TauP

class of dascore.transform.taup
inherits from: PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

TauP(
*args ,
velocities: Any ,
)-> None

Compute linear tau-p transform.

The patch must have time and distance dimensions.

Parameters

Parameter	Description
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')
    .sort_coords('slowness')
)
ax = taup_patch.viz.waterfall(show=False, cbar=False)
_ = taup_patch.viz.waterfall(ax=ax)

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
get_metadata	Return the tau-p metadata, and the gather’s axes, spacing and slownesses.
model_copy	Copy the model, dropping cached values the update invalidates.
new	Create new instance with some attributed updated.
numpy_kernel	Return the transform of the gather, distance first.
tau_p	Compute linear tau-p transform.
reconcile	Return metadata or a patch holding the final data; default as is.
run	Run the operation: check, get_metadata, kernel, reconcile, record.