typos

Author: bgctw

_typos.toml

@@ -1,2 +1,3 @@
 [default.extend-words]
-SOM = "SOM"
+SOM = "SOM"
+negLogLik = "negLogLik"

dev/doubleMM.jl

@@ -381,7 +381,7 @@ end
     save("ys_density.pdf", fig)
     save("tmp.svg", fig)
 
-    #slighly worse (higher) negLogLik
+    #slightly worse (higher) negLogLikelihood
     df = DataFrame(nL = vcat(nLs, nLsc),
         scenario = vcat(fill.(["unconstrained", "meanθ"], n_sample_pred)...))
     plt = data(df) * mapping(:nL => "-logDensity", color = :scenario => "Scenario") *

src/AbstractHybridProblem.jl

@@ -176,7 +176,7 @@ gdev is applied to xM.
 If :f_on_gpu is in scenario tuple, gdev is also applied to `xP`, `y_o`, and `y_unc`,
 to put the entire data to gpu.
 Alternatively, gdev could be applied to the dataloader, then for each
-iteration the subset of data is separatly transferred to gpu.
+iteration the subset of data is separately transferred to gpu.
 """
 function construct_dataloader_from_synthetic(rng::AbstractRNG, prob::AbstractHybridProblem;
         scenario = (), n_batch, 

src/HybridSolver.jl

@@ -131,7 +131,7 @@ Create a loss function for parameter vector ϕ, given
 - `interpreters`: assigning structure to pure vectors, see `neg_elbo_gtf`
 - `n_MC`: number of Monte-Carlo sample to approximate the expected value across distribution
 - `pbm_covars`: tuple of symbols of process-based parameters provided to the ML model
-- `θP`: CompoenntVector as a template to select indices of pbm_covars
+- `θP`: ComponentVector as a template to select indices of pbm_covars
 
 The loss function takes in addition to ϕ, data that changes with minibatch
 - `rng`: random generator

test/test_elbo.jl

@@ -173,7 +173,7 @@ test_scenario = (scenario) -> begin
         #     # currently only works with identity transformations but not elementwise(exp)
         #     transPM_ident = get_hybridproblem_transforms(prob; scenario = (scenario..., :transIdent))
         #     get_transPMs_ident = (() -> begin
-        #         # wrap in function to not overide get_transPMs
+        #         # wrap in function to not override get_transPMs
         #         (; get_transPMs) = init_hybrid_params(
         #             θP_true, θMs_true[:, 1], cor_ends, ϕg0, n_batch; 
         #             transP = transPM_ident.transP, transM = transPM_ident.transM);