def appendIdxs(df, pair_idx, seed="Seed"):
detID = "rawID" + seed + "SC" + pair_idx
ecal = ecalic.icCMS().iov
print(df)
ecal = ecal.reset_index().set_index(["cmsswId"])
print(ecal)
print(df.set_index([detID]).index)
df["iTT" + seed + "SC" + pair_idx] = df.set_index([detID
]).index.map(ecal.ccu)
df["iX" + seed + "SC" + pair_idx] = df.set_index([detID
]).index.map(ecal["ix"])
df["iY" + seed + "SC" + pair_idx] = df.set_index([detID
]).index.map(ecal.iy)
FED = df.set_index([detID]).index.map(ecal.FED)
isEB = (FED > 609) & (FED < 646)
##positiveZ()
##https://github.com/cms-sw/cmssw/blob/master/DataFormats/EcalDetId/interface/EBDetId.h#L76
##https://github.com/cms-sw/cmssw/blob/master/DataFormats/EcalDetId/interface/EEDetId.h#L174
positiveZ = np.where(isEB, df[detID].values & 0x10000,
df[detID].values & 0x4000).astype("int")
df["sc" + seed + "SC" + pair_idx] = np.where(
isEB,
getSM(df["iX" + seed + "SC" + pair_idx], positiveZ),
getSC(df["iX" + seed + "SC" + pair_idx],
df["iY" + seed + "SC" + pair_idx], isEB),
) # SM for EB, SC for EE
# df["VFE"+seed+"SC"+pair_idx] = np.where(isEB, VFE_EB(df[ieta]), np.nan)
# df["TRT"+seed+"SC"+pair_idx] = np.where(isEB, TRT(df["iTT"+seed+"SC"+pair_idx], isEB), np.nan)
df = df.drop(
columns=["iX" + seed + "SC" + pair_idx, "iY" + seed + "SC" + pair_idx])
return df
parser = argparse.ArgumentParser(description='Command line parser of plotting options')
parser.add_argument('--fed', dest='fed', type=int, help='fed', default=None)
parser.add_argument('--isgreen', dest='isgreen', help='green laser', default=False, action ='store_true')
parser.add_argument('--grid', dest='grid', help='draw TT grid', default=False, action ='store_true')
args = parser.parse_args()
fed = 610
if args.fed: fed = args.fed
filename_blue = "fits_results/temperature/FEDX_ch_split_rootfit.csv"
filename_green = "fits_results/temperature/FEDX_ch_split_rootfit_green.csv"
ecal = ecalic.icCMS().iov
if fed: ecal = ecal[ecal['FED']== fed]
ecal = ecal.reset_index().set_index(["elecID", "FED"])
df_blue = read_fit(filename_blue, fed, ecal).reset_index().set_index(["ieta","iphi","TT","side","ch", "FED"])
df_green = read_fit(filename_green, fed, ecal).reset_index().set_index(["ieta","iphi","TT", "side","ch", "FED"])
print(df_blue)
df = pd.concat([df_blue, df_green], axis = 1, keys = ["blue","green"])
print(df)
df = df.reset_index().set_index(["ch", "FED"])
TCDSs = ["TCDS2", "TCDS3", "TCDS4"]
TCDSmean = [40.078887, 40.078963, 40.078974]
x = np.asarray(df['iphi'].tolist(), dtype = np.float64)