Skip to content

Latest commit

 

History

History
178 lines (140 loc) · 10.2 KB

README.md

File metadata and controls

178 lines (140 loc) · 10.2 KB

FRBGui

FRBGui is a graphical user interface for measuring spectro-temporal properties of Fast Radio Bursts from their waterfalls using 2D autocorrelations. It can be used to split bursts with multiple components, change the dispersion measure (DM), add noise filters, and other preparation tasks before measurement.

After measurement, FRBGui can be used to review and fix incorrect measurements by supplying initial guessues, producing an output pdf of all measurements and spreadsheets of measured values. Spreadsheets produced in this way can be loaded back into the FRBGui for further work or different sessions of measurements.

Measurements can be performed over a range of DMs and include the burst frequency, the sub-burst slope and/or drift rate, burst duration and burst bandwidth.

Features include:

  • Change the DM of a burst
  • Crop waterfalls
  • Mitigate noise and RFI via background subtraction, SK-SG filter, manual channel zapping, and mask ranges
  • Import and export of noise masks
  • Measure over user-defined ranges of DMs
  • Downsample waterfalls in frequency and time
  • Split bursts with arbitrary numbers of sub-burst components
  • Define inital fit guesses
  • Review measurements via the output table
  • Correct individual fits by DM
  • Output measurements as a csv spreadsheet and/or PDF with plots of each waterfall with its measurements.
  • Provides driftrate and driftlaw python modules for scripting and automation.
  • Automatic backups of measurements as they are made

Click here for a video demo of FRBGui

Screenshot of FRBGui

The GUI is extensible and pull requests are welcome.

Status

Currently FRBGui works best with waterfalls saved as 2d numpy arrays (See Usage for more details). FRBGui is functional and can produce thousands of measurements but is quirky, buggy, and not tested on different platforms. FRBGui will run on most platforms but with varying performance.

Installation

Install FRBGui with

pip install --user frbgui

For a local, editable installation with bleeding edge updates you may clone the repo and install locally:

    git clone https://github.com/mef51/frbgui.git
    cd frbgui
    pip install --user --editable .

Acknowledgements

If used in an academic study please cite

"A broad survey of spectro-temporal properties from FRB20121102A", Chamma, Mohammed A. ; Rajabi, Fereshteh ; Kumar, Aishwarya ; Houde, Martin. Oct. 4 2022. Submitted to MNRAS. arxiv:2210.00106, ADS:2022arXiv221000106C

Usage

Frbgui Demo

Getting Started

Run from the command-line with the following command to start in your current working directory:

frbgui

In a python script, you can invoke the gui in the following way:

from frbgui import frbgui

frbgui() # starts the GUI

At the moment FRBGui works best with burst waterfalls that are prepared as python .npz archives. The following snippet shows the format of the archive and an example of how a burst can be saved in the right format:

wfall = # 2D numpy array with shape (num freq channels, num time channels)
burstmetadata = {
    ### required fields:
    'dfs'       : # 1D array of frequency channels in MHz,
    'DM'        : # dispersion measure (DM) in pc/cm^3, float
    'bandwidth' : # bandwidth of `wfall` in MHz, float
    'duration'  : # duration of `wfall` in seconds, float
    ### optional fields:
    'center_f'  : # burst frequency in MHz, optional,
    'freq_unit' : # string of freqeuncy unit, e.g. 'MHz', optional,
    'time_unit' : # string of time unit, e.g. 'ms', optional,
    'int_unit'  : # string of intensity unit, e.g. 'Jy', optional,
    'telescope' : # string of observing telescope, e.g. 'Arecibo', optional,
    'burstSN'   : # float of signal to noise ratio, optional,
    'tbin'      : # float of time resolution, optional
}

np.savez('burst.npz', wfall=wfall, **burstmetadata)

Optional fields are used for display purposes and do not otherwise affect measurements from within frbgui.

Documentation

For complete documentation and tutorials please visit https://frbgui.readthedocs.io/en/latest/.

Output CSVs

frbgui outputs measurements as a spreadsheet along with a corresponding PDF that contains plots of each burst waterfall with its measurements overlaid. The output spreadsheet is arranged by one measurement per row under the following columns:

Note:

  • Plaintext columns like "slope (mhz/ms)" indicate a measurement.
  • Italicized columns indicate information about how the measurement was taken, such as "time_res (s)".
  • Stricken column names indicate a deprecated column and normally should not be used.
Column Name Description
name The name of the burst file measured, potentially suffixed with a letter (e.g., “a”, “b”, “c”) denoting the sub-pulse
DM The particular trial DM used to perform measurements
center_f The center frequency of the burst as measured by frbgui
center_f_err The propagated uncertainty on center_f. For sub-pulses, this value will be the same across DMs, as the waterfall noise needed to compute this value will be sampled once from the full waterfall.
slope (mhz/ms) The sub-burst slope, obtained from the cotangent of the fit angle
slope error (mhz/ms) The propagated uncertainty on the slope
theta The angle of the semi major axis of the fit ellipse measured counter-clockwise from the positive y-axis
red_chisq Reduced chi-squared indicating the goodness-of-fit of the 2D Gaussian to the 2D ACF
amplitude Amplitude of the 2D Gaussian fit. Not normalized.
xo Central x-position (time) of the 2D gaussian fit to the 2D-ACF
yo Central y-position (frequency) of the 2D gaussian fit to the 2D-ACF
sigmax Standard deviation in x (time if vertical) of the 2D gaussian fit to the 2D-ACF
sigmay Standard deviation in y (frequency if vertical) of the 2D gaussian fit to the 2D-ACF
angle The fit angle. Equivalent to theta up to a difference of pi/2 due to the ambiguity between axes when fitting
amp_error The fit uncertainty on the amplitude
xo_error The fit uncertainty on xo
yo_error The fit uncertainty on yo
sigmax_error The fit uncertainty on sigmax
sigmay_error The fit uncertainty on sigmay
angle_error The fit uncertainty on angle
slope_abs The absolute value of slope (mhz/ms). If negative, this indicates a potential measurement issue
slope_over_nuobs 'slope_abs’ / ‘center_f’. In the TRDM, this is proportional to 1/’tau_w_ms’
slope_over_nuobs_err The propagated 2D gaussian fit uncertainty for ‘slope_over_nuobs’.
recip_slope_over_nuobs The reciprocal of slope_over_nuobs
slope_abs_nuobssq 'slope_abs’ / ‘center_f**2’. In the TRDM, this is proportional to a constant.
min_sigma Same as either sigmax or sigmay, whichever is smaller
max_sigma Same as either sigmax or sigmay, whichever is larger
min_sigma_error Same as either sigmax_error or sigmay_error, associated with whichever sigma is smaller
max_sigma_error Same as either sigmax_error or sigmay_error, associated with whichever sigma is larger
tau_w The sub-burst duration in milliseconds as defined in Chamma et al. (2022).
tau_w_error The propagated uncertainty on tau_w (ms)
tau_w_ms The sub-burst duration in milliseconds as defined in Chamma et al. (2022). An alias of tau_w. Units are implied by the choice of coordinates when fitting
bandwidth (mhz) Best-fit bandwidth for the sub-pulse in MHz
bandwidth error (mhz) Propagated uncertainty for the bandwidth in MHz
f_res (mhz) The frequency resolution (MHz) of the final waterfall used for the FRBGUI measurements
time_res (s) The time resolution (seconds) of the final data array used for the FRBGUI measurements
downf The factor by which the file was downsampled in frequency from FRBGUI from the original waterfall
downt The factor by which the file was downsampled in time from FRBGUI from the original waterfall
fchans The number of frequency channels remaining after the downsample in FRBGUI
tchans The number of time channels remaining after the downsample in FRBGUI
tsamp_width The number of time channels set by the user in FRBGUI used for measurement (i.e., the width of the waterfall)
subbg_start (ms) The time, in ms, from the start of the file that the user-defined background sample begins
subbg_end (ms) The time, in ms, from the start of the file that the user-defined background sample ends
sksigma The sigma chosen for the SK-SG filter, which performs RFI removal
skwindow The window chosen for the SK-SG filter, which performs RFI removal
regstart_a When using regions, the start of the “a” subpulse region in ms
regend_a When using regions, the end of the “a” subpulse region in ms
regstart_b When using regions, the start of the “b” subpulse region in ms
regend_b When using regions, the end of the “b” subpulse region in ms
background The size of the background subpulse region in ms. Used to pad sub-pulses with zeroes, which improves measurement stability. Background region is assumed to start from 0 ms
sigma_t The product of min_sigma and time_res (s). This is a (poor) measure of burst duration. Use tau_w or tau_w_ms for duration instead
tau_w_old The sub-burst duration as defined and used in Chamma et al. (2021). Due to the choice of coordinates when performing fits, this form can be subject to larger uncertainties when the burst is near vertical
t_from_sigma The product of min_sigma and sin(theta). This is a (poor) measure of burst duration when finding fits with physical coordinates
sigma_t_ms 'sigma_t’ in ms. See sigma_t
tau_w_ms_old tau_w_old in milliseconds

Special thanks to Dr. Sofia Sheikh for contributions to this table.

Attributions

Meteor icon created by Freepik - Flaticon