rtm.stack module

rtm.stack.calculate_semblance(data_in)[source]

Calculates the semblance, a measure of multi-channel coherence, following the definition of Neidell & Taner (1971). Assumes data are already time-shifted to construct the beam.

Parameters:

data_in – Time-shifted Stream or time-shifted numpy.ndarray

Returns:

Multi-channel coherence, defined on \([0, 1]\)

Return type:

numpy.ndarray

rtm.stack.get_peak_coordinates(S, global_max=True, height=None, min_time=None, prominence=None, unproject=False)[source]

Find the values of the coordinates corresponding to the maxima (peaks) in a stack function \(S\). Function will return all peaks above the height and separated by greater than min_time in the stack function. Returns just global max if there are less than three time segments. Optionally “unprojects” UTM coordinates to (latitude, longitude) for projected grids.

Parameters:

  • S (DataArray) – The stack function \(S\)

  • global_max (bool) – Only return values for the max of the stack function (default: True)

  • height (int or float) – Minimum threshold for the value of a detection (peak) in \(S\) (default: None). Only used if global_max=False.

  • min_time (int or float) – Minimum time (distance) between peaks in \(S\) [s] (default: None). Only used if global_max=False.

  • prominence (int or float) – Minimum peak prominence. Represents the vertical distance between the peak and its lowest contour line. Only used if global_max=False.

  • unproject (bool) – If True and if S is a projected grid, unprojects the UTM coordinates to (latitude, longitude) (default: False)

Returns:

Tuple containing:

  • time_max (UTCDateTime) – Time(s) corresponding to peak(s) in \(S\)

  • y_max – [deg lat. or m N] \(y\)-coordinate(s) corresponding to peak(s) in \(S\)

  • x_max – [deg lon. or m E] \(x\)-coordinate(s) corresponding to peak(s) in \(S\)

  • peaks (numpy.ndarray) – Peak indices

  • props – Dictionary containing peak properties

Return type:

tuple