undo formatting

TuringLang · Oct 21, 2024 · f340df7 · f340df7
1 parent eedb02f
commit f340df7
Showing 1 changed file with 29 additions and 29 deletions.
diff --git a/test/abstractmcmc.jl b/test/abstractmcmc.jl
@@ -8,7 +8,7 @@ using Statistics: mean
  θ_init = randn(rng, 2)
 
  nuts = NUTS(0.8)
- hmc = HMC(100; integrator=Leapfrog(0.05))
+ hmc = HMC(100; integrator = Leapfrog(0.05))
  hmcda = HMCDA(0.8, 0.1)
 
  integrator = Leapfrog(1e-3)
@@ -38,10 +38,10 @@ using Statistics: mean
  model,
  nuts,
  n_adapts + n_samples;
- n_adapts=n_adapts,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ n_adapts = n_adapts,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
 
  # Error if keyword argument `nadapts` is used
@@ -50,10 +50,10 @@ using Statistics: mean
  model,
  nuts,
  n_adapts + n_samples;
- nadapts=n_adapts,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ nadapts = n_adapts,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
  @test_throws ArgumentError AbstractMCMC.sample(
  rng,
@@ -62,10 +62,10 @@ using Statistics: mean
  MCMCThreads(),
  n_adapts + n_samples,
  2;
- nadapts=n_adapts,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ nadapts = n_adapts,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
 
  # Transform back to original space.
@@ -85,10 +85,10 @@ using Statistics: mean
  model,
  hmc,
  n_adapts + n_samples;
- n_adapts=n_adapts,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ n_adapts = n_adapts,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
 
  # Transform back to original space.
@@ -108,10 +108,10 @@ using Statistics: mean
  model,
  custom,
  n_adapts + n_samples;
- n_adapts=0,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ n_adapts = 0,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
 
  # Transform back to original space.
@@ -134,20 +134,20 @@ using Statistics: mean
  model,
  custom,
  10;
- n_adapts=0,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ n_adapts = 0,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
  samples2 = AbstractMCMC.sample(
  rng2,
  model,
  custom,
  10;
- n_adapts=0,
- initial_params=θ_init,
- progress=false,
- verbose=false,
+ n_adapts = 0,
+ initial_params = θ_init,
+ progress = false,
+ verbose = false,
  )
  @test mapreduce(*, samples1, samples2) do s1, s2
  s1.z.θ == s2.z.θ