## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----run-app, eval = FALSE---------------------------------------------------- # library(soilKey) # run_classify_app() # abre um app Shiny em uma única tela no navegador ## ----quick-start-------------------------------------------------------------- library(soilKey) pedon <- make_ferralsol_canonical() # Latossolo Vermelho canônico classify_wrb2022(pedon, on_missing = "silent")$name classify_sibcs(pedon)$name classify_usda(pedon, on_missing = "silent")$name ## ----build-pedon-------------------------------------------------------------- meu_pedon <- PedonRecord$new( site = list( id = "exemplo-001", lat = -22.5, lon = -43.7, country = "BR", parent_material = "gnaisse" ), horizons = data.frame( top_cm = c(0, 15, 65, 130), bottom_cm = c(15, 65, 130, 200), designation = c("A", "AB", "Bw1", "Bw2"), munsell_hue_moist = rep("2.5YR", 4), munsell_value_moist = c(3, 3, 4, 4), munsell_chroma_moist = c(4, 6, 6, 6), clay_pct = c(50, 55, 60, 60), silt_pct = c(15, 10, 8, 8), sand_pct = c(35, 35, 32, 32), cec_cmol = c(8, 5.5, 5.0, 4.8), bs_pct = c(24, 14, 13, 13), ph_h2o = c(4.8, 4.7, 4.8, 4.9), oc_pct = c(2.0, 0.6, 0.3, 0.2) ) ) ## ----classify-three-systems--------------------------------------------------- res_wrb <- classify_wrb2022(meu_pedon, on_missing = "silent") res_sibcs <- classify_sibcs(meu_pedon, include_familia = TRUE) res_usda <- classify_usda(meu_pedon, on_missing = "silent") res_wrb$name res_sibcs$name res_usda$name ## ----classify-all------------------------------------------------------------- todos <- classify_all(meu_pedon, on_missing = "silent") todos$summary ## ----trace-------------------------------------------------------------------- res_wrb$trace ## ----prov--------------------------------------------------------------------- meu_pedon$add_measurement( horizon_idx = 4, attribute = "clay_pct", value = 60, source = "predicted_spectra", confidence = 0.85, notes = "Vis-NIR PLSR-local, OSSL South-America library", overwrite = TRUE ) ## ----cross-system------------------------------------------------------------- todos <- classify_all(meu_pedon, on_missing = "silent") data.frame( Sistema = c("WRB 2022", "SiBCS 5ª ed.", "USDA ST 13"), Nome = c(todos$wrb$name, todos$sibcs$name, todos$usda$name) )