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
