TESS Variable Star Light Curve Fitter
Project description
Varstar Detect
Python package optimized for variable star detection in TESS Secctor 1 data.
Initialization:
To install repository from PyPi: from varstardectect import Star
Looking for stellar variability:
Use the amplitude_test()
function, with the following documentation,
to determine objects which are variable. In which you have to determine
the directory of the archive file with the sector info, it must be a csv.
amplitude_test(min, max, amp, directory):
"""
amplitude_test DOCUMENTATION
---------------------------------------------------------------------
Detects variable stars with amplitude higher than threshold.
---------------------------------------------------------------------
INPUTS: - min: lower star search (TESS) range delimiter
- max: higher star search (TESS) range delimiter
- amp: amplitude threshold
- directory: directory with TESS sector 1 files csv. You can
download from
https://tess.mit.edu/observations/target-lists/
-------------------------------------------------------------
OUTPUTS: - candidates: 1D numpy array with variable candidate
target IDs
- chis: 1D numpy array with the chi^2 parameter of each
approximation.
- degree: 1D numpy array with the degree of the optimal
degree of the approximation.
- periods: 1D numpy array with the period of each
approimating function.
- period_errors: 1D numpy array with the period
uncertainty for each candidate.
- amplitudes: 1D numpy array with the amplitude of each
approximation.
- amplitude_errors: 1D numpy array with the uncertainty
of the amplitude of each candidate.
----------------------------------------------------------------------
PROCEDURE:
1. Calculates amplitude for an observed star.
2. Calculates if amplitude is bigger than threshold.
3. Returns candidates and their characteristics.
----------------------------------------------------------------------
"""
Background:
The function uses several numerical and statistical methods to filter and interpret the data obtained form TESS, providing the characteristics of each star through phenomenological analysis of the lightcurve, given that it has passed the amplitude test.
DISCLAIMER:
This is a Beta state of the program. It is unstable therefore itcan have bugs. It has not been optimized correctly yet.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file varstardetect-1.1.10.tar.gz
.
File metadata
- Download URL: varstardetect-1.1.10.tar.gz
- Upload date:
- Size: 234.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 390afec3d44344200455eac79507d95a07c679425597ca3c12f288c60b7ed26a |
|
MD5 | 5594477236771cd2d16ea17be4013e93 |
|
BLAKE2b-256 | 26a2708c6de1b208a68d2c5675d30add4e5ebf393e6b41adbe9c5da0c582f1e6 |
File details
Details for the file varstardetect-1.1.10-py3-none-any.whl
.
File metadata
- Download URL: varstardetect-1.1.10-py3-none-any.whl
- Upload date:
- Size: 232.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d10758026fadc7e72cfd12b50515643f8516da48021ea771346a0137e928c7f2 |
|
MD5 | 0674fc6f8687f040e4ce93f4dd9841ca |
|
BLAKE2b-256 | 2abc6a87ed6eb8cbbb97d289806bd200f020d88ad5a63d2bcaec1f9863385b20 |