The xpose package was designed as a standardized interface between model outputs and R. Hence model output files can easily be imported in R and used to summarize data or create plots.
The files attached to an xpdb object can be displayed to the console
simply by writing the xpdb name to the console or by using the
print() function. Any of these files can be accessed from
the xpdb using one of the functions listed below.
run001.lst overview: 
 - Software: nonmem 7.3.0 
 - Attached files (memory usage 1.4 Mb): 
   + obs tabs: $prob no.1: catab001.csv, cotab001, patab001, sdtab001 
   + sim tabs: $prob no.2: simtab001.zip 
   + output files: run001.cor, run001.cov, run001.ext, run001.grd, run001.phi, run001.shk 
   + special: <none> 
 - gg_theme: theme_readable 
 - xp_theme: theme_xp_default 
 - Options: dir = data, quiet = FALSE, manual_import = NULLThe get_code() function can be used to access the parsed
model code from the xpdb. This code was used to create the summary and
find table names. The parsed code can be used to get additional
information about the run. If the argument .problem is
specified a subset of the code can be returned based on
$PROBLEM.
Note that general code warnings and PsN outputs appended are listed as problem 0.
# A tibble: 764 × 5
   problem level subroutine code                                                     comment        
 *   <int> <int> <chr>      <chr>                                                    <chr>          
 1       0     0 oth        "Mon Oct 16 13:34:28 CEST 2017"                          ""             
 2       0     0 oth        ""                                                       "; 1. Based on…
 3       0     0 oth        ""                                                       "; 2. Descript…
 4       0     0 oth        ""                                                       "; NONMEM PK e…
 5       1     1 pro        "Parameter estimation"                                   ""             
 6       1     2 inp        "ID DOSE DV SCR AGE SEX CLASS WT ACE MED1 MED2 TAD TIME" ""             
 7       1     2 inp        " CLCR AMT SS II EVID"                                   ""             
 8       1     3 dat        "../../mx19_2.csv IGNORE=@"                              ""             
 9       1     4 abb        "DERIV2=NO"                                              ""             
10       1     5 sub        "ADVAN2 TRANS1"                                          ""             
# ℹ 754 more rowsThe get_data() function can be used to access the
imported table files. Tables can be accessed by table name
or by .problem. In the latter a single dataset containing
all aggregated tables is returned. If more than one table
name or .problem number is provided a named list is
returned.
Note when providing a table name it is not guaranteed that the
table will be identical to its file (i.e. the order of the columns may
have been changed and tables with FIRSTONLY will no longer
be deduplicated).
# A tibble: 550 × 4
   ID     CLCR   AGE    WT
   <fct> <dbl> <dbl> <dbl>
 1 110      66    68   105
 2 110      66    68   105
 3 110      66    68   105
 4 110      66    68   105
 5 110      66    68   105
 6 110      66    68   105
 7 110      66    68   105
 8 112      47    73    80
 9 112      47    73    80
10 112      47    73    80
# ℹ 540 more rowsThe get_file() function can be used to access the
imported output files. Files can be accessed by file name,
by .problem, .subprob and/or
.method. If more than one file name,
.problem, .subprob, or .method is
provided a named list is returned.
# A tibble: 28 × 16
   ITERATION THETA1 THETA2 THETA3 THETA4 THETA5  THETA6  THETA7 `SIGMA(1,1)` `OMEGA(1,1)`
       <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>   <dbl>        <dbl>        <dbl>
 1         0   25.4   1.47   7.45  0.214  0.200 0.00983 0.00601            1       0.0740
 2         1   26.3   1.26   7.35  0.219  0.217 0.00989 0.00602            1       0.0744
 3         2   25.6   1.47   7.29  0.216  0.212 0.00987 0.00603            1       0.0741
 4         3   26.8   1.49   5.76  0.213  0.213 0.00979 0.00628            1       0.0730
 5         4   26.7   1.49   5.69  0.213  0.212 0.00979 0.00629            1       0.0730
 6         5   26.7   1.49   5.66  0.213  0.212 0.00979 0.00630            1       0.0730
 7         6   26.6   1.49   5.03  0.210  0.217 0.0100  0.00652            1       0.0724
 8         7   26.6   1.49   4.93  0.205  0.217 0.0100  0.00658            1       0.0717
 9         8   26.6   1.48   4.62  0.211  0.217 0.00951 0.00735            1       0.0633
10         9   26.6   1.46   4.41  0.209  0.217 0.00903 0.00874            1       0.0766
# ℹ 18 more rows
# ℹ 6 more variables: `OMEGA(2,1)` <dbl>, `OMEGA(2,2)` <dbl>, `OMEGA(3,1)` <dbl>,
#   `OMEGA(3,2)` <dbl>, `OMEGA(3,3)` <dbl>, OBJ <dbl>The get_prm() function can be used to access the
parameter estimates. To get a nice parameter table printed to the
console use the function prm_table() instead. The arguments
.problem, .subprob and .method
can be used to select the parameter estimates to output.
# A tibble: 11 × 10
   type  name       label           value       se     rse fixed diagonal     m     n
 * <chr> <chr>      <chr>           <dbl>    <dbl>   <dbl> <lgl> <lgl>    <dbl> <dbl>
 1 the   THETA1     "TVCL"       26.3      0.892    0.0339 FALSE NA           1    NA
 2 the   THETA2     "TVV"         1.35     0.0438   0.0325 FALSE NA           2    NA
 3 the   THETA3     "TVKA"        4.20     0.809    0.192  FALSE NA           3    NA
 4 the   THETA4     "LAG"         0.208    0.0157   0.0755 FALSE NA           4    NA
 5 the   THETA5     "Prop. Err"   0.205    0.0224   0.110  FALSE NA           5    NA
 6 the   THETA6     "Add. Err"    0.0106   0.00366  0.347  FALSE NA           6    NA
 7 the   THETA7     "CRCL on CL"  0.00717  0.00170  0.237  FALSE NA           7    NA
 8 ome   OMEGA(1,1) "IIV CL"      0.270    0.0233   0.0862 FALSE TRUE         1     1
 9 ome   OMEGA(2,2) "IIV V"       0.195    0.0320   0.164  FALSE TRUE         2     2
10 ome   OMEGA(3,3) "IIV KA"      1.38     0.202    0.146  FALSE TRUE         3     3
11 sig   SIGMA(1,1) ""            1       NA       NA      TRUE  TRUE         1     1
Reporting transformed parameters:
For the OMEGA and SIGMA matrices, values are reported as standard deviations for the diagonal elements and as correlations for the off-diagonal elements. The relative standard errors (RSE) for OMEGA and SIGMA are reported on the approximate standard deviation scale (SE/variance estimate)/2. Use `transform = FALSE` to report untransformed parameters.
Estimates for $prob no.1, subprob no.1, method foce
 Parameter  Label      Value        RSE
 THETA1     TVCL       26.29        0.03391
 THETA2     TVV        1.348        0.0325
 THETA3     TVKA       4.204        0.1925
 THETA4     LAG        0.208        0.07554
 THETA5     Prop. Err  0.2046       0.1097
 THETA6     Add. Err   0.01055      0.3466
 THETA7     CRCL on CL 0.007172     0.2366
 OMEGA(1,1) IIV CL     0.2701       0.08616
 OMEGA(2,2) IIV V      0.195        0.1643
 OMEGA(3,3) IIV KA     1.381        0.1463
 SIGMA(1,1)            1        fix  - The get_summary() function can be used to access the
generated run summary from which the template_titles. If
the argument .problem is specified a subset of the summary
can be returned based on $PROBLEM.
Note that general summary information are listed as problem 0.
# A tibble: 12 × 5
   problem subprob descr               label       value                        
     <dbl>   <dbl> <chr>               <chr>       <chr>                        
 1       0       0 Run description     descr       NONMEM PK example for xpose  
 2       0       0 Run directory       dir         data                         
 3       0       0 Run errors          errors      na                           
 4       0       0 ESAMPLE seed number esampleseed na                           
 5       0       0 Run file            file        run001.lst                   
 6       0       0 Number of ESAMPLE   nesample    na                           
 7       0       0 Reference model     ref         000                          
 8       0       0 Run number          run         run001                       
 9       0       0 Software            software    nonmem                       
10       0       0 Run start time      timestart   Mon Oct 16 13:34:28 CEST 2017
11       0       0 Run stop time       timestop    Mon Oct 16 13:34:35 CEST 2017
12       0       0 Software version    version     7.3.0