burstfit.data

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BurstData Objects

class BurstData(Candidate)

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Class to handle burst data

Arguments:

• fp Union[str, list] - String or a list of files. It can either filterbank or psrfits files.
• dm float - Dispersion Measure of the candidate
• tcand float - start time of the candidate in seconds at the highest frequency channel
• width int - pulse width of the candidate in samples
• snr float - Signal to Noise Ratio
• min_samp int - Minimum number of time samples
• kill_mask numpy.ndarray - Boolean mask of channels to kill
• spectral_kurtosis_sigma float - Sigma for spectral kurtosis filter
• savgol_frequency_window float - Filter window for savgol filter
• savgol_sigma float - Sigma for savgol filter
• flag_rfi bool - To turn on RFI flagging

prepare_data

 | def prepare_data(mask_chans=[], time_window=200e-3, normalise=True)

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Prepares data for burst fitting

Arguments:

• mask_chans - list with tuples (start_freq, end_freq) and channel numbers to mask
• time_window - time window (s) around the burst to use for burst fitting
• normalise - To normalise the mean and std of the data using an off pulse region

Returns:

nstart

 | @property
 | def nstart()

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Returns: start sample number of the spectrogram

mask

 | @property
 | def mask()

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Returns: Channel mask array using all the available masks

prepare_input_mask

 | def prepare_input_mask(mask_chans=[])

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Function to mask some frequency channels using input_mask, kill_mask and rfi_mask

Arguments:

• mask_chans - list with tuples (start_freq, end_freq) and channel numbers to mask

Returns:

mask_channels

 | def mask_channels()

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Apply channel mask to the dedispersed data

Returns:

normalise_data

 | def normalise_data(on_pulse_data, off_pulse_data, return_clip_fac=True)

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Function to normalise data

Arguments:

• on_pulse_data - Data to normalise
• off_pulse_data - Data to use to estimate mean and std
• return_clip_fac - To return the clipping factor, decided using nbits of data

Returns:

crop_dedispersed_data

 | def crop_dedispersed_data(time_window)

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To get a cutout of data from only around the burst

Arguments:

• time_window - time length to use on both sides of burst for the cutout

Returns: