Closed callistosp closed 4 years ago
callistosp
commented
5 years ago Assumption: if multiple estimation methods are used, JSON will contain an array parameter estimates. Default case will be to select results from final estimation method implemented
dpastoor
commented
5 years ago current json output looks as follows:
{
"run_details": {
"version": "7.4.3",
"run_start": "Sat Aug 24 15:34:42 EDT 2019",
"run_end": "Sat Aug 24 15:34:47 EDT 2019",
"estimation_time": 1.74,
"function_evaluations": 366,
"significant_digits": 3.2,
"problem_text": "LEM PK model 1 cmt base",
"estimation_method": [
"First Order Conditional Estimation with Interaction"
],
"data_set": "../acop.csv",
"number_of_patients": 40,
"number_of_obs": 760,
"number_of_data_records": 799
},
"run_heuristics": {},
"parameters_data": [
{
"estimates": {
"theta": [
2.31,
55,
465,
-0.0806,
4.13
],
"omega": [
0.0964,
0,
0.154
],
"sigma": [
1,
0.311,
0,
0.392,
1
]
},
"std_err": {
"theta": [
0.0863,
3.33,
29.6,
0.0555,
1.36
],
"omega": [
0.02,
0,
0.0267
],
"sigma": [
0,
0.0322,
0,
0.0341,
0
]
},
"random_effect_sd": {},
"random_effect_sdse": {}
}
],
"parameter_structures": {
"Theta": 5,
"Omega": [
1,
0,
1
],
"Sigma": [
1
]
},
"parameter_names": {
"theta": [
"KA",
"CL",
"V2",
"RUVp",
"RUVa"
]
},
"ofv": {
"ofv": 1396.7865704711026,
"ofv_no_constant": 2636.846,
"ofv_with_constant": 4033.6323404241416
},
"shrinkage_details": {
"eta": {
"sd": [
17.511,
2.0596
],
"vr": [
31.956,
4.0768
]
},
"ebv": {
"sd": [
18.525,
2.5411
],
"vr": [
33.618,
5.0177
]
},
"eps": {
"sd": [
4.091
],
"vr": [
8.0147
]
}
}
}from the following lst model
Sat Aug 24 15:34:42 EDT 2019
;; 1. Based on:
;; 2. Description: PK model 1 cmt base WT-CL allom
;; x1. Author: devin
$PROBLEM PK model 1 cmt base
$INPUT ID TIME MDV EVID DV AMT SEX WT ETN
$DATA ../acop.csv IGNORE=@
$SUBROUTINES ADVAN2 TRANS2
$PK
ET=1
IF(ETN.EQ.3) ET=1.3
KA = THETA(1)
CL = THETA(2)*((WT/70)**0.75)* EXP(ETA(1))
V = THETA(3)*EXP(ETA(2))
SC=V
$THETA
(0, 2) ; KA
(0, 3) ; CL
(0, 10) ; V2
(0.02) ; RUVp
(1) ; RUVa
$OMEGA
0.05 ; iiv CL
0.2 ; iiv V2
$SIGMA
1 FIX
$ERROR
IPRED = F
IRES = DV-IPRED
W = IPRED*THETA(4) + THETA(5)
IF (W.EQ.0) W = 1
IWRES = IRES/W
Y= IPRED+W*ERR(1)
$EST METHOD=1 INTERACTION MAXEVAL=9999 SIG=3 PRINT=5 NOABORT POSTHOC
$COV
NM-TRAN MESSAGES
WARNINGS AND ERRORS (IF ANY) FOR PROBLEM 1
(WARNING 2) NM-TRAN INFERS THAT THE DATA ARE POPULATION.
License Registered to: Metrum Research Group
Expiration Date: 14 JUL 2020
Current Date: 24 AUG 2019
Days until program expires : 325
1NONLINEAR MIXED EFFECTS MODEL PROGRAM (NONMEM) VERSION 7.4.3
ORIGINALLY DEVELOPED BY STUART BEAL, LEWIS SHEINER, AND ALISON BOECKMANN
CURRENT DEVELOPERS ARE ROBERT BAUER, ICON DEVELOPMENT SOLUTIONS,
AND ALISON BOECKMANN. IMPLEMENTATION, EFFICIENCY, AND STANDARDIZATION
PERFORMED BY NOUS INFOSYSTEMS.
PROBLEM NO.: 1
PK model 1 cmt base
0DATA CHECKOUT RUN: NO
DATA SET LOCATED ON UNIT NO.: 2
THIS UNIT TO BE REWOUND: NO
NO. OF DATA RECS IN DATA SET: 799
NO. OF DATA ITEMS IN DATA SET: 9
ID DATA ITEM IS DATA ITEM NO.: 1
DEP VARIABLE IS DATA ITEM NO.: 5
MDV DATA ITEM IS DATA ITEM NO.: 3
0INDICES PASSED TO SUBROUTINE PRED:
4 2 6 0 0 0 0 0 0 0 0
0LABELS FOR DATA ITEMS:
ID TIME MDV EVID DV AMT SEX WT ETN
0FORMAT FOR DATA:
(E3.0,E5.0,2E2.0,E10.0,E6.0,E2.0,E5.0,E2.0)
TOT. NO. OF OBS RECS: 760
TOT. NO. OF INDIVIDUALS: 40
0LENGTH OF THETA: 5
0DEFAULT THETA BOUNDARY TEST OMITTED: NO
0OMEGA HAS SIMPLE DIAGONAL FORM WITH DIMENSION: 2
0DEFAULT OMEGA BOUNDARY TEST OMITTED: NO
0SIGMA HAS SIMPLE DIAGONAL FORM WITH DIMENSION: 1
0DEFAULT SIGMA BOUNDARY TEST OMITTED: NO
0INITIAL ESTIMATE OF THETA:
LOWER BOUND INITIAL EST UPPER BOUND
0.0000E+00 0.2000E+01 0.1000E+07
0.0000E+00 0.3000E+01 0.1000E+07
0.0000E+00 0.1000E+02 0.1000E+07
-0.1000E+07 0.2000E-01 0.1000E+07
-0.1000E+07 0.1000E+01 0.1000E+07
0INITIAL ESTIMATE OF OMEGA:
0.5000E-01
0.0000E+00 0.2000E+00
0INITIAL ESTIMATE OF SIGMA:
0.1000E+01
0SIGMA CONSTRAINED TO BE THIS INITIAL ESTIMATE
0COVARIANCE STEP OMITTED: NO
EIGENVLS. PRINTED: NO
SPECIAL COMPUTATION: NO
COMPRESSED FORMAT: NO
GRADIENT METHOD USED: NOSLOW
SIGDIGITS ETAHAT (SIGLO): -1
SIGDIGITS GRADIENTS (SIGL): -1
EXCLUDE COV FOR FOCE (NOFCOV): NO
TURN OFF Cholesky Transposition of R Matrix (CHOLROFF): NO
KNUTHSUMOFF: -1
RESUME COV ANALYSIS (RESUME): NO
SIR SAMPLE SIZE (SIRSAMPLE): -1
NON-LINEARLY TRANSFORM THETAS DURING COV (THBND): 1
PRECONDTIONING CYCLES (PRECOND): 0
PRECONDTIONING TYPES (PRECONDS): TOS
FORCED PRECONDTIONING CYCLES (PFCOND):0
PRECONDTIONING TYPE (PRETYPE): 0
FORCED POS. DEFINITE SETTING: (FPOSDEF):0
1DOUBLE PRECISION PREDPP VERSION 7.4.3
ONE COMPARTMENT MODEL WITH FIRST-ORDER ABSORPTION (ADVAN2)
0MAXIMUM NO. OF BASIC PK PARAMETERS: 3
0BASIC PK PARAMETERS (AFTER TRANSLATION):
ELIMINATION RATE (K) IS BASIC PK PARAMETER NO.: 1
ABSORPTION RATE (KA) IS BASIC PK PARAMETER NO.: 3
TRANSLATOR WILL CONVERT PARAMETERS
CLEARANCE (CL) AND VOLUME (V) TO K (TRANS2)
0COMPARTMENT ATTRIBUTES
COMPT. NO. FUNCTION INITIAL ON/OFF DOSE DEFAULT DEFAULT
STATUS ALLOWED ALLOWED FOR DOSE FOR OBS.
1 DEPOT OFF YES YES YES NO
2 CENTRAL ON NO YES NO YES
3 OUTPUT OFF YES NO NO NO
1
ADDITIONAL PK PARAMETERS - ASSIGNMENT OF ROWS IN GG
COMPT. NO. INDICES
SCALE BIOAVAIL. ZERO-ORDER ZERO-ORDER ABSORB
FRACTION RATE DURATION LAG
1 * * * * *
2 4 * * * *
3 * - - - -
- PARAMETER IS NOT ALLOWED FOR THIS MODEL
* PARAMETER IS NOT SUPPLIED BY PK SUBROUTINE;
WILL DEFAULT TO ONE IF APPLICABLE
0DATA ITEM INDICES USED BY PRED ARE:
EVENT ID DATA ITEM IS DATA ITEM NO.: 4
TIME DATA ITEM IS DATA ITEM NO.: 2
DOSE AMOUNT DATA ITEM IS DATA ITEM NO.: 6
0PK SUBROUTINE CALLED WITH EVERY EVENT RECORD.
PK SUBROUTINE NOT CALLED AT NONEVENT (ADDITIONAL OR LAGGED) DOSE TIMES.
0ERROR SUBROUTINE CALLED WITH EVERY EVENT RECORD.
1
#TBLN: 1
#METH: First Order Conditional Estimation with Interaction
ESTIMATION STEP OMITTED: NO
ANALYSIS TYPE: POPULATION
NUMBER OF SADDLE POINT RESET ITERATIONS: 0
GRADIENT METHOD USED: NOSLOW
CONDITIONAL ESTIMATES USED: YES
CENTERED ETA: NO
EPS-ETA INTERACTION: YES
LAPLACIAN OBJ. FUNC.: NO
NO. OF FUNCT. EVALS. ALLOWED: 9999
NO. OF SIG. FIGURES REQUIRED: 3
INTERMEDIATE PRINTOUT: YES
ESTIMATE OUTPUT TO MSF: NO
ABORT WITH PRED EXIT CODE 1: NO
IND. OBJ. FUNC. VALUES SORTED: NO
NUMERICAL DERIVATIVE
FILE REQUEST (NUMDER): NONE
MAP (ETAHAT) ESTIMATION METHOD (OPTMAP): 0
ETA HESSIAN EVALUATION METHOD (ETADER): 0
INITIAL ETA FOR MAP ESTIMATION (MCETA): 0
SIGDIGITS FOR MAP ESTIMATION (SIGLO): 100
GRADIENT SIGDIGITS OF
FIXED EFFECTS PARAMETERS (SIGL): 100
NOPRIOR SETTING (NOPRIOR): OFF
NOCOV SETTING (NOCOV): OFF
DERCONT SETTING (DERCONT): OFF
FINAL ETA RE-EVALUATION (FNLETA): ON
EXCLUDE NON-INFLUENTIAL (NON-INFL.) ETAS
IN SHRINKAGE (ETASTYPE): NO
NON-INFL. ETA CORRECTION (NONINFETA): OFF
RAW OUTPUT FILE (FILE): run002.ext
EXCLUDE TITLE (NOTITLE): NO
EXCLUDE COLUMN LABELS (NOLABEL): NO
FORMAT FOR ADDITIONAL FILES (FORMAT): S1PE12.5
PARAMETER ORDER FOR OUTPUTS (ORDER): TSOL
WISHART PRIOR DF INTERPRETATION (WISHTYPE):0
KNUTHSUMOFF: 0
INCLUDE LNTWOPI: NO
INCLUDE CONSTANT TERM TO PRIOR (PRIORC): NO
INCLUDE CONSTANT TERM TO OMEGA (ETA) (OLNTWOPI):NO
ADDITIONAL CONVERGENCE TEST (CTYPE=4)?: NO
EM OR BAYESIAN METHOD USED: NONE
THE FOLLOWING LABELS ARE EQUIVALENT
PRED=PREDI
RES=RESI
WRES=WRESI
IWRS=IWRESI
IPRD=IPREDI
IRS=IRESI
MONITORING OF SEARCH:
0ITERATION NO.: 0 OBJECTIVE VALUE: 15294.0021441482 NO. OF FUNC. EVALS.: 7
CUMULATIVE NO. OF FUNC. EVALS.: 7
NPARAMETR: 2.0000E+00 3.0000E+00 1.0000E+01 2.0000E-02 1.0000E+00 5.0000E-02 2.0000E-01
PARAMETER: 1.0000E-01 1.0000E-01 1.0000E-01 1.0000E-01 1.0000E-01 1.0000E-01 1.0000E-01
GRADIENT: -1.7140E+03 -3.1290E+03 -1.5123E+03 -9.7238E+03 -1.2685E+05 -8.1552E+03 -5.9227E+03
0ITERATION NO.: 5 OBJECTIVE VALUE: 3740.54126084373 NO. OF FUNC. EVALS.: 43
CUMULATIVE NO. OF FUNC. EVALS.: 50
NPARAMETR: 4.2445E+00 2.0127E+01 1.8445E+01 -6.0458E-03 5.2654E+00 8.6993E-02 8.2997E-01
PARAMETER: 8.5249E-01 2.0034E+00 7.1219E-01 -3.0229E-02 5.2654E-01 3.7690E-01 8.1154E-01
GRADIENT: 1.1708E+02 -3.1565E+02 -3.1209E+02 4.9206E+02 1.1608E+03 -1.5629E+02 -9.9874E+02
0ITERATION NO.: 10 OBJECTIVE VALUE: 3133.06375083444 NO. OF FUNC. EVALS.: 42
CUMULATIVE NO. OF FUNC. EVALS.: 92
NPARAMETR: 5.0079E+00 7.7110E+01 5.0306E+02 -1.3215E-01 6.2545E+00 7.0846E-03 1.5996E-01
PARAMETER: 1.0179E+00 3.3466E+00 4.0181E+00 -6.6074E-01 6.2545E-01 -8.7705E-01 -1.1712E-02
GRADIENT: 5.0046E+02 6.5436E+02 5.5156E+01 -2.5691E+02 -6.6306E+01 -6.2982E+01 1.8658E+01
0ITERATION NO.: 15 OBJECTIVE VALUE: 2648.75702123470 NO. OF FUNC. EVALS.: 57
CUMULATIVE NO. OF FUNC. EVALS.: 149
NPARAMETR: 2.4008E+00 5.3788E+01 3.8275E+02 -7.6997E-02 4.0364E+00 1.1665E-01 2.4380E-01
PARAMETER: 2.8266E-01 2.9864E+00 3.7448E+00 -3.8498E-01 4.0364E-01 5.2356E-01 1.9901E-01
GRADIENT: 6.7725E+01 -4.4322E+00 -6.4813E+01 -9.3945E+00 -1.1678E+02 8.1678E+00 1.5706E+01
0ITERATION NO.: 20 OBJECTIVE VALUE: 2638.50300128957 NO. OF FUNC. EVALS.: 87
CUMULATIVE NO. OF FUNC. EVALS.: 236
NPARAMETR: 2.3053E+00 5.5806E+01 4.7226E+02 -8.0515E-02 4.1259E+00 9.0992E-02 2.0698E-01
PARAMETER: 2.4206E-01 3.0233E+00 3.9549E+00 -4.0258E-01 4.1259E-01 3.9938E-01 1.1714E-01
GRADIENT: 1.6528E+00 8.7972E+00 5.4843E+00 -3.8902E+00 -9.0647E+00 -2.7106E+00 1.9097E+01
0ITERATION NO.: 25 OBJECTIVE VALUE: 2636.87816969085 NO. OF FUNC. EVALS.: 86
CUMULATIVE NO. OF FUNC. EVALS.: 322
NPARAMETR: 2.3130E+00 5.4495E+01 4.6538E+02 -8.0789E-02 4.1361E+00 9.6129E-02 1.5741E-01
PARAMETER: 2.4541E-01 2.9995E+00 3.9403E+00 -4.0395E-01 4.1361E-01 4.2683E-01 -1.9732E-02
GRADIENT: 5.4078E-02 -4.3356E+00 2.2907E-01 5.5046E-01 5.8353E+00 -3.2657E-01 1.7703E+00
0ITERATION NO.: 28 OBJECTIVE VALUE: 2636.84576995304 NO. OF FUNC. EVALS.: 44
CUMULATIVE NO. OF FUNC. EVALS.: 366
NPARAMETR: 2.3103E+00 5.4960E+01 4.6466E+02 -8.0572E-02 4.1303E+00 9.6440E-02 1.5357E-01
PARAMETER: 2.4425E-01 3.0080E+00 3.9387E+00 -4.0286E-01 4.1303E-01 4.2845E-01 -3.2076E-02
GRADIENT: 1.5543E-02 -2.0976E-02 -1.4512E-01 5.8260E-02 -5.3329E-02 -1.8857E-02 3.4097E-03
#TERM:
0MINIMIZATION SUCCESSFUL
NO. OF FUNCTION EVALUATIONS USED: 366
NO. OF SIG. DIGITS IN FINAL EST.: 3.2
ETABAR IS THE ARITHMETIC MEAN OF THE ETA-ESTIMATES,
AND THE P-VALUE IS GIVEN FOR THE NULL HYPOTHESIS THAT THE TRUE MEAN IS 0.
ETABAR: 1.7969E-03 -7.3892E-03
SE: 3.9994E-02 5.9922E-02
N: 40 40
P VAL.: 9.6416E-01 9.0186E-01
ETASHRINKSD(%) 1.7511E+01 2.0596E+00
ETASHRINKVR(%) 3.1956E+01 4.0768E+00
EBVSHRINKSD(%) 1.8525E+01 2.5411E+00
EBVSHRINKVR(%) 3.3618E+01 5.0177E+00
EPSSHRINKSD(%) 4.0910E+00
EPSSHRINKVR(%) 8.0147E+00
TOTAL DATA POINTS NORMALLY DISTRIBUTED (N): 760
N*LOG(2PI) CONSTANT TO OBJECTIVE FUNCTION: 1396.7865704711026
OBJECTIVE FUNCTION VALUE WITHOUT CONSTANT: 2636.8457699530391
OBJECTIVE FUNCTION VALUE WITH CONSTANT: 4033.6323404241416
REPORTED OBJECTIVE FUNCTION DOES NOT CONTAIN CONSTANT
TOTAL EFFECTIVE ETAS (NIND*NETA): 80
#TERE:
Elapsed estimation time in seconds: 1.74
Elapsed covariance time in seconds: 0.55
Elapsed postprocess time in seconds: 0.00
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
#OBJT:************** MINIMUM VALUE OF OBJECTIVE FUNCTION ********************
******************** ********************
************************************************************************************************************************
#OBJV:******************************************** 2636.846 **************************************************
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
******************** FINAL PARAMETER ESTIMATE ********************
******************** ********************
************************************************************************************************************************
THETA - VECTOR OF FIXED EFFECTS PARAMETERS *********
TH 1 TH 2 TH 3 TH 4 TH 5
2.31E+00 5.50E+01 4.65E+02 -8.06E-02 4.13E+00
OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
ETA1 ETA2
ETA1
+ 9.64E-02
ETA2
+ 0.00E+00 1.54E-01
SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS ****
EPS1
EPS1
+ 1.00E+00
1
OMEGA - CORR MATRIX FOR RANDOM EFFECTS - ETAS *******
ETA1 ETA2
ETA1
+ 3.11E-01
ETA2
+ 0.00E+00 3.92E-01
SIGMA - CORR MATRIX FOR RANDOM EFFECTS - EPSILONS ***
EPS1
EPS1
+ 1.00E+00
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
******************** STANDARD ERROR OF ESTIMATE ********************
******************** ********************
************************************************************************************************************************
THETA - VECTOR OF FIXED EFFECTS PARAMETERS *********
TH 1 TH 2 TH 3 TH 4 TH 5
8.63E-02 3.33E+00 2.96E+01 5.55E-02 1.36E+00
OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
ETA1 ETA2
ETA1
+ 2.00E-02
ETA2
+ ......... 2.67E-02
SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS ****
EPS1
EPS1
+ .........
1
OMEGA - CORR MATRIX FOR RANDOM EFFECTS - ETAS *******
ETA1 ETA2
ETA1
+ 3.22E-02
ETA2
+ ......... 3.41E-02
SIGMA - CORR MATRIX FOR RANDOM EFFECTS - EPSILONS ***
EPS1
EPS1
+ .........
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
******************** COVARIANCE MATRIX OF ESTIMATE ********************
******************** ********************
************************************************************************************************************************
TH 1 TH 2 TH 3 TH 4 TH 5 OM11 OM12 OM22 SG11
TH 1
+ 7.44E-03
TH 2
+ 1.29E-02 1.11E+01
TH 3
+ -3.02E-01 -2.18E+01 8.77E+02
TH 4
+ -2.76E-03 4.00E-02 9.63E-02 3.08E-03
TH 5
+ 6.53E-02 -1.09E+00 -4.27E+00 -7.50E-02 1.85E+00
OM11
+ 8.42E-05 -1.32E-02 -1.19E-01 1.27E-04 -2.85E-03 4.01E-04
OM12
+ ......... ......... ......... ......... ......... ......... .........
OM22
+ 1.56E-04 3.32E-02 -2.59E-02 3.46E-04 -8.21E-03 1.10E-04 ......... 7.15E-04
SG11
+ ......... ......... ......... ......... ......... ......... ......... ......... .........
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
******************** CORRELATION MATRIX OF ESTIMATE ********************
******************** ********************
************************************************************************************************************************
TH 1 TH 2 TH 3 TH 4 TH 5 OM11 OM12 OM22 SG11
TH 1
+ 8.63E-02
TH 2
+ 4.48E-02 3.33E+00
TH 3
+ -1.18E-01 -2.21E-01 2.96E+01
TH 4
+ -5.77E-01 2.16E-01 5.86E-02 5.55E-02
TH 5
+ 5.56E-01 -2.40E-01 -1.06E-01 -9.93E-01 1.36E+00
OM11
+ 4.88E-02 -1.98E-01 -2.01E-01 1.14E-01 -1.05E-01 2.00E-02
OM12
+ ......... ......... ......... ......... ......... ......... .........
OM22
+ 6.76E-02 3.73E-01 -3.27E-02 2.33E-01 -2.26E-01 2.06E-01 ......... 2.67E-02
SG11
+ ......... ......... ......... ......... ......... ......... ......... ......... .........
1
************************************************************************************************************************
******************** ********************
******************** FIRST ORDER CONDITIONAL ESTIMATION WITH INTERACTION ********************
******************** INVERSE COVARIANCE MATRIX OF ESTIMATE ********************
******************** ********************
************************************************************************************************************************
TH 1 TH 2 TH 3 TH 4 TH 5 OM11 OM12 OM22 SG11
TH 1
+ 2.35E+02
TH 2
+ -3.71E-01 1.65E-01
TH 3
+ 8.65E-02 8.31E-03 1.90E-03
TH 4
+ 8.52E+02 3.04E+01 4.50E+00 3.83E+04
TH 5
+ 2.55E+01 1.34E+00 1.88E-01 1.54E+03 6.31E+01
OM11
+ -8.68E+01 1.02E+01 8.66E-01 1.69E+03 8.11E+01 3.38E+03
OM12
+ ......... ......... ......... ......... ......... ......... .........
OM22
+ -1.37E+02 -8.18E+00 -4.89E-01 -2.50E+03 -9.49E+01 -8.30E+02 ......... 2.04E+03
SG11
+ ......... ......... ......... ......... ......... ......... ......... ......... .........
Elapsed finaloutput time in seconds: 0.00
#CPUT: Total CPU Time in Seconds, 2.302
Stop Time:
Sat Aug 24 15:34:47 EDT 2019@dpastoor I'm confused about the structure of this json. I see that parameter_data contains an array of objects, I'm assuming to separate estimates/std_err from different runs as objects in the array. However, looking at the other objects (e.g. ofv and shrinkage_details), they do not share this same structure, and only contain a single object instead of an array. Is this correct?
callistosp
commented
5 years ago also it would help if the parameter_structures parameter names were not capitalized to match the rest of the data structure
seth127
commented
4 years ago @dpastoor and @callistosp am I right that we should close this (very old) issue and call it complete. We can indeed get the model summary into a list in R. Furthermore, any questions about the structure of that json really belong in https://github.com/metrumresearchgroup/babylon/issues because rbabylon is just reading in the json output from bbi nonmem summary. Do you guys agree?
I also put a similar comment in https://github.com/metrumresearchgroup/rbabylon/issues/2 but I think we should start collecting issues for what we want to be able to easily parse from this summary object.
Anyway, if we're cool with this closing, we can attach these tests to the issue:
callistosp
commented
4 years ago yes @seth127, the current functionality addresses this need. Thanks for cleaning up the repo
Create a function with similar syntax to existing
jsonlite::read_json()function which takes a json object output from Babylon as argument and creates arun_resultsobject.Proposed syntax:
res <- read_results("examples/101.json")res <- read_results(101, dir="examples")Input: JSON file containing information from NONMEM run. This will be produced by a call to
bbi nonmem summary --jsonOutput: A
listoflists for post-processing: theta_df, omega_df, sigma_df, run_details, etc.Converting each of these to separate
data.frames suitable for downstream use (e.g. get_estimate_table(), get_shrinkage_table()) will be part of future issues.Tests