Analysis tool for the search of narrow band drifting signals in filterbank data
Project description
TURBO_SETI
Summary
turboSETI is an analysis tool for the search of narrow band drifting signals in filterbank data (frequency vs. time). The main purpose of the code is to hopefully one day find signals of extraterrestrial origin!! It can search the data for hundreds of drift rates (in Hz/sec). It can handle either .fil or .h5 file formats.
NOTE: This code is stable, but new features are currently under development. 'Git pull' for the latest version.
Some details for the expert eye:
- Python based, with taylor tree in Cython for improved performance.
- Pre-calculated
drift index arrays. - Output plain text file with information on each hit.
- Including output reader into a pandas DataFrame.
It was originally based on dedoppler dedoppler; which is based on rawdopplersearch.c gbt_seti/src/rawdopplersearch.c)
Dependencies
- astropy
- cython
- numpy
- blimpy (Breakthrough Listen I/O Methods for Python : https://github.com/UCBerkeleySETI/blimpy)
Usage
Expected Inputs
At the moment it expects a single .h5 file produced with blimpy.Waterfall .
Command Line
$turboSETI <FULL_PATH_TO_INPUT_FIL_FILE> [OPTIONS]Use
$turboSETI -hto view usage details.
Example:
NOTE:
Will add an example file here in the near future.
Sample Outputs
File ID: blc07_guppi_57650_67573_Voyager1_0002.gpuspec.0000_57
Source:Voyager1 MJD: 57650.782094907408 RA: 17:10:04.0 DEC: +12:10:58.8 DELTAT: 18.253611 DELTAF(Hz): 2.793968
--------------------------
N_candidates: 1055
--------------------------
Top Hit # Drift Rate SNR Uncorrected Frequency Corrected Frequency Index freq_start freq_end SEFD SEFD_freq
--------------------------
001 -0.353960 51.107710 8419.274366 8419.274366 292536 8419.274344 8419.274386 0.0 0.000000
002 -0.363527 48.528281 8419.274687 8419.274687 292651 8419.274665 8419.274707 0.0 0.000000
003 -0.382660 118.779830 8419.297028 8419.297028 300647 8419.297006 8419.297047 0.0 0.000000
004 -0.392226 51.193226 8419.319366 8419.319366 308642 8419.319343 8419.319385 0.0 0.000000
005 -0.363527 49.893235 8419.319681 8419.319681 308755 8419.319659 8419.319701 0.0 0.000000
006 0.000000 298.061948 8419.921871 8419.921871 524287 8419.921848 8419.921890 0.0 0.000000
Use as a package
> import turbo_seti
> from turbo_seti.findoppler.findopp import FinDoppler
BL internal:
Currently, there is some voyager test data in bls0 at the GBT cluster. From the .../turbo_seti/bin/ folder run the next command.
$ python seti_event.py /datax/users/eenriquez/voyager_test/blc07_guppi_57650_67573_Voyager1_0002.gpuspec.0000.fil -o <your_test_folder> -M 2
This will take /datax/users/eenriquez/voyager_test/blc07_guppi_57650_67573_Voyager1_0002.gpuspec.0000.fil as input (and in this particular case it will discover that this file is too big to handle all at once, so it will first partition it into smaller FITS files and save them into the directory specified by option -o, and then proceed with drift signal search for each small FITS files). Everything else was set to default values.
Sample Outputs:
See /datax/eenriquez/voyager_test/*/*.log, /datax/eenriquez/voyager_test/*.dat for search results and see /datax/eenriquez/voyager_test/*.png for some plots.
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