Package 'ggPMX'

Title: 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models
Description: At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling activities in order to reduce the overall effort required for generating such plots. For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox, called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient for publication and submissions using few lines of code. This package focuses on plots recommended by ISoP <doi:10.1002/psp4.12161>. While not required, you can get/install the 'R' 'lixoftConnectors' package in the 'Monolix' installation, as described at the following url <https://monolix.lixoft.com/monolix-api/lixoftconnectors_installation/>. When 'lixoftConnectors' is available, 'R' can use 'Monolix' directly to create the required Chart Data instead of exporting it from the 'Monolix' gui.
Authors: Amine Gassem [aut], Bruno Bieth [aut], Irina Baltcheva [aut], Thomas Dumortier [aut], Christian Bartels [aut], Souvik Bhattacharya [aut], Inga Ludwig [aut], Ines Paule [aut], Didier Renard [aut], Matthew Fidler [aut, cre] , Seid Hamzic [aut], Benjamin Guiastrennec [ctb], Kyle T Baron [ctb] , Qing Xi Ooi [ctb], Novartis Pharma AG [cph]
Maintainer: Matthew Fidler <[email protected]>
License: GPL-2
Version: 1.2.11.9000
Built: 2024-10-25 04:34:03 UTC
Source: https://github.com/ggpmxdevelopment/ggpmx

Help Index

Method for subsetting "pmx_gpar" objects

Description

Method for subsetting "pmx_gpar" objects

Usage

## S3 method for class 'pmx_gpar'
x[index, ...]

Arguments

x

pmx_gpar object
index

can be character/integer of element
...

other parameter (not used just for generic)

Value

if exists the parameter description

Give the whole abbreviation definition

Description

Give the whole abbreviation definition

Usage

abbrev(param)

Arguments

param

abbreviation term

Value

character abbreviation definition

Examples

abbrev("VPC")

Add draft layer annotation

Description

This function adds the word draft to certain graphics.

Usage

add_draft(
  label = "DRAFT",
  size = 10,
  colour = "grey50",
  x = Inf,
  y = -Inf,
  ...
)

Arguments

label

draft layer default to DRAFT
size

size of the annotation
colour

color of the annotation default to grey50
x

numeric x coordinate of the draft label
y

numeric y coordinate of the draft label
...

extra parameters to geom text used to annotate the draft

Value

ggplot2 annotation

Performs checks of names in shrink list

Description

Performs checks of names in shrink list

Usage

check_shrink(shrink_list)

Arguments

shrink_list

list list of shrink arguments

creates a graphic distribution object

Description

creates a graphic distribution object

Usage

distrib(
  labels,
  is.shrink,
  type = c("box", "hist"),
  is.jitter = FALSE,
  jitter = NULL,
  facets = NULL,
  histogram = NULL,
  shrink = NULL,
  dname = NULL,
  ...
)

Arguments

labels

list of texts/titles used within the plot
is.shrink

logical if TRUE add shrinkage layer
type

box for boxplot or histogram
is.jitter

logical if TRUE add jitter operator for points
jitter

list set jitter parameter
facets

list set the facet setting in case of histogram plot
histogram

list histogram graphical parameters
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one
dname

name of dataset to be used
...

others graphics arguments passed to pmx_gpar internal object.

Details

labels is a list that contains:

  • title: plot title default "EBE distribution"

  • subtitle: plot subtitle default empty

  • x: x axis label default to "Etas"

  • y: y axis label default to empty

  • legend: legend title default to "random Effect"

shrink is a list that contains:

  • fun: shrinkage function can be sd or var

  • size: shrinkage text size

  • color: shrinkage text color

  • vjust: shrinkage position vertical adjustment

Value

distrib object

See Also

Other plot_pmx: eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..

Description

This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..

Usage

eta_cov(
  labels,
  type = c("cats", "conts"),
  dname = NULL,
  show.correl = TRUE,
  correl = NULL,
  facets = NULL,
  point = NULL,
  covariates = NULL,
  is.strat.color = FALSE,
  ...
)

Arguments

labels

list of texts/titles used within the plot
type

box for cats or conts
dname

name of dataset to be used
show.correl

logical if TRUE add correlation to the plot
correl

list correl geom text graphical parameter
facets

list facetting graphical parameter
point

list geom point graphical parameter
covariates

pmxCOVObject pmx_cov
is.strat.color

logical if 'TRUE' use a different color for the spline stratification.
...

others graphics arguments passed to pmx_gpar internal object.

Details

labels is a list that contains:

  • title: plot title default "EBE vs. covariates"

  • x: x axis label default to "Etas"

  • y: y axis label default to empty

Value

eta_cov object

See Also

Other plot_pmx: distrib(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

Eta Covariates plots

Description

Eta Covariates plots

Relationships between (ETA) and categorical covariates

Relationships between (ETA) and continuous covariates

Usage

dummy(
  dname,
  show.correl,
  correl,
  point,
  facets,
  filter,
  strat.facet,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales
)

pmx_plot_eta_cats(ctr, ...)

pmx_plot_eta_conts(ctr, ...)

Arguments

dname

character name of dataset to be used
show.correl

logical if TRUE add correlation to the plot
correl

list correl geom text graphical parameter
point

list geom point graphical parameter
facets

list facetting graphical parameter

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
ctr

pmx controller
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • eta_cov generic object for eta/covariates plots.

  • pmx_update function.

eta_cov parameters

Value

ggplot2 object

Examples

# basic use  ---------------------------------------

ctr <- theophylline()
ctr %>% pmx_plot_eta_cats
ctr %>% pmx_plot_eta_conts

# update graphical parameter  ----------------------

## update labels
ctr %>% pmx_plot_eta_cats(
  labels = list(title = "New eta cats title")
)

## remove draft
ctr %>% pmx_plot_eta_cats(is.draft = FALSE)

## change text color line
ctr %>% pmx_plot_eta_conts(
  correl=list(colour="magenta")
  )

## set covariates custom labels 

ctr %>% pmx_plot_eta_conts(
  covariates=pmx_cov(values=list("WT0","AGE0"),
                     labels=list("Weight","Age"))
)

## set effects and covaraites custom labels


ctr <- theophylline( settings = pmx_settings(
  effects=list( levels=c("ka", "V", "Cl"), 
                labels=c("Concentration","Volume","Clearance")
  )
)
)
ctr %>% pmx_plot_eta_conts(
  covariates=pmx_cov(values=list("WT0","AGE0"),
                     labels=list("Weight","Age"))
)

Eta distribution plots

Description

Eta distribution plots

Eta Distribution boxplot

Eta Distribution histogram plot

Usage

eta_distribution_plot(
  jitter,
  type,
  dname,
  is.shrink,
  shrink,
  is.jitter,
  histogram,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

pmx_plot_eta_box(ctr, ...)

pmx_plot_eta_hist(ctr, ...)

Arguments

jitter

list set jitter parameter
type

box for boxplot or histogram
dname

name of dataset to be used
is.shrink

logical if TRUE add shrinkage layer
shrink

list parameters to control shrinkage, must contain "fun"
is.jitter

logical if TRUE add jitter operator for points
histogram

list histogram graphical parameters

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • distrib generic object for distribution plots (histogram/boxplot).

  • pmx_update function.

distrib parameters
ctr

pmx controller

Value

ggplot2 object

Examples

# *************** basic use ***************** ------

ctr <- theophylline()
## boxplot variation
p <- ctr %>% pmx_plot_eta_box()
## histogram variation
p <- ctr %>% pmx_plot_eta_hist()

# update graphical parameter  ----------------------

## add jitter
ctr %>%
  pmx_plot_eta_hist(is.jitter = TRUE, jitter = list(alpha = 0.4, color = "red"))

## remove shrinkage
ctr %>%
  pmx_plot_eta_hist(is.shrink = FALSE)

## update histogram graphical parameters
ctr %>%
  pmx_plot_eta_hist(
    histogram = list(
      color = NA,
      position = "fill",
      binwidth = 1 / 100
    )
  )



# stratification  ----------------------------------

## categorical stratification color parameter
ctr %>% pmx_plot_eta_hist(is.jitter = TRUE, strat.facet = ~STUD, strat.color = ~SEX)
  
## categorical stratification facetting
ctr %>% pmx_plot_eta_hist(strat.facet = ~SEX)

## using formula categorical stratification facetting
ctr %>% pmx_plot_eta_hist(
  strat.facet = STUD ~ SEX,
  shrink = pmx_shrink(hjust = 0.5)
)

# subsetting  --------------------------------------

## select a set of random effect
ctr %>% pmx_plot_eta_hist(filter = EFFECT %in% c("ka", "Cl"))
## filter and stratify by facets
ctr %>% pmx_plot_eta_hist(
  filter = EFFECT %in% c("ka", "Cl"), strat.facet = ~SEX
)
ctr %>% pmx_plot_eta_hist(
  filter = EFFECT %in% c("ka", "Cl"), strat.facet = ~SEX
)

This creates an eta correlation which defines the relationship between parameters

Description

This creates an eta correlation which defines the relationship between parameters

Usage

eta_pairs(
  is.title,
  title,
  dname = NULL,
  type.eta = c("mode", "mean"),
  text_color = "black",
  is.shrink = TRUE,
  is.smooth = TRUE,
  smooth = NULL,
  point = NULL,
  shrink = NULL,
  is.hline = FALSE,
  hline = NULL,
  is.vreference_line = FALSE,
  vreference_line = list(colour = "orange", linetype = "longdash"),
  ...
)

Arguments

is.title

logical if TRUE then a title is used for the plot
title

character the plot title
dname

name of dataset to be used
type.eta

character type of eat can be 'mode' or 'mean'.'mode' by default
text_color

color of the correlation text in the upper matrix
is.shrink

logical if TRUE add shrinkage to the plot
is.smooth

logical if TRUE add smoothing to lower matrix plots
smooth

list geom_smooth graphical parameters
point

list geom_point graphical parameter
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one
is.hline

logical if TRUE add horizontal line to lower matrix plots
hline

list geom_hline graphical parameters
is.vreference_line

logical if TRUE add the +- 1.96 lines
vreference_line

list geom_hline graphical parameters for the reference lines
...

others graphics arguments passed to pmx_gpar internal object.

Value

ecorrel object

See Also

Other plot_pmx: distrib(), eta_cov(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

Try to evaluate a symbol in the parent frame (on errorr eturn the symbol)

Description

Try to evaluate a symbol in the parent frame (on errorr eturn the symbol)

Usage

eval_sym_parent_env(x)

Arguments

x

any object

Get abbreviation definition by key

Description

Get abbreviation definition by key

Usage

get_abbrev(ctr, param)

Arguments

ctr

pmxClass controller
param

abbreviation term

Value

character abbreviation definition

Get category covariates

Description

Get category covariates

Usage

get_cats(ctr)

Arguments

ctr

the controller object

Value

a charcater vector

See Also

Other pmxclass: get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get continuous covariates

Description

Get continuous covariates

Usage

get_conts(ctr)

Arguments

ctr

the controller object

Value

a charcater vector

See Also

Other pmxclass: get_cats(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get covariates variables

Description

Get covariates variables

Usage

get_covariates(ctr)

Arguments

ctr

the controller object

Value

a charcater vector

See Also

Other pmxclass: get_cats(), get_conts(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get controller data set

Description

Get controller data set

Usage

get_data(
  ctr,
  data_set = c("estimates", "predictions", "eta", "finegrid", "input", "sim",
    "individual")
)

Arguments

ctr

the controller object
data_set

the data set name

Value

a data.table of the named data set if available.

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get controller occasional covariates

Description

Get controller occasional covariates

Usage

get_occ(ctr)

Arguments

ctr

the controller object

Value

a charcater vector

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get plot object

Description

Get plot object

Usage

get_plot(ctr, nplot, which_pages = "all")

Arguments

ctr

pmxClass controller object
nplot

character the plot name
which_pages

integer vector (can be length 1), set page number in case of multi pages plot, or character "all" to plot all pages.

Value

ggplot object

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Examples

library(ggPMX)
ctr <- theophylline()
p1 <- ctr %>% get_plot("iwres_ipred")
## get all pages or some pages
p2 <- ctr %>% get_plot("individual")
## returns one page of individual plot
p2 <- ctr %>% get_plot("individual", which_pages = 1)
p3 <- ctr %>% get_plot("individual", which_pages = c(1, 3))
## get distribution plot
pdistri <- ctr %>% get_plot("eta_hist")

Get the plot config by name

Description

Get the plot config by name

Usage

get_plot_config(ctr, pname)

Arguments

ctr

the controller object
pname

the plot name

Value

the config object

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Examples

ctr <- theophylline()
ctr %>% set_plot("IND", pname = "indiv1")
ctr %>% get_plot_config("distr1")

Get extra stratification variables

Description

Get extra stratification variables

Usage

get_strats(ctr)

Arguments

ctr

the controller object

Value

a charcater vector

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), plot_names(), plots(), pmx_update(), set_data(), set_plot()

Get ggPMX Option

Description

Get ggPMX Option

Usage

getPmxOption(name, default = NULL)

Arguments

name

Name of an option to get.
default

Value to be returned if the option is not currently set.

Examples

## Not run: 
pmxOptions(myOption = 10)
getPmxOption("myOption")

## End(Not run)

Remove named elements from gtable

Description

Remove named elements from gtable

Usage

gtable_remove_grobs(table, names, ...)

Arguments

table

The table from which grobs should be removed
names

A character vector of the grob names (as listed in table$layout) that should be removed
...

Other parameters passed through to gtable_filter.

This function can be used to obtain individual prediction and compare with observed data and population prediction for each individual separately

Description

This function can be used to obtain individual prediction and compare with observed data and population prediction for each individual separately

Usage

individual(
  labels,
  facets = NULL,
  dname = NULL,
  ipred_line = NULL,
  pred_line = NULL,
  point = NULL,
  bloq = NULL,
  is.legend,
  use.finegrid,
  ...
)

Arguments

labels

plot texts. labels, axis,
facets

list facets settings nrow/ncol
dname

name of dataset to be used
ipred_line

list some pred line geom properties aesthetics
pred_line

list some ipred line geom properties aesthetics
point

list some point geom properties aesthetics
bloq

pmxBLOQ object created by pmx_bloq
is.legend

logical if TRUE add a legend
use.finegrid

logical if FALSE use predictions data set
...

others graphics arguments passed to pmx_gpar internal object.

Value

individual fit object

See Also

plot_pmx.individual

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

Merge input and fingrid data sets

Description

Merge input and fingrid data sets

Usage

input_finegrid(input, finegrid)

Arguments

input

data.table input data set
finegrid

data.table finegrid data set

Value

data.table

Check if an object is a pmx_gpar class

Description

Check if an object is a pmx_gpar class

Usage

is.pmx_gpar(x)

Arguments

x

pmx_gpar object

Value

logical returns TRUE if it is a pmx_gpar object

Merge 2 lists

Description

left join , the first list is updated by the seond one

Usage

l_left_join(base_list, overlay_list, recursive = TRUE)

Arguments

base_list

list to update
overlay_list

list used to update the first list
recursive

logical if TRUE do the merge in depth

Value

list

Obtain the data source config

Description

Obtain the data source config

Usage

load_config(x, sys = c("mlx", "nm", "mlx18"))

Arguments

x

the config name.
sys

can be mlx,nm,...

Value

a list :data configuration object

Load data set

Description

Load data set

Usage

load_data_set(x, path, sys, ...)

Arguments

x

data set config
path

character path to the directory
sys

character mlx or nm
...

extra parameter passed to special readers

Value

data.table

Load all/or some source data set

Description

Load all/or some source data set

Usage

load_source(sys, path, dconf, ...)

Arguments

sys

type cane mlx/nom
path

character directory path containing all sources.
dconf

configuration object
...

any extra parameters for readers

Value

list of data.table

Determine the number of pages in a paginated facet plot

Description

This is a simple helper that returns the number of pages it takes to plot all panels when using facet_wrap_paginate . It partially builds the plot so depending on the complexity of your plot it might take some time to calculate...

Usage

n_pages(plot)

Arguments

plot

A ggplot object using either facet_wrap_paginate or facet_grid_paginate

Value

If the plot uses using either facet_wrap_paginate or facet_grid_paginate it returns the total number of pages. Otherwise it returns NULL

Creates parameter kable

Description

Creates parameter kable

Usage

param_table(ctr, fun, return_table = FALSE, scientific = FALSE, digits = 2)

Arguments

ctr

Generated controller from e.g. pmx_mlx for Monolix.
fun

character can be "sd" or "var" for shrinkage computation, see pmx_comp_shrink
return_table

If TRUE, returns the same table as in get_data('estimates') otherwise it returns a kable
scientific

logical set to TRUE to get scientific notation of parameter values, or FALSE otherwise
digits

integer the number of significant digits to use when rounding parameter values

Value

Returns a kable with the parameter estimates from get_data('estimates')

Examples

#ctr <- theophylline()
#my_params <- ctr %>% param_table(fun = "var")

Parse MONOLIX mlxtran file

Description

Parse MONOLIX mlxtran file

Usage

parse_mlxtran(file_name)

Arguments

file_name

absolute path to mlxtran file

Value

list key/values to initialize ggPMX controller

Creates pmx controller using monlix data having Occasional variable

Description

Creates pmx controller using monlix data having Occasional variable

Usage

pk_occ()

Value

pmx controller

Examples

## Not run: 
pk_occ()

## End(Not run)

Creates pkpd pmx controller using package internal data

Description

Creates pkpd pmx controller using package internal data

Usage

pk_pd(code = "3")

Arguments

code

can be 3 or 4

Get plot names

Description

Get plot names

Usage

plot_names(ctr)

Arguments

ctr

pmxClass controller object

Value

list of plot names

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plots(), pmx_update(), set_data(), set_plot()

This is a generic plot method that produces all plots by default described in pmx model evaluation guidance.

Description

This is a generic plot method that produces all plots by default described in pmx model evaluation guidance.

Usage

plot_pmx(x, dx, ...)

## S3 method for class 'pmx_vpc'
plot_pmx(x, dx, ...)

Arguments

x

object to plot
dx

data.table , plot source data
...

extra argument (not used)

See Also

pmx_gpar.

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual()

Plot EBE distribution

Description

Plot EBE distribution

Usage

## S3 method for class 'distrib'
plot_pmx(x, dx, ...)

Arguments

x

distribution object
dx

data set
...

not used for the moment

Value

ggplot2 plot

See Also

distrib

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

This plots an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage

Description

This plots an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage

Usage

## S3 method for class 'eta_cov'
plot_pmx(x, dx, ...)

Arguments

x

eta_cov object
dx

data set
...

not used for the moment

Value

ggplot2 plot

See Also

eta_cov

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

Plot random effect correlation plot

Description

Plot random effect correlation plot

Usage

## S3 method for class 'eta_pairs'
plot_pmx(x, dx, ...)

Arguments

x

distribution object
dx

data set
...

not used for the moment

Value

ggpairs plot

See Also

distrib

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

This function can be used to plot individual prediction and compare with observed data and population prediction for each individual separately

Description

This function can be used to plot individual prediction and compare with observed data and population prediction for each individual separately

Usage

## S3 method for class 'individual'
plot_pmx(x, dx, ...)

Arguments

x

individual object
dx

data set
...

not used for the moment

Value

a list of ggplot2

See Also

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

This function plots EBE versus covariates using qq plots

Description

This function plots EBE versus covariates using qq plots

Usage

## S3 method for class 'pmx_dens'
plot_pmx(x, dx, ...)

Arguments

x

eta_cov object
dx

data set
...

not used for the moment

Value

ggplot2 plot

See Also

eta_cov

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

The ggPMX base plot function

Description

This function should be called internally by other plots to set general settings like , smoothing, add band, labelling, theming,...

Usage

## S3 method for class 'pmx_gpar'
plot_pmx(x, dx, ...)

Arguments

x

object of pmx_gpar type
dx

plot
...

ignored parameters

Value

ggplot2 object

See Also

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

This function plot EBE versus covariates using qq plots

Description

This function plot EBE versus covariates using qq plots

Usage

## S3 method for class 'pmx_qq'
plot_pmx(x, dx, ...)

Arguments

x

pmx_qq object
dx

data set
...

not used for the moment

Value

ggplot2 plot

See Also

eta_cov

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.residual(), plot_pmx()

This function plots residual for each observed value by finding the difference between observed and predicted points. It also fits a distribution to the residual value.

Description

This function plots residual for each observed value by finding the difference between observed and predicted points. It also fits a distribution to the residual value.

Usage

## S3 method for class 'residual'
plot_pmx(x, dx, ...)

Arguments

x

residual object
dx

data set
...

not used for the moment

Value

ggplot2 object

See Also

residual

Other plot_pmx: distrib(), eta_cov(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx()

Plot shrink in eta matric

Description

Plot shrink in eta matric

Usage

plot_shrink(x, shrink.dx, shrink)

Arguments

x

pmx_gpar object
shrink.dx

data.table of shrinkage
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one

Value

ggplot2 object

Get plots description

Description

Get plots description

Usage

plots(ctr)

Arguments

ctr

pmxClass controller object

Value

data.frame of plots

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), pmx_update(), set_data(), set_plot()

Create a pmx object

Description

Create a pmx object from a data source

Usage

pmx(
  config,
  sys = "mlx",
  directory,
  input,
  dv,
  dvid,
  cats = NULL,
  conts = NULL,
  occ = NULL,
  strats = NULL,
  settings = NULL,
  endpoint = NULL,
  sim = NULL,
  bloq = NULL,
  id = NULL,
  time = NULL,
  sim_blq = NULL
)

pmx_mlx(
  config,
  directory,
  input,
  dv,
  dvid,
  cats,
  conts,
  occ,
  strats,
  settings,
  endpoint,
  sim,
  bloq,
  id,
  time,
  sim_blq
)

pmx_mlxtran(
  file_name,
  config = "standing",
  call = FALSE,
  endpoint,
  version = -1,
  ...
)

Arguments

config

Can be either : The complete path for the configuration file, the name of configuration within the built-in list of configurations, or a configuration object.
sys

the system name can "mlx" (for Monolix 2016) or "mlx18" (for Monolix 2018/19 and later)
directory

character modelling output directory.
input

character complete path to the modelling input file
dv

character the name of measurable variable used in the input modelling file
dvid

[Optional] character observation type parameter. This is mandatory in case of multiple endpoint (PKPD).
cats

[Optional]character vector of categorical covariates
conts

[Optional]character vector of continuous covariates
occ

[Optional]character occasional covariate variable name
strats

[Optional]character extra stratification variables
settings

[Optional]pmxSettingsClass pmx_settings shared between all plots
endpoint

pmxEndpointClass or integer or charcater default to NULL of the endpoint code. pmx_endpoint
sim

pmxSimClass default to NULL. pmx_sim used for VPC, e.g.: sim = pmx_sim(file=vpc_file, irun="rep",idv="TIME")
bloq

pmxBLOQClass default to NULL. pmx_bloq specify bloq, within controller: e.g. bloq=pmx_bloq(cens = "BLOQ_name", limit = "LIMIT_name")
id

[Optional] character the name of Indvidual variable used in the input modelling file
time

[Optional] character Time variable.
sim_blq

logical if TRUE uses sim_blq values for plotting. Only for Monolix 2018 and later.
file_name

character mlxtran file path.
call

logical if TRUE the result is the parameters parsed
version

integer Non-negative integer. Non-obligatory option, if you don't use a wildcard in the file_name. Otherwise you MUST provide version and wildcard will be substituted with "version", which represents the mlxtran model version.
...

extra arguments passed to pmx_mlx.

Details

pmx_mlx is a wrapper to mlx for the MONOLIX system ( sys="mlx")

pmx_mlxtran parses mlxtran file and guess pmx_mlx arguments. In case of multi endpoint the first endpoint is selected. You can though set the endpoint through the same argument. When you set call=TRUE,no controller is created but only the parameters parsed by mlxtran. This can be very helpful, in case you would like to customize parameters (adding settings vi pmx_settings, chnag eth edefault endpoint.)

Value

pmxClass controller object.

Examples

## Example to create the controller using theophylline data
theophylline <- file.path(system.file(package = "ggPMX"), "testdata",
                          "theophylline")
WORK_DIR <- file.path(theophylline, "Monolix")
input_file <- file.path(theophylline, "data_pk.csv")

## using only mandatory variables
ctr <- pmx(
  sys="mlx",
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid ="DVID"
)
## Using covariates
ctr <- pmx(
  sys="mlx",
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid ="DVID",
  cats=c("SEX"),
  conts=c("WT0","AGE0"),
  strats="STUD"
)
## using settings parameter
ctr <- pmx(
  sys="mlx",
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid ="DVID",
  settings=list(is.draft=FALSE)
)

## using mlxtran file
mlxtran_file <- 
  file.path(system.file(package = "ggPMX"), 
    "testdata","1_popPK_model","project.mlxtran")
pmx_mlxtran(mlxtran_file)

## mlxtran , call =TRUE to get the pmx_mlx argument parsed by  pmx_mlxtran
params <- pmx_mlxtran(mlxtran_file,call=TRUE)

str(params)
# $ directory: chr results_pathile 
# $ input    : chr observation file path
# $ dv       : chr "DV"
# $ cats     : chr [1:4] "SEX" "RACE" "DISE" "ILOW"
# $ conts    : chr [1:4] "AGE0" "WT0" "HT0" "TRT"
# $ occ      : chr "ISS"
# $ dvid     : chr "YTYPE"
# $ endpoint :List of 5
# ..$ code     : chr "1"
# ..$ label    : chr ""
# ..$ unit     : chr ""
# ..$ file.code: chr "1"
# ..$ trans    : NULL
# ..- attr(*, "class")= chr "pmxEndpointClass"
# $ config   : chr "standing"

Creates BLOQ object attributes

Description

Creates BLOQ object attributes

Usage

pmx_bloq(
  cens = "CENS",
  limit = "LIMIT",
  colour = "pink",
  size = 2,
  linewidth = 1,
  alpha = 0.9,
  show = TRUE,
  ...
)

Arguments

cens

character the censoring column name
limit

character the limit column name (optional)
colour

character the color of the geom
size

numeric the size of the geom when using geom_point()
linewidth

numeric the line width of the segment when using geom_segment()
alpha

numeric the alpha of the geom
show

logical if FALSE remove all censory observations
...

any other graphical parameter

Details

To define that a measurement is censored, the observation data set should include a CENSORING column ( default to 'CENS' ) and put 1 for lower limit or -1 for upper limit.
Optionally, data set can contain have a limit column ( default to 'LIMIT') column to set the other limit.

Compute Shrinkage

Description

Compute Shrinkage

Usage

pmx_comp_shrink(
  ctr,
  fun = c("var", "sd"),
  strat.facet,
  strat.color,
  filter,
  ...
)

Arguments

ctr

pmxClass controller object
fun

character can be sd or var , var by default
strat.facet

formula optional stratification parameter
strat.color

character optional stratification parameter
filter

optional filter which will be applied to plotting data
...

others parameters not used for the moment

Value

data.table

This function can be used to define the pmx configuration used in plots. e.g. Monolix/Nonmem

Description

This function can be used to define the pmx configuration used in plots. e.g. Monolix/Nonmem

Usage

pmx_config(sys = "mlx", inputs, plots, ...)

Arguments

sys

charcarter system used , monolix,nonmem,...
inputs

charcater path to the inputs settings file (yaml format)
plots

charcater path to the inputs settings file (yaml format)
...

extra arguments not used

Details

To create a controller user can create a pmxConfig object using
- either an input template file
- or a plot template file
- or both.
By default the 'standing' configuration will be used.

Value

pmxConfig object

Examples

# *************** Create a controller using custom plot configuration ***************** ------

library(ggPMX)
theophylline <- file.path(
  system.file(package = "ggPMX"), "testdata",
  "theophylline"
)
WORK_DIR <- file.path(theophylline, "Monolix")
input_file <- file.path(theophylline, "data_pk.csv")


# create a controller with a custom plots template
ctr <-  pmx_mlx(
  config = pmx_config(
    plots=file.path( system.file(package = "ggPMX"),"examples/plots.yaml"),
    inputs = system.file(package = "ggPMX","examples/custom_inputs.yaml")
  ),
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid = "DVID",
  cats = c("SEX"),
  conts = c("WT0", "AGE0"),
  strats = "STUD"
)

## get the list of plots
ctr %>% plots
ctr %>% get_plot("custom_res_time")
ctr %>% get_plot("custom_npde_time")

Creates a deep copy of the controller

Description

Creates a deep copy of the controller

Usage

pmx_copy(ctr, keep_globals = FALSE, ...)

Arguments

ctr

pmxClass object
keep_globals

logical if TRUE we keep the global parameters changed by pmx_settings
...

extra parameters passed to pmx_settings

Details

The controller is an 'R6' object, it behaves like a reference object. Some functions ( methods) can have a side effect on the controller and modify it internally. Technically speaking we talk about chaining not piping here. However , using pmx_copy user can work on a copy of the controller.

By default the copy does not keep global parameters set using pmx_settings.

Value

an object of pmxClass

Examples

ctr <- theophylline()
cctr <- ctr %>% pmx_copy()
## Any change in the ctr has no side effect in the ctr and vice versa

Select/Map covariates using human labels

Description

Select/Map covariates using human labels

Usage

pmx_cov(values, labels = NULL)

Arguments

values

list of covariates to use to create the plot
labels

list of covariates facets labels

Details

In case of 'pmx_plot_eta_cats' and 'pmx_plot_eta_conts' you can customize the covariates and covaraites labels using 'pmx_cov'.

Value

pmxCOVObject object

Creates a density plot object

Description

Creates a density plot object

Usage

pmx_dens(
  x,
  labels,
  dname = NULL,
  xlim = 3,
  var_line = NULL,
  snd_line = NULL,
  vline = NULL,
  is.legend = TRUE,
  ...
)

Arguments

x

character variable name to sample
labels

list of texts/titles used within the plot
dname

name of dataset to be used
xlim

numeric x axis limits
var_line

list variable density graphics parameters
snd_line

list normal density graphics parameters
vline

list vertical line graphics parameters
is.legend

logical whether to add a legend (defaults TRUE)
...

others graphics arguments passed to pmx_gpar internal object.

Details

labels is a list that contains:

  • title: plot title default "IWRES density plot"

  • x: x axis label default to "Etas"

  • y: y axis label default to empty

var_line is a list that contains:

  • linetype: default to 1

  • color: default to black

  • linewidth: default to 1

snd_line is a list that contains:

  • linetype: default to 2

  • color: default to black

  • linewidth: default to 1

vline is a list that contains:

  • linetype: default to 3

  • color: default to black

  • linewidth: default to 1

Creates pmx endpoint object

Description

Creates pmx endpoint object

Usage

pmx_endpoint(code, label = "", unit = "", file.code = code, trans = NULL)

Arguments

code

character endpoint code : used to filter observations DVID==code.
label

character endpoint label: used to set title and axis labels
unit

character endpoint unit : used to set title and axis labels
file.code

character endpoint file code : used to set predictions and finegrid
files extensions in case using code parameter is not enough.
trans

list Transformation parameter not used yet.

Details

In case of multiple endpoints, pkpd case for example, we need to pass endpoint to the pmx call. Internally , ggPMX will filter the observations data set to keep only rows satisfying DVID==code. The code is also used to find the right predictions and or fingrid files. ggPMX use the configuration file to fine the path of the predictions file (like the single endpoint case) and then filter the right file using the code parameter.
For example:

  • predictions{code}.txt for mlx16

  • predictions{code}.txt and y{code}_residual for mlx18

For some tricky examples the code parameter is not enough to find the files. In that case the file.code parameter is used to distinguish the endpoint files.

Examples

## Use file.code parameter
pk_pd_path <- file.path(system.file(package = "ggPMX"), "testdata","pk_pd")

WORK_DIR <- file.path(pk_pd_path, "RESULTS")

ep <- pmx_endpoint(
  code="4",
  file.code="2"
)

input_file <- file.path(pk_pd_path, "pk_pd.csv")

ctr <- pmx_mlx(
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "dv",
  dvid = "dvid",
  cats = "sex",
  conts = "wt",
  endpoint = ep
 )

## using mlxtran 

ep <- pmx_endpoint(
  code="3",
 file.code="1"
)

mlxtran_file <- file.path(pk_pd_path, "pk_pd.mlxtran")
ctr <- pmx_mlxtran(mlxtran_file,endpoint=ep)

filter data in a pmx controller

Description

filter data in a pmx controller

Usage

pmx_filter(
  ctr,
  data_set = c("estimates", "predictions", "eta", "finegrid", "shrink", "input",
    "individual", "sim_blq"),
  pmx_exp
)

Arguments

ctr

A controller. An object of 'pmxClass'
data_set

A data_set within the controller to apply a filter to.
pmx_exp

A filter expression

Value

Returns a pmx controller with a filtered data set.

Examples

## example of global filter
ctr <- theophylline()
ctr %>% pmx_filter(data_set = "prediction", ID == 5 & TIME < 2)
ctr %>% get_data("prediction")

Get List of built-in configurations

Description

Get List of built-in configurations

Usage

pmx_get_configs(sys = "mlx")

Arguments

sys

can be mlx, by default all configurations will be listed

Value

names of the config

Examples

pmx_get_configs()

Handling pmx Graphical parameters

Description

Handling pmx Graphical parameters

Usage

pmx_gpar(
  is.title,
  labels,
  axis.title,
  which_pages,
  print,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  discrete,
  is.identity_line,
  identity_line,
  smooth_with_bloq,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  is.legend,
  legend.position
)

Arguments

is.title

logical if TRUE then a title is used for the plot
labels

list of labels, like title, subtitle, x , y
axis.title

list or element_text (same as ggplot2 axis.title theme)
which_pages

page(s) to display; if "all" display all pages, if 1 display first page, if c(1,2) display first and second pages
print

if TRUE the ouptut will be a print not a ggplot2. This is useful for rmarkdwon output to avoid verbose list index print.
axis.text

list or element_text (same as ggplot2 axis.text theme)
ranges

limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

smooth layer parameters
is.band

logical if TRUE add horizontal band
band

horizontal band parameters
is.draft

logical if TRUE add draft layer
draft

draft layer parameters
discrete

logical if TRUE x axis is discrete(FALSE by default)
is.identity_line

logical if TRUE add y=x line
identity_line

list y=x aes properties
smooth_with_bloq

logical if TRUE perform spline in plots with BLOQ data
scale_x_log10

logical if TRUE add scale_x_log10 layer
scale_y_log10

logical if TRUE add scale_y_log10 layer
color.scales

list define scales parameter in case of strat.color pmx_settings
is.legend

logical if TRUE x axis is discrete(FALSE by default)
legend.position

charcater legend position it takes the same value as the equivalent ggplot2 parameter

Details

This object contains all general graphic settings. It used internally by all pmx_plot(generic function) to set the default behavior.

Value

An object of class "pmx_gpar".

List NONMEM output tables

Description

List NONMEM output tables file names from a nm_model object.

Usage

pmx_list_nm_tables(nm_model = NULL)

Arguments

nm_model

An nm_model object generated with pmx_read_nm_model.

See Also

pmx_read_nm_model, pmx_read_nm_tables

Examples

## Not run: 
pmx_read_nm_model(file = 'run001.lst') %>% 
  pmx_list_nm_tables()

## End(Not run)

Manually define nonmem tables to be imported

Description

Manually provide names of the table files to be imported.

Usage

pmx_manual_nm_import(
  tab_names = c("sdtab", "mutab", "patab", "catab", "cotab", "mytab", "extra", "xptab",
    "cwtab"),
  tab_suffix = "",
  sim_suffix = "sim"
)

Arguments

tab_names

Provide the name of the tables to import e.g. 'sdtab', 'patab', 'cotab', 'catab' for NONMEM.
tab_suffix

Default is ”, but can be changed to any character string to be used as suffix in the table names.
sim_suffix

Default is 'sim', but can be changed to any character string to be used as suffix in the simulation table names e.g. sdtab001sim.

Creates pmx controller from an nlimxr fit object

Description

Creates pmx controller from an nlimxr fit object

Usage

pmx_nlmixr(fit, dvid, conts, cats, strats, endpoint, settings, vpc = FALSE)

Arguments

fit

nlmixr object
dvid

[Optional] character observation type parameter.
conts

[Optional]character vector of continuous covariates
cats

[Optional]character vector of categorical covariates
strats

[Optional]character extra stratification variables
endpoint

pmxEndpointClass or integer or charcater defalut to NULL of the endpoint code. pmx_endpoint
settings

[Optional]pmxSettingsClass pmx_settings
vpc

[Optional] logical a boolean indiacting if vpc should be calculated (by default TRUE)

Value

pmxClass controller object.

Creates pmx controller from NONMEM model outputs

Description

Creates pmx controller from NONMEM model outputs

Usage

pmx_nm(
  file = NULL,
  directory = ".",
  runno = NULL,
  ext = ".lst",
  table_suffix = "",
  sim_suffix = "sim",
  simfile = NULL,
  prefix = "run",
  table_names = c("sdtab", "mutab", "patab", "catab", "cotab", "mytab", "extra", "xptab",
    "cwtab"),
  dvid = "DVID",
  pred = "PRED",
  time = "TIME",
  dv = "DV",
  conts,
  cats,
  npde,
  iwres,
  ipred,
  endpoint,
  strats = "",
  settings = pmx_settings(),
  vpc = TRUE,
  bloq = NULL,
  obs = FALSE,
  quiet = FALSE
)

Arguments

file

A character vector of path to the files or a nm_table_list object created with pmx_list_nm_tables.
directory

directory of the model files.
runno

run number which is used for generating the model file name, or used for alternative import of NONMEM-output tables.
ext

Extension to be used to generate model file name. Should be one of'.lst' (default), '.out', '.res', '.mod' or '.ctl' for NONMEM.
table_suffix

suffix of the output tables, standard is "" (no suffix).
sim_suffix

suffix of the simulation output tables, standard is "sim" (e.g. stdab1sim).
simfile

Useful if the simulation is peformed post-hoc and an additional simulation model file is generated e.g. "simulation.lst"; similar to "file" see above.
prefix

Prefix to be used to generate model file name. Used in combination with runno and ext.
table_names

contains the names of the NONMEM-output tables e.g. "sdtab", "patab", "cotab", "catab".
dvid

[Optional] character observation type parameter, mandatory in case of multiple endpoint (PKPD). Standard = "DVID"
pred

[Optional] character specifing variable name of the population prediction (standard ggPMX nomenclautre = "PRED")
time

[Optional] character specifing variable name of time (standard ggPMX nomenclautre = "TIME")
dv

character the name of measurable variable used in the input modelling file (standard ggPMX nomenclautre = "DV")
conts

[Optional] character vector of continuous covariates (automatically detected if "cotab" is provided)
cats

[Optional] character vector of categorical covariates (automatically detected if "catab" is provided)
npde

[Optional] character specifing variable name of the normalized population predictor (standard ggPMX nomenclautre = "NPDE")
iwres

[Optional] character specifing variable name of the individual weighted residuals (standard ggPMX nomenclautre = "IWRES")
ipred

[Optional] character specifing variable name of the individual population prediction (standard ggPMX nomenclautre = "IPRED")
endpoint

[Optional] pmxEndpointClass or integer or charcater default to NULL of the endpoint code. pmx_endpoint
strats

[Optional] character extra stratification variables
settings

pmxSettingsClass pmx_settings shared between all plots
vpc

logical a boolean indiacting if vpc should be calculated, simulation tables are required for VPC generation (by default TRUE)
bloq

pmxBLOQClass default to NULL. pmx_bloq specify bloq, within controller: e.g. bloq=pmx_bloq(cens = "BLOQ_name", limit = "LIMIT_name")
obs

logical if set to TRUE will filter dataset according to "MDV", default is FALSE
quiet

Logical, if FALSE messages are printed to the console.

Value

pmxClass controller object.

Author(s)

The ggPMX NONMEM reader (pmx_nm) is strongly based on NONMEM reading functions of the xpose package (v.0.4.11) (Thanks to Benjamin Guiastrennec) To avoid conflicts with the xpose package, the necessary xpose-based functions have been renamed with a "pmx_" prefix. If the user wants to use individual functions e.g. "read_nm_tables" please use the xpose-package

Examples

## using only runnumber 
# ctr <- pmx_nm(
#  directory=model_dir,
#  runno = "001" 
#)

## using a model file (e.g. run001.lst)
#ctr <- pmx_nm(
#  directory=model_dir,
#  file = "run001.lst" 
#)

## if simulation was performed post-hoc, an additional simulation file can be loaded for VPC
#ctr <- pmx_nm(
#  directory=model_dir,
#  file = "run001.lst", 
#  simfile = "simulation.ctl"
#)

## loading with individual table(s)-names
#ctr <- pmx_nm(directory = model_dir,
#              runno = 3, 
#              table_names = "xptab")

Generic pmx plot

Description

Generic pmx plot

Usage

pmx_plot(ctr, pname, ...)

Arguments

ctr

pmxClass pmx controller
pname

plot name
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • pmx_qq quantile-quantile plot object

  • pmx_update function.

Generic pmx stratified plot

Description

Generic pmx stratified plot

Usage

pmx_plot_cats(ctr, pname, cats, chunk = "", print = TRUE, ...)

Arguments

ctr

pmxClass pmx controller
pname

plot name
cats

list of categorical variables. By default all of them
chunk

chunk name
print

logical if TRUE print plots otherwise the list of plots is returned
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • pmx_qq quantile-quantile plot object

  • pmx_update function.

Eta matrix plot

Description

Eta matrix plot

Usage

pmx_plot_eta_matrix(
  ctr,
  title,
  dname,
  type.eta,
  text_color,
  is.shrink,
  shrink,
  point,
  is.smooth,
  smooth,
  is.hline,
  hline,
  is.vreference_line,
  vreference_line,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

Arguments

ctr

pmx controller
title

character the plot title
dname

name of dataset to be used
type.eta

character type of eat can be 'mode' or 'mean'.'mode' by default
text_color

color of the correlation text in the upper matrix
is.shrink

logical if TRUE add shrinkage to the plot
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one
point

list geom_point graphical parameter
is.smooth

logical if TRUE add smoothing to lower matrix plots
smooth

list geom_smooth graphical parameters
is.hline

logical if TRUE add horizontal line to lower matrix plots
hline

list geom_hline graphical parameters
is.vreference_line

logical if TRUE add reference line to diag plots
vreference_line

list geom_vline graphical parameters

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • eta_pairs ggPMX internal function for eta matrix plot.

  • pmx_update function.

eta_pairs parameters

Value

ggplot2 object

Examples

# basic use  ---------------------------------------

ctr <- theophylline()
p <- ctr %>% pmx_plot_eta_matrix

# update graphical parameter  ----------------------

## update labels
ctr %>% pmx_plot_eta_matrix(
  labels = list(title = "Eta matrix new title")
)

## remove draft
ctr %>% pmx_plot_eta_matrix(is.draft = FALSE)

## change text color line
ctr %>% pmx_plot_eta_matrix(
  text_color="red",
  shrink=pmx_shrink(mapping=aes(color="magenta"))
  )

## custom point aes and static parameters
## we can customize any geom_point parameter
ctr %>% pmx_plot_eta_matrix(
  point = list(color = "blue", shape = 4)
)



# stratification  ----------------------------------

## IGNORE continuous stratification
ctr %>% pmx_plot_eta_matrix(strat.color = "WT0")
## IGNORE  categorical stratification
ctr %>% pmx_plot_eta_matrix(strat.facet = ~SEX)

# subsetting  --------------------------------------

## we can use any expression involving the data
ctr %>% pmx_plot_eta_matrix(filter = EFFECT%in%  c("Cl","ka"))

Individual plot

Description

Individual plot

Usage

pmx_plot_individual(
  ctr,
  which_pages = 1L,
  print = FALSE,
  dname,
  pred_line,
  ipred_line,
  point,
  is.legend,
  use.finegrid,
  bloq,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

Arguments

ctr

pmx controller
which_pages

integer page(s) to display, or character "all" to display all pages (argument previously called npage, now deprecated)
print

logical if TRUE the ouptut will be a print not a ggplot2. This is useful for rmarkdwon output to avoid verbose list index print.
dname

character name of dataset to be used. User can create his own dataset using set_data and pass it as dname to be plotted.
pred_line

list some ipred line geom properties aesthetics
ipred_line

list some pred line geom properties aesthetics
point

list some point geom properties aesthetics
is.legend

logical if TRUE add a legend
use.finegrid

logical if FALSE use predictions data set
bloq

pmxBLOQ object created by pmx_bloq.

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

individual parameters

Value

ggplot2 or list of ggplot2 objects

Examples

# basic use  ---------------------------------------

ctr <- theophylline()
ctr %>% pmx_plot_individual(which_pages = 1)
## multiple pages
ctr %>% pmx_plot_individual(which_pages = c(1, 3))
## change faceting
ctr %>% pmx_plot_individual(facets = list(nrow = 5, ncol = 5), which_pages = 2)


# update graphical parameter  ----------------------

## update labels
ctr %>% pmx_plot_individual(
  labels = list(title = "Custom individual plot")
)

## remove draft
ctr %>% pmx_plot_individual(is.draft = FALSE)

## Customize ipred_line with any geom_line parameter
ctr %>% pmx_plot_individual(
  pred_line = list(color = "red", linetype = 20, alpha = 0.5)
)

## Customize ipred_line with any geom_line parameter
ctr %>% pmx_plot_individual(
  ipred_line = list(size = 5)
)


## Customize any geom_point parameter
ctr %>% pmx_plot_individual(
  point = list(aes(alpha = DV), color = "green", shape = 4)
)


## legend

p <- ctr %>% pmx_plot_individual(
  is.legend=TRUE,
  point=list(shape=20),
  pred_line=list(linetype=6)
)

# # stratification  ----------------------------------
#
# ## continuous stratification
ctr %>% pmx_plot_individual(strat.color = "WT0")

# # subsetting  --------------------------------------
#
# ## we can use any expression involving the data
# ## filter and stratify
ctr %>% pmx_plot_individual(
  filter = SEX == 1, strat.facet = ~SEX, 
  facets = list(nrow = 5, ncol = 5))

# # transformation  --------------------------------------
#
# ## apply a log transformation in y
ctr %>% pmx_plot_individual(trans = "log10_y")
# ## apply a custonm trsnformation to normalize axis between 0 and 1

## get a list of parameter
p <- ctr %>% pmx_plot_individual(
  which_pages="all",
  point=list(shape=4,color='blue',size=10),
  facets = list(nrow = 5, ncol = 5),
  labels = list(title = "My individuals",x='my time',y='PD data')
)

IWRES density plot

Description

IWRES density plot

Usage

pmx_plot_iwres_dens(
  ctr,
  sim_blq,
  dname,
  xlim,
  var_line,
  snd_line,
  vline,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

Arguments

ctr

pmx controller
sim_blq

logical if TRUE uses sim_blq as dataset for plotting instead of predictions.
dname

character name of dataset to be used. User can create his own dataset using set_data and pass it as dname to be plotted.
xlim

numeric x axis limits
var_line

list variable denstiy graphics parameters
snd_line

list normal denstiy graphics parameters
vline

list vertical line graphics parameters

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

pmx_dens parameters

Value

ggplot2 or list of ggplot2 objects

VPC plot

Description

VPC plot

Usage

pmx_plot_vpc(
  ctr,
  type,
  idv,
  obs,
  pi,
  ci,
  rug,
  bin,
  is.legend,
  sim_blq,
  dname,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  is.footnote,
  ...
)

Arguments

ctr

pmx controller
type

charcater can be either percentile or scatter
idv

chracater individual variable
obs

pmx_vpc_obs object observation layer pmx_vpc_obs
pi

pmx_vpc_pi object percentile layer pmx_vpc_pi
ci

pmx_vpc_ci object confidence interval layer pmx_vpc_ci
rug

pmx_vpc_rug object rug layer pmx_vpc_rug. Note: consider not using a rug layer when bin[["within_strat"]]=TRUE, since the rugs plotted will not reflect the bins.
bin

pmx_vpc_bin object pmx_vpc_bin specify within pmx_plot_vpc() e.g.: bin = pmx_vpc_bin(style = "kmeans", n = 10)
is.legend

logical if TRUE add legend
sim_blq

logical if TRUE uses sim_blq values for plotting. Only for Monolix 2018 and later.
dname

added for compatibility with other ggPMX plots

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
is.footnote

logical if TRUE add footnote
...

others graphics parameters passed :

pmx_vpc parameters

Details

You can use pmx_vpc_bin to set the bin parameters. In case of stratification, binning can be different for each strat level (case within_strat equal to FALSE).

Value

ggplot2 or list of ggplot2 objects

See Also

Other vpc: pmx_vpc_bin(), pmx_vpc_ci(), pmx_vpc_obs(), pmx_vpc_pi(), pmx_vpc_rug(), pmx_vpc()

Examples

library(ggPMX)

theo_path <- file.path(
  system.file(package = "ggPMX"), "testdata",
  "theophylline"
)
WORK_DIR <- file.path(theo_path, "Monolix")
input_file <- file.path(theo_path, "data_pk.csv")
vpc_file <- file.path(theo_path, "sim.csv")

ctr <- pmx_mlx(
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid = "dvid",
  cats = c("SEX"),
  conts = c("WT0", "AGE0"),
  strats = "STUD",
  settings = pmx_settings(
    use.labels=TRUE,
    cats.labels=list(
      SEX=c("0"="Male","1"="Female")
    )
  ),
  sim = pmx_sim(
    file = vpc_file,
    irun ="rep",
    idv="TIME"
  )
)


ctr %>% pmx_plot_vpc(
  strat.facet=~SEX,
  facets=list(nrow=2),
  type="percentile",
  is.draft = FALSE,
  pi = pmx_vpc_pi(interval = c(0.1,0.9),
              median=list(color="green"),
              extreme= list(color="green")),
  obs = pmx_vpc_obs(color="blue",shape=18,size=2),
  ci = pmx_vpc_ci(interval = c(0.1,0.9),
              median=list(fill="pink")),
  bin=pmx_vpc_bin("kmeans",n=5)
)

ctr %>% 
  pmx_plot_vpc(bin= pmx_vpc_bin(
     style = "fixed",
     fixedBreaks=c(-10,2, 5, 10,15,50))
  )

# example with legend 

ctr %>% pmx_plot_vpc(
  is.legend = TRUE,
  pi = pmx_vpc_pi(interval=c(0.02,0.98),median = list(linetype="dotted")),
  ci = pmx_vpc_ci(interval = c(0.05,0.95),median=list(fill="red"))
)

This function creates a qq plot object

Description

This function creates a qq plot object

Usage

pmx_qq(
  x,
  labels,
  dname = NULL,
  point = NULL,
  xmax = TRUE,
  facets = NULL,
  is.reference_line = NULL,
  reference_line = NULL,
  is.shrink = NULL,
  shrink = NULL,
  is.hline = NULL,
  hline = NULL,
  is.vline = NULL,
  vline = NULL,
  ...
)

Arguments

x

character variable name to sample
labels

list of texts/titles used within the plot
dname

name of dataset to be used
point

list geom_point attributes color, shape,...
xmax

logical if FALSE do not use max(aes(x)) as limits default to TRUE
facets

list
is.reference_line

logical if TRUE add reference line to the plot
reference_line

list geom_line attributes. Used only for pmx_plot_eta_qq
is.shrink

logical if TRUE add shrinkage to the plot
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one
is.hline

logical if TRUE add horizontal line y=0 ( TRUE by default)
hline

geom hline graphical parameters
is.vline

logical if TRUE add vertical line x=0 ( TRUE by default)
vline

geom vline graphical parameters
...

others graphics arguments passed to pmx_gpar internal object.

Details

labels is a list that contains:

  • title: plot title default "EBE vs. covariates"

  • x: x axis label default to "Etas"

  • y: y axis label default to empty

point is a list that contains:

  • shape: default to 1

  • color: default to black

  • size: default to 1

Value

pmx_qq object

Quantile-quantile plots

Description

Quantile-quantile plots

Quantile-quantile plot of IWRES

Quantile-quantile plot of eta variables

Quantile-quantile plot of NPDE

Quantile-quantile plot of NPD

Quantile-quantile plot of CWRES

Usage

pmx_qq_plot(
  dname,
  point,
  is.reference_line,
  reference_line,
  is.shrink,
  shrink,
  is.hline,
  hline,
  is.vline,
  vline,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

pmx_plot_iwres_qq(ctr, ...)

pmx_plot_eta_qq(ctr, ...)

pmx_plot_npde_qq(ctr, ...)

pmx_plot_npd_qq(ctr, ...)

pmx_plot_cwres_qq(ctr, ...)

Arguments

dname

name of dataset to be used
point

list geom_point parameters.
is.reference_line

logical if TRUE add reference line to the plot
reference_line

list geom_abline parameters.
is.shrink

logical if TRUE add shrinkage to the plot
shrink

pmxShrinkClass shrinkage graphical parameter or list coercible into one
is.hline

logical if TRUE add horizontal line y=0 ( TRUE by default)
hline

list geom hline graphical parameters
is.vline

logical if TRUE add vertical line x=0 ( TRUE by default)
vline

list geom vline graphical parameters

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

an object of class pmx_gpar
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • pmx_qq quantile-quantile plot object.

  • pmx_update function.

pmx_qq parameters
ctr

pmx controller

Value

ggplot2 object

Examples

# *************** basic use ***************** ------

ctr <- theophylline()
ctr %>% pmx_plot_eta_qq
ctr %>% pmx_plot_npde_qq
ctr %>% pmx_plot_iwres_qq

# update graphical parameter  ----------------------

## add reference line
ctr %>% pmx_plot_npde_qq(reference_line=list(color="blue"))

## remove reference line
ctr %>% pmx_plot_eta_qq(reference_line=NULL)


# stratification  ----------------------------------

## categorical stratification color parameter
ctr %>% pmx_plot_iwres_qq(strat.facet=~STUD,strat.color="SEX")
## categorical stratification facetting
ctr %>% pmx_plot_eta_qq(strat.facet = ~SEX)

## do not use symmetric axis
ctr %>% pmx_plot_npde_qq(xmax=FALSE,reference_line=list())

NONMEM output file import function

Description

Quickly import NONMEM output files into R.

Usage

pmx_read_nm_files(
  runno = NULL,
  prefix = "run",
  ext = c(".ext", ".cor", ".cov", ".phi", ".grd", ".shk"),
  file = NULL,
  dir = NULL,
  quiet = FALSE
)

Arguments

runno

Run number to be evaluated.
prefix

Prefix of the model file names.
ext

A vector of the file extension to import. By default '.ext', '.cor', '.cov', '.phi', '.grd', '.shk' files are listed.
file

Names of the model output file to be imported. Alternative argument to prefix, runno and ext.
dir

Location of the model files.
quiet

Logical, if FALSE messages are printed to the console.

Examples

## Not run: 
# Using the `file` argument to import a model file:
ext_file <- pmx_read_nm_files(file = 'run001.ext', dir = 'models')

# Using the `runno` argument to import a model file:
ext_file <- pmx_read_nm_files(runno = '001', ext = '.ext', dir = 'models')

## End(Not run)

NONMEM model file parser

Description

Parse NONMEM model files in R format

Usage

pmx_read_nm_model(
  runno = NULL,
  prefix = "run",
  ext = ".lst",
  file = NULL,
  dir = NULL
)

Arguments

runno

run number which is used for generating the model file name
prefix

Prefix to be used to generate model file name. Used in combination with runno and ext.
ext

Extension to be used to generate model file name. Should be one of'.lst' (default), '.out', '.res', '.mod' or '.ctl' for NONMEM.
file

A character vector of path to the files or a nm_table_list object created with list_nm_tables.
dir

directory of the model files.

Value

A tibble of class model containing the following columns:

  • problem: a numeric identifier for the $PROBLEM associated with the code.

  • level: a unique numeric identifier to each subroutine block associated with the code.

  • subroutine: a character identifier named after the 3 first letters of the subroutine name e.g. '$THETA' and '$TABLE' will become 'the' and 'tab' respectively. In addition all output from the .lst is labeled 'lst', the general nonmem output e.g. NM-TRAN messages are labelled 'oth'. With priors thp, tpv, omp, opd, sip, spd abbreviations are given to the THETAP, THETAPV, OMEGAP, etc.

  • code: the code without comments or subroutine names e.g. '$THETA 0.5 ; TVCL' will return '0.5'.

  • comment: the last comment of a record e.g. '0.5 ; Clearance (L/h) ; TVCL' will return 'TVCL'.

See Also

pmx_read_nm_tables

Examples

## Not run: 
# Using the `file` argument to import a model file:
nm_model <- pmx_read_nm_model(file = 'run001.lst', dir = 'models')

# Using the `runno` argument to import a model file:
nm_model <- pmx_read_nm_model(runno = '001', ext = '.lst', dir = 'models')

## End(Not run)

NONMEM output table import function

Description

Quickly import NONMEM output tables into R. This function automatically detects the optimal settings to import the tables from nonmem. It is based on the read_nm_tables function of xpose. Slight adjustment were made for purposes of pmx_nm()

Usage

pmx_read_nm_tables(
  file = NULL,
  dir = NULL,
  combined = TRUE,
  rm_duplicates = TRUE,
  quiet = FALSE,
  simtab = NULL,
  ziptab = TRUE,
  user_mode = TRUE,
  ...
)

Arguments

file

A character vector of path to the files or a nm_table_list object created with list_nm_tables.
dir

Location of the model files.
combined

Logical value indicating whether multiple tables should be combined into a single one. If the number of rows does not match an error will be returned.
rm_duplicates

Logical value indicating whether duplicated columns should be removed.
quiet

Logical, if FALSE messages are printed to the console.
simtab

If TRUE only reads in simulation tables, if FALSE only reads estimation tables. Default NULL reads all tables.
ziptab

If TRUE search for the tables that have been compressed and renamed ??<file>.zip'.
user_mode

Adjustment to the original code: usermode is set to "usermode = TRUE" in order to improve this function for purposes of pmx_nm() (nonmem_reader.R), In order to use this function seperatly, the use of the original function in the xpose package is advised.
...

Additional arguments to be passed to the read_table or read_csv functions.

Table format requirement

When using pmx_read_nm_tables with the combined argument set to FALSE an ID column must be present in all data tables. When combined is set to TRUE instead an ID column must be present in at least one table for each problem and for each 'firstonly' category. ID columns are required to properly combine/merge tables and removing NA records. If the ID column is missing from a table and combined = FALSE pmx_read_nm_tables will return the following warning: Unknown variables: `ID`. While the data is returned beware that NA records might be left in the data and the output should be checked carefully. If combined = TRUE pmx_read_nm_tables is more strict and will return the following warning instead: Dropped `<tablenames>` due to missing required `ID` column..

Examples

## Not run: 

# Adjustment to the original code: usermode is set to "usermode = TRUE" 
# in order to improve this function for purposes of pmx_nm() (nonmem_reader.R)
# In order to use this function seperatly, the use of the original function in 
# the xpose package is advised.

# Import tables manually and return them as a list of individual tables
nm_tables <- pmx_read_nm_tables(file = c('sdtab001', 'patab001'), 
                            dir = 'models', combined = FALSE)

# Import tables manually and return them as a single merged table
nm_tables <- pmx_read_nm_tables(file = c('sdtab001', 'patab001'), 
                            dir = 'models', combined = TRUE)


## End(Not run)

Register plot

Description

Register plot

Usage

pmx_register_plot(ctr, pp, pname = NULL)

Arguments

ctr

pmxClass controller
pp

ggplot2 plot
pname

character plot nme

Generates ggpmX report from a pre-defined template

Description

Generates ggpmX report from a pre-defined template

Usage

pmx_report(
  contr,
  name,
  save_dir,
  plots_subdir = "ggpmx_GOF",
  output = c("all", "plots", "report"),
  template = "standing",
  footnote = output == "all",
  edit = FALSE,
  format = NULL,
  title,
  ...
)

Arguments

contr

pmxClass controller
name

character The report name
save_dir

Output directory. A directory to write the results files to
plots_subdir

Output folder name, ggpmx_GOF by default
output

character the result type, can be
a standalone directory of plots or a report document as defined in the template
(pdf, docx,..) ,or both
template

character ggPMX predefined template or the path to a custom rmarkdown template.
Use pmx_report_template to get the list of available templates
footnote

logical TRUE to add a footnote to the generated plots. The default footnote is to add
the path where the plot is saved.
edit

logical TRUE to edit the template immediately
format

character The output document format. By default, a word report is generated.
User can specify one or more formats from c("word","pdf","html","all"). format "all" to generate all formats.
title

character report title (optional)
...

extra parameters depending in the template used

Details

pmx_report uses pre-defined template .Rmd to generate the report. The idea is to pass the controller as a report argument using knitr params artifact.

Examples

library(ggPMX)
# you probably want to create the report in your own directory
# But using a temp directory allows for easy cleanup

## case1: generate a single report
withr::with_tempdir({
  ctr <- theophylline()
  ctr %>% pmx_report(
    name = "my_report",
    save_dir = getwd(),
    output="report"
  )
})


## case2: generate standalone plots
withr::with_tempdir({
  ctr <- theophylline()
  ctr %>% pmx_report(
    name = "my_report",
    save_dir = getwd(),
    output="plots"
  )
})


## case3: generate both : reports + plots
## by default add footnote
## Note, you can force footnote to FALSE using footnote parameter
withr::with_tempdir({
  ctr <- theophylline()
  ctr %>% pmx_report(
    name="my_report",
    save_dir=getwd(),
    output="all"
  )
})


## case4 : generate standalone plots with footnotes
withr::with_tempdir({
  ctr <- theophylline()
  ctr %>% pmx_report(
    name="my_report",
    save_dir=getwd(),
    footnote=TRUE,
    output="plots"
  )
})


##  case6: dynamic edit
## uncomment to run
# ctr <- theophylline()
# ctr %>% pmx_report(
#   save_dir = file.path(getwd(),"case6"),
#   name="my_report",
#   output="report",
#   edit = TRUE)


## case7 : generate individual plots report
## ctr <- theophylline()
## ctr %>% pmx_report(
##   name="report2",
##   save_dir = getwd(),
##   template="individual",
##   format="all",
##   which_pages=1:2
## )

Gets build-in report templates

Description

Gets build-in report templates

Usage

pmx_report_template()

Value

list of templates names

Examples

pmx_report_template()

Create controller global settings

Description

Create controller global settings

Usage

pmx_settings(
  is.draft = TRUE,
  use.abbrev = TRUE,
  color.scales = NULL,
  cats.labels = NULL,
  use.labels = FALSE,
  use.titles = FALSE,
  effects = NULL,
  ...
)

Arguments

is.draft

logical if FALSE any plot is without draft annotation
use.abbrev

logical if FALSE use full description from abbreviation mapping for axis names
color.scales

list list containing elements of scale_color_manual
cats.labels

list list of named vectors for each factor
use.labels

logical if TRUE replace factor named by cats.labels
use.titles

logical FALSE to generate plots without titles
effects

list list of effects levels and labels
...

extra parameter not used yet

Value

pmxSettingsClass object

Examples

library(ggPMX)
library(ggplot2)
ctr <- theophylline(
  settings=
    pmx_settings(
      color.scales=list(
        "Study",
        labels=c("Study 1","Study 2"),
        values=c("1"="lightyellow","2"="lightblue")),
      cats.labels=list(
        SEX=c("0"="M","1"="F"),
        STUD=c("1"="Study 1","2"="Study 2")
      ),
      use.abbrev=TRUE,
      is.draft=TRUE,
      use.labels=TRUE
    )
)



ctr %>% 
  pmx_plot_npde_time(strat.color="STUD",strat.facet=~SEX)
# 
# 
ctr  %>%
  pmx_plot_eta_box(strat.color="STUD", strat.facet =~SEX)

ctr  %>%  pmx_plot_eta_hist

Create shrinkage parameter object

Description

Create shrinkage parameter object

Usage

pmx_shrink(
  fun = c("var", "sd"),
  size = 1,
  color = "green",
  vjust = 1.5,
  hjust = 0.5,
  ...
)

Arguments

fun

list shrinkage function can be sd or var
size

numeric shrinkage text size
color

character shrinkage text color
vjust

numeric shrinkage position vertical adjustment
hjust

numeric shrinkage position horizontal adjustment
...

any other parameter

Value

pmxShrinkClass object (list)

Create simulation object

Description

Create simulation object

Usage

pmx_sim(file, data, irun, idv)

Arguments

file

character path to the simulation file
data

data.table simulation data
irun

character name of the simulation column
idv

character name of the ind. variable

Examples

library(ggPMX)

theo_path <- file.path(
  system.file(package = "ggPMX"), "testdata",
  "theophylline"
)
WORK_DIR <- file.path(theo_path, "Monolix")
input_file <- file.path(theo_path, "data_pk.csv")
vpc_file <- file.path(theo_path, "sim.csv")

ctr <- pmx_mlx(
  config = "standing",
  directory = WORK_DIR,
  input = input_file,
  dv = "Y",
  dvid = "dvid",
  cats = c("SEX"),
  conts = c("WT0", "AGE0"),
  strats = "STUD",
  settings = pmx_settings(
    use.labels=TRUE,
    cats.labels=list(
      SEX=c("0"="Male","1"="Female")
    )
  ),
  sim = pmx_sim(
    file = vpc_file,
    irun ="rep",
    idv="TIME"
  )
)


ctr %>% pmx_plot_vpc(
  strat.facet=~SEX,
  facets=list(nrow=2),
  type="percentile",
  is.draft = FALSE,
  pi = pmx_vpc_pi(interval = c(0.1,0.9),
              median=list(color="green"),
              extreme= list(color="green")),
  obs = pmx_vpc_obs(color="blue",shape=18,size=2),
  ci = pmx_vpc_ci(interval = c(0.1,0.9),
              median=list(fill="pink")),
  bin=pmx_vpc_bin("kmeans",n=5)
)

ctr %>% 
  pmx_plot_vpc(bin= pmx_vpc_bin(
     style = "fixed",
     fixedBreaks=c(-10,2, 5, 10,15,50))
  )

# example with legend 

ctr %>% pmx_plot_vpc(
  is.legend = TRUE,
  pi = pmx_vpc_pi(interval=c(0.02,0.98),median = list(linetype="dotted")),
  ci = pmx_vpc_ci(interval = c(0.05,0.95),median=list(fill="red"))
)

Define ggPMX theme

Description

This theme is a simple wrapper gdoc theme from ggthems package.

Usage

pmx_theme(...)

Arguments

...

can contain any valid argument of ggplot2 theme object.

Update plot object

Description

Update plot object

Usage

pmx_update(
  ctr,
  pname,
  strat.color = NULL,
  strat.facet = NULL,
  color.scales = NULL,
  filter = NULL,
  trans = NULL,
  ...,
  pmxgpar = NULL
)

Arguments

ctr

pmxClass controller object
pname

character the plot name to update
strat.color

character optional stratification parameter
strat.facet

formula optional stratification parameter
color.scales

list can be used with strat.color to set scale_color_manual pmx_gpar function.
filter

optional filter which will be applied to plotting data
trans

character define the transformation to apply on x or y or both variables
...

others graphical parameters given to set the plot
pmxgpar

a object of class pmx_gpar possibly the output of the

Details

trans is a transformation that user can apply to x, or y coordinates. The transformation is applied to the data before the plotting. This gives more felxiblilty to the user and also conserves all static positions like annotations ( draft specially)

For example:

var_x apply variance to x coordinates the variance function

var_xy apply variance to both This mechanism is applied internally to scale log.

Value

controller object with the plot updated

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), set_data(), set_plot()

Creates vpc object

Description

Creates vpc object

Usage

pmx_vpc(
  type = c("percentile", "scatter"),
  idv = "TIME",
  obs = pmx_vpc_obs(),
  pi = pmx_vpc_pi(),
  ci = pmx_vpc_ci(),
  rug = pmx_vpc_rug(),
  bin = pmx_vpc_bin(),
  labels = NULL,
  facets = NULL,
  is.legend = TRUE,
  is.footnote = TRUE,
  dname = NULL,
  ...
)

Arguments

type

charcater can be either percentile or scatter
idv

chracater individual variable
obs

pmx_vpc_obs object observation layer pmx_vpc_obs
pi

pmx_vpc_pi object percentile layer pmx_vpc_pi
ci

pmx_vpc_ci object confidence interval layer pmx_vpc_ci
rug

pmx_vpc_rug object rug layer pmx_vpc_rug
bin

pmx_vpc_bin object pmx_vpc_bin
labels

list define title and axis labels
facets

is a list of parameters passed to facet_wrap in case of startification
is.legend

logical if TRUE add legend
is.footnote

logical if TRUE add footnote
dname

added for compatibility with other ggPMX plots
...

extra parameters passed to base graphical parameters

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_bin(), pmx_vpc_ci(), pmx_vpc_obs(), pmx_vpc_pi(), pmx_vpc_rug()

Creates vpc bins

Description

Creates vpc bins

Usage

pmx_vpc_bin(style, within_strat = TRUE, seed = 42, ...)

Arguments

style

character style chosen on of the:
"fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust" or "jenks"
within_strat

logical if TRUE compute the bining for each strat level.
By default t is false and bining are equal for all stratifications levels.
seed

integer used in set.seed call to ensure
reproducibility if style is "kmeans". Set to NULL if this
is not desired.
...

other classInt::classIntervals parameters excpet style and n

Details

This is a wrapper to the bin based VPC

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_ci(), pmx_vpc_obs(), pmx_vpc_pi(), pmx_vpc_rug(), pmx_vpc()

Sets vpc confidence interval layer

Description

Sets vpc confidence interval layer

Usage

pmx_vpc_ci(
  show = c("all", "median"),
  interval = c(0.025, 0.975),
  method = c("ribbon", "rectangle"),
  median = list(fill = "red", alpha = 0.3),
  extreme = list(fill = "#3388cc", alpha = 0.3)
)

Arguments

show

charcater how areas are displayed:

  • show="all" areas will be displayed for each of the 3 percentiles.

  • show="median" Show only median area.

interval

numeric quantiles values default to c(.05,.95)
method

charcater which areas are displayed:

  • method="ribbon" areas are ribbons.

  • method="rectangle" areas are horizontal rectangles.

median

list containing:

  • fill character Color of the area representing the CI for the median. Default: "#3388cc".

  • alpha numeric Transparency of the area representing the PI for the median. Default=0.3.

extreme

list containing:

  • fill character Color of the area representing the CI for the extreme percentiles. Default: "#3388cc".

  • alpha numeric Transparency of the area representing the PI for the extreme percentiles. Default=0.3.

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_bin(), pmx_vpc_obs(), pmx_vpc_pi(), pmx_vpc_rug(), pmx_vpc()

Sets vpc observation layer

Description

Sets vpc observation layer

Usage

pmx_vpc_obs(show = TRUE, color = "#000000", size = 1, alpha = 0.7, shape = 1)

Arguments

show

logical if TRUE show observation points
color

character Color of the observed endpoint values. Default: "#000000".
size

numeric Size of the observed endpoint values. Default: 1.
alpha

numeric Transparency of the observed endpoint values. Default: 0.7.
shape

numeric Shape of the observed endpoint values. Default: 1.

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_bin(), pmx_vpc_ci(), pmx_vpc_pi(), pmx_vpc_rug(), pmx_vpc()

Sets vpc percentile layer

Description

Sets vpc percentile layer

Usage

pmx_vpc_pi(
  show = c("all", "median", "area"),
  interval = c(0.05, 0.95),
  median = list(color = "#000000", linewidth = 1, alpha = 0.7, linetype = "solid"),
  extreme = list(color = "#000000", linewidth = 1, alpha = 0.7, linetype = "dashed"),
  area = list(fill = "blue", alpha = 0.1)
)

Arguments

show

charcater how lines are displayed:

  • show=all lines will be displayed for each of the 3 percentiles. with a shaded area.

  • show=median Show only median line.

  • show=area Show only median line and the shaded area

interval

numeric quantiles values default to c(.05,.95)
median

list containing:

  • color charcater Color of the median percentile line. Default: "#000000".

  • linewidth numeric Thickness of the median percentile line. Default: 1.

  • alpha numeric Transparency of the median percentile line. Default: 0.7.

  • linetype charcater Linetype of the median percentile line. Default: "solid".

extreme

list containing:

  • color charcater Color of the median percentile line. Default: "#000000".

  • linewidth numeric Thickness of the median percentile line. Default: 1.

  • alpha numeric Transparency of the median percentile line. Default: 0.7.

  • linetype charcater Linetype of the median percentile line. Default: "solid"

area

list containing:

  • fill charcater Color of the shaded area. Default: "blue".

  • alpha numeric Transparency of the sahded area. Default: 0.1.

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_bin(), pmx_vpc_ci(), pmx_vpc_obs(), pmx_vpc_rug(), pmx_vpc()

Sets vpc rug layer

Description

Sets vpc rug layer

Usage

pmx_vpc_rug(show = TRUE, color = "#000000", linewidth = 1, alpha = 0.7, size)

Arguments

show

logical If TRUE show bin separators
color

character Color of the rug. Default: "#000000".
linewidth

numeric Thickness of the rug. Default: 1.
alpha

numeric Transparency of the rug. Default: 0.7.
size

numeric Depreciated thickness of the rug. Default: 1.

Details

When the vpc confidence interval layer method is rectangles we don't show rug separators.

See Also

Other vpc: pmx_plot_vpc(), pmx_vpc_bin(), pmx_vpc_ci(), pmx_vpc_obs(), pmx_vpc_pi(), pmx_vpc()

This function can be used to set ggPMX options

Description

getPmxOption retrieves the value of a ggPMX option. ggPMXOptions sets the value of ggPMX options; it can also be used to return a list of all currently-set ggPMX options.

Usage

pmxOptions(...)

Arguments

...

Options to set, with the form name = value.

Details

There is a global option set, which is available by default.

Options used in ggPMX

  • template_dir: path to template directory

Examples

## Not run: 
pmxOptions(template_dir = PATH_TO_CUSTOM_CONFIGURATION)

## End(Not run)

S3 print abbreviation

Description

S3 print abbreviation

Usage

## S3 method for class 'abbreviation'
print(x, ...)

Arguments

x

object of class configs
...

pass additional options (not used presently)

Value

print abbreviation

This function can be used to print configuration of the defined object using S3 method.

Description

This function can be used to print configuration of the defined object using S3 method.

Usage

## S3 method for class 'configs'
print(x, ...)

Arguments

x

object of class configs
...

pass additional options (not used presently)

Value

print result

Print pmx_gpar object

Description

Print pmx_gpar object

Usage

## S3 method for class 'pmx_gpar'
print(x, ...)

Arguments

x

pmx_gpar object
...

argument passed to print ( to satisfy generic)

Value

a character description of graphical parameters

Print pmxClass object

Description

Print pmxClass object

Usage

## S3 method for class 'pmxClass'
print(x, ...)

Arguments

x

pmxClass object
...

additinal arguments to pass to print

Value

print object to screen

S3 method print pmxConfig object

Description

S3 method print pmxConfig object

Usage

## S3 method for class 'pmxConfig'
print(x, ...)

Arguments

x

pmxConfig object
...

addtional arguments to pass to print (unused currently)

Value

invisible object

Reads .ext files generated by NONMEM

Description

Reads .ext files generated by NONMEM

Usage

read_extfile(
  run = NA_real_,
  project = getwd(),
  file = paste0(run, ".ext"),
  path = NULL,
  read_fun = c("data.table", "read.table"),
  quiet
)

Arguments

run

run a run number or run identifier
project

project the NONMEM project directory
file

file the 'ext' file name
path

path full path and file name for 'ext' file
read_fun

read_fun function to read the 'ext' file
quiet

Logical, if FALSE messages are printed to the console.

Value

A list with param, omega, and sigma in a format ready to be used.

Author(s)

This function is based on read_nmext from mrgsolve, Original Author: Kyle T Baron. This function has some changes to the original code: Addition of param, "quiet", (option of pmx_msg function, from xpose package) (Line: 27) The code was slightly adjusted to check for multiple tables and also extract SE (ITERATION == 1000000001) (Line: 44-58, Line: 86-96, respectively) The output was also slightly adjusted to fit ggPMX output (df and df2) (Line: 105,106) as_bmat was replaced by bmat_like to create the diagonal matrix (Line 116:142)

Examples

#project <- system.file("nonmem", package = "mrgsolve")
#est <- read_nmext(1005, project = project)

Read Modelling input data

Description

Read Modelling input data

Usage

read_input(
  ipath,
  dv,
  dvid,
  cats = "",
  conts = "",
  strats = "",
  occ = "",
  endpoint = NULL,
  id = NULL,
  time = NULL
)

Arguments

ipath

full path of the input file
dv

character the name of measurable variable used in the input modelling file
dvid

character observation type parameter
cats

[Optional]character vector of categorical covariates
conts

[Optional]character vector of continuous covariates
strats

[Optional]character extra stratification variables
occ

[Optional]character inter individual occasion variables
endpoint

integer null in case of a single endpoint otherwise the index of endpoints.
id

character the name of identifier variable used in the input modelling file.
time

character the name of time variable used in the input modelling file

Value

data.table well formatted containing modelling input data

Read MONOLIX individual parameters

Description

Read MONOLIX individual parameters

Usage

read_mlx_ind_est(path, x, ...)

Arguments

path

character path to the file
x

dataset object
...

extra parameter not used

Value

data.table object

Read MONOLIX parameter estimation file

Description

Read MONOLIX parameter estimation file

Usage

read_mlx_par_est(path, x, ...)

Arguments

path

character path to the file
x

dataset object
...

extra parameter not used

Value

data.table object

Read MONOLIX model predictions

Description

Read MONOLIX model predictions

Usage

read_mlx_pred(path, x, ...)

Arguments

path

character path to the file
x

dataset object
...

extra parameter not used

Value

data.table object

This function create a residual for each observed value and also generates a residual distribution

Description

This function create a residual for each observed value and also generates a residual distribution

Usage

residual(
  x,
  y,
  labels = NULL,
  point = NULL,
  is.hline = FALSE,
  hline = NULL,
  dname = NULL,
  facets = NULL,
  bloq = NULL,
  square_plot = TRUE,
  ...
)

Arguments

x

x axis aesthetics
y

y axis aesthetics
labels

list that contain title,subtitle, axis labels
point

geom point graphical parameters
is.hline

logical if TRUE add horizontal line y=0 ( TRUE by default)
hline

geom hline graphical parameters
dname

name of dataset to be used
facets

list wrap facetting in case of strat.facet
bloq

pmxBLOQ object created by pmx_bloq
square_plot

square dv_pred plot (TRUE by default)
...

others graphics arguments passed to pmx_gpar internal object.

Details

Some parameters are a list of parameters :

point is a list that contains:

  • shape: default to 1

  • color: default to black

  • size: default to 1

labels is a list that contains:

  • title: plot title default to AES_X versus AES_Y

  • subtitle: plot subtitle default empty

  • x: x axis label default to AES_X

  • y: y axis label default to AES_Y

Value

a residual object

See Also

plot_pmx.residual

Scatter residual plots

Description

Scatter residual plots

DV vs PRED plot

DV vs IPRED plot

IWRES vs IPRED plot

|IWRES| vs IPRED plot

|IWRES| vs TIME plot

IWRES vs TIME plot

NPDE vs TIME plot

NPDE vs PRED plot

NPD vs TIME plot

NPD vs EPRED plot

NPD vs PRED plot

CWRES vs TIME plot

CWRES vs CPRED plot

CWRES vs PRED plot

Usage

residual_scatter(
  sim_blq,
  point,
  is.hline,
  hline,
  dname,
  bloq,
  filter,
  strat.facet,
  facets,
  strat.color,
  trans,
  pmxgpar,
  labels,
  axis.title,
  axis.text,
  ranges,
  is.smooth,
  smooth,
  is.band,
  band,
  is.draft,
  draft,
  is.identity_line,
  identity_line,
  scale_x_log10,
  scale_y_log10,
  color.scales,
  ...
)

pmx_plot_dv_pred(ctr, ...)

pmx_plot_dv_ipred(ctr, ...)

pmx_plot_iwres_ipred(ctr, ...)

pmx_plot_abs_iwres_ipred(ctr, ...)

pmx_plot_abs_iwres_time(ctr, ...)

pmx_plot_iwres_time(ctr, ...)

pmx_plot_npde_time(ctr, ...)

pmx_plot_npde_pred(ctr, ...)

pmx_plot_npd_time(ctr, ...)

pmx_plot_npd_epred(ctr, ...)

pmx_plot_npd_pred(ctr, ...)

pmx_plot_cwres_time(ctr, ...)

pmx_plot_cwres_cpred(ctr, ...)

pmx_plot_cwres_pred(ctr, ...)

Arguments

sim_blq

logical if TRUE uses sim_blq values for plotting. Only for Monolix 2018 and later.
point

list geom_point graphical parameters.
is.hline

logical if TRUE add horizontal line y=0 ( TRUE by default).
hline

list geom_hline graphical parameters.
dname

character name of dataset to be used. User can create his own dataset using set_data and pass it as dname to be plotted.
bloq

pmxBLOQ object created by pmx_bloq.

pmx_update parameters
filter

expression filter which will be applied to plotting data.
strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)
facets

list facet_wrap parameters.
strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.
trans

character define the transformation to apply on x or y or both variables
pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters
labels

list list containing plot and/or axis labels: title, subtitle, x , y
axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)
axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)
ranges

list limits of x/y ranges
is.smooth

logical if set to TRUE add smooth layer
smooth

list geom_smooth graphical/smoothing fun parameters
is.band

logical if TRUE add horizontal band
band

list horizontal band parameters. geom_hline graphical parameters.
is.draft

logical if TRUE add draft layer
draft

list draft layer parameters. geom_text graphical parameters.
is.identity_line

logical if TRUE add an identity line
identity_line

listgeom_abline graphical parameters.
scale_x_log10

logical if TRUE use log10 scale for x axis.
scale_y_log10

logical if TRUE use log10 scale for y axis.
color.scales

list define scales parameter in case of strat.color pmx_settings
...

others graphics parameters passed :

  • pmx_gpar internal function to customize shared graphical parameters

  • residual generic object for all residual (scatter) plots .

  • pmx_update function.

  • aess can be used to change time variable within the plot (e.g. aess = list(x="TADQBW"))

residual parameters
ctr

pmx controller

Value

ggplot2 object

Examples

# NOTES ######################
# examples are availables for all residual plots:
# - pmx_plot_abs_iwres_ipred
# - pmx_plot_dv_ipred
# - pmx_plot_dv_pred
# - pmx_plot_iwres_ipred
# - pmx_plot_iwres_time
# - pmx_plot_npde_time


# basic use  ---------------------------------------

ctr <- theophylline()
p <- ctr %>% pmx_plot_dv_pred()
## p is a ggplot2 object you can add any layer here
p + ggplot2::theme_minimal()

# update graphical parameter  ----------------------

## update labels
ctr %>% pmx_plot_dv_pred(
  labels = list(title = "DV versus PRED new title")
)

## remove draft
ctr %>% pmx_plot_dv_pred(is.draft = FALSE)

## remove horizontal line
ctr %>% pmx_plot_dv_pred(is.hline = FALSE)

## custom point aes and static parameters
## we can customize any geom_point parameter
ctr %>% pmx_plot_dv_pred(
  point = list(aes(alpha = DV), color = "green", shape = 4)
)



# stratification  ----------------------------------

## continuous stratification
ctr %>% pmx_plot_dv_pred(strat.color = ~WT0)
## categorical stratification
ctr %>% pmx_plot_dv_pred(strat.facet = ~SEX)
## using formula notation
ctr %>% pmx_plot_dv_pred(strat.facet = STUD~SEX)

# subsetting  --------------------------------------

## we can use any expression involving the data
ctr %>% pmx_plot_dv_pred(filter = DV > mean(DV) & PRED < median(PRED))
## filter and stratify
ctr %>% pmx_plot_dv_pred(filter = SEX == 1, strat.facet = ~SEX)


# transformation  --------------------------------------

## apply a log transformation in y
ctr %>% pmx_plot_dv_pred(trans = "log10_y")

update or add a new abbreviation

Description

update or add a new abbreviation

Usage

set_abbrev(ctr, ...)

Arguments

ctr

pmxClass controller object
...

Options to set or add, with the form name = value.

Examples

ctr <- theophylline()
ctr %>% set_abbrev("new_param" = "new value")
ctr %>% get_abbrev("new_param")

Set a controller data set

Description

Set a controller data set

Usage

set_data(ctr, ..., envir = parent.frame())

Arguments

ctr

the controller object
...

a named list parameters (see example)
envir

the environment in which expr is to be evaluated. May also be NULL, a list, a data frame, a pairlist or an integer as specified to sys.call.

Details

This function can be used to set an existing data set or to create a new one. The basic idea is to change the built-in data set (change the factor level names, change some rows values or apply any other data set operation) and use the new data set using the dname parameter of pmx_plot family functions.

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_plot()

Examples

ctr <- theophylline()
dx <- ctr %>% get_data("eta")
dx <- dx[, EFFECT := factor(
  EFFECT,
  levels = c("ka", "V", "Cl"),
  labels = c("Concentration", "Volume", "Clearance")
)]
## update existing data set
ctr %>% set_data(eta = dx)
## or create a new data set
ctr %>% set_data(eta_long = dx)

Create a new plot of the desired type

Description

Create a new plot of the desired type

Usage

set_plot(
  ctr,
  ptype = c("IND", "DIS", "SCATTER", "ETA_PAIRS", "ETA_COV", "PMX_QQ", "VPC", "PMX_DENS"),
  pname,
  use.defaults = TRUE,
  filter = NULL,
  strat.color = NULL,
  strat.facet = NULL,
  color.scales = NULL,
  trans = NULL,
  ...
)

Arguments

ctr

pmxClass controller object
ptype

plot type can be:

pname

plot name, if missing it will be created using function aestetics
use.defaults

logical if FALSE do not use defaults defined in yaml init files
filter

optional filter which will be applied to plotting data
strat.color

character
strat.facet

formula define categorical stratification as formula
color.scales

list can be used with strat.color to set scale_color_manual
trans

list transformation operator
...

other plot parameters to configure pmx_gpar.

Value

invisible ctr object

See Also

Other pmxclass: get_cats(), get_conts(), get_covariates(), get_data(), get_occ(), get_plot_config(), get_plot(), get_strats(), plot_names(), plots(), pmx_update(), set_data()

Creates pmx controller using theophylline data

Description

Creates pmx controller using theophylline data

Usage

theophylline(settings = NULL, ...)

Arguments

settings

pmxSettings object
...

other parameters of pmx_mlx like endpoint

Value

pmx controller

Examples

## Not run: 
theophylline()

## End(Not run)

merge facets formula with new formula

Description

merge facets formula with new formula

Usage

wrap_formula(x, origin = "lfacet")

Arguments

x

formula object
origin

the origin formula default to ~lfacets

Value

formula object