If I do it for the first spin:
cdp.mol[0].res[0].spin[0].dw_sim
import numpy as np
a = np.array([0.9451997476845593, 0.8054522239552819, 0.9277366066500237,
0.9625036075584432, 0.8802059033496906, 0.9972921559805459,
0.8743682211305104, 0.9500671171775412, 0.9155241775057494,
0.9468124355863968, 0.96417019553941, 1.0170148731646576,
0.808583141857603, 0.9101215951359578, 0.950865223270674,
1.0307772448494004, 0.8993891518585049, 0.9139606433668193,
0.956733004106492, 0.8978513006468936, 0.9453834676054009,
0.910827776695774, 0.8808826708447804, 0.9260230255021042,
0.9502172231153962, 0.86537440977864, 0.8859323973019857,
0.8893764312486083, 0.9731605295027338, 1.0041329485057724,
0.9484007034626689, 0.8562407086263037, 0.8949760705986323,
0.9494159177232087, 0.9536607612740096, 0.981423499818791,
0.8795248912995862, 0.9703162419092174, 0.9498731423252795,
0.8766210928540752, 0.8716559260505473, 0.9697324548237327,
0.8330252500434963, 0.9463453433710509, 0.8936136907056889,
0.9393334443985975, 0.9310091998291463, 0.9409086436225335,
0.9194230869394555, 0.9150169906828444, 0.937755163159723,
0.821586577578577, 0.8844807208799657, 0.9509710398156324,
0.9244476893902771, 0.8912100177428832, 0.8667907082691229,
0.8523582565296183, 0.911207452505568, 0.8546152190640066,
0.8797463442344267, 0.932394336758319, 0.965515026672257,
0.8967984708313228, 0.9562847792473697, 0.9662836189055034,
0.9187032714923455, 0.9552991998159039, 0.8721372679559742,
0.951677098087865, 0.970701220083394, 0.880277858875798,
0.8868837879487532, 0.8289936757848054, 0.8452643978000389,
0.8608520989786752, 0.9408859834978103, 0.9477671884481794,
0.9355182739828974, 0.9058402170229929, 0.888170996310456,
0.8872799805467638, 0.872024994152445, 0.8802787599729809,
0.9527566512472332, 0.8864763874519584, 0.8436371510886024,
0.9828573401629994, 0.9771419297773668, 0.9060195555424908,
0.9707157553507724, 0.879689193482642, 0.9436375392843368,
0.9927180210208233, 0.9267041637380232, 0.9412299434835303,
0.926346676233505, 0.8774254634406635, 0.8826805167518188,
0.8865687070701256, 0.9512379465525047, 0.9641813779931143,
0.953277273069755, 1.0047488071722177, 0.8521615788684946,
0.8680916457728691, 0.9340561986882852, 0.9477037339014749,
0.9469454099421577, 0.9005897924118794, 0.8803998440278067,
0.9024692253200567, 0.909122984887152, 0.8399468552579564,
0.9571308078096232, 0.9683939646310176, 0.9419649402214831,
0.9613040120941247, 0.9781781986426726, 0.9805816556476108,
0.94937687356695, 0.960693374108915, 0.9530824549428941,
0.8843910508664925, 0.8945735422767003, 0.9049315573495563,
0.8802084472126279, 0.8328713211676385, 0.9406572364992218,
0.910325290850831, 0.9318781551216802, 0.8934350965988851,
0.8353799932488288, 0.951313819820305, 0.855414485205892,
0.909767822028357, 0.8924203614902587, 0.9408505916987862,
0.8751269857340623, 0.9388220465429999, 0.9499696867836579,
0.9605708328530759, 0.9054195520491586, 0.8859714100727238,
0.9305256454920723, 0.937758620326129, 0.9320519159136575,
0.9656009544636446, 0.9584255887448183, 0.8738507316066699,
0.9661737748832995, 0.8717799481773607, 0.959731591608098,
0.9640387155993229, 0.8600096309525227, 0.8762991916520275,
0.9329290121054334, 0.838440295115923, 0.8399242891708862,
0.8145405034437483, 0.961537851810333, 0.9430802765990043,
0.9358230046912992, 0.9359556594347389, 0.9553690216306725,
0.9943161816393639, 0.9823102347443102, 0.9586429773877578,
0.9599901351410914, 0.9229179343561751, 0.9481274587922217,
0.8970870418193109, 0.9940991138386224, 0.8321641241392229,
0.820820360597734, 0.9239612738883967, 0.8028677971498746,
0.9470524563800362, 0.8770948453727446, 0.8786234926518741,
0.9500563596927654, 0.9425646627827216, 0.9813509472882151,
0.8963925974037248, 0.9665748645186323, 0.9481002238259164,
0.9762925493355714, 0.9448903713592451, 0.8703265705873551,
0.9615577958883464, 0.9507772932563718, 0.8694530133244274,
0.9551720951577658, 0.9601529698972405, 0.8265749162591152,
0.8877938702538734, 0.9300041468281581, 0.9190766932800695,
0.8777912273883446, 0.8296984188149442, 0.8758324948849263,
0.9638111876579756, 0.8717796834493945, 0.8781824620184063,
0.9292229859457032, 0.9631461440984229, 0.8855046691390046,
0.9116243504655235, 0.9687775465275965, 0.9743721132160679,
0.8765056908708677, 0.7816886178045854, 0.790022742686771,
0.9593793091277658, 0.9803752894894269, 0.8352973629093705,
0.8775207642505513, 0.9680040806307247, 0.908234130574229,
0.900942944747484, 0.933641001393801, 0.8924035170601451,
0.9169964871487871, 0.9583231080403987, 0.9542419125192333,
0.9390001439256719, 0.8323987419607359, 0.8403481568766829,
0.9570952512572252, 0.9415894364990589, 0.9420935133016923,
0.9672157901774194, 0.9461672394692229, 0.8955333476227065,
0.8225999305208208, 0.9059140446636067, 0.8408297028056471,
0.8782230260026257, 0.8329068600700191, 0.9501153345379366,
0.8525250463704599, 0.8930388826261108, 0.9583253299772412,
0.9748914949547898, 1.0149052172216142, 0.9389789372888069,
0.9337360405670624, 0.9327486416577837, 0.8682063500699172,
0.9396962725697757, 0.9244651664429935, 0.886634688707868,
0.934683578566043, 0.8846313267323913, 0.9140693547592385,
0.8960639175715508, 0.8957103073469439, 0.9618246176869939,
0.8800243097899317, 0.8358867841795912, 0.96157189548614,
0.8946748865039788, 0.9381963688628534, 0.8991021512665122,
0.9630989549147373, 1.0306271099454114, 0.8337907334776982,
0.8846817843039123, 0.8805438134285963, 0.8696011129927964,
0.8719446260141073, 0.9004969634936539, 0.957584654370097,
0.9741661107810871, 0.9743728353528538, 0.8978825299830381,
0.9348185063132597, 0.8789973416985811, 0.8651956968215125,
0.8827993798954048, 0.9654395533531213, 0.9717461307314912,
1.0135164470868605, 0.9149878946315309, 0.9628964038776808,
0.9307651980454417, 0.9357475193756133, 0.9677094795088932,
0.9538313088924631, 0.9775629520444014, 0.9354738721873824,
0.9566141851895558, 0.950953965012808, 0.9216788258347537,
0.8682166523275501, 0.9766660718306558, 0.9619591071153,
0.9451470061016918, 0.9928201921068524, 0.9985660139540029,
0.9191885285393425, 1.00064688514426, 0.8558150042354784,
0.9523984521354733, 0.9044870522827702, 0.9551604948863599,
0.956139128930233, 0.874885369922159, 0.9421867676209141,
0.9458194390961585, 0.9351938237072461, 0.9239825599538652,
0.9533742856448693, 0.959334847126333, 0.8712202628516148,
0.8868809039562306, 0.9394536377556304, 0.917736337996731,
0.8750099638116768, 0.9146944568892723, 0.817809005996513,
0.9353847716979621, 0.9710236165888657, 0.8658949203638375,
0.9281632272709377, 0.8380083701097822, 0.9514045399217044,
0.9268547152541529, 0.988314421412019, 0.8711882008696186,
0.9466477576850298, 0.98955480948684, 0.9282670795120422,
0.9707321802517554, 0.96179659242783, 0.9370051655892183,
0.9255924842310339, 0.9447461288560601, 0.8673433469216435,
0.8669079644533857, 0.9734485868678899, 0.8478218447278388,
0.9861321262922089, 0.9355809012897522, 0.8228120965648424,
0.8810580429527199, 0.9313603863999176, 0.9637081606452766,
0.9589972995901423, 0.9605175311239016, 0.9457353902816623,
0.9689992784081013, 0.969326610272077, 0.9306832636419429,
0.8895400069646056, 0.930267535398837, 1.016583891414082,
0.9104770446926943, 0.9631821642637364, 0.90657672405395,
0.8864471501590206, 0.9543482415184957, 0.9688298224105104,
0.9701195266730105, 0.9014281299869491, 0.9400344204417157,
0.8020451311726335, 0.9732727263061483, 0.9257744252944384,
0.8930361674653782, 0.9077514541086867, 0.9563024200699006,
0.9673603350679845, 0.9353113972743984, 0.9202859738705844,
0.931181180546891, 0.9575673626164821, 0.9671631168062729,
0.9685182521461788, 0.9619858410387789, 0.9512552739154172,
0.8697026381537316, 0.9422935309867227, 0.9271009551086151,
0.8760172657400351, 0.8923310171669755, 0.9560007244086678,
0.9176169472096192, 0.8570018945581233, 0.8678541844200598,
0.9503477866568958, 0.8888610772905267, 0.8824425718910942,
0.9852708572264075, 0.8875991268888754, 0.9498340419798412,
0.9536127998490802, 0.9492090546722824, 0.9689693913824984,
0.9362417464095366, 0.966299200302192, 0.9721497865946775,
0.8933339119605521, 0.9428166198085944, 0.8305143098064691,
0.9283439969920211, 0.8907740121188827, 0.877936154189384,
0.8596408854774868, 0.8309890750830218, 0.9286508994405575,
0.9211233726975172, 0.9883191332146377, 0.9832672211863914,
0.9305869089271899, 0.8840803912090848, 0.88957856489226,
0.9530487538660497, 0.9152986660064438, 0.9231067960182588,
0.9959078592665846, 0.871518452768852, 0.8787627955325459,
0.9441495017182309, 1.0160497450818742, 0.9633532372322091,
0.9484302692006568, 0.922382212854596, 0.8949436816354353,
0.942360596140404, 0.889446292922918, 1.0043832324206474,
0.9673071097227514, 0.843127561172194, 0.9779230212341419,
0.9818048373130641, 0.8996073352908409, 0.873289112664652,
0.8699224213105194, 0.8753156380643405, 0.9608400284362808,
0.8819200861846517, 0.9454018354081715, 0.9290623356315197,
0.9046541238982699, 0.9900032521469266, 0.9568191623768304,
0.9780628192993167, 0.9092553357362723, 0.9812194210515344,
0.9624981864792568, 0.8230748066065992, 0.9744753772604806,
0.9048371833212552, 0.9107424524010674, 0.9296167548573961,
0.8787732935358206, 0.9744599520825077, 0.9712798367599296,
0.9776193878640571, 0.9939048581261195, 0.9330742502301856,
0.9344137014644689, 0.8972382492830351, 1.0435614793556311,
0.986074313274093, 0.8566407607795148, 0.9411256955747267,
0.8861687481250582, 0.9585202008402863, 0.9518496263389327,
0.8246356022039467, 0.9225621662287964, 0.9745017636377904,
0.9212490357250713, 0.8845246546981802, 0.871521421114521,
0.9762919408389895, 0.8735394131940821, 0.9118838378962291,
0.8823742739518485, 0.9460894234186342, 0.9336960184448355,
0.9436407275870633, 0.8540496846977848, 0.9635667520050752,
0.9450693822302689, 0.8862405570696326, 0.8909100552767579,
0.9640289360980878, 0.9094496144496429, 0.9113646255093484,
0.9022477682066261, 0.9719013909880769, 0.9535100151752098,
0.9429493098274335, 0.9837187230878975, 0.9666334534020062,
0.9553935035880392, 0.9686574004464])
print len(a)
print np.std(a, ddof=1)
I get:
500
0.0468277753385
which is exactly
cdp.mol[0].res[0].spin[0].dw_err
0.046827775338478594
I think the error is in:
specific_analyses.relax_disp/api.sim_return_param()
# Convert the parameter index.
if model_param:
param_name, si, mi = param_index_to_param_info(index=index,
spins=spins)
if not param_name in ['r2eff', 'i0']:
si = 0
else:
param_name = aux_params[index - total_param_num]
si = 0
mi = 0
...............
# Model and auxiliary parameters.
else:
sim_data = getattr(spins[si], param_name + "_sim")
Since si = 0, it takes dw values from initial spin, and uses this as error
for all spins.
I note the same behaviour for r2.
Best
Troels
Troels Emtekær Linnet
2015-01-14 13:20 GMT+01:00 Troels Emtekær Linnet <tlinnet@xxxxxxxxx>:
If I isolate the sim dw
cdp.mol[0].res[81].spin[0].dw_sim
Copy output from prompt to small test.py file.
---------------
import numpy as np
a = np.array([3.56199604639644, 3.7650948468782706, 3.7734884987727297,
3.642139129321543, 3.7666853635523303, 3.6315803417395633,
3.548618513663966, 3.5534026300790322, 3.6560050261342427,
3.559393613964833, 3.643742783984535, 3.8417557850398145,
3.633261341904902, 3.744204424801951, 3.6023836683438333,
3.629402707080922, 3.538289939828068, 3.853741712706393, 3.592047531696704,
3.6309378185683134, 3.768703169586926, 3.7862087881341924,
3.908928286097882, 3.693988276574685, 3.648907472307944, 3.534075058176779,
3.6270285971623712, 3.616447361371553, 3.518131195735667,
3.5921264889450617, 3.690282977512058, 3.5722828138859173,
3.6947690157713327, 3.353267973165118, 3.661855199312702,
3.7481230080917847, 3.8072741676273836, 3.5717863863755435,
3.82647524415927, 3.638932239485707, 3.8627381794143854,
3.8562874852691067, 3.8251946462546695, 3.718900815941118,
3.669183187562206, 3.6812860050150054, 3.596567337492485,
3.643255044215514, 3.8358609617626023, 3.589885966376562,
3.768422008946675, 3.6442067782560175, 3.5360631161686857,
3.706309147308013, 3.723441628305323, 3.7019914055614977,
3.673276772934729, 3.8785449202641784, 3.7101861781755368,
3.693584107288858, 3.7125564094760852, 3.6762850609584126,
3.8157117257138813, 3.7018158644513677, 3.530279936895104,
3.7009902789169105, 3.5736495381254194, 3.7367811504330666,
3.58979193413104, 3.9020629160458435, 3.8045967460431678,
3.751451216439939, 3.602605771168253, 3.8125873436655437,
3.7304066459719567, 3.545396121222916, 3.7349432336572153,
3.807433568014422, 3.6249325786241045, 3.639882263177061,
3.713199134762557, 3.6579265879166387, 3.6505364404873917,
3.7071566660282587, 3.691216327566044, 3.5966085864962483,
3.569229413366312, 3.5970618547062214, 3.6139477602545846,
3.742589813924136, 3.6080539317067366, 3.7445704966176265,
3.6052692253220435, 3.6939619008140188, 3.7352649601924823,
3.6882917261309167, 3.6430935861383418, 3.7128272377377862,
3.6392872820121713, 3.7835114014256046, 3.529329678378972,
3.666044605642382, 3.7284970021608967, 3.553633430947111,
3.768663233026153, 3.656077156065453, 3.6392136075179025,
3.5527517958434065, 3.627428688176744, 3.7004280072046627,
3.606779732841823, 3.5855768696462915, 3.817869184320143,
3.897885555994164, 3.4768562505555316, 3.678791336542599,
3.6809169528168866, 3.5212931732732358, 3.80645768572404,
3.5336477461052613, 3.6055908654129603, 3.689528484460423,
3.6505212536967067, 3.8323529554109808, 3.6858933288476177,
3.6759299817767026, 3.6610567688519535, 3.7860845954799114,
3.6603458115022933, 3.7785578086603673, 3.902354668299148,
3.8055861482832816, 3.682400719521998, 3.6940814556366712,
3.6252208208592855, 3.759148584942981, 3.586642522840439,
3.7634008748970116, 3.5863527479976023, 3.5813112066676016,
3.733249297200884, 3.680077657973306, 3.8146083646296454,
3.747622934450785, 3.751763729360891, 3.645216312057557, 3.627711031714324,
3.743806087120281, 3.754090422035011, 3.742774232386197,
3.7860885026891733, 3.644920826496917, 3.780760363373208,
3.740365533825603, 3.669239475114871, 3.749224549998295, 3.750666913036093,
3.5569128940937507, 3.6333489712976688, 3.572262098541855,
3.711118004907809, 3.452706649658693, 3.558697797848791,
3.6025802917377066, 3.51208420919845, 3.5302665430394917, 3.55047412533738,
3.620294642920974, 3.7125150288399498, 3.6550041859736337,
3.603145954616103, 3.7121712828648894, 3.7333345721954085,
3.9019178238038044, 3.5780488310855305, 3.8083092600730017,
3.797783381443727, 3.7111414020359574, 3.768926895445126,
3.6076613938570112, 3.7389296153778795, 3.726560063335822,
3.7349172940580706, 3.6785139220194587, 3.8411499268808766,
3.651622883456889, 3.669203921911223, 3.595015138849902, 3.756782584819988,
3.6087945157651538, 3.7396909764952793, 3.611396900111491,
3.59007961047317, 3.5640398983331147, 3.6920519200575312,
3.738990802773734, 3.774977105422998, 3.721857153491999, 3.592398274058418,
3.8000979011525677, 3.6825876372773974, 3.6140358720411974,
3.7201112308069213, 3.5927342724618354, 3.742712877741823,
3.6514875821852755, 3.705261957243619, 3.628437422517394, 3.68329564116722,
3.5175049987405984, 3.599320535174879, 3.6935915027553365,
3.5405676308746257, 3.6527910534778965, 3.7256960669886547,
3.5597772960028324, 3.588324588188865, 3.64573890695546, 3.641769060029505,
3.6847044674901315, 3.642884904153416, 3.672823881791987,
3.7555366743294627, 3.595044846478588, 3.787432842343791, 3.69793757478375,
3.5497887067466842, 3.5319876432216883, 3.7990178094267852,
3.7034904333566594, 3.7678442363268303, 3.695625818451896,
3.702246796878483, 3.627921590685772, 3.4555314995683046,
3.510475880439481, 3.834770417574009, 3.7386669597544904,
3.608707401422296, 3.928008814872595, 3.7172939243178775,
3.5347692344509367, 3.6377139413072124, 3.697181566482374,
3.8270903158045617, 3.655938124012822, 3.5783349730929688,
3.545163722671805, 3.763731595802845, 3.827136249693701,
3.5315040544347793, 3.6539082795612003, 3.5504828404335957,
3.5965211896170697, 3.7383453161929863, 3.8230338366087846,
3.627048598848577, 3.648390897416328, 3.68423507795786, 3.731209731198659,
3.4895035362430056, 3.6374449477462196, 3.738202718950397,
3.6189134160348053, 3.8859540817918736, 3.7872602557645987,
3.6839955689687365, 3.7413041452971134, 3.603901617876547,
3.8365540177947937, 3.7158842958686216, 3.2963981313194726,
3.736167469104169, 3.8656069914966777, 3.7262452412039986,
3.724978564948022, 3.6589168669167558, 3.664106608644678,
3.742056188005555, 3.8567680797002497, 3.765771181189931,
3.7689943287070435, 3.634087470863829, 3.7226136514636368,
3.6537406678469733, 3.550330017121598, 3.8165218137921038,
3.6455485509170336, 3.845130518854767, 3.623238757561012,
3.566609365296191, 3.788642967459456, 3.716156258672269, 3.6805685585326,
3.548048892417176, 3.684046186449083, 3.6115550466423936,
3.7476621123455836, 3.7594284275941945, 3.7452154212960886,
3.778755194749163, 3.887944617108257, 3.5735069740281737,
3.7509438004088986, 3.6802535209188845, 3.64948595331264,
3.794517301646539, 3.6217363401946727, 3.775471683046014,
3.5507685750741795, 3.6702260704152847, 3.695832344198455,
3.737069310317808, 3.7364639796791064, 3.8111885735012363,
3.6828799822043363, 3.5905504540568227, 3.824738062392524,
4.042676512808615, 3.6735073333314805, 3.502646786485088,
3.844176767051466, 3.6796980511374544, 3.588035503647361,
3.617966158671891, 3.791087239054204, 3.60013459071069, 3.4973042068514006,
3.759983441435442, 3.627425278628225, 3.7586423436404175,
3.6017727846032477, 3.6484472425828733, 3.600534336317735,
3.868801773923902, 3.6132963094926627, 3.6788670048991268,
3.614449637405996, 3.5368492393788005, 3.6019019213313417,
3.6467572048010997, 3.416116665643858, 3.6882713886175242,
3.9069557842080362, 3.6796414531331094, 3.8916174686851086,
3.596086092442806, 3.774932329507215, 3.574571664292506, 3.714399822595807,
3.6782258762606173, 3.6111452730827622, 3.679108576762216,
3.753721487868907, 3.5303618921775186, 3.8277749029174366,
3.8401522443527094, 3.766379971223831, 3.6861534360317485,
3.5550297044806385, 3.6739038502770414, 3.671772792707439,
3.7338578866741976, 3.754569968976897, 3.738291618674821,
3.7451140911700147, 3.956986996037874, 3.659533650702718,
3.7629087492327002, 3.538961830330332, 3.64945003264093,
3.6754379430144057, 3.6410214735939714, 3.6355416921955594,
3.650130084247056, 3.654990988273896, 3.624597550900315, 3.611857211065539,
3.5212740223065886, 3.715534039331449, 3.714450430519905,
3.7534853922315774, 3.668464964433396, 3.7264569324756964,
3.5004061054556486, 3.636242554227535, 3.6730204013722325,
3.800543800567683, 3.6693157796465687, 3.5991580734901527,
3.617360841067001, 3.6124119625936086, 4.034372797816842,
3.6794178244196103, 3.7755133531239684, 3.652086361675156,
3.6789417844111263, 3.576979494013252, 3.5884566275601917,
3.907720773532597, 3.7366983411875676, 3.7209263704682103,
3.727741858292903, 3.6735954623574854, 3.6064683273770872,
3.527981107053151, 3.709532384633967, 3.6210295410876387,
3.5222801002248936, 3.612588149908407, 3.9935196468741347,
3.558406630946854, 3.617764158289809, 3.7166827125111688,
3.6347100066437212, 3.5441968356273046, 3.5469330782728843,
3.83116335720549, 3.737347598957387, 3.67149813503603, 3.786308325632029,
3.7181623591892983, 3.7649155408666894, 3.57986506214882,
3.763642217619097, 3.8194956188629416, 3.633104627807313,
3.5049092404229816, 3.6440334567798214, 3.5740465357274385,
3.667632546652383, 3.7108995833399225, 3.5434861227460077,
3.6892551147519415, 3.5502672036502476, 3.9151043751681835,
3.606290594298331, 3.690565157572469, 3.6958138113963095,
3.7097713814615805, 3.6545230012906513, 3.947909314488077,
3.6827400672386577, 4.039658211616647, 3.6410235972840623,
3.8449033455834245, 3.6059377230869973, 3.842894876528751,
3.6889860900134384, 3.8657177989633693, 3.8714533897701013,
3.6411304550499013, 3.5798238114264054, 3.6362013746759967,
3.6907899160776374, 3.7807936495026704, 3.80260320682006,
3.6298733640230676, 3.9267717523095103, 3.6307358437695623,
3.8003450781285357, 3.7366534878146145, 3.7110043904097756,
3.509567432311692, 3.6665317876739127, 3.6447054012102953,
3.7787998619198087, 3.7855562737282007, 3.7721213099168542,
3.8644241755674007, 3.799337950076101, 3.660762073429478,
3.5143731438571075, 3.7976485754984743, 3.6487372553885122,
3.79096684551853, 3.6236793979487083, 3.6421440085675076,
3.789013355064313, 3.6557979787054444, 3.936184181631426,
3.952142168637194, 3.667227295171413, 3.7187027458281854,
3.722518742325237, 3.7196252949813475, 3.869233283689267,
3.7411264918088323, 3.6898233820686173, 3.5684404868901165,
3.7151372493402075, 3.6738810532379143, 3.8093362437246796,
3.769659702158876, 3.673148858969734, 3.597894459097, 3.6436104862818874,
3.684957784861707, 3.6154569886122454, 3.6397883716309427])
print len(a)
print np.std(a, ddof=1)
-------
500
0.105036572661
-----------
But the error in relax is:
cdp.mol[0].res[81].spin[0].dw_err
0.046827775338478594
Is there something I am missing here?
Best
Troels
Troels Emtekær Linnet
2015-01-14 13:05 GMT+01:00 Troels Emtekær Linnet <tlinnet@xxxxxxxxx>:
Hi Edward.
When I do an MC simulation of say 500, I get the same error value for dw.
Is this because it goes through all spins, then through all sim states,
and collect the difference, and then do an error calculation?
I would expect, that each dw would have its own error, based on the 500
fittings.
Would this be wrong?
Best
Troels
Troels Emtekær Linnet
Re: Error calculation of individual parameter "dw" from MC