From d2945b00875e2bf025765a16a1d97537d925e883 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=BAlio=20Hoffimann?= <julio.hoffimann@gmail.com>
Date: Tue, 5 Dec 2023 15:59:53 -0300
Subject: [PATCH] Bump version

---
 Project.toml                    | 6 +++---
 docs/src/variography/fitting.md | 8 ++++----
 ext/variogram.jl                | 2 +-
 3 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/Project.toml b/Project.toml
index e8a29723..f2496d3c 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "GeoStats"
 uuid = "dcc97b0b-8ce5-5539-9008-bb190f959ef6"
 author = "Júlio Hoffimann <julio.hoffimann@gmail.com>"
-version = "0.47.10"
+version = "0.48.0"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -52,7 +52,7 @@ GeoStatsTransforms = "0.2"
 GeoTables = "1.8"
 LossFunctions = "0.11"
 Makie = "0.20"
-Meshes = "0.36"
+Meshes = "0.37"
 Reexport = "1.0"
 Rotations = "1.5"
 Statistics = "1.9"
@@ -60,5 +60,5 @@ StatsLearnModels = "0.2"
 TableTransforms = "1.9"
 Tables = "1.10"
 Unitful = "1.15"
-Variography = "0.19"
+Variography = "0.20"
 julia = "1.9"
diff --git a/docs/src/variography/fitting.md b/docs/src/variography/fitting.md
index 6c63974b..e5f6543e 100644
--- a/docs/src/variography/fitting.md
+++ b/docs/src/variography/fitting.md
@@ -12,7 +12,7 @@ modeling step to ensure valid mathematical models of spatial continuity.
 Given an empirical variogram, the `fit` function can be used to perform the fit:
 
 ```@docs
-fit(::Type{Variogram}, ::EmpiricalVariogram, ::VariogramFitAlgo)
+Variography.fit(::Type{Variogram}, ::EmpiricalVariogram, ::VariogramFitAlgo)
 ```
 
 ## Example
@@ -30,7 +30,7 @@ Mke.plot(g)
 We can fit specific models to the empirical variogram:
 
 ```@example variofit
-γ = fit(SineHoleVariogram, g)
+γ = Variography.fit(SineHoleVariogram, g)
 
 Mke.plot(g)
 Mke.plot!(γ, maxlag = 25.)
@@ -40,7 +40,7 @@ Mke.current_figure()
 or let the framework find the model with minimum error:
 
 ```@example variofit
-γ = fit(Variogram, g)
+γ = Variography.fit(Variogram, g)
 
 Mke.plot(g)
 Mke.plot!(γ, maxlag = 25.)
@@ -53,7 +53,7 @@ of this example is sinusoidal.
 Optionally, we can specify a weighting function to give different weights to the lags:
 
 ```@example variofit
-γ = fit(SineHoleVariogram, g, h -> exp(-h))
+γ = Variography.fit(SineHoleVariogram, g, h -> exp(-h))
 
 Mke.plot(g)
 Mke.plot!(γ, maxlag = 25.)
diff --git a/ext/variogram.jl b/ext/variogram.jl
index d8c6f313..8918e9b7 100644
--- a/ext/variogram.jl
+++ b/ext/variogram.jl
@@ -112,7 +112,7 @@ function Makie.plot!(plot::VarioPlot{<:Tuple{EmpiricalVarioplane}})
 
   # show model range
   if rshow[]
-    ls = Makie.@lift [range(fit($rmodel, γ)) for γ in $γs]
+    ls = Makie.@lift [range(Variography.fit($rmodel, γ)) for γ in $γs]
     ls = Makie.@lift [$ls; $ls]
     zs = Makie.@lift fill(maximum($Z) + 1, length($ls))
     Makie.lines!(plot, θs, ls, zs, color=plot[:rcolor])