Skip to main content

A fast generic spectrum simulator

Project description

PyEchelle

PyEchelle is a simulation tool, to generate realistic 2D spectra, in particular cross-dispersed echelle spectra. However, it is not limited to echelle spectrographs, but allows simulating arbitrary spectra for any fiber-fed or slit spectrograph, where a model file is available. Optical aberrations are treated accurately, the simulated spectra include photon and read-out noise.

PyEchelle uses numba for implementing fast Python-based simulation code. It also comes with CUDA support for major speed improvements.

Example usage

You can use PyEchelle directly from the console:

pyechelle --spectrograph MaroonX --fiber 2-4 --sources Phoenix --phoenix_t_eff 3500 -t 10 --rv 100 -o mdwarf.fit

If you rather script in python, you can do the same as above with the following python script:

from pyechelle.simulator import Simulator
from pyechelle.sources import Phoenix
from pyechelle.spectrograph import ZEMAX

sim = Simulator(ZEMAX("MaroonX"))
sim.set_ccd(1)
sim.set_fibers([2, 3, 4])
sim.set_sources(Phoenix(t_eff=3500))
sim.set_exposure_time(10.)
sim.set_radial_velocities(100.)
sim.set_output('mdwarf.fits', overwrite=True)
sim.run()

Both times, a PHOENIX M-dwarf spectrum with the given stellar parameters, and a RV shift of 100m/s for the MAROON-X spectrograph is simulated.

The output is a 2D raw frame (.fits) and will look similar to:

Check out the Documentation for more examples.

Pyechelle is the successor of Echelle++ which has a similar functionality but was written in C++. This package was rewritten in python for better maintainability, easier package distribution and for smoother cross-platform development.

Installation

As simple as

pip install pyechelle

Check out the Documentation for alternative installation instruction.

Usage

See

pyechelle -h

for all available command line options.

See Documentation for more examples.

Concept:

The basic idea is that any spectrograph can be modelled with a set of wavelength-dependent transformation matrices and point spread functions which describe the spectrographs' optics:

First, wavelength-dependent affine transformation matrices are extracted from the ZEMAX model of the spectrograph. As the underlying geometric transformations (scaling, rotation, shearing, translation) vary smoothly across an echelle order, these matrices can be interpolated for any intermediate wavelength.

Second, a wavelength-dependent point spread functions (PSFs) is applied on the transformed slit images to properly account for optical aberrations. Again, the PSF is only slowly varying across an echelle order, allowing for interpolation at intermediate wavelength.

Echelle simulation

Both, the matrices and the PSFs have to be extracted from ZEMAX only once. It is therefore possible to simulate spectra without access to ZEMAX

Citation

Please cite this paper if you find this work useful in your research.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyechelle-0.3.2.tar.gz (32.4 kB view details)

Uploaded Source

Built Distribution

pyechelle-0.3.2-py3-none-any.whl (36.3 kB view details)

Uploaded Python 3

File details

Details for the file pyechelle-0.3.2.tar.gz.

File metadata

  • Download URL: pyechelle-0.3.2.tar.gz
  • Upload date:
  • Size: 32.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.7 CPython/3.8.11 Linux/5.4.0-124-generic

File hashes

Hashes for pyechelle-0.3.2.tar.gz
Algorithm Hash digest
SHA256 cf066907a19799a08a90a387925f8e64c3f590387ac6b6d668068618fac4fc7a
MD5 4e74b930789c2cccf516e491cbe0978d
BLAKE2b-256 896b457df5bdec40f95ae2735ab6a6dfc48b335c54818cb8e5e04898646b050c

See more details on using hashes here.

File details

Details for the file pyechelle-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: pyechelle-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 36.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.7 CPython/3.8.11 Linux/5.4.0-124-generic

File hashes

Hashes for pyechelle-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 1eabd4d50cde386db120a73b04bd2f4d87a63faba4cb4d43350f46b73ba37461
MD5 4adba098c801dc7415fbd94d4245fce7
BLAKE2b-256 58b56dbafdf8d7a68088a946e0ff05ca1d9f34fa2cbfdfc1a2c29ceb6480f053

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page