chartcatalog

The chartcatalog package contains tools to

  • Lookup available charts in JAMES;
  • Create and parse chart codes;
  • Find outcomes, chart group and growth reference;
  • Obtain viewport number and transformation functions;
  • Lookup break points from the brokenstick model.

Installation

You can install the development version chartcatalog by

install.packages("remotes")
remotes::install_github("growthcharts/chartcatalog")

There is no release on CRAN.

Example 1: Available charts in JAMES

The current catalogs holds 440 Dutch charts.

library(chartcatalog)
head(ynames_lookup)
#>   chartgrp chartcode yname vpn vp                         reference
#> 1   nl2010      DJAA   hdc   3  A clopus::nl2009[["nl2009.mhdcDS"]]
#> 2   nl2010      DJAA   hgt   4  B clopus::nl2009[["nl2009.mhgtDS"]]
#> 3   nl2010      DJAA   wgt   5  C   clopus::nl1980[["nl1980.mwgt"]]
#> 4   nl2010      DJAH   hgt   1  A clopus::nl2009[["nl2009.mhgtDS"]]
#> 5   nl2010      DJAO   hdc   1  A clopus::nl2009[["nl2009.mhdcDS"]]
#> 6   nl2010      DJAW   wgt   1  A   clopus::nl1980[["nl1980.mwgt"]]
#>                   tx             inv_tx            ty        inv_ty seq
#> 1 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#> 2 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#> 3 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#> 4 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#> 5 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#> 6 function(x) x * 12 function(x) x / 12 function(y) y function(y) y  tr
#>               refcode
#> 1 nl_2009_hdc_male_ds
#> 2 nl_2009_hgt_male_ds
#> 3   nl_1980_wgt_male_
#> 4 nl_2009_hgt_male_ds
#> 5 nl_2009_hdc_male_ds
#> 6   nl_1980_wgt_male_
length(unique(ynames_lookup$chartcode))
#> [1] 440

The charts are subdivided into three groups:

unique(ynames_lookup$chartgrp)
#> [1] "nl2010"  "preterm" "who"

There are five outcomes, but not every outcome (yname) appears in all chart groups:

with(ynames_lookup, table(chartgrp, yname))
#>          yname
#> chartgrp  bmi dsc hdc hgt wfh wgt
#>   nl2010   20   4  56  64  40  24
#>   preterm   0  48  48  96   0  96
#>   who       0  52   4   8   4   4

Example 2: Chartcode creating and parsing

A chartcode identifies the type of growth chart. The code is a combination of 4–7 alphanumeric characters. The create_chartcode() and parse_chartcode() functions can be used to obtain information from the codes. For example,

parse_chartcode(c("HJAA"))
#> $population
#> [1] "HS"
#> 
#> $sex
#> [1] "male"
#> 
#> $design
#> [1] "A"
#> 
#> $side
#> [1] "front"
#> 
#> $language
#> [1] "dutch"
#> 
#> $week
#> [1] ""

shows that chart with code "HJAA" identifies the front of the chart for Hindustan boys living in the Netherlands, design A (A4 size, 0-15 months).

Example 3: Find outcomes, chart group and growth reference

If we have a chart code, we may find its chart group and outcomes as

get_chartgrp("PJEAN26")
#>   PJEAN26 
#> "preterm"
get_ynames("PJEAN26")
#> PJEAN26 PJEAN26 
#>   "hgt"   "wgt"

We obtain the call to the clopus package to the post-natal growth reference of weight of preterms born at a gestational age of 26 week by

call <- get_reference_call("PJEAN26", yname = "wgt")
call
#> [1] "clopus::preterm[[\"pt2012a.mwgt26\"]]"

This call can be stored as a shortcut to the reference. Use eval(parse(text = call)) to execute the call. Alternatively, if you have clopus installed, we may obtain the reference directly by

tb <- get_reference("PJEAN26", yname = "wgt")
slotNames(tb)
#> [1] "table" "info"
head(data.frame(tb@table@table))
#>        x    L     M     S
#> 1 0.0000 1.09 0.985 0.206
#> 2 0.0027 1.08 0.971 0.206
#> 3 0.0055 1.08 0.960 0.207
#> 4 0.0082 1.07 0.950 0.207
#> 5 0.0110 1.07 0.943 0.208
#> 6 0.0137 1.06 0.937 0.208

More details can be found in the info slot:

tb@info
#> An object of class "referenceInfo"
#> Slot "n":
#> [1] 4
#> 
#> Slot "i":
#> [1] 2
#> 
#> Slot "j":
#> [1] 2
#> 
#> Slot "code":
#> [1] "mpt2012a"
#> 
#> Slot "country":
#> [1] "NL"
#> 
#> Slot "year":
#> [1] 2012
#> 
#> Slot "sex":
#> [1] "male"
#> 
#> Slot "sub":
#> character(0)
#> 
#> Slot "yname":
#> [1] "wgt"
#> 
#> Slot "dist":
#> [1] "LMS"
#> 
#> Slot "mnx":
#> [1] 0
#> 
#> Slot "mxx":
#> [1] 4
#> 
#> Slot "source":
#> [1] "Bocca-Tjeertes 2012"
#> 
#> Slot "public":
#> character(0)
#> 
#> Slot "remark":
#> [1] "Bemerkung =\t\t\t\t\t\t\t\t\t\t\t\t\t"
#> 
#> Slot "date":
#> [1] "2021-01-27 16:33:21 CET"

Added support for nlreferences package 

library(centile)
library(nlreferences)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
refcode <- get_refcode("PJEAN26", "wgt")
ref <- load_reference(refcode, pkg = "nlreferences", verbose = TRUE)
head(ref)
#> # A tibble: 6 × 4
#>        x     L     M     S
#>    <dbl> <dbl> <dbl> <dbl>
#> 1 0       1.09 0.985 0.206
#> 2 0.0027  1.08 0.971 0.206
#> 3 0.0055  1.08 0.96  0.207
#> 4 0.0082  1.07 0.95  0.207
#> 5 0.011   1.07 0.943 0.208
#> 6 0.0137  1.06 0.937 0.208