Bins a lightcurve in equally-spaced bins in time.
If the original light curve contains flux uncertainties (flux_err),
the binned lightcurve will report the root-mean-square error.
If no uncertainties are included, the binned curve will return the
standard deviation of the data.
The time interval for the binned time series.
(Default: 0.5 days; default unit: days.)
The start time for the binned time series. Defaults to the first
time in the sampled time series.
The number of bins to use. Defaults to the number needed to fit all
the original points. Note that this will create this number of bins
of length time_bin_size independent of the lightkurve length.
The function to use for combining points in the same bin. Defaults
The number of bins to divide the lightkurve into. In contrast to
n_bins this sets the length of time_bin_size accordingly.
In Lightkurve v1.x, the default behavior of bin() was to create
bins which contained an equal number data points in each bin.
This type of binning is discouraged because it usually makes more sense to
create equally-sized bins in time duration, which is the new default
behavior in Lightkurve v2.x. Nevertheless, this binsize parameter
allows users to simulate the old behavior of Lightkurve v1.x.
For ease of implementation, setting this parameter is identical to passing
time_bin_size = lc.time[binsize] - time, which means that
the bins are not guaranteed to contain an identical number of
time_bin_size = lc.time[binsize] - time
A new light curve which has been binned.