pulse

class time_domain_astronomy_sandbox.pulse.Pulse(backend: time_domain_astronomy_sandbox.backend.Backend = <time_domain_astronomy_sandbox.backend.Backend object>, width: int = 10)

delays(dm)

Create array of delays for each backend frequency channel.

Parameters:dm (int) -- Value for dispersion measure of the pulse Returns:delays -- Array of delays (in second) Return type:Numpy.array

plot_delay_v_frequency(dm, xscale='linear', savefig=False, ext='png')

Plot pulse's delay vs frequency.

Parameters:

• dm (int) -- Value for dispersion measure of the pulse
• xscale (str) -- matplotlib's xscale option (default: 'linear')
• savefig (bool) -- save figure to disk (default: False)
• ext ('str') -- figure's file extention (default: png)

plot_delay_v_frequency_interactive(xscale='linear', dm_min=0, dm_max=5000, dm_step=5, dm_init=0, savefig=False, ext='png')

Plot pulse's delay vs frequency interactively with ipywidgets.

Parameters:

• xscale (str) -- matplotlib's xscale option
• dm_min (int) -- minimum dm for interactive widget (default: 0)
• dm_max (int) -- maximum dm for interactive widget (default: 5000)
• dm_step (int) -- increment step dm for interactive widget (default: 0)
• dm_init (int) -- initial dm for interactive widget (default: 5000)
• savefig (bool) -- save figure to disk (default: False)
• ext ('str') -- figure's file extention

plot_signal_dispersed_dedispersed(dm, step=200, xscale='linear', savefig=False, ext='png', dpi=150)

Plot pulse's delay vs frequency.

Parameters:

• dm (int) -- Value for dispersion measure of the pulse
• xscale (str) -- matplotlib's xscale option (default: 'linear')
• savefig (bool) -- save figure to disk (default: False)
• ext ('str') -- figure's file extention (default: png)