Updates for latest release

01-geodata.qmd

@@ -262,15 +262,6 @@ with specific file formats:
 - `XLSX.Worksheet` from [XLSX.jl](https://github.com/felipenoris/XLSX.jl)
 - Databases from [JuliaDatabases](https://github.com/JuliaDatabases)
 
-As an example, we consider the table representation of a `table.csv` file
-stored on disk:
-
-```{julia}
-using CSV
-
-CSV.File("data/table.csv")
-```
-
 The choice of table representation is a function of the application.
 
 ### Domain

08-splitcombine.qmd

@@ -50,9 +50,9 @@ We will use the `Bonnie` data set to illustrate our geospatial split-apply-combi
 > It is issued under the Creative Commons Attribution-ShareAlike 4.0 International Public License.
 
 ```{julia}
-using CSV
+using GeoIO
 
-gt = georef(CSV.File("data/bonnie.csv"), (:EAST, :NORTH, :RL))
+gt = GeoIO.load("data/bonnie.csv", coords = ("EAST", "NORTH", "RL"))
 ```
 
 It represents a 3D mineral deposit with grades in parts per million (ppm),
@@ -72,20 +72,33 @@ gt |> viewer
 ```
 
 Let's clean the geotable using what we learned in previous chapters.
-We will reject the column with sulfur, will drop missing values, and
-will rename the variables for greater readability:
+We will reject the column with sulfur, will rename the variables for
+greater readability, and will drop missing values. We will also add
+units to some of the variables using bracket notation:
 
 ```{julia}
 clean = Reject("Sper") →
+        Rename("Agppm" => "Ag [ppm]",
+               "Auppm" => "Au [ppm]",
+               "Asppm" => "As [ppm]",
+               "Cuppm" => "Cu [ppm]",
+               "ISBD" => "ρ [Mg/m^3]",
+               "CODE" => "geo",
+               "OX" => "litho") →
         DropMissing() →
-        Rename("Auppm" => "Au", "Agppm" => "Ag",
-               "Cuppm" => "Cu", "Asppm" => "As",
-               "CODE" => "geo", "OX" => "litho",
-               "ISBD" => "ρ")
+        Unitify()
 
 gt = gt |> clean
 ```
 
+::: {.callout-note}
+
+The `Unitify` transform recognizes unit bracket notation in column names.
+It adds the units specified within brackets to the values of the columns,
+and removes the brackets from the column names.
+
+:::
+
 That is a lot better! Let's assume that we want to answer the following
 business question:
 

12-mining.qmd

@@ -15,8 +15,8 @@ In this chapter, we will cover simple steps for resource estimation and
 economic assessment of a real mineral deposit.
 
 **TOOLS COVERED:** `@groupby`, `@transform`, `@combine`, `CLR`, `ProjectionPursuit`,
-`EmpiricalVariogram`, `Kriging`, `Interpolate`, `InterpolateNeighbors`, `Map`, `Filter`,
-`boundingbox`, `convexhull`, `viewer`
+`EmpiricalVariogram`, `Kriging`, `Interpolate`, `InterpolateNeighbors`, `Shadow`,
+`Map`, `Filter`, `boundingbox`, `convexhull`, `viewer`
 
 **MODULES:**
 
@@ -25,7 +25,7 @@ economic assessment of a real mineral deposit.
 using GeoStats
 
 # IO modules
-using CSV
+using GeoIO
 
 # viz modules
 using PairPlots
@@ -60,7 +60,9 @@ of the centroids of the cylinders were stored:
 ```{julia}
 url = "https://zenodo.org/record/7051975/files/drillholes.csv?download=1"
 
-dtable = georef(CSV.File(download(url)), ("X", "Y", "Z"))
+csv = download(url, tempname()*".csv")
+
+dtable = GeoIO.load(csv, coords = ("X", "Y", "Z"))
 
 dtable |> Select("Cu ppm") |> viewer
 ```
@@ -191,15 +193,12 @@ viz!(grid, alpha = 0.2)
 Mke.current_figure()
 ```
 
-Second, let's compute the `convexhull` of points projected on the horizontal plane:
+Second, let's compute the `convexhull` of the `Shadow` of all points on the xy plane:
 
 ```{julia}
-function proj(point)
-  x, y, z = to(point)
-  Point(x, y)
-end
+shadow(point) = point |> Shadow("xy")
 
-points = proj.(dtable.geometry)
+points = shadow.(dtable.geometry)
 
 chull = convexhull(points)
 ```
@@ -214,7 +213,7 @@ We can filter the grid to retain `Hexahedron`s for which the projected centroid
 is inside the `convexhull`:
 
 ```{julia}
-active = findall(h -> proj(centroid(h)) ∈ chull, grid)
+active = findall(h -> shadow(centroid(h)) ∈ chull, grid)
 
 blocks = view(grid, active) 
 ```
@@ -226,15 +225,15 @@ Let's create a simple terrain elevation model by interpolating the vertical
 ```{julia}
 ztable = @chain dtable begin
   @groupby(:HOLEID)
-  @transform(:Z = last(to(:geometry)), :geometry = proj(:geometry))
+  @transform(:Z = last(to(:geometry)), :geometry = shadow(:geometry))
   @combine(:Z = first(:Z), :geometry = first(:geometry))
 end
 ```
 
 We perform the interpolation of the "Z" coordinate on the projected centroids of the blocks:
 
 ```{julia}
-centroids = unique(proj.(centroid.(blocks)))
+centroids = unique(shadow.(centroid.(blocks)))
 
 ztable = ztable |> Select("Z") |> Interpolate(centroids, IDW())
 ```
@@ -246,7 +245,7 @@ ztable |> viewer
 Finally, we can filter the blocks for which the "Z" coordinate is below the terrain:
 
 ```{julia}
-p(h) = proj(centroid(h))
+p(h) = shadow(centroid(h))
 Z(h) = last(to(centroid(h)))
 
 zdict = Dict(ztable.geometry .=> ztable.Z)

Manifest.toml

@@ -1,8 +1,8 @@
 # This file is machine-generated - editing it directly is not advised
 
-julia_version = "1.10.3"
+julia_version = "1.10.4"
 manifest_format = "2.0"
-project_hash = "fd5683c081b6d9795d83d72d8cb6b8bf6e1482e8"
+project_hash = "01ea7963ef90015f9a8a3384bfe71e594e2e87e0"
 
 [[deps.AbstractFFTs]]
 deps = ["LinearAlgebra"]
@@ -877,9 +877,9 @@ version = "0.4.2"
 
 [[deps.GeoIO]]
 deps = ["ArchGDAL", "CSV", "Colors", "CommonDataModel", "FileIO", "Format", "GRIBDatasets", "GeoInterface", "GeoJSON", "GeoParquet", "GeoTables", "GslibIO", "ImageIO", "Meshes", "NCDatasets", "PlyIO", "PrecompileTools", "PrettyTables", "ReadVTK", "Shapefile", "StaticArrays", "Tables", "TransformsBase", "Unitful", "VTKBase", "WriteVTK"]
-git-tree-sha1 = "ff9991c2ab560bd20d967c40fa02fde53ee93a2f"
+git-tree-sha1 = "7a60e047155a8b57e6fe70be769609388aa4372d"
 uuid = "f5a160d5-e41d-4189-8b61-d57781c419e3"
-version = "1.13.3"
+version = "1.13.4"
 
 [[deps.GeoInterface]]
 deps = ["Extents"]
@@ -1151,9 +1151,15 @@ version = "0.3.1"
 
 [[deps.InlineStrings]]
 deps = ["Parsers"]
-git-tree-sha1 = "9cc2baf75c6d09f9da536ddf58eb2f29dedaf461"
+git-tree-sha1 = "86356004f30f8e737eff143d57d41bd580e437aa"
 uuid = "842dd82b-1e85-43dc-bf29-5d0ee9dffc48"
-version = "1.4.0"
+version = "1.4.1"
+
+    [deps.InlineStrings.extensions]
+    ArrowTypesExt = "ArrowTypes"
+
+    [deps.InlineStrings.weakdeps]
+    ArrowTypes = "31f734f8-188a-4ce0-8406-c8a06bd891cd"
 
 [[deps.IntelOpenMP_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
@@ -1652,9 +1658,9 @@ version = "0.1.0"
 
 [[deps.NearestNeighbors]]
 deps = ["Distances", "StaticArrays"]
-git-tree-sha1 = "e4a9d37f0ee694da969def1f0dd4654642dfb51c"
+git-tree-sha1 = "91a67b4d73842da90b526011fa85c5c4c9343fe0"
 uuid = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
-version = "0.4.17"
+version = "0.4.18"
 
 [[deps.NelderMead]]
 git-tree-sha1 = "25abc2f9b1c752e69229f37909461befa7c1f85d"
@@ -2316,9 +2322,9 @@ version = "1.0.1"
 
 [[deps.TableTransforms]]
 deps = ["AbstractTrees", "CategoricalArrays", "CoDa", "ColumnSelectors", "DataScienceTraits", "Distributions", "InverseFunctions", "LinearAlgebra", "NelderMead", "PrettyTables", "Random", "Statistics", "StatsBase", "Tables", "Transducers", "TransformsBase", "Unitful"]
-git-tree-sha1 = "2404c9860c305b86deb818564ef7f4e732837626"
+git-tree-sha1 = "6ad8c3cc51d7390b9fe9e709154a9f995a416c0e"
 uuid = "0d432bfd-3ee1-4ac1-886a-39f05cc69a3e"
-version = "1.31.2"
+version = "1.31.3"
 
 [[deps.Tables]]
 deps = ["DataAPI", "DataValueInterfaces", "IteratorInterfaceExtensions", "LinearAlgebra", "OrderedCollections", "TableTraits"]

Project.toml

@@ -1,5 +1,4 @@
 [deps]
-CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
 Cairo_jll = "83423d85-b0ee-5818-9007-b63ccbeb887a"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

preface.qmd

@@ -118,7 +118,7 @@ pkg"activate @GDSJL"
 pkg"add [email protected]"
 
 # install IO module
-pkg"add [email protected].3"
+pkg"add [email protected].4"
 
 # install artifacts
 pkg"add [email protected]"
@@ -129,7 +129,6 @@ pkg"add [email protected]"
 
 # install other modules
 pkg"add [email protected]"
-pkg"add [email protected]"
 ```
 
 If you need to reproduce the exact same environment with