def selectdfrunlist(dfr, runlist, runvar): """ Select smaller runlist on dataframe """ if runlist is not None: isgoodrun = select_runs(runlist, dfr[runvar].values) dfr = dfr[np.array(isgoodrun, dtype=bool)] return dfr
def selectdfrunlist(dfr, runlist, runvar): """ Select smaller runlist on dataframe """ if runlist is not None: runlist_np = np.asarray(runlist) array_run_np = np.asarray(dfr[runvar].values) issel = select_runs(runlist_np, array_run_np) dfr = dfr[issel] return dfr
def skimmer(filein, filevt, fileout, skimming_sel, var_evt_match, param_case, presel_reco, sel_cent, skimming2_dotrackpid, runlist): df = pickle.load(open(filein, "rb")) dfevt = pickle.load(open(filevt, "rb")) if "Evt" not in filein: df = pd.merge(df, dfevt, on=var_evt_match) if skimming_sel is not None: df = df.query(skimming_sel) if runlist is not None: array_run = df.run_number.values isgoodrun = select_runs(runlist, array_run) df = df[np.array(isgoodrun, dtype=bool)] if "Reco" in filein: if skimming2_dotrackpid is True: df = filter_df_cand(df, param_case, 'presel_track_pid') if presel_reco is not None: df = df.query(presel_reco) array_pt = df.pt_cand.values array_y = df.y_cand.values isselacc = selectfidacc(array_pt, array_y) df = df[np.array(isselacc, dtype=bool)] if sel_cent is not None: df = df.query(sel_cent) df.to_pickle(fileout)
def selectdfrunlist(dfr, runlist, runvar): if runlist is not None: isgoodrun = select_runs(runlist, dfr[runvar].values) dfr = dfr[np.array(isgoodrun, dtype=bool)] return dfr