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Mar 31, 2025
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test bayesian spatiotemporal model #6

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8b03f29
test bayesian spatiotemporal model
Mar 31, 2025
756be59
solve linting problem
Mar 31, 2025
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1 change: 1 addition & 0 deletions tests/testdata/area_rect.cpg
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PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0]]
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PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0]]
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97 changes: 97 additions & 0 deletions tests/testthat/test-bayesian_spatiotemporal_model.R
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test_that("inference function works as expected", {
data <- "../testdata/cws_fake.csv" |>
testthat::test_path() |>
read.csv()
pred <- "../testdata/pred_fake.csv" |>
testthat::test_path() |>
read.csv()
data$time <- as.POSIXct(data$time, tz = "UTC", format = "%Y-%m-%d %H:%M:%S")
pred$time <- as.POSIXct(pred$time, tz = "UTC", format = "%Y-%m-%d %H:%M:%S")
polygon <- "../testdata/area_rect.shp" |>
testthat::test_path() |>
terra::vect()
# Run inference
result <- inference(
data = data,
pred = pred,
polygon = polygon,
ts = lubridate::ymd_hms("1000-07-28 00:00:00"),
te = lubridate::ymd_hms("1000-07-28 02:00:00"),
verbose = TRUE,
debug = FALSE
)
# Assertions
expect_type(result, "list")
expect_named(result, c("pred", "mod", "info"))
expect_s3_class(result$pred, "data.frame")
expect_true(
all(
c(
"pred_mean",
"pred_ll",
"pred_ul",
"pred_sd"
) %in% colnames(result$pred)
)
)
expect_s3_class(result$mod, "inla")
expect_s3_class(result$info, "data.frame")
expect_true(
all(
c(
"mesh_max_edge",
"mesh_cutoff",
"pcrange_thresh",
"pcrange_proba",
"pcsigma_thresh",
"pcsigma_proba",
"pccor1_thresh",
"pccor1_proba",
"s2n_data_prior",
"s2x_data_prior",
"prior_a2",
"prior_b2",
"int_mean",
"era5_t2m_mean",
"era5_rh_mean",
"era5_tp_mean",
"era5_u10_mean",
"era5_v10_mean",
"era5_tcc_mean",
"local_hour19:elev_mean",
"local_hour20:elev_mean",
"local_hour21:elev_mean",
"local_hour19:fch_mean",
"local_hour20:fch_mean",
"local_hour21:fch_mean",
"local_hour19:imp_mean",
"local_hour20:imp_mean",
"local_hour21:imp_mean",
"int_sd",
"era5_t2m_sd",
"era5_rh_sd",
"era5_tp_sd",
"era5_u10_sd",
"era5_v10_sd",
"era5_tcc_sd",
"local_hour19:elev_sd",
"local_hour20:elev_sd",
"local_hour21:elev_sd",
"local_hour19:fch_sd",
"local_hour20:fch_sd",
"local_hour21:fch_sd",
"local_hour19:imp_sd",
"local_hour20:imp_sd",
"local_hour21:imp_sd",
"prec_gaussian_obs_mean",
"range_gaussian_obs_mean",
"stdev_s_mean",
"grouprho_s_mean",
"prec_gaussian_obs_sd",
"range_gaussian_obs_sd",
"stdev_s_sd",
"grouprho_s_sd"
) %in% colnames(result$info)
)
)
})