833d
BLAKE2b-256 checksum
How to use checksums
74008fa6a18defc461e7ac21d39ea15a90a1eec0e80bfe31078246704306dac4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Security for deepstars 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page