tau_p

function of dascore.transform.taup source

tau_p(
    patch: Patch ,
    velocities: numpy.ndarray[tuple[Any, …], numpy.dtype[floating]] ,
)-> ‘PatchType’

Compute linear tau-p transform.

Parameters

Parameter Description
patch Patch to transform. Has to have dimensions of time and distance.
velocities NumPY array of velocities, in m/s if units are not attached,
for which to compute slowness (p).
Note

  • Output will always be double the size of vels, with negative velocities (right-to-left) first, followed by positive velocities (left-to-right).

  • Uses linear interpolation in time

Example

import dascore as dc
import numpy as np

patch = (
   dc.get_example_patch('example_event_1')
)
taup_patch = (
    patch.taper(time=0.1)
    .pass_filter(time=(..., 300))
    .tau_p(np.arange(1000,6000,10))
    .transpose('time','slowness')
)
ax = taup_patch.viz.waterfall(show=False, cmap=None)
_ = taup_patch.viz.waterfall(ax=ax)