Analysis tool for the search of narrow band drifting signals in filterbank data
Project description
TURBO_SETI
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.
Some details for the expert eye:
- Python based, with taylor tree in Numba 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
- Python 3.7+
- astropy
- numpy
- blimpy 2.0.34+ (Breakthrough Listen I/O Methods for Python : https://github.com/UCBerkeleySETI/blimpy)
- pandas
- toolz
- fsspec
- dask
- dask[bag]
- numba
- cloudpickle
- cupy (NVIDIA GPU mode only)
Installation
If you have not yet installed blimpy, do so in this manner:
python3 -m pip install --user -U blimpy
Then, install turbo_seti:
python3 -m pip install --user -U turbo_seti
NVIDIA GPU Users
Already included is NUMBA Just-in-Time (JIT) CPU performance enhancements. However, if you have NVIDIA GPU hardware on the computer where turbo_seti is going to execute, you can get significant additional performance improvement. Enable GPU enhanced processing with these steps:
- Install pypi package "cupy":
python3 -m pip install cupy
- Run the executable this way:
turboSETI <PATH_TO_INPUT_HDF5_FILE> -g y [OTHER OPTIONS]
Usage
Expected Input File Format
At the moment, the turboSETI
command line and the FindDoppler
object expect a Filterbank HDF5 file (.h5) or a Filterbank SIGPROC file (.fil). If a SIGPROC file is supplied, it will automatically be converted to an HDF5 file which resides in the same directory as the SIGPROC file.
Usage as a Command Line
Run with data: turboSETI <PATH_TO_INPUT_HDF5_FILE> [OPTIONS]
For an explanation of the program parameters: turboSETI -h
Usage as a Python Package
from turbo_seti.find_doppler.find_doppler import FindDoppler
fdop = FindDoppler(datafile=my_HDF5_file, ...)
fdop.search(...)
Example Usage as a Python Package
import time
from blimpy import Waterfall
from turbo_seti.find_doppler.find_doppler import FindDoppler
H5DIR = "/path_to_seti_data/voyager/"
H5PATH = H5DIR + "Voyager1.single_coarse.fine_res.h5"
OUT_DIR = "/path_to_output_directory"
print("\nUsing HDF5 file: {}\nHeader and data shape:".format(H5PATH))
# -- Get a report of header and data shape
wf = Waterfall(H5PATH)
wf.info()
# -- Instantiate FindDoppler.
print("\nInstantiating the FindDoppler object.")
fdop = FindDoppler(datafile=H5PATH, max_drift=4, snr=25, out_dir=OUT_DIR)
# -- Search for hits and report elapsed time.
print("\nBegin doppler search. Please wait ...")
t1 = time.time()
fdop.search()
elapsed_time = time.time() - t1
print("\nFindDoppler.search() elapsed time = {} seconds".format(elapsed_time))
Sample DAT File Output
# -------------------------- o --------------------------
# File ID: Voyager1.single_coarse.fine_res.h5
# -------------------------- o --------------------------
# Source:Voyager1
# MJD: 57650.782094907408 RA: 17h10m03.984s DEC: 12d10m58.8s
# DELTAT: 18.253611 DELTAF(Hz): -2.793968
# --------------------------
# Top_Hit_# Drift_Rate SNR Uncorrected_Frequency Corrected_Frequency Index freq_start freq_end SEFD SEFD_freq Coarse_Channel_Number Full_number_of_hits
# --------------------------
001 -0.392226 30.612128 8419.319368 8419.319368 739933 8419.321003 8419.317740 0.0 0.000000 0 858
002 -0.373093 245.707984 8419.297028 8419.297028 747929 8419.298662 8419.295399 0.0 0.000000 0 858
003 -0.392226 31.220652 8419.274374 8419.274374 756037 8419.276009 8419.272745 0.0 0.000000 0 858
Sample Console Logging (level=INFO) Output
Note that the coarse channel number appears as a suffix of the logger name. For example, "find_doppler.8" depicts logging for find_doppler.py in coarse channel number 8 (relative to 0).
Using HDF5 file: /seti_data/voyager/Voyager1.single_coarse.fine_res.h5
Header and data shape:
--- File Info ---
DIMENSION_LABELS : ['frequency' 'feed_id' 'time']
az_start : 0.0
data_type : 1
fch1 : 8421.386717353016 MHz
foff : -2.7939677238464355e-06 MHz
ibeam : 1
machine_id : 20
nbeams : 1
nbits : 32
nchans : 1048576
nifs : 1
rawdatafile : guppi_57650_67573_Voyager1_0002.0000.raw
source_name : Voyager1
src_dej : 12:10:58.8
src_raj : 17:10:03.984
telescope_id : 6
tsamp : 18.253611008
tstart (ISOT) : 2016-09-19T18:46:13.000
tstart (MJD) : 57650.78209490741
za_start : 0.0
Num ints in file : 16
File shape : (16, 1, 1048576)
--- Selection Info ---
Data selection shape : (16, 1, 1048576)
Minimum freq (MHz) : 8418.457032646984
Maximum freq (MHz) : 8421.386717353016
Instantiating the FindDoppler object.
find_doppler.0 INFO {'DIMENSION_LABELS': array(['frequency', 'feed_id', 'time'], dtype=object), 'az_start': 0.0, 'data_type': 1, 'fch1': 8421.386717353016, 'foff': -2.7939677238464355e-06, 'ibeam': 1, 'machine_id': 20, 'nbeams': 1, 'nbits': 32, 'nchans': 1048576, 'nifs': 1, 'rawdatafile': 'guppi_57650_67573_Voyager1_0002.0000.raw', 'source_name': 'Voyager1', 'src_dej': <Angle 12.183 deg>, 'src_raj': <Angle 17.16777333 hourangle>, 'telescope_id': 6, 'tsamp': 18.253611008, 'tstart': 57650.78209490741, 'za_start': 0.0}
Begin doppler search. Please wait ...
find_doppler.0 INFO File: /seti_data/voyager/Voyager1.single_coarse.fine_res.h5
drift rates (min, max): (0.000000, 4.000000)
SNR: 25.000000
Starting ET search using /seti_data/voyager/Voyager1.single_coarse.fine_res.h5
find_doppler.0 INFO Parameters: datafile=/seti_data/voyager/Voyager1.single_coarse.fine_res.h5, max_drift=4, min_drift=0.0, snr=25, out_dir=/seti_data/voyager/, coarse_chans=None, flagging=False, n_coarse_chan=None, kernels=None, gpu_backend=False, precision=2, append_output=False, log_level_int=20, obs_info={'pulsar': 0, 'pulsar_found': 0, 'pulsar_dm': 0.0, 'pulsar_snr': 0.0, 'pulsar_stats': array([0., 0., 0., 0., 0., 0.]), 'RFI_level': 0.0, 'Mean_SEFD': 0.0, 'psrflux_Sens': 0.0, 'SEFDs_val': [0.0], 'SEFDs_freq': [0.0], 'SEFDs_freq_up': [0.0]}
find_doppler.0 INFO Top hit found! SNR 30.612128, Drift Rate -0.392226, index 739933
find_doppler.0 INFO Top hit found! SNR 245.707984, Drift Rate -0.373093, index 747929
find_doppler.0 INFO Top hit found! SNR 31.220652, Drift Rate -0.392226, index 756037
FindDoppler.search() elapsed time = 9.972093105316162 seconds
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