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Improve population error #453

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Improve population error #453

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084ae69
Update population warning on model fitting
rtesra Nov 19, 2024
d04059c
Merge branch 'master' into improve-warnings
rtesra Nov 19, 2024
c1ce23a
Merge branch 'master' into improve-warnings
r-ash Nov 19, 2024
879bbaa
Update error message to make it more understandable
r-ash Nov 20, 2024
cd1b566
Translate the error messages
r-ash Nov 21, 2024
d11c86e
make error more infromative
rtesra Nov 29, 2024
b17b74d
Merge branch 'master' into improve-warnings
rtesra Nov 29, 2024
82fbc90
fix failing test
rtesra Nov 29, 2024
e1df8fd
Merge branch 'improve-warnings' of https://github.com/mrc-ide/naomi i…
rtesra Nov 29, 2024
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
Package: naomi
Title: Naomi Model for Subnational HIV Estimates
Version: 2.10.1
Version: 2.10.2
Authors@R:
person(given = "Jeff",
family = "Eaton",
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4 changes: 4 additions & 0 deletions NEWS.md
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@@ -1,3 +1,7 @@
# naomi 2.10.2

* Improve warning generated when user fits model at admin level where no population data exists.
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# naomi 2.10.1

* Patch error in reading `anc_already_art` from Spectrum PJNZ file (was errantly
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6 changes: 6 additions & 0 deletions R/model.R
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Expand Up @@ -329,6 +329,12 @@ naomi_model_frame <- function(area_merged,
## of a Spectrum file and then calibrated. Currently no way to know if areas
## comparise only part of a Spectrum file, so can't address.

if(any( mf_areas[["area_id"]] %in% unique(population_agesex$area_id) == FALSE)){
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stop(
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"Population data not available for admin level selected for model projections.
Please review model options selection to ensure that area level selection is correct.")
}

pop_subset <- dplyr::filter(population_agesex, area_id %in% mf_areas[["area_id"]])
pop_t1 <- interpolate_population_agesex(pop_subset, calendar_quarter1)
pop_t2 <- interpolate_population_agesex(pop_subset, calendar_quarter2)
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29 changes: 24 additions & 5 deletions tests/testthat/test-04-model-frame.R
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Expand Up @@ -53,7 +53,26 @@ test_that("artnum_mf() works with single quarter ART data", {
})


test_that("Informative error displayed when model run to admin level higher/lower than population data supplied", {

x <- expect_error(
naomi_model_frame(a_area_merged,
demo_population_agesex,
a_spec,
scope = "MWI",
level = 3,
calendar_quarter1 = "CY2016Q1",
calendar_quarter2 = "CY2018Q4",
calendar_quarter3 = "CY2019Q2",
calendar_quarter4 = "CY2022Q3",
calendar_quarter5 = "CY2023Q3"))


expect_equal(x$message,
"Population data not available for admin level selected for model projections.\n Please review model options selection to ensure that area level selection is correct."
)

})
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Could the error message here quote the area level and area level label selected?

"Population data not available for selected area level 3 (District). Pleas review model options"

Also I'm think I would remove the "for model projections". We usually use "projections" to refer to the T3/T4/T5 projection, but here this area level selection pertains to everything.


test_that("population calibration options", {

Expand Down Expand Up @@ -85,7 +104,7 @@ test_that("population calibration options", {
mf_none$mf_model$population_t2 +
mf_none$mf_model$population_t3 +
mf_none$mf_model$population_t4 +
mf_none$mf_model$population_t5
mf_none$mf_model$population_t5
),
sum(mf_none$spectrum_calibration$population_raw))

Expand All @@ -102,7 +121,7 @@ test_that("population calibration options", {
calendar_quarter2 = "CY2018Q4",
calendar_quarter3 = "CY2019Q2",
calendar_quarter4 = "CY2022Q3",
calendar_quarter5 = "CY2023Q3",
calendar_quarter5 = "CY2023Q3",
spectrum_population_calibration = "national")

expect_false(sum(mf_nat$spectrum_calibration$population_raw) ==
Expand Down Expand Up @@ -132,7 +151,7 @@ test_that("population calibration options", {
calendar_quarter2 = "CY2018Q4",
calendar_quarter3 = "CY2019Q2",
calendar_quarter4 = "CY2022Q3",
calendar_quarter5 = "CY2023Q3",
calendar_quarter5 = "CY2023Q3",
spectrum_population_calibration = "subnational")

expect_false(sum(mf_subnat$spectrum_calibration$population_raw) ==
Expand Down Expand Up @@ -162,7 +181,7 @@ test_that("population calibration options", {
calendar_quarter2 = "CY2018Q4",
calendar_quarter3 = "CY2019Q2",
calendar_quarter4 = "CY2022Q3",
calendar_quarter5 = "CY2023Q3",
calendar_quarter5 = "CY2023Q3",
spectrum_population_calibration = "jibberish"),
"spectrum_calibration_option \"jibberish\" not found."
)
Expand Down Expand Up @@ -319,7 +338,7 @@ test_that("naomi_model_frame() interpolated population depends on quarter specif
calendar_quarter2 = "CY2018Q4",
calendar_quarter3 = "CY2019Q2",
calendar_quarter4 = "CY2022Q3",
calendar_quarter5 = "CY2023Q3",
calendar_quarter5 = "CY2023Q3",
spectrum_population_calibration = "subnational")


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