Writer

your.writer.Writer(
    your_object,
    nstart=0,
    nsamp=None,
    c_min=None,
    c_max=None,
    npoln=1,
    outdir=None,
    outname=None,
    flag_rfi=False,
    progress=True,
    spectral_kurtosis_sigma=4,
    savgol_frequency_window=15,
    savgol_sigma=4,
    gulp=None,
    zero_dm_subt=False,
    time_decimation_factor=1,
    frequency_decimation_factor=1,
    replacement_policy="mean",
)

The unified writer class.

Args:

your_object: Your object
nstart (int): Start sample to read from
nsamp (int): Number of samples to write
c_min (int): Starting channel index (default: 0)
c_max (int): End channel index (default: total number of frequencies)
npoln (int): Number of output polarisations (default: 1)
outdir (str): Output directory for file
outname (str): Name of the file to write to (without the file extension)
progress (bool): Set to it to false to disable progress bars
flag_rfi (bool): To turn on RFI flagging
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
gulp (int): Gulp size for the data
zero_dm_subt (bool): Enable zero DM rfi excision
time_decimation_factor (int): Time Decimation Factor (in number of samples)
frequency_decimation_factor (int): Frequency Decimation Factor (in number of samples)
replacement_policy (str): Replace flagged values with mean, median or zeros.

[source]

to_fil

Writer.to_fil(data=None)

Writes out a Filterbank File.

Args: data (np.ndarray): Write out your custom data from a numpy array. If not specified it will read the input file and write with the attributes setup in the writer class.

[source]

to_fits

Writer.to_fits(npsub=-1)

Writes out a PSRFITS file

Args:

npsub (int): number of spectra per subint

[source]

get_data_to_write

Writer.get_data_to_write(start_sample, nsamp)

Read data to self.data, selects channels Optionally perform RFI filtering and zero-DM subtraction

Args:

start_sample (int): Start sample number to read from
nsamp (int): Number of samples to read

[source]

dada_header

Writer.dada_header()

Create the psrdada header dictionary

Returns:

dict: psrdada header dictionary

[source]

setup_dada

Writer.setup_dada(dada_key=None, data_step=None)

Set up the psrdada buffers.

Args:

dada_key (hex): hex key, if left None, key would be chosen randomly
data_step (int): size of each page in the ring buffer in bytes

[source]

to_dada

Writer.to_dada()

Start the process of dumping data to the dada buffers till the EOF.