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Defaultn_adapts and discard_initial to zero #124

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Defaultn_adapts and discard_initial to zero #124

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2298fb3
Update sample.jl
yebai Jul 29, 2023
8dc2dcf
Update Project.toml
yebai Jul 29, 2023
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2 changes: 1 addition & 1 deletion Project.toml
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Expand Up @@ -3,7 +3,7 @@ uuid = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
keywords = ["markov chain monte carlo", "probablistic programming"]
license = "MIT"
desc = "A lightweight interface for common MCMC methods."
version = "4.4.2"
version = "4.4.3"

[deps]
BangBang = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"
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8 changes: 8 additions & 0 deletions src/sample.jl
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Expand Up @@ -100,6 +100,7 @@ function mcmcsample(
progress=PROGRESS[],
progressname="Sampling",
callback=nothing,
n_adapts=0,
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n_adapts is not a general thing (in contrast to discard_initial), so my feeling is this should not be specified in AbstractMCMC but downstream packages where it is relevant.

discard_initial=0,
thinning=1,
chain_type::Type=Any,
Expand Down Expand Up @@ -209,6 +210,7 @@ function mcmcsample(
progress=PROGRESS[],
progressname="Convergence sampling",
callback=nothing,
n_adapts=0,
discard_initial=0,
thinning=1,
kwargs...,
Expand Down Expand Up @@ -287,6 +289,8 @@ function mcmcsample(
N::Integer,
nchains::Integer;
progress=PROGRESS[],
n_adapts=0,
discard_initial=0,
progressname="Sampling ($(min(nchains, Threads.nthreads())) threads)",
init_params=nothing,
kwargs...,
Expand Down Expand Up @@ -395,6 +399,8 @@ function mcmcsample(
::MCMCDistributed,
N::Integer,
nchains::Integer;
n_adapts=0,
discard_initial=0,
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This should not be needed - the keyword arguments are forwarded to the single-chain version and there a default of 0 is already specified.

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The same is true for the other ensemble algorithms.

progress=PROGRESS[],
progressname="Sampling ($(Distributed.nworkers()) processes)",
init_params=nothing,
Expand Down Expand Up @@ -490,6 +496,8 @@ function mcmcsample(
::MCMCSerial,
N::Integer,
nchains::Integer;
n_adapts=0,
discard_initial=0,
progressname="Sampling",
init_params=nothing,
kwargs...,
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