v1.0.0

see NEWS

DESCRIPTION

@@ -1,16 +1,19 @@
 Package: dsmartr
 Type: Package
 Title: dsmartr: An R implementation of the DSMART algorithm
-Version: 0.0.0.9013
-Date: 2017-08-24
+Version: 1.0.0
+Date: 2018-01-09
 Authors@R: c(
-    person("Lauren", "O'Brien", email = "obrl_soil@gmail.com",          role = c('aut', 'cre')),
-    person("Nathan", "Odgers",  email = "[email protected]",  role = 'aut'),
-	person("Brendan", "Malone", email = "[email protected]", role = 'aut'))
+    person("Lauren", "O'Brien", email = "obrlsoilau@gmail.com",         role = c('aut', 'cre')),
+    person("Nathan", "Odgers",  email = "[email protected]",  role = 'ctb'),
+	person("Brendan", "Malone", email = "[email protected]", role = 'ctb'))
 Description: This package reinterprets legacy soil mapping by correlating existing map information with higher-density environmental data.
 URL: https://github.com/obrl-soil/dsmartr
 BugReports: https://github.com/obrl-soil/dsmartr/issues
-Depends: R (>= 3.3.0)
+Depends: R (>= 3.3.0),
+    raster,
+    sp,
+    sf
 Imports:
     C50,
     bindrcpp,
@@ -19,12 +22,10 @@ Imports:
     magrittr,
     methods,
     purrr,
-    raster,
     rgdal,
+	rgeos,
     rlang,
-    sf (>= 0.5),
 	snow,
-    sp,
     stats,
     tidyr,
     units,

NAMESPACE

@@ -1,17 +1,18 @@
 # Generated by roxygen2: do not edit by hand
 
-export(dsmartr_check_polygons)
-export(dsmartr_class_maps)
-export(dsmartr_collate)
-export(dsmartr_eval_npred)
-export(dsmartr_eval_nxpred)
-export(dsmartr_eval_pgap)
-export(dsmartr_eval_ties)
-export(dsmartr_iterate)
-export(dsmartr_most_likely)
-export(dsmartr_pred_masks)
-export(dsmartr_prep_points)
-export(dsmartr_prep_polygons)
+export(check_attributes)
+export(class_maps)
+export(collate)
+export(eval_npred)
+export(eval_pgap)
+export(eval_ties)
+export(in_range)
+export(iterate)
+export(most_likely)
+export(prediction_masks)
+export(prep_points)
+export(prep_polygons)
+export(strict_cfp)
 importFrom(C50,C5.0)
 importFrom(dplyr,distinct)
 importFrom(dplyr,filter)
@@ -23,31 +24,42 @@ importFrom(methods,is)
 importFrom(purrr,map)
 importFrom(purrr,map2_lgl)
 importFrom(purrr,map_int)
+importFrom(raster,alignExtent)
 importFrom(raster,beginCluster)
 importFrom(raster,calc)
 importFrom(raster,cellFromPolygon)
 importFrom(raster,cellFromXY)
 importFrom(raster,clusterR)
+importFrom(raster,crop)
 importFrom(raster,crs)
 importFrom(raster,endCluster)
+importFrom(raster,extent)
 importFrom(raster,extract)
 importFrom(raster,getCluster)
 importFrom(raster,inMemory)
+importFrom(raster,intersect)
+importFrom(raster,ncell)
 importFrom(raster,nlayers)
+importFrom(raster,raster)
+importFrom(raster,rasterToPoints)
 importFrom(raster,ratify)
 importFrom(raster,readAll)
 importFrom(raster,stack)
 importFrom(raster,unstack)
 importFrom(raster,writeRaster)
 importFrom(raster,xyFromCell)
+importFrom(rgeos,gIntersection)
+importFrom(rgeos,gIntersects)
+importFrom(rgeos,gUnaryUnion)
 importFrom(sf,st_area)
 importFrom(sf,st_as_sf)
+importFrom(sf,st_geometry)
 importFrom(sf,st_point)
 importFrom(sf,st_set_crs)
 importFrom(sf,st_set_geometry)
 importFrom(sf,st_sfc)
 importFrom(sf,st_transform)
-importFrom(sf,write_sf)
+importFrom(sf,st_write)
 importFrom(sp,spTransform)
 importFrom(stats,complete.cases)
 importFrom(stats,na.omit)

NEWS.md

@@ -1,3 +1,15 @@
+## v.1.0.0 'what I did on my holidays'
+  * Happy New Year, have an API change. Took 'dsmartr_' out of all function names because Twitter Said
+  * Added @importFroms to data.R so sf/sp/raster don't need to be libraried
+  * switched to custom function 'strict_cfp' for returning cell numbers that intersect polygons - better performance, plus old way has some obscure bugs with particular geometries
+  * Covariate samples now write to GPKG as slow write issue has been resolved (see sf issue #470)
+  * all internal functions separated from wrappers, enabling unit testing
+  * Core functions all have unit tests
+  * prediction_masks function corrected
+  * eval_npred and eval_nxpred functions combined
+  * Documentation updated
+  * Regenerated demo data with some tidying up, particularly soil map geometry
+
 ## v.0.0.0.9013
 
   * simplified and debugged `dsmartr_class_maps`

R/data.R

@@ -69,8 +69,8 @@
 #' A dataset containing an extract of 1:100,000 scale soils mapping from the Whitsunday coast area.
 #' The complete dataset can be viewed in the \href{https://qldglobe.information.qld.gov.au/}{Queensland
 #'  Globe.} Data was extracted from the Queensland Soil and Land Information (SALI) database in 2017
-#'  and formatted for dsmartr in R 3.3.
-#'  @format A tbl/sf dataframe of mixed POLYGON/MULTIPOLYGON types in EPSG:3577, with 100 rows
+#'  and formatted for dsmartr in R 3.4.2.
+#' @format An sf data.frame of POLYGON type in EPSG:3577, with 105 rows
 #'    and 10 variables:
 #'  \describe{
 #'  \item{PROJECT_CODE}{Three-letter code identifying the soil survey}
@@ -82,18 +82,19 @@
 #'  \item{PERC_1}{Estimated percentage of the map unit occupied by CLASS_1}
 #'  \item{PERC_2}{Estimated percentage of the map unit occupied by CLASS_2}
 #'  \item{PERC_3}{Estimated percentage of the map unit occupied by CLASS_3}
-#'  \item{geom}{list-column with class 'sfc_GEOMETRY', 'sfc'}}
+#'  \item{geom}{list-column with class 'sfc_POLYGON', 'sfc'}}
 #' @source \itemize{
 #'   \item{\url{https://publications.qld.gov.au/dataset/soils-whitsunday-coast-wcs}}
 #'   \item{\url{https://www.qld.gov.au/environment/land/soil/soil-data/survey-types/}}}
+#' @note This object's geometry has its precision attribute set to one decimal place (approx 10cm on the ground).
 'heronvale_soilmap'
 
 #' Data: Decoded soil class names
 #'
 #' A table of soil class labels found in 'heronvale_soilmap' and 'heronvale_known_sites', along with
 #' their full names. Explanations of the concept associated with each soil name are available in the
 #'  report associated with this mapping project.
-#' @format A tibble with 38 rows and 2 columns:
+#' @format A data.frame with 37 rows and 2 columns:
 #' \describe{
 #'   \item{CLASS}{Soil class label}
 #'   \item{NAME}{Soil class name}}

R/dsmartr.R

@@ -3,12 +3,14 @@
 #' dsmartr is an approach to the DSMART model (Odgers, 2014), which attempts increase the
 #' level of detail in legacy soil maps. Relationships between these maps and various environmental
 #' datasets are used to build a classification tree model. The model is used to map the map
-#' components as a fine-scaled raster. This process is repeated multiple times, with variation introduced around sample location and
-#' soil class proportions to vary the outputs somewhat. The model realisations are then processed
-#' to give a 'most likely' soils map. Refer to the package vignette for more detail.
+#' components as a fine-scaled raster. This process is repeated multiple times, with variation
+#' introduced around sample location and soil class proportions to vary the outputs somewhat. The
+#' model realisations are then processed to give a 'most likely' soils map. Refer to the package
+#' vignette for more detail.
 #'
 #' @references Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., (2014)
 #' \href{http://dx.doi.org/10.1016/j.geoderma.2013.09.024}{Disaggregating and harmonising soil map
 #' units through resampled classification trees}. Geoderma, 214-215: 91-100.
-#'
 "_PACKAGE"
+
+utils::globalVariables(names = c("CELL"), package = 'dsmartr')