Use n_adapts instead of nadapts (#375)

* Use `n_adapts` instead of `nadapts`

* Update Project.toml

* Apply suggestions from code review

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: devmotion

Project.toml

@@ -1,6 +1,6 @@
 name = "AdvancedHMC"
 uuid = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
-version = "0.6.1"
+version = "0.6.2"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"

README.md

@@ -128,7 +128,7 @@ samples = AbstractMCMC.sample(
       model,
       sampler,
       n_adapts + n_samples;
-      nadapts = n_adapts,
+      n_adapts = n_adapts,
       initial_params = initial_θ,
   )
 ```

src/abstractmcmc.jl

@@ -47,6 +47,14 @@ function AbstractMCMC.sample(
     callback = nothing,
     kwargs...,
 )
+    if haskey(kwargs, :nadapts)
+        throw(
+            ArgumentError(
+                "keyword argument `nadapts` is unsupported. Please use `n_adapts` to specify the number of adaptation steps.",
+            ),
+        )
+    end
+
     if callback === nothing
         callback = HMCProgressCallback(N, progress = progress, verbose = verbose)
         progress = false # don't use AMCMC's progress-funtionality
@@ -78,6 +86,13 @@ function AbstractMCMC.sample(
     callback = nothing,
     kwargs...,
 )
+    if haskey(kwargs, :nadapts)
+        throw(
+            ArgumentError(
+                "keyword argument `nadapts` is unsupported. Please use `n_adapts` to specify the number of adaptation steps.",
+            ),
+        )
+    end
 
     if callback === nothing
         callback = HMCProgressCallback(N, progress = progress, verbose = verbose)
@@ -144,6 +159,14 @@ function AbstractMCMC.step(
     n_adapts::Int = 0,
     kwargs...,
 )
+    if haskey(kwargs, :nadapts)
+        throw(
+            ArgumentError(
+                "keyword argument `nadapts` is unsupported. Please use `n_adapts` to specify the number of adaptation steps.",
+            ),
+        )
+    end
+
     # Compute transition.
     i = state.i + 1
     t_old = state.transition
@@ -200,7 +223,16 @@ function HMCProgressCallback(n_samples; progress = true, verbose = false)
     HMCProgressCallback(pm, progress, verbose, Ref(0), Ref(0))
 end
 
-function (cb::HMCProgressCallback)(rng, model, spl, t, state, i; nadapts = 0, kwargs...)
+function (cb::HMCProgressCallback)(
+    rng,
+    model,
+    spl,
+    t,
+    state,
+    i;
+    n_adapts::Int = 0,
+    kwargs...,
+)
     progress = cb.progress
     verbose = cb.verbose
     pm = cb.pm
@@ -243,8 +275,8 @@ function (cb::HMCProgressCallback)(rng, model, spl, t, state, i; nadapts = 0, kw
             ),
         )
         # Report finish of adapation
-    elseif verbose && isadapted && i == nadapts
-        @info "Finished $nadapts adapation steps" adaptor κ.τ.integrator metric
+    elseif verbose && isadapted && i == n_adapts
+        @info "Finished $(n_adapts) adapation steps" adaptor κ.τ.integrator metric
     end
 end
 

test/abstractmcmc.jl

@@ -32,6 +32,30 @@ using Statistics: mean
         verbose = false,
     )
 
+    # Error if keyword argument `nadapts` is used
+    @test_throws ArgumentError AbstractMCMC.sample(
+        rng,
+        model,
+        nuts,
+        n_adapts + n_samples;
+        nadapts = n_adapts,
+        initial_params = θ_init,
+        progress = false,
+        verbose = false,
+    )
+    @test_throws ArgumentError AbstractMCMC.sample(
+        rng,
+        model,
+        nuts,
+        MCMCThreads(),
+        n_adapts + n_samples,
+        2;
+        nadapts = n_adapts,
+        initial_params = θ_init,
+        progress = false,
+        verbose = false,
+    )
+
     # Transform back to original space.
     # NOTE: We're not correcting for the `logabsdetjac` here since, but
     # we're only interested in the mean it doesn't matter.

test/mcmcchains.jl

@@ -23,7 +23,7 @@ using Statistics: mean
         model,
         sampler,
         n_adapts + n_samples;
-        nadapts = n_adapts,
+        n_adapts = n_adapts,
         initial_params = θ_init,
         chain_type = Chains,
         progress = false,