a ߙfb%@sxddlZddlZddlmZddlmZmZddl m Z ddl m Z ddl mZdgZdd Zdddddd d dZdS) N)units)Time TimeDelta)AstropyUserWarning) TimeSeries)BinnedTimeSeriesaggregate_downsamplec Cst|dkrtgSt|dr2t|||Sg}tt|dD]V}||d||dkrz|||||qF|||||||dqF||||ddt|SdS)z Manual reduceat functionality for cases where Numpy functions don't have a reduceat. It will check if the input function has a reduceat and call that if it does. rreduceatN)lennparrayhasattrr rangeappend)rindicesZfunctionresultir|durt|j st|} |jdd}| |d<|dd|d d<|dur|j s|j st |d d|ddkrtd tt||||d } |durt j}| j} | j} |dus|j st| }|j| dk|j| dk@} t|d D]8}t t |j| |k|j| |d k}d | |<q(|| }t | |j| }t|rt | d d| ddkrt |j| | |jdk}t t|||<t|rt !dt "t #|dd g}n t $g}t %|}|j&D]}|d kr.q||}t|t j'tjfsZtdtqt|tjrtjt (t j)||j*d}tjt+|j,|||j*d d||<n2t j-j.||j/d}d |_0t+|||||<d|j0|<|| |<q| S)aZ Downsample a time series by binning values into bins with a fixed size or custom sizes, using a single function to combine the values in the bin. Parameters ---------- time_series : :class:`~astropy.timeseries.TimeSeries` The time series to downsample. time_bin_size : `~astropy.units.Quantity` or `~astropy.time.TimeDelta` ['time'], optional The time interval for the binned time series - this is either a scalar value (in which case all time bins will be assumed to have the same duration) or as an array of values (in which case each time bin can have a different duration). If this argument is provided, ``time_bin_end`` should not be provided. time_bin_start : `~astropy.time.Time` or iterable, optional The start time for the binned time series - this can be either given directly as a `~astropy.time.Time` array or as any iterable that initializes the `~astropy.time.Time` class. This can also be a scalar value if ``time_bin_size`` or ``time_bin_end`` is provided. Defaults to the first time in the sampled time series. time_bin_end : `~astropy.time.Time` or iterable, optional The times of the end of each bin - this can be either given directly as a `~astropy.time.Time` array or as any iterable that initializes the `~astropy.time.Time` class. This can only be given if ``time_bin_start`` is provided or its default is used. If ``time_bin_end`` is scalar and ``time_bin_start`` is an array, time bins are assumed to be contiguous; the end of each bin is the start of the next one, and ``time_bin_end`` gives the end time for the last bin. If ``time_bin_end`` is an array and ``time_bin_start`` is scalar, bins will be contiguous. If both ``time_bin_end`` and ``time_bin_start`` are arrays, bins do not need to be contiguous. If this argument is provided, ``time_bin_size`` should not be provided. n_bins : int, optional The number of bins to use. Defaults to the number needed to fit all the original points. If both ``time_bin_start`` and ``time_bin_size`` are provided and are scalar values, this determines the total bins within that interval. If ``time_bin_start`` is an iterable, this parameter will be ignored. aggregate_func : callable, optional The function to use for combining points in the same bin. Defaults to np.nanmean. Returns ------- binned_time_series : :class:`~astropy.timeseries.BinnedTimeSeries` The downsampled time series. z"time_series should be a TimeSeriesNz3'time_bin_size' should be a Quantity or a TimeDeltarr z_With single 'time_bin_start' either 'n_bins', 'time_bin_size' or time_bin_end' must be providedT)copyr zaOverlapping bins should be avoided since they can lead to double-counting of data during binning.)rrrrFtimez.Skipping column {0} since it has a mix-in type)unit)dtype)1 isinstancer TypeErroruZQuantityrrZilocrZisscalarZsecsr ZmaximumZto_valueintZceilZ replicateanywarningswarnrrZnanmeanrrr rwhereZ logical_andZ searchsortedallZarangeZhstackZnonzeroZdiffruniqueZcolnamesZndarrayrepeatnanrr valueZmaZzerosrmask)Z time_seriesrrrrrZ ts_sortedZ time_durationZ bin_size_secZscalar_start_timeZbinnedZ bin_startZbin_endZkeepZindZdelete_indicesZsubsetrZ indices_startgroupsZunique_indicesZcolnamevaluesdatarrrr$s1           * $        )r&Znumpyr Zastropyrr"Z astropy.timerrZastropy.utils.exceptionsrZastropy.timeseries.sampledrZastropy.timeseries.binnedr__all__r rrrrrs