Check if the number of chains is greater than the number of samples per chain

Author: devmotion

src/sample.jl

@@ -197,6 +197,11 @@ function mcmcsample(
         @warn "Only a single thread available: MCMC chains are not sampled in parallel"
     end
 
+    # Check if the number of chains is larger than the number of samples
+    if nchains > N
+        @warn "Number of chains ($nchains) is greater than number of samples per chain ($N)"
+    end
+
     # Copy the random number generator, model, and sample for each thread
     rngs = [deepcopy(rng) for _ in 1:Threads.nthreads()]
     models = [deepcopy(model) for _ in 1:Threads.nthreads()]
@@ -269,6 +274,11 @@ function mcmcsample(
         @warn "Only a single process available: MCMC chains are not sampled in parallel"
     end
 
+    # Check if the number of chains is larger than the number of samples
+    if nchains > N
+        @warn "Number of chains ($nchains) is greater than number of samples per chain ($N)"
+    end
+
     # Create a seed for each chain using the provided random number generator.
     seeds = rand(rng, UInt, nchains)
 

test/runtests.jl

@@ -139,6 +139,11 @@ include("interface.jl")
 
             @test all(((x, y),) -> x.as == y.as && x.bs == y.bs, zip(chains, chains2))
 
+            # Unexpected order of arguments.
+            str = "Number of chains (10) is greater than number of samples per chain (5)"
+            @test_logs (:warn, str) sample(MyModel(), MySampler(), MCMCThreads(), 5, 10;
+                                           chain_type = MyChain)
+
             # Suppress output.
             logs, _ = collect_test_logs(; min_level=Logging.LogLevel(-1)) do
                 sample(MyModel(), MySampler(), MCMCThreads(), 10_000, 1000;
@@ -189,6 +194,11 @@ include("interface.jl")
 
         @test all(((x, y),) -> x.as == y.as && x.bs == y.bs, zip(chains, chains2))
 
+        # Unexpected order of arguments.
+        str = "Number of chains (10) is greater than number of samples per chain (5)"
+        @test_logs (:warn, str) sample(MyModel(), MySampler(), MCMCDistributed(), 5, 10;
+                                       chain_type = MyChain)
+
         # Suppress output.
         logs, _ = collect_test_logs(; min_level=Logging.LogLevel(-1)) do
             sample(MyModel(), MySampler(), MCMCDistributed(), 10_000, 100;