How to Install and Uninstall python3-pysynphot Package on Kali Linux

Last updated: November 22,2024

1. Install "python3-pysynphot" package

Here is a brief guide to show you how to install python3-pysynphot on Kali Linux

$ sudo apt update $ sudo apt install python3-pysynphot

2. Uninstall "python3-pysynphot" package

This is a short guide on how to uninstall python3-pysynphot on Kali Linux:

$ sudo apt remove python3-pysynphot $ sudo apt autoclean && sudo apt autoremove

3. Information about the python3-pysynphot package on Kali Linux

Package: python3-pysynphot
Source: pysynphot (2.0.0+dfsg-1)
Version: 2.0.0+dfsg-1+b5
Installed-Size: 18036
Maintainer: Debian Astronomy Team
Architecture: amd64
Depends: python3 (<< 3.13), python3 (>= 3.11~), python3-astropy, python3-bs4, python3-numpy (>= 1:1.22.0), python3-numpy-abi9, python3-six, python3:any, libc6 (>= 2.4)
Size: 1928140
SHA256: ce2f18d889dc9c091ea2d2239922cf87670bad819150d88ce60a434e368addee
SHA1: fea593f1a2d9ee74f99e03890a4a5a07b58f7263
MD5sum: 046d94435335317049062fec303d36a5
Description: Python Synthetic Photometry Utilities
pysynphot simulates photometric data and spectra as they are observed with
the Hubble Space Telescope (HST). Passbands for standard photometric systems
are available, and users can incorporate their own filters, spectra, and
data. pysynphot user interface allows you to:
.
* Construct complicated composite spectra from various grids of model
atmosphere spectra, parameterized spectrum models, and atlases of stellar
spectrophotometry.
* Simulate observations.
* Query the resulting structures for quantities of interest, such as
countrate, effective wavelength, effective stimulus, as well as the
wavelength and flux arrays.
* Plot HST sensitivity curves and calibration target spectra.
* Compute photometric calibration parameters for any HST instrument mode.
.
pysynphot can help HST observers to perform cross-instrument simulations, to
examine the transmission curve of the HST Optical Telescope Assembly (OTA),
and spectra of HST calibration targets. Expert users can take advantage of
the control and data structures available in Python to easily perform
repetitive operations such as simulate the observation of multiple type of
sources through multiple observing modes.
Description-md5:
Homepage: https://ssb.stsci.edu/pysynphot/docs/
Section: python
Priority: optional
Filename: pool/main/p/pysynphot/python3-pysynphot_2.0.0+dfsg-1+b5_amd64.deb