teas - Tools for the Extraction and Analysis of Spectra from JWST observations
teas is a package of utilities to analyze spectra from the James Webb Space Telescope. It provides tools to align and process JWST data products, extract 1D spectra from 3D integral-field-unit data cubes from NIRSpec and MIRI MRS, and create images of observed regions with NIRCam observations.
Features:
Extract 1D spectra from 3D IFU data from NIRSpec and MIRI MRS
Create images of spectrally imaged regions using NIRCam data
Align and reproject the WCS of data cubes and images
Find the field of view of NIRSpec or MIRI MRS data products within NIRCam images
Fit the continuum using either an anchors-and-splines fitting or linear regression
Stitch together spectra
Shift, scale, and normalize spectrum flux
Installation
It is recommended to install teas in a new environment to avoid version conflicts with other packages. To do this, run:
conda create --name teas-env python=3.9Then, activate the environment and install the package. The latest released version can be installed with pip:
conda activate teas-env
pip install teas --upgrade1 maintainer
Release files for teas 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| teas-0.1.1.tar.gz | 21.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| teas-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 43.7 kB
Release files / teas-0.1.1.tar.gz
| Download URL | teas-0.1.1.tar.gz |
|---|---|
| Size | 21.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / teas-0.1.1-py3-none-any.whl
| Download URL | teas-0.1.1-py3-none-any.whl |
|---|---|
| Size | 21.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
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