labels_4.py

def apply_pt_sl_on_t1(close, events, pt_sl, molecule):
    """
    :param close: (series) close prices
    :param events: (series) of indices that signify "events" 
    :param pt_sl: (array) element 0, indicates the profit taking level; 
                          element 1 is stop loss level
    :param molecule: (an array) a set of datetime index values for processing
    :return: (dataframe) timestamps at which each barrier was touched
    """
    # apply stop loss/profit taking, if it takes place before t1 (end of event)
    events_ = events.loc[molecule]
    out = events_[['t1']].copy(deep=True)
    if pt_sl[0] > 0:
        pt = pt_sl[0] * events_['trgt']
    else:
        pt = pd.Series(index=events.index)  # NaNs

    if pt_sl[1] > 0:
        sl = -pt_sl[1] * events_['trgt']
    else:
        sl = pd.Series(index=events.index)  # NaNs

    for loc, t1 in events_['t1'].fillna(close.index[-1]).iteritems():
        df0 = close[loc:t1]  # path prices
        df0 = (df0 / close[loc] - 1) * events_.at[loc, 'side']  # path returns
        out.loc[loc, 'sl'] = df0[df0 < sl[loc]].index.min()  # earliest stop loss
        out.loc[loc, 'pt'] = df0[df0 > pt[loc]].index.min()  # earliest profit taking

    return out