Shot

class pysit.core.Shot(sources, receivers)[source]

Bases: object

Container class for a seismic shot.

The Shot class provides a logical grouping of seismic sources with receivers. This class may be refactored so that it is a base class for subclasses like SuperShot, SyntheticShot, SegyShot, ProductionShot, etc.

Attributes:
sources : subclass of SourceBase

Source or set of source objects.

receivers : subclass of ReceiverBase

Receiver or set of receiver objects.

Methods Summary

compute_data_dft(self, frequencies[, …]) Precompute the DFT of the data at the given list of frequencies.
gather(self[, as_array, offset]) Collect a sub list of receivers or an array of the data from those receivers.
initialize(self, data_length) Clear the data from each receiver in the list of receivers.
reset_time_series(self, ts)
serialize_dict(self)
unserialize_dict(self, d)

Methods Documentation

compute_data_dft(self, frequencies, force_computation=False)[source]

Precompute the DFT of the data at the given list of frequencies.

Parameters:
frequencies : float, iterable

The frequency or frequencies for which to compute the DFT.

force_computation : bool {optional}

Force computation of DFT. By default already computed frequencies are not recomputed.

gather(self, as_array=False, offset=None)[source]

Collect a sub list of receivers or an array of the data from those receivers.

Parameters:
as_array : bool, optional

Return the data from the selected receivers as an array, rather than returning a list of selected receivers.

offset : float or int, optional

Not implemented. Will eventually allow an offset to be passed so that reduced sized gathers can be collected.

Returns:
sublist : list of SeismicReceiver

If as_array is False, list of references to the selected receivers.

A : numpy.ndarray

If as_array is True, an array of the data from the selected receivers.

initialize(self, data_length)[source]

Clear the data from each receiver in the list of receivers.

Parameters:
data_length : int

Length of the desired data array.

reset_time_series(self, ts)[source]
serialize_dict(self)[source]
unserialize_dict(self, d)[source]