B d?@sddlmZddlZddlmZmZmZddlm Z m Z ddl m Z ddlmZmZddlmZddlmZmZd gZeGd d d eZdS) )deepcopyN)groupsQTableTable)Time TimeDelta)units)Quantity UnitsError)deprecated_renamed_argument)BaseTimeSeriesautocheck_required_columns TimeSeriescseZdZdZdgZddddddfdd ZeddZed d d dddZ fddZ fddZ fddZ e dddZddZe d fdd ZZS)!ra A class to represent time series data in tabular form. `~astropy.timeseries.TimeSeries` provides a class for representing time series as a collection of values of different quantities measured at specific points in time (for time series with finite time bins, see the `~astropy.timeseries.BinnedTimeSeries` class). `~astropy.timeseries.TimeSeries` is a sub-class of `~astropy.table.QTable` and thus provides all the standard table maniplation methods available to tables, but it also provides additional conveniences for dealing with time series, such as a flexible initializer for setting up the times, a method for folding time series, and a ``time`` attribute for easy access to the time values. See also: https://docs.astropy.org/en/stable/timeseries/ Parameters ---------- data : numpy ndarray, dict, list, `~astropy.table.Table`, or table-like object, optional Data to initialize time series. This does not need to contain the times, which can be provided separately, but if it does contain the times they should be in a column called ``'time'`` to be automatically recognized. time : `~astropy.time.Time`, `~astropy.time.TimeDelta` or iterable The times at which the values are sampled - this can be either given directly as a `~astropy.time.Time` or `~astropy.time.TimeDelta` array or as any iterable that initializes the `~astropy.time.Time` class. If this is given, then the remaining time-related arguments should not be used. time_start : `~astropy.time.Time` or str The time of the first sample in the time series. This is an alternative to providing ``time`` and requires that ``time_delta`` is also provided. time_delta : `~astropy.time.TimeDelta` or `~astropy.units.Quantity` ['time'] The step size in time for the series. This can either be a scalar if the time series is evenly sampled, or an array of values if it is not. n_samples : int The number of time samples for the series. This is only used if both ``time_start`` and ``time_delta`` are provided and are scalar values. **kwargs : dict, optional Additional keyword arguments are passed to `~astropy.table.QTable`. timeN)r time_start time_delta n_samplesc s&tjfd|i||dkr@|dkr@|dkr@|dkr@d|_dS|dk rn|dk rf|t|krntdnt|}d|jkr|dkr|jd}ntd|dkr|dkrtdn|dk r|dk rtd|dk rt|tt fst|}|dk rt|tt fst|}|dk r(t|t t fs(tdt|t r@|j t j }|dk r|dkr\td |jrpt||}t|}t|d }d t j |d <||}nJt|jd krt|t|krtd t||n|dk rtd|,d|jkr|d|j|d ddWdQRXdS)NdataTzP'n_samples' has been given both and it is not the same length as the input data.rzA'time' has been given both in the table and as a keyword argumentz1Either 'time' or 'time_start' should be specifiedz+Cannot specify both 'time' and 'time_start'z0'time_delta' should be a Quantity or a TimeDeltaz-'time' is scalar, so 'time_delta' is requiredgrz3Length of 'time' ({}) should match data length ({})z='time_delta' should not be specified since 'time' is an array)indexname)super__init__Z_required_columns_relaxlen TypeErrorcolnamescolumns isinstancerrr secusZisscalarnprepeatZcumsumZroll ValueErrorformat_delay_required_column_checks remove_column add_column)selfrrrrrkwargs) __class__g/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/astropy/timeseries/sampled.pyr=sV              "    zTimeSeries.__init__cCs|dS)z" The time values. rr+)r(r+r+r,rszTimeSeries.timeZmidpoint_epoch epoch_timez4.0rFc Cst|tr|jjdkrtd|}|dkr:|jd}nt|}|t j }|rzt|trp|jjdkrptd||}n8|dkrd}n*t|tr|jjdkrtd|t j }|dkr|d }n|rt|tr|j t j std n$|dks|d krt d n||}nNt|trX|jjdkrX|dks@||krJt d n |t j }ntd|j|j||||||} t| t j } |r| |} d }}| |d|j| dddWdQRX|S)a Return a new `~astropy.timeseries.TimeSeries` folded with a period and epoch. Parameters ---------- period : `~astropy.units.Quantity` ['time'] The period to use for folding epoch_time : `~astropy.time.Time` The time to use as the reference epoch, at which the relative time offset / phase will be ``epoch_phase``. Defaults to the first time in the time series. epoch_phase : float or `~astropy.units.Quantity` ['dimensionless', 'time'] Phase of ``epoch_time``. If ``normalize_phase`` is `True`, this should be a dimensionless value, while if ``normalize_phase`` is ``False``, this should be a `~astropy.units.Quantity` with time units. Defaults to 0. wrap_phase : float or `~astropy.units.Quantity` ['dimensionless', 'time'] The value of the phase above which values are wrapped back by one period. If ``normalize_phase`` is `True`, this should be a dimensionless value, while if ``normalize_phase`` is ``False``, this should be a `~astropy.units.Quantity` with time units. Defaults to half the period, so that the resulting time series goes from ``-period / 2`` to ``period / 2`` (if ``normalize_phase`` is `False`) or -0.5 to 0.5 (if ``normalize_phase`` is `True`). normalize_phase : bool If `False` phase is returned as `~astropy.time.TimeDelta`, otherwise as a dimensionless `~astropy.units.Quantity`. Returns ------- folded_timeseries : `~astropy.timeseries.TimeSeries` The folded time series object with phase as the ``time`` column. rz,period should be a Quantity in units of timeNrZ dimensionlesszSepoch_phase should be a dimensionless Quantity or a float when normalize_phase=TruegzLepoch_phase should be a Quantity in units of time when normalize_phase=Falsezsz*TimeSeries.__getitem__..)metaZ copy_indices)indiceskeys) Z_is_list_or_tuple_of_strrrr7Z _copy_indicesrZ TableGroupsZ_indicesZ_keysZ_groupsr __getitem__)r(itemout)r*)r(r,r:s   zTimeSeries.__getitem__cs4tj||}t|jdkr0d|jkr0|d|S)z> See :meth:`~astropy.table.Table.add_column`. rr)rr'rr8r add_index)r(argsr)result)r*r+r,r's zTimeSeries.add_columncs4tj||}t|jdkr0d|jkr0|d|S)z? See :meth:`~astropy.table.Table.add_columns`. rr)r add_columnsrr8rr=)r(r>r)r?)r*r+r,r@ s zTimeSeries.add_columnsutccCsZddlm}m}t||s"tdt|j|s6tdt|j|d}t|}t ||dS)aj Convert a :class:`~pandas.DataFrame` to a :class:`astropy.timeseries.TimeSeries`. Parameters ---------- df : :class:`pandas.DataFrame` A pandas :class:`pandas.DataFrame` instance. time_scale : str The time scale to pass into `astropy.time.Time`. Defaults to ``UTC``. r) DataFrame DatetimeIndexz"Input should be a pandas DataFramez'DataFrame does not have a DatetimeIndex)scale)rr) ZpandasrBrCrrrrr from_pandasr)r(df time_scalerBrCrtabler+r+r,rEs   zTimeSeries.from_pandascCst|jddS)a" Convert this :class:`~astropy.timeseries.TimeSeries` to a :class:`~pandas.DataFrame` with a :class:`~pandas.DatetimeIndex` index. Returns ------- dataframe : :class:`pandas.DataFrame` A pandas :class:`pandas.DataFrame` instance r)r)r to_pandas)r(r+r+r,rI2s zTimeSeries.to_pandasc sytj|f|d|i|Stk r|dkr>> from astropy.timeseries import TimeSeries >>> ts = TimeSeries.read('sampled.dat', format='ascii.ecsv', ... time_column='date') # doctest: +SKIP Parameters ---------- filename : str File to parse. format : str File format specifier. time_column : str, optional The name of the time column. time_format : str, optional The time format for the time column. time_scale : str, optional The time scale for the time column. *args : tuple, optional Positional arguments passed through to the data reader. **kwargs : dict, optional Keyword arguments passed through to the data reader. Returns ------- out : `astropy.timeseries.sampled.TimeSeries` TimeSeries corresponding to file contents. Notes ----- r$NzR``time_column`` should be provided since the default Table readers are being used.)rDr$z Time column 'z' not found in the input data.)rr) rreadrr#rrrrr&r) r(filenameZ time_column time_formatrGr$r>r)rHr)r*r+r,rJ>s-  zTimeSeries.read)N)NNrNF)rA)NNNN)__name__ __module__ __qualname____doc__Z_required_columnsrpropertyrr r3r:r'r@ classmethodrErIrJ __classcell__r+r+)r*r,rs (K   e   )r0rnumpyr!Z astropy.tablerrrZ astropy.timerrZastropyrrZ astropy.unitsr r Zastropy.utils.decoratorsr Zastropy.timeseries.corer r __all__rr+r+r+r,s