obspy.taup.tau_model.TauModel
- class TauModel(s_mod, radius_of_planet, is_spherical=True, cache=None, debug=False, skip_calc=False)[source]
Bases:
object
Provides storage of all the TauBranches comprising a model.
Public Methods
Calculates tau for each branch within a slowness model. |
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Called in TauPTime. |
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Deserialize model from numpy npz binary file. |
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Finds the branch that either has the depth as its top boundary, or strictly contains the depth. |
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Return an array of the depths that are boundaries between branches. |
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Serialize model to numpy npz binary file. |
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Returns a new TauModel with the branches containing depth split at depth. |
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Private Methods
Warning
Private methods are mainly for internal/developer use and their API might change without notice.
Special Methods
- TauModel.__delattr__(name, /)
Implement delattr(self, name).
- TauModel.__dir__()
Default dir() implementation.
- TauModel.__eq__(value, /)
Return self==value.
- TauModel.__format__(format_spec, /)
Default object formatter.
- TauModel.__ge__(value, /)
Return self>=value.
- TauModel.__getattribute__(name, /)
Return getattr(self, name).
- TauModel.__gt__(value, /)
Return self>value.
- TauModel.__hash__()
Return hash(self).
- TauModel.__init__(s_mod, radius_of_planet, is_spherical=True, cache=None, debug=False, skip_calc=False)[source]
- TauModel.__init_subclass__()
This method is called when a class is subclassed.
The default implementation does nothing. It may be overridden to extend subclasses.
- TauModel.__le__(value, /)
Return self<=value.
- TauModel.__lt__(value, /)
Return self<value.
- TauModel.__ne__(value, /)
Return self!=value.
- TauModel.__new__(**kwargs)
- TauModel.__reduce__()
Helper for pickle.
- TauModel.__reduce_ex__(protocol, /)
Helper for pickle.
- TauModel.__repr__()
Return repr(self).
- TauModel.__setattr__(name, value, /)
Implement setattr(self, name, value).
- TauModel.__sizeof__()
Size of object in memory, in bytes.
- TauModel.__subclasshook__()
Abstract classes can override this to customize issubclass().
This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).