Hi Peter,
I am now in the process of releasing relax 1.3.10 which will appear on
http://nmr-relax.com by next Monday. This version has support for
reading the PDC files. If there are additional problems with reading
newer versions of the PDC files (>= 1.1.5), then I'll add these files
to the test suite, fix the issues, and make a new release.
I have also performed some checks to make sure that everything is
running ok, and stumbled across an interesting difference between
relax and the PDC's error analysis. I have used the peak heights and
errors from the R1 data file (testT1.txt version 1.1.5) and
re-performed optimisation and Monte Carlo simulations in relax using
this. I was trying to make sure that I convert the Tx errors
correctly to Rx errors. However there are quite some differences. I
have copied and pasted the print out from the script below. As you
can see at the end, the PDC/relax ratio for the fitted Rx values are
almost the same. However the PDC/relax ratio for the Rx errors vary
quite a lot. To compare, I have taken the PDC T1 and T1 errors and
used the formula:
sigma_R1 = (sigma_T1 / scale) / T1^2.
This is then compared to the relax MC error estimates. All of data
and scripts are in the directory 'test_suite/shared_data/pdc_files/'
in the relax 1.3 main line for reference. Would you know what the
issue could be? I think we need to look into this one very carefully.
Regards,
Edward
P. S. Here is the script print out:
[edward@localhost pdc_files]$ relax convert_data.py
relax repository checkout
Molecular dynamics by NMR data analysis
Copyright (C) 2001-2006 Edward d'Auvergne
Copyright (C) 2006-2011 the relax development team
This is free software which you are welcome to modify and redistribute
under the conditions of the
GNU General Public License (GPL). This program, including all
modules, is licensed under the GPL
and comes with absolutely no warranty. For details type 'GPL' within
the relax prompt.
Assistance in using the relax prompt and scripting interface can be
accessed by typing 'help' within
the prompt.
script = 'convert_data.py'
----------------------------------------------------------------------------------------------------
#! /usr/bin/env python
# The data - PDC T2, PDC T2 err, PDC scale factor, relax R2, relax R2
err (MC sim).
data = [
['Gln', 2, 0.4560, 0.0055642, 2.22814 , 2.19316068443,
0.0264822775112],
['Ile', 3, 0.4289, 0.0040993, 2.22814 , 2.33150942395,
0.0218282475286],
['Phe', 4, 0.4259, 0.0058593, 2.22814 , 2.34809773828,
0.0393993956573],
['Val', 5, 0.4447, 0.0078459, 2.22814 , 2.24905317514,
0.0190416227806],
['Lys', 6, 0.4388, 0.0068723, 2.22814 , 2.27991249993,
0.0073387122964],
['Thr', 7, 0.4504, 0.0077632, 2.22814 , 2.21988325334,
0.0289980021014],
['Leu', 8, 0.4465, 0.011841 , 2.22814, 2.23992585719,
0.0394637142884],
['Thr', 9, 0.5082, 0.018350 , 2.22814, 1.96827404586,
0.0285585555608],
['Gly', 10, 0.4790, 0.011883 , 2.22814, 2.08825352037,
0.00856203608884],
['Lys', 11, 0.5007, 0.011447 , 2.22814, 1.99766965295,
0.0154821098023],
['Thr', 12, 0.4621, 0.013991 , 2.22814, 2.16418266589,
0.0589894950385],
['Ile', 13, 0.4401, 0.0074423, 2.22814 , 2.27249997894,
0.0323797055027],
['Thr', 14, 0.4548, 0.0067366, 2.22814 , 2.19913359459,
0.0261282530191],
['Leu', 15, 0.4387, 0.0095755, 2.22814 , 2.27947735732,
0.0804008170395],
['Glu', 16, 0.4793, 0.013166 , 2.22814, 2.08663871613,
0.0742976416989],
['Val', 17, 0.4378, 0.0045095, 2.22814 , 2.28454679926,
0.0319478148557],
['Glu', 18, 0.4744, 0.0084630, 2.22814 , 2.10794161516,
0.0491390514111],
['Ser', 20, 0.4459, 0.0078165, 2.22814 , 2.2432376545,
0.0174075720472],
['Asp', 21, 0.4256, 0.0058344, 2.22814 , 2.34905882789,
0.00896916086091],
['Thr', 22, 0.4396, 0.0069851, 2.22814 , 2.27492782819,
0.0283784241729],
['Ile', 23, 0.4054, 0.011480 , 2.22814, 2.46692508258,
0.0512139594604],
['Asn', 25, 0.4175, 0.0053666, 2.22814 , 2.39550908267,
0.028141856637],
['Val', 26, 0.4688, 0.015471 , 2.22814, 2.13297271051,
0.0738836932379],
['Lys', 27, 0.4233, 0.0059289, 2.22814 , 2.36245343286,
0.034473000886],
['Ala', 28, 0.4193, 0.0056136, 2.22814 , 2.38481618154,
0.0369276054641],
['Lys', 29, 0.4298, 0.0061273, 2.22814 , 2.32688199592,
0.0267154381038],
['Thr', 30, 0.4132, 0.010655 , 2.22814, 2.42020223098,
0.0641345037416],
['Gln', 31, 0.4216, 0.0066747, 2.22814 , 2.37198006924,
0.0607157552927],
['Asp', 32, 0.4268, 0.0093311, 2.22814 , 2.343030317,
0.0287089229986],
['Lys', 33, 0.4560, 0.0035919, 2.22814 , 2.19288519999,
0.0322404521468],
['Glu', 34, 0.4468, 0.0039100, 2.22814 , 2.23809730593,
0.016155226898],
['Gly', 35, 0.4452, 0.0042318, 2.22814 , 2.24610605696,
0.0166231784999],
['Ile', 36, 0.5023, 0.0092235, 2.22814 , 1.99097003714,
0.018556395961],
['Asp', 39, 0.4360, 0.0059373, 2.22814 , 2.29368308937,
0.0107946336402],
['Gln', 40, 0.4435, 0.0036092, 2.22814 , 2.25465715695,
0.0219579437623],
['Gln', 41, 0.4496, 0.0036133, 2.22814 , 2.22439489827,
0.0246838738103],
['Arg', 42, 0.4387, 0.016448 , 2.22814, 2.27979894813,
0.14609662846],
['Leu', 43, 0.4603, 0.0091587, 2.22814 , 2.17239195077,
0.0562093749792],
['Ile', 44, 0.4387, 0.0082883, 2.22814 , 2.27944810393,
0.0274015962376],
['Phe', 45, 0.4413, 0.0052304, 2.22814 , 2.26621382042,
0.0325598012054],
['Ala', 46, 0.4604, 0.016900 , 2.22814, 2.17327103743,
0.0366263114163],
['Gly', 47, 0.4564, 0.010048 , 2.22814, 2.19159971705,
0.0200974396044],
['Lys', 48, 0.4543, 0.013460 , 2.22814, 2.20125816954,
0.0769594227925],
['Gln', 49, 0.4731, 0.0092575, 2.22814 , 2.11409184343,
0.0211565921351],
['Leu', 50, 0.4456, 0.0065931, 2.22814 , 2.24441747047,
0.0466054926297],
['Glu', 51, 0.4687, 0.0064085, 2.22814 , 2.13351495913,
0.0369010861993],
['Asp', 52, 0.4888, 0.0082688, 2.22814 , 2.04583349976,
0.0309251585403],
['Arg', 54, 0.4562, 0.0075315, 2.22814 , 2.19228267695,
0.0125176652031],
['Thr', 55, 0.4396, 0.0066617, 2.22814 , 2.27502074947,
0.0319568936121],
['Leu', 56, 0.4221, 0.0050821, 2.22814 , 2.36913113746,
0.0158844775147],
['Ser', 57, 0.4352, 0.0045934, 2.22814 , 2.29814478201,
0.0142640516301],
['Asp', 58, 0.4207, 0.0047524, 2.22814 , 2.37720483191,
0.0272911357828],
['Tyr', 59, 0.4493, 0.0054211, 2.22814 , 2.22553611629,
0.0125933167265],
['Asn', 60, 0.4377, 0.0042069, 2.22814 , 2.28459962433,
0.013370924242],
['Ile', 61, 0.4270, 0.0066972, 2.22814 , 2.34213728573,
0.0264153868176],
['Gln', 62, 0.5067, 0.0066460, 2.22814 , 1.97367886288,
0.0217945020797],
['Lys', 63, 0.4619, 0.0052284, 2.22814 , 2.16500024708,
0.0195312534223],
['Glu', 64, 0.4312, 0.0037115, 2.22814 , 2.31913930394,
0.0223294049604],
['Ser', 65, 0.4568, 0.0047875, 2.22814 , 2.18918681844,
0.00908363177241],
['Thr', 66, 0.4585, 0.0079772, 2.22814 , 2.18167008464,
0.0112902195625],
['Leu', 67, 0.4410, 0.012010 , 2.22814, 2.26772345178,
0.0444564014823],
['His', 68, 0.4452, 0.0033200, 2.22814 , 2.24680733455,
0.00926065649886],
['Leu', 69, 0.4447, 0.0061155, 2.22814 , 2.24851949133,
0.0379125750722],
['Val', 70, 0.4319, 0.0049952, 2.22814 , 2.31543911345,
0.0279226422469],
['Leu', 71, 0.4596, 0.0071340, 2.22814 , 2.1756894166,
0.00987045835498],
['Arg', 72, 0.4622, 0.0058587, 2.22814 , 2.16361975928,
0.0253849160526],
['Leu', 73, 0.5386, 0.013172 , 2.22814, 1.85657597782,
0.0255460422485],
['Arg', 74, 0.6203, 0.026077 , 2.22814, 1.6122677679,
0.0231001217925],
['Gly', 75, 0.8604, 0.062462 , 2.22814, 1.16243924266,
0.023448186193],
['Gly', 76, 1.310, 0.026787 , 2.22814, 0.763064480891,
0.0030557315479]]
r1 = []
r1_err = []
print("%-4s %-3s %-15s %-15s %-15s %-15s" % ('Name', 'Num', 'r1',
'err', 'r1_relax_ratio', 'err_relax_ratio'))
for i in range(len(data)):
r1.append(1.0/data[i][2])
r1_err.append((data[i][3] / data[i][4]) / data[i][2]**2)
print("%-4s %-3s %15.10f %15.10f %15.10f %15.10f" % (data[i][0],
data[i][1], r1[-1], r1_err[-1], r1[-1]/data[i][5],
r1_err[-1]/data[i][6]))
print("\nr1 = %s" % r1)
print("\nr1_err = %s" % r1_err)
----------------------------------------------------------------------------------------------------
Name Num r1 err r1_relax_ratio
err_relax_ratio
Gln 2 2.1929824561 0.0120096561 0.9999187345
0.4534978569
Ile 3 2.3315458149 0.0100012696 1.0000156083
0.4581801445
Phe 4 2.3479690068 0.0144973285 0.9999451763
0.3679581436
Val 5 2.2487069935 0.0178059863 0.9998460767
0.9351086556
Lys 6 2.2789425706 0.0160186679 0.9995745761
2.1827627541
Thr 7 2.2202486679 0.0171751894 1.0001646098
0.5922887162
Leu 8 2.2396416573 0.0266564910 0.9998731209
0.6754683762
Thr 9 1.9677292405 0.0318877790 0.9997232065
1.1165753452
Gly 10 2.0876826722 0.0232440925 0.9997266385
2.7147856256
Lys 11 1.9972039145 0.0204924566 0.9997668591
1.3236217091
Thr 12 2.1640337589 0.0294058911 0.9999311948
0.4984936905
Ile 13 2.2722108612 0.0172449508 0.9998727755
0.5325851656
Thr 14 2.1987686895 0.0146169706 0.9998340687
0.5594316083
Leu 15 2.2794620470 0.0223297426 0.9999932834
0.2777302944
Glu 16 2.0863759649 0.0257215134 0.9998740792
0.3461955559
Val 17 2.2841480128 0.0105592823 0.9998254418
0.3305165742
Glu 18 2.1079258010 0.0168768933 0.9999924978
0.3434517522
Ser 20 2.2426553039 0.0176439132 0.9997403973
1.0135769158
Asp 21 2.3496240602 0.0144560781 1.0002406207
1.6117536917
Thr 22 2.2747952684 0.0162223880 0.9999417301
0.5716451318
Ile 23 2.4666995560 0.0313495942 0.9999085799
0.6121298679
Asn 25 2.3952095808 0.0138179556 0.9998749736
0.4910108005
Val 26 2.1331058020 0.0315937156 1.0000623972
0.4276141899
Lys 27 2.3623907394 0.0148502961 0.9999734626
0.4307804867
Ala 28 2.3849272597 0.0143301014 1.0000465772
0.3880593182
Lys 29 2.3266635644 0.0148865427 0.9999061270
0.5572262233
Thr 30 2.4201355276 0.0280085324 0.9999724389
0.4367155083
Gln 31 2.3719165085 0.0168534211 0.9999732035
0.2775790398
Asp 32 2.3430178069 0.0229901363 0.9999946607
0.8008010732
Lys 33 2.1929824561 0.0077526839 1.0000443508
0.2404644904
Glu 34 2.2381378693 0.0087903861 1.0000181240
0.5441202529
Gly 35 2.2461814915 0.0095823570 1.0000335846
0.5764455346
Ile 36 1.9908421262 0.0164069147 0.9999357545
0.8841649395
Asp 39 2.2935779817 0.0140175960 0.9999541751
1.2985707981
Gln 40 2.2547914318 0.0082353341 1.0000595544
0.3750503341
Gln 41 2.2241992883 0.0080224855 0.9999120615
0.3250091764
Arg 42 2.2794620470 0.0383561805 0.9998522233
0.2625398058
Leu 43 2.1724961981 0.0194003430 1.0000479874
0.3451442578
Ile 44 2.2794620470 0.0193280357 1.0000061168
0.7053616691
Phe 45 2.2660321777 0.0120538164 0.9999198475
0.3702054675
Ala 46 2.1720243267 0.0357827405 0.9994263436
0.9769681729
Gly 47 2.1910604733 0.0216494007 0.9997539497
1.0772218339
Lys 48 2.2011886419 0.0292696218 0.9999684146
0.3803253812
Gln 49 2.1137180300 0.0185628797 0.9998231801
0.8774040520
Leu 50 2.2441651706 0.0149024208 0.9998875878
0.3197567495
Glu 51 2.1335609132 0.0130925429 1.0000215391
0.3548010173
Asp 52 2.0458265139 0.0155323661 0.9999965853
0.5022566356
Arg 54 2.1920210434 0.0162415863 0.9998806570
1.2974932631
Thr 55 2.2747952684 0.0154713150 0.9999008884
0.4841307536
Leu 56 2.3691068467 0.0128017702 0.9999897470
0.8059295738
Ser 57 2.2977941176 0.0108846387 0.9998474142
0.7630818348
Asp 58 2.3769907297 0.0120510666 0.9999099353 0.4415743901
Tyr 59 2.2256843980 0.0120523603 1.0000666274 0.9570441654
Asn 60 2.2846698652 0.0098552267 1.0000307454 0.7370639871
Ile 61 2.3419203747 0.0164852312 0.9999073876 0.6240768439
Gln 62 1.9735543714 0.0116175902 0.9999369242 0.5330514163
Lys 63 2.1649707729 0.0109984227 0.9999863861 0.5631191428
Glu 64 2.3191094620 0.0089587927 0.9999871323 0.4012105415
Ser 65 2.1891418564 0.0102970808 0.9999794618 1.1335863312
Thr 66 2.1810250818 0.0170305756 0.9997043536 1.5084361698
Leu 67 2.2675736961 0.0277155405 0.9999339621 0.6234319383
His 68 2.2461814915 0.0075177053 0.9997214523 0.8117896720
Leu 69 2.2487069935 0.0138789061 1.0000833892 0.3660765864
Val 70 2.3153507756 0.0120183265 0.9999618484 0.4304150871
Leu 71 2.1758050479 0.0151576052 1.0000531470 1.5356536249
Arg 72 2.1635655560 0.0123083235 0.9999749479 0.4848676073
Leu 73 1.8566654289 0.0203787034 1.0000481807 0.7977244855
Arg 74 1.6121231662 0.0304166646 0.9999103116 1.3167317865
Gly 75 1.1622501162 0.0378680208 0.9998373021 1.6149658876
Gly 76 0.7633587786 0.0070054980 1.0003856787 2.2925763776
Addition of PDC support to relax 1.3.10 and an inconsistency in the error calculation.