import numpy as np
import copy
import os
import time
from sys import getsizeof
from itertools import chain

I dati sono dei CSV, ma per finta: le righe non hanno lo stesso numero di colonne. Bisogna immaginarli come una sequenza di 12 numeri (tecnicamente uno è True/Fase), racchiusi tra apici e parentesi. Ogni riga contiene una interrogazione del pc alla scheda. Questo mi consente, a meno di scartare a mano gli estremi di riga (cosa per altro banale) di splittare in corrispondenza di )","(

La prima riga dovrebbe essere solo un header, e la salto. In realtà ha anche degli eventi, peggio per loro...

Questo metodo, funziona, mi sembra anche piuttosto performante, ma mi confonde che per solo due colonne, sia necessario avere una intera matrice di interi a 64 bit.

Ho quindi provato a definirmi il mio tipo di dato (di cui non sono ancora certo al 100% perché sto aspettando una risposta da chi ha scritto il sw di acquisizione). Anche nel caso limite in cui metto tutti i campi a 64 bit, comunque diventa clamorosamente più lento e soprattutto più pesante in memoria, mentre io mi aspetterei che pesasse esattamente uguale.

#%% Carico i dati nel modo usuale
listaFiles = ("run__57__18_03_52.csv",
              "run__16__13_15_14.csv", 
              "run__18__13_27_50.csv")

fileToLoad = rf"./Data/{listaFiles[2]}"
print(f"File to load: {fileToLoad}")

superLista = []



t = time.time()
with open(fileToLoad) as f:
    for i, line in enumerate(f):
        
        # Salto la prima riga di HEADER.
        # A dire la verità ci sono anche un po' di dati...
        if i == 0: 
            print("===== HEADER =====")
            print(line)
            continue
            
        # Così si può vedere come è fatta una linea.
        if i == 1:
            print("======================================================")
            print(line)

        # Sostituisco le stringhe vero e falso con una rappr. numerica
        line = line.replace("False", "0")
        line = line.replace("True", "1")
        
        # Splitto ciascuna linea in corrispondenza di )","(
        # Stando attento a saltare apici e parentesi ad inizio e fine riga
        superLista.append( line[2:-3].split(')","(') )

    
# Let's flatten the list
#superLista = np.array([np.array(i.split(","), dtype = np.uint64) for sublist in superLista for i in sublist])
#superLista = np.array([np.fromstring(i, sep = ",", dtype = np.int64) for sublist in superLista for i in sublist])
superLista = np.array(list(chain.from_iterable(superLista)))


print(f"Time elapsed: {time.time()-t:.2f}")

print(superLista.shape)
print(type(superLista))

print(f"Dimensione su disco: {getsizeof(superLista)/1024**2:.2f} Mb")

File to load: ./Data/run__18__13_27_50.csv
===== HEADER =====
"{'BIAS0_BGR_MEAN': 15, 'BIAS0_BGR_SLOPE': 7, 'BIAS0_IBIAS': 2, 'BIAS0_ICLIP': 1, 'BIAS0_ID': 1, 'BIAS0_IFB': 2, 'BIAS0_IOTA': 0, 'BIAS0_ISF': 2, 'BIAS0_ISF_VINREF': 7, 'BIAS0_LDO_EN': 1, 'BIAS0_VCAL_HI': 0, 'BIAS0_VCAL_LO': 1, 'BIAS0_VCASD': 4, 'BIAS0_VCASN': 25, 'BIAS0_VCASP': 4, 'BIAS0_VINREF': 7, 'BIAS0_VREF_LDO': 1, 'BIAS10_BGR_MEAN': 8, 'BIAS10_BGR_SLOPE': 7, 'BIAS10_IBIAS': 2, 'BIAS10_ICLIP': 1, 'BIAS10_ID': 1, 'BIAS10_IFB': 2, 'BIAS10_IOTA': 0, 'BIAS10_ISF': 2, 'BIAS10_ISF_VINREF': 7, 'BIAS10_LDO_EN': 1, 'BIAS10_VCAL_HI': 0, 'BIAS10_VCAL_LO': 1, 'BIAS10_VCASD': 4, 'BIAS10_VCASN': 25, 'BIAS10_VCASP': 4, 'BIAS10_VINREF': 7, 'BIAS10_VREF_LDO': 1, 'BIAS11_BGR_MEAN': 4, 'BIAS11_BGR_SLOPE': 7, 'BIAS11_IBIAS': 2, 'BIAS11_ICLIP': 1, 'BIAS11_ID': 1, 'BIAS11_IFB': 2, 'BIAS11_IOTA': 0, 'BIAS11_ISF': 2, 'BIAS11_ISF_VINREF': 7, 'BIAS11_LDO_EN': 1, 'BIAS11_VCAL_HI': 0, 'BIAS11_VCAL_LO': 1, 'BIAS11_VCASD': 4, 'BIAS11_VCASN': 25, 'BIAS11_VCASP': 4, 'BIAS11_VINREF': 7, 'BIAS11_VREF_LDO': 1, 'BIAS12_BGR_MEAN': 6, 'BIAS12_BGR_SLOPE': 7, 'BIAS12_IBIAS': 2, 'BIAS12_ICLIP': 1, 'BIAS12_ID': 1, 'BIAS12_IFB': 2, 'BIAS12_IOTA': 0, 'BIAS12_ISF': 2, 'BIAS12_ISF_VINREF': 7, 'BIAS12_LDO_EN': 1, 'BIAS12_VCAL_HI': 0, 'BIAS12_VCAL_LO': 1, 'BIAS12_VCASD': 4, 'BIAS12_VCASN': 25, 'BIAS12_VCASP': 4, 'BIAS12_VINREF': 7, 'BIAS12_VREF_LDO': 1, 'BIAS13_BGR_MEAN': 5, 'BIAS13_BGR_SLOPE': 7, 'BIAS13_IBIAS': 2, 'BIAS13_ICLIP': 1, 'BIAS13_ID': 1, 'BIAS13_IFB': 2, 'BIAS13_IOTA': 0, 'BIAS13_ISF': 2, 'BIAS13_ISF_VINREF': 7, 'BIAS13_LDO_EN': 1, 'BIAS13_VCAL_HI': 0, 'BIAS13_VCAL_LO': 1, 'BIAS13_VCASD': 4, 'BIAS13_VCASN': 25, 'BIAS13_VCASP': 4, 'BIAS13_VINREF': 7, 'BIAS13_VREF_LDO': 1, 'BIAS14_BGR_MEAN': 5, 'BIAS14_BGR_SLOPE': 7, 'BIAS14_IBIAS': 2, 'BIAS14_ICLIP': 1, 'BIAS14_ID': 1, 'BIAS14_IFB': 2, 'BIAS14_IOTA': 0, 'BIAS14_ISF': 2, 'BIAS14_ISF_VINREF': 7, 'BIAS14_LDO_EN': 1, 'BIAS14_VCAL_HI': 0, 'BIAS14_VCAL_LO': 1, 'BIAS14_VCASD': 4, 'BIAS14_VCASN': 25, 'BIAS14_VCASP': 4, 'BIAS14_VINREF': 7, 'BIAS14_VREF_LDO': 1, 'BIAS15_BGR_MEAN': 7, 'BIAS15_BGR_SLOPE': 7, 'BIAS15_IBIAS': 2, 'BIAS15_ICLIP': 1, 'BIAS15_ID': 1, 'BIAS15_IFB': 2, 'BIAS15_IOTA': 0, 'BIAS15_ISF': 2, 'BIAS15_ISF_VINREF': 7, 'BIAS15_LDO_EN': 1, 'BIAS15_VCAL_HI': 0, 'BIAS15_VCAL_LO': 1, 'BIAS15_VCASD': 4, 'BIAS15_VCASN': 25, 'BIAS15_VCASP': 4, 'BIAS15_VINREF': 7, 'BIAS15_VREF_LDO': 1, 'BIAS1_BGR_MEAN': 3, 'BIAS1_BGR_SLOPE': 7, 'BIAS1_IBIAS': 2, 'BIAS1_ICLIP': 1, 'BIAS1_ID': 1, 'BIAS1_IFB': 2, 'BIAS1_IOTA': 0, 'BIAS1_ISF': 2, 'BIAS1_ISF_VINREF': 7, 'BIAS1_LDO_EN': 1, 'BIAS1_VCAL_HI': 0, 'BIAS1_VCAL_LO': 1, 'BIAS1_VCASD': 4, 'BIAS1_VCASN': 25, 'BIAS1_VCASP': 4, 'BIAS1_VINREF': 7, 'BIAS1_VREF_LDO': 1, 'BIAS2_BGR_MEAN': 5, 'BIAS2_BGR_SLOPE': 7, 'BIAS2_IBIAS': 2, 'BIAS2_ICLIP': 1, 'BIAS2_ID': 1, 'BIAS2_IFB': 2, 'BIAS2_IOTA': 0, 'BIAS2_ISF': 2, 'BIAS2_ISF_VINREF': 7, 'BIAS2_LDO_EN': 1, 'BIAS2_VCAL_HI': 0, 'BIAS2_VCAL_LO': 1, 'BIAS2_VCASD': 4, 'BIAS2_VCASN': 25, 'BIAS2_VCASP': 4, 'BIAS2_VINREF': 7, 'BIAS2_VREF_LDO': 1, 'BIAS3_BGR_MEAN': 5, 'BIAS3_BGR_SLOPE': 7, 'BIAS3_IBIAS': 2, 'BIAS3_ICLIP': 1, 'BIAS3_ID': 1, 'BIAS3_IFB': 2, 'BIAS3_IOTA': 0, 'BIAS3_ISF': 2, 'BIAS3_ISF_VINREF': 7, 'BIAS3_LDO_EN': 1, 'BIAS3_VCAL_HI': 0, 'BIAS3_VCAL_LO': 1, 'BIAS3_VCASD': 4, 'BIAS3_VCASN': 25, 'BIAS3_VCASP': 4, 'BIAS3_VINREF': 7, 'BIAS3_VREF_LDO': 1, 'BIAS4_BGR_MEAN': 4, 'BIAS4_BGR_SLOPE': 7, 'BIAS4_IBIAS': 2, 'BIAS4_ICLIP': 1, 'BIAS4_ID': 1, 'BIAS4_IFB': 2, 'BIAS4_IOTA': 0, 'BIAS4_ISF': 2, 'BIAS4_ISF_VINREF': 7, 'BIAS4_LDO_EN': 1, 'BIAS4_VCAL_HI': 0, 'BIAS4_VCAL_LO': 1, 'BIAS4_VCASD': 4, 'BIAS4_VCASN': 25, 'BIAS4_VCASP': 4, 'BIAS4_VINREF': 7, 'BIAS4_VREF_LDO': 1, 'BIAS5_BGR_MEAN': 5, 'BIAS5_BGR_SLOPE': 7, 'BIAS5_IBIAS': 2, 'BIAS5_ICLIP': 1, 'BIAS5_ID': 1, 'BIAS5_IFB': 2, 'BIAS5_IOTA': 0, 'BIAS5_ISF': 2, 'BIAS5_ISF_VINREF': 7, 'BIAS5_LDO_EN': 1, 'BIAS5_VCAL_HI': 0, 'BIAS5_VCAL_LO': 1, 'BIAS5_VCASD': 4, 'BIAS5_VCASN': 25, 'BIAS5_VCASP': 4, 'BIAS5_VINREF': 7, 'BIAS5_VREF_LDO': 1, 'BIAS6_BGR_MEAN': 5, 'BIAS6_BGR_SLOPE': 7, 'BIAS6_IBIAS': 2, 'BIAS6_ICLIP': 1, 'BIAS6_ID': 1, 'BIAS6_IFB': 2, 'BIAS6_IOTA': 0, 'BIAS6_ISF': 2, 'BIAS6_ISF_VINREF': 7, 'BIAS6_LDO_EN': 1, 'BIAS6_VCAL_HI': 0, 'BIAS6_VCAL_LO': 1, 'BIAS6_VCASD': 4, 'BIAS6_VCASN': 25, 'BIAS6_VCASP': 4, 'BIAS6_VINREF': 7, 'BIAS6_VREF_LDO': 1, 'BIAS7_BGR_MEAN': 5, 'BIAS7_BGR_SLOPE': 7, 'BIAS7_IBIAS': 2, 'BIAS7_ICLIP': 1, 'BIAS7_ID': 1, 'BIAS7_IFB': 2, 'BIAS7_IOTA': 0, 'BIAS7_ISF': 2, 'BIAS7_ISF_VINREF': 7, 'BIAS7_LDO_EN': 1, 'BIAS7_VCAL_HI': 0, 'BIAS7_VCAL_LO': 1, 'BIAS7_VCASD': 4, 'BIAS7_VCASN': 25, 'BIAS7_VCASP': 4, 'BIAS7_VINREF': 7, 'BIAS7_VREF_LDO': 1, 'BIAS8_BGR_MEAN': 9, 'BIAS8_BGR_SLOPE': 7, 'BIAS8_IBIAS': 2, 'BIAS8_ICLIP': 1, 'BIAS8_ID': 1, 'BIAS8_IFB': 2, 'BIAS8_IOTA': 0, 'BIAS8_ISF': 2, 'BIAS8_ISF_VINREF': 7, 'BIAS8_LDO_EN': 1, 'BIAS8_VCAL_HI': 0, 'BIAS8_VCAL_LO': 1, 'BIAS8_VCASD': 4, 'BIAS8_VCASN': 25, 'BIAS8_VCASP': 4, 'BIAS8_VINREF': 7, 'BIAS8_VREF_LDO': 1, 'BIAS9_BGR_MEAN': 6, 'BIAS9_BGR_SLOPE': 7, 'BIAS9_IBIAS': 2, 'BIAS9_ICLIP': 1, 'BIAS9_ID': 1, 'BIAS9_IFB': 2, 'BIAS9_IOTA': 0, 'BIAS9_ISF': 2, 'BIAS9_ISF_VINREF': 7, 'BIAS9_LDO_EN': 1, 'BIAS9_VCAL_HI': 0, 'BIAS9_VCAL_LO': 1, 'BIAS9_VCASD': 4, 'BIAS9_VCASN': 25, 'BIAS9_VCASP': 4, 'BIAS9_VINREF': 7, 'BIAS9_VREF_LDO': 1, 'DIGITAL_INJECTION': 0, 'DISABLE_SMART_READOUT': 1, 'EOS_CLOCK_GATING_ENABLE': 0, 'FORCE_DISABLE_MASK': 0, 'FORCE_ENABLE_INJECTION': 0, 'HELPER_SECCFG_CFGDATA': 1, 'HELPER_SECCFG_COLUMNS': 1, 'HELPER_SECCFG_PIXELSELECT': 1, 'HELPER_SECCFG_PRSKIP': 0, 'HELPER_SECCFG_PRSTART': 0, 'HELPER_SECCFG_PRSTOP': 0, 'HELPER_SECCFG_SECTIONS': 4, 'LVDS_STRENGTH': 7, 'MAX_READS': 8, 'OPERATION': 0, 'READOUT_CLK_DIVIDER': 3, 'SECTION_CLOCK_GATING': 0, 'SECTION_CLOCK_MASK': 0, 'SECTION_READ_MASK': 0, 'SERIALIZER_SYNC': 0, 'TEST_PULSE_MASK': 0, 'TIMESTAMP_LATCHES': 1, 'TIMING_CLK_DIVIDER': 1, 'TOKEN_COUNTER': 15}","(1, 2, 82, 9, 12, 12, False, 234, 2155505, 0, 2155498, 1)","(1, 8, 81, 8, 12, 12, False, 238, 2155509, 0, 2155502, 1)","(0, 176, 81, 9, 12, 12, False, 234, 2155513, 0, 2155498, 1)","(0, 64, 81, 10, 12, 12, False, 238, 2155517, 0, 2155502, 1)","(0, 48, 1, 15, 5, 5, False, 198, 2159821, 0, 2159814, 2)","(0, 32, 1, 14, 5, 5, False, 198, 2159825, 0, 2159814, 2)","(1, 3, 53, 13, 11, 11, False, 122, 2206081, 0, 2206074, 5)","(1, 1, 53, 14, 11, 11, False, 130, 2206089, 0, 2206082, 5)","(0, 64, 52, 14, 11, 11, False, 130, 2206093, 0, 2206082, 5)","(1, 60, 11, 14, 11, 11, False, 98, 2210921, 0, 2210914, 6)","(0, 224, 11, 13, 11, 11, False, 102, 2210925, 0, 2210918, 6)"

======================================================
"(1, 2, 103, 15, 11, 11, False, 238, 2326261, 0, 2326254, 10)","(1, 45, 103, 0, 12, 12, False, 238, 2326261, 0, 2326254, 10)","(0, 192, 102, 15, 11, 11, False, 238, 2326265, 0, 2326254, 10)","(0, 80, 103, 1, 12, 12, False, 238, 2326265, 0, 2326254, 10)","(0, 32, 38, 12, 7, 7, False, 6, 2327053, 0, 2327046, 11)","(1, 20, 38, 13, 7, 7, False, 10, 2327057, 0, 2327050, 11)","(0, 128, 84, 7, 11, 11, False, 218, 2329313, 0, 2329306, 12)","(1, 9, 85, 8, 11, 11, False, 218, 2329317, 0, 2329306, 12)","(1, 52, 85, 9, 11, 11, False, 218, 2329321, 0, 2329306, 12)","(0, 128, 17, 10, 8, 8, False, 14, 2330133, 0, 2330126, 13)","(0, 224, 17, 11, 8, 8, False, 14, 2330137, 0, 2330126, 13)","(0, 240, 17, 12, 8, 8, False, 14, 2330141, 0, 2330126, 13)","(0, 80, 17, 13, 8, 8, False, 14, 2330145, 0, 2330126, 13)","(0, 64, 58, 15, 5, 5, False, 86, 2351453, 0, 2351446, 14)","(1, 28, 58, 13, 5, 5, False, 86, 2351457, 0, 2351446, 14)","(1, 180, 58, 14, 5, 5, False, 86, 2351461, 0, 2351446, 14)","(1, 46, 67, 4, 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False, 26, 2390317, 0, 2390298, 18)","(1, 1, 67, 4, 13, 13, False, 30, 2390321, 0, 2390302, 18)","(0, 64, 66, 4, 13, 13, False, 30, 2390325, 0, 2390302, 18)","(0, 160, 67, 6, 5, 5, False, 30, 2430501, 0, 2430494, 19)","(1, 22, 67, 7, 5, 5, False, 30, 2430505, 0, 2430494, 19)","(0, 128, 66, 7, 5, 5, False, 30, 2430509, 0, 2430494, 19)","(1, 60, 37, 5, 7, 7, False, 214, 2436317, 0, 2436310, 20)","(1, 12, 37, 6, 7, 7, False, 214, 2436321, 0, 2436310, 20)","(1, 3, 72, 15, 2, 2, False, 182, 2456509, 0, 2456502, 22)","(0, 192, 71, 15, 2, 2, False, 182, 2456513, 0, 2456502, 22)","(0, 192, 71, 0, 3, 3, False, 182, 2456509, 0, 2456502, 22)","(0, 160, 98, 3, 12, 12, False, 90, 2486369, 0, 2486362, 23)","(1, 11, 99, 4, 12, 12, False, 90, 2486373, 0, 2486362, 23)","(0, 64, 98, 4, 12, 12, False, 90, 2486377, 0, 2486362, 23)","(1, 180, 99, 5, 12, 12, False, 90, 2486381, 0, 2486362, 23)","(1, 3, 100, 6, 12, 12, False, 90, 2486385, 0, 2486362, 23)","(1, 12, 100, 7, 12, 12, False, 90, 2486389, 0, 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0, 2602942, 34)","(1, 52, 35, 4, 3, 3, False, 70, 2612813, 0, 2612806, 35)","(1, 8, 35, 3, 3, 3, False, 74, 2612817, 0, 2612810, 35)","(1, 10, 115, 7, 12, 12, False, 58, 2614849, 0, 2614842, 36)","(1, 180, 115, 8, 12, 12, False, 58, 2614853, 0, 2614842, 36)","(1, 45, 116, 9, 12, 12, False, 58, 2614857, 0, 2614842, 36)","(0, 64, 115, 9, 12, 12, False, 58, 2614861, 0, 2614842, 36)","(0, 16, 116, 10, 12, 12, False, 58, 2614865, 0, 2614842, 36)","(1, 2, 29, 7, 13, 13, False, 158, 2620325, 0, 2620318, 37)","(1, 173, 28, 7, 13, 13, False, 158, 2620329, 0, 2620318, 37)","(0, 160, 27, 7, 13, 13, False, 158, 2620333, 0, 2620318, 37)","(1, 15, 29, 8, 13, 13, False, 158, 2620337, 0, 2620318, 37)","(0, 80, 28, 8, 13, 13, False, 158, 2620341, 0, 2620318, 37)","(1, 120, 27, 8, 13, 13, False, 158, 2620345, 0, 2620318, 37)","(1, 60, 29, 9, 13, 13, False, 158, 2620349, 0, 2620318, 37)","(0, 16, 27, 9, 13, 13, False, 158, 2620353, 0, 2620318, 37)","(1, 126, 29, 10, 13, 13, False, 158, 2620357, 0, 2620318, 37)","(1, 21, 29, 11, 13, 13, False, 158, 2620361, 0, 2620318, 37)","(0, 64, 28, 11, 13, 13, False, 158, 2620365, 0, 2620318, 37)","(1, 175, 107, 14, 9, 9, False, 234, 2650353, 0, 2650346, 38)","(0, 64, 106, 14, 9, 9, False, 234, 2650357, 0, 2650346, 38)","(0, 64, 107, 15, 9, 9, False, 242, 2650361, 0, 2650354, 38)","(1, 2, 71, 15, 9, 9, False, 74, 2650449, 0, 2650442, 38)","(1, 2, 97, 1, 8, 8, False, 10, 2675729, 0, 2675722, 41)","(1, 2, 96, 0, 8, 8, False, 14, 2675733, 0, 2675726, 41)","(1, 181, 95, 0, 8, 8, False, 14, 2675737, 0, 2675726, 41)","(1, 181, 96, 1, 8, 8, False, 10, 2675741, 0, 2675722, 41)","(0, 64, 95, 1, 8, 8, False, 10, 2675745, 0, 2675722, 41)","(1, 9, 97, 2, 8, 8, False, 14, 2675749, 0, 2675726, 41)","(1, 12, 29, 4, 3, 3, False, 66, 2703945, 0, 2703938, 42)","(1, 12, 29, 2, 3, 3, False, 70, 2703949, 0, 2703942, 42)","(1, 8, 29, 1, 3, 3, False, 74, 2703953, 0, 2703946, 42)","(1, 12, 29, 3, 3, 3, False, 70, 2703957, 0, 2703942, 42)","(1, 12, 29, 5, 3, 3, False, 70, 2703961, 0, 2703942, 42)","(1, 8, 29, 6, 3, 3, False, 70, 2703965, 0, 2703942, 42)","(1, 12, 29, 7, 3, 3, False, 66, 2703969, 0, 2703938, 42)","(0, 192, 7, 6, 11, 11, False, 66, 2705993, 0, 2705986, 44)","(1, 8, 8, 4, 11, 11, False, 70, 2705997, 0, 2705990, 44)","(1, 7, 8, 5, 11, 11, False, 70, 2706001, 0, 2705990, 44)","(0, 112, 7, 7, 11, 11, False, 66, 2706005, 0, 2705986, 44)","(1, 24, 7, 8, 11, 11, False, 66, 2706009, 0, 2705986, 44)","(1, 7, 7, 9, 11, 11, False, 66, 2706013, 0, 2705986, 44)","(0, 128, 6, 9, 11, 11, False, 66, 2706017, 0, 2705986, 44)","(0, 64, 6, 10, 11, 11, False, 70, 2706021, 0, 2705990, 44)","(1, 188, 36, 7, 2, 2, False, 34, 2719273, 0, 2719266, 46)","(0, 208, 36, 8, 2, 2, False, 38, 2719277, 0, 2719270, 46)","(0, 192, 61, 7, 10, 10, False, 26, 2738721, 0, 2738714, 48)","(1, 23, 61, 8, 10, 10, False, 26, 2738725, 0, 2738714, 48)","(0, 64, 60, 8, 10, 10, False, 26, 2738729, 0, 2738714, 48)","(1, 9, 21, 14, 3, 3, False, 70, 2771277, 0, 2771270, 49)","(0, 208, 20, 13, 3, 3, False, 74, 2771281, 0, 2771274, 49)","(0, 64, 20, 14, 3, 3, False, 70, 2771285, 0, 2771270, 49)","(1, 10, 101, 3, 2, 2, False, 254, 2792965, 0, 2792958, 50)","(1, 248, 100, 3, 2, 2, False, 254, 2792969, 0, 2792958, 50)","(1, 45, 101, 4, 2, 2, False, 254, 2792973, 0, 2792958, 50)","(1, 1, 104, 3, 4, 4, False, 234, 2818033, 0, 2818026, 51)","(1, 250, 103, 3, 4, 4, False, 234, 2818037, 0, 2818026, 51)","(1, 1, 103, 4, 4, 4, False, 234, 2818041, 0, 2818026, 51)","(1, 3, 14, 15, 13, 13, False, 126, 2864261, 0, 2864254, 52)","(1, 56, 14, 13, 13, 13, False, 126, 2864265, 0, 2864254, 52)","(1, 7, 14, 14, 13, 13, False, 126, 2864269, 0, 2864254, 52)","(1, 45, 14, 0, 14, 14, False, 126, 2864261, 0, 2864254, 52)","(1, 10, 69, 3, 8, 8, False, 2, 2877193, 0, 2877186, 53)","(1, 20, 69, 4, 8, 8, False, 2, 2877197, 0, 2877186, 53)","(1, 43, 2, 13, 2, 2, False, 66, 2902857, 0, 2902850, 54)","(0, 192, 1, 13, 2, 2, False, 66, 2902861, 0, 2902850, 54)","(0, 16, 2, 14, 2, 2, False, 66, 2902865, 0, 2902850, 54)","(0, 240, 78, 7, 11, 11, False, 90, 2925665, 0, 2925658, 56)","(1, 45, 78, 6, 11, 11, False, 94, 2925669, 0, 2925662, 56)","(1, 13, 79, 8, 11, 11, False, 94, 2925673, 0, 2925662, 56)","(0, 64, 78, 8, 11, 11, False, 94, 2925677, 0, 2925662, 56)","(0, 160, 18, 15, 4, 4, False, 10, 2935569, 0, 2935562, 57)","(1, 2, 19, 0, 5, 5, False, 10, 2935569, 0, 2935562, 57)","(0, 64, 18, 0, 5, 5, False, 10, 2935573, 0, 2935562, 57)","(1, 45, 9, 15, 3, 3, False, 102, 2946669, 0, 2946662, 58)","(1, 2, 10, 0, 4, 4, False, 102, 2946669, 0, 2946662, 58)","(1, 2, 9, 14, 3, 3, False, 102, 2946673, 0, 2946662, 58)","(0, 208, 9, 0, 4, 4, False, 102, 2946673, 0, 2946662, 58)","(1, 3, 72, 12, 7, 7, False, 250, 2963201, 0, 2963194, 59)","(1, 94, 71, 12, 7, 7, False, 250, 2963205, 0, 2963194, 59)","(1, 2, 34, 10, 14, 14, False, 2, 2968585, 0, 2968578, 60)","(0, 128, 33, 5, 14, 14, False, 6, 2968589, 0, 2968582, 60)","(0, 192, 33, 6, 14, 14, False, 6, 2968593, 0, 2968582, 60)","(0, 192, 33, 7, 14, 14, False, 6, 2968597, 0, 2968582, 60)","(0, 64, 33, 8, 14, 14, False, 10, 2968601, 0, 2968586, 60)","(0, 128, 33, 9, 14, 14, False, 10, 2968605, 0, 2968586, 60)","(0, 192, 33, 10, 14, 14, False, 2, 2968609, 0, 2968578, 60)","(1, 3, 34, 11, 14, 14, False, 6, 2968613, 0, 2968582, 60)","(0, 64, 33, 11, 14, 14, False, 6, 2968617, 0, 2968582, 60)","(0, 32, 46, 4, 11, 11, False, 98, 2985321, 0, 2985314, 61)","(1, 2, 47, 5, 11, 11, False, 98, 2985325, 0, 2985314, 61)","(0, 192, 46, 5, 11, 11, False, 98, 2985329, 0, 2985314, 61)","(1, 5, 47, 6, 11, 11, False, 98, 2985333, 0, 2985314, 61)","(1, 173, 84, 1, 10, 10, False, 90, 2986593, 0, 2986586, 62)","(1, 84, 83, 1, 10, 10, False, 90, 2986597, 0, 2986586, 62)","(0, 80, 84, 2, 10, 10, False, 94, 2986601, 0, 2986590, 62)","(0, 16, 34, 15, 14, 14, False, 6, 3000845, 0, 3000838, 64)","(1, 21, 59, 12, 3, 3, False, 254, 3000837, 0, 3000830, 64)","(0, 224, 58, 12, 3, 3, False, 254, 3000841, 0, 3000830, 64)","(1, 28, 58, 13, 3, 3, False, 254, 3000845, 0, 3000830, 64)","(0, 112, 7, 15, 10, 10, False, 154, 3001505, 0, 3001498, 65)","(1, 2, 8, 14, 10, 10, False, 154, 3001509, 0, 3001498, 65)","(0, 160, 7, 14, 10, 10, False, 154, 3001513, 0, 3001498, 65)","(1, 20, 7, 0, 11, 11, False, 154, 3001505, 0, 3001498, 65)","(0, 224, 105, 8, 3, 3, False, 242, 3025913, 0, 3025906, 66)","(1, 2, 106, 7, 3, 3, False, 246, 3025917, 0, 3025910, 66)","(1, 30, 105, 9, 3, 3, False, 242, 3025921, 0, 3025906, 66)","(1, 168, 29, 2, 9, 9, False, 202, 3037649, 0, 3037642, 67)","(1, 85, 29, 3, 9, 9, False, 202, 3037653, 0, 3037642, 67)","(1, 14, 72, 2, 5, 5, False, 166, 3039149, 0, 3039142, 68)","(0, 160, 71, 2, 5, 5, False, 166, 3039153, 0, 3039142, 68)","(0, 80, 71, 3, 5, 5, False, 166, 3039157, 0, 3039142, 68)","(1, 7, 60, 11, 4, 4, False, 58, 3047233, 0, 3047226, 69)","(1, 2, 60, 10, 4, 4, False, 62, 3047237, 0, 3047230, 69)","(1, 14, 60, 12, 4, 4, False, 58, 3047241, 0, 3047226, 69)","(1, 3, 60, 13, 4, 4, False, 58, 3047245, 0, 3047226, 69)","(1, 1, 60, 14, 4, 4, False, 58, 3047249, 0, 3047226, 69)","(0, 64, 59, 14, 4, 4, False, 58, 3047253, 0, 3047226, 69)","(1, 21, 78, 14, 4, 4, False, 6, 3054349, 0, 3054342, 70)","(1, 42, 78, 13, 4, 4, False, 10, 3054353, 0, 3054346, 70)","(0, 64, 77, 14, 4, 4, False, 6, 3054357, 0, 3054342, 70)","(1, 2, 33, 3, 10, 10, False, 94, 3062885, 0, 3062878, 71)","(1, 3, 33, 4, 10, 10, False, 94, 3062889, 0, 3062878, 71)","(0, 192, 32, 4, 10, 10, False, 94, 3062893, 0, 3062878, 71)","(0, 64, 32, 5, 10, 10, False, 98, 3062897, 0, 3062882, 71)","(1, 3, 54, 2, 8, 8, False, 226, 3087337, 0, 3087330, 72)","(0, 64, 53, 2, 8, 8, False, 226, 3087341, 0, 3087330, 72)","(1, 5, 54, 3, 8, 8, False, 230, 3087345, 0, 3087334, 72)","(1, 12, 33, 0, 3, 3, False, 154, 3093409, 0, 3093402, 73)","(0, 176, 33, 1, 3, 3, False, 154, 3093413, 0, 3093402, 73)","(0, 64, 33, 2, 3, 3, False, 154, 3093417, 0, 3093402, 73)","(1, 10, 73, 9, 7, 7, False, 238, 3098613, 0, 3098606, 74)","(0, 240, 72, 9, 7, 7, False, 238, 3098617, 0, 3098606, 74)","(1, 2, 74, 10, 7, 7, False, 238, 3098621, 0, 3098606, 74)","(1, 212, 73, 10, 7, 7, False, 238, 3098625, 0, 3098606, 74)","(1, 60, 60, 15, 9, 9, False, 142, 3102101, 0, 3102094, 75)","(1, 12, 60, 14, 9, 9, False, 142, 3102105, 0, 3102094, 75)","(1, 4, 60, 0, 10, 10, False, 146, 3102105, 0, 3102098, 75)","(1, 45, 0, 6, 2, 2, False, 62, 3126853, 0, 3126846, 77)","(1, 10, 0, 5, 2, 2, False, 66, 3126857, 0, 3126850, 77)","(1, 2, 1, 7, 2, 2, False, 62, 3126861, 0, 3126846, 77)","(0, 208, 0, 7, 2, 2, False, 62, 3126865, 0, 3126846, 77)","(1, 1, 1, 8, 2, 2, False, 66, 3126869, 0, 3126850, 77)","(0, 64, 0, 8, 2, 2, False, 66, 3126873, 0, 3126850, 77)","(1, 9, 82, 15, 11, 11, False, 238, 3182325, 0, 3182318, 81)","(1, 4, 81, 13, 11, 11, False, 238, 3182329, 0, 3182318, 81)","(1, 3, 31, 9, 8, 8, False, 166, 3183789, 0, 3183782, 82)","(0, 128, 30, 9, 8, 8, False, 166, 3183793, 0, 3183782, 82)","(1, 120, 30, 10, 8, 8, False, 166, 3183797, 0, 3183782, 82)","(1, 12, 30, 11, 8, 8, False, 166, 3183801, 0, 3183782, 82)","(0, 240, 15, 9, 2, 2, False, 18, 3209241, 0, 3209234, 86)","(0, 32, 15, 8, 2, 2, False, 22, 3209245, 0, 3209238, 86)","(0, 208, 15, 10, 2, 2, False, 18, 3209249, 0, 3209234, 86)","(1, 2, 12, 10, 2, 2, False, 122, 3216769, 0, 3216762, 88)","(0, 192, 11, 10, 2, 2, False, 122, 3216773, 0, 3216762, 88)","(1, 45, 12, 11, 2, 2, False, 122, 3216777, 0, 3216762, 88)","(0, 16, 12, 12, 2, 2, False, 122, 3216781, 0, 3216762, 88)","(1, 30, 74, 7, 3, 3, False, 198, 3225805, 0, 3225798, 90)","(1, 1, 74, 8, 3, 3, False, 198, 3225809, 0, 3225798, 90)","(0, 64, 73, 8, 3, 3, False, 198, 3225813, 0, 3225798, 90)","(1, 10, 82, 4, 4, 4, False, 18, 3252761, 0, 3252754, 91)","(0, 160, 81, 4, 4, 4, False, 18, 3252765, 0, 3252754, 91)","(1, 5, 82, 5, 4, 4, False, 18, 3252769, 0, 3252754, 91)","(1, 84, 81, 5, 4, 4, False, 18, 3252773, 0, 3252754, 91)","(1, 85, 115, 9, 12, 12, False, 190, 3256261, 0, 3256254, 92)","(0, 32, 115, 8, 12, 12, False, 194, 3256265, 0, 3256258, 92)","(1, 94, 114, 9, 12, 12, False, 190, 3256269, 0, 3256254, 92)","(0, 96, 113, 10, 12, 12, False, 190, 3256273, 0, 3256254, 92)","(1, 28, 113, 11, 12, 12, False, 190, 3256277, 0, 3256254, 92)","(1, 7, 113, 12, 12, 12, False, 190, 3256281, 0, 3256254, 92)","(0, 128, 112, 12, 12, 12, False, 190, 3256285, 0, 3256254, 92)","(1, 2, 110, 12, 12, 12, False, 190, 3256289, 0, 3256254, 92)","(0, 192, 109, 12, 12, 12, False, 190, 3256293, 0, 3256254, 92)","(1, 94, 112, 13, 12, 12, False, 190, 3256297, 0, 3256254, 92)","(1, 170, 111, 13, 12, 12, False, 190, 3256301, 0, 3256254, 92)","(1, 148, 110, 13, 12, 12, False, 190, 3256305, 0, 3256254, 92)","(0, 16, 111, 14, 12, 12, False, 194, 3256309, 0, 3256258, 92)","(1, 11, 19, 12, 5, 5, False, 142, 3256981, 0, 3256974, 93)","(1, 8, 18, 10, 5, 5, False, 146, 3256985, 0, 3256978, 93)","(1, 180, 18, 11, 5, 5, False, 146, 3256989, 0, 3256978, 93)","(0, 64, 18, 12, 5, 5, False, 142, 3256993, 0, 3256974, 93)","(1, 1, 19, 13, 5, 5, False, 146, 3256997, 0, 3256978, 93)"

Time elapsed: 5.09
(4466747,)
<class 'numpy.ndarray'>
Dimensione su disco: 1175.71 Mb

myEvent = np.dtype([
    ('aa', np.dtype('u8')),
    ('bb', np.dtype('u2')),
])


tmpLst = np.array([(i, i**2) for i in range(10)], dtype = myEvent)
#aaa = np.array((1,2), dtype=myEvent)


# Alcune prove a caso
print(tmpLst[0], type(tmpLst[0][0]))
print(tmpLst[1], type(tmpLst[1][1]))

print(tmpLst["aa"], type(tmpLst["aa"][0]))
print(tmpLst["bb"], type(tmpLst["bb"][0]))

(0, 0) <class 'numpy.uint64'>
(1, 1) <class 'numpy.uint16'>
[0 1 2 3 4 5 6 7 8 9] <class 'numpy.uint64'>
[ 0  1  4  9 16 25 36 49 64 81] <class 'numpy.uint16'>

Quello sopra è in teoria il formato giusto. Ma da qualche parte mi dà un errore, per provare ho messo tutto a 64 bit

myEvent = np.dtype([
    ('aa', np.dtype('u2')),
    ('hitmap', np.dtype('u1')),
    ('cc', np.dtype('u2')),
    ('dd', np.dtype('u2')),
    ('ee', np.dtype('u2')),
    ('ff', np.dtype('u2')),
    ('gg', np.dtype('u2')),
    ('ts', np.dtype('u2')),
    ('ts_fpga', np.dtype('u8')),
    ('ts_sw', np.dtype('u2')),
    ('ts_ext', np.dtype('u8')),
    ('nEvent', np.dtype('u8')),
])
     
myEvent = np.dtype([
    ('aa', np.dtype('u8')),
    ('hitmap', np.dtype('u8')),
    ('cc', np.dtype('u8')),
    ('dd', np.dtype('u8')),
    ('ee', np.dtype('u8')),
    ('ff', np.dtype('u8')),
    ('gg', np.dtype('u8')),
    ('ts', np.dtype('u8')),
    ('ts_fpga', np.dtype('u8')),
    ('ts_sw', np.dtype('u8')),
    ('ts_ext', np.dtype('u8')),
    ('nEvent', np.dtype('u8')),
])

listaFiles = ("run__57__18_03_52.csv",
              "run__16__13_15_14.csv", 
              "run__18__13_27_50.csv")

fileToLoad = rf"./Data/{listaFiles[2]}"
print(f"File to load: {fileToLoad}")

superLista = []



t = time.time()
with open(fileToLoad) as f:
    for i, line in enumerate(f):
        
        # Salto la prima riga di HEADER.
        # A dire la verità ci sono anche un po' di dati...
        if i == 0: 
            print("===== HEADER =====")
            print(line)
            continue

        # Sostituisco le stringhe vero e falso con una rappr. numerica
        line = line.replace("False", "0")
        line = line.replace("True", "1")
        
        # Splitto ciascuna linea in corrispondenza di )","(
        # Stando attento a saltare apici e parentesi ad inizio e fine riga
        superLista.append( line[2:-3].split(')","(') )

    
# Let's flatten the list
#superLista = np.array([np.array(i.split(","), dtype=myEvent) for sublist in superLista for i in sublist])
#superLista = np.array([np.fromstring(i, sep = ",", dtype = np.int64) for sublist in superLista for i in sublist])
superLista = np.array(list(chain.from_iterable(superLista)))


print(f"Time elapsed: {time.time()-t:.2f}")

print(superLista.shape)
print(type(superLista))

print(f"Dimensione su disco: {getsizeof(superLista)/1024**2:.2f} Mb")

File to load: ./Data/run__18__13_27_50.csv
===== HEADER =====
"{'BIAS0_BGR_MEAN': 15, 'BIAS0_BGR_SLOPE': 7, 'BIAS0_IBIAS': 2, 'BIAS0_ICLIP': 1, 'BIAS0_ID': 1, 'BIAS0_IFB': 2, 'BIAS0_IOTA': 0, 'BIAS0_ISF': 2, 'BIAS0_ISF_VINREF': 7, 'BIAS0_LDO_EN': 1, 'BIAS0_VCAL_HI': 0, 'BIAS0_VCAL_LO': 1, 'BIAS0_VCASD': 4, 'BIAS0_VCASN': 25, 'BIAS0_VCASP': 4, 'BIAS0_VINREF': 7, 'BIAS0_VREF_LDO': 1, 'BIAS10_BGR_MEAN': 8, 'BIAS10_BGR_SLOPE': 7, 'BIAS10_IBIAS': 2, 'BIAS10_ICLIP': 1, 'BIAS10_ID': 1, 'BIAS10_IFB': 2, 'BIAS10_IOTA': 0, 'BIAS10_ISF': 2, 'BIAS10_ISF_VINREF': 7, 'BIAS10_LDO_EN': 1, 'BIAS10_VCAL_HI': 0, 'BIAS10_VCAL_LO': 1, 'BIAS10_VCASD': 4, 'BIAS10_VCASN': 25, 'BIAS10_VCASP': 4, 'BIAS10_VINREF': 7, 'BIAS10_VREF_LDO': 1, 'BIAS11_BGR_MEAN': 4, 'BIAS11_BGR_SLOPE': 7, 'BIAS11_IBIAS': 2, 'BIAS11_ICLIP': 1, 'BIAS11_ID': 1, 'BIAS11_IFB': 2, 'BIAS11_IOTA': 0, 'BIAS11_ISF': 2, 'BIAS11_ISF_VINREF': 7, 'BIAS11_LDO_EN': 1, 'BIAS11_VCAL_HI': 0, 'BIAS11_VCAL_LO': 1, 'BIAS11_VCASD': 4, 'BIAS11_VCASN': 25, 'BIAS11_VCASP': 4, 'BIAS11_VINREF': 7, 'BIAS11_VREF_LDO': 1, 'BIAS12_BGR_MEAN': 6, 'BIAS12_BGR_SLOPE': 7, 'BIAS12_IBIAS': 2, 'BIAS12_ICLIP': 1, 'BIAS12_ID': 1, 'BIAS12_IFB': 2, 'BIAS12_IOTA': 0, 'BIAS12_ISF': 2, 'BIAS12_ISF_VINREF': 7, 'BIAS12_LDO_EN': 1, 'BIAS12_VCAL_HI': 0, 'BIAS12_VCAL_LO': 1, 'BIAS12_VCASD': 4, 'BIAS12_VCASN': 25, 'BIAS12_VCASP': 4, 'BIAS12_VINREF': 7, 'BIAS12_VREF_LDO': 1, 'BIAS13_BGR_MEAN': 5, 'BIAS13_BGR_SLOPE': 7, 'BIAS13_IBIAS': 2, 'BIAS13_ICLIP': 1, 'BIAS13_ID': 1, 'BIAS13_IFB': 2, 'BIAS13_IOTA': 0, 'BIAS13_ISF': 2, 'BIAS13_ISF_VINREF': 7, 'BIAS13_LDO_EN': 1, 'BIAS13_VCAL_HI': 0, 'BIAS13_VCAL_LO': 1, 'BIAS13_VCASD': 4, 'BIAS13_VCASN': 25, 'BIAS13_VCASP': 4, 'BIAS13_VINREF': 7, 'BIAS13_VREF_LDO': 1, 'BIAS14_BGR_MEAN': 5, 'BIAS14_BGR_SLOPE': 7, 'BIAS14_IBIAS': 2, 'BIAS14_ICLIP': 1, 'BIAS14_ID': 1, 'BIAS14_IFB': 2, 'BIAS14_IOTA': 0, 'BIAS14_ISF': 2, 'BIAS14_ISF_VINREF': 7, 'BIAS14_LDO_EN': 1, 'BIAS14_VCAL_HI': 0, 'BIAS14_VCAL_LO': 1, 'BIAS14_VCASD': 4, 'BIAS14_VCASN': 25, 'BIAS14_VCASP': 4, 'BIAS14_VINREF': 7, 'BIAS14_VREF_LDO': 1, 'BIAS15_BGR_MEAN': 7, 'BIAS15_BGR_SLOPE': 7, 'BIAS15_IBIAS': 2, 'BIAS15_ICLIP': 1, 'BIAS15_ID': 1, 'BIAS15_IFB': 2, 'BIAS15_IOTA': 0, 'BIAS15_ISF': 2, 'BIAS15_ISF_VINREF': 7, 'BIAS15_LDO_EN': 1, 'BIAS15_VCAL_HI': 0, 'BIAS15_VCAL_LO': 1, 'BIAS15_VCASD': 4, 'BIAS15_VCASN': 25, 'BIAS15_VCASP': 4, 'BIAS15_VINREF': 7, 'BIAS15_VREF_LDO': 1, 'BIAS1_BGR_MEAN': 3, 'BIAS1_BGR_SLOPE': 7, 'BIAS1_IBIAS': 2, 'BIAS1_ICLIP': 1, 'BIAS1_ID': 1, 'BIAS1_IFB': 2, 'BIAS1_IOTA': 0, 'BIAS1_ISF': 2, 'BIAS1_ISF_VINREF': 7, 'BIAS1_LDO_EN': 1, 'BIAS1_VCAL_HI': 0, 'BIAS1_VCAL_LO': 1, 'BIAS1_VCASD': 4, 'BIAS1_VCASN': 25, 'BIAS1_VCASP': 4, 'BIAS1_VINREF': 7, 'BIAS1_VREF_LDO': 1, 'BIAS2_BGR_MEAN': 5, 'BIAS2_BGR_SLOPE': 7, 'BIAS2_IBIAS': 2, 'BIAS2_ICLIP': 1, 'BIAS2_ID': 1, 'BIAS2_IFB': 2, 'BIAS2_IOTA': 0, 'BIAS2_ISF': 2, 'BIAS2_ISF_VINREF': 7, 'BIAS2_LDO_EN': 1, 'BIAS2_VCAL_HI': 0, 'BIAS2_VCAL_LO': 1, 'BIAS2_VCASD': 4, 'BIAS2_VCASN': 25, 'BIAS2_VCASP': 4, 'BIAS2_VINREF': 7, 'BIAS2_VREF_LDO': 1, 'BIAS3_BGR_MEAN': 5, 'BIAS3_BGR_SLOPE': 7, 'BIAS3_IBIAS': 2, 'BIAS3_ICLIP': 1, 'BIAS3_ID': 1, 'BIAS3_IFB': 2, 'BIAS3_IOTA': 0, 'BIAS3_ISF': 2, 'BIAS3_ISF_VINREF': 7, 'BIAS3_LDO_EN': 1, 'BIAS3_VCAL_HI': 0, 'BIAS3_VCAL_LO': 1, 'BIAS3_VCASD': 4, 'BIAS3_VCASN': 25, 'BIAS3_VCASP': 4, 'BIAS3_VINREF': 7, 'BIAS3_VREF_LDO': 1, 'BIAS4_BGR_MEAN': 4, 'BIAS4_BGR_SLOPE': 7, 'BIAS4_IBIAS': 2, 'BIAS4_ICLIP': 1, 'BIAS4_ID': 1, 'BIAS4_IFB': 2, 'BIAS4_IOTA': 0, 'BIAS4_ISF': 2, 'BIAS4_ISF_VINREF': 7, 'BIAS4_LDO_EN': 1, 'BIAS4_VCAL_HI': 0, 'BIAS4_VCAL_LO': 1, 'BIAS4_VCASD': 4, 'BIAS4_VCASN': 25, 'BIAS4_VCASP': 4, 'BIAS4_VINREF': 7, 'BIAS4_VREF_LDO': 1, 'BIAS5_BGR_MEAN': 5, 'BIAS5_BGR_SLOPE': 7, 'BIAS5_IBIAS': 2, 'BIAS5_ICLIP': 1, 'BIAS5_ID': 1, 'BIAS5_IFB': 2, 'BIAS5_IOTA': 0, 'BIAS5_ISF': 2, 'BIAS5_ISF_VINREF': 7, 'BIAS5_LDO_EN': 1, 'BIAS5_VCAL_HI': 0, 'BIAS5_VCAL_LO': 1, 'BIAS5_VCASD': 4, 'BIAS5_VCASN': 25, 'BIAS5_VCASP': 4, 'BIAS5_VINREF': 7, 'BIAS5_VREF_LDO': 1, 'BIAS6_BGR_MEAN': 5, 'BIAS6_BGR_SLOPE': 7, 'BIAS6_IBIAS': 2, 'BIAS6_ICLIP': 1, 'BIAS6_ID': 1, 'BIAS6_IFB': 2, 'BIAS6_IOTA': 0, 'BIAS6_ISF': 2, 'BIAS6_ISF_VINREF': 7, 'BIAS6_LDO_EN': 1, 'BIAS6_VCAL_HI': 0, 'BIAS6_VCAL_LO': 1, 'BIAS6_VCASD': 4, 'BIAS6_VCASN': 25, 'BIAS6_VCASP': 4, 'BIAS6_VINREF': 7, 'BIAS6_VREF_LDO': 1, 'BIAS7_BGR_MEAN': 5, 'BIAS7_BGR_SLOPE': 7, 'BIAS7_IBIAS': 2, 'BIAS7_ICLIP': 1, 'BIAS7_ID': 1, 'BIAS7_IFB': 2, 'BIAS7_IOTA': 0, 'BIAS7_ISF': 2, 'BIAS7_ISF_VINREF': 7, 'BIAS7_LDO_EN': 1, 'BIAS7_VCAL_HI': 0, 'BIAS7_VCAL_LO': 1, 'BIAS7_VCASD': 4, 'BIAS7_VCASN': 25, 'BIAS7_VCASP': 4, 'BIAS7_VINREF': 7, 'BIAS7_VREF_LDO': 1, 'BIAS8_BGR_MEAN': 9, 'BIAS8_BGR_SLOPE': 7, 'BIAS8_IBIAS': 2, 'BIAS8_ICLIP': 1, 'BIAS8_ID': 1, 'BIAS8_IFB': 2, 'BIAS8_IOTA': 0, 'BIAS8_ISF': 2, 'BIAS8_ISF_VINREF': 7, 'BIAS8_LDO_EN': 1, 'BIAS8_VCAL_HI': 0, 'BIAS8_VCAL_LO': 1, 'BIAS8_VCASD': 4, 'BIAS8_VCASN': 25, 'BIAS8_VCASP': 4, 'BIAS8_VINREF': 7, 'BIAS8_VREF_LDO': 1, 'BIAS9_BGR_MEAN': 6, 'BIAS9_BGR_SLOPE': 7, 'BIAS9_IBIAS': 2, 'BIAS9_ICLIP': 1, 'BIAS9_ID': 1, 'BIAS9_IFB': 2, 'BIAS9_IOTA': 0, 'BIAS9_ISF': 2, 'BIAS9_ISF_VINREF': 7, 'BIAS9_LDO_EN': 1, 'BIAS9_VCAL_HI': 0, 'BIAS9_VCAL_LO': 1, 'BIAS9_VCASD': 4, 'BIAS9_VCASN': 25, 'BIAS9_VCASP': 4, 'BIAS9_VINREF': 7, 'BIAS9_VREF_LDO': 1, 'DIGITAL_INJECTION': 0, 'DISABLE_SMART_READOUT': 1, 'EOS_CLOCK_GATING_ENABLE': 0, 'FORCE_DISABLE_MASK': 0, 'FORCE_ENABLE_INJECTION': 0, 'HELPER_SECCFG_CFGDATA': 1, 'HELPER_SECCFG_COLUMNS': 1, 'HELPER_SECCFG_PIXELSELECT': 1, 'HELPER_SECCFG_PRSKIP': 0, 'HELPER_SECCFG_PRSTART': 0, 'HELPER_SECCFG_PRSTOP': 0, 'HELPER_SECCFG_SECTIONS': 4, 'LVDS_STRENGTH': 7, 'MAX_READS': 8, 'OPERATION': 0, 'READOUT_CLK_DIVIDER': 3, 'SECTION_CLOCK_GATING': 0, 'SECTION_CLOCK_MASK': 0, 'SECTION_READ_MASK': 0, 'SERIALIZER_SYNC': 0, 'TEST_PULSE_MASK': 0, 'TIMESTAMP_LATCHES': 1, 'TIMING_CLK_DIVIDER': 1, 'TOKEN_COUNTER': 15}","(1, 2, 82, 9, 12, 12, False, 234, 2155505, 0, 2155498, 1)","(1, 8, 81, 8, 12, 12, False, 238, 2155509, 0, 2155502, 1)","(0, 176, 81, 9, 12, 12, False, 234, 2155513, 0, 2155498, 1)","(0, 64, 81, 10, 12, 12, False, 238, 2155517, 0, 2155502, 1)","(0, 48, 1, 15, 5, 5, False, 198, 2159821, 0, 2159814, 2)","(0, 32, 1, 14, 5, 5, False, 198, 2159825, 0, 2159814, 2)","(1, 3, 53, 13, 11, 11, False, 122, 2206081, 0, 2206074, 5)","(1, 1, 53, 14, 11, 11, False, 130, 2206089, 0, 2206082, 5)","(0, 64, 52, 14, 11, 11, False, 130, 2206093, 0, 2206082, 5)","(1, 60, 11, 14, 11, 11, False, 98, 2210921, 0, 2210914, 6)","(0, 224, 11, 13, 11, 11, False, 102, 2210925, 0, 2210918, 6)"

Time elapsed: 5.06
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<class 'numpy.ndarray'>
Dimensione su disco: 1175.71 Mb