Skip to main content

AGB Star Deprojection

A package for visualising radially expanding circumstellar envelopes of AGB stars.


Quick Start

Installation

python3 -m pip install agb_star_deprojection_methods

Import

from agb_star_deprojection_methods.classes import CondensedData, StarData

Initialise a StarData object

fits_file = "example_fits_file.fits"  # relative path to fits file
distance_to_star = 8.04e8             # distance to star in AU
rest_frequency = 2.3e11               # rest frequency in Hz

star = StarData(fits_file, distance_to_star, rest_frequency)

Plot channel maps (opens in matplotlib window)

star.plot_channel_maps()  # many optional arguments

Plot 3D deprojection using plotly

star.plot_3D()  # many optional arguments

Export to a CondensedData object

data = star.export()

Tweak parameters and create a new StarData object

data.v_exp = 20
new_star = StarData(data)

Expand envelope over time

years = 1000
info = new_star(years)  # CondensedData object representing the envelope in 1000 years
expanded_star = StarData(info)

Save animation frame-by-frame to a folder

path_to_folder = "animation/frames"
star.plot_3D(folder = path_to_folder, num_angles = 100)

Creating a Mask

To create a mask manually, use the following script:

from agb_star_deprojection_methods.classes import StarData

fits_file = "example_fits_file.fits"
distance_to_star = 8.04e8
rest_frequency = 2.3e11

star = StarData(fits_file, distance_to_star, rest_frequency)

stds = 3  # number of standard deviations to initially filter by
savefile = "trial_mask.npy"  # .npy file to save mask to

# open mask selector
star.create_mask(filter_stds=stds, savefile=savefile)

Running this will open a matplotlib window with a subplot for each velocity channel.

  • Double click inside a subplot, then drag to lasso points.
  • When you finish dragging, press:
    • A to keep only these points in the mask,
    • R to remove these points from the mask,
    • Enter to do neither.
  • Once you have completed the mask, close the matplotlib application.
  • The mask will be saved to the location specified by savefile.

To load the star data with the mask:

from agb_star_deprojection_methods.classes import StarData

fits_file = "example_fits_file.fits"
distance_to_star = 8.04e8
rest_frequency = 2.3e11

maskfile = "trial_mask.npy"  # .npy file to load mask from

star = StarData(fits_file, distance_to_star, rest_frequency, maskfile)

# any other operations you want done
# ...

Further Reading

See our report and more detailed documentation at https://psychedelickoala.github.io/agb-star-deprojection-docs/AGB-Star-Deprojection.html.

Metadata

Release files for agb-star-deprojection-methods 0.0.3

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

Source distribution (sdist)

Source distribution for agb-star-deprojection-methods 0.0.3
File Size Uploaded Provenance
agb_star_deprojection_methods-0.0.3.tar.gz 20.0 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for agb-star-deprojection-methods 0.0.3
File Interpreter ABI Platform
agb_star_deprojection_methods-0.0.3-py3-none-any.whl Python 3 none any Details

Total release size: 41.1 kB

Release files / agb_star_deprojection_methods-0.0.3.tar.gz

Download URL agb_star_deprojection_methods-0.0.3.tar.gz
Size 20.0 kB
Tags Source
SHA-256 checksum
How to use checksums
2c1f278f9a7525de42e7911feb1525650a6a588d8e84b0e5f631337a932c76d5
BLAKE2b-256 checksum
How to use checksums
c856d2a64bf9168b3791b501ab6d4ebdc39d91e5b1b68d2dd3b5ee0247f760a5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.4

Release files / agb_star_deprojection_methods-0.0.3-py3-none-any.whl

Download URL agb_star_deprojection_methods-0.0.3-py3-none-any.whl
Size 21.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a8f5cd6cf5eb70c7fdd21b0f766e52f380d06ddd29f731f3f59e8fe6f3ea1f2f
BLAKE2b-256 checksum
How to use checksums
5eec96e2a3f71300f461869ed87bb7dd9db28ef46ff44aa1cac3b9ff07483a51
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.4

Security for agb-star-deprojection-methods 0.0.3

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.

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