# obspy.core.trace.Stats

class `Stats`(header={})

  Bases: `obspy.core.util.attribdict.AttribDict`

  A container for additional header information of a ObsPy Trace object.

  A `Stats` object may contain all header information (also known as meta data) of a `Trace` object. Those headers may be accessed or modified either in the dictionary style or directly via a corresponding attribute. There are various default attributes which are required by every waveform import and export modules within ObsPy such as `obspy.io.mseed`.

  Parameters: | header (dict or `Stats`, optional) Dictionary containing meta information of a single `Trace` object. Possible keywords are summarized in the following Default Attributes section.

  Basic Usage

      >>> stats = Stats()
      >>> stats.network = 'BW'
      >>> print(stats['network'])
      BW
      >>> stats['station'] = 'MANZ'
      >>> print(stats.station)
      MANZ

  Default Attributes

  `sampling_rate` : float, optional
    Sampling rate in hertz (default value is 1.0).
  `delta` : float, optional
    Sample distance in seconds (default value is 1.0).
  `calib` : float, optional
    Calibration factor (default value is 1.0).
  `npts` : int, optional
    Number of sample points (default value is 0, which implies that no data is present).
  `network` : string, optional
    Network code (default is an empty string).
  `location` : string, optional
    Location code (default is an empty string).
  `station` : string, optional
    Station code (default is an empty string).
  `channel` : string, optional
    Channel code (default is an empty string).
  `starttime` : `UTCDateTime`, optional
    Date and time of the first data sample given in UTC (default value is “1970-01-01T00:00:00.0Z”).
  `endtime` : `UTCDateTime`, optional
    Date and time of the last data sample given in UTC (default value is “1970-01-01T00:00:00.0Z”).

  Notes

  1. The attributes `sampling_rate` and `delta` are linked to each other. If one of the attributes is modified the other will be recalculated.

         >>> stats = Stats()
         >>> stats.sampling_rate
         1.0
         >>> stats.delta = 0.005
         >>> stats.sampling_rate
         200.0

  2. The attributes `starttime`, `npts`, `sampling_rate` and `delta` are monitored and used to automatically calculate the `endtime`.

         >>> stats = Stats()
         >>> stats.npts = 60
         >>> stats.delta = 1.0
         >>> stats.starttime = UTCDateTime(2009, 1, 1, 12, 0, 0)
         >>> stats.endtime
         UTCDateTime(2009, 1, 1, 12, 0, 59)
         >>> stats.delta = 0.5
         >>> stats.endtime
         UTCDateTime(2009, 1, 1, 12, 0, 29, 500000)

  3. The attribute `endtime` is read only and can not be modified.

         >>> stats = Stats()
         >>> stats.endtime = UTCDateTime(2009, 1, 1, 12, 0, 0)
         Traceback (most recent call last):
         ...
         AttributeError: Attribute "endtime" in Stats object is read only!
         >>> stats['endtime'] = UTCDateTime(2009, 1, 1, 12, 0, 0)
         Traceback (most recent call last):
         ...
         AttributeError: Attribute "endtime" in Stats object is read only!

  4. The attribute `npts` will be automatically updated from the `Trace` object.

         >>> trace = Trace()
         >>> trace.stats.npts
         0
         >>> trace.data = np.array([1, 2, 3, 4])
         >>> trace.stats.npts
         4

  Attributes

  `__abstractmethods__` | frozenset() -> empty frozenset object
  `__dict__` |
  `__doc__` | str(object=’‘) -> str
  `__hash__` |
  `__module__` | str(object=’‘) -> str
  `__slots__` | tuple() -> empty tuple
  `__weakref__` | list of weak references to the object (if defined)
  `defaults` | dict() -> new empty dictionary
  `do_not_warn_on` | list() -> new empty list
  `readonly` | list() -> new empty list
  `warn_on_non_default_key` | bool(x) -> bool

  Public Methods

  `clear` |
  `copy` |
  `get` |
  `items` |
  `keys` |
  `pop` | If key is not found, d is returned if given, otherwise KeyError is raised.
  `popitem` | as a 2-tuple; but raise KeyError if D is empty.
  `setdefault` |
  `update` |
  `values` |

  Private Methods

  Warning

  Private methods are mainly for internal/developer use and their API might change without notice.

  `_pretty_str` | Return better readable string representation of AttribDict object.
  `_repr_pretty_` |

  Special Methods

  `__contains__` |
  `__deepcopy__` |
  `__delattr__` |
  `__delitem__` |
  `__dir__` | default dir() implementation
  `__eq__` |
  `__format__` | default object formatter
  `__getattr__` | Py3k hasattr() expects an AttributeError no KeyError to be
  `__getitem__` |
  `__getstate__` |
  `__init__` |
  `__iter__` |
  `__len__` |
  `__new__` | Create and return a new object.
  `__reduce__` | helper for pickle
  `__reduce_ex__` | helper for pickle
  `__repr__` |
  `__setattr__` |
  `__setitem__` |
  `__setstate__` |
  `__sizeof__` | size of object in memory, in bytes
  `__str__` | Return better readable string representation of Stats object.
  `__subclasshook__` |

### Thank you!

We would like to thank our contributors, whose efforts make this software what it is. These people have helped by writing code and documentation, and by testing. They have created and maintained this product, its associated libraries and applications, our build tools and our web sites.

#### Contributors

- Ackerley, Nick
- Allgeyer, Sebastien
- Ammon, Charles J.
- Antunes, Emanuel
- Arnarsson, Ólafur St.
- Bank, Markus
- Barsch, Robert
- Behr, Yannik
- Bernardi, Fabrizio
- Bernauer, Felix
- Bes de Berc, Maxime
- Beyreuther, Moritz
- Boltz, Shawn
- Bonaimé, Sébastien
- Carothers, Lloyd
- Chamberlain, Calum
- Chambers, Derrick
- Chen, Zhao
- Clark, Adam
- Danecek, Peter
- Egdorf, Sven
- Engels, Fabian
- Ermert, Laura
- Eulenfeld, Tom

- Fabbri, Tommaso
- Falco, Nicholas
- Fee, Jeremy
- Grellier, Clément
- Grunberg, Marc
- Hammer, Conny
- Heimann, Sebastian
- Heiniger, Lukas
- Hope, Gaute
- Igel, Heiner
- Inza, Adolfo
- Isken, Marius
- Ketchum, David
- Koymans, Mathijs
- Kremers, Simon
- Kress, Victor
- Krieger, Lars
- Krischer, Lion
- Kula, Damian
- Käufl, Paul
- Köhler, Andreas
- Lecocq, Thomas
- Leeman, John
- Legovini, Paride

- Lesage, Philippe
- Li, Yulin
- Lomax, Anthony
- Lopes, Rui L.
- MacCarthy, Jonathan
- Maggi, Alessia
- Martin, Henri
- Medlin, Andrew
- Megies, Tobias
- Meschede, Matthias
- Michelini, Alberto
- Miller, Nathaniel C.
- Morgenstern, Bernhard
- Nof, Ran Novitsky
- Panning, Mark P.
- Parker, Tom
- Pestourie, Romain
- Rapagnani, Giovanni
- Reyes, Celso
- Ringler, Adam
- Rothenhäusler, Nicolas
- Russo, Emiliano
- Sales de Andrade, Elliott

- Satriano, Claudio
- Saul, Joachim
- Scheingraber, Chris
- Schneider, Simon
- Sippl, Christian
- Snoke, Arthur
- Stange, Stefan
- Stähler, Simon C.
- Sullivan, Benjamin
- Tian, Dongdong
- Trabant, Chad
- Trani, Luca
- Uieda, Leonardo
- Walker, Andrew
- Walther, Marcus
- Wassermann, Joachim
- Williams, Mark C.
- Winkelman, Andrew
- Zaccarelli, Riccardo
- Zad, Seyed Kasra Hosseini
- Zhu, Lijun
- van Driel, Martin
- van Wijk, Kasper

#### Funds

ObsPy was partially funded by the

- German Science Foundation (DFG) via grant DFG IG 16/9-1
- German Ministry for Education and Research (BMBF), GEOTECHNOLOGIEN grant 03G0646H.
- NERA project (Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation) under the European Community's Seventh Framework Programme (FP7/2007-2013) grant agreement n° 262330
- Leibniz Institute for Applied Geophysics (LIAG)
- VERCE EU-FP7 project (no. 283543)