Command line interface#

Pharmpy has a command line interface for some of its functionality. The command line tool is an integrated part of the Pharmpy python package.

The main command is `pharmpy` and the functionality is divided into subcommands with two levels. The first and top level most often represents a type of object to perform on operation on. For example `model` or `data`. (The built in help system will give an overview of available subcommands with `pharmpy -h`. The second level is most often an operation or verb to perform. After the main command and the two subcommands follows the input and options of the particular command.

pharmpy#

Welcome to the command line interface of Pharmpy!

Functionality is split into various subcommands

try –help after a COMMAND
all keyword arguments can be abbreviated if unique

usage: pharmpy [-h] [--version] COMMAND ...

-h, --help#: show this help message and exit

--version#: show program’s version number and exit

Examples:

# Create 100 bootstrap datasets pharmpy data resample pheno_real.mod –resamples=100 –replace

# prettyprint model pharmpy model print pheno_real.mod

# version/install information pharmpy info

pharmpy data#

usage: pharmpy data [-h] ACTION ...

-h, --help#: show this help message and exit

pharmpy data append#

Append a column to dataset given an assignment expression.The expression can contain already present columns of the dataset.

usage: pharmpy data append [-h] [-f] [-o file] FILE expression

file#: input model or dataset file

expression#

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

pharmpy data deidentify#

Deidentify dataset by renumbering the id column and changing dates.

usage: pharmpy data deidentify [-h] [-f] [-o file] [--idcol COLUMN]
                               [--datecols COLUMNS]
                               FILE

file#: A csv file dataset

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

--idcol <column>#: id column name (default ID)

--datecols <columns>#: Comma separated list of date column names

pharmpy data filter#

Filter rows of dataset via expressions. All rows matching all expressions will be kept.abs A new model with the filtered dataset connected is created.

usage: pharmpy data filter [-h] [-f] [-o file] FILE ...

file#: input model or dataset file

expressions#

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

pharmpy data print#

Print whole dataset or selected columns from model or csv file via a pager to stdout. For NM-TRAN models the dataset will be filtered first.

usage: pharmpy data print [-h] [--columns COLUMNS] FILE

file#: input model or dataset file

-h, --help#: show this help message and exit

--columns <columns>#: Select specific columns (default is all)

pharmpy data reference#

Set values in specific columns to provided reference values

usage: pharmpy data reference [-h] [-f] [-o file]
                              FILE COLNAME=VALUE [COLNAME=VALUE ...]

file#: input model file

colname=value#: List of pairs of column names and reference values

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

pharmpy data resample#

Bootstrap resample datasetsMultiple new models and datasets will be created

usage: pharmpy data resample [-h] [--seed INTEGER] [--group COLUMN]
                             [--resamples NUMBER] [--stratify COLUMN]
                             [--replace] [--sample_size NUMBER]
                             FILE

file#: input model or dataset file

-h, --help#: show this help message and exit

--seed <integer>#: Provide a random seed. The seed must be an integer between 0 and 2^32 - 1

--group <column>#: Column to use for grouping (default is ID)

--resamples <number>#: Number of resampled datasets (default 1)

--stratify <column>#: Column to use for stratification

--replace#: Sample with replacement (default is without)

--sample_size <number>#: Number of groups to sample for each resample

pharmpy data write#

Write a dataset from model as the model sees it. For NM-TRAN models this means to filter all IGNORE and ACCEPT statements in $DATA and to convert the dataset to csv format.

usage: pharmpy data write [-h] [-f] [-o file] FILE

file#: input model file

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

pharmpy info#

usage: pharmpy info [-h]

-h, --help#: show this help message and exit

pharmpy model#

usage: pharmpy model [-h] ACTION ...

-h, --help#: show this help message and exit

pharmpy model print#

Print an overview of a model.

usage: pharmpy model print [-h] [--explicit-odes] FILE [FILE ...]

file#: input model files

-h, --help#: show this help message and exit

--explicit-odes#: Print the ODE system explicitly instead of as a compartmental graph

pharmpy model sample#

Sample parameter initial estimates using uncertainty givenby covariance matrix.

usage: pharmpy model sample [-h] [--seed INTEGER] [--samples NUMBER] FILE

file#: input model file

-h, --help#: show this help message and exit

--seed <integer>#: Provide a random seed. The seed must be an integer between 0 and 2^32 - 1

--samples <number>#: Number of sampled models

pharmpy model update_inits#

Update inits using modelfit results.

usage: pharmpy model update_inits [-h] [-f] [-o file] FILE

file#: input model file

-h, --help#: show this help message and exit

-f, --force#: remove existing destination files (all)

-o <file>, --output_file <file>#: output file

pharmpy results#

usage: pharmpy results [-h] ACTION ...

-h, --help#: show this help message and exit

pharmpy results bootstrap#

Generate results from a PsN bootstrap run

usage: pharmpy results bootstrap [-h] PsN directory

psn directory#: Path to PsN bootstrap run directory

-h, --help#: show this help message and exit

pharmpy results cdd#

Generate results from a PsN cdd run

usage: pharmpy results cdd [-h] PsN directory

psn directory#: Path to PsN cdd run directory

-h, --help#: show this help message and exit

pharmpy results frem#

Generate results from a PsN frem run

usage: pharmpy results frem [-h] [--method {cov_sampling,bipp}]
                            [--force_posdef_covmatrix]
                            [--force_posdef_samples FORCE_POSDEF_SAMPLES]
                            PsN directory

psn directory#: Path to PsN frem run directory

-h, --help#: show this help message and exit

--method {cov_sampling,bipp}#: Method to use for uncertainty of covariate effects

--force_posdef_covmatrix#: Should covariance matrix be forced to become positive definite

--force_posdef_samples <force_posdef_samples>#: Number of sampling tries to do before starting to force posdef

pharmpy results linearize#

Generate results from a PsN linearize run

usage: pharmpy results linearize [-h] PsN directory

psn directory#: Path to PsN linearize run directory

-h, --help#: show this help message and exit

pharmpy results ofv#

Extract OFVs from one or more model runs

usage: pharmpy results ofv [-h] FILE [FILE ...]

file#: input model files

-h, --help#: show this help message and exit

pharmpy results print#

Print results from PsN run to stdout

usage: pharmpy results print [-h] file or directory

file or directory#: Path to directory containing results.json or directly to json results file

-h, --help#: show this help message and exit

pharmpy results qa#

Generate results from a PsN qa run

usage: pharmpy results qa [-h] PsN directory

psn directory#: Path to PsN qa run directory

-h, --help#: show this help message and exit

pharmpy results report#

Generate results report for PsN run (currently only frem)

usage: pharmpy results report [-h] PsN directory

psn directory#: Path to PsN run directory

-h, --help#: show this help message and exit

pharmpy results ruvsearch#

Generate results from a PsN ruvsearch run

usage: pharmpy results ruvsearch [-h] PsN directory

psn directory#: Path to PsN ruvsearch run directory

-h, --help#: show this help message and exit

pharmpy results scm#

Generate results from a PsN scm run

usage: pharmpy results scm [-h] PsN directory

psn directory#: Path to PsN scm run directory

-h, --help#: show this help message and exit

pharmpy results simeval#

Generate results from a PsN simeval run

usage: pharmpy results simeval [-h] PsN directory

psn directory#: Path to PsN simeval run directory

-h, --help#: show this help message and exit

pharmpy results summary#

Print a summary of a model estimates to stdout.

usage: pharmpy results summary [-h] FILE [FILE ...]

file#: input model files

-h, --help#: show this help message and exit

pharmpy run#

usage: pharmpy run [-h] TOOL ...

-h, --help#: show this help message and exit

pharmpy run allometry#

usage: pharmpy run allometry [-h] [--allometric_variable ALLOMETRIC_VARIABLE]
                             [--reference_value REFERENCE_VALUE]
                             [--parameters PARAMETERS] [--initials INITIALS]
                             [--lower_bounds LOWER_BOUNDS]
                             [--upper_bounds UPPER_BOUNDS] [--non_fixed]
                             [--path PATH]
                             FILE

file#: input model file

-h, --help#: show this help message and exit

--allometric_variable <allometric_variable>#: Name of the allometric variable

--reference_value <reference_value>#: Reference value for the allometric variable

--parameters <parameters>#: List of parameters to apply scaling to

--initials <initials>#: Initial estimates for the exponents

--lower_bounds <lower_bounds>#: Lower bounds for the exponents

--upper_bounds <upper_bounds>#: Upper bounds for the exponents

--non_fixed#: Should the exponents not be fixed

--path <path>#: Path to output directory

pharmpy run amd#

usage: pharmpy run amd [-h] [--modeltype MODELTYPE]
                       [--administration ADMINISTRATION] [--cl_init CL_INIT]
                       [--vc_init VC_INIT] [--mat_init MAT_INIT]
                       [--search_space SEARCH_SPACE]
                       [--lloq_method LLOQ_METHOD] [--lloq_limit LLOQ_LIMIT]
                       [--order ORDER]
                       [--allometric_variable ALLOMETRIC_VARIABLE]
                       [--occasion OCCASION] [--path PATH] [--resume RESUME]
                       input_path

input_path#: Path to output directory

-h, --help#: show this help message and exit

--modeltype <modeltype>#: Type of model to build. Currently only “basic_pk”

--administration <administration>#: Type of model to build. One of “iv”, “oral” or “ivoral”

--cl_init <cl_init>#: Initial estimate for the population clearance

--vc_init <vc_init>#: Initial estimate for the central compartment population volume

--mat_init <mat_init>#: Initial estimate for the mean absorption time (not for iv models)

--search_space <search_space>#: MFL for search space for structural model

--lloq_method <lloq_method>#: Method for how to remove LOQ data. See transform_blq for list of available methods

--lloq_limit <lloq_limit>#: Lower limit of quantification. If None LLOQ column from dataset will be used

--order <order>#: Runorder of components

--allometric_variable <allometric_variable>#: Variable to use for allometry

--occasion <occasion>#: Name of occasion column

--path <path>#: Path to run AMD in

--resume <resume>#: Whether to allow resuming previous run

pharmpy run bootstrap#

usage: pharmpy run bootstrap [-h] [--samples SAMPLES] FILE

file#: input model file

-h, --help#: show this help message and exit

--samples <samples>#: Number of bootstrap datasets

pharmpy run covsearch#

usage: pharmpy run covsearch [-h] [--effects EFFECTS] [--p_forward P_FORWARD]
                             [--p_backward P_BACKWARD] [--max_steps MAX_STEPS]
                             [--algorithm ALGORITHM] [--path PATH]
                             FILE

file#: input model file

-h, --help#: show this help message and exit

--effects <effects>#: The candidate effects to search through (required)

--p_forward <p_forward>#: The p-value threshold for forward steps (default is 0.05)

--p_backward <p_backward>#: The p-value threshold for backward steps (default is 0.01)

--max_steps <max_steps>#: The maximum number of search algorithm steps to perform, or -1 for no maximum (default).

--algorithm <algorithm>#: The search algorithm to use (default is ‘scm-forward-then-backward’)

--path <path>#: Path to output directory

pharmpy run estmethod#

usage: pharmpy run estmethod [-h] [--methods METHODS] [--solvers SOLVERS]
                             [--path PATH]
                             FILE algorithm

file#: input model file

algorithm#: Algorithm to use

-h, --help#: show this help message and exit

--methods <methods>#: List of methods to try, mark group of methods in single quote separated by spaces. Supported are: FOCE, FO, IMP, IMPMAP, ITS, SAEM, LAPLACE, BAYES, or ‘all’. Default is None.

--solvers <solvers>#: List of solvers to try, mark group of methods in single quote separated by spaces. Supported are: CVODES (ADVAN14), DGEAR (ADVAN8), DVERK (ADVAN6), IDA (ADVAN15), LSODA (ADVAN13) and LSODI (ADVAN9), or ‘all’. Default is None.

--path <path>#: Path to output directory

pharmpy run execute#

usage: pharmpy run execute [-h] FILE [FILE ...]

file#: input model files

-h, --help#: show this help message and exit

pharmpy run iivsearch#

usage: pharmpy run iivsearch [-h] [--iiv_strategy IIV_STRATEGY]
                             [--rank_type RANK_TYPE] [--cutoff CUTOFF]
                             [--path PATH]
                             FILE algorithm

file#: input model file

algorithm#: Algorithm to use

-h, --help#: show this help message and exit

--iiv_strategy <iiv_strategy>#: If/how IIV should be added to start model

--rank_type <rank_type>#: Name of function to use for ranking candidates (default is bic).

--cutoff <cutoff>#: Which selection criteria to rank models on

--path <path>#: Path to output directory

pharmpy run iovsearch#

usage: pharmpy run iovsearch [-h] [--column COLUMN]
                             [--list_of_parameters LIST_OF_PARAMETERS]
                             [--rank_type RANK_TYPE] [--cutoff CUTOFF]
                             [--distribution DISTRIBUTION] [--path PATH]
                             FILE

file#: input model file

-h, --help#: show this help message and exit

--column <column>#: Name of column in dataset to use as occasion column (default is “OCC”)

--list_of_parameters <list_of_parameters>#: List of parameters to test IOV on

--rank_type <rank_type>#: Name of function to use for ranking candidates (default is bic).

--cutoff <cutoff>#: Which selection criteria to rank models on

--distribution <distribution>#: Which distribution added IOVs should have (default is same-as-iiv)

--path <path>#: Path to output directory

pharmpy run modelsearch#

usage: pharmpy run modelsearch [-h] [--rank_type RANK_TYPE] [--cutoff CUTOFF]
                               [--iiv_strategy IIV_STRATEGY] [--path PATH]
                               FILE mfl algorithm

file#: input model file

mfl#: Search space to test

algorithm#: Algorithm to use

-h, --help#: show this help message and exit

--rank_type <rank_type>#: Name of function to use for ranking candidates (default is bic).

--cutoff <cutoff>#: Which selection criteria to rank models on

--iiv_strategy <iiv_strategy>#: If/how IIV should be added to candidate models

--path <path>#: Path to output directory

pharmpy run ruvsearch#

usage: pharmpy run ruvsearch [-h] [--groups GROUPS] [--p_value P_VALUE]
                             [--skip SKIP] [--path PATH]
                             FILE

file#: input model file

-h, --help#: show this help message and exit

--groups <groups>#: Number of groups for the time varying models

--p_value <p_value>#: p_value to use for the likelihood ratio test

--skip <skip>#: List of models to not test

--path <path>#: Path to output directory