The goal of jamesclient is to facilitate interaction for R users
with the Joint Automatic Measurement and Evaluation System (JAMES).
JAMES is an online resource for creating growth charts and analysing
growth curves.
You can install the development version from GitHub with:
install.packages("remotes")
remotes::install_github("growthcharts/jamesclient")The primary functions are:
| Function | Description |
|---|---|
james_post |
Send POST request to JAMES |
james_get |
Send GET request to JAMES |
inspect_demodata() |
Upload demo child data and download parsed file |
Upload BDS data
library(jamesclient)
fn <- system.file("extdata", "allegrosultum", "client3.json",
package = "jamesdemodata", mustWork = TRUE)
host <- "https://james.groeidiagrammen.nl"
r1 <- james_post(host = host, path = "data/upload/json", txt = fn)
r1$parsed
#> $psn
#> id name dob dobf dobm src
#> 1 -1 fa308134-069e-49ce-9847-ccdae380ed6f 2018-10-11 1995-07-04 1990-12-02 1234
#> sex gad ga smo bw hgtm hgtf agem etn
#> 1 female 189 27 1 990 167 190 27 NL
#>
#> $xyz
#> age xname yname zname zref x y z
#> 1 0.0849 age hgt hgt_z nl_2012_hgt_female_27 0.0849 38.00 -0.158
#> 2 0.1670 age hgt hgt_z nl_2012_hgt_female_27 0.1670 43.50 0.047
#> 3 0.0849 age wgt wgt_z nl_2012_wgt_female_27 0.0849 1.25 -0.203
#> 4 0.1670 age wgt wgt_z nl_2012_wgt_female_27 0.1670 2.10 0.015
#> 5 0.0849 age hdc hdc_z nl_2012_hdc_female_27 0.0849 27.00 -0.709
#> 6 0.1670 age hdc hdc_z nl_2012_hdc_female_27 0.1670 30.50 -0.913
#> 7 0.0849 age bmi bmi_z nl_1997_bmi_female_nl 0.0849 8.66 -5.719
#> 8 0.1670 age bmi bmi_z nl_1997_bmi_female_nl 0.1670 11.10 -3.767
#> 9 0.0849 hgt wfh wfh_z nl_2012_wfh_female_ 38.0000 1.25 -0.001
#> 10 0.1670 hgt wfh wfh_z nl_2012_wfh_female_ 43.5000 2.10 0.326
#> 11 0.0000 age wgt wgt_z nl_2012_wgt_female_27 0.0000 0.99 0.190Get output from R console (just for checking)
r2 <- james_get(host = host, path = paste(r1$session, "console", sep = "/"))
cat(r2$parsed, "\n")
#> > upload_data(txt = c("{\"Referentie\":\"fa308134-069e-49ce-9847-ccdae380ed6f\",\"OrganisatieCode\":1234,\"ClientGegevens\":{\"Elementen\":[{\"Bdsnummer\":19,\"Waarde\":\"2\"},{\"Bdsnummer\":20,\"Waarde\":\"20181011\"},{\"Bdsnummer\":82,\"Waarde\":\"189\"},{\"Bdsnummer\":91,\"Waarde\":\"1\"},{\"Bdsnummer\":110,\"Waarde\":\"990\"},{\"Bdsnummer\":238,\"Waarde\":\"1670\"},{\"Bdsnummer\":240,\"Waarde\":\"1900\"}],\"Groepen\":[{\"Elementen\":[{\"Bdsnummer\":63,\"Waarde\":\"19950704\"},{\"Bdsnummer\":71,\"Waarde\":\"6030\"},{\"Bdsnummer\":62,\"Waarde\":\"01\"}]},{\"Elementen\":[{\"Bdsnummer\":63,\"Waarde\":\"19901202\"},{\"Bdsnummer\":71,\"Waarde\":\"6030\"},{\"Bdsnummer\":62,\"Waarde\":\"02\"}]}]},\"Contactmomenten\":[{\"Tijdstip\":\"20181111\",\"Elementen\":[{\"Bdsnummer\":235,\"Waarde\":\"380\"},{\"Bdsnummer\":245,\"Waarde\":\"1250\"},{\"Bdsnummer\":252,\"Waarde\":\"270\"}]},{\"Tijdstip\":\"20181211\",\"Elementen\":[{\"Bdsnummer\":235,\"Waarde\":\"435\"},{\"Bdsnummer\":245,\"Waarde\":\"2100\"},{\"Bdsnummer\":252,\"Waarde\":\"305\"}]}]}"))
#> List of length 2
#> [psn]
#> [xyz]For other end points, see https://james.groeidiagrammen.nl.
library(jamesclient)
data <- inspect_demodata(name = "Anne_S", "smocc", format = "1.0")
data
#> $psn
#> id name dob dobf dobm src dnr sex gad ga smo bw hgtm
#> 1 -1 Anne S 1989-01-31 <NA> 1961-08-01 0 <NA> female 283 40 0 3300 172
#> hgtf agem etn
#> 1 183 27 NL
#>
#> $xyz
#> age xname yname zname zref x y z
#> 1 0.0000 age hgt hgt_z nl_1997_hgt_female_nl 0.0000 51.00 0.052
#> 2 0.0986 age hgt hgt_z nl_1997_hgt_female_nl 0.0986 54.70 0.145
#> 3 0.1369 age hgt hgt_z nl_1997_hgt_female_nl 0.1369 56.00 0.114
#> 4 0.2327 age hgt hgt_z nl_1997_hgt_female_nl 0.2327 59.50 0.206
#> 5 0.5010 age hgt hgt_z nl_1997_hgt_female_nl 0.5010 68.00 0.661
#> 6 0.7885 age hgt hgt_z nl_1997_hgt_female_nl 0.7885 73.00 0.498
#> 7 0.9610 age hgt hgt_z nl_1997_hgt_female_nl 0.9610 75.50 0.375
#> 8 1.2485 age hgt hgt_z nl_1997_hgt_female_nl 1.2485 80.00 0.434
#> 9 1.5140 age hgt hgt_z nl_1997_hgt_female_nl 1.5140 83.50 0.449
#> 10 1.9740 age hgt hgt_z nl_1997_hgt_female_nl 1.9740 89.50 0.731
#> 11 0.0000 age wgt wgt_z nl_1997_wgt_female_nl 0.0000 3.30 -0.105
#> 12 0.0986 age wgt wgt_z nl_1997_wgt_female_nl 0.0986 4.10 -0.280
#> 13 0.1369 age wgt wgt_z nl_1997_wgt_female_nl 0.1369 4.52 -0.123
#> 14 0.2327 age wgt wgt_z nl_1997_wgt_female_nl 0.2327 5.64 0.350
#> 15 0.5010 age wgt wgt_z nl_1997_wgt_female_nl 0.5010 7.95 0.723
#> 16 0.7885 age wgt wgt_z nl_1997_wgt_female_nl 0.7885 9.46 0.714
#> 17 0.9610 age wgt wgt_z nl_1997_wgt_female_nl 0.9610 10.01 0.552
#> 18 1.2485 age wgt wgt_z nl_1997_wgt_female_nl 1.2485 11.35 0.827
#> 19 1.5140 age wgt wgt_z nl_1997_wgt_female_nl 1.5140 12.01 0.711
#> 20 1.9740 age wgt wgt_z nl_1997_wgt_female_nl 1.9740 13.34 0.747
#> 21 0.0986 age hdc hdc_z nl_1997_hdc_female_nl 0.0986 37.60 0.461
#> 22 0.1369 age hdc hdc_z nl_1997_hdc_female_nl 0.1369 38.30 0.398
#> 23 0.2327 age hdc hdc_z nl_1997_hdc_female_nl 0.2327 40.40 0.655
#> 24 0.5010 age hdc hdc_z nl_1997_hdc_female_nl 0.5010 44.40 1.134
#> 25 0.7885 age hdc hdc_z nl_1997_hdc_female_nl 0.7885 46.00 0.829
#> 26 0.9610 age hdc hdc_z nl_1997_hdc_female_nl 0.9610 47.00 0.929
#> 27 1.2485 age hdc hdc_z nl_1997_hdc_female_nl 1.2485 48.00 0.896
#> 28 1.5140 age hdc hdc_z nl_1997_hdc_female_nl 1.5140 48.50 0.801
#> 29 1.9740 age hdc hdc_z nl_1997_hdc_female_nl 1.9740 50.10 1.354
#> 30 0.0000 age bmi bmi_z nl_1997_bmi_female_nl 0.0000 12.69 0.160
#> 31 0.0986 age bmi bmi_z nl_1997_bmi_female_nl 0.0986 13.70 -0.476
#> 32 0.1369 age bmi bmi_z nl_1997_bmi_female_nl 0.1369 14.41 -0.295
#> 33 0.2327 age bmi bmi_z nl_1997_bmi_female_nl 0.2327 15.93 0.214
#> 34 0.5010 age bmi bmi_z nl_1997_bmi_female_nl 0.5010 17.19 0.352
#> 35 0.7885 age bmi bmi_z nl_1997_bmi_female_nl 0.7885 17.75 0.590
#> 36 0.9610 age bmi bmi_z nl_1997_bmi_female_nl 0.9610 17.56 0.514
#> 37 1.2485 age bmi bmi_z nl_1997_bmi_female_nl 1.2485 17.73 0.824
#> 38 1.5140 age bmi bmi_z nl_1997_bmi_female_nl 1.5140 17.23 0.641
#> 39 1.9740 age bmi bmi_z nl_1997_bmi_female_nl 1.9740 16.65 0.436
#> 40 0.0986 age dsc dsc_z nl_2014_dsc_female_40 0.0986 14.69 0.190
#> 41 0.1369 age dsc dsc_z nl_2014_dsc_female_40 0.1369 16.72 -0.094
#> 42 0.2327 age dsc dsc_z nl_2014_dsc_female_40 0.2327 20.82 -0.743
#> 43 0.5010 age dsc dsc_z nl_2014_dsc_female_40 0.5010 35.30 -0.002
#> 44 0.7885 age dsc dsc_z nl_2014_dsc_female_40 0.7885 41.52 -0.806
#> 45 0.9610 age dsc dsc_z nl_2014_dsc_female_40 0.9610 47.59 -0.157
#> 46 1.2485 age dsc dsc_z nl_2014_dsc_female_40 1.2485 56.21 0.844
#> 47 1.5140 age dsc dsc_z nl_2014_dsc_female_40 1.5140 59.75 0.654
#> 48 1.9740 age dsc dsc_z nl_2014_dsc_female_40 1.9740 64.21 0.248
#> 49 0.0000 hgt wfh wfh_z nl_1997_wfh_female_nla 51.0000 3.30 -0.858
#> 50 0.0986 hgt wfh wfh_z nl_1997_wfh_female_nla 54.7000 4.10 -0.780
#> 51 0.1369 hgt wfh wfh_z nl_1997_wfh_female_nla 56.0000 4.52 -0.419
#> 52 0.2327 hgt wfh wfh_z nl_1997_wfh_female_nla 59.5000 5.64 0.215
#> 53 0.5010 hgt wfh wfh_z nl_1997_wfh_female_nla 68.0000 7.95 0.326
#> 54 0.7885 hgt wfh wfh_z nl_1997_wfh_female_nla 73.0000 9.46 0.655
#> 55 0.9610 hgt wfh wfh_z nl_1997_wfh_female_nla 75.5000 10.01 0.584
#> 56 1.2485 hgt wfh wfh_z nl_1997_wfh_female_nla 80.0000 11.35 0.851
#> 57 1.5140 hgt wfh wfh_z nl_1997_wfh_female_nla 83.5000 12.01 0.644
#> 58 1.9740 hgt wfh wfh_z nl_1997_wfh_female_nla 89.5000 13.34 0.464Everything can be done with james_post() and james_get(). The
functions below are not needed anymore, and will be deprecated in the
future.
Upload BDS data and create a tibble on the server:
library(jamesclient)
fn <- file.path(path.package("jamesclient"), "testdata", "client3.json")
r1 <- upload_txt(fn)
browseURL(get_url(r1, "return"))Make a combined upload and automatic chartcode choice:
r2 <- request_chart(fn, chartcode = "PJAHN27")
browseURL(get_url(r2, "svg"))| Function | Description | Alternative |
|---|---|---|
request_site() |
Create personalised site | james_post() |
upload_bds() |
Upload and parse data | james_post() |