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)