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我正在尝试使用 cuDF row_apply 根据其他行计算新列。

对于单行，它适用于以下脚本 filteredhlcdf.loc[(filteredhlcdf.ddate == %%Ddate%%) & (filteredhlcdf.sstart == %%sTime%%) & (filteredhlcdf.ttime <= %%etime%%) & (filteredhlcdf.H > %%ustep%%) , "ttime" ].min() ，其中 %% 之间的变量被常量替换。

但是，当我尝试按如下方式使用行应用时，会产生错误

crossappliedcdf = cudf.from_pandas(crossapplieddf)
filteredhlcdf = cudf.from_pandas(filteredhldf)

def rowcal(ddate: int, stime: int, etime: int, usteps: float, dsteps: float, ctime: int, creturn: float):
#def rowcal(ddate: float, stime: float, etime: float, usteps: float, dsteps: float, ctime: int, creturn: float, kwarg1: int):

    for i, (tddate, tstime, tetime, tusteps, tdsteps) in enumerate(zip(ddate, stime, etime, usteps, dsteps)):
        
        ctime[i] = filteredhlcdf.loc[(filteredhlcdf.ddate == tddate) & (filteredhlcdf.sstart == tstime) & (filteredhlcdf.ttime <= tetime) & (filteredhlcdf.H > tusteps) , "ttime" ].min()
        creturn[i] =  tddate +  tstime + tetime+ tdsteps

crossappliedcdf.apply_rows(rowcal, incols=['ddate', 'stime', 'etime','usteps','dsteps'], outcols=dict(ctime=np.int32, creturn=float), kwargs={})

我确定错误发生在以下行

ctime[i] = filteredhlcdf.loc[(filteredhlcdf.ddate == tddate) & (filteredhlcdf.sstart == tstime) & (filteredhlcdf.ttime <= tetime) & (filteredhlcdf.H > tusteps) , "ttime" ].min()

因为错误在被替换后消失了ctime[i] = tddate + tstime + tetime+ tdsteps

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