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fixed issue "Error with cvAcc for ENLR" #67 #68

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merged 1 commit into from
Mar 13, 2020
Merged

fixed issue "Error with cvAcc for ENLR" #67 #68

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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "PosDefManifoldML"
uuid = "a07f4532-e2c9-11e9-2ea2-6d98fe4a1f21"
authors = ["Marco-Congedo <marco.congedo@gmail.com>"]
version = "0.3.6"
version = "0.3.7"

[deps]
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
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2 changes: 1 addition & 1 deletion docs/Project.toml
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
authors = ["Marco Congedo, Saloni Jain, Anton Andreev"]
version = "0.3.6"
version = "0.3.7"

[deps]
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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4 changes: 2 additions & 2 deletions src/enlr.jl
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Expand Up @@ -204,7 +204,7 @@ function fit(model :: ENLRmodel,
dfmax :: Int = _getDim(𝐏Tr, vecRange),
pmax :: Int = min(dfmax*2+20, _getDim(𝐏Tr, vecRange)),
nlambda :: Int = 100,
lambda_min_ratio:: Real = (length(yTr) < _getDim(𝐏Tr, vecRange) ? 1e-2 : 1e-4),
lambda_min_ratio:: Real = (length(yTr)*2 < _getDim(𝐏Tr, vecRange) ? 1e-2 : 1e-4),
lambda :: Vector{Float64} = Float64[],
tol :: Real = 1e-5,
maxit :: Int = 1000000,
Expand Down Expand Up @@ -468,7 +468,7 @@ function fit(model :: ENLRmodel,
dfmax :: Int = _getDim(𝐏Tr, vecRange),
pmax :: Int = min(dfmax*2+20, _getDim(𝐏Tr, vecRange)),
nlambda :: Int = 100,
lambda_min_ratio :: Real = (length(yTr) < _getDim(𝐏Tr, vecRange) ? 1e-2 : 1e-4),
lambda_min_ratio :: Real = (length(yTr)*2 < _getDim(𝐏Tr, vecRange) ? 1e-2 : 1e-4),
lambda :: Vector{Float64} = Float64[],
tol :: Real = 1e-5,
maxit :: Int = 1000000,
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8 changes: 4 additions & 4 deletions src/tools.jl
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Expand Up @@ -114,9 +114,9 @@ function tsMap(metric :: Metric,
meanInit :: Union{ℍ, Nothing} = nothing,
tol :: Real = 0.,
transpose :: Bool = true,
vecRange :: UnitRange = 1:size(𝐏[1], 1))
vecRange :: UnitRange = 1:size(𝐏[1], 2))

k, n, getMeanISR = dim(𝐏, 1), dim(𝐏, 2), meanISR==nothing
k, n, getMeanISR = dim(𝐏, 1), dim(𝐏, 2), meanISR===nothing
getMeanISR ? G⁻½ = pow(mean(metric, 𝐏;
w=w,
✓w=✓w,
Expand Down Expand Up @@ -632,13 +632,13 @@ end
# Get the feature matrix for fit functions of ML model in the tangent space:
# if `𝐏Tr` is a matrix just return the columns in `vecRange` (by default all).
# if `𝐏Tr` is vector of Hermitian matrices, they are projected onto the
# tangent space. If the the inversesquare root of a base point `meanISR`
# tangent space. If the inversesquare root of a base point `meanISR`
# is provided, the projection is obtained at this base point, otherwise the
# mean of all points is computed and used as base point.
# If the mean is to be computed by an iterative algorithm (e.g., if the metric
# of the model is the Fisher metric), an initialization `meanInit`, weights
# `w` and a tolerance `tol` are used.
# Once projected onto the tangent spave, the matrces in `𝐏Tr` are vectorized
# Once projected onto the tangent space, the matrices in `𝐏Tr` are vectorized
# using only the rows (or columns) specified by `vecRange`.
# if `verbose` is true, print "Projecting data onto the tangent space..."
# if `transpose` the feature vectors are in the rows of `X`, otherwise in the
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