resolve review

Author: odunbar

src/Emulator.jl

@@ -479,7 +479,8 @@ Positional Arguments
 Keyword Arguments 
  -  `encoder_schedule`[=`nothing`]: the schedule of data encoding/decoding. This will be passed into the method `create_encoder_schedule` internally. `nothing` sets sets a default schedule `[(decorrelate_sample_cov(), "in_and_out")]`, or `[(decorrelate_sample_cov(), "in"), (decorrelate_structure_mat(), "out")]` if an `encoder_kwargs` has a key `:obs_noise_cov`. Pass `[]` for no encoding.
  - `encoder_kwargs`[=`NamedTuple()`]: a Dict or NamedTuple with keyword arguments to be passed to `initialize_and_encode_with_schedule!`
- - `noise_injector_threshold`[=`0.001`]: A threshold to implementing noise boosting when decoding from an lossily encoded space. If the variance loss due to encoding is `>noise_injector_threshold` then additional noise is added to the null-space (consistent with the prior correlation structure).
+ - `noise_injector_threshold`[=`0.001`]: A threshold to implementing noise injection when decoding from an lossily encoded space. If the variance loss due to encoding is `>noise_injector_threshold` then additional noise is added to the null-space (consistent with the prior correlation structure).
+ - `noise_injector_scaling`[=`1.0`]: a multiplicative scaling that is applied to injected noise samples. (1.0 is "consistent" with Gaussian theory, but may cause instability in Non-Gaussian problems and can be reduced)
 """
 function forward_map_wrapper(
     forward_map::Function,
@@ -488,7 +489,7 @@ function forward_map_wrapper(
     encoder_schedule = nothing,
     encoder_kwargs = NamedTuple(),
     noise_injector_threshold = 0.001,
-    noise_injector_scaling = 0.1,
+    noise_injector_scaling = 1.0,
 ) where {FT <: Real, PD <: ParameterDistribution}
 
     # Default processing: decorrelate_sample_cov() where no structure matrix provided, and decorrelate_structure_mat() where provided.

src/MarkovChainMonteCarlo.jl

@@ -817,7 +817,7 @@ $(DocStringExtensions.TYPEDSIGNATURES)
 Returns a `ParameterDistribution` object corresponding to the empirical distribution of the 
 samples in `chain`.
 
-keywod args
+keyword args
 - `noise_injector_threshold`[`=0.001`]: If the encoded space is lossy, and the lost variability due to encoding exceeds a threshold `noise_injector_threshold`, then in place of decoding posterior samples, additional noise consistent with the prior is injected into the null space of the encoder. See `decode_and_add_noise()` for more detail.  
 - `noise_injector_scaling`[`=1.0`]: Scales the injected noise; though 1.0 is the only "consistent" value, reduction may be necessary if noise injection causes posterior samples to be unstable in simulations.
 

src/Utilities.jl

@@ -867,9 +867,9 @@ struct NoiseInjector{
     L::NorMM
     "Scale the noise (may be needed (<1.0) for robustness if samples will be run in a physical model)"
     scaling::FT
-    "whether to use the encoding or not"
+    "whether to use the noise injection or not"
     use_noise::Bool
-    "the encoding that was used to construct this"
+    "the encoding that was used to construct this object"
     encoder_schedule::VV
 end
 
@@ -934,13 +934,15 @@ function decode_and_add_noise(
         return samples
     end
 
-    K, enc_m, m, L, scaling, use_noise, encoder_schedule = noise_injector.K,
-    noise_injector.enc_m,
-    noise_injector.m,
-    noise_injector.L,
-    noise_injector.scaling,
-    noise_injector.use_noise,
-    noise_injector.encoder_schedule
+    (K, enc_m, m, L, scaling, use_noise, encoder_schedule) = (
+        noise_injector.K,
+        noise_injector.enc_m,
+        noise_injector.m,
+        noise_injector.L,
+        noise_injector.scaling,
+        noise_injector.use_noise,
+        noise_injector.encoder_schedule,
+    )
 
     if use_noise
         recovered_samples = m .+ K * (samples .- enc_m)