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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def first_return_times(dts, c=None, d=0.0):
 """For an ensemble of time series, return the set of all time intervals between successive returns to value c for all instances in the ensemble. If c is not given, the default is the mean across all times and across all time series in the ensemble. Args: dts (DistTimeseries) c (float):
 Optional target value (default is the ensemble mean value) d (float):
 Optional min distance from c to be attained between returns Returns: array of time intervals (Can take the mean of these to estimate the expected first return time for the whole ensemble) """

    if c is None:
        c = dts.mean()
    vmrt = distob.vectorize(analyses1.first_return_times)
    all_intervals = vmrt(dts, c, d)
    if hasattr(type(all_intervals), '__array_interface__'):
        return np.ravel(all_intervals)
    else:
        return np.hstack([distob.gather(ilist) for ilist in all_intervals])